An improved non-Markovian degradation model with long-term dependency and item-to-item uncertainty

Science.gov (United States)

Xi, Xiaopeng; Chen, Maoyin; Zhang, Hanwen; Zhou, Donghua

2018-05-01

It is widely noted in the literature that the degradation should be simplified into a memoryless Markovian process for the purpose of predicting the remaining useful life (RUL). However, there actually exists the long-term dependency in the degradation processes of some industrial systems, including electromechanical equipments, oil tankers, and large blast furnaces. This implies the new degradation state depends not only on the current state, but also on the historical states. Such dynamic systems cannot be accurately described by traditional Markovian models. Here we present an improved non-Markovian degradation model with both the long-term dependency and the item-to-item uncertainty. As a typical non-stationary process with dependent increments, fractional Brownian motion (FBM) is utilized to simulate the fractal diffusion of practical degradations. The uncertainty among multiple items can be represented by a random variable of the drift. Based on this model, the unknown parameters are estimated through the maximum likelihood (ML) algorithm, while a closed-form solution to the RUL distribution is further derived using a weak convergence theorem. The practicability of the proposed model is fully verified by two real-world examples. The results demonstrate that the proposed method can effectively reduce the prediction error.

Markovian agents models for wireless sensor networks deployed in environmental protection

International Nuclear Information System (INIS)

Cerotti, Davide; Gribaudo, Marco; Bobbio, Andrea

2014-01-01

Wireless sensor networks (WSNs) are gaining popularity as distributed monitoring systems in safety critical applications, when the location to be controlled may be dangerous for a human operator or difficult to access. Fire is one of the major thread in urban as well as in open environments, and WSNs are receiving increasing attention as a mean to build effective and timely fire protection systems. The present paper presents a novel analytical technique for the study of the propagation of a fire in a wide open area and the interaction with a WSN deployed to monitor the outbreak of the fire and to send a warning signal to a base station. For the complex scenario under study, an analytical modeling and analysis technique based on Markovian agents (MAs) is discussed. It is shown that, even if the overall state space of the models is huge, nevertheless an analytical solution is feasible, by exploiting the locality of the interactions among MAs, based on a message passing mechanism combined with a perception function. - Highlights: • We present a revised theory of Markovian agent models, detailing the analysis techniques and its complexity • We a target a complex application of a wireless sensor network (WSN) that monitors forest fire. • The model captures the propagation of fire, heat, and the detection by the WSN. • We compute key performance indices such us the fire propagation front, and message travel time. • We perform an extensive set of experiments to study the effectiveness of the WSN in detecting forest fire

Markovian approach: From Ising model to stochastic radiative transfer

International Nuclear Information System (INIS)

Kassianov, E.; Veron, D.

2009-01-01

The origin of the Markovian approach can be traced back to 1906; however, it gained explicit recognition in the last few decades. This overview outlines some important applications of the Markovian approach, which illustrate its immense prestige, respect, and success. These applications include examples in the statistical physics, astronomy, mathematics, computational science and the stochastic transport problem. In particular, the overview highlights important contributions made by Pomraning and Titov to the neutron and radiation transport theory in a stochastic medium with homogeneous statistics. Using simple probabilistic assumptions (Markovian approximation), they have introduced a simplified, but quite realistic, representation of the neutron/radiation transfer through a two-component discrete stochastic mixture. New concepts and methodologies introduced by these two distinguished scientists allow us to generalize the Markovian treatment to the stochastic medium with inhomogeneous statistics and demonstrate its improved predictive performance for the down-welling shortwave fluxes. (authors)

Non-Markovianity Measure Based on Brukner-Zeilinger Invariant Information for Unital Quantum Dynamical Maps

Science.gov (United States)

He, Zhi; Zhu, Lie-Qiang; Li, Li

2017-03-01

A non-Markovianity measure based on Brukner-Zeilinger invariant information to characterize non-Markovian effect of open systems undergoing unital dynamical maps is proposed. The method takes advantage of non-increasing property of the Brukner-Zeilinger invariant information under completely positive and trace-preserving unital maps. The simplicity of computing the Brukner-Zeilinger invariant information is the advantage of the proposed measure because of mainly depending on the purity of quantum state. The measure effectively captures the characteristics of non-Markovianity of unital dynamical maps. As some concrete application, we consider two typical non-Markovian noise channels, i.e., the phase damping channel and the random unitary channel to show the sensitivity of the proposed measure. By investigation, we find that the conditions of detecting the non-Markovianity for the phase damping channel are consistent with the results of existing measures for non-Markovianity, i.e., information flow, divisibility and quantum mutual information. However, for the random unitary channel non-Markovian conditions are same to that of the information flow, but is different from that of the divisibility and quantum mutual information. Supported by the National Natural Science Foundation of China under Grant No. 61505053, the Natural Science Foundation of Hunan Province under Grant No. 2015JJ3092, the Research Foundation of Education Bureau of Hunan Province, China under Grant No. 16B177, the School Foundation from the Hunan University of Arts and Science under Grant No. 14ZD01

An application of superpositions of two-state Markovian sources to the modelling of self-similar behaviour

DEFF Research Database (Denmark)

Andersen, Allan T.; Nielsen, Bo Friis

1997-01-01

We present a modelling framework and a fitting method for modelling second order self-similar behaviour with the Markovian arrival process (MAP). The fitting method is based on fitting to the autocorrelation function of counts a second order self-similar process. It is shown that with this fittin...

Adaptive resummation of Markovian quantum dynamics

International Nuclear Information System (INIS)

Lucas, Felix

2014-01-01

In this thesis we derive a highly convergent, nonperturbative expansion of Markovian open quantum dynamics. It is based on a splitting of the incoherent dynamics into periods of continuous evolution and abrupt jumps and attains its favorable convergence properties from an adaptive resummation of this so-called jump expansion. By means of the long-standing problems of spatial particle detection and Landau-Zener tunneling in the presence of dephasing, we show that this adaptive resummation technique facilitates new highly accurate analytic approximations of Markovian open systems. The open Landau-Zener model leads us to propose an efficient and robust incoherent control technique for the isomerization reaction of the visual pigment protein rhodopsin. Besides leading to approximate analytic descriptions of Markovian open quantum dynamics, the adaptive resummation of the jump expansion implies an efficient numerical simulation method. We spell out the corresponding numerical algorithm by means of Monte Carlo integration of the relevant terms in the jump expansion and demonstrate it in a set of paradigmatic open quantum systems.

Delineating incoherent non-Markovian dynamics using quantum coherence

Energy Technology Data Exchange (ETDEWEB)

Chanda, Titas, E-mail: titaschanda@hri.res.in; Bhattacharya, Samyadeb, E-mail: samyadebbhattacharya@hri.res.in

2016-03-15

We introduce a method of characterization of non-Markovianity using coherence of a system interacting with the environment. We show that under the allowed incoherent operations, monotonicity of a valid coherence measure is affected due to non-Markovian features of the system–environment evolution. We also define a measure to quantify non-Markovianity of the underlying dynamics based on the non-monotonic behavior of the coherence measure. We investigate our proposed non-Markovianity marker in the behavior of dephasing and dissipative dynamics for one and two qubit cases. We also show that our proposed measure captures the back-flow of information from the environment to the system and compatible with well known distinguishability criteria of non-Markovianity.

Noise suppression via generalized-Markovian processes

Science.gov (United States)

Marshall, Jeffrey; Campos Venuti, Lorenzo; Zanardi, Paolo

2017-11-01

It is by now well established that noise itself can be useful for performing quantum information processing tasks. We present results which show how one can effectively reduce the error rate associated with a noisy quantum channel by counteracting its detrimental effects with another form of noise. In particular, we consider the effect of adding on top of a purely Markovian (Lindblad) dynamics, a more general form of dissipation, which we refer to as generalized-Markovian noise. This noise has an associated memory kernel and the resulting dynamics are described by an integrodifferential equation. The overall dynamics are characterized by decay rates which depend not only on the original dissipative time scales but also on the new integral kernel. We find that one can engineer this kernel such that the overall rate of decay is lowered by the addition of this noise term. We illustrate this technique for the case where the bare noise is described by a dephasing Pauli channel. We analytically solve this model and show that one can effectively double (or even triple) the length of the channel, while achieving the same fidelity, entanglement, and error threshold. We numerically verify this scheme can also be used to protect against thermal Markovian noise (at nonzero temperature), which models spontaneous emission and excitation processes. A physical interpretation of this scheme is discussed, whereby the added generalized-Markovian noise causes the system to become periodically decoupled from the background Markovian noise.

Mixed H2/H∞ Pitch Control of Wind Turbine with a Markovian Jump Model

DEFF Research Database (Denmark)

Lin, Zhongwei; Liu, Jizhen; Wu, Qiuwei

2016-01-01

This paper proposes a Markovian jump model and the corresponding H2 /H∞ control strategy for the wind turbine driven by the stochastic switching wind speed, which can be used to regulate the generator speed in order to harvest the rated power while reducing the fatigue loads on the mechanical side...... operating points of wind turbine can be divided into separate subregions correspondingly, where the model parameters and the control mode can be fixed in each mode. Then, the mixed H2 /H∞ control problem is discussed for such a class of Markovian jump wind turbine working above the rated wind speed...

Quantum measurements in spin-boson model under non-Markovian environment

Science.gov (United States)

Berrada, K.; Aldaghri, O.

2017-07-01

We propose a control approach of the parameter estimation for a two-level quantum system interacting with a bosonic reservoir considering non-Markovian open, dissipative quantum system. We show that the precision of the estimation significantly affected and behaves differently within the framework of the markovian and non-Markovian regimes. The influence of memory effects for an Ohmic reservoir with Lorentz-Drude regularization on the estimation-parameter precision are numerically demonstrated under the following three conditions: ω0 ≪ωc , ω0 ≈ωc or ω0 ≫ωc , where ω0 is the characteristic frequency of the two-level system, and ωc is the cut-off frequency of Ohmic reservoir. We investigate the precision rate in high temperature, intermediate temperature, and low temperature reservoirs for various values of the ratio r =ωc /ω0 considering manifold external fields. We reveal that the enhancement and preservation of the measurement precision, highly depend on the combination of the external control field, reservoir parameters, and non-Markovian effects.

Pseudothermalization in driven-dissipative non-Markovian open quantum systems

Science.gov (United States)

Lebreuilly, José; Chiocchetta, Alessio; Carusotto, Iacopo

2018-03-01

We investigate a pseudothermalization effect, where an open quantum system coupled to a nonequilibrated environment consisting of several non-Markovian reservoirs presents an emergent thermal behavior. This thermal behavior is visible at both static and dynamical levels and the system satisfies the fluctuation-dissipation theorem. Our analysis is focused on the exactly solvable model of a weakly interacting driven-dissipative Bose gas in presence of frequency-dependent particle pumping and losses, and is based on a quantum Langevin theory, which we derive starting from a microscopical quantum optics model. For generic non-Markovian reservoirs, we demonstrate that the emergence of thermal properties occurs in the range of frequencies corresponding to low-energy excitations. For the specific case of non-Markovian baths verifying the Kennard-Stepanov relation, we show that pseudothermalization can instead occur at all energy scales. The possible implications regarding the interpretation of thermal laws in low-temperature exciton-polariton experiments are discussed. We finally show that the presence of either a saturable pumping or a dispersive environment leads to a breakdown of the pseudothermalization effect.

Optimal management of non-Markovian biological populations

Science.gov (United States)

Williams, B.K.

2007-01-01

Wildlife populations typically are described by Markovian models, with population dynamics influenced at each point in time by current but not previous population levels. Considerable work has been done on identifying optimal management strategies under the Markovian assumption. In this paper we generalize this work to non-Markovian systems, for which population responses to management are influenced by lagged as well as current status and/or controls. We use the maximum principle of optimal control theory to derive conditions for the optimal management such a system, and illustrate the effects of lags on the structure of optimal habitat strategies for a predator-prey system.

Nonlocal non-Markovian effects in dephasing environments

International Nuclear Information System (INIS)

Xie Dong; Wang An-Min

2014-01-01

We study the nonlocal non-Markovian effects through local interactions between two subsystems and the corresponding two environments. It has been found that the initial correlations between two environments can turn a Markovian to a non-Markovian regime with extra control on the local interaction time. We further research the nonlocal non-Markovian effects from two situations: without extra control, the nonlocal non-Markovian effects only appear under the condition that two local dynamics are non-Markovian–non-Markovian (both of the two local dynamics are non-Markovian) or Markovian–non-Markovian, but not under the condition of Markovian–Markovian; with extra control, the nonlocal non-Markovian effects can occur under the condition of Markovian–Markovian. It shows that the function of correlations between two environments has an upper bound, which makes a flow of information from the environment back to the global system beginning finitely earlier than that back to one of the two local systems, not infinitely. Then, we proposed two special ways to distribute classical correlations between two environments without initial correlations. Finally, from numerical solutions in the spin star configuration, we found that the self-correlation (internal correlation) of each environment promotes the nonlocal non-Markovian effects. (general)

Foundations and measures of quantum non-Markovianity

International Nuclear Information System (INIS)

Breuer, Heinz-Peter

2012-01-01

The basic features of the dynamics of open quantum systems, such as the dissipation of energy, the decay of coherences, the relaxation to an equilibrium or non-equilibrium stationary state, and the transport of excitations in complex structures are of central importance in many applications of quantum mechanics. The theoretical description, analysis and control of non-Markovian quantum processes play an important role in this context. While in a Markovian process an open system irretrievably loses information to its surroundings, non-Markovian processes feature a flow of information from the environment back to the open system, which implies the presence of memory effects and represents the key property of non-Markovian quantum behaviour. Here, we review recent ideas developing a general mathematical definition for non-Markovianity in the quantum regime and a measure for the degree of memory effects in the dynamics of open systems, which are based on the exchange of information between system and environment. We further study the dynamical effects induced by the presence of system–environment correlations in the total initial state and design suitable methods to detect such correlations through local measurements on the open system. (topical review)

Quantum non-Markovianity: characterization, quantification and detection

International Nuclear Information System (INIS)

Rivas, Ángel; Huelga, Susana F; Plenio, Martin B

2014-01-01

We present a comprehensive and up-to-date review of the concept of quantum non-Markovianity, a central theme in the theory of open quantum systems. We introduce the concept of a quantum Markovian process as a generalization of the classical definition of Markovianity via the so-called divisibility property and relate this notion to the intuitive idea that links non-Markovianity with the persistence of memory effects. A detailed comparison with other definitions presented in the literature is provided. We then discuss several existing proposals to quantify the degree of non-Markovianity of quantum dynamics and to witness non-Markovian behavior, the latter providing sufficient conditions to detect deviations from strict Markovianity. Finally, we conclude by enumerating some timely open problems in the field and provide an outlook on possible research directions. (review article)

Quantum non-Markovianity: characterization, quantification and detection

Science.gov (United States)

Rivas, Ángel; Huelga, Susana F.; Plenio, Martin B.

2014-09-01

We present a comprehensive and up-to-date review of the concept of quantum non-Markovianity, a central theme in the theory of open quantum systems. We introduce the concept of a quantum Markovian process as a generalization of the classical definition of Markovianity via the so-called divisibility property and relate this notion to the intuitive idea that links non-Markovianity with the persistence of memory effects. A detailed comparison with other definitions presented in the literature is provided. We then discuss several existing proposals to quantify the degree of non-Markovianity of quantum dynamics and to witness non-Markovian behavior, the latter providing sufficient conditions to detect deviations from strict Markovianity. Finally, we conclude by enumerating some timely open problems in the field and provide an outlook on possible research directions.

Mean first-passage times in confined media: from Markovian to non-Markovian processes

International Nuclear Information System (INIS)

Bénichou, O; Voituriez, R; Guérin, T

2015-01-01

We review recent theoretical works that enable the accurate evaluation of the mean first passage time (MFPT) of a random walker to a target in confinement for Markovian (memory-less) and non-Markovian walkers. For the Markovian problem, we present a general theory which allows one to accurately evaluate the MFPT and its extensions to related first-passage observables such as splitting probabilities and occupation times. We show that this analytical approach provides a universal scaling dependence of the MFPT on both the volume of the confining domain and the source–target distance in the case of general scale-invariant processes. This analysis is applicable to a broad range of stochastic processes characterized by length scale-invariant properties, and reveals the key role that can be played by the starting position of the random walker. We then present an extension to non-Markovian walks by taking the specific example of a tagged monomer of a polymer chain looking for a target in confinement. We show that the MFPT can be calculated accurately by computing the distribution of the positions of all the monomers in the chain at the instant of reaction. Such a theory can be used to derive asymptotic relations that generalize the scaling dependence with the volume and the initial distance to the target derived for Markovian walks. Finally, we present an application of this theory to the problem of the first contact time between the two ends of a polymer chain, and review the various theoretical approaches of this non- Markovian problem. (topical review)

Non-Markovian features of deeply inelastic collisions

International Nuclear Information System (INIS)

Pal, D.; Chattopadhyay, S.; Kar, K.

1988-01-01

To study the effect of memory in the diffusion processes (of charge, mass etc) observed in deeply inelastic heavy-ion reactions, we derive non-Markovian transport equations for the exponential and Gaussian memory kernels. The centroid and the variance of the distribution are expressed in terms of the memory time, drift and diffusion coefficients. The predictions based on this theory show better agreement with the experimental data than the Markovian results. (author)

Non-Markovian linear response theory for quantum open systems and its applications.

Science.gov (United States)

Shen, H Z; Li, D X; Yi, X X

2017-01-01

The Kubo formula is an equation that expresses the linear response of an observable due to a time-dependent perturbation. It has been extended from closed systems to open systems in recent years under the Markovian approximation, but is barely explored for open systems in non-Markovian regimes. In this paper, we derive a formula for the linear response of an open system to a time-independent external field. This response formula is available for both Markovian and non-Markovian dynamics depending on parameters in the spectral density of the environment. As an illustration of the theory, the Hall conductance of a two-band system subjected to environments is derived and discussed. With the tight-binding model, we point out the Hall conductance changes from Markovian to non-Markovian dynamics by modulating the spectral density of the environment. Our results suggest a way to the controlling of the system response, which has potential applications for quantum statistical mechanics and condensed matter physics.

A Dynamical Theory of Markovian Diffusion

OpenAIRE

Davidson, Mark

2001-01-01

A dynamical treatment of Markovian diffusion is presented and several applications discussed. The stochastic interpretation of quantum mechanics is considered within this framework. A model for Brownian movement which includes second order quantum effects is derived.

Superdiffusion in a non-Markovian random walk model with a Gaussian memory profile

Science.gov (United States)

Borges, G. M.; Ferreira, A. S.; da Silva, M. A. A.; Cressoni, J. C.; Viswanathan, G. M.; Mariz, A. M.

2012-09-01

Most superdiffusive Non-Markovian random walk models assume that correlations are maintained at all time scales, e.g., fractional Brownian motion, Lévy walks, the Elephant walk and Alzheimer walk models. In the latter two models the random walker can always "remember" the initial times near t = 0. Assuming jump size distributions with finite variance, the question naturally arises: is superdiffusion possible if the walker is unable to recall the initial times? We give a conclusive answer to this general question, by studying a non-Markovian model in which the walker's memory of the past is weighted by a Gaussian centered at time t/2, at which time the walker had one half the present age, and with a standard deviation σt which grows linearly as the walker ages. For large widths we find that the model behaves similarly to the Elephant model, but for small widths this Gaussian memory profile model behaves like the Alzheimer walk model. We also report that the phenomenon of amnestically induced persistence, known to occur in the Alzheimer walk model, arises in the Gaussian memory profile model. We conclude that memory of the initial times is not a necessary condition for generating (log-periodic) superdiffusion. We show that the phenomenon of amnestically induced persistence extends to the case of a Gaussian memory profile.

Shot-noise at a Fermi-edge singularity: Non-Markovian dynamics

Energy Technology Data Exchange (ETDEWEB)

Ubbelohde, N.; Maire, N.; Haug, R. J. [Institut für Festkörperphysik, Leibniz Universität Hannover, Appelstraße 2, D-30167 Hannover (Germany); Roszak, K. [Institute of Physics, Wrocław University of Technology, PL-50370 Wrocław (Poland); Hohls, F. [Physikalisch-Technische Bundesanstalt, D-38116 Braunschweig (Germany); Novotný, T. [Department of Condensed Matter Physics, Faculty of Mathematics and Physics, Charles University, CZ-12116 Prague (Czech Republic)

2013-12-04

For an InAs quantum dot we study the current shot noise at a Fermi-edge singularity in low temperature cross-correlation measurements. In the regime of the interaction effect the strong suppression of noise observed at zero magnetic field and the sequence of enhancement and suppression in magnetic field go beyond a Markovian master equation model. Qualitative and quantitative agreement can however be achieved by a generalized master equation model taking non-Markovian dynamics into account.

Some performance measures for vacation models with a batch Markovian arrival process

Directory of Open Access Journals (Sweden)

Sadrac K. Matendo

1994-01-01

Full Text Available We consider a single server infinite capacity queueing system, where the arrival process is a batch Markovian arrival process (BMAP. Particular BMAPs are the batch Poisson arrival process, the Markovian arrival process (MAP, many batch arrival processes with correlated interarrival times and batch sizes, and superpositions of these processes. We note that the MAP includes phase-type (PH renewal processes and non-renewal processes such as the Markov modulated Poisson process (MMPP.

Bulk-mediated surface diffusion: non-Markovian desorption dynamics

International Nuclear Information System (INIS)

Revelli, Jorge A; Budde, Carlos E; Prato, Domingo; Wio, Horacio S

2005-01-01

Here we analyse the dynamics of adsorbed molecules within the bulk-mediated surface diffusion framework, when the particle's desorption mechanism is characterized by a non-Markovian process, while the particle's adsorption as well as its motion in the bulk is governed by Markovian dynamics. We study the diffusion of particles in both semi-infinite and finite cubic lattices, analysing the conditional probability to find the system on the reference absorptive plane as well as the surface dispersion as functions of time. The results are compared with known Markovian cases showing the differences that can be exploited to distinguish between Markovian and non-Markovian desorption mechanisms in experimental situations

Thermodynamic description of non-Markovian information flux of nonequilibrium open quantum systems

Science.gov (United States)

Chen, Hong-Bin; Chen, Guang-Yin; Chen, Yueh-Nan

2017-12-01

One of the fundamental issues in the field of open quantum systems is the classification and quantification of non-Markovianity. In the contest of quantity-based measures of non-Markovianity, the intuition of non-Markovianity in terms of information backflow is widely discussed. However, it is not easy to characterize the information flux for a given system state and show its connection to non-Markovianity. Here, by using the concepts from thermodynamics and information theory, we discuss a potential definition of information flux of an open quantum system, valid for static environments. We present a simple protocol to show how a system attempts to share information with its environment and how it builds up system-environment correlations. We also show that the information returned from the correlations characterizes the non-Markovianity and a hierarchy of indivisibility of the system dynamics.

Exact solution for a non-Markovian dissipative quantum dynamics.

Science.gov (United States)

Ferialdi, Luca; Bassi, Angelo

2012-04-27

We provide the exact analytic solution of the stochastic Schrödinger equation describing a harmonic oscillator interacting with a non-Markovian and dissipative environment. This result represents an arrival point in the study of non-Markovian dynamics via stochastic differential equations. It is also one of the few exactly solvable models for infinite-dimensional systems. We compute the Green's function; in the case of a free particle and with an exponentially correlated noise, we discuss the evolution of Gaussian wave functions.

Mixing-induced quantum non-Markovianity and information flow

Science.gov (United States)

Breuer, Heinz-Peter; Amato, Giulio; Vacchini, Bassano

2018-04-01

Mixing dynamical maps describing open quantum systems can lead from Markovian to non-Markovian processes. Being surprising and counter-intuitive, this result has been used as argument against characterization of non-Markovianity in terms of information exchange. Here, we demonstrate that, quite the contrary, mixing can be understood in a natural way which is fully consistent with existing theories of memory effects. In particular, we show how mixing-induced non-Markovianity can be interpreted in terms of the distinguishability of quantum states, system-environment correlations and the information flow between system and environment.

Quench of non-Markovian coherence in the deep sub-Ohmic spin–boson model: A unitary equilibration scheme

International Nuclear Information System (INIS)

Yao, Yao

2015-01-01

The deep sub-Ohmic spin–boson model shows a longstanding non-Markovian coherence at low temperature. Motivating to quench this robust coherence, the thermal effect is unitarily incorporated into the time evolution of the model, which is calculated by the adaptive time-dependent density matrix renormalization group algorithm combined with the orthogonal polynomials theory. Via introducing a unitary heating operator to the bosonic bath, the bath is heated up so that a majority portion of the bosonic excited states is occupied. It is found in this situation the coherence of the spin is quickly quenched even in the coherent regime, in which the non-Markovian feature dominates. With this finding we come up with a novel way to implement the unitary equilibration, the essential term of the eigenstate-thermalization hypothesis, through a short-time evolution of the model

Non-Markovian nuclear dynamics

International Nuclear Information System (INIS)

Kolomietz, V.M.

2011-01-01

A prove of equations of motion for the nuclear shape variables which establish a direct connection of the memory effects with the dynamic distortion of the Fermi surface is suggested. The equations of motion for the nuclear Fermi liquid drop are derived from the collisional kinetic equation. In general, the corresponding equations are non-Markovian. The memory effects appear due to the Fermi surface distortions and depend on the relaxation time. The main purpose of the present work is to apply the non-Markovian dynamics to the description of the nuclear giant multipole resonances (GMR) and the large amplitude motion. We take also into consideration the random forces and concentrate on the formation of both the conservative and the friction forces to make more clear the memory effect on the nuclear dynamics. In this respect, the given approach represents an extension of the traditional liquid drop model (LDM) to the case of the nuclear Fermi liquid drop. In practical application, we pay close attention to the description of the descent of the nucleus from the fission barrier to the scission point.

Continuous quantum error correction for non-Markovian decoherence

International Nuclear Information System (INIS)

Oreshkov, Ognyan; Brun, Todd A.

2007-01-01

We study the effect of continuous quantum error correction in the case where each qubit in a codeword is subject to a general Hamiltonian interaction with an independent bath. We first consider the scheme in the case of a trivial single-qubit code, which provides useful insights into the workings of continuous error correction and the difference between Markovian and non-Markovian decoherence. We then study the model of a bit-flip code with each qubit coupled to an independent bath qubit and subject to continuous correction, and find its solution. We show that for sufficiently large error-correction rates, the encoded state approximately follows an evolution of the type of a single decohering qubit, but with an effectively decreased coupling constant. The factor by which the coupling constant is decreased scales quadratically with the error-correction rate. This is compared to the case of Markovian noise, where the decoherence rate is effectively decreased by a factor which scales only linearly with the rate of error correction. The quadratic enhancement depends on the existence of a Zeno regime in the Hamiltonian evolution which is absent in purely Markovian dynamics. We analyze the range of validity of this result and identify two relevant time scales. Finally, we extend the result to more general codes and argue that the performance of continuous error correction will exhibit the same qualitative characteristics

Computing the non-Markovian coarse-grained interactions derived from the Mori-Zwanzig formalism in molecular systems: Application to polymer melts

Science.gov (United States)

Li, Zhen; Lee, Hee Sun; Darve, Eric; Karniadakis, George Em

2017-01-01

Memory effects are often introduced during coarse-graining of a complex dynamical system. In particular, a generalized Langevin equation (GLE) for the coarse-grained (CG) system arises in the context of Mori-Zwanzig formalism. Upon a pairwise decomposition, GLE can be reformulated into its pairwise version, i.e., non-Markovian dissipative particle dynamics (DPD). GLE models the dynamics of a single coarse particle, while DPD considers the dynamics of many interacting CG particles, with both CG systems governed by non-Markovian interactions. We compare two different methods for the practical implementation of the non-Markovian interactions in GLE and DPD systems. More specifically, a direct evaluation of the non-Markovian (NM) terms is performed in LE-NM and DPD-NM models, which requires the storage of historical information that significantly increases computational complexity. Alternatively, we use a few auxiliary variables in LE-AUX and DPD-AUX models to replace the non-Markovian dynamics with a Markovian dynamics in a higher dimensional space, leading to a much reduced memory footprint and computational cost. In our numerical benchmarks, the GLE and non-Markovian DPD models are constructed from molecular dynamics (MD) simulations of star-polymer melts. Results show that a Markovian dynamics with auxiliary variables successfully generates equivalent non-Markovian dynamics consistent with the reference MD system, while maintaining a tractable computational cost. Also, transient subdiffusion of the star-polymers observed in the MD system can be reproduced by the coarse-grained models. The non-interacting particle models, LE-NM/AUX, are computationally much cheaper than the interacting particle models, DPD-NM/AUX. However, the pairwise models with momentum conservation are more appropriate for correctly reproducing the long-time hydrodynamics characterised by an algebraic decay in the velocity autocorrelation function.

Basic mechanisms in the laser control of non-Markovian dynamics

Science.gov (United States)

Puthumpally-Joseph, R.; Mangaud, E.; Chevet, V.; Desouter-Lecomte, M.; Sugny, D.; Atabek, O.

2018-03-01

Referring to a Fano-type model qualitative analogy we develop a comprehensive basic mechanism for the laser control of the non-Markovian bath response and fully implement it in a realistic control scheme, in strongly coupled open quantum systems. Converged hierarchical equations of motion are worked out to numerically solve the master equation of a spin-boson Hamiltonian to reach the reduced electronic density matrix of a heterojunction in the presence of strong terahertz laser pulses. Robust and efficient control is achieved increasing by a factor of 2 the non-Markovianity measured by the time evolution of the volume of accessible states. The consequences of such fields on the central system populations and coherence are examined, putting the emphasis on the relation between the increase of non-Markovianity and the slowing down of decoherence processes.

Monte Carlo simulation of fully Markovian stochastic geometries

International Nuclear Information System (INIS)

Lepage, Thibaut; Delaby, Lucie; Malvagi, Fausto; Mazzolo, Alain

2010-01-01

The interest in resolving the equation of transport in stochastic media has continued to increase these last years. For binary stochastic media it is often assumed that the geometry is Markovian, which is never the case in usual environments. In the present paper, based on rigorous mathematical theorems, we construct fully two-dimensional Markovian stochastic geometries and we study their main properties. In particular, we determine a percolation threshold p c , equal to 0.586 ± 0.0015 for such geometries. Finally, Monte Carlo simulations are performed through these geometries and the results compared to homogeneous geometries. (author)

On the application of semi-Markovian processes to the unavailability analysis of majority voting protective systems

International Nuclear Information System (INIS)

Frutuoso e Melo, Paulo Fernando Ferreira

1992-01-01

In this work the application of semi-Markovian processes to the unavailability analysis of majority voting protective systems is discussed aiming at: modeling two problems that, possess practical relevance: explicit consideration of test intervals and possibility of including nonexponential repair times. Initially, protective systems up to 5 channels are modeled considering intervals between tests by means of a Markovian model in or.der to take into account the possibility of high demand rates. This model is a new extension of previous ones already published in the literature. The above mentioned Markovian model allows for considering either that the failure of a single channel is re by a real system demand or, alternatively, the failure is revealed only when k channels are found failed. Practical implications of this policies are important as they allow for different system actuation policies to be discussed and evaluated. A computer co de named RAMPSMM has been written in order to perform the aforementioned analysis. Results for different system configurations are shown and compared to published results concerning one and two channels. Those results agree adequately and the effect of higher demand rates on the systems is acknowledged. Next, a new semi-Markovian model for the the intervals between tests is discussed. The reason for employing it is that it describes a time interval that is constant, so that its describing process is not Markovian anymore. The model takes into account the influence of different parameters and repair policies as, for example, demand rate (considering the possibility of test overrides), staggered and sequential test policies and so on. l' Another consideration is made concerning the possibility of nonexponential ,- repair times. These kind of repair times are modeled by means of negative binomial distributions which correspond to discretized gamma densities assumed for the repair times. A second computer code named RAMPSSM has been

SIMULTANEOUS MULTI-BAND DETECTION OF LOW SURFACE BRIGHTNESS GALAXIES WITH MARKOVIAN MODELING

International Nuclear Information System (INIS)

Vollmer, B.; Bonnarel, F.; Louys, M.; Perret, B.; Petremand, M.; Lavigne, F.; Collet, Ch.; Van Driel, W.; Sabatini, S.; MacArthur, L. A.

2013-01-01

We present to the astronomical community an algorithm for the detection of low surface brightness (LSB) galaxies in images, called MARSIAA (MARkovian Software for Image Analysis in Astronomy), which is based on multi-scale Markovian modeling. MARSIAA can be applied simultaneously to different bands. It segments an image into a user-defined number of classes, according to their surface brightness and surroundings—typically, one or two classes contain the LSB structures. We have developed an algorithm, called DetectLSB, which allows the efficient identification of LSB galaxies from among the candidate sources selected by MARSIAA. The application of the method to two and three bands simultaneously was tested on simulated images. Based on our tests, we are confident that we can detect LSB galaxies down to a central surface brightness level of only 1.5 times the standard deviation from the mean pixel value in the image background. To assess the robustness of our method, the method was applied to a set of 18 B- and I-band images (covering 1.3 deg 2 in total) of the Virgo Cluster to which Sabatini et al. previously applied a matched-filter dwarf LSB galaxy search algorithm. We have detected all 20 objects from the Sabatini et al. catalog which we could classify by eye as bona fide LSB galaxies. Our method has also detected four additional Virgo Cluster LSB galaxy candidates undetected by Sabatini et al. To further assess the completeness of the results of our method, both MARSIAA, SExtractor, and DetectLSB were applied to search for (1) mock Virgo LSB galaxies inserted into a set of deep Next Generation Virgo Survey (NGVS) gri-band subimages and (2) Virgo LSB galaxies identified by eye in a full set of NGVS square degree gri images. MARSIAA/DetectLSB recovered ∼20% more mock LSB galaxies and ∼40% more LSB galaxies identified by eye than SExtractor/DetectLSB. With a 90% fraction of false positives from an entirely unsupervised pipeline, a completeness of 90% is

A classical appraisal of quantum definitions of non-Markovian dynamics

International Nuclear Information System (INIS)

Vacchini, Bassano

2012-01-01

We consider the issue of non-Markovianity of a quantum dynamics starting from a comparison with the classical definition of Markovian processes. We point to the fact that two sufficient but not necessary signatures of non-Markovianity of a classical process find their natural quantum counterpart in recently introduced measures of quantum non-Markovianity. This behaviour is analysed in detail for quantum dynamics which can be built taking as input a class of classical processes. (paper)

Continuous Markovian Logics

DEFF Research Database (Denmark)

Mardare, Radu Iulian; Cardelli, Luca; Larsen, Kim Guldstrand

2012-01-01

Continuous Markovian Logic (CML) is a multimodal logic that expresses quantitative and qualitative properties of continuous-time labelled Markov processes with arbitrary (analytic) state-spaces, henceforth called continuous Markov processes (CMPs). The modalities of CML evaluate the rates...... of the exponentially distributed random variables that characterize the duration of the labeled transitions of a CMP. In this paper we present weak and strong complete axiomatizations for CML and prove a series of metaproperties, including the finite model property and the construction of canonical models. CML...... characterizes stochastic bisimilarity and it supports the definition of a quantified extension of the satisfiability relation that measures the "compatibility" between a model and a property. In this context, the metaproperties allows us to prove two robustness theorems for the logic stating that one can...

Non-Markovian closure models for large eddy simulations using the Mori-Zwanzig formalism

Science.gov (United States)

Parish, Eric J.; Duraisamy, Karthik

2017-01-01

This work uses the Mori-Zwanzig (M-Z) formalism, a concept originating from nonequilibrium statistical mechanics, as a basis for the development of coarse-grained models of turbulence. The mechanics of the generalized Langevin equation (GLE) are considered, and insight gained from the orthogonal dynamics equation is used as a starting point for model development. A class of subgrid models is considered which represent nonlocal behavior via a finite memory approximation [Stinis, arXiv:1211.4285 (2012)], the length of which is determined using a heuristic that is related to the spectral radius of the Jacobian of the resolved variables. The resulting models are intimately tied to the underlying numerical resolution and are capable of approximating non-Markovian effects. Numerical experiments on the Burgers equation demonstrate that the M-Z-based models can accurately predict the temporal evolution of the total kinetic energy and the total dissipation rate at varying mesh resolutions. The trajectory of each resolved mode in phase space is accurately predicted for cases where the coarse graining is moderate. Large eddy simulations (LESs) of homogeneous isotropic turbulence and the Taylor-Green Vortex show that the M-Z-based models are able to provide excellent predictions, accurately capturing the subgrid contribution to energy transfer. Last, LESs of fully developed channel flow demonstrate the applicability of M-Z-based models to nondecaying problems. It is notable that the form of the closure is not imposed by the modeler, but is rather derived from the mathematics of the coarse graining, highlighting the potential of M-Z-based techniques to define LES closures.

a markovian study of manpow an study of manpower planning

African Journals Online (AJOL)

eobe

The Markovian method of manpower planning foretell the future. ... ive years from a soft drink manufacturing company based in Lagos, Nigeria company based ... ces management approach. ... handbook have also used Markov processes for.

SIMULTANEOUS MULTI-BAND DETECTION OF LOW SURFACE BRIGHTNESS GALAXIES WITH MARKOVIAN MODELING

Energy Technology Data Exchange (ETDEWEB)

Vollmer, B.; Bonnarel, F.; Louys, M. [CDS, Observatoire Astronomique, UMR 7550, 11 rue de l' universite, F-67000 Strasbourg (France); Perret, B.; Petremand, M.; Lavigne, F.; Collet, Ch. [LSIIT, Universite de Strasbourg, 7, Rue Rene Descartes, F-67084 Strasbourg (France); Van Driel, W. [GEPI, Observatoire de Paris, CNRS, Universite Paris Diderot, 5 place Jules Janssen, F-92190 Meudon (France); Sabatini, S. [INAF/IASF-Roma, via Fosso de Cavaliere 100, I-00133 Roma (Italy); MacArthur, L. A., E-mail: Bernd.Vollmer@astro.unistra.fr [Herzberg Institute of Astrophysics, National Research Council of Canada, Victoria, BC V9E 2E7 (Canada)

2013-02-01

We present to the astronomical community an algorithm for the detection of low surface brightness (LSB) galaxies in images, called MARSIAA (MARkovian Software for Image Analysis in Astronomy), which is based on multi-scale Markovian modeling. MARSIAA can be applied simultaneously to different bands. It segments an image into a user-defined number of classes, according to their surface brightness and surroundings-typically, one or two classes contain the LSB structures. We have developed an algorithm, called DetectLSB, which allows the efficient identification of LSB galaxies from among the candidate sources selected by MARSIAA. The application of the method to two and three bands simultaneously was tested on simulated images. Based on our tests, we are confident that we can detect LSB galaxies down to a central surface brightness level of only 1.5 times the standard deviation from the mean pixel value in the image background. To assess the robustness of our method, the method was applied to a set of 18 B- and I-band images (covering 1.3 deg{sup 2} in total) of the Virgo Cluster to which Sabatini et al. previously applied a matched-filter dwarf LSB galaxy search algorithm. We have detected all 20 objects from the Sabatini et al. catalog which we could classify by eye as bona fide LSB galaxies. Our method has also detected four additional Virgo Cluster LSB galaxy candidates undetected by Sabatini et al. To further assess the completeness of the results of our method, both MARSIAA, SExtractor, and DetectLSB were applied to search for (1) mock Virgo LSB galaxies inserted into a set of deep Next Generation Virgo Survey (NGVS) gri-band subimages and (2) Virgo LSB galaxies identified by eye in a full set of NGVS square degree gri images. MARSIAA/DetectLSB recovered {approx}20% more mock LSB galaxies and {approx}40% more LSB galaxies identified by eye than SExtractor/DetectLSB. With a 90% fraction of false positives from an entirely unsupervised pipeline, a completeness of

Quantum Darwinism and non-Markovian dissipative dynamics from quantum phases of the spin-1/2 X X model

Science.gov (United States)

Giorgi, Gian Luca; Galve, Fernando; Zambrini, Roberta

2015-08-01

Quantum Darwinism explains the emergence of a classical description of objects in terms of the creation of many redundant registers in an environment containing their classical information. This amplification phenomenon, where only classical information reaches the macroscopic observer and through which different observers can agree on the objective existence of such object, has been revived lately for several types of situations, successfully explaining classicality. We explore quantum Darwinism in the setting of an environment made of two level systems which are initially prepared in the ground state of the XX model, which exhibits different phases; we find that the different phases have different abilities to redundantly acquire classical information about the system, the "ferromagnetic phase" being the only one able to complete quantum Darwinism. At the same time we relate this ability to how non-Markovian the system dynamics is, based on the interpretation that non-Markovian dynamics is associated with backflow of information from environment to system, thus spoiling the information transfer needed for Darwinism. Finally, we explore mixing of bath registers by allowing a small interaction among them, finding that this spoils the stored information as previously found in the literature.

Selected Aspects of Markovian and Non-Markovian Quantum Master Equations

Science.gov (United States)

Lendi, K.

A few particular marked properties of quantum dynamical equations accounting for general relaxation and dissipation are selected and summarized in brief. Most results derive from the universal concept of complete positivity. The considerations mainly regard genuinely irreversible processes as characterized by a unique asymptotically stationary final state for arbitrary initial conditions. From ordinary Markovian master equations and associated quantum dynamical semigroup time-evolution, derivations of higher order Onsager coefficients and related entropy production are discussed. For general processes including non-faithful states a regularized version of quantum relative entropy is introduced. Further considerations extend to time-dependent infinitesimal generators of time-evolution and to a possible description of propagation of initial states entangled between open system and environment. In the coherence-vector representation of the full non-Markovian equations including entangled initial states, first results are outlined towards identifying mathematical properties of a restricted class of trial integral-kernel functions suited to phenomenological applications.

Non-Markovianity-assisted high-fidelity Deutsch-Jozsa algorithm in diamond

Science.gov (United States)

Dong, Yang; Zheng, Yu; Li, Shen; Li, Cong-Cong; Chen, Xiang-Dong; Guo, Guang-Can; Sun, Fang-Wen

2018-01-01

The memory effects in non-Markovian quantum dynamics can induce the revival of quantum coherence, which is believed to provide important physical resources for quantum information processing (QIP). However, no real quantum algorithms have been demonstrated with the help of such memory effects. Here, we experimentally implemented a non-Markovianity-assisted high-fidelity refined Deutsch-Jozsa algorithm (RDJA) with a solid spin in diamond. The memory effects can induce pronounced non-monotonic variations in the RDJA results, which were confirmed to follow a non-Markovian quantum process by measuring the non-Markovianity of the spin system. By applying the memory effects as physical resources with the assistance of dynamical decoupling, the probability of success of RDJA was elevated above 97% in the open quantum system. This study not only demonstrates that the non-Markovianity is an important physical resource but also presents a feasible way to employ this physical resource. It will stimulate the application of the memory effects in non-Markovian quantum dynamics to improve the performance of practical QIP.

Bayesian feedback versus Markovian feedback in a two-level atom

International Nuclear Information System (INIS)

Wiseman, H.M.; Mancini, Stefano; Wang Jin

2002-01-01

We compare two different approaches to the control of the dynamics of a continuously monitored open quantum system. The first is Markovian feedback, as introduced in quantum optics by Wiseman and Milburn [Phys. Rev. Lett. 70, 548 (1993)]. The second is feedback based on an estimate of the system state, developed recently by Doherty and Jacobs [Phys. Rev. A 60, 2700 (1999)]. Here we choose to call it, for brevity, Bayesian feedback. For systems with nonlinear dynamics, we expect these two methods of feedback control to give markedly different results. The simplest possible nonlinear system is a driven and damped two-level atom, so we choose this as our model system. The monitoring is taken to be homodyne detection of the atomic fluorescence, and the control is by modulating the driving. The aim of the feedback in both cases is to stabilize the internal state of the atom as close as possible to an arbitrarily chosen pure state, in the presence of inefficient detection and other forms of decoherence. Our results (obtained without recourse to stochastic simulations) prove that Bayesian feedback is never inferior, and is usually superior, to Markovian feedback. However, it would be far more difficult to implement than Markovian feedback and it loses its superiority when obvious simplifying approximations are made. It is thus not clear which form of feedback would be better in the face of inevitable experimental imperfections

Non-Markovianity of Gaussian Channels.

Science.gov (United States)

Torre, G; Roga, W; Illuminati, F

2015-08-14

We introduce a necessary and sufficient criterion for the non-Markovianity of Gaussian quantum dynamical maps based on the violation of divisibility. The criterion is derived by defining a general vectorial representation of the covariance matrix which is then exploited to determine the condition for the complete positivity of partial maps associated with arbitrary time intervals. Such construction does not rely on the Choi-Jamiolkowski representation and does not require optimization over states.

Non-Markovian dynamics, decoherence and entanglement in dissipative quantum systems with applications to quantum information theory of continuous variable systems

International Nuclear Information System (INIS)

Hoerhammer, C.

2007-01-01

In this thesis, non-Markovian dynamics, decoherence and entanglement in dissipative quantum systems are studied. In particular, applications to quantum information theory of continuous variable systems are considered. The non-Markovian dynamics are described by the Hu-Paz-Zhang master equation of quantum Brownian motion. In this context the focus is on non-Markovian effects on decoherence and separability time scales of various single- mode and two-mode continuous variable states. It is verified that moderate non-Markovian influences slow down the decay of interference fringes and quantum correlations, while strong non-Markovian effects resulting from an out-of-resonance bath can even accelerate the loss of coherence, compared to predictions of Markovian approximations. Qualitatively different scenarios including exponential, Gaussian or algebraic decay of the decoherence function are analyzed. It is shown that partial recurrence of coherence can occur in case of non-Lindblad-type dynamics. The time evolution of quantum correlations of entangled two-mode continuous variable states is examined in single-reservoir and two-reservoir models, representing noisy correlated or uncorrelated non-Markovian quantum channels. For this purpose the model of quantum Brownian motion is extended. Various separability criteria for Gaussian and non-Gaussian continuous variable systems are applied. In both types of reservoir models moderate non-Markovian effects prolong the separability time scales. However, in these models the properties of the stationary state may differ. In the two-reservoir model the initial entanglement is completely lost and both modes are finally uncorrelated. In a common reservoir both modes interact indirectly via the coupling to the same bath variables. Therefore, new quantum correlations may emerge between the two modes. Below a critical bath temperature entanglement is preserved even in the steady state. A separability criterion is derived, which depends

Properties of quantum Markovian master equations

International Nuclear Information System (INIS)

Gorini, V.; Frigerio, A.; Verri, M.; Kossakowski, A.; Sudarshan, E.C.G.

1976-11-01

An essentially self-contained account is given of some general structural properties of the dynamics of quantum open Markovian systems. Some recent results regarding the problem of the classification of quantum Markovian master equations and the limiting conditions under which the dynamical evolution of a quantum open system obeys an exact semigroup law (weak coupling limit and singular coupling limit are reviewed). A general form of quantum detailed balance and its relation to thermal relaxation and to microreversibility is discussed

Non-Markovian electron dynamics in nanostructures coupled to dissipative contacts

Science.gov (United States)

Novakovic, B.; Knezevic, I.

2013-02-01

In quasiballistic semiconductor nanostructures, carrier exchange between the active region and dissipative contacts is the mechanism that governs relaxation. In this paper, we present a theoretical treatment of transient quantum transport in quasiballistic semiconductor nanostructures, which is based on the open system theory and valid on timescales much longer than the characteristic relaxation time in the contacts. The approach relies on a model interaction between the current-limiting active region and the contacts, given in the scattering-state basis. We derive a non-Markovian master equation for the irreversible evolution of the active region's many-body statistical operator by coarse-graining the exact dynamical map over the contact relaxation time. In order to obtain the response quantities of a nanostructure under bias, such as the potential and the charge and current densities, the non-Markovian master equation must be solved numerically together with the Schr\\"{o}dinger, Poisson, and continuity equations. We discuss how to numerically solve this coupled system of equations and illustrate the approach on the example of a silicon nin diode.

Connecting two jumplike unravelings for non-Markovian open quantum systems

Energy Technology Data Exchange (ETDEWEB)

Luoma, Kimmo; Suominen, Kalle-Antti; Piilo, Jyrki [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku, FI-20014 Turun Yliopisto (Finland)

2011-09-15

The development and use of Monte Carlo algorithms plays a visible role in the study of non-Markovian quantum dynamics due to the provided insight and powerful numerical methods for solving the system dynamics. In the Markovian case, the connections between the various types of methods are fairly well understood while, for the non-Markovian case, there has so far been only a few studies. We focus here on two jumplike unravelings of non-Markovian dynamics: the non-Markovian quantum jump (NMQJ) method and the property state method by Gambetta, Askerud, and Wiseman (GAW). The results for simple quantum optical systems illustrate the connections between the realizations of the two methods and also highlight how the probability currents between the system and environment, or between the property states of the total system, are associated with the decay rates of time-local master equations and, consequently, with the jump rates of the NMQJ method.

Connecting two jumplike unravelings for non-Markovian open quantum systems

International Nuclear Information System (INIS)

Luoma, Kimmo; Suominen, Kalle-Antti; Piilo, Jyrki

2011-01-01

The development and use of Monte Carlo algorithms plays a visible role in the study of non-Markovian quantum dynamics due to the provided insight and powerful numerical methods for solving the system dynamics. In the Markovian case, the connections between the various types of methods are fairly well understood while, for the non-Markovian case, there has so far been only a few studies. We focus here on two jumplike unravelings of non-Markovian dynamics: the non-Markovian quantum jump (NMQJ) method and the property state method by Gambetta, Askerud, and Wiseman (GAW). The results for simple quantum optical systems illustrate the connections between the realizations of the two methods and also highlight how the probability currents between the system and environment, or between the property states of the total system, are associated with the decay rates of time-local master equations and, consequently, with the jump rates of the NMQJ method.

A comparison between Markovian models and Bayesian networks for treating some dependent events in reliability evaluations

International Nuclear Information System (INIS)

Duarte, Juliana P.; Leite, Victor C.; Melo, P.F. Frutuoso e

2013-01-01

Bayesian networks have become a very handy tool for solving problems in various application areas. This paper discusses the use of Bayesian networks to treat dependent events in reliability engineering typically modeled by Markovian models. Dependent events play an important role as, for example, when treating load-sharing systems, bridge systems, common-cause failures, and switching systems (those for which a standby component is activated after the main one fails by means of a switching mechanism). Repair plays an important role in all these cases (as, for example, the number of repairmen). All Bayesian network calculations are performed by means of the Netica™ software, of Norsys Software Corporation, and Fortran 90 to evaluate them over time. The discussion considers the development of time-dependent reliability figures of merit, which are easily obtained, through Markovian models, but not through Bayesian networks, because these latter need probability figures as input and not failure and repair rates. Bayesian networks produced results in very good agreement with those of Markov models and pivotal decomposition. Static and discrete time (DTBN) Bayesian networks were used in order to check their capabilities of modeling specific situations, like switching failures in cold-standby systems. The DTBN was more flexible to modeling systems where the time of occurrence of an event is important, for example, standby failure and repair. However, the static network model showed as good results as DTBN by a much more simplified approach. (author)

A comparison between Markovian models and Bayesian networks for treating some dependent events in reliability evaluations

Energy Technology Data Exchange (ETDEWEB)

Duarte, Juliana P.; Leite, Victor C.; Melo, P.F. Frutuoso e, E-mail: julianapduarte@poli.ufrj.br, E-mail: victor.coppo.leite@poli.ufrj.br, E-mail: frutuoso@nuclear.ufrj.br [Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, RJ (Brazil)

2013-07-01

Bayesian networks have become a very handy tool for solving problems in various application areas. This paper discusses the use of Bayesian networks to treat dependent events in reliability engineering typically modeled by Markovian models. Dependent events play an important role as, for example, when treating load-sharing systems, bridge systems, common-cause failures, and switching systems (those for which a standby component is activated after the main one fails by means of a switching mechanism). Repair plays an important role in all these cases (as, for example, the number of repairmen). All Bayesian network calculations are performed by means of the Netica™ software, of Norsys Software Corporation, and Fortran 90 to evaluate them over time. The discussion considers the development of time-dependent reliability figures of merit, which are easily obtained, through Markovian models, but not through Bayesian networks, because these latter need probability figures as input and not failure and repair rates. Bayesian networks produced results in very good agreement with those of Markov models and pivotal decomposition. Static and discrete time (DTBN) Bayesian networks were used in order to check their capabilities of modeling specific situations, like switching failures in cold-standby systems. The DTBN was more flexible to modeling systems where the time of occurrence of an event is important, for example, standby failure and repair. However, the static network model showed as good results as DTBN by a much more simplified approach. (author)

Thermodynamic fingerprints of non-Markovianity in a system of coupled superconducting qubits

Science.gov (United States)

Hamedani Raja, Sina; Borrelli, Massimo; Schmidt, Rebecca; Pekola, Jukka P.; Maniscalco, Sabrina

2018-03-01

The exploitation and characterization of memory effects arising from the interaction between system and environment is a key prerequisite for quantum reservoir engineering beyond the standard Markovian limit. In this paper we investigate a prototype of non-Markovian dynamics experimentally implementable with superconducting qubits. We rigorously quantify non-Markovianity, highlighting the effects of the environmental temperature on the Markovian to non-Markovian crossover. We investigate how memory effects influence, and specifically suppress, the ability to perform work on the driven qubit. We show that the average work performed on the qubit can be used as a diagnostic tool to detect the presence or absence of memory effects.

A framework for the direct evaluation of large deviations in non-Markovian processes

International Nuclear Information System (INIS)

Cavallaro, Massimo; Harris, Rosemary J

2016-01-01

We propose a general framework to simulate stochastic trajectories with arbitrarily long memory dependence and efficiently evaluate large deviation functions associated to time-extensive observables. This extends the ‘cloning’ procedure of Giardiná et al (2006 Phys. Rev. Lett. 96 120603) to non-Markovian systems. We demonstrate the validity of this method by testing non-Markovian variants of an ion-channel model and the totally asymmetric exclusion process, recovering results obtainable by other means. (letter)

Colloquium: Non-Markovian dynamics in open quantum systems

Science.gov (United States)

Breuer, Heinz-Peter; Laine, Elsi-Mari; Piilo, Jyrki; Vacchini, Bassano

2016-04-01

The dynamical behavior of open quantum systems plays a key role in many applications of quantum mechanics, examples ranging from fundamental problems, such as the environment-induced decay of quantum coherence and relaxation in many-body systems, to applications in condensed matter theory, quantum transport, quantum chemistry, and quantum information. In close analogy to a classical Markovian stochastic process, the interaction of an open quantum system with a noisy environment is often modeled phenomenologically by means of a dynamical semigroup with a corresponding time-independent generator in Lindblad form, which describes a memoryless dynamics of the open system typically leading to an irreversible loss of characteristic quantum features. However, in many applications open systems exhibit pronounced memory effects and a revival of genuine quantum properties such as quantum coherence, correlations, and entanglement. Here recent theoretical results on the rich non-Markovian quantum dynamics of open systems are discussed, paying particular attention to the rigorous mathematical definition, to the physical interpretation and classification, as well as to the quantification of quantum memory effects. The general theory is illustrated by a series of physical examples. The analysis reveals that memory effects of the open system dynamics reflect characteristic features of the environment which opens a new perspective for applications, namely, to exploit a small open system as a quantum probe signifying nontrivial features of the environment it is interacting with. This Colloquium further explores the various physical sources of non-Markovian quantum dynamics, such as structured environmental spectral densities, nonlocal correlations between environmental degrees of freedom, and correlations in the initial system-environment state, in addition to developing schemes for their local detection. Recent experiments addressing the detection, quantification, and control of

Control and filtering for semi-Markovian jump systems

CERN Document Server

Li, Fanbiao; Wu, Ligang

2017-01-01

This book presents up-to-date research developments and novel methodologies on semi-Markovian jump systems (S-MJS). It presents solutions to a series of problems with new approaches for the control and filtering of S-MJS, including stability analysis, sliding mode control, dynamic output feedback control, robust filter design, and fault detection. A set of newly developed techniques such as piecewise analysis method, positively invariant set approach, event-triggered method, and cone complementary linearization approaches are presented. Control and Filtering for Semi-Markovian Jump Systems is a comprehensive reference for researcher and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.

Markovian Model in High Order Sequence Prediction From Log-Motif Patterns in Agbada Paralic Section, Niger Delta, Nigeria

International Nuclear Information System (INIS)

Olabode, S. O.; Adekoya, J. A.

2002-01-01

Markovian model in the elucidation of high order sequence was applied to repetitive events of regressive and transgressive phases in the Agbada paralic section Niger Delta. The repetitive events are made up of delta front, delta topset and fluvio-deltaic sediments. The sediments consist of sands, sandstones, siltstones and shales in various proportions. Five wells: MN1, AA1, NP2, NP6 and NP8 were studied.Summary of biostratigraphic report and well log-motif patterns was used to delineate the third order depositional sequences in the wells.Various Markovian properties - observed transition frequency matrix, observed transition probability matrix, fixed probability vector, expected random matrix (randomised transition matrix) and difference matrix were determined for stacked high order sequence (high frequency cyclic events) nested within the third-order sequences using the log-motif patterns for the various sand bodies and shales. Flow diagrams were constructed for each of the depositional sequences to know the likely occurrence of number of cycles.Upward transition matrix between the log-motif patterns and flow diagram to elucidate cyclicity show that the overall regressive sequence of the Niger Delta has been modified by deltaic depositional elements and fluctuations in sea level. The predictions of higher order sequence within third order sequences from Markovian Properties provide good basis for correlation within the depositional sequences. The model has also been used to decipher the dominant depositional processes during the formation of the sequences. Discrete reservoir intervals and seal potentials within the sequences were also predicted from the flow diagrams constructed

Non-Markovianity hinders Quantum Darwinism

Science.gov (United States)

Galve, Fernando; Zambrini, Roberta; Maniscalco, Sabrina

2016-01-01

We investigate Quantum Darwinism and the emergence of a classical world from the quantum one in connection with the spectral properties of the environment. We use a microscopic model of quantum environment in which, by changing a simple system parameter, we can modify the information back flow from environment into the system, and therefore its non-Markovian character. We show that the presence of memory effects hinders the emergence of classical objective reality, linking these two apparently unrelated concepts via a unique dynamical feature related to decoherence factors.

Non-Markovian decoherent quantum walks

International Nuclear Information System (INIS)

Xue Peng; Zhang Yong-Sheng

2013-01-01

Quantum walks act in obviously different ways from their classical counterparts, but decoherence will lessen and close this gap between them. To understand this process, it is necessary to investigate the evolution of quantum walks under different decoherence situations. In this article, we study a non-Markovian decoherent quantum walk on a line. In a short time regime, the behavior of the walk deviates from both ideal quantum walks and classical random walks. The position variance as a measure of the quantum walk collapses and revives for a short time, and tends to have a linear relation with time. That is, the walker's behavior shows a diffusive spread over a long time limit, which is caused by non-Markovian dephasing affecting the quantum correlations between the quantum walker and his coin. We also study both quantum discord and measurement-induced disturbance as measures of the quantum correlations, and observe both collapse and revival in the short time regime, and the tendency to be zero in the long time limit. Therefore, quantum walks with non-Markovian decoherence tend to have diffusive spreading behavior over long time limits, while in the short time regime they oscillate between ballistic and diffusive spreading behavior, and the quantum correlation collapses and revives due to the memory effect

Fault-tolerant quantum computation for local non-Markovian noise

International Nuclear Information System (INIS)

Terhal, Barbara M.; Burkard, Guido

2005-01-01

We derive a threshold result for fault-tolerant quantum computation for local non-Markovian noise models. The role of error amplitude in our analysis is played by the product of the elementary gate time t 0 and the spectral width of the interaction Hamiltonian between system and bath. We discuss extensions of our model and the applicability of our analysis

Interpretation of non-Markovian stochastic Schroedinger equations as a hidden-variable theory

International Nuclear Information System (INIS)

Gambetta, Jay; Wiseman, H.M.

2003-01-01

Do diffusive non-Markovian stochastic Schroedinger equations (SSEs) for open quantum systems have a physical interpretation? In a recent paper [Phys. Rev. A 66, 012108 (2002)] we investigated this question using the orthodox interpretation of quantum mechanics. We found that the solution of a non-Markovian SSE represents the state the system would be in at that time if a measurement was performed on the environment at that time, and yielded a particular result. However, the linking of solutions at different times to make a trajectory is, we concluded, a fiction. In this paper we investigate this question using the modal (hidden variable) interpretation of quantum mechanics. We find that the noise function z(t) appearing in the non-Markovian SSE can be interpreted as a hidden variable for the environment. That is, some chosen property (beable) of the environment has a definite value z(t) even in the absence of measurement on the environment. The non-Markovian SSE gives the evolution of the state of the system 'conditioned' on this environment hidden variable. We present the theory for diffusive non-Markovian SSEs that have as their Markovian limit SSEs corresponding to homodyne and heterodyne detection, as well as one which has no Markovian limit

Generalized formalism for information backflow in assessing Markovianity and its equivalence to divisibility

Science.gov (United States)

Chakraborty, Sagnik

2018-03-01

We present a general framework for the information backflow (IB) approach of Markovianity that not only includes a large number, if not all, of IB prescriptions proposed so far but also is equivalent to completely positive divisibility for invertible evolutions. Following the common approach of IB, where monotonic decay of some physical property or some information quantifier is seen as the definition of Markovianity, we propose in our framework a general description of what should be called a proper "physicality quantifier" to define Markovianity. We elucidate different properties of our framework and use them to argue that an infinite family of non-Markovianity measures can be constructed, which would capture varied strengths of non-Markovianity in the dynamics. Moreover, we show that generalized trace-distance measure in two dimensions serve as a sufficient criteria for IB Markovianity for a number of prescriptions suggested earlier in the literature.

Sufficient conditions for positivity of non-Markovian master equations with Hermitian generators

International Nuclear Information System (INIS)

Wilkie, Joshua; Wong Yinmei

2009-01-01

We use basic physical motivations to develop sufficient conditions for positive semidefiniteness of the reduced density matrix for generalized non-Markovian integrodifferential Lindblad-Kossakowski master equations with Hermitian generators. We show that it is sufficient for the memory function to be the Fourier transform of a real positive symmetric frequency density function with certain properties. These requirements are physically motivated, and are more general and more easily checked than previously stated sufficient conditions. We also explore the decoherence dynamics numerically for some simple models using the Hadamard representation of the propagator. We show that the sufficient conditions are not necessary conditions. We also show that models exist in which the long time limit is in part determined by non-Markovian effects

Study on the security of discrete-variable quantum key distribution over non-Markovian channels

International Nuclear Information System (INIS)

Huang Peng; Zhu Jun; He Guangqiang; Zeng Guihua

2012-01-01

The dynamic of the secret key rate of the discrete-variable quantum key distribution (QKD) protocol over the non-Markovian quantum channel is investigated. In particular, we calculate the secret key rate for the six-state protocol over non-Markovian depolarizing channels with coloured noise and Markovian depolarizing channels with Gaussian white noise, respectively. We find that the secure secret key rate for the non-Markovian depolarizing channel will be larger than the Markovian one under the same conditions even when their upper bounds of tolerable quantum bit error rate are equal. This indicates that this coloured noise in the non-Markovian depolarizing channel can enhance the security of communication. Moreover, we show that the secret key rate fluctuates near the secure point when the coupling strength of the system with the environment is high. The results demonstrate that the non-Markovian effects of the transmission channel can have a positive impact on the security of discrete-variable QKD. (paper)

Rate processes with non-Markovian dynamical disorder

International Nuclear Information System (INIS)

Goychuk, Igor

2005-01-01

Rate processes with dynamical disorder are investigated within a simple framework provided by unidirectional electron transfer (ET) with fluctuating transfer rate. The rate fluctuations are assumed to be described by a non-Markovian stochastic jump process which reflects conformational dynamics of an electron transferring donor-acceptor molecular complex. A tractable analytical expression is obtained for the relaxation of the donor population (in the Laplace-transformed time domain) averaged over the stationary conformational fluctuations. The corresponding mean transfer time is also obtained in an analytical form. The case of two-state fluctuations is studied in detail for a model incorporating substate diffusion within one of the conformations. It is shown that an increase of the conformational diffusion time results in a gradual transition from the regime of fast modulation characterized by the averaged ET rate to the regime of quasistatic disorder. This transition occurs at the conformational mean residence time intervals fixed much less than the inverse of the corresponding ET rates. An explanation of this paradoxical effect is provided. Moreover, its presence is also manifested for the simplest, exactly solvable non-Markovian model with a biexponential distribution of the residence times in one of the conformations. The nontrivial conditions for this phenomenon to occur are found

Pricing Exotic Options under a High-Order Markovian Regime Switching Model

Directory of Open Access Journals (Sweden)

Wai-Ki Ching

2007-10-01

Full Text Available We consider the pricing of exotic options when the price dynamics of the underlying risky asset are governed by a discrete-time Markovian regime-switching process driven by an observable, high-order Markov model (HOMM. We assume that the market interest rate, the drift, and the volatility of the underlying risky asset's return switch over time according to the states of the HOMM, which are interpreted as the states of an economy. We will then employ the well-known tool in actuarial science, namely, the Esscher transform to determine an equivalent martingale measure for option valuation. Moreover, we will also investigate the impact of the high-order effect of the states of the economy on the prices of some path-dependent exotic options, such as Asian options, lookback options, and barrier options.

Non-Markovian dynamics in the theory of full counting statistics

DEFF Research Database (Denmark)

Flindt, Christian; Braggio, A.; Novotny, Tomas

2007-01-01

generating function corresponding to the resulting non-Markovian rate equation and find that the measured current cumulants behave significantly differently compared to those of a Markovian transport process. Our findings provide a novel interpretation of noise suppression found in a number of systems....

Robust Guaranteed Cost Observer Design for Singular Markovian Jump Time-Delay Systems with Generally Incomplete Transition Probability

Directory of Open Access Journals (Sweden)

Yanbo Li

2014-01-01

Full Text Available This paper is devoted to the investigation of the design of robust guaranteed cost observer for a class of linear singular Markovian jump time-delay systems with generally incomplete transition probability. In this singular model, each transition rate can be completely unknown or only its estimate value is known. Based on stability theory of stochastic differential equations and linear matrix inequality (LMI technique, we design an observer to ensure that, for all uncertainties, the resulting augmented system is regular, impulse free, and robust stochastically stable with the proposed guaranteed cost performance. Finally, a convex optimization problem with LMI constraints is formulated to design the suboptimal guaranteed cost filters for linear singular Markovian jump time-delay systems with generally incomplete transition probability.

Burst of virus infection and a possibly largest epidemic threshold of non-Markovian susceptible-infected-susceptible processes on networks

Science.gov (United States)

Liu, Qiang; Van Mieghem, Piet

2018-02-01

Since a real epidemic process is not necessarily Markovian, the epidemic threshold obtained under the Markovian assumption may be not realistic. To understand general non-Markovian epidemic processes on networks, we study the Weibullian susceptible-infected-susceptible (SIS) process in which the infection process is a renewal process with a Weibull time distribution. We find that, if the infection rate exceeds 1 /ln(λ1+1 ) , where λ1 is the largest eigenvalue of the network's adjacency matrix, then the infection will persist on the network under the mean-field approximation. Thus, 1 /ln(λ1+1 ) is possibly the largest epidemic threshold for a general non-Markovian SIS process with a Poisson curing process under the mean-field approximation. Furthermore, non-Markovian SIS processes may result in a multimodal prevalence. As a byproduct, we show that a limiting Weibullian SIS process has the potential to model bursts of a synchronized infection.

Non-equilibrium effects upon the non-Markovian Caldeira-Leggett quantum master equation

International Nuclear Information System (INIS)

Bolivar, A.O.

2011-01-01

Highlights: → Classical Brownian motion described by a non-Markovian Fokker-Planck equation. → Quantization process. → Quantum Brownian motion described by a non-Markovian Caldeira-Leggett equation. → A non-equilibrium quantum thermal force is predicted. - Abstract: We obtain a non-Markovian quantum master equation directly from the quantization of a non-Markovian Fokker-Planck equation describing the Brownian motion of a particle immersed in a generic environment (e.g. a non-thermal fluid). As far as the especial case of a heat bath comprising of quantum harmonic oscillators is concerned, we derive a non-Markovian Caldeira-Leggett master equation on the basis of which we work out the concept of non-equilibrium quantum thermal force exerted by the harmonic heat bath upon the Brownian motion of a free particle. The classical limit (or dequantization process) of this sort of non-equilibrium quantum effect is scrutinized, as well.

Exact non-Markovian master equations for multiple qubit systems: Quantum-trajectory approach

Science.gov (United States)

Chen, Yusui; You, J. Q.; Yu, Ting

2014-11-01

A wide class of exact master equations for a multiple qubit system can be explicitly constructed by using the corresponding exact non-Markovian quantum-state diffusion equations. These exact master equations arise naturally from the quantum decoherence dynamics of qubit system as a quantum memory coupled to a collective colored noisy source. The exact master equations are also important in optimal quantum control, quantum dissipation, and quantum thermodynamics. In this paper, we show that the exact non-Markovian master equation for a dissipative N -qubit system can be derived explicitly from the statistical average of the corresponding non-Markovian quantum trajectories. We illustrated our general formulation by an explicit construction of a three-qubit system coupled to a non-Markovian bosonic environment. This multiple qubit master equation offers an accurate time evolution of quantum systems in various domains, and paves the way to investigate the memory effect of an open system in a non-Markovian regime without any approximation.

Individual-based modeling of fish: Linking to physical models and water quality.

Energy Technology Data Exchange (ETDEWEB)

Rose, K.A.

1997-08-01

The individual-based modeling approach for the simulating fish population and community dynamics is gaining popularity. Individual-based modeling has been used in many other fields, such as forest succession and astronomy. The popularity of the individual-based approach is partly a result of the lack of success of the more aggregate modeling approaches traditionally used for simulating fish population and community dynamics. Also, recent recognition that it is often the atypical individual that survives has fostered interest in the individual-based approach. Two general types of individual-based models are distribution and configuration. Distribution models follow the probability distributions of individual characteristics, such as length and age. Configuration models explicitly simulate each individual; the sum over individuals being the population. DeAngelis et al (1992) showed that, when distribution and configuration models were formulated from the same common pool of information, both approaches generated similar predictions. The distribution approach was more compact and general, while the configuration approach was more flexible. Simple biological changes, such as making growth rate dependent on previous days growth rates, were easy to implement in the configuration version but prevented simple analytical solution of the distribution version.

Evolution of entropy in different types of non-Markovian three-level ...

Indian Academy of Sciences (India)

ference between Markovian and non-Markovian systems lies in the memory ... In recent years, research on quantum entanglement has attracted a lot of attention, which .... Hamiltonians for three types of atoms in the interaction picture are.

Kinetics of subdiffusion-assisted reactions: non-Markovian stochastic Liouville equation approach

International Nuclear Information System (INIS)

Shushin, A I

2005-01-01

Anomalous specific features of the kinetics of subdiffusion-assisted bimolecular reactions (time-dependence, dependence on parameters of systems, etc) are analysed in detail with the use of the non-Markovian stochastic Liouville equation (SLE), which has been recently derived within the continuous-time random-walk (CTRW) approach. In the CTRW approach, subdiffusive motion of particles is modelled by jumps whose onset probability distribution function is of a long-tailed form. The non-Markovian SLE allows for rigorous describing of some peculiarities of these reactions; for example, very slow long-time behaviour of the kinetics, non-analytical dependence of the reaction rate on the reactivity of particles, strong manifestation of fluctuation kinetics showing itself in very slowly decreasing behaviour of the kinetics at very long times, etc

Enhancement of Quantum Correlations in Qubit-Qutrit Systems under the non-Markovian Environment

Institute of Scientific and Technical Information of China (English)

Abdul Basit; Hamad Ali; Fazal Badshah; Guo-Qin Ge

2017-01-01

We investigate the time evolution of quantum correlations of a hybrid qubit-qutrit system under the classical Ornstein-Uhlenbeck (OU) noise.Here we consider two different one-parameter families of qubit-qutrit states which independently interact with the non-Markovian reservoirs.A comparison with the Markovian dynamics reveals that for the same set of initial condition parameters,the non-Markovian behavior of the environment plays an important role in the enhancement of the survival time of quantum correlations.In addition,it is observed that the non-Markovian strength (γ/F) has a positive impact on the correlations time.For the initial separable states it is found that there is a finite time interval in which the geometric quantum discord is frozen despite the presence of a noisy environment and that interval can be further prolonged by using the non-Markovian property.Moreover,its decay can be significantly delayed.

Non-Markovian spontaneous emission from a single quantum dot

DEFF Research Database (Denmark)

Madsen, Kristian Høeg; Ates, Serkan; Lund-Hansen, Toke

2011-01-01

We observe non-Markovian dynamics of a single quantum dot when tuned into resonance with a cavity mode. Excellent agreement between experiment and theory is observed providing the first quantitative description of such a system.......We observe non-Markovian dynamics of a single quantum dot when tuned into resonance with a cavity mode. Excellent agreement between experiment and theory is observed providing the first quantitative description of such a system....

Jump probabilities in the non-Markovian quantum jump method

International Nuclear Information System (INIS)

Haerkoenen, Kari

2010-01-01

The dynamics of a non-Markovian open quantum system described by a general time-local master equation is studied. The propagation of the density operator is constructed in terms of two processes: (i) deterministic evolution and (ii) evolution of a probability density functional in the projective Hilbert space. The analysis provides a derivation for the jump probabilities used in the recently developed non-Markovian quantum jump (NMQJ) method (Piilo et al 2008 Phys. Rev. Lett. 100 180402).

Controlling quantum memory-assisted entropic uncertainty in non-Markovian environments

Science.gov (United States)

Zhang, Yanliang; Fang, Maofa; Kang, Guodong; Zhou, Qingping

2018-03-01

Quantum memory-assisted entropic uncertainty relation (QMA EUR) addresses that the lower bound of Maassen and Uffink's entropic uncertainty relation (without quantum memory) can be broken. In this paper, we investigated the dynamical features of QMA EUR in the Markovian and non-Markovian dissipative environments. It is found that dynamical process of QMA EUR is oscillation in non-Markovian environment, and the strong interaction is favorable for suppressing the amount of entropic uncertainty. Furthermore, we presented two schemes by means of prior weak measurement and posterior weak measurement reversal to control the amount of entropic uncertainty of Pauli observables in dissipative environments. The numerical results show that the prior weak measurement can effectively reduce the wave peak values of the QMA-EUA dynamic process in non-Markovian environment for long periods of time, but it is ineffectual on the wave minima of dynamic process. However, the posterior weak measurement reversal has an opposite effects on the dynamic process. Moreover, the success probability entirely depends on the quantum measurement strength. We hope that our proposal could be verified experimentally and might possibly have future applications in quantum information processing.

Entanglement, non-Markovianity, and causal non-separability

Science.gov (United States)

Milz, Simon; Pollock, Felix A.; Le, Thao P.; Chiribella, Giulio; Modi, Kavan

2018-03-01

Quantum mechanics, in principle, allows for processes with indefinite causal order. However, most of these causal anomalies have not yet been detected experimentally. We show that every such process can be simulated experimentally by means of non-Markovian dynamics with a measurement on additional degrees of freedom. In detail, we provide an explicit construction to implement arbitrary a causal processes. Furthermore, we give necessary and sufficient conditions for open system dynamics with measurement to yield processes that respect causality locally, and find that tripartite entanglement and nonlocal unitary transformations are crucial requirements for the simulation of causally indefinite processes. These results show a direct connection between three counter-intuitive concepts: entanglement, non-Markovianity, and causal non-separability.

Non-Markovian effect on the geometric phase of a dissipative qubit

International Nuclear Information System (INIS)

Chen Juanjuan; Tong Qingjun; An Junhong; Luo Honggang; Oh, C. H.

2010-01-01

We studied the geometric phase of a two-level atom coupled to an environment with Lorentzian spectral density. The non-Markovian effect on the geometric phase is explored analytically and numerically. In the weak coupling limit, the lowest order correction to the geometric phase is derived analytically and the general case is calculated numerically. It was found that the correction to the geometric phase is significantly large if the spectral width is small, and in this case the non-Markovian dynamics has a significant impact on the geometric phase. When the spectral width increases, the correction to the geometric phase becomes negligible, which shows the robustness of the geometric phase to the environmental white noises. The result is significant to the quantum information processing based on the geometric phase.

Reliability Analysis of Wireless Sensor Networks Using Markovian Model

Directory of Open Access Journals (Sweden)

Jin Zhu

2012-01-01

Full Text Available This paper investigates reliability analysis of wireless sensor networks whose topology is switching among possible connections which are governed by a Markovian chain. We give the quantized relations between network topology, data acquisition rate, nodes' calculation ability, and network reliability. By applying Lyapunov method, sufficient conditions of network reliability are proposed for such topology switching networks with constant or varying data acquisition rate. With the conditions satisfied, the quantity of data transported over wireless network node will not exceed node capacity such that reliability is ensured. Our theoretical work helps to provide a deeper understanding of real-world wireless sensor networks, which may find its application in the fields of network design and topology control.

Non-Markovian near-infrared Q branch of HCl diluted in liquid Ar.

Science.gov (United States)

Padilla, Antonio; Pérez, Justo

2013-08-28

By using a non-Markovian spectral theory based in the Kubo cumulant expansion technique, we have qualitatively studied the infrared Q branch observed in the fundamental absorption band of HCl diluted in liquid Ar. The statistical parameters of the anisotropic interaction present in this spectral theory were calculated by means of molecular dynamics techniques, and found that the values of the anisotropic correlation times are significantly greater (by a factor of two) than those previously obtained by fitting procedures or microscopic cell models. This fact is decisive for the observation in the theoretical spectral band of a central Q resonance which is absent in the abundant previous researches carried out with the usual theories based in Kubo cumulant expansion techniques. Although the theory used in this work only allows a qualitative study of the Q branch, we can employ it to study the unknown characteristics of the Q resonance which are difficult to obtain with the quantum simulation techniques recently developed. For example, in this study we have found that the Q branch is basically a non-Markovian (or memory) effect produced by the spectral line interferences, where the PR interferential profile basically determines the Q branch spectral shape. Furthermore, we have found that the Q resonance is principally generated by the first rotational states of the first two vibrational levels, those more affected by the action of the dissolvent.

INDIVIDUAL BASED MODELLING APPROACH TO THERMAL ...

Science.gov (United States)

Diadromous fish populations in the Pacific Northwest face challenges along their migratory routes from declining habitat quality, harvest, and barriers to longitudinal connectivity. Changes in river temperature regimes are producing an additional challenge for upstream migrating adult salmon and steelhead, species that are sensitive to absolute and cumulative thermal exposure. Adult salmon populations have been shown to utilize cold water patches along migration routes when mainstem river temperatures exceed thermal optimums. We are employing an individual based model (IBM) to explore the costs and benefits of spatially-distributed cold water refugia for adult migrating salmon. Our model, developed in the HexSim platform, is built around a mechanistic behavioral decision tree that drives individual interactions with their spatially explicit simulated environment. Population-scale responses to dynamic thermal regimes, coupled with other stressors such as disease and harvest, become emergent properties of the spatial IBM. Other model outputs include arrival times, species-specific survival rates, body energetic content, and reproductive fitness levels. Here, we discuss the challenges associated with parameterizing an individual based model of salmon and steelhead in a section of the Columbia River. Many rivers and streams in the Pacific Northwest are currently listed as impaired under the Clean Water Act as a result of high summer water temperatures. Adverse effec

Stochastic stability analysis for delayed neural networks of neutral type with Markovian jump parameters

International Nuclear Information System (INIS)

Lou Xuyang; Cui Baotong

2009-01-01

In this paper, the problem of stochastic stability for a class of delayed neural networks of neutral type with Markovian jump parameters is investigated. The jumping parameters are modelled as a continuous-time, discrete-state Markov process. A sufficient condition guaranteeing the stochastic stability of the equilibrium point is derived for the Markovian jumping delayed neural networks (MJDNNs) with neutral type. The stability criterion not only eliminates the differences between excitatory and inhibitory effects on the neural networks, but also can be conveniently checked. The sufficient condition obtained can be essentially solved in terms of linear matrix inequality. A numerical example is given to show the effectiveness of the obtained results.

Quantum operation for a one-qubit system under a non-Markovian environment

International Nuclear Information System (INIS)

Xue Shibei; Zhang Jing; Wu Rebing; Li Chunwen; Tarn, Tzyh-Jong

2011-01-01

This paper introduces a simple alternating-current (AC) control strategy to perform quantum state manipulations under non-Markovian noise. A genetic algorithm is adopted to optimize the parameters of the AC control, which can be further used to fulfil one-qubit quantum operations at a given final time. Theoretical analysis and simulations show that our method works almost equally well for 1/f noise, ohmic, sub-ohmic and super-ohmic noise, which demonstrates the robustness of our strategy for noise with various spectra. In comparison with the Markovian cases, our method is more suitable to be used to suppress non-Markovian noise.

Individual-based modeling of ecological and evolutionary processes

NARCIS (Netherlands)

DeAngelis, D.L.; Mooij, W.M.

2005-01-01

Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential and difference equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis

Bilayer graphene lattice-layer entanglement in the presence of non-Markovian phase noise

Science.gov (United States)

Bittencourt, Victor A. S. V.; Blasone, Massimo; Bernardini, Alex E.

2018-03-01

The evolution of single particle excitations of bilayer graphene under effects of non-Markovian noise is described with focus on the decoherence process of lattice-layer (LL) maximally entangled states. Once the noiseless dynamics of an arbitrary initial state is identified by the correspondence between the tight-binding Hamiltonian for the AB-stacked bilayer graphene and the Dirac equation—which includes pseudovectorlike and tensorlike field interactions—the noisy environment is described as random fluctuations on bias voltage and mass terms. The inclusion of noisy dynamics reproduces the Ornstein-Uhlenbeck processes: A non-Markovian noise model with a well-defined Markovian limit. Considering that an initial amount of entanglement shall be dissipated by the noise, two profiles of dissipation are identified. On one hand, for eigenstates of the noiseless Hamiltonian, deaths and revivals of entanglement are identified along the oscillation pattern for long interaction periods. On the other hand, for departing LL Werner and Cat states, the entanglement is suppressed although, for both cases, some identified memory effects compete with the pure noise-induced decoherence in order to preserve the the overall profile of a given initial state.

Perturbative approach to Markovian open quantum systems.

Science.gov (United States)

Li, Andy C Y; Petruccione, F; Koch, Jens

2014-05-08

The exact treatment of Markovian open quantum systems, when based on numerical diagonalization of the Liouville super-operator or averaging over quantum trajectories, is severely limited by Hilbert space size. Perturbation theory, standard in the investigation of closed quantum systems, has remained much less developed for open quantum systems where a direct application to the Lindblad master equation is desirable. We present such a perturbative treatment which will be useful for an analytical understanding of open quantum systems and for numerical calculation of system observables which would otherwise be impractical.

Deterministic quantum controlled-PHASE gates based on non-Markovian environments

Science.gov (United States)

Zhang, Rui; Chen, Tian; Wang, Xiang-Bin

2017-12-01

We study the realization of the quantum controlled-PHASE gate in an atom-cavity system beyond the Markovian approximation. The general description of the dynamics for the atom-cavity system without any approximation is presented. When the spectral density of the reservoir has the Lorentz form, by making use of the memory backflow from the reservoir, we can always construct the deterministic quantum controlled-PHASE gate between a photon and an atom, no matter the atom-cavity coupling strength is weak or strong. While, the phase shift in the output pulse hinders the implementation of quantum controlled-PHASE gates in the sub-Ohmic, Ohmic or super-Ohmic reservoirs.

Robust extended Kalman filter of discrete-time Markovian jump nonlinear system under uncertain noise

International Nuclear Information System (INIS)

Zhu, Jin; Park, Jun Hong; Lee, Kwan Soo; Spiryagin, Maksym

2008-01-01

This paper examines the problem of robust extended Kalman filter design for discrete -time Markovian jump nonlinear systems with noise uncertainty. Because of the existence of stochastic Markovian switching, the state and measurement equations of underlying system are subject to uncertain noise whose covariance matrices are time-varying or un-measurable instead of stationary. First, based on the expression of filtering performance deviation, admissible uncertainty of noise covariance matrix is given. Secondly, two forms of noise uncertainty are taken into account: Non- Structural and Structural. It is proved by applying game theory that this filter design is a robust mini-max filter. A numerical example shows the validity of the method

Markovian Dynamics of Josephson Parametric Amplification

Directory of Open Access Journals (Sweden)

W. Kaiser

2017-09-01

Full Text Available In this work, we derive the dynamics of the lossy DC pumped non-degenerate Josephson parametric amplifier (DCPJPA. The main element in a DCPJPA is the superconducting Josephson junction. The DC bias generates the AC Josephson current varying the nonlinear inductance of the junction. By this way the Josephson junction acts as the pump oscillator as well as the time varying reactance of the parametric amplifier. In quantum-limited amplification, losses and noise have an increased impact on the characteristics of an amplifier. We outline the classical model of the lossy DCPJPA and derive the available noise power spectral densities. A classical treatment is not capable of including properties like spontaneous emission which is mandatory in case of amplification at the quantum limit. Thus, we derive a quantum mechanical model of the lossy DCPJPA. Thermal losses are modeled by the quantum Langevin approach, by coupling the quantized system to a photon heat bath in thermodynamic equilibrium. The mode occupation in the bath follows the Bose-Einstein statistics. Based on the second quantization formalism, we derive the Heisenberg equations of motion of both resonator modes. We assume the dynamics of the system to follow the Markovian approximation, i.e. the system only depends on its actual state and is memory-free. We explicitly compute the time evolution of the contributions to the signal mode energy and give numeric examples based on different damping and coupling constants. Our analytic results show, that this model is capable of including thermal noise into the description of the DC pumped non-degenerate Josephson parametric amplifier.

Markovian Dynamics of Josephson Parametric Amplification

Science.gov (United States)

Kaiser, Waldemar; Haider, Michael; Russer, Johannes A.; Russer, Peter; Jirauschek, Christian

2017-09-01

In this work, we derive the dynamics of the lossy DC pumped non-degenerate Josephson parametric amplifier (DCPJPA). The main element in a DCPJPA is the superconducting Josephson junction. The DC bias generates the AC Josephson current varying the nonlinear inductance of the junction. By this way the Josephson junction acts as the pump oscillator as well as the time varying reactance of the parametric amplifier. In quantum-limited amplification, losses and noise have an increased impact on the characteristics of an amplifier. We outline the classical model of the lossy DCPJPA and derive the available noise power spectral densities. A classical treatment is not capable of including properties like spontaneous emission which is mandatory in case of amplification at the quantum limit. Thus, we derive a quantum mechanical model of the lossy DCPJPA. Thermal losses are modeled by the quantum Langevin approach, by coupling the quantized system to a photon heat bath in thermodynamic equilibrium. The mode occupation in the bath follows the Bose-Einstein statistics. Based on the second quantization formalism, we derive the Heisenberg equations of motion of both resonator modes. We assume the dynamics of the system to follow the Markovian approximation, i.e. the system only depends on its actual state and is memory-free. We explicitly compute the time evolution of the contributions to the signal mode energy and give numeric examples based on different damping and coupling constants. Our analytic results show, that this model is capable of including thermal noise into the description of the DC pumped non-degenerate Josephson parametric amplifier.

Semiclassical evolution of dissipative Markovian systems

International Nuclear Information System (INIS)

Ozorio de Almeida, A M; Rios, P de M; Brodier, O

2009-01-01

A semiclassical approximation for an evolving density operator, driven by a 'closed' Hamiltonian operator and 'open' Markovian Lindblad operators, is obtained. The theory is based on the chord function, i.e. the Fourier transform of the Wigner function. It reduces to an exact solution of the Lindblad master equation if the Hamiltonian operator is a quadratic function and the Lindblad operators are linear functions of positions and momenta. Initially, the semiclassical formulae for the case of Hermitian Lindblad operators are reinterpreted in terms of a (real) double phase space, generated by an appropriate classical double Hamiltonian. An extra 'open' term is added to the double Hamiltonian by the non-Hermitian part of the Lindblad operators in the general case of dissipative Markovian evolution. The particular case of generic Hamiltonian operators, but linear dissipative Lindblad operators, is studied in more detail. A Liouville-type equivariance still holds for the corresponding classical evolution in double phase space, but the centre subspace, which supports the Wigner function, is compressed, along with expansion of its conjugate subspace, which supports the chord function. Decoherence narrows the relevant region of double phase space to the neighbourhood of a caustic for both the Wigner function and the chord function. This difficulty is avoided by a propagator in a mixed representation, so that a further 'small-chord' approximation leads to a simple generalization of the quadratic theory for evolving Wigner functions

Markovian Processes for Quantitative Information Leakage

DEFF Research Database (Denmark)

Biondi, Fabrizio

Quantification of information leakage is a successful approach for evaluating the security of a system. It models the system to be analyzed as a channel with the secret as the input and an output as observable by the attacker as the output, and applies information theory to quantify the amount...... and randomized processes with Markovian models and to compute their information leakage for a very general model of attacker. We present the QUAIL tool that automates such analysis and is able to compute the information leakage of an imperative WHILE language. Finally, we show how to use QUAIL to analyze some...... of information transmitted through such channel, thus effectively quantifying how many bits of the secret can be inferred by the attacker by analyzing the system’s output. Channels are usually encoded as matrices of conditional probabilities, known as channel matrices. Such matrices grow exponentially...

Non-Markovianity and memory of the initial state

Science.gov (United States)

Hinarejos, Margarida; Bañuls, Mari-Carmen; Pérez, Armando; de Vega, Inés

2017-08-01

We explore in a rigorous manner the intuitive connection between the non-Markovianity of the evolution of an open quantum system and the performance of the system as a quantum memory. Using the paradigmatic case of a two-level open quantum system coupled to a bosonic bath, we compute the recovery fidelity, which measures the best possible performance of the system to store a qubit of information. We deduce that this quantity is connected, but not uniquely determined, by the non-Markovianity, for which we adopt the Breuer-Laine-Piilo measure proposed in Breuer et al (2009 Phys. Rev. Lett. 103 210401). We illustrate our findings with explicit calculations for the case of a structured environment.

Non-Markovian Effects on the Brownian Motion of a Free Particle

OpenAIRE

Bolivar, A. O.

2010-01-01

Non-Markovian effects upon the Brownian movement of a free particle in the presence as well as in the absence of inertial force are investigated within the framework of Fokker-Planck equations (Rayleigh and Smoluchowski equations). More specifically, it is predicted that non-Markovian features can enhance the values of the mean square displacement and momentum, thereby assuring the mathematical property of differentiability of the these physically observable quantities.

Non-Markovian entanglement dynamics of noisy continuous-variable quantum channels

International Nuclear Information System (INIS)

An, J.-H.; Zhang, W.-M.

2007-01-01

We investigate the entanglement dynamics of continuous-variable quantum channels in terms of an entangled squeezed state of two cavity fields in a general non-Markovian environment. Using the Feynman-Vernon influence functional theory in the coherent-state representation, we derive an exact master equation with time-dependent coefficients reflecting the non-Markovian influence of the environment. The influence of environments with different spectral densities, e.g., Ohmic, sub-Ohmic, and super-Ohmic, is numerically studied. The non-Markovian process shows its remarkable influence on the entanglement dynamics due to the sensitive time dependence of the dissipation and noise functions within the typical time scale of the environment. The Ohmic environment shows a weak dissipation-noise effect on the entanglement dynamics, while the sub-Ohmic and super-Ohmic environments induce much more severe noise. In particular, the memory of the system interacting with the environment contributes a strong decoherence effect to the entanglement dynamics in the super-Ohmic case

Closed hierarchy of correlations in Markovian open quantum systems

International Nuclear Information System (INIS)

Žunkovič, Bojan

2014-01-01

We study the Lindblad master equation in the space of operators and provide simple criteria for closeness of the hierarchy of equations for correlations. We separately consider the time evolution of closed and open systems and show that open systems satisfying the closeness conditions are not necessarily of Gaussian type. In addition, we show that dissipation can induce the closeness of the hierarchy of correlations in interacting quantum systems. As an example we study an interacting optomechanical model, the Fermi–Hubbard model, and the Rabi model, all coupled to a fine-tuned Markovian environment and obtain exact analytic expressions for the time evolution of two-point correlations. (paper)

Joint probability distributions for a class of non-Markovian processes.

Science.gov (United States)

Baule, A; Friedrich, R

2005-02-01

We consider joint probability distributions for the class of coupled Langevin equations introduced by Fogedby [H. C. Fogedby, Phys. Rev. E 50, 1657 (1994)]. We generalize well-known results for the single-time probability distributions to the case of N -time joint probability distributions. It is shown that these probability distribution functions can be obtained by an integral transform from distributions of a Markovian process. The integral kernel obeys a partial differential equation with fractional time derivatives reflecting the non-Markovian character of the process.

Non-Markovianity in the optimal control of an open quantum system described by hierarchical equations of motion

Science.gov (United States)

Mangaud, E.; Puthumpally-Joseph, R.; Sugny, D.; Meier, C.; Atabek, O.; Desouter-Lecomte, M.

2018-04-01

Optimal control theory is implemented with fully converged hierarchical equations of motion (HEOM) describing the time evolution of an open system density matrix strongly coupled to the bath in a spin-boson model. The populations of the two-level sub-system are taken as control objectives; namely, their revivals or exchange when switching off the field. We, in parallel, analyze how the optimal electric field consequently modifies the information back flow from the environment through different non-Markovian witnesses. Although the control field has a dipole interaction with the central sub-system only, its indirect influence on the bath collective mode dynamics is probed through HEOM auxiliary matrices, revealing a strong correlation between control and dissipation during a non-Markovian process. A heterojunction is taken as an illustrative example for modeling in a realistic way the two-level sub-system parameters and its spectral density function leading to a non-perturbative strong coupling regime with the bath. Although, due to strong system-bath couplings, control performances remain rather modest, the most important result is a noticeable increase of the non-Markovian bath response induced by the optimally driven processes.

Femtosecond Non-Markovian Optical Dynamics in Solution

NARCIS (Netherlands)

Nibbering, Erik T.J.; Wiersma, Douwe A.; Duppen, Koos

1991-01-01

Femtosecond photon-echo experiments on sodium resorufin in dimethylsulfoxide at room temperature show that optical dephasing in solution is of non-Markovian character. A single Gauss-Markov stochastic modulation process is used to interpret both the femtosecond light-scattering results and the

Individual based and mean-field modeling of direct aggregation

KAUST Repository

Burger, Martin

2013-10-01

We introduce two models of biological aggregation, based on randomly moving particles with individual stochasticity depending on the perceived average population density in their neighborhood. In the firstorder model the location of each individual is subject to a density-dependent random walk, while in the second-order model the density-dependent random walk acts on the velocity variable, together with a density-dependent damping term. The main novelty of our models is that we do not assume any explicit aggregative force acting on the individuals; instead, aggregation is obtained exclusively by reducing the individual stochasticity in response to higher perceived density. We formally derive the corresponding mean-field limits, leading to nonlocal degenerate diffusions. Then, we carry out the mathematical analysis of the first-order model, in particular, we prove the existence of weak solutions and show that it allows for measure-valued steady states. We also perform linear stability analysis and identify conditions for pattern formation. Moreover, we discuss the role of the nonlocality for well-posedness of the first-order model. Finally, we present results of numerical simulations for both the first- and second-order model on the individual-based and continuum levels of description. 2012 Elsevier B.V. All rights reserved.

Individual based and mean-field modeling of direct aggregation

KAUST Repository

Burger, Martin; Haskovec, Jan; Wolfram, Marie-Therese

2013-01-01

We introduce two models of biological aggregation, based on randomly moving particles with individual stochasticity depending on the perceived average population density in their neighborhood. In the firstorder model the location of each individual is subject to a density-dependent random walk, while in the second-order model the density-dependent random walk acts on the velocity variable, together with a density-dependent damping term. The main novelty of our models is that we do not assume any explicit aggregative force acting on the individuals; instead, aggregation is obtained exclusively by reducing the individual stochasticity in response to higher perceived density. We formally derive the corresponding mean-field limits, leading to nonlocal degenerate diffusions. Then, we carry out the mathematical analysis of the first-order model, in particular, we prove the existence of weak solutions and show that it allows for measure-valued steady states. We also perform linear stability analysis and identify conditions for pattern formation. Moreover, we discuss the role of the nonlocality for well-posedness of the first-order model. Finally, we present results of numerical simulations for both the first- and second-order model on the individual-based and continuum levels of description. 2012 Elsevier B.V. All rights reserved.

Individual-based modelling and control of bovine brucellosis

Science.gov (United States)

Nepomuceno, Erivelton G.; Barbosa, Alípio M.; Silva, Marcos X.; Perc, Matjaž

2018-05-01

We present a theoretical approach to control bovine brucellosis. We have used individual-based modelling, which is a network-type alternative to compartmental models. Our model thus considers heterogeneous populations, and spatial aspects such as migration among herds and control actions described as pulse interventions are also easily implemented. We show that individual-based modelling reproduces the mean field behaviour of an equivalent compartmental model. Details of this process, as well as flowcharts, are provided to facilitate the reproduction of the presented results. We further investigate three numerical examples using real parameters of herds in the São Paulo state of Brazil, in scenarios which explore eradication, continuous and pulsed vaccination and meta-population effects. The obtained results are in good agreement with the expected behaviour of this disease, which ultimately showcases the effectiveness of our theory.

Individual-based modeling of ecological and evolutionary processes

Science.gov (United States)

DeAngelis, Donald L.; Mooij, Wolf M.

2005-01-01

Individual-based models (IBMs) allow the explicit inclusion of individual variation in greater detail than do classical differential-equation and difference-equation models. Inclusion of such variation is important for continued progress in ecological and evolutionary theory. We provide a conceptual basis for IBMs by describing five major types of individual variation in IBMs: spatial, ontogenetic, phenotypic, cognitive, and genetic. IBMs are now used in almost all subfields of ecology and evolutionary biology. We map those subfields and look more closely at selected key papers on fish recruitment, forest dynamics, sympatric speciation, metapopulation dynamics, maintenance of diversity, and species conservation. Theorists are currently divided on whether IBMs represent only a practical tool for extending classical theory to more complex situations, or whether individual-based theory represents a radically new research program. We feel that the tension between these two poles of thinking can be a source of creativity in ecology and evolutionary theory.

Solutions for a non-Markovian diffusion equation

International Nuclear Information System (INIS)

Lenzi, E.K.; Evangelista, L.R.; Lenzi, M.K.; Ribeiro, H.V.; Oliveira, E.C. de

2010-01-01

Solutions for a non-Markovian diffusion equation are investigated. For this equation, we consider a spatial and time dependent diffusion coefficient and the presence of an absorbent term. The solutions exhibit an anomalous behavior which may be related to the solutions of fractional diffusion equations and anomalous diffusion.

Multilevel Approximations of Markovian Jump Processes with Applications in Communication Networks

KAUST Repository

Vilanova, Pedro

2015-05-04

This thesis focuses on the development and analysis of efficient simulation and inference techniques for Markovian pure jump processes with a view towards applications in dense communication networks. These techniques are especially relevant for modeling networks of smart devices —tiny, abundant microprocessors with integrated sensors and wireless communication abilities— that form highly complex and diverse communication networks. During 2010, the number of devices connected to the Internet exceeded the number of people on Earth: over 12.5 billion devices. By 2015, Cisco’s Internet Business Solutions Group predicts that this number will exceed 25 billion. The first part of this work proposes novel numerical methods to estimate, in an efficient and accurate way, observables from realizations of Markovian jump processes. In particular, hybrid Monte Carlo type methods are developed that combine the exact and approximate simulation algorithms to exploit their respective advantages. These methods are tailored to keep a global computational error below a prescribed global error tolerance and within a given statistical confidence level. Indeed, the computational work of these methods is similar to the one of an exact method, but with a smaller constant. Finally, the methods are extended to systems with a disparity of time scales. The second part develops novel inference methods to estimate the parameters of Markovian pure jump process. First, an indirect inference approach is presented, which is based on upscaled representations and does not require sampling. This method is simpler than dealing directly with the likelihood of the process, which, in general, cannot be expressed in closed form and whose maximization requires computationally intensive sampling techniques. Second, a forward-reverse Monte Carlo Expectation-Maximization algorithm is provided to approximate a local maximum or saddle point of the likelihood function of the parameters given a set of

System–environment correlations and non-Markovian dynamics

International Nuclear Information System (INIS)

Pernice, A; Helm, J; Strunz, W T

2012-01-01

We determine the total state dynamics of a dephasing open quantum system using the standard environment of harmonic oscillators. Of particular interest are random unitary approaches to the same reduced dynamics and system–environment correlations in the full model. Concentrating on a model with an at times negative dephasing rate, the issue of ‘non-Markovianity’ will also be addressed. Crucially, given the quantum environment, the appearance of non-Markovian dynamics turns out to be accompanied by a loss of system–environment correlations. Depending on the initial purity of the qubit state, these system–environment correlations may be purely classical over the whole relevant time scale, or there may be intervals of genuine system–environment entanglement. In the latter case, we see no obvious relation between the build-up or decay of these quantum correlations and ‘non-Markovianity’. (paper)

Markovian Interpretations of Dual Retrieval Processes.

Science.gov (United States)

Gomes, C F A; Brainerd, C J; Nakamura, K; Reyna, V F

2014-04-01

A half-century ago, at the dawn of the all-or-none learning era, Estes showed that finite Markov chains supply a tractable, comprehensive framework for discrete-change data of the sort that he envisioned for shifts in conditioning states in stimulus sampling theory. Shortly thereafter, such data rapidly accumulated in many spheres of human learning and animal conditioning, and Estes' work stimulated vigorous development of Markov models to handle them. A key outcome was that the data of the workhorse paradigms of episodic memory, recognition and recall, proved to be one- and two-stage Markovian, respectively, to close approximations. Subsequently, Markov modeling of recognition and recall all but disappeared from the literature, but it is now reemerging in the wake of dual-process conceptions of episodic memory. In recall, in particular, Markov models are being used to measure two retrieval operations (direct access and reconstruction) and a slave familiarity operation. In the present paper, we develop this family of models and present the requisite machinery for fit evaluation and significance testing. Results are reviewed from selected experiments in which the recall models were used to understand dual memory processes.

Markovian Interpretations of Dual Retrieval Processes

Science.gov (United States)

Gomes, C. F. A.; Nakamura, K.; Reyna, V. F.

2013-01-01

A half-century ago, at the dawn of the all-or-none learning era, Estes showed that finite Markov chains supply a tractable, comprehensive framework for discrete-change data of the sort that he envisioned for shifts in conditioning states in stimulus sampling theory. Shortly thereafter, such data rapidly accumulated in many spheres of human learning and animal conditioning, and Estes’ work stimulated vigorous development of Markov models to handle them. A key outcome was that the data of the workhorse paradigms of episodic memory, recognition and recall, proved to be one- and two-stage Markovian, respectively, to close approximations. Subsequently, Markov modeling of recognition and recall all but disappeared from the literature, but it is now reemerging in the wake of dual-process conceptions of episodic memory. In recall, in particular, Markov models are being used to measure two retrieval operations (direct access and reconstruction) and a slave familiarity operation. In the present paper, we develop this family of models and present the requisite machinery for fit evaluation and significance testing. Results are reviewed from selected experiments in which the recall models were used to understand dual memory processes. PMID:24948840

Non-Markovian stochastic Schroedinger equations: Generalization to real-valued noise using quantum-measurement theory

International Nuclear Information System (INIS)

Gambetta, Jay; Wiseman, H.M.

2002-01-01

Do stochastic Schroedinger equations, also known as unravelings, have a physical interpretation? In the Markovian limit, where the system on average obeys a master equation, the answer is yes. Markovian stochastic Schroedinger equations generate quantum trajectories for the system state conditioned on continuously monitoring the bath. For a given master equation, there are many different unravelings, corresponding to different sorts of measurement on the bath. In this paper we address the non-Markovian case, and in particular the sort of stochastic Schroedinger equation introduced by Strunz, Diosi, and Gisin [Phys. Rev. Lett. 82, 1801 (1999)]. Using a quantum-measurement theory approach, we rederive their unraveling that involves complex-valued Gaussian noise. We also derive an unraveling involving real-valued Gaussian noise. We show that in the Markovian limit, these two unravelings correspond to heterodyne and homodyne detection, respectively. Although we use quantum-measurement theory to define these unravelings, we conclude that the stochastic evolution of the system state is not a true quantum trajectory, as the identity of the state through time is a fiction

Structure and sensitivity analysis of individual-based predator–prey models

International Nuclear Information System (INIS)

Imron, Muhammad Ali; Gergs, Andre; Berger, Uta

2012-01-01

The expensive computational cost of sensitivity analyses has hampered the use of these techniques for analysing individual-based models in ecology. A relatively cheap computational cost, referred to as the Morris method, was chosen to assess the relative effects of all parameters on the model’s outputs and to gain insights into predator–prey systems. Structure and results of the sensitivity analysis of the Sumatran tiger model – the Panthera Population Persistence (PPP) and the Notonecta foraging model (NFM) – were compared. Both models are based on a general predation cycle and designed to understand the mechanisms behind the predator–prey interaction being considered. However, the models differ significantly in their complexity and the details of the processes involved. In the sensitivity analysis, parameters that directly contribute to the number of prey items killed were found to be most influential. These were the growth rate of prey and the hunting radius of tigers in the PPP model as well as attack rate parameters and encounter distance of backswimmers in the NFM model. Analysis of distances in both of the models revealed further similarities in the sensitivity of the two individual-based models. The findings highlight the applicability and importance of sensitivity analyses in general, and screening design methods in particular, during early development of ecological individual-based models. Comparison of model structures and sensitivity analyses provides a first step for the derivation of general rules in the design of predator–prey models for both practical conservation and conceptual understanding. - Highlights: ► Structure of predation processes is similar in tiger and backswimmer model. ► The two individual-based models (IBM) differ in space formulations. ► In both models foraging distance is among the sensitive parameters. ► Morris method is applicable for the sensitivity analysis even of complex IBMs.

Synchronization of Markovian jumping stochastic complex networks with distributed time delays and probabilistic interval discrete time-varying delays

International Nuclear Information System (INIS)

Li Hongjie; Yue Dong

2010-01-01

The paper investigates the synchronization stability problem for a class of complex dynamical networks with Markovian jumping parameters and mixed time delays. The complex networks consist of m modes and the networks switch from one mode to another according to a Markovian chain with known transition probability. The mixed time delays are composed of discrete and distributed delays, the discrete time delay is assumed to be random and its probability distribution is known a priori. In terms of the probability distribution of the delays, the new type of system model with probability-distribution-dependent parameter matrices is proposed. Based on the stochastic analysis techniques and the properties of the Kronecker product, delay-dependent synchronization stability criteria in the mean square are derived in the form of linear matrix inequalities which can be readily solved by using the LMI toolbox in MATLAB, the solvability of derived conditions depends on not only the size of the delay, but also the probability of the delay-taking values in some intervals. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the proposed method.

MR brain scan tissues and structures segmentation: local cooperative Markovian agents and Bayesian formulation

International Nuclear Information System (INIS)

Scherrer, B.

2008-12-01

Accurate magnetic resonance brain scan segmentation is critical in a number of clinical and neuroscience applications. This task is challenging due to artifacts, low contrast between tissues and inter-individual variability that inhibit the introduction of a priori knowledge. In this thesis, we propose a new MR brain scan segmentation approach. Unique features of this approach include (1) the coupling of tissue segmentation, structure segmentation and prior knowledge construction, and (2) the consideration of local image properties. Locality is modeled through a multi-agent framework: agents are distributed into the volume and perform a local Markovian segmentation. As an initial approach (LOCUS, Local Cooperative Unified Segmentation), intuitive cooperation and coupling mechanisms are proposed to ensure the consistency of local models. Structures are segmented via the introduction of spatial localization constraints based on fuzzy spatial relations between structures. In a second approach, (LOCUS-B, LOCUS in a Bayesian framework) we consider the introduction of a statistical atlas to describe structures. The problem is reformulated in a Bayesian framework, allowing a statistical formalization of coupling and cooperation. Tissue segmentation, local model regularization, structure segmentation and local affine atlas registration are then coupled in an EM framework and mutually improve. The evaluation on simulated and real images shows good results, and in particular, a robustness to non-uniformity and noise with low computational cost. Local distributed and cooperative MRF models then appear as a powerful and promising approach for medical image segmentation. (author)

Two-dimensional spectroscopy for harmonic vibrational modes with nonlinear system-bath interactions. II. Gaussian-Markovian case

NARCIS (Netherlands)

Tanimura, Y; Steffen, T

2000-01-01

The relaxation processes in a quantum system nonlinearly coupled to a harmonic Gaussian-Markovian heat bath are investigated by the quantum Fokker-Planck equation in the hierarchy form. This model describes frequency fluctuations in the quantum system with an arbitrary correlation time and thus

Dynamics of interacting qubits coupled to a common bath: Non-Markovian quantum-state-diffusion approach

International Nuclear Information System (INIS)

Zhao Xinyu; Jing Jun; Corn, Brittany; Yu Ting

2011-01-01

Non-Markovian dynamics is studied for two interacting qubits strongly coupled to a dissipative bosonic environment. We derive a non-Markovian quantum-state-diffusion (QSD) equation for the coupled two-qubit system without any approximations, and in particular, without the Markov approximation. As an application and illustration of our derived time-local QSD equation, we investigate the temporal behavior of quantum coherence dynamics. In particular, we find a strongly non-Markovian regime where entanglement generation is significantly modulated by the environmental memory. Additionally, we study residual entanglement in the steady state by analyzing the steady-state solution of the QSD equation. Finally, we discuss an approximate QSD equation.

Integrating Biodiversity into Biosphere-Atmosphere Interactions Using Individual-Based Models (IBM)

Science.gov (United States)

Wang, B.; Shugart, H. H., Jr.; Lerdau, M.

2017-12-01

A key component regulating complex, nonlinear, and dynamic biosphere-atmosphere interactions is the inherent diversity of biological systems. The model frameworks currently widely used, i.e., Plant Functional Type models) do not even begin to capture the metabolic and taxonomic diversity found in many terrestrial systems. We propose that a transition from PFT-based to individual-based modeling approaches (hereafter referred to as IBM) is essential for integrating biodiversity into research on biosphere-atmosphere interactions. The proposal emerges from our studying the interactions of forests with atmospheric processes in the context of climate change using an individual-based forest volatile organic compounds model, UVAFME-VOC. This individual-based model can explicitly simulate VOC emissions based on an explicit modelling of forest dynamics by computing the growth, death, and regeneration of each individual tree of different species and their competition for light, moisture, and nutrient, from which system-level VOC emissions are simulated by explicitly computing and summing up each individual's emissions. We found that elevated O3 significantly altered the forest dynamics by favoring species that are O3-resistant, which, meanwhile, are producers of isoprene. Such compositional changes, on the one hand, resulted in unsuppressed forest productivity and carbon stock because of the compensation by O3-resistant species. On the other hand, with more isoprene produced arising from increased producers, a possible positive feedback loop between tropospheric O3 and forest thereby emerged. We also found that climate warming will not always stimulate isoprene emissions because warming simultaneously reduces isoprene emissions by causing a decline in the abundance of isoprene-emitting species. These results suggest that species diversity is of great significance and that individual-based modelling strategies should be applied in studying biosphere-atmosphere interactions.

Counting statistics of non-markovian quantum stochastic processes

DEFF Research Database (Denmark)

Flindt, Christian; Novotny, T.; Braggio, A.

2008-01-01

We derive a general expression for the cumulant generating function (CGF) of non-Markovian quantum stochastic transport processes. The long-time limit of the CGF is determined by a single dominating pole of the resolvent of the memory kernel from which we extract the zero-frequency cumulants...

Non-Markovian dynamics, decoherence and entanglement in dissipative quantum systems with applications to quantum information theory of continuous variable systems; Nicht-Markovsche Dynamik, Dekohaerenz und Verschraenkung in dissipativen Quantensystemen mit Anwendung in der Quanteninformationstheorie von Systemen kontinuierlicher Variablen

Energy Technology Data Exchange (ETDEWEB)

Hoerhammer, C.

2007-11-26

In this thesis, non-Markovian dynamics, decoherence and entanglement in dissipative quantum systems are studied. In particular, applications to quantum information theory of continuous variable systems are considered. The non-Markovian dynamics are described by the Hu-Paz-Zhang master equation of quantum Brownian motion. In this context the focus is on non-Markovian effects on decoherence and separability time scales of various single- mode and two-mode continuous variable states. It is verified that moderate non-Markovian influences slow down the decay of interference fringes and quantum correlations, while strong non-Markovian effects resulting from an out-of-resonance bath can even accelerate the loss of coherence, compared to predictions of Markovian approximations. Qualitatively different scenarios including exponential, Gaussian or algebraic decay of the decoherence function are analyzed. It is shown that partial recurrence of coherence can occur in case of non-Lindblad-type dynamics. The time evolution of quantum correlations of entangled two-mode continuous variable states is examined in single-reservoir and two-reservoir models, representing noisy correlated or uncorrelated non-Markovian quantum channels. For this purpose the model of quantum Brownian motion is extended. Various separability criteria for Gaussian and non-Gaussian continuous variable systems are applied. In both types of reservoir models moderate non-Markovian effects prolong the separability time scales. However, in these models the properties of the stationary state may differ. In the two-reservoir model the initial entanglement is completely lost and both modes are finally uncorrelated. In a common reservoir both modes interact indirectly via the coupling to the same bath variables. Therefore, new quantum correlations may emerge between the two modes. Below a critical bath temperature entanglement is preserved even in the steady state. A separability criterion is derived, which depends

H∞ Filtering for Networked Markovian Jump Systems with Multiple Stochastic Communication Delays

Directory of Open Access Journals (Sweden)

Hui Dong

2015-01-01

Full Text Available This paper is concerned with the H∞ filtering for a class of networked Markovian jump systems with multiple communication delays. Due to the existence of communication constraints, the measurement signal cannot arrive at the filter completely on time, and the stochastic communication delays are considered in the filter design. Firstly, a set of stochastic variables is introduced to model the occurrence probabilities of the delays. Then based on the stochastic system approach, a sufficient condition is obtained such that the filtering error system is stable in the mean-square sense and with a prescribed H∞ disturbance attenuation level. The optimal filter gain parameters can be determined by solving a convex optimization problem. Finally, a simulation example is given to show the effectiveness of the proposed filter design method.

Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry

Directory of Open Access Journals (Sweden)

Míriam R. García

2018-01-01

Full Text Available A realistic description of the variability in bacterial growth and division is critical to produce reliable predictions of safety risks along the food chain. Individual-based modeling of bacteria provides the theoretical framework to deal with this variability, but it requires information about the individual behavior of bacteria inside populations. In this work, we overcome this problem by estimating the individual behavior of bacteria from population statistics obtained with flow cytometry. For this objective, a stochastic individual-based modeling framework is defined based on standard assumptions during division and exponential growth. The unknown single-cell parameters required for running the individual-based modeling simulations, such as cell size growth rate, are estimated from the flow cytometry data. Instead of using directly the individual-based model, we make use of a modified Fokker-Plank equation. This only equation simulates the population statistics in function of the unknown single-cell parameters. We test the validity of the approach by modeling the growth and division of Pediococcus acidilactici within the exponential phase. Estimations reveal the statistics of cell growth and division using only data from flow cytometry at a given time. From the relationship between the mother and daughter volumes, we also predict that P. acidilactici divide into two successive parallel planes.

A standard protocol for describing individual-based and agent-based models

Science.gov (United States)

Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Muller, Birgit; Pe'er, Guy; Piou, Cyril; Railsback, Steven F.; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Ruger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L.

2006-01-01

Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

On the Moments and the Distribution of Aggregate Discounted Claims in a Markovian Environment

Directory of Open Access Journals (Sweden)

Shuanming Li

2018-05-01

Full Text Available This paper studies the moments and the distribution of the aggregate discounted claims (ADCs in a Markovian environment, where the claim arrivals, claim amounts, and forces of interest (for discounting are influenced by an underlying Markov process. Specifically, we assume that claims occur according to a Markovian arrival process (MAP. The paper shows that the vector of joint Laplace transforms of the ADC occurring in each state of the environment process by any specific time satisfies a matrix-form first-order partial differential equation, through which a recursive formula is derived for the moments of the ADC occurring in certain states (a subset. We also study two types of covariances of the ADC occurring in any two subsets of the state space and with two different time lengths. The distribution of the ADC occurring in certain states by any specific time is also investigated. Numerical results are also presented for a two-state Markov-modulated model case.

An Individual-based Probabilistic Model for Fish Stock Simulation

Directory of Open Access Journals (Sweden)

Federico Buti

2010-08-01

Full Text Available We define an individual-based probabilistic model of a sole (Solea solea behaviour. The individual model is given in terms of an Extended Probabilistic Discrete Timed Automaton (EPDTA, a new formalism that is introduced in the paper and that is shown to be interpretable as a Markov decision process. A given EPDTA model can be probabilistically model-checked by giving a suitable translation into syntax accepted by existing model-checkers. In order to simulate the dynamics of a given population of soles in different environmental scenarios, an agent-based simulation environment is defined in which each agent implements the behaviour of the given EPDTA model. By varying the probabilities and the characteristic functions embedded in the EPDTA model it is possible to represent different scenarios and to tune the model itself by comparing the results of the simulations with real data about the sole stock in the North Adriatic sea, available from the recent project SoleMon. The simulator is presented and made available for its adaptation to other species.

Simulating individual-based models of epidemics in hierarchical networks

NARCIS (Netherlands)

Quax, R.; Bader, D.A.; Sloot, P.M.A.

2009-01-01

Current mathematical modeling methods for the spreading of infectious diseases are too simplified and do not scale well. We present the Simulator of Epidemic Evolution in Complex Networks (SEECN), an efficient simulator of detailed individual-based models by parameterizing separate dynamics

Exact master equations for the non-Markovian decay of a qubit

International Nuclear Information System (INIS)

Vacchini, Bassano; Breuer, Heinz-Peter

2010-01-01

Exact master equations describing the decay of a two-state system into a structured reservoir are constructed. By employing the exact solution for the model, analytical expressions are determined for the memory kernel of the Nakajima-Zwanzig master equation and for the generator of the corresponding time-convolutionless master equation. This approach allows an explicit comparison of the convergence behavior of the corresponding perturbation expansions. Moreover, the structure of widely used phenomenological master equations with a memory kernel may be incompatible with a nonperturbative treatment of the underlying microscopic model. Several physical implications of the results on the microscopic analysis and the phenomenological modeling of non-Markovian quantum dynamics of open systems are discussed.

Developing an agent-based model on how different individuals solve complex problems

Directory of Open Access Journals (Sweden)

Ipek Bozkurt

2015-01-01

Full Text Available Purpose: Research that focuses on the emotional, mental, behavioral and cognitive capabilities of individuals has been abundant within disciplines such as psychology, sociology, and anthropology, among others. However, when facing complex problems, a new perspective to understand individuals is necessary. The main purpose of this paper is to develop an agent-based model and simulation to gain understanding on the decision-making and problem-solving abilities of individuals. Design/Methodology/approach: The micro-level analysis modeling and simulation paradigm Agent-Based Modeling Through the use of Agent-Based Modeling, insight is gained on how different individuals with different profiles deal with complex problems. Using previous literature from different bodies of knowledge, established theories and certain assumptions as input parameters, a model is built and executed through a computer simulation. Findings: The results indicate that individuals with certain profiles have better capabilities to deal with complex problems. Moderate profiles could solve the entire complex problem, whereas profiles within extreme conditions could not. This indicates that having a strong predisposition is not the ideal way when approaching complex problems, and there should always be a component from the other perspective. The probability that an individual may use these capabilities provided by the opposite predisposition provides to be a useful option. Originality/value: The originality of the present research stems from how individuals are profiled, and the model and simulation that is built to understand how they solve complex problems. The development of the agent-based model adds value to the existing body of knowledge within both social sciences, and modeling and simulation.

INDIVIDUAL-BASED MODELS: POWERFUL OR POWER STRUGGLE?

Science.gov (United States)

Willem, L; Stijven, S; Hens, N; Vladislavleva, E; Broeckhove, J; Beutels, P

2015-01-01

Individual-based models (IBMs) offer endless possibilities to explore various research questions but come with high model complexity and computational burden. Large-scale IBMs have become feasible but the novel hardware architectures require adapted software. The increased model complexity also requires systematic exploration to gain thorough system understanding. We elaborate on the development of IBMs for vaccine-preventable infectious diseases and model exploration with active learning. Investment in IBM simulator code can lead to significant runtime reductions. We found large performance differences due to data locality. Sorting the population once, reduced simulation time by a factor two. Storing person attributes separately instead of using person objects also seemed more efficient. Next, we improved model performance up to 70% by structuring potential contacts based on health status before processing disease transmission. The active learning approach we present is based on iterative surrogate modelling and model-guided experimentation. Symbolic regression is used for nonlinear response surface modelling with automatic feature selection. We illustrate our approach using an IBM for influenza vaccination. After optimizing the parameter spade, we observed an inverse relationship between vaccination coverage and the clinical attack rate reinforced by herd immunity. These insights can be used to focus and optimise research activities, and to reduce both dimensionality and decision uncertainty.

Non-markovian effects in semiconductor cavity QED: Role of phonon-mediated processes

DEFF Research Database (Denmark)

Nielsen, Per Kær; Nielsen, Torben Roland; Lodahl, Peter

We show theoretically that the non-Markovian nature of the carrier-phonon interaction influences the dynamical properties of a semiconductor cavity QED system considerably, leading to asymmetries with respect to detuning in carrier lifetimes. This pronounced phonon effect originates from the pola......We show theoretically that the non-Markovian nature of the carrier-phonon interaction influences the dynamical properties of a semiconductor cavity QED system considerably, leading to asymmetries with respect to detuning in carrier lifetimes. This pronounced phonon effect originates from...... the polaritonic quasi-particle nature of the carrier-photon system interacting with the phonon reservoir....

The quantum entropic uncertainty relation and entanglement witness in the two-atom system coupling with the non-Markovian environments

International Nuclear Information System (INIS)

Zou, Hong-Mei; Fang, Mao-Fa; Yang, Bai-Yuan; Guo, You-Neng; He, Wei; Zhang, Shi-Yang

2014-01-01

The quantum entropic uncertainty relation and entanglement witness in the two-atom system coupling with the non-Markovian environments are studied using the time-convolutionless master-equation approach. The influence of the non-Markovian effect and detuning on the lower bound of the quantum entropic uncertainty relation and entanglement witness is discussed in detail. The results show that, only if the two non-Markovian reservoirs are identical, increasing detuning and non-Markovian effect can reduce the lower bound of the entropic uncertainty relation, lengthen the time region during which the entanglement can be witnessed, and effectively protect the entanglement region witnessed by the lower bound of the entropic uncertainty relation. The results can be applied in quantum measurement, quantum cryptography tasks and quantum information processing. (paper)

Non-Markovian Investigation of an Autonomous Quantum Heat Engine

Science.gov (United States)

Goyal, Ketan

A systematic study of a quantum heat engine is presented in this thesis. In particular, we study heat conduction through a two-two level composite system, which is then connected to a photon cavity to extract work, forming an autonomous quantum heat engine. The question as to what extent quantum effects such as quantum coherence and correlations impact thermodynamic properties of such a system is addressed. The investigated heat engine has been previously studied using the popular Born-Markovian quantum master equation under weak internal coupling approximation. However, we show that the used approach is quite limited in addressing such problems as it is incapable of correctly accounting for the quantum effects. By using a non-Markovian approach involving hierarchical equations of motion, we show that quantum coherence and correlations between system and environments play a significant role in energy transfer processes of heat conduction and work.

Non-Markovian quantum Brownian motion in one dimension in electric fields

Science.gov (United States)

Shen, H. Z.; Su, S. L.; Zhou, Y. H.; Yi, X. X.

2018-04-01

Quantum Brownian motion is the random motion of quantum particles suspended in a field (or an effective field) resulting from their collision with fast-moving modes in the field. It provides us with a fundamental model to understand various physical features concerning open systems in chemistry, condensed-matter physics, biophysics, and optomechanics. In this paper, without either the Born-Markovian or rotating-wave approximation, we derive a master equation for a charged-Brownian particle in one dimension coupled with a thermal reservoir in electric fields. The effect of the reservoir and the electric fields is manifested as time-dependent coefficients and coherent terms, respectively, in the master equation. The two-photon correlation between the Brownian particle and the reservoir can induce nontrivial squeezing dynamics to the particle. We derive a current equation including the source from the driving fields, transient current from the system flowing into the environment, and the two-photon current caused by the non-rotating-wave term. The presented results then are compared with that given by the rotating-wave approximation in the weak-coupling limit, and these results are extended to a more general quantum network involving an arbitrary number of coupled-Brownian particles. The presented formalism might open a way to better understand exactly the non-Markovian quantum network.

Non-Markovian reservoir-dependent squeezing

International Nuclear Information System (INIS)

Paavola, J

2010-01-01

The squeezing dynamics of a damped harmonic oscillator are studied for different types of environment without making the Markovian approximation. The squeezing dynamics of a coherent state depend on the reservoir spectrum in a unique way that can, in the weak coupling approximation, be analysed analytically. Comparison of squeezing dynamics for ohmic, sub-ohmic and super-ohmic environments is done, showing a clear connection between the squeezing-non-squeezing oscillations and reservoir structure. Understanding the effects occurring due to structured reservoirs is important both from a purely theoretical point of view and in connection with evolving experimental techniques and future quantum computing applications.

Phonon-induced dissipation and decoherence in solid-state quantum devices: Markovian versus non-Markovian treatments

Science.gov (United States)

Iotti, Rita Claudia; Rossi, Fausto

2017-12-01

Microscopic modeling of electronic phase coherence versus energy dissipation plays a crucial role in the design and optimization of new-generation electronic quantum nanodevices, like quantum-cascade light sources and quantum logic gates; in this context, non-Markovian density-matrix approaches are widely used simulation strategies. Here we show that such methods, along with valuable virtues, in some circumstances may exhibit potential limitations that need to be taken into account for a reliable description of quantum materials and related devices. More specifically, extending the analysis recently proposed in [EPL 112, 67005 (2015)] to high temperatures and degenerate conditions, we show that the usual mean-field treatment - employed to derive quantum-kinetic equations - in some cases may lead to anomalous results, characterized by decoherence suppression and positivity violations. By means of a simple two-level model, we show that such unexpected behaviors may affect zero-dimensional electronic systems coupled to dispersionless phonon modes, while such anomalies are expected to play a negligible role in nanosystems with higher dimensionality; these limitations are found to be significant in the low-density and low-temperature limit, while in the degenerate and/or finite-temperature regime - typical of many state-of-the-art quantum devices - their impact is strongly reduced.

Stochastic Wilson–Cowan models of neuronal network dynamics with memory and delay

International Nuclear Information System (INIS)

Goychuk, Igor; Goychuk, Andriy

2015-01-01

We consider a simple Markovian class of the stochastic Wilson–Cowan type models of neuronal network dynamics, which incorporates stochastic delay caused by the existence of a refractory period of neurons. From the point of view of the dynamics of the individual elements, we are dealing with a network of non-Markovian stochastic two-state oscillators with memory, which are coupled globally in a mean-field fashion. This interrelation of a higher-dimensional Markovian and lower-dimensional non-Markovian dynamics is discussed in its relevance to the general problem of the network dynamics of complex elements possessing memory. The simplest model of this class is provided by a three-state Markovian neuron with one refractory state, which causes firing delay with an exponentially decaying memory within the two-state reduced model. This basic model is used to study critical avalanche dynamics (the noise sustained criticality) in a balanced feedforward network consisting of the excitatory and inhibitory neurons. Such avalanches emerge due to the network size dependent noise (mesoscopic noise). Numerical simulations reveal an intermediate power law in the distribution of avalanche sizes with the critical exponent around −1.16. We show that this power law is robust upon a variation of the refractory time over several orders of magnitude. However, the avalanche time distribution is biexponential. It does not reflect any genuine power law dependence. (paper)

Non-Markovian quantum processes: Complete framework and efficient characterization

Science.gov (United States)

Pollock, Felix A.; Rodríguez-Rosario, César; Frauenheim, Thomas; Paternostro, Mauro; Modi, Kavan

2018-01-01

Currently, there is no systematic way to describe a quantum process with memory solely in terms of experimentally accessible quantities. However, recent technological advances mean we have control over systems at scales where memory effects are non-negligible. The lack of such an operational description has hindered advances in understanding physical, chemical, and biological processes, where often unjustified theoretical assumptions are made to render a dynamical description tractable. This has led to theories plagued with unphysical results and no consensus on what a quantum Markov (memoryless) process is. Here, we develop a universal framework to characterize arbitrary non-Markovian quantum processes. We show how a multitime non-Markovian process can be reconstructed experimentally, and that it has a natural representation as a many-body quantum state, where temporal correlations are mapped to spatial ones. Moreover, this state is expected to have an efficient matrix-product-operator form in many cases. Our framework constitutes a systematic tool for the effective description of memory-bearing open-system evolutions.

Exponential Synchronization for Stochastic Neural Networks with Mixed Time Delays and Markovian Jump Parameters via Sampled Data

Directory of Open Access Journals (Sweden)

Yingwei Li

2014-01-01

Full Text Available The exponential synchronization issue for stochastic neural networks (SNNs with mixed time delays and Markovian jump parameters using sampled-data controller is investigated. Based on a novel Lyapunov-Krasovskii functional, stochastic analysis theory, and linear matrix inequality (LMI approach, we derived some novel sufficient conditions that guarantee that the master systems exponentially synchronize with the slave systems. The design method of the desired sampled-data controller is also proposed. To reflect the most dynamical behaviors of the system, both Markovian jump parameters and stochastic disturbance are considered, where stochastic disturbances are given in the form of a Brownian motion. The results obtained in this paper are a little conservative comparing the previous results in the literature. Finally, two numerical examples are given to illustrate the effectiveness of the proposed methods.

Uhrig dynamical control of a three-level system via non-Markovian quantum state diffusion

International Nuclear Information System (INIS)

Shu, Wenchong; Zhao, Xinyu; Jing, Jun; Yu, Ting; Wu, Lian-Ao

2013-01-01

In this paper, we use the quantum state diffusion (QSD) equation to implement the Uhrig dynamical decoupling to a three-level quantum system coupled to a non-Markovian reservoir comprising of infinite numbers of degrees of freedom. For this purpose, we first reformulate the non-Markovian QSD to incorporate the effect of the external control fields. With this stochastic QSD approach, we demonstrate that an unknown state of the three-level quantum system can be universally protected against both coloured phase and amplitude noises when the control-pulse sequences and control operators are properly designed. The advantage of using non-Markovian QSD equations is that the control dynamics of open quantum systems can be treated exactly without using Trotter product formula and be efficiently simulated even when the environment is comprised of infinite numbers of degrees of freedom. We also show how the control efficacy depends on the environment memory time and the designed time points of applied control pulses. (paper)

Zero-crossing statistics for non-Markovian time series.

Science.gov (United States)

Nyberg, Markus; Lizana, Ludvig; Ambjörnsson, Tobias

2018-03-01

In applications spanning from image analysis and speech recognition to energy dissipation in turbulence and time-to failure of fatigued materials, researchers and engineers want to calculate how often a stochastic observable crosses a specific level, such as zero. At first glance this problem looks simple, but it is in fact theoretically very challenging, and therefore few exact results exist. One exception is the celebrated Rice formula that gives the mean number of zero crossings in a fixed time interval of a zero-mean Gaussian stationary process. In this study we use the so-called independent interval approximation to go beyond Rice's result and derive analytic expressions for all higher-order zero-crossing cumulants and moments. Our results agree well with simulations for the non-Markovian autoregressive model.

Zero-crossing statistics for non-Markovian time series

Science.gov (United States)

Nyberg, Markus; Lizana, Ludvig; Ambjörnsson, Tobias

2018-03-01

In applications spanning from image analysis and speech recognition to energy dissipation in turbulence and time-to failure of fatigued materials, researchers and engineers want to calculate how often a stochastic observable crosses a specific level, such as zero. At first glance this problem looks simple, but it is in fact theoretically very challenging, and therefore few exact results exist. One exception is the celebrated Rice formula that gives the mean number of zero crossings in a fixed time interval of a zero-mean Gaussian stationary process. In this study we use the so-called independent interval approximation to go beyond Rice's result and derive analytic expressions for all higher-order zero-crossing cumulants and moments. Our results agree well with simulations for the non-Markovian autoregressive model.

Sojourn time distributions in a Markovian G-queue with batch arrival and batch removal

Directory of Open Access Journals (Sweden)

Yang Woo Shin

1999-01-01

Full Text Available We consider a single server Markovian queue with two types of customers; positive and negative, where positive customers arrive in batches and arrivals of negative customers remove positive customers in batches. Only positive customers form a queue and negative customers just reduce the system congestion by removing positive ones upon their arrivals. We derive the LSTs of sojourn time distributions for a single server Markovian queue with positive customers and negative customers by using the first passage time arguments for Markov chains.

Optimizing Maintenance Planning in the Production Industry Using the Markovian Approach

Directory of Open Access Journals (Sweden)

B Kareem

2012-12-01

Full Text Available Maintenance is an essential activity in every manufacturing establishment, as manufacturing effectiveness counts on the functionality of production equipment and machinery in terms of their productivity and operational life. Maintenance cost minimization can be achieved by adopting an appropriate maintenance planning policy. This paper applies the Markovian approach to maintenance planning decision, thereby generating optimal maintenance policy from the identified alternatives over a specified period of time. Markov chains, transition matrices, decision processes, and dynamic programming models were formulated for the decision problem related to maintenance operations of a cable production company. Preventive and corrective maintenance data based on workloads and costs, were collected from the company and utilized in this study. The result showed variability in the choice of optimal maintenance policy that was adopted in the case study. Post optimality analysis of the process buttressed the claim. The proposed approach is promising for solving the maintenance scheduling decision problems of the company.

State estimation for discrete-time Markovian jumping neural networks with mixed mode-dependent delays

International Nuclear Information System (INIS)

Liu Yurong; Wang Zidong; Liu Xiaohui

2008-01-01

In this Letter, we investigate the state estimation problem for a new class of discrete-time neural networks with Markovian jumping parameters as well as mode-dependent mixed time-delays. The parameters of the discrete-time neural networks are subject to the switching from one mode to another at different times according to a Markov chain, and the mixed time-delays consist of both discrete and distributed delays that are dependent on the Markovian jumping mode. New techniques are developed to deal with the mixed time-delays in the discrete-time setting, and a novel Lyapunov-Krasovskii functional is put forward to reflect the mode-dependent time-delays. Sufficient conditions are established in terms of linear matrix inequalities (LMIs) that guarantee the existence of the state estimators. We show that both the existence conditions and the explicit expression of the desired estimator can be characterized in terms of the solution to an LMI. A numerical example is exploited to show the usefulness of the derived LMI-based conditions

Neural Network-Based Passive Filtering for Delayed Neutral-Type Semi-Markovian Jump Systems.

Science.gov (United States)

Shi, Peng; Li, Fanbiao; Wu, Ligang; Lim, Cheng-Chew

2017-09-01

This paper investigates the problem of exponential passive filtering for a class of stochastic neutral-type neural networks with both semi-Markovian jump parameters and mixed time delays. Our aim is to estimate the states by designing a Luenberger-type observer, such that the filter error dynamics are mean-square exponentially stable with an expected decay rate and an attenuation level. Sufficient conditions for the existence of passive filters are obtained, and a convex optimization algorithm for the filter design is given. In addition, a cone complementarity linearization procedure is employed to cast the nonconvex feasibility problem into a sequential minimization problem, which can be readily solved by the existing optimization techniques. Numerical examples are given to demonstrate the effectiveness of the proposed techniques.

Individual Subjective Initiative Merge Model Based on Cellular Automaton

Directory of Open Access Journals (Sweden)

Yin-Jie Xu

2013-01-01

Full Text Available The merge control models proposed for work zones are classified into two types (Hard Control Merge (HCM model and Soft Control Merge (SCM model according to their own control intensity and are compared with a new model, called Individual Subjective Initiative Merge (ISIM model, which is based on the linear lane-changing probability strategy in the merging area. The attention of this paper is paid to the positive impact of the individual subjective initiative for the whole traffic system. Three models (ISIM, HCM, and SCM are established and compared with each other by two order parameters, that is, system output and average vehicle travel time. Finally, numerical results show that both ISIM and SCM perform better than HCM. Compared with SCM, the output of ISIM is 20 vehicles per hour higher under the symmetric input condition and is more stable under the asymmetric input condition. Meanwhile, the average travel time of ISIM is 2000 time steps less under the oversaturated input condition.

Reliability importance analysis of Markovian systems at steady state using perturbation analysis

Energy Technology Data Exchange (ETDEWEB)

Phuc Do Van [Institut Charles Delaunay - FRE CNRS 2848, Systems Modeling and Dependability Group, Universite de technologie de Troyes, 12, rue Marie Curie, BP 2060-10010 Troyes cedex (France); Barros, Anne [Institut Charles Delaunay - FRE CNRS 2848, Systems Modeling and Dependability Group, Universite de technologie de Troyes, 12, rue Marie Curie, BP 2060-10010 Troyes cedex (France)], E-mail: anne.barros@utt.fr; Berenguer, Christophe [Institut Charles Delaunay - FRE CNRS 2848, Systems Modeling and Dependability Group, Universite de technologie de Troyes, 12, rue Marie Curie, BP 2060-10010 Troyes cedex (France)

2008-11-15

Sensitivity analysis has been primarily defined for static systems, i.e. systems described by combinatorial reliability models (fault or event trees). Several structural and probabilistic measures have been proposed to assess the components importance. For dynamic systems including inter-component and functional dependencies (cold spare, shared load, shared resources, etc.), and described by Markov models or, more generally, by discrete events dynamic systems models, the problem of sensitivity analysis remains widely open. In this paper, the perturbation method is used to estimate an importance factor, called multi-directional sensitivity measure, in the framework of Markovian systems. Some numerical examples are introduced to show why this method offers a promising tool for steady-state sensitivity analysis of Markov processes in reliability studies.

Reliability importance analysis of Markovian systems at steady state using perturbation analysis

International Nuclear Information System (INIS)

Phuc Do Van; Barros, Anne; Berenguer, Christophe

2008-01-01

Sensitivity analysis has been primarily defined for static systems, i.e. systems described by combinatorial reliability models (fault or event trees). Several structural and probabilistic measures have been proposed to assess the components importance. For dynamic systems including inter-component and functional dependencies (cold spare, shared load, shared resources, etc.), and described by Markov models or, more generally, by discrete events dynamic systems models, the problem of sensitivity analysis remains widely open. In this paper, the perturbation method is used to estimate an importance factor, called multi-directional sensitivity measure, in the framework of Markovian systems. Some numerical examples are introduced to show why this method offers a promising tool for steady-state sensitivity analysis of Markov processes in reliability studies

Markov Jump Linear Systems-Based Position Estimation for Lower Limb Exoskeletons

Directory of Open Access Journals (Sweden)

Samuel L. Nogueira

2014-01-01

Full Text Available In this paper, we deal with Markov Jump Linear Systems-based filtering applied to robotic rehabilitation. The angular positions of an impedance-controlled exoskeleton, designed to help stroke and spinal cord injured patients during walking rehabilitation, are estimated. Standard position estimate approaches adopt Kalman filters (KF to improve the performance of inertial measurement units (IMUs based on individual link configurations. Consequently, for a multi-body system, like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank are not taken into account in other link position estimation (e.g., the foot. In this paper, we propose a collective modeling of all inertial sensors attached to the exoskeleton, combining them in a Markovian estimation model in order to get the best information from each sensor. In order to demonstrate the effectiveness of our approach, simulation results regarding a set of human footsteps, with four IMUs and three encoders attached to the lower limb exoskeleton, are presented. A comparative study between the Markovian estimation system and the standard one is performed considering a wide range of parametric uncertainties.

Analysis of habitat-selection rules using an individual-based model

Science.gov (United States)

Steven F. Railsback; Bret C. Harvey

2002-01-01

Abstract - Despite their promise for simulating natural complexity,individual-based models (IBMs) are rarely used for ecological research or resource management. Few IBMs have been shown to reproduce realistic patterns of behavior by individual organisms.To test our IBM of stream salmonids and draw conclusions about foraging theory,we analyzed the IBM ’s ability to...

Tightness Entropic Uncertainty Relation in Quantum Markovian-Davies Environment

Science.gov (United States)

Zhang, Jun; Liu, Liang; Han, Yan

2018-05-01

In this paper, we investigate the tightness of entropic uncertainty relation in the absence (presence) of the quantum memory which the memory particle being weakly coupled to a decohering Davies-type Markovian environment. The results show that the tightness of the quantum uncertainty relation can be controlled by the energy relaxation time F, the dephasing time G and the rescaled temperature p, the perfect tightness can be arrived by dephasing and energy relaxation satisfying F = 2G and p = 1/2. In addition, the tightness of the memory-assisted entropic uncertainty relation and the entropic uncertainty relation can be influenced mainly by the purity. While in memory-assisted model, the purity and quantum correlation can also influence the tightness actively while the quantum entanglement can influence the tightness slightly.

Optical signatures of non-Markovian behavior in open quantum systems

DEFF Research Database (Denmark)

McCutcheon, Dara

2016-01-01

for the correlation functions, making only a second-order expansion in the system-environment coupling strength and invoking the Born approximation at a fixed initial time. The results are used to investigate a driven semiconductor quantum dot coupled to an acoustic phonon bath, where we find the non-Markovian nature...

Transport benchmarks for one-dimensional binary Markovian mixtures revisited

International Nuclear Information System (INIS)

Malvagi, F.

2013-01-01

The classic benchmarks for transport through a binary Markovian mixture are revisited to look at the probability distribution function of the chosen 'results': reflection, transmission and scalar flux. We argue that the knowledge of the ensemble averaged results is not sufficient for reliable predictions: a measure of the dispersion must also be obtained. An algorithm to estimate this dispersion is tested. (author)

Markovian Limit of a Spatio-Temporal Correlated Open Systems

Science.gov (United States)

Monnai, T.

Large fluctuation of Brownian particles is affected by the finiteness of the correlation length of the background noise field. Indeed a Fokker—Planck equation is derived in a Markovian limit of a spatio-temporal short correlated noise. Corresponding kinetic quantities are renormalized due to the spatio-temporal memory. We also investigate the case of open system by connecting a thermostat to the system.

Individual based model of slug population and spatial dynamics

NARCIS (Netherlands)

Choi, Y.H.; Bohan, D.A.; Potting, R.P.J.; Semenov, M.A.; Glen, D.M.

2006-01-01

The slug, Deroceras reticulatum, is one of the most important pests of agricultural and horticultural crops in UK and Europe. In this paper, a spatially explicit individual based model (IbM) is developed to study the dynamics of a population of D. reticulatum. The IbM establishes a virtual field

Non-Markovian dissipative quantum mechanics with stochastic trajectories

International Nuclear Information System (INIS)

Koch, Werner

2010-01-01

All fields of physics - be it nuclear, atomic and molecular, solid state, or optical - offer examples of systems which are strongly influenced by the environment of the actual system under investigation. The scope of what is called ''the environment'' may vary, i.e., how far from the system of interest an interaction between the two does persist. Typically, however, it is much larger than the open system itself. Hence, a fully quantum mechanical treatment of the combined system without approximations and without limitations of the type of system is currently out of reach. With the single assumption of the environment to consist of an internally thermalized set of infinitely many harmonic oscillators, the seminal work of Stockburger and Grabert [Chem. Phys., 268:249-256, 2001] introduced an open system description that captures the environmental influence by means of a stochastic driving of the reduced system. The resulting stochastic Liouville-von Neumann equation describes the full non-Markovian dynamics without explicit memory but instead accounts for it implicitly through the correlations of the complex-valued noise forces. The present thesis provides a first application of the Stockburger-Grabert stochastic Liouville-von Neumann equation to the computation of the dynamics of anharmonic, continuous open systems. In particular, it is demonstrated that trajectory based propagators allow for the construction of a numerically stable propagation scheme. With this approach it becomes possible to achieve the tremendous increase of the noise sample count necessary to stochastically converge the results when investigating such systems with continuous variables. After a test against available analytic results for the dissipative harmonic oscillator, the approach is subsequently applied to the analysis of two different realistic, physical systems. As a first example, the dynamics of a dissipative molecular oscillator is investigated. Long time propagation - until

Bulk-mediated surface diffusion: non-Markovian desorption and biased behaviour in an infinite system

International Nuclear Information System (INIS)

Revelli, Jorge A; Budde, Carlos E; Wio, Horacio S

2005-01-01

We analyse the dynamics of adsorbed molecules within the bulk-mediated surface diffusion framework. We consider that the particle's desorption mechanism is characterized by a non-Markovian process, while the particle's adsorption and its motion in the bulk are governed by Markovian dynamics, and include the effect of an external field in the form of a bias in the normal motion to the surface. We study this system for the diffusion of particles in a semi-infinite lattice, analysing the conditional probability to find the system on the reference absorptive plane as well as the surface dispersion as functions of time. The agreement between numerical and analytical asymptotic results is discussed

Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization.

Directory of Open Access Journals (Sweden)

Devaraj Jayachandran

Full Text Available 6-Mercaptopurine (6-MP is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN through enzymatic reaction involving thiopurine methyltransferase (TPMT. Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP's widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient's ability to metabolize the drug instead of the traditional standard-dose-for-all approach.

Model-Based Individualized Treatment of Chemotherapeutics: Bayesian Population Modeling and Dose Optimization

Science.gov (United States)

Jayachandran, Devaraj; Laínez-Aguirre, José; Rundell, Ann; Vik, Terry; Hannemann, Robert; Reklaitis, Gintaras; Ramkrishna, Doraiswami

2015-01-01

6-Mercaptopurine (6-MP) is one of the key drugs in the treatment of many pediatric cancers, auto immune diseases and inflammatory bowel disease. 6-MP is a prodrug, converted to an active metabolite 6-thioguanine nucleotide (6-TGN) through enzymatic reaction involving thiopurine methyltransferase (TPMT). Pharmacogenomic variation observed in the TPMT enzyme produces a significant variation in drug response among the patient population. Despite 6-MP’s widespread use and observed variation in treatment response, efforts at quantitative optimization of dose regimens for individual patients are limited. In addition, research efforts devoted on pharmacogenomics to predict clinical responses are proving far from ideal. In this work, we present a Bayesian population modeling approach to develop a pharmacological model for 6-MP metabolism in humans. In the face of scarcity of data in clinical settings, a global sensitivity analysis based model reduction approach is used to minimize the parameter space. For accurate estimation of sensitive parameters, robust optimal experimental design based on D-optimality criteria was exploited. With the patient-specific model, a model predictive control algorithm is used to optimize the dose scheduling with the objective of maintaining the 6-TGN concentration within its therapeutic window. More importantly, for the first time, we show how the incorporation of information from different levels of biological chain-of response (i.e. gene expression-enzyme phenotype-drug phenotype) plays a critical role in determining the uncertainty in predicting therapeutic target. The model and the control approach can be utilized in the clinical setting to individualize 6-MP dosing based on the patient’s ability to metabolize the drug instead of the traditional standard-dose-for-all approach. PMID:26226448

Optimal chemotherapy for leukemia: a model-based strategy for individualized treatment.

Directory of Open Access Journals (Sweden)

Devaraj Jayachandran

Full Text Available Acute Lymphoblastic Leukemia, commonly known as ALL, is a predominant form of cancer during childhood. With the advent of modern healthcare support, the 5-year survival rate has been impressive in the recent past. However, long-term ALL survivors embattle several treatment-related medical and socio-economic complications due to excessive and inordinate chemotherapy doses received during treatment. In this work, we present a model-based approach to personalize 6-Mercaptopurine (6-MP treatment for childhood ALL with a provision for incorporating the pharmacogenomic variations among patients. Semi-mechanistic mathematical models were developed and validated for i 6-MP metabolism, ii red blood cell mean corpuscular volume (MCV dynamics, a surrogate marker for treatment efficacy, and iii leukopenia, a major side-effect. With the constraint of getting limited data from clinics, a global sensitivity analysis based model reduction technique was employed to reduce the parameter space arising from semi-mechanistic models. The reduced, sensitive parameters were used to individualize the average patient model to a specific patient so as to minimize the model uncertainty. Models fit the data well and mimic diverse behavior observed among patients with minimum parameters. The model was validated with real patient data obtained from literature and Riley Hospital for Children in Indianapolis. Patient models were used to optimize the dose for an individual patient through nonlinear model predictive control. The implementation of our approach in clinical practice is realizable with routinely measured complete blood counts (CBC and a few additional metabolite measurements. The proposed approach promises to achieve model-based individualized treatment to a specific patient, as opposed to a standard-dose-for-all, and to prescribe an optimal dose for a desired outcome with minimum side-effects.

From BBGKY hierarchy to non-Markovian evolution equations

International Nuclear Information System (INIS)

Gerasimenko, V.I.; Shtyk, V.O.; Zagorodny, A.G.

2009-01-01

The problem of description of the evolution of the microscopic phase density and its generalizations is discussed. With this purpose, the sequence of marginal microscopic phase densities is introduced, and the appropriate BBGKY hierarchy for these microscopic distributions and their average values is formulated. The microscopic derivation of the generalized evolution equation for the average value of the microscopic phase density is given, and the non-Markovian generalization of the Fokker-Planck collision integral is proposed

Evolution of entropy in different types of non-Markovian three-level ...

Indian Academy of Sciences (India)

Home; Journals; Pramana – Journal of Physics; Volume 86; Issue 5. Evolution of entropy in different types of non-Markovian three-level systems: Single reservoir vs. two independent reservoirs. JAGHOURI HAKIMEH SARBISHAEI MOHSEN JAVIDAN KUROSH. Regular Volume 86 Issue 5 May 2016 pp 997-1008 ...

H2 Control for the Continuous-Time Markovian Jump Linear Uncertain Systems with Partly Known Transition Rates and Input Quantization

Directory of Open Access Journals (Sweden)

Xin-Gang Zhao

2013-01-01

Full Text Available For a class of continuous-time Markovian jump linear uncertain systems with partly known transition rates and input quantization, the H2 state-feedback control design is considered. The elements in the transition rates matrix include completely known, boundary known, and completely unknown ones. First, an H2 cost index for Markovian jump linear uncertain systems is introduced; then by introducing a new matrix inequality condition, sufficient conditions are formulated in terms of linear matrix inequalities (LMIs for the H2 control of the Markovian jump linear uncertain systems. Less conservativeness is achieved than the result obtained with the existing technique. Finally, a numerical example is given to verify the validity of the theoretical results.

Robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays

International Nuclear Information System (INIS)

Balasubramaniam, P.; Lakshmanan, S.; Manivannan, A.

2012-01-01

Highlights: ► Robust stability analysis for Markovian jumping interval neural networks is considered. ► Both linear fractional and interval uncertainties are considered. ► A new LKF is constructed with triple integral terms. ► MATLAB LMI control toolbox is used to validate theoretical results. ► Numerical examples are given to illustrate the effectiveness of the proposed method. - Abstract: This paper investigates robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays. The parameter uncertainties are assumed to be bounded in given compact sets. The delay is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. Based on the new Lyapunov–Krasovskii functional (LKF), some inequality techniques and stochastic stability theory, new delay-dependent stability criteria have been obtained in terms of linear matrix inequalities (LMIs). Finally, two numerical examples are given to illustrate the less conservative and effectiveness of our theoretical results.

Replacement policy in a system under shocks following a Markovian arrival process

International Nuclear Information System (INIS)

Montoro-Cazorla, Delia; Perez-Ocon, Rafael; Carmen Segovia, Maria del

2009-01-01

We present a system subject to shocks that arrive following a Markovian arrival process. The system is minimally repaired. It is replaced when a certain number of shocks arrive. A general model where the replacements are governed by a discrete phase-type distribution is studied. For this system, the Markov process governing the system is constructed, and the interarrival times between replacements and the number of replacements are calculated. A special case of this system is when it can stand a prefixed number of shocks. For this new system, the same performance measures are calculated. The systems are considered in transient and stationary regime

Replacement policy in a system under shocks following a Markovian arrival process

Energy Technology Data Exchange (ETDEWEB)

Montoro-Cazorla, Delia [Department of Statistics and Operational Research, University of Jaen (Spain); Perez-Ocon, Rafael [Department of Statistics and Operational Research, University of Granada, Granada (Spain)], E-mail: rperezo@ugr.es; Carmen Segovia, Maria del [Departamento de Estadistica e I.O., University of Granada, Granada (Spain)

2009-02-15

We present a system subject to shocks that arrive following a Markovian arrival process. The system is minimally repaired. It is replaced when a certain number of shocks arrive. A general model where the replacements are governed by a discrete phase-type distribution is studied. For this system, the Markov process governing the system is constructed, and the interarrival times between replacements and the number of replacements are calculated. A special case of this system is when it can stand a prefixed number of shocks. For this new system, the same performance measures are calculated. The systems are considered in transient and stationary regime.

Evolution of entropy in different types of non-Markovian three-level ...

Indian Academy of Sciences (India)

We solve the Nakajima–Zwanzig (NZ) non-Markovian master equation to study the dynamics of different types of three-level atomic systems interacting with bosonic Lorentzian reservoirs at zero temperature. Von Neumann entropy (S) is used to show the evolution of the degree of entanglement of the subsystems.

A community model of ciliate Tetrahymena and bacteria E. coli. Part 1: Individual-based models of Tetrahymena and E. coli populations

Energy Technology Data Exchange (ETDEWEB)

Jaworska, J.S.; Hallam, T.G.; Schultz, T.W. [Univ. of Tennessee, Knoxville, TN (United States)

1996-03-01

The dynamics of a microbial community consisting of a eucaryotic ciliate Tetrahymena pyriformis and procaryotic. Escherichia coli in a batch culture is explored by employing an individual-based approach. In this portion of the article, Part 1, population models are presented. Because both models are individual-based, models of individual organisms are developed prior to construction of the population models. The individual models use an energy budget method in which growth depends on energy gain from feeding and energy sinks such as maintenance and reproduction. These models are not limited by simplifying assumptions about constant yield, constant energy sinks and Monod growth kinetics as are traditional models of microbial organisms. Population models are generated from individual models by creating distinct individual types and assigning to each type the number of real individuals they represent. A population is a compilation of individual types that vary in a phase of cell cycle and physiological parameters such as filtering rate for ciliates and maximum anabolic rate for bacteria. An advantage of the developed models is that they realistically describe the growth of the individual cells feeding on resource which varies in density and composition. Part 2, the core of the project, integrates models into a dynamic microbial community and provides model analysis based upon available data.

Computing Rates of Small Molecule Diffusion Through Protein Channels Using Markovian Milestoning

Science.gov (United States)

Abrams, Cameron

2014-03-01

Measuring diffusion rates of ligands plays a key role in understanding the kinetic processes inside proteins. For example, although many molecular simulation studies have reported free energy barriers to infer rates for CO diffusion in myoglobin (Mb), they typically do not include direct calculation of diffusion rates because of the long simulation times needed to infer these rates with statistical accuracy. We show in this talk how to apply Markovian milestoning along minimum free-energy pathways to calculate diffusion rates of CO inside Mb. In Markovian milestoning, one partitions a suitable reaction coordinate space into regions and performs restrained molecular dynamics in each region to accumulate kinetic statistics that, when assembled across regions, provides an estimate of the mean first-passage time between states. The mean escape time for CO directly from the so-called distal pocket (DP) through the histidine gate (HG) is estimated at about 24 ns, confirming the importance of this portal for CO. But Mb is known to contain several internal cavities, and cavity-to-cavity diffusion rates are also computed and used to build a complete kinetic network as a Markov state model. Within this framework, the effective mean time of escape to the solvent through HG increases to 30 ns. Our results suggest that carrier protein structure may have evolved under pressure to modulate dissolved gas release rates using a network of ligand-accessible cavities. Support: NIH R01GM100472.

Stochastic wave-function simulation of irreversible emission processes for open quantum systems in a non-Markovian environment

Science.gov (United States)

Polyakov, Evgeny A.; Rubtsov, Alexey N.

2018-02-01

When conducting the numerical simulation of quantum transport, the main obstacle is a rapid growth of the dimension of entangled Hilbert subspace. The Quantum Monte Carlo simulation techniques, while being capable of treating the problems of high dimension, are hindered by the so-called "sign problem". In the quantum transport, we have fundamental asymmetry between the processes of emission and absorption of environment excitations: the emitted excitations are rapidly and irreversibly scattered away. Whereas only a small part of these excitations is absorbed back by the open subsystem, thus exercising the non-Markovian self-action of the subsystem onto itself. We were able to devise a method for the exact simulation of the dominant quantum emission processes, while taking into account the small backaction effects in an approximate self-consistent way. Such an approach allows us to efficiently conduct simulations of real-time dynamics of small quantum subsystems immersed in non-Markovian bath for large times, reaching the quasistationary regime. As an example we calculate the spatial quench dynamics of Kondo cloud for a bozonized Kodno impurity model.

Two parallel finite queues with simultaneous services and Markovian arrivals

Directory of Open Access Journals (Sweden)

S. R. Chakravarthy

1997-01-01

Full Text Available In this paper, we consider a finite capacity single server queueing model with two buffers, A and B, of sizes K and N respectively. Messages arrive one at a time according to a Markovian arrival process. Messages that arrive at buffer A are of a different type from the messages that arrive at buffer B. Messages are processed according to the following rules: 1. When buffer A(B has a message and buffer B(A is empty, then one message from A(B is processed by the server. 2. When both buffers, A and B, have messages, then two messages, one from A and one from B, are processed simultaneously by the server. The service times are assumed to be exponentially distributed with parameters that may depend on the type of service. This queueing model is studied as a Markov process with a large state space and efficient algorithmic procedures for computing various system performance measures are given. Some numerical examples are discussed.

Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution

Directory of Open Access Journals (Sweden)

Ivan B. Djordjevic

2015-08-01

Full Text Available Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i Markovian classical model, (ii Markovian-like quantum model, and (iii hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage Markov chain-like models of aging, which

Optimized auxiliary representation of non-Markovian impurity problems by a Lindblad equation

International Nuclear Information System (INIS)

Dorda, A; Sorantin, M; Linden, W von der; Arrigoni, E

2017-01-01

We present a general scheme to address correlated nonequilibrium quantum impurity problems based on a mapping onto an auxiliary open quantum system of small size. The infinite fermionic reservoirs of the original system are thereby replaced by a small number N B of noninteracting auxiliary bath sites whose dynamics are described by a Lindblad equation, which can then be exactly solved by numerical methods such as Lanczos or matrix-product states. The mapping becomes exponentially exact with increasing N B , and is already quite accurate for small N B . Due to the presence of the intermediate bath sites, the overall dynamics acting on the impurity site is non-Markovian. While in previous work we put the focus on the manybody solution of the associated Lindblad problem, here we discuss the mapping scheme itself, which is an essential part of the overall approach. On the one hand, we provide technical details together with an in-depth discussion of the employed algorithms, and on the other hand, we present a detailed convergence study. The latter clearly demonstrates the above-mentioned exponential convergence of the procedure with increasing N B . Furthermore, the influence of temperature and an external bias voltage on the reservoirs is investigated. The knowledge of the particular convergence behavior is of great value to assess the applicability of the scheme to certain physical situations. Moreover, we study different geometries for the auxiliary system. On the one hand, this is of importance for advanced manybody solution techniques such as matrix product states which work well for short-ranged couplings, and on the other hand, it allows us to gain more insights into the underlying mechanisms when mapping non-Markovian reservoirs onto Lindblad-type impurity problems. Finally, we present results for the spectral function of the Anderson impurity model in and out of equilibrium and discuss the accuracy obtained with the different geometries of the auxiliary system

A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.

Science.gov (United States)

Marken, John P; Halleran, Andrew D; Rahman, Atiqur; Odorizzi, Laura; LeFew, Michael C; Golino, Caroline A; Kemper, Peter; Saha, Margaret S

2016-01-01

Methods to analyze the dynamics of calcium activity often rely on visually distinguishable features in time series data such as spikes, waves, or oscillations. However, systems such as the developing nervous system display a complex, irregular type of calcium activity which makes the use of such methods less appropriate. Instead, for such systems there exists a class of methods (including information theoretic, power spectral, and fractal analysis approaches) which use more fundamental properties of the time series to analyze the observed calcium dynamics. We present a new analysis method in this class, the Markovian Entropy measure, which is an easily implementable calcium time series analysis method which represents the observed calcium activity as a realization of a Markov Process and describes its dynamics in terms of the level of predictability underlying the transitions between the states of the process. We applied our and other commonly used calcium analysis methods on a dataset from Xenopus laevis neural progenitors which displays irregular calcium activity and a dataset from murine synaptic neurons which displays activity time series that are well-described by visually-distinguishable features. We find that the Markovian Entropy measure is able to distinguish between biologically distinct populations in both datasets, and that it can separate biologically distinct populations to a greater extent than other methods in the dataset exhibiting irregular calcium activity. These results support the benefit of using the Markovian Entropy measure to analyze calcium dynamics, particularly for studies using time series data which do not exhibit easily distinguishable features.

A Markovian Entropy Measure for the Analysis of Calcium Activity Time Series.

Directory of Open Access Journals (Sweden)

John P Marken

Full Text Available Methods to analyze the dynamics of calcium activity often rely on visually distinguishable features in time series data such as spikes, waves, or oscillations. However, systems such as the developing nervous system display a complex, irregular type of calcium activity which makes the use of such methods less appropriate. Instead, for such systems there exists a class of methods (including information theoretic, power spectral, and fractal analysis approaches which use more fundamental properties of the time series to analyze the observed calcium dynamics. We present a new analysis method in this class, the Markovian Entropy measure, which is an easily implementable calcium time series analysis method which represents the observed calcium activity as a realization of a Markov Process and describes its dynamics in terms of the level of predictability underlying the transitions between the states of the process. We applied our and other commonly used calcium analysis methods on a dataset from Xenopus laevis neural progenitors which displays irregular calcium activity and a dataset from murine synaptic neurons which displays activity time series that are well-described by visually-distinguishable features. We find that the Markovian Entropy measure is able to distinguish between biologically distinct populations in both datasets, and that it can separate biologically distinct populations to a greater extent than other methods in the dataset exhibiting irregular calcium activity. These results support the benefit of using the Markovian Entropy measure to analyze calcium dynamics, particularly for studies using time series data which do not exhibit easily distinguishable features.

Non-Markovian dissipative quantum mechanics with stochastic trajectories

Energy Technology Data Exchange (ETDEWEB)

Koch, Werner

2010-09-09

All fields of physics - be it nuclear, atomic and molecular, solid state, or optical - offer examples of systems which are strongly influenced by the environment of the actual system under investigation. The scope of what is called ''the environment'' may vary, i.e., how far from the system of interest an interaction between the two does persist. Typically, however, it is much larger than the open system itself. Hence, a fully quantum mechanical treatment of the combined system without approximations and without limitations of the type of system is currently out of reach. With the single assumption of the environment to consist of an internally thermalized set of infinitely many harmonic oscillators, the seminal work of Stockburger and Grabert [Chem. Phys., 268:249-256, 2001] introduced an open system description that captures the environmental influence by means of a stochastic driving of the reduced system. The resulting stochastic Liouville-von Neumann equation describes the full non-Markovian dynamics without explicit memory but instead accounts for it implicitly through the correlations of the complex-valued noise forces. The present thesis provides a first application of the Stockburger-Grabert stochastic Liouville-von Neumann equation to the computation of the dynamics of anharmonic, continuous open systems. In particular, it is demonstrated that trajectory based propagators allow for the construction of a numerically stable propagation scheme. With this approach it becomes possible to achieve the tremendous increase of the noise sample count necessary to stochastically converge the results when investigating such systems with continuous variables. After a test against available analytic results for the dissipative harmonic oscillator, the approach is subsequently applied to the analysis of two different realistic, physical systems. As a first example, the dynamics of a dissipative molecular oscillator is investigated. Long time

Analysis and design of singular Markovian jump systems

CERN Document Server

Wang, Guoliang; Yan, Xinggang

2014-01-01

This monograph is an up-to-date presentation of the analysis and design of singular Markovian jump systems (SMJSs) in which the transition rate matrix of the underlying systems is generally uncertain, partially unknown and designed. The problems addressed include stability, stabilization, H∞ control and filtering, observer design, and adaptive control. applications of Markov process are investigated by using Lyapunov theory, linear matrix inequalities (LMIs), S-procedure and the stochastic Barbalat's Lemma, among other techniques.Features of the book include:·???????? study of the stability pr

Non-Markovian dynamics of a qubit due to single-photon scattering in a waveguide

Science.gov (United States)

Fang, Yao-Lung L.; Ciccarello, Francesco; Baranger, Harold U.

2018-04-01

We investigate the open dynamics of a qubit due to scattering of a single photon in an infinite or semi-infinite waveguide. Through an exact solution of the time-dependent multi-photon scattering problem, we find the qubit's dynamical map. Tools of open quantum systems theory allow us then to show the general features of this map, find the corresponding non-Linbladian master equation, and assess in a rigorous way its non-Markovian nature. The qubit dynamics has distinctive features that, in particular, do not occur in emission processes. Two fundamental sources of non-Markovianity are present: the finite width of the photon wavepacket and the time delay for propagation between the qubit and the end of the semi-infinite waveguide.

Robust stability of uncertain Markovian jumping Cohen-Grossberg neural networks with mixed time-varying delays

International Nuclear Information System (INIS)

Sheng Li; Yang Huizhong

2009-01-01

This paper considers the robust stability of a class of uncertain Markovian jumping Cohen-Grossberg neural networks (UMJCGNNs) with mixed time-varying delays. The parameter uncertainties are norm-bounded and the mixed time-varying delays comprise discrete and distributed time delays. Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. An example is given to show the effectiveness of the proposed results.

Solving QCD evolution equations in rapidity space with Markovian Monte Carlo

CERN Document Server

Golec-Biernat, K; Placzek, W; Skrzypek, M

2009-01-01

This work covers methodology of solving QCD evolution equation of the parton distribution using Markovian Monte Carlo (MMC) algorithms in a class of models ranging from DGLAP to CCFM. One of the purposes of the above MMCs is to test the other more sophisticated Monte Carlo programs, the so-called Constrained Monte Carlo (CMC) programs, which will be used as a building block in the parton shower MC. This is why the mapping of the evolution variables (eikonal variable and evolution time) into four-momenta is also defined and tested. The evolution time is identified with the rapidity variable of the emitted parton. The presented MMCs are tested independently, with ~0.1% precision, against the non-MC program APCheb especially devised for this purpose.

An individual-based simulation model for mottled sculpin (Cottus bairdi) in a southern Appalachian stream

Science.gov (United States)

Brenda Rashleigh; Gary D. Grossman

2005-01-01

We describe and analyze a spatially explicit, individual-based model for the local population dynamics of mottled sculpin (Cottus bairdi). The model simulated daily growth, mortality, movement and spawning of individuals within a reach of stream. Juvenile and adult growth was based on consumption bioenergetics of benthic macroinvertebrate prey;...

Implied Stopping Rules for American Basket Options from Markovian Projection

KAUST Repository

Bayer, Christian; Hä ppö lä , Juho; Tempone, Raul

2017-01-01

This work addresses the problem of pricing American basket options in a multivariate setting, which includes among others, the Bachelier and the Black-Scholes models. In high dimensions, nonlinear partial differential equation methods for solving the problem become prohibitively costly due to the curse of dimensionality. Instead, this work proposes to use a stopping rule that depends on the dynamics of a low-dimensional Markovian projection of the given basket of assets. It is shown that the ability to approximate the original value function by a lower-dimensional approximation is a feature of the dynamics of the system and is unaffected by the path-dependent nature of the American basket option. Assuming that we know the density of the forward process and using the Laplace approximation, we first efficiently evaluate the diffusion coefficient corresponding to the low-dimensional Markovian projection of the basket. Then, we approximate the optimal early-exercise boundary of the option by solving a Hamilton-Jacobi-Bellman partial differential equation in the projected, low-dimensional space. The resulting near-optimal early-exercise boundary is used to produce an exercise strategy for the high-dimensional option, thereby providing a lower bound for the price of the American basket option. A corresponding upper bound is also provided. These bounds allow to assess the accuracy of the proposed pricing method. Indeed, our approximate early-exercise strategy provides a straightforward lower bound for the American basket option price. Following a duality argument due to Rogers, we derive a corresponding upper bound solving only the low-dimensional optimal control problem. Numerically, we show the feasibility of the method using baskets with dimensions up to fifty. In these examples, the resulting option price relative errors are only of the order of few percent.

Implied Stopping Rules for American Basket Options from Markovian Projection

KAUST Repository

Bayer, Christian

2017-05-01

This work addresses the problem of pricing American basket options in a multivariate setting, which includes among others, the Bachelier and the Black-Scholes models. In high dimensions, nonlinear partial differential equation methods for solving the problem become prohibitively costly due to the curse of dimensionality. Instead, this work proposes to use a stopping rule that depends on the dynamics of a low-dimensional Markovian projection of the given basket of assets. It is shown that the ability to approximate the original value function by a lower-dimensional approximation is a feature of the dynamics of the system and is unaffected by the path-dependent nature of the American basket option. Assuming that we know the density of the forward process and using the Laplace approximation, we first efficiently evaluate the diffusion coefficient corresponding to the low-dimensional Markovian projection of the basket. Then, we approximate the optimal early-exercise boundary of the option by solving a Hamilton-Jacobi-Bellman partial differential equation in the projected, low-dimensional space. The resulting near-optimal early-exercise boundary is used to produce an exercise strategy for the high-dimensional option, thereby providing a lower bound for the price of the American basket option. A corresponding upper bound is also provided. These bounds allow to assess the accuracy of the proposed pricing method. Indeed, our approximate early-exercise strategy provides a straightforward lower bound for the American basket option price. Following a duality argument due to Rogers, we derive a corresponding upper bound solving only the low-dimensional optimal control problem. Numerically, we show the feasibility of the method using baskets with dimensions up to fifty. In these examples, the resulting option price relative errors are only of the order of few percent.

Stability of the Markov operator and synchronization of Markovian random products

Science.gov (United States)

Díaz, Lorenzo J.; Matias, Edgar

2018-05-01

We study Markovian random products on a large class of ‘m-dimensional’ connected compact metric spaces (including products of closed intervals and trees). We introduce a splitting condition, generalizing the classical one by Dubins and Freedman, and prove that this condition implies the asymptotic stability of the corresponding Markov operator and (exponentially fast) synchronization.

Functional form comparison between the population and the individual Poisson based TCP models

International Nuclear Information System (INIS)

Schinkel, C.; Stavreva, N.; Stavrev, P.; Carlone, M.; Fallone, B.G.

2007-01-01

In this work, the functional form similarity between the individual and fundamental population TCP models is investigated. Using the fact that both models can be expressed in terms of the geometric parameters γ 50 and D 50 , we show that they have almost identical functional form for values of γ 50 ≥1. The conceptual inadequacy of applying an individual model to clinical data is also discussed. A general individual response TCP expression is given, parameterized by D f and γ f - the dose corresponding to a control level of f, and the normalized slope at that point. It is shown that the dose-response may be interpreted as an individual response only if γ 50 is sufficiently high. Based on the functional form equivalency between the individual and the population TCP models, we discuss the possibility of applying the individual TCP model for the case of heterogeneous irradiations. Due to the fact that the fundamental population TCP model is derived for homogeneous irradiations only, we propose the use of the EUD, given by the generalized mean dose, when the fundamental population TCP model is used to fit clinical data. (author)

The analysis of the derivation principles of kinetic equations based on exactly solvable models of the bulk reaction A + B → Product

International Nuclear Information System (INIS)

Kipriyanov, A.A.; Doktorov, A.B.

2005-01-01

We have considered two many-particle models of the irreversible reaction A + B → Product for which closed kinetic equations for the mean concentration N A (t) of A species can be exactly obtained. These equations are identically recast into a unified form of integro-differential equation of general kinetic theory. It is shown that the memory functions for both models under consideration can be represented as a sum of the Markovian and non-Markovian parts. It is essential that the Markovian part of the Laplace transform of any kernel can be obtained using the Laplace transform of the kernel itself, and is the root of the non-Markovian part of the Laplace transform of the kernel. The properties established allowed us to perform correct approximation of the memory functions at small concentrations [B] of B species and derive the binary non-Markovian integro-differential equation. Within the binary theory accuracy this equation has been rewritten in a regular frame of a familiar rate equation satisfying general principles of binary kinetic equations. Thus using particular exactly solvable many-particle models, we have reproduced the most essential steps of the known general way for the derivation of the binary kinetic equation avoiding the sophisticated many-particle technique and the corresponding approximations. Besides, the results obtained can serve as an additional evidence of the approximations made in a general many-particle approach to the derivation of the binary kinetic equation

Dynamics of non-Markovian exclusion processes

International Nuclear Information System (INIS)

Khoromskaia, Diana; Grosskinsky, Stefan; Harris, Rosemary J

2014-01-01

Driven diffusive systems are often used as simple discrete models of collective transport phenomena in physics, biology or social sciences. Restricting attention to one-dimensional geometries, the asymmetric simple exclusion process (ASEP) plays a paradigmatic role to describe noise-activated driven motion of entities subject to an excluded volume interaction and many variants have been studied in recent years. While in the standard ASEP the noise is Poissonian and the process is therefore Markovian, in many applications the statistics of the activating noise has a non-standard distribution with possible memory effects resulting from internal degrees of freedom or external sources. This leads to temporal correlations and can significantly affect the shape of the current-density relation as has been studied recently for a number of scenarios. In this paper we report a general framework to derive the fundamental diagram of ASEPs driven by non-Poissonian noise by using effectively only two simple quantities, viz., the mean residual lifetime of the jump distribution and a suitably defined temporal correlation length. We corroborate our results by detailed numerical studies for various noise statistics under periodic boundary conditions and discuss how our approach can be applied to more general driven diffusive systems. (paper)

Dynamics of non-Markovian exclusion processes

Science.gov (United States)

Khoromskaia, Diana; Harris, Rosemary J.; Grosskinsky, Stefan

2014-12-01

Driven diffusive systems are often used as simple discrete models of collective transport phenomena in physics, biology or social sciences. Restricting attention to one-dimensional geometries, the asymmetric simple exclusion process (ASEP) plays a paradigmatic role to describe noise-activated driven motion of entities subject to an excluded volume interaction and many variants have been studied in recent years. While in the standard ASEP the noise is Poissonian and the process is therefore Markovian, in many applications the statistics of the activating noise has a non-standard distribution with possible memory effects resulting from internal degrees of freedom or external sources. This leads to temporal correlations and can significantly affect the shape of the current-density relation as has been studied recently for a number of scenarios. In this paper we report a general framework to derive the fundamental diagram of ASEPs driven by non-Poissonian noise by using effectively only two simple quantities, viz., the mean residual lifetime of the jump distribution and a suitably defined temporal correlation length. We corroborate our results by detailed numerical studies for various noise statistics under periodic boundary conditions and discuss how our approach can be applied to more general driven diffusive systems.

Asymptotic results for the semi-Markovian random walk with delay

International Nuclear Information System (INIS)

Khaniyev, T.A.; Aliyev, R.T.

2006-12-01

In this study, the semi-Markovian random walk with a discrete interference of chance (X(t) ) is considered and under some weak assumptions the ergodicity of this process is discussed. Characteristic function of the ergodic distribution of X(t) is expressed by means of the probability characteristics of the boundary functionals (N,S N ). Some exact formulas for first and second moments of ergodic distribution of the process X(t) are obtained when the random variable ζ 1 - s, which is describing a discrete interference of chance, has Gamma distribution on the interval [0, ∞) with parameter (α,λ) . Based on these results, the asymptotic expansions with three terms for the first two moments of the ergodic distribution of the process X(t) are obtained, as λ → 0. (author)

Perturbative approach to non-Markovian stochastic Schroedinger equations

International Nuclear Information System (INIS)

Gambetta, Jay; Wiseman, H.M.

2002-01-01

In this paper we present a perturbative procedure that allows one to numerically solve diffusive non-Markovian stochastic Schroedinger equations, for a wide range of memory functions. To illustrate this procedure numerical results are presented for a classically driven two-level atom immersed in an environment with a simple memory function. It is observed that as the order of the perturbation is increased the numerical results for the ensemble average state ρ red (t) approach the exact reduced state found via Imamog-barlu ' s enlarged system method [Phys. Rev. A 50, 3650 (1994)

Quantum Non-Markovian Langevin Equations and Transport Coefficients

International Nuclear Information System (INIS)

Sargsyan, V.V.; Antonenko, N.V.; Kanokov, Z.; Adamian, G.G.

2005-01-01

Quantum diffusion equations featuring explicitly time-dependent transport coefficients are derived from generalized non-Markovian Langevin equations. Generalized fluctuation-dissipation relations and analytic expressions for calculating the friction and diffusion coefficients in nuclear processes are obtained. The asymptotic behavior of the transport coefficients and correlation functions for a damped harmonic oscillator that is linearly coupled in momentum to a heat bath is studied. The coupling to a heat bath in momentum is responsible for the appearance of the diffusion coefficient in coordinate. The problem of regression of correlations in quantum dissipative systems is analyzed

THE HALO MASS FUNCTION FROM EXCURSION SET THEORY. I. GAUSSIAN FLUCTUATIONS WITH NON-MARKOVIAN DEPENDENCE ON THE SMOOTHING SCALE

International Nuclear Information System (INIS)

Maggiore, Michele; Riotto, Antonio

2010-01-01

A classic method for computing the mass function of dark matter halos is provided by excursion set theory, where density perturbations evolve stochastically with the smoothing scale, and the problem of computing the probability of halo formation is mapped into the so-called first-passage time problem in the presence of a barrier. While the full dynamical complexity of halo formation can only be revealed through N-body simulations, excursion set theory provides a simple analytic framework for understanding various aspects of this complex process. In this series of papers we propose improvements of both technical and conceptual aspects of excursion set theory, and we explore up to which point the method can reproduce quantitatively the data from N-body simulations. In Paper I of the series, we show how to derive excursion set theory from a path integral formulation. This allows us both to derive rigorously the absorbing barrier boundary condition, that in the usual formulation is just postulated, and to deal analytically with the non-Markovian nature of the random walk. Such a non-Markovian dynamics inevitably enters when either the density is smoothed with filters such as the top-hat filter in coordinate space (which is the only filter associated with a well-defined halo mass) or when one considers non-Gaussian fluctuations. In these cases, beside 'Markovian' terms, we find 'memory' terms that reflect the non-Markovianity of the evolution with the smoothing scale. We develop a general formalism for evaluating perturbatively these non-Markovian corrections, and in this paper we perform explicitly the computation of the halo mass function for Gaussian fluctuations, to first order in the non-Markovian corrections due to the use of a top-hat filter in coordinate space. In Paper II of this series we propose to extend excursion set theory by treating the critical threshold for collapse as a stochastic variable, which better captures some of the dynamical complexity of the

Non-Markovian effects on quantum-communication protocols

International Nuclear Information System (INIS)

Yeo, Ye; Oh, C. H.; An, Jun-Hong

2010-01-01

We show how, under the influence of non-Markovian environments, two different maximally entangled Bell states give rise to states that have equal classical correlations and the same capacities to violate the Bell-Clauser-Horne-Shimony-Holt inequality, but intriguingly differing usefulness for teleportation and dense coding. We elucidate how different entanglement measures like negativity and concurrence, and two different measures of quantum discord, could account for these behaviors. In particular, we explicitly show how the Ollivier-Zurek measure of discord directly accounts for one state being a better resource for dense coding compared to another. Our study leads to several important issues about these measures of discord.

An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis

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Corrie H. Allen

2016-05-01

Full Text Available Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from

Uniting statistical and individual-based approaches for animal movement modelling.

Science.gov (United States)

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.

Population dynamics of excited atoms in non-Markovian environments at zero and finite temperature

International Nuclear Information System (INIS)

Zou Hong-Mei; Fang Mao-Fa

2015-01-01

The population dynamics of a two-atom system, which is in two independent Lorentzian reservoirs or in two independent Ohmic reservoirs respectively, where the reservoirs are at zero temperature or finite temperature, is studied by using the time-convolutionless master-equation method. The influences of the characteristics and temperature of a non-Markovian environment on the population of the excited atoms are analyzed. We find that the population trapping of the excited atoms is related to the characteristics and the temperature of the non-Markovian environment. The results show that, at zero temperature, the two atoms can be effectively trapped in the excited state both in the Lorentzian reservoirs and in the Ohmic reservoirs. At finite temperature, the population of the excited atoms will quickly decay to a nonzero value. (paper)

Large deviation estimates for a Non-Markovian Lévy generator of big order

International Nuclear Information System (INIS)

Léandre, Rémi

2015-01-01

We give large deviation estimates for a non-markovian convolution semi-group with a non-local generator of Lévy type of big order and with the standard normalisation of semi-classical analysis. No stochastic process is associated to this semi-group. (paper)

Fuzzy Stochastic Optimal Guaranteed Cost Control of Bio-Economic Singular Markovian Jump Systems.

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Li, Li; Zhang, Qingling; Zhu, Baoyan

2015-11-01

This paper establishes a bio-economic singular Markovian jump model by considering the price of the commodity as a Markov chain. The controller is designed for this system such that its biomass achieves the specified range with the least cost in a finite-time. Firstly, this system is described by Takagi-Sugeno fuzzy model. Secondly, a new design method of fuzzy state-feedback controllers is presented to ensure not only the regularity, nonimpulse, and stochastic singular finite-time boundedness of this kind of systems, but also an upper bound achieved for the cost function in the form of strict linear matrix inequalities. Finally, two examples including a practical example of eel seedling breeding are given to illustrate the merit and usability of the approach proposed in this paper.

Stochastic representation of a class of non-Markovian completely positive evolutions

International Nuclear Information System (INIS)

Budini, Adrian A.

2004-01-01

By modeling the interaction of an open quantum system with its environment through a natural generalization of the classical concept of continuous time random walk, we derive and characterize a class of non-Markovian master equations whose solution is a completely positive map. The structure of these master equations is associated with a random renewal process where each event consist in the application of a superoperator over a density matrix. Strong nonexponential decay arise by choosing different statistics of the renewal process. As examples we analyze the stochastic and averaged dynamics of simple systems that admit an analytical solution. The problem of positivity in quantum master equations induced by memory effects [S. M. Barnett and S. Stenholm, Phys. Rev. A 64, 033808 (2001)] is clarified in this context

Data-driven non-Markovian closure models

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Kondrashov, Dmitri; Chekroun, Mickaël D.; Ghil, Michael

2015-03-01

This paper has two interrelated foci: (i) obtaining stable and efficient data-driven closure models by using a multivariate time series of partial observations from a large-dimensional system; and (ii) comparing these closure models with the optimal closures predicted by the Mori-Zwanzig (MZ) formalism of statistical physics. Multilayer stochastic models (MSMs) are introduced as both a generalization and a time-continuous limit of existing multilevel, regression-based approaches to closure in a data-driven setting; these approaches include empirical model reduction (EMR), as well as more recent multi-layer modeling. It is shown that the multilayer structure of MSMs can provide a natural Markov approximation to the generalized Langevin equation (GLE) of the MZ formalism. A simple correlation-based stopping criterion for an EMR-MSM model is derived to assess how well it approximates the GLE solution. Sufficient conditions are derived on the structure of the nonlinear cross-interactions between the constitutive layers of a given MSM to guarantee the existence of a global random attractor. This existence ensures that no blow-up can occur for a broad class of MSM applications, a class that includes non-polynomial predictors and nonlinearities that do not necessarily preserve quadratic energy invariants. The EMR-MSM methodology is first applied to a conceptual, nonlinear, stochastic climate model of coupled slow and fast variables, in which only slow variables are observed. It is shown that the resulting closure model with energy-conserving nonlinearities efficiently captures the main statistical features of the slow variables, even when there is no formal scale separation and the fast variables are quite energetic. Second, an MSM is shown to successfully reproduce the statistics of a partially observed, generalized Lotka-Volterra model of population dynamics in its chaotic regime. The challenges here include the rarity of strange attractors in the model's parameter

Joint Probability Distributions for a Class of Non-Markovian Processes

OpenAIRE

Baule, A.; Friedrich, R.

2004-01-01

We consider joint probability distributions for the class of coupled Langevin equations introduced by Fogedby [H.C. Fogedby, Phys. Rev. E 50, 1657 (1994)]. We generalize well-known results for the single time probability distributions to the case of N-time joint probability distributions. It is shown that these probability distribution functions can be obtained by an integral transform from distributions of a Markovian process. The integral kernel obeys a partial differential equation with fr...

Sensitivity analysis of an individual-based model for simulation of influenza epidemics.

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Elaine O Nsoesie

Full Text Available Individual-based epidemiology models are increasingly used in the study of influenza epidemics. Several studies on influenza dynamics and evaluation of intervention measures have used the same incubation and infectious period distribution parameters based on the natural history of influenza. A sensitivity analysis evaluating the influence of slight changes to these parameters (in addition to the transmissibility would be useful for future studies and real-time modeling during an influenza pandemic.In this study, we examined individual and joint effects of parameters and ranked parameters based on their influence on the dynamics of simulated epidemics. We also compared the sensitivity of the model across synthetic social networks for Montgomery County in Virginia and New York City (and surrounding metropolitan regions with demographic and rural-urban differences. In addition, we studied the effects of changing the mean infectious period on age-specific epidemics. The research was performed from a public health standpoint using three relevant measures: time to peak, peak infected proportion and total attack rate. We also used statistical methods in the design and analysis of the experiments. The results showed that: (i minute changes in the transmissibility and mean infectious period significantly influenced the attack rate; (ii the mean of the incubation period distribution appeared to be sufficient for determining its effects on the dynamics of epidemics; (iii the infectious period distribution had the strongest influence on the structure of the epidemic curves; (iv the sensitivity of the individual-based model was consistent across social networks investigated in this study and (v age-specific epidemics were sensitive to changes in the mean infectious period irrespective of the susceptibility of the other age groups. These findings suggest that small changes in some of the disease model parameters can significantly influence the uncertainty

Individual Travel Behavior Modeling of Public Transport Passenger Based on Graph Construction

OpenAIRE

Quan Liang; Jiancheng Weng; Wei Zhou; Selene Baez Santamaria; Jianming Ma; Jian Rong

2018-01-01

This paper presents a novel method for mining the individual travel behavior regularity of different public transport passengers through constructing travel behavior graph based model. The individual travel behavior graph is developed to represent spatial positions, time distributions, and travel routes and further forecasts the public transport passenger’s behavior choice. The proposed travel behavior graph is composed of macronodes, arcs, and transfer probability. Each macronode corresponds...

An individual-based probabilistic model for simulating fisheries population dynamics

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Jie Cao

2016-12-01

Full Text Available The purpose of stock assessment is to support managers to provide intelligent decisions regarding removal from fish populations. Errors in assessment models may have devastating impacts on the population fitness and negative impacts on the economy of the resource users. Thus, accuracte estimations of population size, growth rates are critical for success. Evaluating and testing the behavior and performance of stock assessment models and assessing the consequences of model mis-specification and the impact of management strategies requires an operating model that accurately describe the dynamics of the target species, and can resolve spatial and seasonal changes. In addition, the most thorough evaluations of assessment models use an operating model that takes a different form than the assessment model. This paper presents an individual-based probabilistic model used to simulate the complex dynamics of populations and their associated fisheries. Various components of population dynamics are expressed as random Bernoulli trials in the model and detailed life and fishery histories of each individual are tracked over their life span. The simulation model is designed to be flexible so it can be used for different species and fisheries. It can simulate mixing among multiple stocks and link stock-recruit relationships to environmental factors. Furthermore, the model allows for flexibility in sub-models (e.g., growth and recruitment and model assumptions (e.g., age- or size-dependent selectivity. This model enables the user to conduct various simulation studies, including testing the performance of assessment models under different assumptions, assessing the impacts of model mis-specification and evaluating management strategies.

The simulation of the non-Markovian behaviour of a two-level system

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Semina, I.; Petruccione, F.

2016-05-01

Non-Markovian relaxation dynamics of a two-level system is studied with the help of the non-linear stochastic Schrödinger equation with coloured Ornstein-Uhlenbeck noise. This stochastic Schrödinger equation is investigated numerically with an adapted Platen scheme. It is shown, that the memory effects have a significant impact to the dynamics of the system.

Synchronization of Markovian jumping inertial neural networks and its applications in image encryption.

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Prakash, M; Balasubramaniam, P; Lakshmanan, S

2016-11-01

This study is mainly concerned with the problem on synchronization criteria for Markovian jumping time delayed bidirectional associative memory neural networks and their applications in secure image communications. Based on the variable transformation method, the addressed second order differential equations are transformed into first order differential equations. Then, by constructing a suitable Lyapunov-Krasovskii functional and based on integral inequalities, the criteria which ensure the synchronization between the uncontrolled system and controlled system are established through designed feedback controllers and linear matrix inequalities. Further, the proposed results proved that the error system is globally asymptotically stable in the mean square. Moreover, numerical illustrations are provided to validate the effectiveness of the derived analytical results. Finally, the application of addressed system is explored via image encryption/decryption process. Copyright © 2016 Elsevier Ltd. All rights reserved.

A single-server Markovian queuing system with discouraged arrivals and retention of reneged customers

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Kumar Rakesh

2014-01-01

Full Text Available Customer impatience has a very negative impact on the queuing system under investigation. If we talk from business point of view, the firms lose their potential customers due to customer impatience, which affects their business as a whole. If the firms employ certain customer retention strategies, then there are chances that a certain fraction of impatient customers can be retained in the queuing system. A reneged customer may be convinced to stay in the queuing system for his further service with some probability, say q and he may abandon the queue without receiving the service with a probability p(=1− q. A finite waiting space Markovian single-server queuing model with discouraged arrivals, reneging and retention of reneged customers is studied. The steady state solution of the model is derived iteratively. The measures of effectiveness of the queuing model are also obtained. Some important queuing models are derived as special cases of this model.

Individual-based models for adaptive diversification in high-dimensional phenotype spaces.

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Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

2016-02-07

Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient. Copyright © 2015 Elsevier Ltd. All rights reserved.

Conjunction of wavelet transform and SOM-mutual information data pre-processing approach for AI-based Multi-Station nitrate modeling of watersheds

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Nourani, Vahid; Andalib, Gholamreza; Dąbrowska, Dominika

2017-05-01

Accurate nitrate load predictions can elevate decision management of water quality of watersheds which affects to environment and drinking water. In this paper, two scenarios were considered for Multi-Station (MS) nitrate load modeling of the Little River watershed. In the first scenario, Markovian characteristics of streamflow-nitrate time series were proposed for the MS modeling. For this purpose, feature extraction criterion of Mutual Information (MI) was employed for input selection of artificial intelligence models (Feed Forward Neural Network, FFNN and least square support vector machine). In the second scenario for considering seasonality-based characteristics of the time series, wavelet transform was used to extract multi-scale features of streamflow-nitrate time series of the watershed's sub-basins to model MS nitrate loads. Self-Organizing Map (SOM) clustering technique which finds homogeneous sub-series clusters was also linked to MI for proper cluster agent choice to be imposed into the models for predicting the nitrate loads of the watershed's sub-basins. The proposed MS method not only considers the prediction of the outlet nitrate but also covers predictions of interior sub-basins nitrate load values. The results indicated that the proposed FFNN model coupled with the SOM-MI improved the performance of MS nitrate predictions compared to the Markovian-based models up to 39%. Overall, accurate selection of dominant inputs which consider seasonality-based characteristics of streamflow-nitrate process could enhance the efficiency of nitrate load predictions.

Sample efficient multiagent learning in the presence of Markovian agents

CERN Document Server

Chakraborty, Doran

2014-01-01

The problem of Multiagent Learning (or MAL) is concerned with the study of how intelligent entities can learn and adapt in the presence of other such entities that are simultaneously adapting. The problem is often studied in the stylized settings provided by repeated matrix games (a.k.a. normal form games). The goal of this book is to develop MAL algorithms for such a setting that achieve a new set of objectives which have not been previously achieved. In particular this book deals with learning in the presence of a new class of agent behavior that has not been studied or modeled before in a MAL context: Markovian agent behavior. Several new challenges arise when interacting with this particular class of agents. The book takes a series of steps towards building completely autonomous learning algorithms that maximize utility while interacting with such agents. Each algorithm is meticulously specified with a thorough formal treatment that elucidates its key theoretical properties.

IASM: Individualized activity space modeler

Science.gov (United States)

Hasanzadeh, Kamyar

2018-01-01

Researchers from various disciplines have long been interested in analyzing and describing human mobility patterns. Activity space (AS), defined as an area encapsulating daily human mobility and activities, has been at the center of this interest. However, given the applied nature of research in this field and the complexity that advanced geographical modeling can pose to its users, the proposed models remain simplistic and inaccurate in many cases. Individualized Activity Space Modeler (IASM) is a geographic information system (GIS) toolbox, written in Python programming language using ESRI's Arcpy module, comprising four tools aiming to facilitate the use of advanced activity space models in empirical research. IASM provides individual-based and context-sensitive tools to estimate home range distances, delineate activity spaces, and model place exposures using individualized geographical data. In this paper, we describe the design and functionality of IASM, and provide an example of how it performs on a spatial dataset collected through an online map-based survey.

USING ECO-EVOLUTIONARY INDIVIDUAL-BASED MODELS TO INVESTIGATE SPATIALLY-DEPENDENT PROCESSES IN CONSERVATION GENETICS

Science.gov (United States)

Eco-evolutionary population simulation models are powerful new forecasting tools for exploring management strategies for climate change and other dynamic disturbance regimes. Additionally, eco-evo individual-based models (IBMs) are useful for investigating theoretical feedbacks ...

Non-Markovian dynamics of quantum systems: formalism, transport coefficients

International Nuclear Information System (INIS)

Kanokov, Z.; Palchikov, Yu.V.; Antonenko, N.V.; Adamian, G.G.; Kanokov, Z.; Adamian, G.G.; Scheid, W.

2004-01-01

Full text: The generalized Linbland equations with non-stationary transport coefficients are derived from the Langevin equations for the case of nonlinear non-Markovian noise [1]. The equations of motion for the collective coordinates are consistent with the generalized quantum fluctuation dissipation relations. The microscopic justification of the Linbland axiomatic approach is performed. Explicit expressions for the time-dependent transport coefficients are presented for the case of FC- and RWA-oscillators and a general linear coupling in coordinate and in momentum between the collective subsystem and heat bath. The explicit equations for the correlation functions show that the Onsanger's regression hypothesis does not hold exactly for the non-Markovian equations of motion. However, under some conditions the regression of fluctuations goes to zero in the same manner as the average values. In the low and high temperature regimes we found that the dissipation leads to long-time tails in correlation functions in the RWA-oscillator. In the case of the FC-oscillator a non-exponential power-like decay of the correlation function in coordinate is only obtained only at the low temperature limit. The calculated results depend rather weakly on the memory time in many applications. The found transient times for diffusion coefficients D pp (t), D qp (t) and D qq (t) are quite short. The value of classical diffusion coefficients in momentum underestimates the asymptotic value of quantum one D pp (t), but the asymptotic values of classical σ qq c and quantum σ qq second moments are close due to the negativity of quantum mixed diffusion coefficient D qp (t)

Quantum adiabatic Markovian master equations

International Nuclear Information System (INIS)

Albash, Tameem; Zanardi, Paolo; Boixo, Sergio; Lidar, Daniel A

2012-01-01

We develop from first principles Markovian master equations suited for studying the time evolution of a system evolving adiabatically while coupled weakly to a thermal bath. We derive two sets of equations in the adiabatic limit, one using the rotating wave (secular) approximation that results in a master equation in Lindblad form, the other without the rotating wave approximation but not in Lindblad form. The two equations make markedly different predictions depending on whether or not the Lamb shift is included. Our analysis keeps track of the various time and energy scales associated with the various approximations we make, and thus allows for a systematic inclusion of higher order corrections, in particular beyond the adiabatic limit. We use our formalism to study the evolution of an Ising spin chain in a transverse field and coupled to a thermal bosonic bath, for which we identify four distinct evolution phases. While we do not expect this to be a generic feature, in one of these phases dissipation acts to increase the fidelity of the system state relative to the adiabatic ground state. (paper)

Non-Markovian dynamics of dust charge fluctuations in dusty plasmas

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Asgari, H.; Muniandy, S. V.; Ghalee, Amir; Ghalee

2014-06-01

Dust charge fluctuates even in steady-state uniform plasma due to the discrete nature of the charge carriers and can be described using standard Langevin equation. In this work, two possible approaches in order to introduce the memory effect in dust charging dynamics are proposed. The first part of the paper provides the generalization form of the fluctuation-dissipation relation for non-Markovian systems based on generalized Langevin equations to determine the amplitudes of the dust charge fluctuations for two different kinds of colored noises under the assumption that the fluctuation-dissipation relation is valid. In the second part of the paper, aiming for dusty plasma system out of equilibrium, the fractionalized Langevin equation is used to derive the temporal two-point correlation function of grain charge fluctuations which is shown to be non-stationary due to the dependence on both times and not the time difference. The correlation function is used to derive the amplitude of fluctuations for early transient time.

Stability and Linear Quadratic Differential Games of Discrete-Time Markovian Jump Linear Systems with State-Dependent Noise

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Huiying Sun

2014-01-01

Full Text Available We mainly consider the stability of discrete-time Markovian jump linear systems with state-dependent noise as well as its linear quadratic (LQ differential games. A necessary and sufficient condition involved with the connection between stochastic Tn-stability of Markovian jump linear systems with state-dependent noise and Lyapunov equation is proposed. And using the theory of stochastic Tn-stability, we give the optimal strategies and the optimal cost values for infinite horizon LQ stochastic differential games. It is demonstrated that the solutions of infinite horizon LQ stochastic differential games are concerned with four coupled generalized algebraic Riccati equations (GAREs. Finally, an iterative algorithm is presented to solve the four coupled GAREs and a simulation example is given to illustrate the effectiveness of it.

An individual-based growth and competition model for coastal redwood forest restoration

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van Mantgem, Phillip J.; Das, Adrian J.

2014-01-01

Thinning treatments to accelerate coastal redwood forest stand development are in wide application, but managers have yet to identify prescriptions that might best promote Sequoia sempervirens (Lamb. ex D. Don) Endl. (redwood) growth. The creation of successful thinning prescriptions would be aided by identifying the underlying mechanisms governing how individual tree growth responds to competitive environments in coastal redwood forests. We created a spatially explicit individual-based model of tree competition and growth parameterized using surveys of upland redwood forests at Redwood National Park, California. We modeled competition for overstory trees (stems ≥ 20 cm stem diameter at breast height, 1.37 m (dbh)) as growth reductions arising from sizes, distances, and species identity of competitor trees. Our model explained up to half of the variation in individual tree growth, suggesting that neighborhood crowding is an important determinant of growth in this forest type. We used our model to simulate the effects of novel thinning prescriptions (e.g., 40% stand basal area removal) for redwood forest restoration, concluding that these treatments could lead to substantial growth releases, particularly for S. sempervirens. The results of this study, along with continued improvements to our model, will help to determine spacing and species composition that best encourage growth.

Vibrational Markovian modelling of footprints after the interaction of antibiotics with the packaging region of HIV type 1.

Science.gov (United States)

Díaz, Humberto González; de Armas, Ronal Ramos; Molina, Reinaldo

2003-11-01

The design of novel anti-HIV compounds has now become a crucial area for scientists working in numerous interrelated fields of science such as molecular biology, medicinal chemistry, mathematical biology, molecular modelling and bioinformatics. In this context, the development of simple but physically meaningful mathematical models to represent the interaction between anti-HIV drugs and their biological targets is of major interest. One such area currently under investigation involves the targets in the HIV-RNA-packaging region. In the work described here, we applied Markov chain theory in an attempt to describe the interaction between the antibiotic paromomycin and the packaging region of the RNA in Type-1 HIV. In this model, a nucleic acid squeezed graph is used. The vertices of the graph represent the nucleotides while the edges are the phosphodiester bonds. A stochastic (Markovian) matrix was subsequently defined on this graph, an operation that codifies the probabilities of interaction between specific nucleotides of HIV-RNA and the antibiotic. The strength of these local interactions can be calculated through an inelastic vibrational model. The successive power of this matrix codifies the probabilities with which the vibrations after drug-RNA interactions vanish along the polynucleotide main chain. The sums of self-return probabilities in the k-vicinity of each nucleotide represent physically meaningful descriptors. A linear discriminant function was developed and gave rise to excellent discrimination in 80.8% of interacting and footprinted nucleotides. The Jackknife method was employed to assess the stability and predictability of the model. On the other hand, a linear regression model predicted the local binding affinity constants between a specific nucleotide and the antibiotic (R(2)=0.91, Q(2)=0.86). These kinds of models could play an important role either in the discovery of new anti-HIV compounds or the study of their mode of action.

Stability analysis of Markovian jumping stochastic Cohen—Grossberg neural networks with discrete and distributed time varying delays

International Nuclear Information System (INIS)

Ali, M. Syed

2014-01-01

In this paper, the global asymptotic stability problem of Markovian jumping stochastic Cohen—Grossberg neural networks with discrete and distributed time-varying delays (MJSCGNNs) is considered. A novel LMI-based stability criterion is obtained by constructing a new Lyapunov functional to guarantee the asymptotic stability of MJSCGNNs. Our results can be easily verified and they are also less restrictive than previously known criteria and can be applied to Cohen—Grossberg neural networks, recurrent neural networks, and cellular neural networks. Finally, the proposed stability conditions are demonstrated with numerical examples

An individual-based model of skipjack tuna (Katsuwonus pelamis) movement in the tropical Pacific ocean

Science.gov (United States)

Scutt Phillips, Joe; Sen Gupta, Alex; Senina, Inna; van Sebille, Erik; Lange, Michael; Lehodey, Patrick; Hampton, John; Nicol, Simon

2018-05-01

The distribution of marine species is often modeled using Eulerian approaches, in which changes to population density or abundance are calculated at fixed locations in space. Conversely, Lagrangian, or individual-based, models simulate the movement of individual particles moving in continuous space, with broader-scale patterns such as distribution being an emergent property of many, potentially adaptive, individuals. These models offer advantages in examining dynamics across spatiotemporal scales and making comparisons with observations from individual-scale data. Here, we introduce and describe such a model, the Individual-based Kinesis, Advection and Movement of Ocean ANimAls model (Ikamoana), which we use to replicate the movement processes of an existing Eulerian model for marine predators (the Spatial Ecosystem and Population Dynamics Model, SEAPODYM). Ikamoana simulates the movement of either individual or groups of animals by physical ocean currents, habitat-dependent stochastic movements (kinesis), and taxis movements representing active searching behaviours. Applying our model to Pacific skipjack tuna (Katsuwonus pelamis), we show that it accurately replicates the evolution of density distribution simulated by SEAPODYM with low time-mean error and a spatial correlation of density that exceeds 0.96 at all times. We demonstrate how the Lagrangian approach permits easy tracking of individuals' trajectories for examining connectivity between different regions, and show how the model can provide independent estimates of transfer rates between commonly used assessment regions. In particular, we find that retention rates in most assessment regions are considerably smaller (up to a factor of 2) than those estimated by this population of skipjack's primary assessment model. Moreover, these rates are sensitive to ocean state (e.g. El Nino vs La Nina) and so assuming fixed transfer rates between regions may lead to spurious stock estimates. A novel feature of the

Robust H∞ Filtering for Uncertain Neutral Stochastic Systems with Markovian Jumping Parameters and Time Delay

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Yajun Li

2015-01-01

Full Text Available This paper deals with the robust H∞ filter design problem for a class of uncertain neutral stochastic systems with Markovian jumping parameters and time delay. Based on the Lyapunov-Krasovskii theory and generalized Finsler Lemma, a delay-dependent stability condition is proposed to ensure not only that the filter error system is robustly stochastically stable but also that a prescribed H∞ performance level is satisfied for all admissible uncertainties. All obtained results are expressed in terms of linear matrix inequalities which can be easily solved by MATLAB LMI toolbox. Numerical examples are given to show that the results obtained are both less conservative and less complicated in computation.

Exploiting Non-Markovianity for Quantum Control.

Science.gov (United States)

Reich, Daniel M; Katz, Nadav; Koch, Christiane P

2015-07-22

Quantum technology, exploiting entanglement and the wave nature of matter, relies on the ability to accurately control quantum systems. Quantum control is often compromised by the interaction of the system with its environment since this causes loss of amplitude and phase. However, when the dynamics of the open quantum system is non-Markovian, amplitude and phase flow not only from the system into the environment but also back. Interaction with the environment is then not necessarily detrimental. We show that the back-flow of amplitude and phase can be exploited to carry out quantum control tasks that could not be realized if the system was isolated. The control is facilitated by a few strongly coupled, sufficiently isolated environmental modes. Our paradigmatic example considers a weakly anharmonic ladder with resonant amplitude control only, restricting realizable operations to SO(N). The coupling to the environment, when harnessed with optimization techniques, allows for full SU(N) controllability.

Markovian description of unbiased polymer translocation

International Nuclear Information System (INIS)

Mondaini, Felipe; Moriconi, L.

2012-01-01

We perform, with the help of cloud computing resources, extensive Langevin simulations which provide compelling evidence in favor of a general Markovian framework for unbiased three-dimensional polymer translocation. Our statistical analysis consists of careful evaluations of (i) two-point correlation functions of the translocation coordinate and (ii) the empirical probabilities of complete polymer translocation (taken as a function of the initial number of monomers on a given side of the membrane). We find good agreement with predictions derived from the Markov chain approach recently addressed in the literature by the present authors. -- Highlights: ► We investigate unbiased polymer translocation through membrane pores. ► Large statistical ensembles have been produced with the help of cloud computing resources. ► We evaluate the two-point correlation function of the translocation coordinate. ► We evaluate empirical probabilities for complete polymer translocation. ► Unbiased polymer translocation is described as a Markov stochastic process.

Markovian description of unbiased polymer translocation

Energy Technology Data Exchange (ETDEWEB)

Mondaini, Felipe [Instituto de Física, Universidade Federal do Rio de Janeiro, C.P. 68528, 21945-970 Rio de Janeiro, RJ (Brazil); Centro Federal de Educação Tecnológica Celso Suckow da Fonseca, UnED Angra dos Reis, Angra dos Reis, 23953-030, RJ (Brazil); Moriconi, L., E-mail: moriconi@if.ufrj.br [Instituto de Física, Universidade Federal do Rio de Janeiro, C.P. 68528, 21945-970 Rio de Janeiro, RJ (Brazil)

2012-10-01

We perform, with the help of cloud computing resources, extensive Langevin simulations which provide compelling evidence in favor of a general Markovian framework for unbiased three-dimensional polymer translocation. Our statistical analysis consists of careful evaluations of (i) two-point correlation functions of the translocation coordinate and (ii) the empirical probabilities of complete polymer translocation (taken as a function of the initial number of monomers on a given side of the membrane). We find good agreement with predictions derived from the Markov chain approach recently addressed in the literature by the present authors. -- Highlights: ► We investigate unbiased polymer translocation through membrane pores. ► Large statistical ensembles have been produced with the help of cloud computing resources. ► We evaluate the two-point correlation function of the translocation coordinate. ► We evaluate empirical probabilities for complete polymer translocation. ► Unbiased polymer translocation is described as a Markov stochastic process.

Individual Travel Behavior Modeling of Public Transport Passenger Based on Graph Construction

Directory of Open Access Journals (Sweden)

Quan Liang

2018-01-01

Full Text Available This paper presents a novel method for mining the individual travel behavior regularity of different public transport passengers through constructing travel behavior graph based model. The individual travel behavior graph is developed to represent spatial positions, time distributions, and travel routes and further forecasts the public transport passenger’s behavior choice. The proposed travel behavior graph is composed of macronodes, arcs, and transfer probability. Each macronode corresponds to a travel association map and represents a travel behavior. A travel association map also contains its own nodes. The nodes of a travel association map are created when the processed travel chain data shows significant change. Thus, each node of three layers represents a significant change of spatial travel positions, travel time, and routes, respectively. Since a travel association map represents a travel behavior, the graph can be considered a sequence of travel behaviors. Through integrating travel association map and calculating the probabilities of the arcs, it is possible to construct a unique travel behavior graph for each passenger. The data used in this study are multimode data matched by certain rules based on the data of public transport smart card transactions and network features. The case study results show that graph based method to model the individual travel behavior of public transport passengers is effective and feasible. Travel behavior graphs support customized public transport travel characteristics analysis and demand prediction.

Non-Markovian dynamics of charge carriers in quantum dots

International Nuclear Information System (INIS)

Vaz, E; Kyriakidis, J

2008-01-01

We have investigated the dynamics of bound particles in multilevel current-carrying quantum dots. We look specifically in the regime of resonant tunnelling transport, where several channels are available for transport. Through a non-Markovian formalism under the Born approximation, we investigate the real-time evolution of the confined particles including transport-induced decoherence and relaxation. In the case of a coherent superposition between states with different particle number, we find that a Fock-space coherence may be preserved even in the presence of tunneling into and out of the dot. Real-time results are presented for various asymmetries of tunneling rates into different orbitals

Nelson's stochastic quantization of free linearized gravitational field and its Markovian structure

International Nuclear Information System (INIS)

Lim, S.C.

1983-05-01

It is shown that by applying Nelson's stochastic quantization scheme to free linearized gravitational field tensor one can associate with the resulting stochastic system a stochastic tensor field which coincides with the ''space'' part of the Riemannian tensor in Euclidean space-time. However, such a stochastic field fails to satisfy the Markov property. Instead, it satisfies the reflection positivity. The Markovian structure of the stochastic fields associated with the electromagnetic field is also discussed. (author)

Hybrid Modelling of Individual Movement and Collective Behaviour

KAUST Repository

Franz, Benjamin

2013-01-01

Mathematical models of dispersal in biological systems are often written in terms of partial differential equations (PDEs) which describe the time evolution of population-level variables (concentrations, densities). A more detailed modelling approach is given by individual-based (agent-based) models which describe the behaviour of each organism. In recent years, an intermediate modelling methodology - hybrid modelling - has been applied to a number of biological systems. These hybrid models couple an individual-based description of cells/animals with a PDE-model of their environment. In this chapter, we overview hybrid models in the literature with the focus on the mathematical challenges of this modelling approach. The detailed analysis is presented using the example of chemotaxis, where cells move according to extracellular chemicals that can be altered by the cells themselves. In this case, individual-based models of cells are coupled with PDEs for extracellular chemical signals. Travelling waves in these hybrid models are investigated. In particular, we show that in contrary to the PDEs, hybrid chemotaxis models only develop a transient travelling wave. © 2013 Springer-Verlag Berlin Heidelberg.

Exponential stability of delayed recurrent neural networks with Markovian jumping parameters

International Nuclear Information System (INIS)

Wang Zidong; Liu Yurong; Yu Li; Liu Xiaohui

2006-01-01

In this Letter, the global exponential stability analysis problem is considered for a class of recurrent neural networks (RNNs) with time delays and Markovian jumping parameters. The jumping parameters considered here are generated from a continuous-time discrete-state homogeneous Markov process, which are governed by a Markov process with discrete and finite state space. The purpose of the problem addressed is to derive some easy-to-test conditions such that the dynamics of the neural network is stochastically exponentially stable in the mean square, independent of the time delay. By employing a new Lyapunov-Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish the desired sufficient conditions, and therefore the global exponential stability in the mean square for the delayed RNNs can be easily checked by utilizing the numerically efficient Matlab LMI toolbox, and no tuning of parameters is required. A numerical example is exploited to show the usefulness of the derived LMI-based stability conditions

Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

Science.gov (United States)

Ginovart, Marta

2014-08-01

The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study of a predator-prey system for a mathematics classroom in the first year of an undergraduate program in biosystems engineering have been designed and implemented. These activities were designed to put two modelling approaches side by side, an individual-based model and a set of ordinary differential equations. In order to organize and display this, a system with wolves and sheep in a confined domain was considered and studied. With the teaching material elaborated and a computer to perform the numerical resolutions involved and the corresponding individual-based simulations, the students answered questions and completed exercises to achieve the learning goals set. Students' responses regarding the modelling of biological systems and these two distinct methodologies applied to the study of a predator-prey system were collected via questionnaires, open-ended queries and face-to-face dialogues. Taking into account the positive responses of the students when they were doing these activities, it was clear that using a discrete individual-based model to deal with a predator-prey system jointly with a set of ordinary differential equations enriches the understanding of the modelling process, adds new insights and opens novel perspectives of what can be done with computational models versus other models. The complementary views given by the two modelling approaches were very well assessed by students.

Individual-based ecology of coastal birds.

Science.gov (United States)

Stillman, Richard A; Goss-Custard, John D

2010-08-01

Conservation objectives for non-breeding coastal birds (shorebirds and wildfowl) are determined from their population size at coastal sites. To advise coastal managers, models must predict quantitatively the effects of environmental change on population size or the demographic rates (mortality and reproduction) that determine it. As habitat association models and depletion models are not able to do this, we developed an approach that has produced such predictions thereby enabling policy makers to make evidence-based decisions. Our conceptual framework is individual-based ecology, in which populations are viewed as having properties (e.g. size) that arise from the traits (e.g. behaviour, physiology) and interactions of their constituent individuals. The link between individuals and populations is made through individual-based models (IBMs) that follow the fitness-maximising decisions of individuals and predict population-level consequences (e.g. mortality rate) from the fates of these individuals. Our first IBM was for oystercatchers Haematopus ostralegus and accurately predicted their density-dependent mortality. Subsequently, IBMs were developed for several shorebird and wildfowl species at several European sites, and were shown to predict accurately overwinter mortality, and the foraging behaviour from which predictions are derived. They have been used to predict the effect on survival in coastal birds of sea level rise, habitat loss, wind farm development, shellfishing and human disturbance. This review emphasises the wider applicability of the approach, and identifies other systems to which it could be applied. We view the IBM approach as a very useful contribution to the general problem of how to advance ecology to the point where we can routinely make meaningful predictions of how populations respond to environmental change.

Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking.

Science.gov (United States)

Nagoski, Emily; Janssen, Erick; Lohrmann, David; Nichols, Eric

2012-08-01

Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.

Individual based population inference using tagging data

DEFF Research Database (Denmark)

Pedersen, Martin Wæver; Thygesen, Uffe Høgsbro; Baktoft, Henrik

A hierarchical framework for simultaneous analysis of multiple related individual datasets is presented. The approach is very similar to mixed effects modelling as known from statistical theory. The model used at the individual level is, in principle, irrelevant as long as a maximum likelihood...... estimate and its uncertainty (Hessian) can be computed. The individual model used in this text is a hidden Markov model. A simulation study concerning a two-dimensional biased random walk is examined to verify the consistency of the hierarchical estimation framework. In addition, a study based on acoustic...... telemetry data from pike illustrates how the framework can identify individuals that deviate from the remaining population....

New Passivity Criteria for Fuzzy Bam Neural Networks with Markovian Jumping Parameters and Time-Varying Delays

Science.gov (United States)

Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Thangaraj, P.

2013-02-01

This paper addresses the problem of passivity analysis issue for a class of fuzzy bidirectional associative memory (BAM) neural networks with Markovian jumping parameters and time varying delays. A set of sufficient conditions for the passiveness of the considered fuzzy BAM neural network model is derived in terms of linear matrix inequalities by using the delay fractioning technique together with the Lyapunov function approach. In addition, the uncertainties are inevitable in neural networks because of the existence of modeling errors and external disturbance. Further, this result is extended to study the robust passivity criteria for uncertain fuzzy BAM neural networks with time varying delays and uncertainties. These criteria are expressed in the form of linear matrix inequalities (LMIs), which can be efficiently solved via standard numerical software. Two numerical examples are provided to demonstrate the effectiveness of the obtained results.

Order-disorder transitions in time-discrete mean field systems with memory: a novel approach via nonlinear autoregressive models

International Nuclear Information System (INIS)

Frank, T D; Mongkolsakulvong, S

2015-01-01

In a previous study strongly nonlinear autoregressive (SNAR) models have been introduced as a generalization of the widely-used time-discrete autoregressive models that are known to apply both to Markov and non-Markovian systems. In contrast to conventional autoregressive models, SNAR models depend on process mean values. So far, only linear dependences have been studied. We consider the case in which process mean values can have a nonlinear impact on the processes under consideration. It is shown that such models describe Markov and non-Markovian many-body systems with mean field forces that exhibit a nonlinear impact on single subsystems. We exemplify that such nonlinear dependences can describe order-disorder phase transitions of time-discrete Markovian and non-Markovian many-body systems. The relevant order parameter equations are derived and issues of stability and stationarity are studied. (paper)

Hard decoding algorithm for optimizing thresholds under general Markovian noise

Science.gov (United States)

Chamberland, Christopher; Wallman, Joel; Beale, Stefanie; Laflamme, Raymond

2017-04-01

Quantum error correction is instrumental in protecting quantum systems from noise in quantum computing and communication settings. Pauli channels can be efficiently simulated and threshold values for Pauli error rates under a variety of error-correcting codes have been obtained. However, realistic quantum systems can undergo noise processes that differ significantly from Pauli noise. In this paper, we present an efficient hard decoding algorithm for optimizing thresholds and lowering failure rates of an error-correcting code under general completely positive and trace-preserving (i.e., Markovian) noise. We use our hard decoding algorithm to study the performance of several error-correcting codes under various non-Pauli noise models by computing threshold values and failure rates for these codes. We compare the performance of our hard decoding algorithm to decoders optimized for depolarizing noise and show improvements in thresholds and reductions in failure rates by several orders of magnitude. Our hard decoding algorithm can also be adapted to take advantage of a code's non-Pauli transversal gates to further suppress noise. For example, we show that using the transversal gates of the 5-qubit code allows arbitrary rotations around certain axes to be perfectly corrected. Furthermore, we show that Pauli twirling can increase or decrease the threshold depending upon the code properties. Lastly, we show that even if the physical noise model differs slightly from the hypothesized noise model used to determine an optimized decoder, failure rates can still be reduced by applying our hard decoding algorithm.

Individualized computer-aided education in mammography based on user modeling: concept and preliminary experiments.

Science.gov (United States)

Mazurowski, Maciej A; Baker, Jay A; Barnhart, Huiman X; Tourassi, Georgia D

2010-03-01

The authors propose the framework for an individualized adaptive computer-aided educational system in mammography that is based on user modeling. The underlying hypothesis is that user models can be developed to capture the individual error making patterns of radiologists-in-training. In this pilot study, the authors test the above hypothesis for the task of breast cancer diagnosis in mammograms. The concept of a user model was formalized as the function that relates image features to the likelihood/extent of the diagnostic error made by a radiologist-in-training and therefore to the level of difficulty that a case will pose to the radiologist-in-training (or "user"). Then, machine learning algorithms were implemented to build such user models. Specifically, the authors explored k-nearest neighbor, artificial neural networks, and multiple regression for the task of building the model using observer data collected from ten Radiology residents at Duke University Medical Center for the problem of breast mass diagnosis in mammograms. For each resident, a user-specific model was constructed that predicts the user's expected level of difficulty for each presented case based on two BI-RADS image features. In the experiments, leave-one-out data handling scheme was applied to assign each case to a low-predicted-difficulty or a high-predicted-difficulty group for each resident based on each of the three user models. To evaluate whether the user model is useful in predicting difficulty, the authors performed statistical tests using the generalized estimating equations approach to determine whether the mean actual error is the same or not between the low-predicted-difficulty group and the high-predicted-difficulty group. When the results for all observers were pulled together, the actual errors made by residents were statistically significantly higher for cases in the high-predicted-difficulty group than for cases in the low-predicted-difficulty group for all modeling

Power-law tails and non-Markovian dynamics in open quantum systems: An exact solution from Keldysh field theory

Science.gov (United States)

Chakraborty, Ahana; Sensarma, Rajdeep

2018-03-01

The Born-Markov approximation is widely used to study the dynamics of open quantum systems coupled to external baths. Using Keldysh formalism, we show that the dynamics of a system of bosons (fermions) linearly coupled to a noninteracting bosonic (fermionic) bath falls outside this paradigm if the bath spectral function has nonanalyticities as a function of frequency. In this case, we show that the dissipative and noise kernels governing the dynamics have distinct power-law tails. The Green's functions show a short-time "quasi"-Markovian exponential decay before crossing over to a power-law tail governed by the nonanalyticity of the spectral function. We study a system of bosons (fermions) hopping on a one-dimensional lattice, where each site is coupled linearly to an independent bath of noninteracting bosons (fermions). We obtain exact expressions for the Green's functions of this system, which show power-law decay ˜|t - t'|-3 /2 . We use these to calculate the density and current profile, as well as unequal-time current-current correlators. While the density and current profiles show interesting quantitative deviations from Markovian results, the current-current correlators show qualitatively distinct long-time power-law tails |t - t'|-3 characteristic of non-Markovian dynamics. We show that the power-law decays survive in the presence of interparticle interaction in the system, but the crossover time scale is shifted to larger values with increasing interaction strength.

Applying and Individual-Based Model to Simultaneously Evaluate Net Ecosystem Production and Tree Diameter Increment

Science.gov (United States)

Fang, F. J.

2017-12-01

Reconciling observations at fundamentally different scales is central in understanding the global carbon cycle. This study investigates a model-based melding of forest inventory data, remote-sensing data and micrometeorological-station data ("flux towers" estimating forest heat, CO2 and H2O fluxes). The individual tree-based model FORCCHN was used to evaluate the tree DBH increment and forest carbon fluxes. These are the first simultaneous simulations of the forest carbon budgets from flux towers and individual-tree growth estimates of forest carbon budgets using the continuous forest inventory data — under circumstances in which both predictions can be tested. Along with the global implications of such findings, this also improves the capacity for forest sustainable management and the comprehensive understanding of forest ecosystems. In forest ecology, diameter at breast height (DBH) of a tree significantly determines an individual tree's cross-sectional sapwood area, its biomass and carbon storage. Evaluation the annual DBH increment (ΔDBH) of an individual tree is central to understanding tree growth and forest ecology. Ecosystem Carbon flux is a consequence of key ecosystem processes in the forest-ecosystem carbon cycle, Gross and Net Primary Production (GPP and NPP, respectively) and Net Ecosystem Respiration (NEP). All of these closely relate with tree DBH changes and tree death. Despite advances in evaluating forest carbon fluxes with flux towers and forest inventories for individual tree ΔDBH, few current ecological models can simultaneously quantify and predict the tree ΔDBH and forest carbon flux.

Teachers’ individual action theories about competence-based education: the value of the cognitive apprenticeship model

NARCIS (Netherlands)

Seezink, Audrey; Poell, Rob; Kirschner, Paul A.

2009-01-01

Seezink, A., Poell, R. F., & Kirschner, P. A. (2009). Teachers' individual action theories about competence-based education: The value of the cognitive apprenticeship model. Journal of Vocational Education & Training, 61, 203-215.

Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

Science.gov (United States)

Ginovart, Marta

2014-01-01

The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study…

A stepwise model to predict monthly streamflow

Science.gov (United States)

Mahmood Al-Juboori, Anas; Guven, Aytac

2016-12-01

In this study, a stepwise model empowered with genetic programming is developed to predict the monthly flows of Hurman River in Turkey and Diyalah and Lesser Zab Rivers in Iraq. The model divides the monthly flow data to twelve intervals representing the number of months in a year. The flow of a month, t is considered as a function of the antecedent month's flow (t - 1) and it is predicted by multiplying the antecedent monthly flow by a constant value called K. The optimum value of K is obtained by a stepwise procedure which employs Gene Expression Programming (GEP) and Nonlinear Generalized Reduced Gradient Optimization (NGRGO) as alternative to traditional nonlinear regression technique. The degree of determination and root mean squared error are used to evaluate the performance of the proposed models. The results of the proposed model are compared with the conventional Markovian and Auto Regressive Integrated Moving Average (ARIMA) models based on observed monthly flow data. The comparison results based on five different statistic measures show that the proposed stepwise model performed better than Markovian model and ARIMA model. The R2 values of the proposed model range between 0.81 and 0.92 for the three rivers in this study.

Mean square stabilization and mean square exponential stabilization of stochastic BAM neural networks with Markovian jumping parameters

International Nuclear Information System (INIS)

Ye, Zhiyong; Zhang, He; Zhang, Hongyu; Zhang, Hua; Lu, Guichen

2015-01-01

Highlights: •This paper introduces a non-conservative Lyapunov functional. •The achieved results impose non-conservative and can be widely used. •The conditions are easily checked by the Matlab LMI Tool Box. The desired state feedback controller can be well represented by the conditions. -- Abstract: This paper addresses the mean square exponential stabilization problem of stochastic bidirectional associative memory (BAM) neural networks with Markovian jumping parameters and time-varying delays. By establishing a proper Lyapunov–Krasovskii functional and combining with LMIs technique, several sufficient conditions are derived for ensuring exponential stabilization in the mean square sense of such stochastic BAM neural networks. In addition, the achieved results are not difficult to verify for determining the mean square exponential stabilization of delayed BAM neural networks with Markovian jumping parameters and impose less restrictive and less conservative than the ones in previous papers. Finally, numerical results are given to show the effectiveness and applicability of the achieved results

Consensus of multiple autonomous underwater vehicles with double independent Markovian switching topologies and timevarying delays

International Nuclear Information System (INIS)

Yan Zhe-Ping; Liu Yi-Bo; Zhou Jia-Jia; Zhang Wei; Wang Lu

2017-01-01

A new method in which the consensus algorithm is used to solve the coordinate control problems of leaderless multiple autonomous underwater vehicles (multi-AUVs) with double independent Markovian switching communication topologies and time-varying delays among the underwater sensors is investigated. This is accomplished by first dividing the communication topology into two different switching parts, i.e., velocity and position, to reduce the data capacity per data package sent between the multi-AUVs in the ocean. Then, the state feedback linearization is used to simplify and rewrite the complex nonlinear and coupled mathematical model of the AUVs into a double-integrator dynamic model. Consequently, coordinate control of the multi-AUVs is regarded as an approximating consensus problem with various time-varying delays and velocity and position topologies. Considering these factors, sufficient conditions of consensus control are proposed and analyzed and the stability of the multi-AUVs is proven by Lyapunov–Krasovskii theorem. Finally, simulation results that validate the theoretical results are presented. (paper)

Bivalves: From individual to population modelling

NARCIS (Netherlands)

Saraiva, S.; van der Meer, J.; Kooijman, S.A.L.M.

2014-01-01

An individual based population model for bivalves was designed, built and tested in a 0D approach, to simulate the population dynamics of a mussel bed located in an intertidal area. The processes at the individual level were simulated following the dynamic energy budget theory, whereas initial egg

Contrast of degraded and restored stream habitat using an individual-based salmon model

Science.gov (United States)

S. F. Railsback; M. Gard; Bret Harvey; Jason White; J.K.H. Zimmerman

2013-01-01

Stream habitat restoration projects are popular, but can be expensive and difficult to evaluate. We describe inSALMO, an individual-based model designed to predict habitat effects on freshwater life stages (spawning through juvenile out-migration) of salmon. We applied inSALMO to Clear Creek, California, simulating the production of total and large (>5 cm FL)...

Profit-Based Model Selection for Customer Retention Using Individual Customer Lifetime Values.

Science.gov (United States)

Óskarsdóttir, María; Baesens, Bart; Vanthienen, Jan

2018-03-01

The goal of customer retention campaigns, by design, is to add value and enhance the operational efficiency of businesses. For organizations that strive to retain their customers in saturated, and sometimes fast moving, markets such as the telecommunication and banking industries, implementing customer churn prediction models that perform well and in accordance with the business goals is vital. The expected maximum profit (EMP) measure is tailored toward this problem by taking into account the costs and benefits of a retention campaign and estimating its worth for the organization. Unfortunately, the measure assumes fixed and equal customer lifetime value (CLV) for all customers, which has been shown to not correspond well with reality. In this article, we extend the EMP measure to take into account the variability in the lifetime values of customers, thereby basing it on individual characteristics. We demonstrate how to incorporate the heterogeneity of CLVs when CLVs are known, when their prior distribution is known, and when neither is known. By taking into account individual CLVs, our proposed approach of measuring model performance gives novel insights when deciding on a customer retention campaign. The method is dependent on the characteristics of the customer base as is compliant with modern business analytics and accommodates the data-driven culture that has manifested itself within organizations.

Adaptive Asymptotical Synchronization for Stochastic Complex Networks with Time-Delay and Markovian Switching

Directory of Open Access Journals (Sweden)

Xueling Jiang

2014-01-01

Full Text Available The problem of adaptive asymptotical synchronization is discussed for the stochastic complex dynamical networks with time-delay and Markovian switching. By applying the stochastic analysis approach and the M-matrix method for stochastic complex networks, several sufficient conditions to ensure adaptive asymptotical synchronization for stochastic complex networks are derived. Through the adaptive feedback control techniques, some suitable parameters update laws are obtained. Simulation result is provided to substantiate the effectiveness and characteristics of the proposed approach.

Ultrafast dynamics of laser-pulse excited semiconductors: non-Markovian quantum kinetic equations with nonequilibrium correlations

Directory of Open Access Journals (Sweden)

V.V.Ignatyuk

2004-01-01

Full Text Available Non-Markovian kinetic equations in the second Born approximation are derived for a two-zone semiconductor excited by a short laser pulse. Both collision dynamics and running nonequilibrium correlations are taken into consideration. The energy balance and relaxation of the system to equilibrium are discussed. Results of numerical solution of the kinetic equations for carriers and phonons are presented.

Use of a model for 3D image reconstruction

International Nuclear Information System (INIS)

Delageniere, S.; Grangeat, P.

1991-01-01

We propose a software for 3D image reconstruction in transmission tomography. This software is based on the use of a model and of the RADON algorithm developed at LETI. The introduction of a markovian model helps us to enhance contrast and straitened the natural transitions existing in the objects studied, whereas standard transform methods smoothe them

Non-Markovian modification of the golden rule rate expression

International Nuclear Information System (INIS)

Basilevsky, M. V.; Davidovich, G. V.; Titov, S. V.; Voronin, A. I.

2006-01-01

The reformulation of the standard golden rule approach considered in this paper for treating reactive tunneling reduces the computation of the reaction rate to a derivation of band shapes for energy levels of reactant and product states. This treatment is based on the assumption that the medium environment is actively involved as a partner in the energy exchange with the reactive subsystem but its reorganization effect is negligible. Starting from the quantum relaxation equation for the density matrix, the required band shapes are represented in terms of the spectral density function, exhibiting the continuum spectrum inherent to the interaction between the reactants and the medium in the total reactive system. The simplest Lorentzian spectral bands, obtained under Redfield approximation, proved to be unsatisfactory because they produced a divergent rate expression at low temperature. The problem is resolved by invoking a refined spectral band shape, which behaves as Lorentzian one at the band center but decays exponentially at its tails. The corresponding closed non-Markovian rate expression is derived and investigated taking as an example the photochemical H-transfer reaction between fluorene and acridine proceeding in the fluorene molecular crystal. The kinetics in this reactive system was thoroughly studied experimentally in a wide temperature range [B. Prass et al., Ber. Bunsenges. Phys. Chem. 102, 498 (1998)

Innovations in individual feature history management - The significance of feature-based temporal model

Science.gov (United States)

Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

2008-01-01

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

Individual-based model for radiation risk assessment

Science.gov (United States)

Smirnova, O.

A mathematical model is developed which enables one to predict the life span probability for mammals exposed to radiation. It relates statistical biometric functions with statistical and dynamic characteristics of an organism's critical system. To calculate the dynamics of the latter, the respective mathematical model is used too. This approach is applied to describe the effects of low level chronic irradiation on mice when the hematopoietic system (namely, thrombocytopoiesis) is the critical one. For identification of the joint model, experimental data on hematopoiesis in nonirradiated and irradiated mice, as well as on mortality dynamics of those in the absence of radiation are utilized. The life span probability and life span shortening predicted by the model agree with corresponding experimental data. Modeling results show the significance of ac- counting the variability of the individual radiosensitivity of critical system cells when estimating the radiation risk. These findings are corroborated by clinical data on persons involved in the elimination of the Chernobyl catastrophe after- effects. All this makes it feasible to use the model for radiation risk assessments for cosmonauts and astronauts on long-term missions such as a voyage to Mars or a lunar colony. In this case the model coefficients have to be determined by making use of the available data for humans. Scenarios for the dynamics of dose accumulation during space flights should also be taken into account.

Solving the master equation without kinetic Monte Carlo: Tensor train approximations for a CO oxidation model

International Nuclear Information System (INIS)

Gelß, Patrick; Matera, Sebastian; Schütte, Christof

2016-01-01

In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO 2 (110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.

Solving the master equation without kinetic Monte Carlo: Tensor train approximations for a CO oxidation model

Science.gov (United States)

Gelß, Patrick; Matera, Sebastian; Schütte, Christof

2016-06-01

In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO2(110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.

Solving the master equation without kinetic Monte Carlo: Tensor train approximations for a CO oxidation model

Energy Technology Data Exchange (ETDEWEB)

Gelß, Patrick, E-mail: p.gelss@fu-berlin.de; Matera, Sebastian, E-mail: matera@math.fu-berlin.de; Schütte, Christof, E-mail: schuette@mi.fu-berlin.de

2016-06-01

In multiscale modeling of heterogeneous catalytic processes, one crucial point is the solution of a Markovian master equation describing the stochastic reaction kinetics. Usually, this is too high-dimensional to be solved with standard numerical techniques and one has to rely on sampling approaches based on the kinetic Monte Carlo method. In this study we break the curse of dimensionality for the direct solution of the Markovian master equation by exploiting the Tensor Train Format for this purpose. The performance of the approach is demonstrated on a first principles based, reduced model for the CO oxidation on the RuO{sub 2}(110) surface. We investigate the complexity for increasing system size and for various reaction conditions. The advantage over the stochastic simulation approach is illustrated by a problem with increased stiffness.

A finite capacity queue with Markovian arrivals and two servers with group services

Directory of Open Access Journals (Sweden)

S. Chakravarthy

1994-01-01

Full Text Available In this paper we consider a finite capacity queuing system in which arrivals are governed by a Markovian arrival process. The system is attended by two exponential servers, who offer services in groups of varying sizes. The service rates may depend on the number of customers in service. Using Markov theory, we study this finite capacity queuing model in detail by obtaining numerically stable expressions for (a the steady-state queue length densities at arrivals and at arbitrary time points; (b the Laplace-Stieltjes transform of the stationary waiting time distribution of an admitted customer at points of arrivals. The stationary waiting time distribution is shown to be of phase type when the interarrival times are of phase type. Efficient algorithmic procedures for computing the steady-state queue length densities and other system performance measures are discussed. A conjecture on the nature of the mean waiting time is proposed. Some illustrative numerical examples are presented.

Stochastic quantization of a topological quantum mechanical model

International Nuclear Information System (INIS)

Antunes, Sergio; Krein, Gastao; Menezes, Gabriel; Svaiter, Nami Fux

2011-01-01

Full text: Stochastic quantization of complex actions has been extensively studied in the literature. In these models, a Markovian Langevin equation is used in order to study the quantization of such systems. In such papers, the advantages of the Markovian stochastic quantization method were explored and exposed. However, many drawbacks of the method were also pointed out, such as instability of the simulations with absence of convergence and sometimes convergence to the wrong limit. Indeed, although several alternative methods have been proposed to deal with interesting physical systems where the action is complex, these approaches do not suggest any general way of solving the particular difficulties that arise in each situation. Here, we wish to make contributions to the program of stochastic quantization of theories with imaginary action by investigating the consequences of a non-Markovian stochastic quantization in a particular situation, namely a quantum mechanical topological action. We analyze the Markovian stochastic quantization for a topological quantum mechanical action which is analog to a Maxwell-Chern-Simons action in the Weyl gauge. Afterwards we consider a Langevin equation with memory kernel and Einstein's relations with colored noise. We show that convergence towards equilibrium is achieved in both regimes. We also sketch a simple numerical analysis to investigate the possible advantages of non-Markovian procedure over the usual Markovian quantization. Both retarded Green's function for the diffusion problem are considered in such analysis. We show that, although the results indicated that the effect of memory kernel, as usually expected, is to delay the convergence to equilibrium, non-Markovian systems imply a faster decay compared to Markovian ones as well as smoother convergence to equilibrium. (author)

Markov Models for Handwriting Recognition

CERN Document Server

Plotz, Thomas

2011-01-01

Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden

Are individual based models a suitable approach to estimate population vulnerability? - a case study

Directory of Open Access Journals (Sweden)

Eva Maria Griebeler

2011-04-01

Full Text Available European populations of the Large Blue Butterfly Maculinea arion have experienced severe declines in the last decades, especially in the northern part of the species range. This endangered lycaenid butterfly needs two resources for development: flower buds of specific plants (Thymus spp., Origanum vulgare, on which young caterpillars briefly feed, and red ants of the genus Myrmica, whose nests support caterpillars during a prolonged final instar. I present an analytically solvable deterministic model to estimate the vulnerability of populations of M. arion. Results obtained from the sensitivity analysis of this mathematical model (MM are contrasted to the respective results that had been derived from a spatially explicit individual based model (IBM for this butterfly. I demonstrate that details in landscape configuration which are neglected by the MM but are easily taken into consideration by the IBM result in a different degree of intraspecific competition of caterpillars on flower buds and within host ant nests. The resulting differences in mortalities of caterpillars lead to erroneous estimates of the extinction risk of a butterfly population living in habitat with low food plant coverage and low abundance in host ant nests. This observation favors the use of an individual based modeling approach over the deterministic approach at least for the management of this threatened butterfly.

Recursive approach for non-Markovian time-convolutionless master equations

Science.gov (United States)

Gasbarri, G.; Ferialdi, L.

2018-02-01

We consider a general open system dynamics and we provide a recursive method to derive the associated non-Markovian master equation in a perturbative series. The approach relies on a momenta expansion of the open system evolution. Unlike previous perturbative approaches of this kind, the method presented in this paper provides a recursive definition of each perturbative term. Furthermore, we give an intuitive diagrammatic description of each term of the series, which provides a useful analytical tool to build them and to derive their structure in terms of commutators and anticommutators. We eventually apply our formalism to the evolution of the observables of the reduced system, by showing how the method can be applied to the adjoint master equation, and by developing a diagrammatic description of the associated series.

Nodal infection in Markovian susceptible-infected-susceptible and susceptible-infected-removed epidemics on networks are non-negatively correlated.

Science.gov (United States)

Cator, E; Van Mieghem, P

2014-05-01

By invoking the famous Fortuin, Kasteleyn, and Ginibre (FKG) inequality, we prove the conjecture that the correlation of infection at the same time between any pair of nodes in a network cannot be negative for (exact) Markovian susceptible-infected-susceptible (SIS) and susceptible-infected-removed (SIR) epidemics on networks. The truth of the conjecture establishes that the N-intertwined mean-field approximation (NIMFA) upper bounds the infection probability in any graph so that network design based on NIMFA always leads to safe protections against malware spread. However, when the infection or/and curing are not Poisson processes, the infection correlation between two nodes can be negative.

Nodal infection in Markovian susceptible-infected-susceptible and susceptible-infected-removed epidemics on networks are non-negatively correlated

Science.gov (United States)

Cator, E.; Van Mieghem, P.

2014-05-01

By invoking the famous Fortuin, Kasteleyn, and Ginibre (FKG) inequality, we prove the conjecture that the correlation of infection at the same time between any pair of nodes in a network cannot be negative for (exact) Markovian susceptible-infected-susceptible (SIS) and susceptible-infected-removed (SIR) epidemics on networks. The truth of the conjecture establishes that the N-intertwined mean-field approximation (NIMFA) upper bounds the infection probability in any graph so that network design based on NIMFA always leads to safe protections against malware spread. However, when the infection or/and curing are not Poisson processes, the infection correlation between two nodes can be negative.

Calculation of Individual Tree Water Use in a Bornean Tropical Rain Forest Using Individual-Based Dynamic Vegetation Model SEIB-DGVM

Science.gov (United States)

Nakai, T.; Kumagai, T.; Saito, T.; Matsumoto, K.; Kume, T.; Nakagawa, M.; Sato, H.

2015-12-01

Bornean tropical rain forests are among the moistest biomes of the world with abundant rainfall throughout the year, and considered to be vulnerable to a change in the rainfall regime; e.g., high tree mortality was reported in such forests induced by a severe drought associated with the ENSO event in 1997-1998. In order to assess the effect (risk) of future climate change on eco-hydrology in such tropical rain forests, it is important to understand the water use of trees individually, because the vulnerability or mortality of trees against climate change can depend on the size of trees. Therefore, we refined the Spatially Explicit Individual-Based Dynamic Global Vegetation Model (SEIB-DGVM) so that the transpiration and its control by stomata are calculated for each individual tree. By using this model, we simulated the transpiration of each tree and its DBH-size dependency, and successfully reproduced the measured data of sap flow of trees and eddy covariance flux data obtained in a Bornean lowland tropical rain forest in Lambir Hills National Park, Sarawak, Malaysia.

Global exponential stability of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays.

Science.gov (United States)

Huang, Haiying; Du, Qiaosheng; Kang, Xibing

2013-11-01

In this paper, a class of neutral high-order stochastic Hopfield neural networks with Markovian jump parameters and mixed time delays is investigated. The jumping parameters are modeled as a continuous-time finite-state Markov chain. At first, the existence of equilibrium point for the addressed neural networks is studied. By utilizing the Lyapunov stability theory, stochastic analysis theory and linear matrix inequality (LMI) technique, new delay-dependent stability criteria are presented in terms of linear matrix inequalities to guarantee the neural networks to be globally exponentially stable in the mean square. Numerical simulations are carried out to illustrate the main results. © 2013 ISA. Published by ISA. All rights reserved.

Non-Markovian decay of a three-level cascade atom in a structured reservoir

International Nuclear Information System (INIS)

Dalton, B.J.; Garraway, B.M.

2003-01-01

The dynamics of a three-level atom in a cascade (or ladder) configuration with both transitions coupled to a single structured reservoir of quantized electromagnetic field modes is treated using Laplace transform methods applied to the coupled amplitude equations. In this system two-photon excitation of the reservoir occurs, and both sequences for emitting the two photons are allowed and included in the theory. An integral equation is found to govern the complex amplitudes of interest. It is shown that the dynamics of the atomic system is completely determined in terms of reservoir structure functions, which are products of the mode density with the coupling constant squared. This dependence on reservoir structure functions rather than on the mode density or coupling constants alone, shows that it may be possible to extend pseudomode theory to treat multiphoton excitation of a structured reservoir--pseudomodes being introduced in one-one correspondence with the poles of reservoir structure functions in the complex frequency plane. A general numerical method for solving the integral equations based on discretizing frequency space, and applicable to different structured reservoirs such as high-Q cavities and photonic band-gap systems, is presented. An application to a high-Q-cavity case with identical Lorentzian reservoir structure functions is made, and the non-Markovian decay of the excited state shown. A formal solution to the integral equations in terms of right and left eigenfunctions of a non-Hermitian kernel is also given. The dynamics of the cascade atom, with the two transitions coupled to two separate structured reservoirs of quantized electromagnetic field modes, is treated similarly to the single structured reservoir situation. Again the dynamics only depends on reservoir structure functions. As only one sequence of emitting the two photons now occurs, the integral equation for the amplitudes can be solved analytically. The non-Markovian decay of the

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

Science.gov (United States)

Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J

2014-01-01

Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

Modelling hen harrier dynamics to inform human-wildlife conflict resolution: a spatially-realistic, individual-based approach.

Directory of Open Access Journals (Sweden)

Johannes P M Heinonen

Full Text Available Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.

DISPLACE: a dynamic, individual-based model for spatial fishing planning and effort displacement: Integrating underlying fish population models

DEFF Research Database (Denmark)

Bastardie, Francois; Nielsen, J. Rasmus; Miethe, Tanja

or to the alteration of individual fishing patterns. We demonstrate that integrating the spatial activity of vessels and local fish stock abundance dynamics allow for interactions and more realistic predictions of fishermen behaviour, revenues and stock abundance......We previously developed a spatially explicit, individual-based model (IBM) evaluating the bio-economic efficiency of fishing vessel movements between regions according to the catching and targeting of different species based on the most recent high resolution spatial fishery data. The main purpose...... was to test the effects of alternative fishing effort allocation scenarios related to fuel consumption, energy efficiency (value per litre of fuel), sustainable fish stock harvesting, and profitability of the fisheries. The assumption here was constant underlying resource availability. Now, an advanced...

A cell-to-cell Markovian model for the reliability of a digital control system of a steam generator

International Nuclear Information System (INIS)

Gomes, Ian B.; Melo, Paulo F.F. Frutuoso e; Saldanha, Pedro L.C.

2013-01-01

With the shift of technology from analog to digital systems, due to the obsolescence of the older analog systems and the functional advantages of the digital ones, existing nuclear power plants have begun to replace their systems, while newer plants use digital systems from the beginning of their construction. However, the process of risk-informed analysis for digital systems has not been satisfactorily developed yet. Traditional methods, such as fault trees, have limitations, while dynamic methods are still in the tests stage and may be difficult to be applied to a real size probabilistic safety assessment (PSA) model. The objective of this paper is to study and obtain a better comprehension of the Markov/CCMT method, a method that combines the traditional Markovian methodology with the cell-to-cell mapping technique for representing the possible failure events that can be originated in the dynamic interactions between the instrumentation and control system and the controlled process, and among the various components of the digital system. The study consists of the simulation of a digital water level control system of the steam generator of a PWR plant. From this simulation, a Failure Modes and Effects Analysis (FMEA) was made and the information obtained was used to calculate the system reliability, using the Markov/CCMT methodology. The results show that the method is capable of identifying the most probable causes for a possible failure of the digital system. (author)

Non-Markovian reduced dynamics of ultrafast charge transfer at an oligothiophene–fullerene heterojunction

Energy Technology Data Exchange (ETDEWEB)

Hughes, Keith H., E-mail: keith.hughes@bangor.ac.uk [School of Chemistry, Bangor University, Bangor, Gwynedd LL57 2UW (United Kingdom); Cahier, Benjamin [School of Chemistry, Bangor University, Bangor, Gwynedd LL57 2UW (United Kingdom); Martinazzo, Rocco [Dipartimento di Chimica Università degli Studi di Milano, v. Golgi 19, 20133 Milano (Italy); Tamura, Hiroyuki [WPI-Advanced Institute for Material Research, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai 980-8577 (Japan); Burghardt, Irene [Institute of Physical and Theoretical Chemistry, Goethe University Frankfurt, Max-von-Laue-Str. 7, 60438 Frankfurt/Main (Germany)

2014-10-17

Highlights: • Quantum dynamical study of exciton dissociation at a heterojunction interface. • The non-Markovian quantum dynamics involves a highly structured spectral density. • Spectral density is reconstructed from an effective mode transformation of the Hamiltonian. • The dynamics is studied using the hierarchical equations of motion approach. • It was found that the temperature has little effect on the charge transfer. - Abstract: We extend our recent quantum dynamical study of the exciton dissociation and charge transfer at an oligothiophene–fullerene heterojunction interface (Tamura et al., 2012) [6] by investigating the process using the non-perturbative hierarchical equations of motion (HEOM) approach. Based upon an effective mode reconstruction of the spectral density the effect of temperature on the charge transfer is studied using reduced density matrices. It was found that the temperature had little effect on the charge transfer and a coherent dynamics persists over the first few tens of femtoseconds, indicating that the primary charge transfer step proceeds by an activationless pathway.

Analysis of Sensitivity and Uncertainty in an Individual-Based Model of a Threatened Wildlife Species

Science.gov (United States)

We present a multi-faceted sensitivity analysis of a spatially explicit, individual-based model (IBM) (HexSim) of a threatened species, the Northern Spotted Owl (Strix occidentalis caurina) on a national forest in Washington, USA. Few sensitivity analyses have been conducted on ...

Fish Individual-based Numerical Simulator (FINS): A particle-based model of juvenile salmonid movement and dissolved gas exposure history in the Columbia River Basin

International Nuclear Information System (INIS)

Scheibe, Timothy D.; Richmond, Marshall C.

2002-01-01

This paper describes a numerical model of juvenile salmonid migration in the Columbia and Snake Rivers. The model, called the Fish Individual-based Numerical Simulator or FINS, employs a discrete, particle-based approach to simulate the migration and history of exposure to dissolved gases of individual fish. FINS is linked to a two-dimensional (vertically-averaged) hydrodynamic simulator that quantifies local water velocity, temperature, and dissolved gas levels as a function of river flow rates and dam operations. Simulated gas exposure histories can be input to biological mortality models to predict the effects of various river configurations on fish injury and mortality due to dissolved gas supersaturation. Therefore, FINS serves as a critical linkage between hydrodynamic models of the river system and models of biological impacts. FINS was parameterized and validated based on observations of individual fish movements collected using radiotelemetry methods during 1997 and 1998 . A quasi-inverse approach was used to decouple fish swimming movements from advection with the local water velocity, allowing inference of time series of non-advective displacements of individual fish from the radiotelemetry data. Statistical analyses of these displacements are presented, and confirm that strong temporal correlation of fish swimming behavior persists in some cases over several hours. A correlated random-walk model was employed to simulate the observed migration behavior, and parameters of the model were estimated that lead to close correspondence between predictions and observations

Agent Based Individual Traffic guidance

DEFF Research Database (Denmark)

Wanscher, Jørgen Bundgaard

2004-01-01

When working with traffic planning or guidance it is common practice to view the vehicles as a combined mass. >From this models are employed to specify the vehicle supply and demand for each region. As the models are complex and the calculations are equally demanding the regions and the detail...... of the road network is aggregated. As a result the calculations reveal only what the mass of vehicles are doing and not what a single vehicle is doing. This is the crucial difference to ABIT (Agent Based Individual Trafficguidance). ABIT is based on the fact that information on the destination of each vehicle...

Synchronization of stochastic delayed neural networks with markovian switching and its application.

Science.gov (United States)

Tang, Yang; Fang, Jian-An; Miao, Qing-Ying

2009-02-01

In this paper, the problem of adaptive synchronization for a class of stochastic neural networks (SNNs) which involve both mixed delays and Markovian jumping parameters is investigated. The mixed delays comprise the time-varying delays and distributed delays, both of which are mode-dependent. The stochastic perturbations are described in terms of Browian motion. By the adaptive feedback technique, several sufficient criteria have been proposed to ensure the synchronization of SNNs in mean square. Moreover, the proposed adaptive feedback scheme is applied to the secure communication. Finally, the corresponding simulation results are given to demonstrate the usefulness of the main results obtained.

Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

Directory of Open Access Journals (Sweden)

Richard P Mann

2012-01-01

Full Text Available Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis. We show that these exhibit a stereotypical 'phase transition', whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have 'memory' of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture fine scale rules of interaction, which are primarily mediated by physical contact. Conversely, the Markovian self-propelled particle model captures the fine scale rules of interaction but fails to reproduce global dynamics. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.

Gap models and their individual-based relatives in the assessment of the consequences of global change

Science.gov (United States)

Shugart, Herman H.; Wang, Bin; Fischer, Rico; Ma, Jianyong; Fang, Jing; Yan, Xiaodong; Huth, Andreas; Armstrong, Amanda H.

2018-03-01

Individual-based models (IBMs) of complex systems emerged in the 1960s and early 1970s, across diverse disciplines from astronomy to zoology. Ecological IBMs arose with seemingly independent origins out of the tradition of understanding the ecosystems dynamics of ecosystems from a ‘bottom-up’ accounting of the interactions of the parts. Individual trees are principal among the parts of forests. Because these models are computationally demanding, they have prospered as the power of digital computers has increased exponentially over the decades following the 1970s. This review will focus on a class of forest IBMs called gap models. Gap models simulate the changes in forests by simulating the birth, growth and death of each individual tree on a small plot of land. The summation of these plots comprise a forest (or set of sample plots on a forested landscape or region). Other, more aggregated forest IBMs have been used in global applications including cohort-based models, ecosystem demography models, etc. Gap models have been used to provide the parameters for these bulk models. Currently, gap models have grown from local-scale to continental-scale and even global-scale applications to assess the potential consequences of climate change on natural forests. Modifications to the models have enabled simulation of disturbances including fire, insect outbreak and harvest. Our objective in this review is to provide the reader with an overview of the history, motivation and applications, including theoretical applications, of these models. In a time of concern over global changes, gap models are essential tools to understand forest responses to climate change, modified disturbance regimes and other change agents. Development of forest surveys to provide the starting points for simulations and better estimates of the behavior of the diversity of tree species in response to the environment are continuing needs for improvement for these and other IBMs.

Noise spectrum of quantum transport through double quantum dots: Renormalization and non-Markovian effects

Directory of Open Access Journals (Sweden)

Pengqin Shi

2016-09-01

Full Text Available Based on the time-nonlocal particle number-resolved master equation, we investigate the sequential electron transport through the interacting double quantum dots. Our calculations show that there exists the effect of energy renormalization in the dispersion of the bath interaction spectrum and it is sensitive to the the bandwidth of the bath. This effect would strongly affect the stationary current and its zero-frequency shot noise for weak inter-dot coherent coupling strength, but for strong inter-dot coupling regime, it is negligible due to the strong intrinsic Rabi coherent dynamics. Moreover, the possible observable effects of the energy renormalization in the noise spectrum are also investigated through the Rabi coherence signal. Finally, the non-Markovian effect is manifested in the finite-frequency noise spectrum with the appearance of quasisteps, and the magnitude of these quasisteps are modified by the dispersion function.

Fokker-Planck modeling of pitting corrosion in underground pipelines

Energy Technology Data Exchange (ETDEWEB)

Camacho, Eliana Nogueira [Risco Ambiental Engenharia, Rio de Janeiro, RJ (Brazil); Melo, Paulo F. Frutuoso e [Coordenacao dos Programas de Pos-Graduacao de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear; Saldanha, Pedro Luiz C. [Comissao Nacional de Energia Nuclear (CGRC/CNEN), Rio de Janeiro, RJ (Brazil). Coordenacao Geral de Reatores e Ciclo do Combustivel; Silva, Edson de Pinho da [Universidade Federal Rural do Rio de Janeiro (UFRRJ), Seropedica, RJ (Brazil). Dept. of Physics

2011-07-01

Full text: The stochastic nature of pitting corrosion has been recognized since the 1930s. It has been learned that this damage retains no memory of its past. Instead, the future state is determined only by the knowledge of its present state. This Markovian property that underlies the stochastic process governing pitting corrosion has been explored as a discrete Markovian process by many authors since the beginning of the 1990s for underground pipelines of the oil and gas industries and nuclear power plants. Corrosion is a genuine continuous time and space state Markovian process, so to model it as a discrete time and/or state space is an approximation to the problem. Markovian chains approaches, with an increasing number of states, could involve a large number of parameters, the transition rates between states, to be experimentally determined. Besides, such an increase in the number of states produces matrices with huge dimensions leading to time-consuming computational solutions. Recent approaches involving Markovian discrete process have overcome those difficulties but, on the other hand, a large number of soil and pipe stochastic variables have to be known. In this work we propose a continuous time and space state approach to the evolution of pit corrosion depths in underground pipelines. In order to illustrate the application of the model for defect depth growth a combination of real life data and Monte Carlo simulation was used. The process is described by a Fokker-Planck equation. The Fokker-Planck equation is completely determined by the knowledge of two functions known as the drift and diffusion coefficients. In this work we also show that those functions can be estimated from corrosion depth data from in-line inspections. Some particular forms of drift and diffusion coefficients lead to particular Fokker-Planck equations for which analytical solutions are known, as is the case for the Wiener process, the Ornstein-Uhlenbeck process and the Brownian motion

Decoherence suppression of tripartite entanglement in non-Markovian environments by using weak measurements

Energy Technology Data Exchange (ETDEWEB)

Ding, Zhi-yong [School of Physics & Material Science, Anhui University, Hefei 230039 (China); School of Physics & Electronic Engineering, Fuyang Normal University, Fuyang 236037 (China); He, Juan, E-mail: juanhe78@163.com [School of Physics & Electronic Engineering, Fuyang Normal University, Fuyang 236037 (China); Ye, Liu, E-mail: yeliu@ahu.edu.cn [School of Physics & Material Science, Anhui University, Hefei 230039 (China)

2017-02-15

A feasible scheme for protecting the Greenberger–Horne–Zeilinger (GHZ) entanglement state in non-Markovian environments is proposed. It consists of prior weak measurement on each qubit before the interaction with decoherence environments followed by post quantum measurement reversals. It is shown that both the fidelity and concurrence of the GHZ state can be effectively improved. Meanwhile, we also verified that our scenario can enhance tripartite nonlocality remarkably. In addition, the result indicates that the larger the weak measurement strength, the better the effectiveness of the scheme with the lower success probability.

Projected metastable Markov processes and their estimation with observable operator models

International Nuclear Information System (INIS)

Wu, Hao; Prinz, Jan-Hendrik; Noé, Frank

2015-01-01

The determination of kinetics of high-dimensional dynamical systems, such as macromolecules, polymers, or spin systems, is a difficult and generally unsolved problem — both in simulation, where the optimal reaction coordinate(s) are generally unknown and are difficult to compute, and in experimental measurements, where only specific coordinates are observable. Markov models, or Markov state models, are widely used but suffer from the fact that the dynamics on a coarsely discretized state spaced are no longer Markovian, even if the dynamics in the full phase space are. The recently proposed projected Markov models (PMMs) are a formulation that provides a description of the kinetics on a low-dimensional projection without making the Markovianity assumption. However, as yet no general way of estimating PMMs from data has been available. Here, we show that the observed dynamics of a PMM can be exactly described by an observable operator model (OOM) and derive a PMM estimator based on the OOM learning

Improved delay-dependent globally asymptotic stability of delayed uncertain recurrent neural networks with Markovian jumping parameters

International Nuclear Information System (INIS)

Yan, Ji; Bao-Tong, Cui

2010-01-01

In this paper, we have improved delay-dependent stability criteria for recurrent neural networks with a delay varying over a range and Markovian jumping parameters. The criteria improve over some previous ones in that they have fewer matrix variables yet less conservatism. In addition, a numerical example is provided to illustrate the applicability of the result using the linear matrix inequality toolbox in MATLAB. (general)

Markovianity in space and time : [dedicated to Professor Mike Keane on the occasion of his 65th birthday

NARCIS (Netherlands)

M.N.M. van Lieshout (Marie-Colette)

2005-01-01

textabstractMarkov chains in time, such as simple random walks, are at the heart of probability. In space, due to the absence of an obvious definition of past and future, a range of definitions of Markovianity have been proposed. In this paper, after a brief review, we introduce a new concept of

Entanglement backflow under the composite effect of two non-Markovian reservoirs

International Nuclear Information System (INIS)

Li, Jun-Gang; Zou, Jian; Shao, Bin

2012-01-01

The entanglement backflow of two qubits coupled to two independent reservoirs is investigated. It is found that under the collective effects of the two independent reservoirs, the entanglement backflow of the qubits does not always increase with the increase of the non-Markovianity of one of the reservoirs but demonstrates an intricate behavior. Interestingly, the action of one reservoir can affect the other reservoir's contribution to the entanglement backflow even when the two reservoirs are independent. -- Highlights: ► We study entanglement backflow of two qubits coupled to two independent reservoirs. ► We find that the entanglement backflow demonstrates an intricate behavior. ► The action of one reservoir can affect the contribution of the other reservoir.

Heterozygosity in an isolated population of a large mammal founded by four individuals is predicted by an individual-based genetic model.

Directory of Open Access Journals (Sweden)

Jaana Kekkonen

Full Text Available Within-population genetic diversity is expected to be dramatically reduced if a population is founded by a low number of individuals. Three females and one male white-tailed deer Odocoileus virginianus, a North American species, were successfully introduced in Finland in 1934 and the population has since been growing rapidly, but remained in complete isolation from other populations.Based on 14 microsatellite loci, the expected heterozygosity H was 0.692 with a mean allelic richness (AR of 5.36, which was significantly lower than what was found in Oklahoma, U.S.A. (H = 0.742; AR = 9.07, demonstrating that a bottleneck occurred. Observed H was in line with predictions from an individual-based model where the genealogy of the males and females in the population were tracked and the population's demography was included.Our findings provide a rare within-population empirical test of the founder effect and suggest that founding a population by a small number of individuals need not have a dramatic impact on heterozygosity in an iteroparous species.

Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

Science.gov (United States)

Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

2015-10-01

This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spherical particle Brownian motion in viscous medium as non-Markovian random process

International Nuclear Information System (INIS)

Morozov, Andrey N.; Skripkin, Alexey V.

2011-01-01

The Brownian motion of a spherical particle in an infinite medium is described by the conventional methods and integral transforms considering the entrainment of surrounding particles of the medium by the Brownian particle. It is demonstrated that fluctuations of the Brownian particle velocity represent a non-Markovian random process. The features of Brownian motion in short time intervals and in small displacements are considered. -- Highlights: → Description of Brownian motion considering the entrainment of medium is developed. → We find the equations for statistical characteristics of impulse fluctuations. → Brownian motion at small time intervals is considered. → Theoretical results and experimental data are compared.

Stochastic parameterizing manifolds and non-Markovian reduced equations stochastic manifolds for nonlinear SPDEs II

CERN Document Server

Chekroun, Mickaël D; Wang, Shouhong

2015-01-01

In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs). This is accomplished via the concept of parameterizing manifolds (PMs), which are stochastic manifolds that improve, for a given realization of the noise, in mean square error the partial knowledge of the full SPDE solution when compared to its projection onto some resolved modes. Backward-forward systems are designed to give access to such PMs in practice. The key idea consists of representing the modes with high wave numbers as a pullback limit depending on the time-history of the modes with low wave numbers. Non-Markovian stochastic reduced systems are then derived based on such a PM approach. The reduced systems take the form of stochastic differential equations involving random coefficients that convey memory effects. The theory is illustrated on a stochastic Burgers-type equation.

Bivalves: From individual to population modelling

Science.gov (United States)

Saraiva, S.; van der Meer, J.; Kooijman, S. A. L. M.; Ruardij, P.

2014-11-01

An individual based population model for bivalves was designed, built and tested in a 0D approach, to simulate the population dynamics of a mussel bed located in an intertidal area. The processes at the individual level were simulated following the dynamic energy budget theory, whereas initial egg mortality, background mortality, food competition, and predation (including cannibalism) were additional population processes. Model properties were studied through the analysis of theoretical scenarios and by simulation of different mortality parameter combinations in a realistic setup, imposing environmental measurements. Realistic criteria were applied to narrow down the possible combination of parameter values. Field observations obtained in the long-term and multi-station monitoring program were compared with the model scenarios. The realistically selected modeling scenarios were able to reproduce reasonably the timing of some peaks in the individual abundances in the mussel bed and its size distribution but the number of individuals was not well predicted. The results suggest that the mortality in the early life stages (egg and larvae) plays an important role in population dynamics, either by initial egg mortality, larvae dispersion, settlement failure or shrimp predation. Future steps include the coupling of the population model with a hydrodynamic and biogeochemical model to improve the simulation of egg/larvae dispersion, settlement probability, food transport and also to simulate the feedback of the organisms' activity on the water column properties, which will result in an improvement of the food quantity and quality characterization.

Markovian Monte Carlo program EvolFMC v.2 for solving QCD evolution equations

Science.gov (United States)

Jadach, S.; Płaczek, W.; Skrzypek, M.; Stokłosa, P.

2010-02-01

We present the program EvolFMC v.2 that solves the evolution equations in QCD for the parton momentum distributions by means of the Monte Carlo technique based on the Markovian process. The program solves the DGLAP-type evolution as well as modified-DGLAP ones. In both cases the evolution can be performed in the LO or NLO approximation. The quarks are treated as massless. The overall technical precision of the code has been established at 5×10. This way, for the first time ever, we demonstrate that with the Monte Carlo method one can solve the evolution equations with precision comparable to the other numerical methods. New version program summaryProgram title: EvolFMC v.2 Catalogue identifier: AEFN_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEFN_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including binary test data, etc.: 66 456 (7407 lines of C++ code) No. of bytes in distributed program, including test data, etc.: 412 752 Distribution format: tar.gz Programming language: C++ Computer: PC, Mac Operating system: Linux, Mac OS X RAM: Less than 256 MB Classification: 11.5 External routines: ROOT ( http://root.cern.ch/drupal/) Nature of problem: Solution of the QCD evolution equations for the parton momentum distributions of the DGLAP- and modified-DGLAP-type in the LO and NLO approximations. Solution method: Monte Carlo simulation of the Markovian process of a multiple emission of partons. Restrictions:Limited to the case of massless partons. Implemented in the LO and NLO approximations only. Weighted events only. Unusual features: Modified-DGLAP evolutions included up to the NLO level. Additional comments: Technical precision established at 5×10. Running time: For the 10 6 events at 100 GeV: DGLAP NLO: 27s; C-type modified DGLAP NLO: 150s (MacBook Pro with Mac OS X v.10

Counting statistics of transport through Coulomb blockade nanostructures: High-order cumulants and non-Markovian effects

DEFF Research Database (Denmark)

Flindt, Christian; Novotny, Tomás; Braggio, Alessandro

2010-01-01

Recent experimental progress has made it possible to detect in real-time single electrons tunneling through Coulomb blockade nanostructures, thereby allowing for precise measurements of the statistical distribution of the number of transferred charges, the so-called full counting statistics...... interactions. Our recursive method can treat systems with many states as well as non-Markovian dynamics. We illustrate our approach with three examples of current experimental relevance: bunching transport through a two-level quantum dot, transport through a nanoelectromechanical system with dynamical Franck...

Inhomogeneous electrochemiluminescence. II Markovian encounter theory of the phenomenon

International Nuclear Information System (INIS)

Gladkikh, V.; Burshtein, A.I.

2005-01-01

The free energy dependence of the electro-chemiluminescence quantum yield is specified, with the Markovian encounter theory accounting for the reversibility of triplet production competing with the irreversible recombination to the ground state. It is shown that diffusional ion recombination is highly inhomogeneous in space. It proceeds at either large positive ionization free energy (mainly to the triplet product) or at large negative free energy when recombination to the ground state dominates. On the contrary at medium free energies, the quasi-resonant generation of triplets is under kinetic control and therefore much more homogeneous. In this case, both recombination products are generated in comparable amounts. The multiple reversible ionization is shown to act as an independent quenching mechanism previously unknown. The role of the triplet quenching at the electrode is also specified. These effects reduce noticeably the luminescence quantum yield but only at larger triplet life times and in different free energy regions

Quantum theory of multiple-input-multiple-output Markovian feedback with diffusive measurements

International Nuclear Information System (INIS)

Chia, A.; Wiseman, H. M.

2011-01-01

Feedback control engineers have been interested in multiple-input-multiple-output (MIMO) extensions of single-input-single-output (SISO) results of various kinds due to its rich mathematical structure and practical applications. An outstanding problem in quantum feedback control is the extension of the SISO theory of Markovian feedback by Wiseman and Milburn [Phys. Rev. Lett. 70, 548 (1993)] to multiple inputs and multiple outputs. Here we generalize the SISO homodyne-mediated feedback theory to allow for multiple inputs, multiple outputs, and arbitrary diffusive quantum measurements. We thus obtain a MIMO framework which resembles the SISO theory and whose additional mathematical structure is highlighted by the extensive use of vector-operator algebra.

A small community model for the transmission of infectious diseases: comparison of school closure as an intervention in individual-based models of an influenza pandemic.

Directory of Open Access Journals (Sweden)

George J Milne

Full Text Available BACKGROUND: In the absence of other evidence, modelling has been used extensively to help policy makers plan for a potential future influenza pandemic. METHOD: We have constructed an individual based model of a small community in the developed world with detail down to exact household structure obtained from census collection datasets and precise simulation of household demographics, movement within the community and individual contact patterns. We modelled the spread of pandemic influenza in this community and the effect on daily and final attack rates of four social distancing measures: school closure, increased case isolation, workplace non-attendance and community contact reduction. We compared the modelled results of final attack rates in the absence of any interventions and the effect of school closure as a single intervention with other published individual based models of pandemic influenza in the developed world. RESULTS: We showed that published individual based models estimate similar final attack rates over a range of values for R(0 in a pandemic where no interventions have been implemented; that multiple social distancing measures applied early and continuously can be very effective in interrupting transmission of the pandemic virus for R(0 values up to 2.5; and that different conclusions reached on the simulated benefit of school closure in published models appear to result from differences in assumptions about the timing and duration of school closure and flow-on effects on other social contacts resulting from school closure. CONCLUSION: Models of the spread and control of pandemic influenza have the potential to assist policy makers with decisions about which control strategies to adopt. However, attention needs to be given by policy makers to the assumptions underpinning both the models and the control strategies examined.

Analytic Approximation of the Solutions of Stochastic Differential Delay Equations with Poisson Jump and Markovian Switching

Directory of Open Access Journals (Sweden)

Hua Yang

2012-01-01

Full Text Available We are concerned with the stochastic differential delay equations with Poisson jump and Markovian switching (SDDEsPJMSs. Most SDDEsPJMSs cannot be solved explicitly as stochastic differential equations. Therefore, numerical solutions have become an important issue in the study of SDDEsPJMSs. The key contribution of this paper is to investigate the strong convergence between the true solutions and the numerical solutions to SDDEsPJMSs when the drift and diffusion coefficients are Taylor approximations.

Integrated Markov-neural reliability computation method: A case for multiple automated guided vehicle system

International Nuclear Information System (INIS)

Fazlollahtabar, Hamed; Saidi-Mehrabad, Mohammad; Balakrishnan, Jaydeep

2015-01-01

This paper proposes an integrated Markovian and back propagation neural network approaches to compute reliability of a system. While states of failure occurrences are significant elements for accurate reliability computation, Markovian based reliability assessment method is designed. Due to drawbacks shown by Markovian model for steady state reliability computations and neural network for initial training pattern, integration being called Markov-neural is developed and evaluated. To show efficiency of the proposed approach comparative analyses are performed. Also, for managerial implication purpose an application case for multiple automated guided vehicles (AGVs) in manufacturing networks is conducted. - Highlights: • Integrated Markovian and back propagation neural network approach to compute reliability. • Markovian based reliability assessment method. • Managerial implication is shown in an application case for multiple automated guided vehicles (AGVs) in manufacturing networks

Simulation of Drought-induced Tree Mortality Using a New Individual and Hydraulic Trait-based Model (S-TEDy)

Science.gov (United States)

Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H.

2017-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

Bacteria can form interconnected microcolonies when a self-excreted product reduces their surface motility: evidence from individual-based model simulations

DEFF Research Database (Denmark)

Mabrouk, Nabil; Deffuant, Guillaume; Tolker-Nielsen, Tim

2010-01-01

Recent experimental observations of Pseudomonas aeruginosa, a model bacterium in biofilm research, reveal that, under specific growth conditions, bacterial cells form patterns of interconnected microcolonies. In the present work, we use an individual-based model to assess the involvement of bacte......Recent experimental observations of Pseudomonas aeruginosa, a model bacterium in biofilm research, reveal that, under specific growth conditions, bacterial cells form patterns of interconnected microcolonies. In the present work, we use an individual-based model to assess the involvement...... of bacteria motility and self-produced extracellular substance in the formation of these patterns. In our simulations, the pattern of interconnected microcolonies appears only when bacteria motility is reduced by excreted extracellular macromolecules. Immotile bacteria form isolated microcolonies...... and constantly motile bacteria form flat biofilms. Based on experimental data and computer simulations, we suggest a mechanism that could be responsible for these interconnected microcolonies....

Fluctuation relation for heat exchange in Markovian open quantum systems

Science.gov (United States)

Ramezani, M.; Golshani, M.; Rezakhani, A. T.

2018-04-01

A fluctuation relation for the heat exchange of an open quantum system under a thermalizing Markovian dynamics is derived. We show that the probability that the system absorbs an amount of heat from its bath, at a given time interval, divided by the probability of the reverse process (releasing the same amount of heat to the bath) is given by an exponential factor which depends on the amount of heat and the difference between the temperatures of the system and the bath. Interestingly, this relation is akin to the standard form of the fluctuation relation (for forward-backward dynamics). We also argue that the probability of the violation of the second law of thermodynamics in the form of the Clausius statement (i.e., net heat transfer from a cold system to its hot bath) drops exponentially with both the amount of heat and the temperature differences of the baths.

Modelling individual difference in visual categorization.

Science.gov (United States)

Shen, Jianhong; Palmeri, Thomas J

Recent years has seen growing interest in understanding, characterizing, and explaining individual differences in visual cognition. We focus here on individual differences in visual categorization. Categorization is the fundamental visual ability to group different objects together as the same kind of thing. Research on visual categorization and category learning has been significantly informed by computational modeling, so our review will focus both on how formal models of visual categorization have captured individual differences and how individual difference have informed the development of formal models. We first examine the potential sources of individual differences in leading models of visual categorization, providing a brief review of a range of different models. We then describe several examples of how computational models have captured individual differences in visual categorization. This review also provides a bit of an historical perspective, starting with models that predicted no individual differences, to those that captured group differences, to those that predict true individual differences, and to more recent hierarchical approaches that can simultaneously capture both group and individual differences in visual categorization. Via this selective review, we see how considerations of individual differences can lead to important theoretical insights into how people visually categorize objects in the world around them. We also consider new directions for work examining individual differences in visual categorization.

Survival probability of a local excitation in a non-Markovian environment: Survival collapse, Zeno and anti-Zeno effects

International Nuclear Information System (INIS)

Rufeil-Fiori, E.; Pastawski, H.M.

2009-01-01

The decay dynamics of a local excitation interacting with a non-Markovian environment, modeled by a semi-infinite tight-binding chain, is exactly evaluated. We identify distinctive regimes for the dynamics. Sequentially: (i) early quadratic decay of the initial-state survival probability, up to a spreading time t S , (ii) exponential decay described by a self-consistent Fermi Golden Rule, and (iii) asymptotic behavior governed by quantum diffusion through the return processes, leading to an inverse power law decay. At this last cross-over time t R a survival collapse becomes possible. This could reduce the survival probability by several orders of magnitude. The cross-over times t S and t R allow to assess the range of applicability of the Fermi Golden Rule and give the conditions for the observation of the Zeno and anti-Zeno effect.

An individual-based model for population viability analysis of humpback chub in Grand Canyon

Science.gov (United States)

Pine, William Pine; Healy, Brian; Smith, Emily Omana; Trammell, Melissa; Speas, Dave; Valdez, Rich; Yard, Mike; Walters, Carl; Ahrens, Rob; Vanhaverbeke, Randy; Stone, Dennis; Wilson, Wade

2013-01-01

We developed an individual-based population viability analysis model (females only) for evaluating risk to populations from catastrophic events or conservation and research actions. This model tracks attributes (size, weight, viability, etc.) for individual fish through time and then compiles this information to assess the extinction risk of the population across large numbers of simulation trials. Using a case history for the Little Colorado River population of Humpback Chub Gila cypha in Grand Canyon, Arizona, we assessed extinction risk and resiliency to a catastrophic event for this population and then assessed a series of conservation actions related to removing specific numbers of Humpback Chub at different sizes for conservation purposes, such as translocating individuals to establish other spawning populations or hatchery refuge development. Our results suggested that the Little Colorado River population is generally resilient to a single catastrophic event and also to removals of larvae and juveniles for conservation purposes, including translocations to establish new populations. Our results also suggested that translocation success is dependent on similar survival rates in receiving and donor streams and low emigration rates from recipient streams. In addition, translocating either large numbers of larvae or small numbers of large juveniles has generally an equal likelihood of successful population establishment at similar extinction risk levels to the Little Colorado River donor population. Our model created a transparent platform to consider extinction risk to populations from catastrophe or conservation actions and should prove useful to managers assessing these risks for endangered species such as Humpback Chub.

Caribou, individual-based modeling and mega-industry in central West Greenland

DEFF Research Database (Denmark)

Raundrup, Katrine; Nymand, Josephine; Nabe-Nielsen, Jacob

in West Greenland. In a newly started PhD-project the focus will be the implementation of spatially explicit individual based modeling (IBM). The project relies on existing knowledge on caribou behavior and feeding ecology along with data on variations in the vegetation. By relating vegetation, snow......Spatial distribution of caribou (Rangifer tarandus groenlandicus) in West Greenland is a result of both short and long term changes in the Arctic landscape. To understand present distribution 40 satellite collars were deployed on 40 female caribou in the Akia-Maniitsoq herd, central West Greenland...... in an area. Further, enhanced or lowered hunting pressure, and changed weather conditions can be studied using IBM. Thus, both short and long term changes in the landscape will be studied and provide insights in how the specific spatial changes impact caribou in West Greenland....

Decentralised output feedback control of Markovian jump interconnected systems with unknown interconnections

Science.gov (United States)

Li, Li-Wei; Yang, Guang-Hong

2017-07-01

The problem of decentralised output feedback control is addressed for Markovian jump interconnected systems with unknown interconnections and general transition rates (TRs) allowed to be unknown or known with uncertainties. A class of decentralised dynamic output feedback controllers are constructed, and a cyclic-small-gain condition is exploited to dispose the unknown interconnections so that the resultant closed-loop system is stochastically stable and satisfies an H∞ performance. With slack matrices to cope with the nonlinearities incurred by unknown and uncertain TRs in control synthesis, a novel controller design condition is developed in linear matrix inequality formalism. Compared with the existing works, the proposed approach leads to less conservatism. Finally, two examples are used to illustrate the effectiveness of the new results.

Optimal Investment-Consumption Strategy under Inflation in a Markovian Regime-Switching Market

Directory of Open Access Journals (Sweden)

Huiling Wu

2016-01-01

Full Text Available This paper studies an investment-consumption problem under inflation. The consumption price level, the prices of the available assets, and the coefficient of the power utility are assumed to be sensitive to the states of underlying economy modulated by a continuous-time Markovian chain. The definition of admissible strategies and the verification theory corresponding to this stochastic control problem are presented. The analytical expression of the optimal investment strategy is derived. The existence, boundedness, and feasibility of the optimal consumption are proven. Finally, we analyze in detail by mathematical and numerical analysis how the risk aversion, the correlation coefficient between the inflation and the stock price, the inflation parameters, and the coefficient of utility affect the optimal investment and consumption strategy.

Coarse-grained representation of the quasi adiabatic propagator path integral for the treatment of non-Markovian long-time bath memory

Science.gov (United States)

Richter, Martin; Fingerhut, Benjamin P.

2017-06-01

The description of non-Markovian effects imposed by low frequency bath modes poses a persistent challenge for path integral based approaches like the iterative quasi-adiabatic propagator path integral (iQUAPI) method. We present a novel approximate method, termed mask assisted coarse graining of influence coefficients (MACGIC)-iQUAPI, that offers appealing computational savings due to substantial reduction of considered path segments for propagation. The method relies on an efficient path segment merging procedure via an intermediate coarse grained representation of Feynman-Vernon influence coefficients that exploits physical properties of system decoherence. The MACGIC-iQUAPI method allows us to access the regime of biological significant long-time bath memory on the order of hundred propagation time steps while retaining convergence to iQUAPI results. Numerical performance is demonstrated for a set of benchmark problems that cover bath assisted long range electron transfer, the transition from coherent to incoherent dynamics in a prototypical molecular dimer and excitation energy transfer in a 24-state model of the Fenna-Matthews-Olson trimer complex where in all cases excellent agreement with numerically exact reference data is obtained.

Unifying ecology and macroevolution with individual-based theory.

Science.gov (United States)

Rosindell, James; Harmon, Luke J; Etienne, Rampal S

2015-05-01

A contemporary goal in both ecology and evolutionary biology is to develop theory that transcends the boundary between the two disciplines, to understand phenomena that cannot be explained by either field in isolation. This is challenging because macroevolution typically uses lineage-based models, whereas ecology often focuses on individual organisms. Here, we develop a new parsimonious individual-based theory by adding mild selection to the neutral theory of biodiversity. We show that this model generates realistic phylogenies showing a slowdown in diversification and also improves on the ecological predictions of neutral theory by explaining the occurrence of very common species. Moreover, we find the distribution of individual fitness changes over time, with average fitness increasing at a pace that depends positively on community size. Consequently, large communities tend to produce fitter species than smaller communities. These findings have broad implications beyond biodiversity theory, potentially impacting, for example, invasion biology and paleontology. © 2015 The Authors. Ecology Letters published by John Wiley & Sons Ltd and CNRS.

[Construction of individual-based ecological model for Scomber japonicas at its early growth stages in East China Sea].

Science.gov (United States)

Li, Yue-Song; Chen, Xin-Jun; Yang, Hong

2012-06-01

By adopting FVCOM-simulated 3-D physical field and based on the biological processes of chub mackerel (Scomber japonicas) in its early life history from the individual-based biological model, the individual-based ecological model for S. japonicas at its early growth stages in the East China Sea was constructed through coupling the physical field in March-July with the biological model by the method of Lagrange particle tracking. The model constructed could well simulate the transport process and abundance distribution of S. japonicas eggs and larvae. The Taiwan Warm Current, Kuroshio, and Tsushima Strait Warm Current directly affected the transport process and distribution of the eggs and larvae, and indirectly affected the growth and survive of the eggs and larvae through the transport to the nursery grounds with different water temperature and foods. The spawning grounds in southern East China Sea made more contributions to the recruitment to the fishing grounds in northeast East China Sea, but less to the Yangtze estuary and Zhoushan Island. The northwestern and southwestern parts of spawning grounds had strong connectivity with the nursery grounds of Cheju and Tsushima Straits, whereas the northeastern and southeastern parts of the spawning ground had strong connectivity with the nursery grounds of Kyushu and Pacific Ocean.

Sandeel ( Ammodytes marinus ) larval transport patterns in the North Sea from an individual-based hydrodynamic egg and larval model

DEFF Research Database (Denmark)

Christensen, Asbjørn; Jensen, Henrik; Mosegaard, Henrik

2008-01-01

We have calculated a time series of larval transport indices for the central and southern North Sea covering 1970-2004, using a combined three-dimensional hydrodynamic and individual-based modelling framework for studying sandeel (Ammodytes marinus) eggs, larval transport, and growth. The egg phase...... is modelled by a stochastic, nonlinear degree-day model describing the extended hatch period. The larval growth model is parameterized by individually back-tracking the local physical environment of larval survivors from their catch location and catch time. Using a detailed map of sandeel habitats...... analyzed, and we introduce novel a scheme to quantify direct and indirect connectivity on equal footings in terms of an interbank transit time scale....

An individual-based model of Zebrafish population dynamics accounting for energy dynamics

DEFF Research Database (Denmark)

Beaudouin, Remy; Goussen, Benoit; Piccini, Benjamin

2015-01-01

Developing population dynamics models for zebrafish is crucial in order to extrapolate from toxicity data measured at the organism level to biological levels relevant to support and enhance ecological risk assessment. To achieve this, a dynamic energy budget for individual zebrafish (DEB model...

Multi-scale inference of interaction rules in animal groups using Bayesian model selection.

Directory of Open Access Journals (Sweden)

Richard P Mann

Full Text Available Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis. We show that these exhibit a stereotypical 'phase transition', whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have 'memory' of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture the observed locality of interactions. Traditional self-propelled particle models fail to capture the fine scale dynamics of the system. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics, while maintaining a biologically plausible perceptual range. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects.

Effectiveness of Gross Model-Based Emotion Regulation Strategies Training on Anger Reduction in Drug-Dependent Individuals and its Sustainability in Follow-up.

Science.gov (United States)

Massah, Omid; Sohrabi, Faramarz; A'azami, Yousef; Doostian, Younes; Farhoudian, Ali; Daneshmand, Reza

2016-03-01

Emotion plays an important role in adapting to life changes and stressful events. Difficulty regulating emotions is one of the problems drug abusers often face, and teaching these individuals to express and manage their emotions can be effective on improving their difficult circumstances. The present study aimed to determine the effectiveness of the Gross model-based emotion regulation strategies training on anger reduction in drug-dependent individuals. The present study had a quasi-experimental design wherein pretest-posttest evaluations were applied using a control group. The population under study included addicts attending Marivan's methadone maintenance therapy centers in 2012 - 2013. Convenience sampling was used to select 30 substance-dependent individuals undergoing maintenance treatment who were then randomly assigned to the experiment and control groups. The experiment group received its training in eight two-hour sessions. Data were analyzed using analysis of co-variance and paired t-test. There was significant reduction in anger symptoms of drug-dependent individuals after gross model based emotion regulation training (ERT) (P emotion regulation strategies training. Based on the results of this study, we may conclude that the gross model based emotion regulation strategies training can be applied alongside other therapies to treat drug abusers undergoing rehabilitation.

Noninvasive Quantum Measurement of Arbitrary Operator Order by Engineered Non-Markovian Detectors

Science.gov (United States)

Bülte, Johannes; Bednorz, Adam; Bruder, Christoph; Belzig, Wolfgang

2018-04-01

The development of solid-state quantum technologies requires the understanding of quantum measurements in interacting, nonisolated quantum systems. In general, a permanent coupling of detectors to a quantum system leads to memory effects that have to be taken into account in interpreting the measurement results. We analyze a generic setup of two detectors coupled to a quantum system and derive a compact formula in the weak-measurement limit that interpolates between an instantaneous (text-book type) and almost continuous—detector dynamics-dependent—measurement. A quantum memory effect that we term "system-mediated detector-detector interaction" is crucial to observe noncommuting observables simultaneously. Finally, we propose a mesoscopic double-dot detector setup in which the memory effect is tunable and that can be used to explore the transition to non-Markovian quantum measurements experimentally.

An individual-based model for biofilm formation at liquid surfaces.

Science.gov (United States)

Ardré, Maxime; Henry, Hervé; Douarche, Carine; Plapp, Mathis

2015-12-10

The bacterium Bacillus subtilis frequently forms biofilms at the interface between the culture medium and the air. We present a mathematical model that couples a description of bacteria as individual discrete objects to the standard advection-diffusion equations for the environment. The model takes into account two different bacterial phenotypes. In the motile state, bacteria swim and perform a run-and-tumble motion that is biased toward regions of high oxygen concentration (aerotaxis). In the matrix-producer state they excrete extracellular polymers, which allows them to connect to other bacteria and to form a biofilm. Bacteria are also advected by the fluid, and can trigger bioconvection. Numerical simulations of the model reproduce all the stages of biofilm formation observed in laboratory experiments. Finally, we study the influence of various model parameters on the dynamics and morphology of biofilms.

Stochastic exponential stability of the delayed reaction-diffusion recurrent neural networks with Markovian jumping parameters

International Nuclear Information System (INIS)

Wang Linshan; Zhang Zhe; Wang Yangfan

2008-01-01

Some criteria for the global stochastic exponential stability of the delayed reaction-diffusion recurrent neural networks with Markovian jumping parameters are presented. The jumping parameters considered here are generated from a continuous-time discrete-state homogeneous Markov process, which are governed by a Markov process with discrete and finite state space. By employing a new Lyapunov-Krasovskii functional, a linear matrix inequality (LMI) approach is developed to establish some easy-to-test criteria of global exponential stability in the mean square for the stochastic neural networks. The criteria are computationally efficient, since they are in the forms of some linear matrix inequalities

On the validity of non-Markovian master equation approaches for the entanglement dynamics of two-qubit systems

Energy Technology Data Exchange (ETDEWEB)

Ferraro, E; Scala, M; Napoli, A [CNISM and Dipartimento di Scienze Fisiche ed Astronomiche, Universita di Palermo, via Archirafi 36, 90123 Palermo (Italy); Migliore, R, E-mail: ferraro@fisica.unipa.i, E-mail: matteo.scala@fisica.unipa.i [CNR-INFM, Research Unit CNISM of Palermo, via Archirafi 36, 90123 Palermo (Italy)

2010-09-01

In the framework of the dissipative dynamics of coupled qubits interacting with independent reservoirs, a comparison between non-Markovian master equation techniques and an exact solution is presented here. We study various regimes in order to find the limits of validity of the Nakajima-Zwanzig and the time-convolutionless master equations in the description of the entanglement dynamics. A comparison between the performances of the concurrence and the negativity as entanglement measures for the system under study is also presented.

An individual-based evolving predator-prey ecosystem simulation using a fuzzy cognitive map as the behavior model

OpenAIRE

Gras , Robin; Devaurs , Didier; Wozniak , Adrianna; Aspinall , Adam

2009-01-01

International audience; This paper presents an individual-based predator-prey model with, for the first time, each agent behavior being modeled by a Fuzzy Cognitive Map (FCM), allowing the evolution of the agent behavior through the epochs of the simulation. The FCM enables the agent to evaluate its environment (e.g., distance to predator/prey, distance to potential breeding partner, distance to food, energy level), its internal state (e.g., fear, hunger, curiosity) with memory and choosing s...

Historical demography of common carp estimated from individuals collected from various parts of the world using the pairwise sequentially markovian coalescent approach.

Science.gov (United States)

Yuan, Zihao; Huang, Wei; Liu, Shikai; Xu, Peng; Dunham, Rex; Liu, Zhanjiang

2018-04-01

The inference of historical demography of a species is helpful for understanding species' differentiation and its population dynamics. However, such inference has been previously difficult due to the lack of proper analytical methods and availability of genetic data. A recently developed method called Pairwise Sequentially Markovian Coalescent (PSMC) offers the capability for estimation of the trajectories of historical populations over considerable time periods using genomic sequences. In this study, we applied this approach to infer the historical demography of the common carp using samples collected from Europe, Asia and the Americas. Comparison between Asian and European common carp populations showed that the last glacial period starting 100 ka BP likely caused a significant decline in population size of the wild common carp in Europe, while it did not have much of an impact on its counterparts in Asia. This was probably caused by differences in glacial activities in East Asia and Europe, and suggesting a separation of the European and Asian clades before the last glacial maximum. The North American clade which is an invasive population shared a similar demographic history as those from Europe, consistent with the idea that the North American common carp probably had European ancestral origins. Our analysis represents the first reconstruction of the historical population demography of the common carp, which is important to elucidate the separation of European and Asian common carp clades during the Quaternary glaciation, as well as the dispersal of common carp across the world.

Individual model evaluation and probabilistic weighting of models

International Nuclear Information System (INIS)

Atwood, C.L.

1994-01-01

This note stresses the importance of trying to assess the accuracy of each model individually. Putting a Bayesian probability distribution on a population of models faces conceptual and practical complications, and apparently can come only after the work of evaluating the individual models. Moreover, the primary issue is open-quotes How good is this modelclose quotes? Therefore, the individual evaluations are first in both chronology and importance. They are not easy, but some ideas are given here on how to perform them

Exploring the persistence of stream-dwelling trout populations under alternative real-world turbidity regimes with an individual-based model

Science.gov (United States)

Bret C. Harvey; Steven F. Railsback

2009-01-01

We explored the effects of elevated turbidity on stream-resident populations of coastal cutthroat trout Oncorhynchus clarkii clarkii using a spatially explicit individual-based model. Turbidity regimes were contrasted by means of 15-year simulations in a third-order stream in northwestern California. The alternative regimes were based on multiple-year, continuous...

Statistical models and NMR analysis of polymer microstructure

Science.gov (United States)

Statistical models can be used in conjunction with NMR spectroscopy to study polymer microstructure and polymerization mechanisms. Thus, Bernoullian, Markovian, and enantiomorphic-site models are well known. Many additional models have been formulated over the years for additional situations. Typica...

A general science-based framework for dynamical spatio-temporal models

Science.gov (United States)

Wikle, C.K.; Hooten, M.B.

2010-01-01

Spatio-temporal statistical models are increasingly being used across a wide variety of scientific disciplines to describe and predict spatially-explicit processes that evolve over time. Correspondingly, in recent years there has been a significant amount of research on new statistical methodology for such models. Although descriptive models that approach the problem from the second-order (covariance) perspective are important, and innovative work is being done in this regard, many real-world processes are dynamic, and it can be more efficient in some cases to characterize the associated spatio-temporal dependence by the use of dynamical models. The chief challenge with the specification of such dynamical models has been related to the curse of dimensionality. Even in fairly simple linear, first-order Markovian, Gaussian error settings, statistical models are often over parameterized. Hierarchical models have proven invaluable in their ability to deal to some extent with this issue by allowing dependency among groups of parameters. In addition, this framework has allowed for the specification of science based parameterizations (and associated prior distributions) in which classes of deterministic dynamical models (e. g., partial differential equations (PDEs), integro-difference equations (IDEs), matrix models, and agent-based models) are used to guide specific parameterizations. Most of the focus for the application of such models in statistics has been in the linear case. The problems mentioned above with linear dynamic models are compounded in the case of nonlinear models. In this sense, the need for coherent and sensible model parameterizations is not only helpful, it is essential. Here, we present an overview of a framework for incorporating scientific information to motivate dynamical spatio-temporal models. First, we illustrate the methodology with the linear case. We then develop a general nonlinear spatio-temporal framework that we call general quadratic

Non-Markovian response of ultrafast coherent electronic ring currents in chiral aromatic molecules in a condensed phase

International Nuclear Information System (INIS)

Mineo, H.; Lin, S. H.; Fujimura, Y.; Xu, J.; Xu, R. X.; Yan, Y. J.

2013-01-01

Results of a theoretical study on non-Markov response for femtosecond laser-driven coherent ring currents in chiral aromatic molecules embedded in a condensed phase are presented. Coherent ring currents are generated by coherent excitation of a pair of quasi-degenerated π-electronic excited states. The coherent electronic dynamical behaviors are strongly influenced by interactions between the electronic system and phonon bath in a condensed phase. Here, the bath correlation time is not instantaneous but should be taken to be a finite time in ultrashort time-resolved experiments. In such a case, Markov approximation breaks down. A hierarchical master equation approach for an improved semiclassical Drude dissipation model was adopted to examine the non-Markov effects on ultrafast coherent electronic ring currents of (P)-2,2 ′ -biphenol in a condensed phase. Time evolution of the coherent ring current derived in the hierarchical master equation approach was calculated and compared with those in the Drude model in the Markov approximation and in the static limit. The results show how non-Markovian behaviors in quantum beat signals of ring currents depend on the Drude bath damping constant. Effects of temperatures on ultrafast coherent electronic ring currents are also clarified

Continued-fraction representation of the Kraus map for non-Markovian reservoir damping

Science.gov (United States)

van Wonderen, A. J.; Suttorp, L. G.

2018-04-01

Quantum dissipation is studied for a discrete system that linearly interacts with a reservoir of harmonic oscillators at thermal equilibrium. Initial correlations between system and reservoir are assumed to be absent. The dissipative dynamics as determined by the unitary evolution of system and reservoir is described by a Kraus map consisting of an infinite number of matrices. For all Laplace-transformed Kraus matrices exact solutions are constructed in terms of continued fractions that depend on the pair correlation functions of the reservoir. By performing factorizations in the Kraus map a perturbation theory is set up that conserves in arbitrary perturbative order both positivity and probability of the density matrix. The latter is determined by an integral equation for a bitemporal matrix and a finite hierarchy for Kraus matrices. In the lowest perturbative order this hierarchy reduces to one equation for one Kraus matrix. Its solution is given by a continued fraction of a much simpler structure as compared to the non-perturbative case. In the lowest perturbative order our non-Markovian evolution equations are applied to the damped Jaynes–Cummings model. From the solution for the atomic density matrix it is found that the atom may remain in the state of maximum entropy for a significant time span that depends on the initial energy of the radiation field.

Quantum trajectories: Memory and continuous observation

Science.gov (United States)

Barchielli, Alberto; Pellegrini, Clément; Petruccione, Francesco

2012-12-01

Starting from a generalization of the quantum trajectory theory [based on the stochastic Schrödinger equation (SSE)], non-Markovian models of quantum dynamics are derived. In order to describe non-Markovian effects, the approach used in this article is based on the introduction of random coefficients in the usual linear SSE. A major interest is that this allows a consistent theory of quantum measurement in continuous time to be developed for these non-Markovian quantum trajectory models. In this context, the notions of “instrument,” “a priori,” and “a posteriori” states can be introduced. The key point is that by starting from a stochastic equation on the Hilbert space of the system, we are able to respect the complete positivity of the mean dynamics for the statistical operator and the requirements of the axioms of quantum measurement theory. The flexibility of the theory is next illustrated by a concrete physical model of a noisy oscillator where non-Markovian effects come from the random environment, colored noises, randomness in the stimulating light, and delay effects. The statistics of the emitted photons and the heterodyne and homodyne spectra are studied, and we show how these quantities are sensitive to the non-Markovian features of the system dynamics, so that, in principle, the observation and analysis of the fluorescent light could reveal the presence of non-Markovian effects and allow for a measure of the spectra of the noises affecting the system dynamics.

Quantifying the mechanical micro-environment during three-dimensional cell expansion on microbeads by means of individual cell-based modelling.

Science.gov (United States)

Smeets, Bart; Odenthal, Tim; Tijskens, Engelbert; Ramon, Herman; Van Oosterwyck, Hans

2013-10-01

Controlled in vitro three-dimensional cell expansion requires culture conditions that optimise the biophysical micro-environment of the cells during proliferation. In this study, we propose an individual cell-based modelling platform for simulating the mechanics of cell expansion on microcarriers. The lattice-free, particle-based method considers cells as individual interacting particles that deform and move over time. The model quantifies how the mechanical micro-environment of individual cells changes during the time of confluency. A sensitivity analysis is performed, which shows that changes in the cell-specific properties of cell-cell adhesion and cell stiffness cause the strongest change in the mechanical micro-environment of the cells. Furthermore, the influence of the mechanical properties of cells and microbead is characterised. The mechanical micro-environment is strongly influenced by the adhesive properties and the size of the microbead. Simulations show that even in the absence of strong biological heterogeneity, a large heterogeneity in mechanical stresses can be expected purely due to geometric properties of the culture system.

A generic framework for individual-based modelling and physical-biological interaction

DEFF Research Database (Denmark)

Christensen, Asbjørn; Mariani, Patrizio; Payne, Mark R.

2018-01-01

The increased availability of high-resolution ocean data globally has enabled more detailed analyses of physical-biological interactions and their consequences to the ecosystem. We present IBMlib, which is a versatile, portable and computationally effective framework for conducting Lagrangian...... scales. The open-source framework features a minimal robust interface to facilitate the coupling between individual-level biological models and oceanographic models, and we provide application examples including forward/backward simulations, habitat connectivity calculations, assessing ocean conditions...

Quantifying population-level risks using an individual-based model: sea otters, Harlequin Ducks, and the Exxon Valdez oil spill.

Science.gov (United States)

Harwell, Mark A; Gentile, John H; Parker, Keith R

2012-07-01

Ecological risk assessments need to advance beyond evaluating risks to individuals that are largely based on toxicity studies conducted on a few species under laboratory conditions, to assessing population-level risks to the environment, including considerations of variability and uncertainty. Two individual-based models (IBMs), recently developed to assess current risks to sea otters and seaducks in Prince William Sound more than 2 decades after the Exxon Valdez oil spill (EVOS), are used to explore population-level risks. In each case, the models had previously shown that there were essentially no remaining risks to individuals from polycyclic aromatic hydrocarbons (PAHs) derived from the EVOS. New sensitivity analyses are reported here in which hypothetical environmental exposures to PAHs were heuristically increased until assimilated doses reached toxicity reference values (TRVs) derived at the no-observed-adverse-effects and lowest-observed-adverse-effects levels (NOAEL and LOAEL, respectively). For the sea otters, this was accomplished by artificially increasing the number of sea otter pits that would intersect remaining patches of subsurface oil residues by orders of magnitude over actual estimated rates. Similarly, in the seaduck assessment, the PAH concentrations in the constituents of diet, sediments, and seawater were increased in proportion to their relative contributions to the assimilated doses by orders of magnitude over measured environmental concentrations, to reach the NOAEL and LOAEL thresholds. The stochastic IBMs simulated millions of individuals. From these outputs, frequency distributions were derived of assimilated doses for populations of 500,000 sea otters or seaducks in each of 7 or 8 classes, respectively. Doses to several selected quantiles were analyzed, ranging from the 1-in-1000th most-exposed individuals (99.9% quantile) to the median-exposed individuals (50% quantile). The resulting families of quantile curves provide the basis for

Input modeling with phase-type distributions and Markov models theory and applications

CERN Document Server

Buchholz, Peter; Felko, Iryna

2014-01-01

Containing a summary of several recent results on Markov-based input modeling in a coherent notation, this book introduces and compares algorithms for parameter fitting and gives an overview of available software tools in the area. Due to progress made in recent years with respect to new algorithms to generate PH distributions and Markovian arrival processes from measured data, the models outlined are useful alternatives to other distributions or stochastic processes used for input modeling. Graduate students and researchers in applied probability, operations research and computer science along with practitioners using simulation or analytical models for performance analysis and capacity planning will find the unified notation and up-to-date results presented useful. Input modeling is the key step in model based system analysis to adequately describe the load of a system using stochastic models. The goal of input modeling is to find a stochastic model to describe a sequence of measurements from a real system...

CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

Science.gov (United States)

Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

2016-01-01

1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

Asymptotic propagators and trajectories in plasma turbulence theory. The importance of irreversibility, asymptoticity and non-Markovian terms

International Nuclear Information System (INIS)

Misguich, J.H.

1978-09-01

The physical meaning of perturbed trajectories in turbulent fields is analysed. Special care is devoted to the asymptotic description of average trajectories for long time intervals, as occuring in many recent plasma turbulence theories. Equivalence is proved between asymptotic average trajectories described as well (i) by the propagators V(t,t-tau) for retrodiction and Wsub(J)(t,t+tau) for prediction, and (ii) by the long time secular behavior of the solution of the equations of motion. This confirms the equivalence between perturbed orbit theories and renormalized theories, including non-Markovian contributions

Adjudicating between face-coding models with individual-face fMRI responses.

Directory of Open Access Journals (Sweden)

Johan D Carlin

2017-07-01

Full Text Available The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging.

Modeling of Individual and Organizational Factors Affecting Traumatic Occupational Injuries Based on the Structural Equation Modeling: A Case Study in Large Construction Industries.

Science.gov (United States)

Mohammadfam, Iraj; Soltanzadeh, Ahmad; Moghimbeigi, Abbas; Akbarzadeh, Mehdi

2016-09-01

Individual and organizational factors are the factors influencing traumatic occupational injuries. The aim of the present study was the short path analysis of the severity of occupational injuries based on individual and organizational factors. The present cross-sectional analytical study was implemented on traumatic occupational injuries within a ten-year timeframe in 13 large Iranian construction industries. Modeling and data analysis were done using the structural equation modeling (SEM) approach and the IBM SPSS AMOS statistical software version 22.0, respectively. The mean age and working experience of the injured workers were 28.03 ± 5.33 and 4.53 ± 3.82 years, respectively. The portions of construction and installation activities of traumatic occupational injuries were 64.4% and 18.1%, respectively. The SEM findings showed that the individual, organizational and accident type factors significantly were considered as effective factors on occupational injuries' severity (P accidents' severity in large construction industries.

Driving-forces model on individual behavior in scenarios considering moving threat agents

Science.gov (United States)

Li, Shuying; Zhuang, Jun; Shen, Shifei; Wang, Jia

2017-09-01

The individual behavior model is a contributory factor to improve the accuracy of agent-based simulation in different scenarios. However, few studies have considered moving threat agents, which often occur in terrorist attacks caused by attackers with close-range weapons (e.g., sword, stick). At the same time, many existing behavior models lack validation from cases or experiments. This paper builds a new individual behavior model based on seven behavioral hypotheses. The driving-forces model is an extension of the classical social force model considering scenarios including moving threat agents. An experiment was conducted to validate the key components of the model. Then the model is compared with an advanced Elliptical Specification II social force model, by calculating the fitting errors between the simulated and experimental trajectories, and being applied to simulate a specific circumstance. Our results show that the driving-forces model reduced the fitting error by an average of 33.9% and the standard deviation by an average of 44.5%, which indicates the accuracy and stability of the model in the studied situation. The new driving-forces model could be used to simulate individual behavior when analyzing the risk of specific scenarios using agent-based simulation methods, such as risk analysis of close-range terrorist attacks in public places.

A Risk-Based Approach for Asset Allocation with A Defaultable Share

Directory of Open Access Journals (Sweden)

Yang Shen

2018-02-01

Full Text Available This paper presents a novel risk-based approach for an optimal asset allocation problem with default risk, where a money market account, an ordinary share and a defaultable security are investment opportunities in a general non-Markovian economy incorporating random market parameters. The objective of an investor is to select an optimal mix of these securities such that a risk metric of an investment portfolio is minimized. By adopting a sub-additive convex risk measure, which takes into account interest rate risk, as a measure for risk, the investment problem is discussed mathematically in a form of a two-player, zero-sum, stochastic differential game between the investor and the market. A backward stochastic differential equation approach is used to provide a flexible and theoretically sound way to solve the game problem. Closed-form expressions for the optimal strategies of the investor and the market are obtained when the penalty function is a quadratic function and when the risk measure is a sub-additive coherent risk measure. An important case of the general non-Markovian model, namely the self-exciting threshold diffusion model with time delay, is considered. Numerical examples based on simulations for the self-exciting threshold diffusion model with and without time delay are provided to illustrate how the proposed model can be applied in this important case. The proposed model can be implemented using Excel spreadsheets.

Efficient Modelling and Generation of Markov Automata

NARCIS (Netherlands)

Koutny, M.; Timmer, Mark; Ulidowski, I.; Katoen, Joost P.; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette

This paper introduces a framework for the efficient modelling and generation of Markov automata. It consists of (1) the data-rich process-algebraic language MAPA, allowing concise modelling of systems with nondeterminism, probability and Markovian timing; (2) a restricted form of the language, the

Neuronal model with distributed delay: analysis and simulation study for gamma distribution memory kernel.

Science.gov (United States)

Karmeshu; Gupta, Varun; Kadambari, K V

2011-06-01

A single neuronal model incorporating distributed delay (memory)is proposed. The stochastic model has been formulated as a Stochastic Integro-Differential Equation (SIDE) which results in the underlying process being non-Markovian. A detailed analysis of the model when the distributed delay kernel has exponential form (weak delay) has been carried out. The selection of exponential kernel has enabled the transformation of the non-Markovian model to a Markovian model in an extended state space. For the study of First Passage Time (FPT) with exponential delay kernel, the model has been transformed to a system of coupled Stochastic Differential Equations (SDEs) in two-dimensional state space. Simulation studies of the SDEs provide insight into the effect of weak delay kernel on the Inter-Spike Interval(ISI) distribution. A measure based on Jensen-Shannon divergence is proposed which can be used to make a choice between two competing models viz. distributed delay model vis-á-vis LIF model. An interesting feature of the model is that the behavior of (CV(t))((ISI)) (Coefficient of Variation) of the ISI distribution with respect to memory kernel time constant parameter η reveals that neuron can switch from a bursting state to non-bursting state as the noise intensity parameter changes. The membrane potential exhibits decaying auto-correlation structure with or without damped oscillatory behavior depending on the choice of parameters. This behavior is in agreement with empirically observed pattern of spike count in a fixed time window. The power spectral density derived from the auto-correlation function is found to exhibit single and double peaks. The model is also examined for the case of strong delay with memory kernel having the form of Gamma distribution. In contrast to fast decay of damped oscillations of the ISI distribution for the model with weak delay kernel, the decay of damped oscillations is found to be slower for the model with strong delay kernel.

Relationships between migration rates and landscape resistance assessed using individual-based simulations

Science.gov (United States)

E. L. Landguth; S. A. Cushman; M. A. Murphy; G. Luikart

2010-01-01

Linking landscape effects on gene flow to processes such as dispersal and mating is essential to provide a conceptual foundation for landscape genetics. It is particularly important to determine how classical population genetic models relate to recent individual-based landscape genetic models when assessing individual movement and its influence on population genetic...

Quantum metrology subject to spatially correlated Markovian noise: restoring the Heisenberg limit

International Nuclear Information System (INIS)

Jeske, Jan; Cole, Jared H; Huelga, Susana F

2014-01-01

Environmental noise can hinder the metrological capabilities of entangled states. While the use of entanglement allows for Heisenberg-limited resolution, the largest permitted by quantum mechanics, deviations from strictly unitary dynamics quickly restore the standard scaling dictated by the central limit theorem. Product and maximally entangled states become asymptotically equivalent when the noisy evolution is both local and strictly Markovian. However, temporal correlations in the noise have been shown to lift this equivalence while fully (spatially) correlated noise allows for the identification of decoherence-free subspaces. Here we analyze precision limits in the presence of noise with finite correlation length and show that there exist robust entangled state preparations which display persistent Heisenberg scaling despite the environmental decoherence, even for small correlation length. Our results emphasize the relevance of noise correlations in the study of quantum advantage and could be relevant beyond metrological applications. (paper)

Multi-scale individual-based model of microbial and bioconversion dynamics in aerobic granular sludge.

Science.gov (United States)

Xavier, Joao B; De Kreuk, Merle K; Picioreanu, Cristian; Van Loosdrecht, Mark C M

2007-09-15

Aerobic granular sludge is a novel compact biological wastewater treatment technology for integrated removal of COD (chemical oxygen demand), nitrogen, and phosphate charges. We present here a multiscale model of aerobic granular sludge sequencing batch reactors (GSBR) describing the complex dynamics of populations and nutrient removal. The macro scale describes bulk concentrations and effluent composition in six solutes (oxygen, acetate, ammonium, nitrite, nitrate, and phosphate). A finer scale, the scale of one granule (1.1 mm of diameter), describes the two-dimensional spatial arrangement of four bacterial groups--heterotrophs, ammonium oxidizers, nitrite oxidizers, and phosphate accumulating organisms (PAO)--using individual based modeling (IbM) with species-specific kinetic models. The model for PAO includes three internal storage compounds: polyhydroxyalkanoates (PHA), poly phosphate, and glycogen. Simulations of long-term reactor operation show how the microbial population and activity depends on the operating conditions. Short-term dynamics of solute bulk concentrations are also generated with results comparable to experimental data from lab scale reactors. Our results suggest that N-removal in GSBR occurs mostly via alternating nitrification/denitrification rather than simultaneous nitrification/denitrification, supporting an alternative strategy to improve N-removal in this promising wastewater treatment process.

Geostatistical Model-Based Estimates of Schistosomiasis Prevalence among Individuals Aged ≤20 Years in West Africa

Science.gov (United States)

Schur, Nadine; Hürlimann, Eveline; Garba, Amadou; Traoré, Mamadou S.; Ndir, Omar; Ratard, Raoult C.; Tchuem Tchuenté, Louis-Albert; Kristensen, Thomas K.; Utzinger, Jürg; Vounatsou, Penelope

2011-01-01

Background Schistosomiasis is a water-based disease that is believed to affect over 200 million people with an estimated 97% of the infections concentrated in Africa. However, these statistics are largely based on population re-adjusted data originally published by Utroska and colleagues more than 20 years ago. Hence, these estimates are outdated due to large-scale preventive chemotherapy programs, improved sanitation, water resources development and management, among other reasons. For planning, coordination, and evaluation of control activities, it is essential to possess reliable schistosomiasis prevalence maps. Methodology We analyzed survey data compiled on a newly established open-access global neglected tropical diseases database (i) to create smooth empirical prevalence maps for Schistosoma mansoni and S. haematobium for individuals aged ≤20 years in West Africa, including Cameroon, and (ii) to derive country-specific prevalence estimates. We used Bayesian geostatistical models based on environmental predictors to take into account potential clustering due to common spatially structured exposures. Prediction at unobserved locations was facilitated by joint kriging. Principal Findings Our models revealed that 50.8 million individuals aged ≤20 years in West Africa are infected with either S. mansoni, or S. haematobium, or both species concurrently. The country prevalence estimates ranged between 0.5% (The Gambia) and 37.1% (Liberia) for S. mansoni, and between 17.6% (The Gambia) and 51.6% (Sierra Leone) for S. haematobium. We observed that the combined prevalence for both schistosome species is two-fold lower in Gambia than previously reported, while we found an almost two-fold higher estimate for Liberia (58.3%) than reported before (30.0%). Our predictions are likely to overestimate overall country prevalence, since modeling was based on children and adolescents up to the age of 20 years who are at highest risk of infection. Conclusion/Significance We

An Individual-Based Diploid Model Predicts Limited Conditions Under Which Stochastic Gene Expression Becomes Advantageous

KAUST Repository

Matsumoto, Tomotaka

2015-11-24

Recent studies suggest the existence of a stochasticity in gene expression (SGE) in many organisms, and its non-negligible effect on their phenotype and fitness. To date, however, how SGE affects the key parameters of population genetics are not well understood. SGE can increase the phenotypic variation and act as a load for individuals, if they are at the adaptive optimum in a stable environment. On the other hand, part of the phenotypic variation caused by SGE might become advantageous if individuals at the adaptive optimum become genetically less-adaptive, for example due to an environmental change. Furthermore, SGE of unimportant genes might have little or no fitness consequences. Thus, SGE can be advantageous, disadvantageous, or selectively neutral depending on its context. In addition, there might be a genetic basis that regulates magnitude of SGE, which is often referred to as “modifier genes,” but little is known about the conditions under which such an SGE-modifier gene evolves. In the present study, we conducted individual-based computer simulations to examine these conditions in a diploid model. In the simulations, we considered a single locus that determines organismal fitness for simplicity, and that SGE on the locus creates fitness variation in a stochastic manner. We also considered another locus that modifies the magnitude of SGE. Our results suggested that SGE was always deleterious in stable environments and increased the fixation probability of deleterious mutations in this model. Even under frequently changing environmental conditions, only very strong natural selection made SGE adaptive. These results suggest that the evolution of SGE-modifier genes requires strict balance among the strength of natural selection, magnitude of SGE, and frequency of environmental changes. However, the degree of dominance affected the condition under which SGE becomes advantageous, indicating a better opportunity for the evolution of SGE in different genetic

Approximate zero-variance Monte Carlo estimation of Markovian unreliability

International Nuclear Information System (INIS)

Delcoux, J.L.; Labeau, P.E.; Devooght, J.

1997-01-01

Monte Carlo simulation has become an important tool for the estimation of reliability characteristics, since conventional numerical methods are no more efficient when the size of the system to solve increases. However, evaluating by a simulation the probability of occurrence of very rare events means playing a very large number of histories of the system, which leads to unacceptable computation times. Acceleration and variance reduction techniques have to be worked out. We show in this paper how to write the equations of Markovian reliability as a transport problem, and how the well known zero-variance scheme can be adapted to this application. But such a method is always specific to the estimation of one quality, while a Monte Carlo simulation allows to perform simultaneously estimations of diverse quantities. Therefore, the estimation of one of them could be made more accurate while degrading at the same time the variance of other estimations. We propound here a method to reduce simultaneously the variance for several quantities, by using probability laws that would lead to zero-variance in the estimation of a mean of these quantities. Just like the zero-variance one, the method we propound is impossible to perform exactly. However, we show that simple approximations of it may be very efficient. (author)

A generic individual-based model to simulate morphogenesis, C-N acquisition and population dynamics in contrasting forage legumes.

Science.gov (United States)

Louarn, Gaëtan; Faverjon, Lucas

2018-04-18

Individual-based models (IBMs) are promising tools to disentangle plant interactions in multi-species grasslands and foster innovative species mixtures. This study describes an IBM dealing with the morphogenesis, growth and C-N acquisition of forage legumes that integrates plastic responses from functional-structural plant models. A generic model was developed to account for herbaceous legume species with contrasting above- and below-ground morphogenetic syndromes and to integrate the responses of plants to light, water and N. Through coupling with a radiative transfer model and a three-dimensional virtual soil, the model allows dynamic resolution of competition for multiple resources at individual plant level within a plant community. The behaviour of the model was assessed on a range of monospecific stands grown along gradients of light, water and N availability. The model proved able to capture the diversity of morphologies encountered among the forage legumes. The main density-dependent features known about even-age plant populations were correctly anticipated. The model predicted (1) the 'reciprocal yield' law relating average plant mass to density, (2) a self-thinning pattern close to that measured for herbaceous species and (3) consistent changes in the size structure of plant populations with time and pedo-climatic conditions. In addition, plastic changes in the partitioning of dry matter, the N acquisition mode and in the architecture of shoots and roots emerged from the integration of plant responses to their local environment. This resulted in taller plants and thinner roots when competition was dominated by light, and shorter plants with relatively more developed root systems when competition was dominated by soil resources. A population dynamic model considering growth and morphogenesis responses to multiple resources heterogeneously distributed in the environment was presented. It should allow scaling plant-plant interactions from individual to

Permanence and asymptotic behaviors of stochastic predator-prey system with Markovian switching and Lévy noise

Science.gov (United States)

Wang, Sheng; Wang, Linshan; Wei, Tengda

2018-04-01

This paper concerns the dynamics of a stochastic predator-prey system with Markovian switching and Lévy noise. First, the existence and uniqueness of global positive solution to the system is proved. Then, by combining stochastic analytical techniques with M-matrix analysis, sufficient conditions of stochastic permanence and extinction are obtained. Furthermore, for the stochastic permanence case, by means of four constants related to the stationary probability distribution of the Markov chain and the parameters of the subsystems, both the superior limit and the inferior limit of the average in time of the sample path of the solution are estimated. Finally, our conclusions are illustrated through an example.

State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

International Nuclear Information System (INIS)

Lakshmanan, S.; Park, Ju H.; Jung, H. Y.; Balasubramaniam, P.

2012-01-01

This paper is concerned with a delay-dependent state estimator for neutral-type neural networks with mixed time-varying delays and Markovian jumping parameters. The addressed neural networks have a finite number of modes, and the modes may jump from one to another according to a Markov process. By construction of a suitable Lyapunov—Krasovskii functional, a delay-dependent condition is developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable in a mean square. The criterion is formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages

A discrete single server queue with Markovian arrivals and phase type group services

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Attahiru Sule Alfa

1995-01-01

Full Text Available We consider a single-server discrete queueing system in which arrivals occur according to a Markovian arrival process. Service is provided in groups of size no more than M customers. The service times are assumed to follow a discrete phase type distribution, whose representation may depend on the group size. Under a probabilistic service rule, which depends on the number of customers waiting in the queue, this system is studied as a Markov process. This type of queueing system is encountered in the operations of an automatic storage retrieval system. The steady-state probability vector is shown to be of (modified matrix-geometric type. Efficient algorithmic procedures for the computation of the rate matrix, steady-state probability vector, and some important system performance measures are developed. The steady-state waiting time distribution is derived explicitly. Some numerical examples are presented.

Fractal-Markovian scaling of turbulent bursting process in open channel flow

International Nuclear Information System (INIS)

Keshavarzi, Ali Reza; Ziaei, Ali Naghi; Homayoun, Emdad; Shirvani, Amin

2005-01-01

The turbulent coherent structure of flow in open channel is a chaotic and stochastic process in nature. The coherence structure of the flow or bursting process consists of a series of eddies with a variety of different length scales and it is very important for the entrainment of sediment particles from the bed. In this study, a fractal-Markovian process is applied to the measured turbulent data in open channel. The turbulent data was measured in an experimental flume using three-dimensional acoustic Doppler velocity meter (ADV). A fractal interpolation function (FIF) algorithm was used to simulate more than 500,000 time series data of measured instantaneous velocity fluctuations and Reynolds shear stress. The fractal interpolation functions (FIF) enables to simulate and construct time series of u', v', and u'v' for any particular movement and state in the Markov process. The fractal dimension of the bursting events is calculated for 16 particular movements with the transition probability of the events based on 1st order Markov process. It was found that the average fractal dimensions of the streamwise flow velocity (u') are; 1.73, 1.74, 1.71 and 1.74 with the transition probability of 60.82%, 63.77%, 59.23% and 62.09% for the 1-1, 2-2, 3-3 and 4-4 movements, respectively. It was also found that the fractal dimensions of Reynold stress u'v' for quadrants 1, 2, 3 and 4 are 1.623, 1.623, 1.625 and 1.618, respectively

Contextual and individual determinants of periodontal disease: Multilevel analysis based on Andersen's model.

Science.gov (United States)

Valente, Maria I B; Vettore, Mario V

2018-04-01

To investigate the relationship of contextual and individual factors with periodontal disease in dentate adults and older people using the Andersen's behavioural model. Secondary individual data from 6011 adults and 2369 older people from the Brazilian Oral Health Survey (2010) were combined with contextual data for 27 cities. Attachment loss (AL) categories for each sextant were coded and summed to obtain the periodontal disease measure. The association of predisposing, enabling and need characteristics at city and individual level with periodontal disease was assessed using an adapted version of the Andersen's behavioural model. Multilevel Poisson regression was used to estimate rate ratios (RR) and 95% CIs. Periodontal disease was associated with contextual predisposing (RR 0.93; 95% CI = 0.87-0.99) and enabling factors (RR 0.99; 95% CI = 0.98-0.99) in adults. Contextual predisposing was also associated with periodontal disease in older people (RR 0.82; 95% CI = 0.73-0.92). Individual predisposing (age, sex and schooling) and need characteristics (perceived treatment need) were common predictors of periodontal disease in adults and older people. Periodontal disease was also associated with behaviours in the latter age group. Contextual predisposing factors and individual characteristics influenced periodontal disease experience in adults and older people. Contextual enabling factors were also meaningful determinants of periodontal disease in the former age group. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Integrating Individual-Based Indices of Contaminant Effects

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Christopher L. Rowe

2001-01-01

Full Text Available Habitat contamination can alter numerous biological processes in individual organisms. Examining multiple individual-level responses in an integrative fashion is necessary to understand how individual health or fitness reflects environmental contamination. Here we provide an example of such an integrated perspective based upon recent studies of an amphibian (the bullfrog, Rana catesbeiana that experiences several, disparate changes when larval development occurs in a trace element�contaminated habitat. First, we present an overview of studies focused on specific responses of individuals collected from, or transplanted into, a habitat contaminated by coal combustion residues (CCR. These studies have reported morphological, behavioral, and physiological modifications to individuals chronically interacting with sediments in the CCR-contaminated site. Morphological abnormalities in the oral and tail regions in contaminant-exposed individuals influenced other properties such as grazing, growth, and swimming performance. Behavioral changes in swimming activities and responses to stimuli appear to influence predation risk in the contaminant-exposed population. Significant changes in bioenergetics in the contaminated habitat, evident as abnormally high energetic expenditures for survival (maintenance costs, may ultimately influence production pathways (growth, energy storage in individuals. We then present a conceptual model to examine how interactions among the affected systems (morphological, behavioral, physiological may ultimately bring about more severe effects than would be predicted if the responses were considered in isolation. A complex interplay among simultaneously occurring biological changes emerges in which multiple, sublethal effects ultimately can translate into reductions in larval or juvenile survival, and thus reduced recruitment of juveniles into the population. In systems where individuals are exposed to low concentrations of

Mechanistic Physiologically Based Pharmacokinetic (PBPK) Model of the Heart Accounting for Inter-Individual Variability: Development and Performance Verification.

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Tylutki, Zofia; Mendyk, Aleksander; Polak, Sebastian

2018-04-01

Modern model-based approaches to cardiac safety and efficacy assessment require accurate drug concentration-effect relationship establishment. Thus, knowledge of the active concentration of drugs in heart tissue is desirable along with inter-subject variability influence estimation. To that end, we developed a mechanistic physiologically based pharmacokinetic model of the heart. The models were described with literature-derived parameters and written in R, v.3.4.0. Five parameters were estimated. The model was fitted to amitriptyline and nortriptyline concentrations after an intravenous infusion of amitriptyline. The cardiac model consisted of 5 compartments representing the pericardial fluid, heart extracellular water, and epicardial intracellular, midmyocardial intracellular, and endocardial intracellular fluids. Drug cardiac metabolism, passive diffusion, active efflux, and uptake were included in the model as mechanisms involved in the drug disposition within the heart. The model accounted for inter-individual variability. The estimates of optimized parameters were within physiological ranges. The model performance was verified by simulating 5 clinical studies of amitriptyline intravenous infusion, and the simulated pharmacokinetic profiles agreed with clinical data. The results support the model feasibility. The proposed structure can be tested with the goal of improving the patient-specific model-based cardiac safety assessment and offers a framework for predicting cardiac concentrations of various xenobiotics. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Towards Linking 3D SAR and Lidar Models with a Spatially Explicit Individual Based Forest Model

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Osmanoglu, B.; Ranson, J.; Sun, G.; Armstrong, A. H.; Fischer, R.; Huth, A.

2017-12-01

In this study, we present a parameterization of the FORMIND individual-based gap model (IBGM)for old growth Atlantic lowland rainforest in La Selva, Costa Rica for the purpose of informing multisensor remote sensing techniques for above ground biomass techniques. The model was successfully parameterized and calibrated for the study site; results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest based on comparisons with CARBONO inventory plot data. Though the simulated stem numbers (378) slightly underestimated the plot data (418), particularly for canopy dominant intermediate shade tolerant trees and shade tolerant understory trees, overall there was a 9.7% difference. Aboveground biomass (kg/ha) showed a 0.1% difference between the simulated forest and inventory plot dataset. The Costa Rica FORMIND simulation was then used to parameterize a spatially explicit (3D) SAR and lidar backscatter models. The simulated forest stands were used to generate a Look Up Table as a tractable means to estimate aboveground forest biomass for these complex forests. Various combinations of lidar and radar variables were evaluated in the LUT inversion. To test the capability of future data for estimation of forest height and biomass, we considered data of 1) L- (or P-) band polarimetric data (backscattering coefficients of HH, HV and VV); 2) L-band dual-pol repeat-pass InSAR data (HH/HV backscattering coefficients and coherences, height of scattering phase center at HH and HV using DEM or surface height from lidar data as reference); 3) P-band polarimetric InSAR data (canopy height from inversion of PolInSAR data or use the coherences and height of scattering phase center at HH, HV and VV); 4) various height indices from waveform lidar data); and 5) surface and canopy top height from photon-counting lidar data. The methods for parameterizing the remote sensing models with the IBGM and developing Look Up Tables will be discussed. Results

Navigating the flow: individual and continuum models for homing in flowing environments.

Science.gov (United States)

Painter, Kevin J; Hillen, Thomas

2015-11-06

Navigation for aquatic and airborne species often takes place in the face of complicated flows, from persistent currents to highly unpredictable storms. Hydrodynamic models are capable of simulating flow dynamics and provide the impetus for much individual-based modelling, in which particle-sized individuals are immersed into a flowing medium. These models yield insights on the impact of currents on population distributions from fish eggs to large organisms, yet their computational demands and intractability reduce their capacity to generate the broader, less parameter-specific, insights allowed by traditional continuous approaches. In this paper, we formulate an individual-based model for navigation within a flowing field and apply scaling to derive its corresponding macroscopic and continuous model. We apply it to various movement classes, from drifters that simply go with the flow to navigators that respond to environmental orienteering cues. The utility of the model is demonstrated via its application to 'homing' problems and, in particular, the navigation of the marine green turtle Chelonia mydas to Ascension Island. © 2015 The Author(s).

Factors affecting competitive dominance of rainbow trout over brook trout in southern Appalachian streams: Implications of an individual-based model

Energy Technology Data Exchange (ETDEWEB)

Clark, M.E. [Univ. of Tennessee, Knoxville, TN (United States); Rose, K.A. [Oak Ridge National Lab., TN (United States)

1997-01-01

We used an individual-based model to examine possible explanations for the dominance of rainbow trout Oncorhynchus mykiss over brook trout Salvelinus fontinalis in southern Appalachian streams. Model simulations were used to quantify the effects on interspecific competition of (1) competitive advantage for feeding sites by rainbow trout, (2) latitudinal differences in stream temperatures, flows, and daylight, (3) year-class failures, (4) lower fecundity of brook trout, and (5) reductions in spawning habitat. The model tracks the daily spawning, growth, and survival of individuals of both species throughout their lifetime in a series of connected stream habitat units (pools, runs, or riffles). Average densities of each species based on 100-year simulations were compared for several levels of each of the five factors and for sympatric and allopatric conditions. Based on model results and empirical information, we conclude that more frequent year-class failures and the lower fecundity of brook trout are both possible and likely explanations for rainbow trout dominance, that warmer temperatures due to latitude and limited spawning habitat are possible but unlikely explanations, and that competitive advantage for feeding sites by rainbow trout is an unlikely explanation. Additional field work should focus on comparative studies of the reproductive success and the early life stage mortalities of brook and rainbow trout among Appalachian streams with varying rainbow trout dominance. 53 refs., 11 figs.

Survival modeling for the estimation of transition probabilities in model-based economic evaluations in the absence of individual patient data: a tutorial.

Science.gov (United States)

Diaby, Vakaramoko; Adunlin, Georges; Montero, Alberto J

2014-02-01

Survival modeling techniques are increasingly being used as part of decision modeling for health economic evaluations. As many models are available, it is imperative for interested readers to know about the steps in selecting and using the most suitable ones. The objective of this paper is to propose a tutorial for the application of appropriate survival modeling techniques to estimate transition probabilities, for use in model-based economic evaluations, in the absence of individual patient data (IPD). An illustration of the use of the tutorial is provided based on the final progression-free survival (PFS) analysis of the BOLERO-2 trial in metastatic breast cancer (mBC). An algorithm was adopted from Guyot and colleagues, and was then run in the statistical package R to reconstruct IPD, based on the final PFS analysis of the BOLERO-2 trial. It should be emphasized that the reconstructed IPD represent an approximation of the original data. Afterwards, we fitted parametric models to the reconstructed IPD in the statistical package Stata. Both statistical and graphical tests were conducted to verify the relative and absolute validity of the findings. Finally, the equations for transition probabilities were derived using the general equation for transition probabilities used in model-based economic evaluations, and the parameters were estimated from fitted distributions. The results of the application of the tutorial suggest that the log-logistic model best fits the reconstructed data from the latest published Kaplan-Meier (KM) curves of the BOLERO-2 trial. Results from the regression analyses were confirmed graphically. An equation for transition probabilities was obtained for each arm of the BOLERO-2 trial. In this paper, a tutorial was proposed and used to estimate the transition probabilities for model-based economic evaluation, based on the results of the final PFS analysis of the BOLERO-2 trial in mBC. The results of our study can serve as a basis for any model

Spatial organization of mesenchymal stem cells in vitro--results from a new individual cell-based model with podia.

Directory of Open Access Journals (Sweden)

Martin Hoffmann

Full Text Available Therapeutic application of mesenchymal stem cells (MSC requires their extensive in vitro expansion. MSC in culture typically grow to confluence within a few weeks. They show spindle-shaped fibroblastoid morphology and align to each other in characteristic spatial patterns at high cell density. We present an individual cell-based model (IBM that is able to quantitatively describe the spatio-temporal organization of MSC in culture. Our model substantially improves on previous models by explicitly representing cell podia and their dynamics. It employs podia-generated forces for cell movement and adjusts cell behavior in response to cell density. At the same time, it is simple enough to simulate thousands of cells with reasonable computational effort. Experimental sheep MSC cultures were monitored under standard conditions. Automated image analysis was used to determine the location and orientation of individual cells. Our simulations quantitatively reproduced the observed growth dynamics and cell-cell alignment assuming cell density-dependent proliferation, migration, and morphology. In addition to cell growth on plain substrates our model captured cell alignment on micro-structured surfaces. We propose a specific surface micro-structure that according to our simulations can substantially enlarge cell culture harvest. The 'tool box' of cell migratory behavior newly introduced in this study significantly enhances the bandwidth of IBM. Our approach is capable of accommodating individual cell behavior and collective cell dynamics of a variety of cell types and tissues in computational systems biology.

Efficient Modelling and Generation of Markov Automata (extended version)

NARCIS (Netherlands)

Timmer, Mark; Katoen, Joost P.; van de Pol, Jan Cornelis; Stoelinga, Mariëlle Ida Antoinette

2012-01-01

This paper introduces a framework for the efficient modelling and generation of Markov automata. It consists of (1) the data-rich process-algebraic language MAPA, allowing concise modelling of systems with nondeterminism, probability and Markovian timing; (2) a restricted form of the language, the

Modeling Feedbacks Between Individual Human Decisions and Hydrology Using Interconnected Physical and Social Models

Science.gov (United States)

Murphy, J.; Lammers, R. B.; Proussevitch, A. A.; Ozik, J.; Altaweel, M.; Collier, N. T.; Alessa, L.; Kliskey, A. D.

2014-12-01

The global hydrological cycle intersects with human decision making at multiple scales, from dams and irrigation works to the taps in individuals' homes. Residential water consumers are commonly encouraged to conserve; these messages are heard against a background of individual values and conceptions about water quality, uses, and availability. The degree to which these values impact the larger-hydrological dynamics, the way that changes in those values have impacts on the hydrological cycle through time, and the feedbacks by which water availability and quality in turn shape those values, are not well explored. To investigate this domain we employ a global-scale water balance model (WBM) coupled with a social-science-grounded agent-based model (ABM). The integration of a hydrological model with an agent-based model allows us to explore driving factors in the dynamics in coupled human-natural systems. From the perspective of the physical hydrologist, the ABM offers a richer means of incorporating the human decisions that drive the hydrological system; from the view of the social scientist, a physically-based hydrological model allows the decisions of the agents to play out against constraints faithful to the real world. We apply the interconnected models to a study of Tucson, Arizona, USA, and its role in the larger Colorado River system. Our core concept is Technology-Induced Environmental Distancing (TIED), which posits that layers of technology can insulate consumers from direct knowledge of a resource. In Tucson, multiple infrastructure and institutional layers have arguably increased the conceptual distance between individuals and their water supply, offering a test case of the TIED framework. Our coupled simulation allows us to show how the larger system transforms a resource with high temporal and spatial variability into a consumer constant, and the effects of this transformation on the regional system. We use this to explore how pricing, messaging, and

Generation of long-living entanglement between two distant three-level atoms in non-Markovian environments.

Science.gov (United States)

Li, Chuang; Yang, Sen; Song, Jie; Xia, Yan; Ding, Weiqiang

2017-05-15

In this paper, a scheme for the generation of long-living entanglement between two distant Λ-type three-level atoms separately trapped in two dissipative cavities is proposed. In this scheme, two dissipative cavities are coupled to their own non-Markovian environments and two three-level atoms are driven by the classical fields. The entangled state between the two atoms is produced by performing Bell state measurement (BSM) on photons leaving the dissipative cavities. Using the time-dependent Schördinger equation, we obtain the analytical results for the evolution of the entanglement. It is revealed that, by manipulating the detunings of classical field, the long-living stationary entanglement between two atoms can be generated in the presence of dissipation.

Protecting entanglement by adjusting the velocities of moving qubits inside non-Markovian environments

Science.gov (United States)

Mortezapour, Ali; Ahmadi Borji, Mahdi; Lo Franco, Rosario

2017-05-01

Efficient entanglement preservation in open quantum systems is a crucial scope towards a reliable exploitation of quantum resources. We address this issue by studying how two-qubit entanglement dynamically behaves when two atom qubits move inside two separated identical cavities. The moving qubits independently interact with their respective cavity. As a main general result, we find that under resonant qubit-cavity interaction the initial entanglement between two moving qubits remains closer to its initial value as time passes compared to the case of stationary qubits. In particular, we show that the initial entanglement can be strongly protected from decay by suitably adjusting the velocities of the qubits according to the non-Markovian features of the cavities. Our results supply a further way of preserving quantum correlations against noise with a natural implementation in cavity-QED scenarios and are straightforwardly extendable to many qubits for scalability.

Weibull aging models for the single protective channel unavailability analysis by the device of stages

International Nuclear Information System (INIS)

Nunes, M.E.C.; Noriega, H.C.; Melo, P.F.F.

1997-01-01

Among the features to take into account in the unavailability analysis of protective channels, there is one that plays a dominant role - that of considering the equipment aging. In this sense, the exponential failure model is not adequate, since some transition rates are no more constant. As a consequence, Markovian models cannot be used anymore. As an alternative, one may use the device of stages that allows for transforming a Non Markovian model into an equivalent Markovian one by insertion of a fictitious states set, called stages. For a given time-dependent transition rate, its failure density is analysed as to the best combination of exponential distributions and then the moments of the original distribution and those of the combination are matched to estimate the necessary parameters. In this paper, the aging of the protective channel is supposed to follow Weibull distributions. Typical means and variances for the times to failure are considered and combinations of stages are checked. Initial conditions features are discussed in connection with states that are fictitious and to check the validity of the developed models. Alternative solutions by the discretization of the failure rates are generated. The results obtained agree quite well. (author). 7 refs., 6 figs

Maintenance of polygenic sex determination in a fluctuating environment: an individual-based model.

Science.gov (United States)

Bateman, A W; Anholt, B R

2017-05-01

R. A. Fisher predicted that individuals should invest equally in offspring of both sexes, and that the proportion of males and females produced (the primary sex ratio) should evolve towards 1:1 when unconstrained. For many species, sex determination is dependent on sex chromosomes, creating a strong tendency for balanced sex ratios, but in other cases, multiple autosomal genes interact to determine sex. In such cases, the maintenance of multiple sex-determining alleles at multiple loci and the consequent among-family variability in sex ratios presents a puzzle, as theory predicts that such systems should be unstable. Theory also predicts that environmental influences on sex can complicate outcomes of genetic sex determination, and that population structure may play a role. Tigriopus californicus, a copepod that lives in splash-pool metapopulations and exhibits polygenic and environment-dependent sex determination, presents a test case for relevant theory. We use this species as a model for parameterizing an individual-based simulation to investigate conditions that could maintain polygenic sex determination. We find that metapopulation structure can delay the degradation of polygenic sex determination and that periods of alternating frequency-dependent selection, imposed by seasonal fluctuations in environmental conditions, can maintain polygenic sex determination indefinitely. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Personality prototypes in individuals with compulsive buying based on the Big Five Model.

Science.gov (United States)

Mueller, Astrid; Claes, Laurence; Mitchell, James E; Wonderlich, Steve A; Crosby, Ross D; de Zwaan, Martina

2010-09-01

Personality prototypes based on the Big Five factor model were investigated in a treatment-seeking sample of 68 individuals with compulsive buying (CB). Cluster analysis of the NEO Five-Factor Inventory (NEO-FFI) scales yielded two distinct personality clusters. Participants in cluster II scored significantly higher than those in cluster I on neuroticism and lower on the other four personality traits. Subjects in cluster II showed higher severity of CB, lower degree of control over CB symptoms, and were more anxious, interpersonally sensitive and impulsive. Furthermore, cluster II was characterized by higher rates of comorbid anxiety disorders, and cluster B personality disorders. The two personality prototypes did not differ with respect to obsessive-compulsive features. Finally and of considerable clinical significance, participants in cluster II reported lower remission rates after undergoing cognitive-behavioral therapy. Implications of the results for treatment are discussed. 2010 Elsevier Ltd. All rights reserved.

Using decision models to enhance investigations of individual differences in cognitive neuroscience

Directory of Open Access Journals (Sweden)

Corey N White

2016-02-01

Full Text Available There is great interest in relating individual differences in cognitive processing to activation of neural systems. The general process involves relating measures of task performance like reaction times or accuracy to brain activity to identify individual differences in neural processing. One limitation of this approach is that measures like reaction times can be affected by multiple components of processing. For instance, some individuals might have higher accuracy in a memory task because they respond more cautiously, not because they have better memory. Computational models of decision making, like the drift-diffusion model and the linear ballistic accumulator model, provide a potential solution to this problem. They can be fitted to data from individual participants to disentangle the effects of the different processes driving behavior. In this sense the models can provide cleaner measures of the processes of interest, and enhance our understanding of how neural activity varies across individuals or populations. The advantages of this model-based approach to investigating individual differences in neural activity are discussed with recent examples of how this method can improve our understanding of the brain-behavior relationship.

Early engagement of stakeholders with individual-based modelling can inform research for improving invasive species management: the round goby as a case study

DEFF Research Database (Denmark)

Samson, Emma; Hirsch, Philipp E.; Palmer, Stephen C.

2017-01-01

Individual-based models (IBMs) incorporating realistic representations of key range-front processes such as dispersal can be used as tools to investigate the dynamics of invasive species. Managers can apply insights from these models to take effective action to prevent further spread and prioriti...

Individual-Based Modeling of Tuberculosis in a User-Friendly Interface: Understanding the Epidemiological Role of Population Heterogeneity in a City.

Science.gov (United States)

Prats, Clara; Montañola-Sales, Cristina; Gilabert-Navarro, Joan F; Valls, Joaquim; Casanovas-Garcia, Josep; Vilaplana, Cristina; Cardona, Pere-Joan; López, Daniel

2015-01-01

For millennia tuberculosis (TB) has shown a successful strategy to survive, making it one of the world's deadliest infectious diseases. This resilient behavior is based not only on remaining hidden in most of the infected population, but also by showing slow evolution in most sick people. The course of the disease within a population is highly related to its heterogeneity. Thus, classic epidemiological approaches with a top-down perspective have not succeeded in understanding its dynamics. In the past decade a few individual-based models were built, but most of them preserved a top-down view that makes it difficult to study a heterogeneous population. We propose an individual-based model developed with a bottom-up approach to studying the dynamics of pulmonary TB in a certain population, considered constant. Individuals may belong to the following classes: healthy, infected, sick, under treatment, and treated with a probability of relapse. Several variables and parameters account for their age, origin (native or immigrant), immunodeficiency, diabetes, and other risk factors (smoking and alcoholism). The time within each infection state is controlled, and sick individuals may show a cavitated disease or not that conditions infectiousness. It was implemented in NetLogo because it allows non-modelers to perform virtual experiments with a user-friendly interface. The simulation was conducted with data from Ciutat Vella, a district of Barcelona with an incidence of 67 TB cases per 100,000 inhabitants in 2013. Several virtual experiments were performed to relate the disease dynamics with the structure of the infected subpopulation (e.g., the distribution of infected times). Moreover, the short-term effect of health control policies on modifying that structure was studied. Results show that the characteristics of the population are crucial for the local epidemiology of TB. The developed user-friendly tool is ready to test control strategies of disease in any city in the

An individual-based model of transmission of resistant bacteria in a veterinary teaching hospital.

Directory of Open Access Journals (Sweden)

Neeraj Suthar

Full Text Available Veterinary nosocomial infections caused by antibiotic resistant bacteria cause increased morbidity, higher cost and length of treatment and increased zoonotic risk because of the difficulty in treating them. In this study, an individual-based model was developed to investigate the effects of movements of canine patients among ten areas (transmission points within a veterinary teaching hospital, and the effects of these movements on transmission of antibiotic susceptible and resistant pathogens. The model simulates contamination of transmission points, healthcare workers, and patients as well as the effects of decontamination of transmission points, disinfection of healthcare workers, and antibiotic treatments of canine patients. The model was parameterized using data obtained from hospital records, information obtained by interviews with hospital staff, and the published literature. The model suggested that transmission resulting from contact with healthcare workers was common, and that certain transmission points (housing wards, diagnostics room, and the intensive care unit presented higher risk for transmission than others (lobby and surgery. Sensitivity analyses using a range of parameter values demonstrated that the risk of acquisition of colonization by resistant pathogens decreased with shorter patient hospital stays (P<0.0001, more frequent decontamination of transmission points and disinfection of healthcare workers (P<0.0001 and better compliance of healthcare workers with hygiene practices (P<0.0001. More frequent decontamination of heavily trafficked transmission points was especially effective at reducing transmission of the model pathogen.

An individual-based approach to SIR epidemics in contact networks.

Science.gov (United States)

Youssef, Mina; Scoglio, Caterina

2011-08-21

Many approaches have recently been proposed to model the spread of epidemics on networks. For instance, the Susceptible/Infected/Recovered (SIR) compartmental model has successfully been applied to different types of diseases that spread out among humans and animals. When this model is applied on a contact network, the centrality characteristics of the network plays an important role in the spreading process. However, current approaches only consider an aggregate representation of the network structure, which can result in inaccurate analysis. In this paper, we propose a new individual-based SIR approach, which considers the whole description of the network structure. The individual-based approach is built on a continuous time Markov chain, and it is capable of evaluating the state probability for every individual in the network. Through mathematical analysis, we rigorously confirm the existence of an epidemic threshold below which an epidemic does not propagate in the network. We also show that the epidemic threshold is inversely proportional to the maximum eigenvalue of the network. Additionally, we study the role of the whole spectrum of the network, and determine the relationship between the maximum number of infected individuals and the set of eigenvalues and eigenvectors. To validate our approach, we analytically study the deviation with respect to the continuous time Markov chain model, and we show that the new approach is accurate for a large range of infection strength. Furthermore, we compare the new approach with the well-known heterogeneous mean field approach in the literature. Ultimately, we support our theoretical results through extensive numerical evaluations and Monte Carlo simulations. Published by Elsevier Ltd.

Camera-Model Identification Using Markovian Transition Probability Matrix

Science.gov (United States)

Xu, Guanshuo; Gao, Shang; Shi, Yun Qing; Hu, Ruimin; Su, Wei

Detecting the (brands and) models of digital cameras from given digital images has become a popular research topic in the field of digital forensics. As most of images are JPEG compressed before they are output from cameras, we propose to use an effective image statistical model to characterize the difference JPEG 2-D arrays of Y and Cb components from the JPEG images taken by various camera models. Specifically, the transition probability matrices derived from four different directional Markov processes applied to the image difference JPEG 2-D arrays are used to identify statistical difference caused by image formation pipelines inside different camera models. All elements of the transition probability matrices, after a thresholding technique, are directly used as features for classification purpose. Multi-class support vector machines (SVM) are used as the classification tool. The effectiveness of our proposed statistical model is demonstrated by large-scale experimental results.

Fractional diffusion models of transport in magnetically confined plasmas

International Nuclear Information System (INIS)

Castillo-Negrete, D. del; Carreras, B. A.; Lynch, V. E.

2005-01-01

Experimental and theoretical evidence suggests that transport in magnetically confined fusion plasmas deviates from the standard diffusion paradigm. Some examples include the confinement time scaling in L-mode plasmas, rapid pulse propagation phenomena, and inward transport in off-axis fueling experiments. The limitations of the diffusion paradigm can be traced back to the restrictive assumptions in which it is based. In particular, Fick's law, one of the cornerstones of diffusive transport, assumes that the fluxes only depend on local quantities, i. e. the spatial gradient of the field (s). another key issue is the Markovian assumption that neglects memory effects. Also, at a microscopic level, standard diffusion assumes and underlying Gaussian, uncorrelated stochastic process (i. e. a Brownian random walk) with well defined characteristic spatio-temporal scales. Motivated by the need to develop models of non-diffusive transport, we discuss here a class of transport models base on the use of fractional derivative operators. The models incorporates in a unified way non-Fickian transport, non-Markovian processes or memory effects, and non-diffusive scaling. At a microscopic level, the models describe an underlying stochastic process without characteristic spatio-temporal scales that generalizes the Brownian random walk. As a concrete case study to motivate and test the model, we consider transport of tracers in three-dimensional, pressure-gradient-driven turbulence. We show that in this system transport is non-diffusive and cannot be described in the context of the standard diffusion parading. In particular, the probability density function (pdf) of the radial displacements of tracers is strongly non-Gaussian with algebraic decaying tails, and the moments of the tracer displacements exhibit super-diffusive scaling. there is quantitative agreement between the turbulence transport calculations and the proposed fractional diffusion model. In particular, the model

Model Of Emergency Department Nurse Performance Improvement Based on Association of Individual Characteristic, Organization Characteristic and Job Characteristic

OpenAIRE

Bogar, Maria Margaretha; Nursalam, Nursalam; Dewi, Yulis Setiya

2017-01-01

Introduction: Nursing care is integral part of health care and having important role in management of patient with emergency condition. The purpose of this research was to develop nurse performance improvement model based on individual, organization and job characteristics association in Emergency Department of RSUD dr TC Hillers Maumere. Method: This was an explanative survey by cross sectional approach held on July -August 2012. Respondents in this study were 22 nurses and 44 patients were ...

Effects of streamflow diversion on a fish population: combining empirical data and individual-based models in a site-specific evaluation

Science.gov (United States)

Bret C. Harvey; Jason L. White; Rodney J. Nakamoto; Steven F. Railsback

2014-01-01

Resource managers commonly face the need to evaluate the ecological consequences of specific water diversions of small streams. We addressed this need by conducting 4 years of biophysical monitoring of stream reaches above and below a diversion and applying two individual-based models of salmonid fish that simulated different levels of behavioral complexity. The...

On the structure of the space of geometric product-form models

NARCIS (Netherlands)

Bayer, Nimrod; Boucherie, Richardus J.

2002-01-01

This article deals with Markovian models defined on a finite-dimensional discrete state space and possess a stationary state distribution of a product-form. We view the space of such models as a mathematical object and explore its structure. We focus on models on an orthant [script Z]+n, which are

Semigroup evolution in the Wigner-Weisskopf pole approximation with Markovian spectral coupling

International Nuclear Information System (INIS)

Shikerman, F.; Peer, A.; Horwitz, L. P.

2011-01-01

We establish the relation between the Wigner-Weisskopf theory for the description of an unstable system and the theory of coupling to an environment. According to the Wigner-Weisskopf general approach, even within the pole approximation, the evolution of a total system subspace is not an exact semigroup for multichannel decay unless the projectors into eigenstates of the reduced evolution generator W(z) are orthogonal. With multichannel decay, the projectors must be evaluated at different pole locations z α ≠z β , and since the orthogonality relation does not generally hold at different values of z, the semigroup evolution is a poor approximation for the multichannel decay, even for very weak coupling. Nevertheless, if the theory is generalized to take into account interactions with an environment, one can ensure orthogonality of the W(z) projectors regardless of the number of poles. Such a possibility occurs when W(z), and hence its eigenvectors, is independent of z, which corresponds to the Markovian limit of the coupling to the continuum spectrum.

Semigroup evolution in the Wigner-Weisskopf pole approximation with Markovian spectral coupling

Energy Technology Data Exchange (ETDEWEB)

Shikerman, F.; Peer, A. [Physics department and BINA center for nano-technology, Bar Ilan University, Ramat Gan 52900 (Israel); Horwitz, L. P. [Physics department and BINA center for nano-technology, Bar Ilan University, Ramat Gan 52900 (Israel); School of Physics, Tel-Aviv University, Ramat-Aviv 69978 (Israel); Department of Physics, Ariel University Center of Samaria, Ariel 40700 (Israel)

2011-07-15

We establish the relation between the Wigner-Weisskopf theory for the description of an unstable system and the theory of coupling to an environment. According to the Wigner-Weisskopf general approach, even within the pole approximation, the evolution of a total system subspace is not an exact semigroup for multichannel decay unless the projectors into eigenstates of the reduced evolution generator W(z) are orthogonal. With multichannel decay, the projectors must be evaluated at different pole locations z{sub {alpha}}{ne}z{sub {beta}}, and since the orthogonality relation does not generally hold at different values of z, the semigroup evolution is a poor approximation for the multichannel decay, even for very weak coupling. Nevertheless, if the theory is generalized to take into account interactions with an environment, one can ensure orthogonality of the W(z) projectors regardless of the number of poles. Such a possibility occurs when W(z), and hence its eigenvectors, is independent of z, which corresponds to the Markovian limit of the coupling to the continuum spectrum.

Individualizing Services, Individualizing Responsibility

DEFF Research Database (Denmark)

Garsten, Christina; Hollertz, Katarina; Jacobsson, Kerstin

possibilities for individual voice, autonomy and self-determination in the local delivery of activation policy? What barriers do specific organisational models and practices imply for clients to choose, determine and access tailor-made programmes and services? What policy technologies are at work in governing......-oriented, and the normative demands placed on individuals appear increasingly totalizing, concerning the whole individual rather than the job-related aspects only. The paper is based on 23 in-depth interviews with individual clients as well as individual caseworkers and other professionals engaged in client-related work...

A lattice-model representation of continuous-time random walks

International Nuclear Information System (INIS)

Campos, Daniel; Mendez, Vicenc

2008-01-01

We report some ideas for constructing lattice models (LMs) as a discrete approach to the reaction-dispersal (RD) or reaction-random walks (RRW) models. The analysis of a rather general class of Markovian and non-Markovian processes, from the point of view of their wavefront solutions, let us show that in some regimes their macroscopic dynamics (front speed) turns out to be different from that by classical reaction-diffusion equations, which are often used as a mean-field approximation to the problem. So, the convenience of a more general framework as that given by the continuous-time random walks (CTRW) is claimed. Here we use LMs as a numerical approach in order to support that idea, while in previous works our discussion was restricted to analytical models. For the two specific cases studied here, we derive and analyze the mean-field expressions for our LMs. As a result, we are able to provide some links between the numerical and analytical approaches studied

A lattice-model representation of continuous-time random walks

Energy Technology Data Exchange (ETDEWEB)

Campos, Daniel [School of Mathematics, Department of Applied Mathematics, University of Manchester, Manchester M60 1QD (United Kingdom); Mendez, Vicenc [Grup de Fisica Estadistica, Departament de Fisica, Universitat Autonoma de Barcelona, 08193 Bellaterra (Barcelona) (Spain)], E-mail: daniel.campos@uab.es, E-mail: vicenc.mendez@uab.es

2008-02-29

We report some ideas for constructing lattice models (LMs) as a discrete approach to the reaction-dispersal (RD) or reaction-random walks (RRW) models. The analysis of a rather general class of Markovian and non-Markovian processes, from the point of view of their wavefront solutions, let us show that in some regimes their macroscopic dynamics (front speed) turns out to be different from that by classical reaction-diffusion equations, which are often used as a mean-field approximation to the problem. So, the convenience of a more general framework as that given by the continuous-time random walks (CTRW) is claimed. Here we use LMs as a numerical approach in order to support that idea, while in previous works our discussion was restricted to analytical models. For the two specific cases studied here, we derive and analyze the mean-field expressions for our LMs. As a result, we are able to provide some links between the numerical and analytical approaches studied.

Individualized Positron Emission Tomography–Based Isotoxic Accelerated Radiation Therapy Is Cost-Effective Compared With Conventional Radiation Therapy: A Model-Based Evaluation

Energy Technology Data Exchange (ETDEWEB)

Bongers, Mathilda L., E-mail: ml.bongers@vumc.nl [Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam (Netherlands); Coupé, Veerle M.H. [Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam (Netherlands); De Ruysscher, Dirk [Radiation Oncology University Hospitals Leuven/KU Leuven, Leuven (Belgium); Department of Radiation Oncology, GROW Research Institute, Maastricht University Medical Center, Maastricht (Netherlands); Oberije, Cary; Lambin, Philippe [Department of Radiation Oncology, GROW Research Institute, Maastricht University Medical Center, Maastricht (Netherlands); Uyl-de Groot, Cornelia A. [Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam (Netherlands); Institute for Medical Technology Assessment, Erasmus University Rotterdam, Rotterdam (Netherlands)

2015-03-15

Purpose: To evaluate long-term health effects, costs, and cost-effectiveness of positron emission tomography (PET)-based isotoxic accelerated radiation therapy treatment (PET-ART) compared with conventional fixed-dose CT-based radiation therapy treatment (CRT) in non-small cell lung cancer (NSCLC). Methods and Materials: Our analysis uses a validated decision model, based on data of 200 NSCLC patients with inoperable stage I-IIIB. Clinical outcomes, resource use, costs, and utilities were obtained from the Maastro Clinic and the literature. Primary model outcomes were the difference in life-years (LYs), quality-adjusted life-years (QALYs), costs, and the incremental cost-effectiveness and cost/utility ratio (ICER and ICUR) of PET-ART versus CRT. Model outcomes were obtained from averaging the predictions for 50,000 simulated patients. A probabilistic sensitivity analysis and scenario analyses were carried out. Results: The average incremental costs per patient of PET-ART were €569 (95% confidence interval [CI] €−5327-€6936) for 0.42 incremental LYs (95% CI 0.19-0.61) and 0.33 QALYs gained (95% CI 0.13-0.49). The base-case scenario resulted in an ICER of €1360 per LY gained and an ICUR of €1744 per QALY gained. The probabilistic analysis gave a 36% probability that PET-ART improves health outcomes at reduced costs and a 64% probability that PET-ART is more effective at slightly higher costs. Conclusion: On the basis of the available data, individualized PET-ART for NSCLC seems to be cost-effective compared with CRT.

Modeling structural, dyadic, and individual factors: the inclusion and exclusion model of HIV related behavior.

Science.gov (United States)

Albarracin, Dolores; Tannenbaum, Melanie B; Glasman, Laura R; Rothman, Alexander J

2010-12-01

Changing HIV-related behaviors requires addressing the individual, dyadic, and structural influences that shape them. This supplement of AIDS & Behavior presents frameworks that integrate these three influences on behavior. Concepts from these frameworks were selected to model the processes by which structural factors affect individual HIV-related behavior. In the Inclusion/Exclusion Model, material and symbolic inclusions and exclusions (sharing versus denying resources) regulate individuals' ability and motivation to detect, prevent, and treat HIV. Structural interventions create inclusions that increase one's ability or motivation to perform these behaviors or exclusions that hinder one's ability or motivation to execute counterproductive behaviors. The need to expand research regarding multilevel influences on HIV-related behavior is also discussed, particularly concerning further understanding of sustained behavior change and effective dissemination of evidence-based intervention strategies.

GPS-based microenvironment tracker (MicroTrac) model to estimate time-location of individuals for air pollution exposure assessments: model evaluation in central North Carolina.

Science.gov (United States)

Breen, Michael S; Long, Thomas C; Schultz, Bradley D; Crooks, James; Breen, Miyuki; Langstaff, John E; Isaacs, Kristin K; Tan, Yu-Mei; Williams, Ronald W; Cao, Ye; Geller, Andrew M; Devlin, Robert B; Batterman, Stuart A; Buckley, Timothy J

2014-07-01

A critical aspect of air pollution exposure assessment is the estimation of the time spent by individuals in various microenvironments (ME). Accounting for the time spent in different ME with different pollutant concentrations can reduce exposure misclassifications, while failure to do so can add uncertainty and bias to risk estimates. In this study, a classification model, called MicroTrac, was developed to estimate time of day and duration spent in eight ME (indoors and outdoors at home, work, school; inside vehicles; other locations) from global positioning system (GPS) data and geocoded building boundaries. Based on a panel study, MicroTrac estimates were compared with 24-h diary data from nine participants, with corresponding GPS data and building boundaries of home, school, and work. MicroTrac correctly classified the ME for 99.5% of the daily time spent by the participants. The capability of MicroTrac could help to reduce the time-location uncertainty in air pollution exposure models and exposure metrics for individuals in health studies.

Design of robust reliable control for T-S fuzzy Markovian jumping delayed neutral type neural networks with probabilistic actuator faults and leakage delays: An event-triggered communication scheme.

Science.gov (United States)

Syed Ali, M; Vadivel, R; Saravanakumar, R

2018-06-01

This study examines the problem of robust reliable control for Takagi-Sugeno (T-S) fuzzy Markovian jumping delayed neural networks with probabilistic actuator faults and leakage terms. An event-triggered communication scheme. First, the randomly occurring actuator faults and their failures rates are governed by two sets of unrelated random variables satisfying certain probabilistic failures of every actuator, new type of distribution based event triggered fault model is proposed, which utilize the effect of transmission delay. Second, Takagi-Sugeno (T-S) fuzzy model is adopted for the neural networks and the randomness of actuators failures is modeled in a Markov jump model framework. Third, to guarantee the considered closed-loop system is exponential mean square stable with a prescribed reliable control performance, a Markov jump event-triggered scheme is designed in this paper, which is the main purpose of our study. Fourth, by constructing appropriate Lyapunov-Krasovskii functional, employing Newton-Leibniz formulation and integral inequalities, several delay-dependent criteria for the solvability of the addressed problem are derived. The obtained stability criteria are stated in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Finally, numerical examples are given to illustrate the effectiveness and reduced conservatism of the proposed results over the existing ones, among them one example was supported by real-life application of the benchmark problem. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Pricing Options and Equity-Indexed Annuities in a Regime-switching Model by Trinomial Tree Method

Directory of Open Access Journals (Sweden)

Fei Lung Yuen

2011-12-01

Full Text Available In this paper we summarize the main idea and results of Yuen and Yang (2009, 2010a, 2010b and provide some results on pricing of Parisian options under the Markov regime-switching model (MRSM. The MRSM allows the parameters of the market model depending on a Markovian process, and the model can reflect the information of the market environment which cannot be modeled solely by linear Gaussian process. However, when the parameters of the stock price model are not constant but governed by a Markovian process, the pricing of the options becomes complex. We present a fast and simple trinomial tree model to price options in MRSM. In recent years, the pricing of modern insurance products, such as Equity-Indexed annuity (EIA and variable annuities (VAs, has become a popular topic. We show here that our trinomial tree model can been used to price EIA with strong path dependent exotic options in the regime switching model.

Omics approaches to individual variation: modeling networks and the virtual patient

OpenAIRE

Lehrach, Hans

2016-01-01

Every human is unique. We differ in our genomes, environment, behavior, disease history, and past and current medical treatment?a complex catalog of differences that often leads to variations in the way each of us responds to a particular therapy. We argue here that true personalization of drug therapies will rely on ?virtual patient? models based on a detailed characterization of the individual patient by molecular, imaging, and sensor techniques. The models will be based, wherever possible,...

Design of Individualized Wheelchairs Using AHP and Kano Model

Directory of Open Access Journals (Sweden)

Yanli Yuan

2014-06-01

Full Text Available To study how to design different grades of individualized wheelchairs according to users' needs, a personalized wheelchair design method based on AHP and Kano model is proposed. The AHP model determines the relative importance of characteristics of customers' demands. The subfunctions of manual wheelchairs and their attributes are given. The weight coefficients are calculated. 20 experts (10 are the members of the research team, 5 are doctors, and 5 are wheelchair designers are involved in the above two parts of the work. Kano model represents the types of user requirements. 30 participants' (wheelchair users needs are divided into 5 categories: M, O, E, I, and R. According to the types of user needs and the weight of each subfunction, three manual wheelchair models are built. Traditional design method usually cannot satisfy the requirements of users and product structure, so this paper makes a contribution to solve this problem. The method can be used to design individualized wheelchairs which may improve the product quality and customers' satisfaction. Meanwhile it also can reduce the design time, thereby reducing the design cost.

Models and Methods for Adaptive Management of Individual and Team-Based Training Using a Simulator

Science.gov (United States)

Lisitsyna, L. S.; Smetyuh, N. P.; Golikov, S. P.

2017-05-01

Research of adaptive individual and team-based training has been analyzed and helped find out that both in Russia and abroad, individual and team-based training and retraining of AASTM operators usually includes: production training, training of general computer and office equipment skills, simulator training including virtual simulators which use computers to simulate real-world manufacturing situation, and, as a rule, the evaluation of AASTM operators’ knowledge determined by completeness and adequacy of their actions under the simulated conditions. Such approach to training and re-training of AASTM operators stipulates only technical training of operators and testing their knowledge based on assessing their actions in a simulated environment.

Markovian robots: Minimal navigation strategies for active particles

Science.gov (United States)

Nava, Luis Gómez; Großmann, Robert; Peruani, Fernando

2018-04-01

We explore minimal navigation strategies for active particles in complex, dynamical, external fields, introducing a class of autonomous, self-propelled particles which we call Markovian robots (MR). These machines are equipped with a navigation control system (NCS) that triggers random changes in the direction of self-propulsion of the robots. The internal state of the NCS is described by a Boolean variable that adopts two values. The temporal dynamics of this Boolean variable is dictated by a closed Markov chain—ensuring the absence of fixed points in the dynamics—with transition rates that may depend exclusively on the instantaneous, local value of the external field. Importantly, the NCS does not store past measurements of this value in continuous, internal variables. We show that despite the strong constraints, it is possible to conceive closed Markov chain motifs that lead to nontrivial motility behaviors of the MR in one, two, and three dimensions. By analytically reducing the complexity of the NCS dynamics, we obtain an effective description of the long-time motility behavior of the MR that allows us to identify the minimum requirements in the design of NCS motifs and transition rates to perform complex navigation tasks such as adaptive gradient following, detection of minima or maxima, or selection of a desired value in a dynamical, external field. We put these ideas in practice by assembling a robot that operates by the proposed minimalistic NCS to evaluate the robustness of MR, providing a proof of concept that is possible to navigate through complex information landscapes with such a simple NCS whose internal state can be stored in one bit. These ideas may prove useful for the engineering of miniaturized robots.

Real-time individualization of the unified model of performance.

Science.gov (United States)

Liu, Jianbo; Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Balkin, Thomas J; Reifman, Jaques

2017-12-01

Existing mathematical models for predicting neurobehavioural performance are not suited for mobile computing platforms because they cannot adapt model parameters automatically in real time to reflect individual differences in the effects of sleep loss. We used an extended Kalman filter to develop a computationally efficient algorithm that continually adapts the parameters of the recently developed Unified Model of Performance (UMP) to an individual. The algorithm accomplishes this in real time as new performance data for the individual become available. We assessed the algorithm's performance by simulating real-time model individualization for 18 subjects subjected to 64 h of total sleep deprivation (TSD) and 7 days of chronic sleep restriction (CSR) with 3 h of time in bed per night, using psychomotor vigilance task (PVT) data collected every 2 h during wakefulness. This UMP individualization process produced parameter estimates that progressively approached the solution produced by a post-hoc fitting of model parameters using all data. The minimum number of PVT measurements needed to individualize the model parameters depended upon the type of sleep-loss challenge, with ~30 required for TSD and ~70 for CSR. However, model individualization depended upon the overall duration of data collection, yielding increasingly accurate model parameters with greater number of days. Interestingly, reducing the PVT sampling frequency by a factor of two did not notably hamper model individualization. The proposed algorithm facilitates real-time learning of an individual's trait-like responses to sleep loss and enables the development of individualized performance prediction models for use in a mobile computing platform. © 2017 European Sleep Research Society.

Role of complementary correlations in the evolution of classical and quantum correlations under Markovian decoherence

International Nuclear Information System (INIS)

Deb, Prasenjit; Banik, Manik

2015-01-01

Quantum correlation lies at the very heart of almost all of the non-classical phenomena exhibited by quantum systems composed of two or more subsystems. In recent times it has been pointed out that there is a kind of quantum correlation, namely discord, which is more general than entanglement. Some authors have investigated the phenomenon that for certain initial states the quantum correlations as well as the classical correlations exhibit sudden change under simple Markovian noise. We show that this dynamical behavior of the correlations of both types can be explained using the idea of complementary correlations. We also show that though a certain class of mixed entangled states can resist the monotonic decay of quantum correlations, this is not true for all mixed states. Moreover, pure entangled states of two qubits will never exhibit such sudden change. (paper)

Pattern formation in individual-based systems with time-varying parameters

Science.gov (United States)

Ashcroft, Peter; Galla, Tobias

2013-12-01

We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

Stability Analysis of Networked Control Systems with Random Time Delays and Packet Dropouts Modeled by Markov Chains

Directory of Open Access Journals (Sweden)

Li Qiu

2013-01-01

unified Markov jump model. The random time delays and packet dropouts existed in feedback communication link are modeled by two independent Markov chains; the resulting closed-loop system is described by a new Markovian jump linear system (MJLS with Markov delays. Sufficient conditions of the stochastic stability for NCSs is obtained by constructing a novel Lyapunov functional, and the mode-dependent output feedback controller design method is presented based on linear matrix inequality (LMI technique. A numerical example is given to illustrate the effectiveness of the proposed method.

Modeling decisions from experience: How models with a set of parameters for aggregate choices explain individual choices

Directory of Open Access Journals (Sweden)

Neha Sharma

2017-10-01

Full Text Available One of the paradigms (called “sampling paradigm” in judgment and decision-making involves decision-makers sample information before making a final consequential choice. In the sampling paradigm, certain computational models have been proposed where a set of single or distribution parameters is calibrated to the choice proportions of a group of participants (aggregate and hierarchical models. However, currently little is known on how aggregate and hierarchical models would account for choices made by individual participants in the sampling paradigm. In this paper, we test the ability of aggregate and hierarchical models to explain choices made by individual participants. Several models, Ensemble, Cumulative Prospect Theory (CPT, Best Estimation and Simulation Techniques (BEAST, Natural-Mean Heuristic (NMH, and Instance-Based Learning (IBL, had their parameters calibrated to individual choices in a large dataset involving the sampling paradigm. Later, these models were generalized to two large datasets in the sampling paradigm. Results revealed that the aggregate models (like CPT and IBL accounted for individual choices better than hierarchical models (like Ensemble and BEAST upon generalization to problems that were like those encountered during calibration. Furthermore, the CPT model, which relies on differential valuing of gains and losses, respectively, performed better than other models during calibration and generalization on datasets with similar set of problems. The IBL model, relying on recency and frequency of sampled information, and the NMH model, relying on frequency of sampled information, performed better than other models during generalization to a challenging dataset. Sequential analyses of results from different models showed how these models accounted for transitions from the last sample to final choice in human data. We highlight the implications of using aggregate and hierarchical models in explaining individual choices

An example of population-level risk assessments for small mammals using individual-based population models.

Science.gov (United States)

Schmitt, Walter; Auteri, Domenica; Bastiansen, Finn; Ebeling, Markus; Liu, Chun; Luttik, Robert; Mastitsky, Sergey; Nacci, Diane; Topping, Chris; Wang, Magnus

2016-01-01

This article presents a case study demonstrating the application of 3 individual-based, spatially explicit population models (IBMs, also known as agent-based models) in ecological risk assessments to predict long-term effects of a pesticide to populations of small mammals. The 3 IBMs each used a hypothetical fungicide (FungicideX) in different scenarios: spraying in cereals (common vole, Microtus arvalis), spraying in orchards (field vole, Microtus agrestis), and cereal seed treatment (wood mouse, Apodemus sylvaticus). Each scenario used existing model landscapes, which differed greatly in size and structural complexity. The toxicological profile of FungicideX was defined so that the deterministic long-term first tier risk assessment would result in high risk to small mammals, thus providing the opportunity to use the IBMs for risk assessment refinement (i.e., higher tier risk assessment). Despite differing internal model design and scenarios, results indicated in all 3 cases low population sensitivity unless FungicideX was applied at very high (×10) rates. Recovery from local population impacts was generally fast. Only when patch extinctions occured in simulations of intentionally high acute toxic effects, recovery periods, then determined by recolonization, were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report. However, further investigation and agreement are needed to develop recommendations for landscape attributes such as size, structure, and crop rotation to define appropriate regulatory risk assessment scenarios. Overall, the application of IBMs provides multiple advantages to higher tier ecological risk assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios. © 2015 SETAC.

Stochastic Stability for Time-Delay Markovian Jump Systems with Sector-Bounded Nonlinearities and More General Transition Probabilities

Directory of Open Access Journals (Sweden)

Dan Ye

2013-01-01

Full Text Available This paper is concerned with delay-dependent stochastic stability for time-delay Markovian jump systems (MJSs with sector-bounded nonlinearities and more general transition probabilities. Different from the previous results where the transition probability matrix is completely known, a more general transition probability matrix is considered which includes completely known elements, boundary known elements, and completely unknown ones. In order to get less conservative criterion, the state and transition probability information is used as much as possible to construct the Lyapunov-Krasovskii functional and deal with stability analysis. The delay-dependent sufficient conditions are derived in terms of linear matrix inequalities to guarantee the stability of systems. Finally, numerical examples are exploited to demonstrate the effectiveness of the proposed method.

Low Tree-Growth Elasticity of Forest Biomass Indicated by an Individual-Based Model

Directory of Open Access Journals (Sweden)

Robbie A. Hember

2018-01-01

Full Text Available Environmental conditions and silviculture fundamentally alter the metabolism of individual trees and, therefore, need to be studied at that scale. However, changes in forest biomass density (Mg C ha−1 may be decoupled from changes in growth (kg C year−1 when the latter also accelerates the life cycle of trees and strains access to light, nutrients, and water. In this study, we refer to an individual-based model of forest biomass dynamics to constrain the magnitude of system feedbacks associated with ontogeny and competition and estimate the scaling relationship between changes in tree growth and forest biomass density. The model was driven by fitted equations of annual aboveground biomass growth (Gag, probability of recruitment (Pr, and probability of mortality (Pm parameterized against field observations of black spruce (Picea mariana (Mill. BSP, interior Douglas-fir (Pseudotsuga menziesii var. glauca (Beissn. Franco, and western hemlock (Tsuga heterophylla (Raf. Sarg.. A hypothetical positive step-change in mean tree growth was imposed half way through the simulations and landscape-scale responses were then evaluated by comparing pre- and post-stimulus periods. Imposing a 100% increase in tree growth above calibrated predictions (i.e., contemporary rates only translated into 36% to 41% increases in forest biomass density. This corresponded with a tree-growth elasticity of forest biomass (εG,SB ranging from 0.33 to 0.55. The inelastic nature of stand biomass density was attributed to the dependence of mortality on intensity of competition and tree size, which decreased stand density by 353 to 495 trees ha−1, and decreased biomass residence time by 10 to 23 years. Values of εG,SB depended on the magnitude of the stimulus. For example, a retrospective scenario in which tree growth increased from 50% below contemporary rates up to contemporary rates indicated values of εG,SB ranging from 0.66 to 0.75. We conclude that: (1 effects of

State-age-dependent maintenance policies for deteriorating systems with Erlang sojourn time distributions

International Nuclear Information System (INIS)

Yeh, R.H.

1997-01-01

This paper investigates state-age-dependent maintenance policies for multistate deteriorating systems with Erlang sojourn time distributions. Since Erlang distributions are serial combinations of exponential phases, the deteriorating process can be modeled by a multi-phase Markovian model and hence easily analyzed. Based on the Markovian model, the optimal phase-dependent inspection and replacement policy can be obtained by using a policy improvement algorithm. However, since phases are fictitious and can not be identified by inspections, two procedures are developed to construct state-age-dependent policies based on the optimal phase-dependent policy. The properties of the constructed state-age-dependent policies are further investigated and the performance of the policy is evaluated through a numerical example

GPS-based microenvironment tracker (MicroTrac) model to estimate time–location of individuals for air pollution exposure assessments: Model evaluation in central North Carolina

Science.gov (United States)

Breen, Michael S.; Long, Thomas C.; Schultz, Bradley D.; Crooks, James; Breen, Miyuki; Langstaff, John E.; Isaacs, Kristin K.; Tan, Yu-Mei; Williams, Ronald W.; Cao, Ye; Geller, Andrew M.; Devlin, Robert B.; Batterman, Stuart A.; Buckley, Timothy J.

2014-01-01

A critical aspect of air pollution exposure assessment is the estimation of the time spent by individuals in various microenvironments (ME). Accounting for the time spent in different ME with different pollutant concentrations can reduce exposure misclassifications, while failure to do so can add uncertainty and bias to risk estimates. In this study, a classification model, called MicroTrac, was developed to estimate time of day and duration spent in eight ME (indoors and outdoors at home, work, school; inside vehicles; other locations) from global positioning system (GPS) data and geocoded building boundaries. Based on a panel study, MicroTrac estimates were compared with 24-h diary data from nine participants, with corresponding GPS data and building boundaries of home, school, and work. MicroTrac correctly classified the ME for 99.5% of the daily time spent by the participants. The capability of MicroTrac could help to reduce the time–location uncertainty in air pollution exposure models and exposure metrics for individuals in health studies. PMID:24619294

Modeling Individual Cyclic Variation in Human Behavior.

Science.gov (United States)

Pierson, Emma; Althoff, Tim; Leskovec, Jure

2018-04-01

Cycles are fundamental to human health and behavior. Examples include mood cycles, circadian rhythms, and the menstrual cycle. However, modeling cycles in time series data is challenging because in most cases the cycles are not labeled or directly observed and need to be inferred from multidimensional measurements taken over time. Here, we present Cyclic Hidden Markov Models (CyH-MMs) for detecting and modeling cycles in a collection of multidimensional heterogeneous time series data. In contrast to previous cycle modeling methods, CyHMMs deal with a number of challenges encountered in modeling real-world cycles: they can model multivariate data with both discrete and continuous dimensions; they explicitly model and are robust to missing data; and they can share information across individuals to accommodate variation both within and between individual time series. Experiments on synthetic and real-world health-tracking data demonstrate that CyHMMs infer cycle lengths more accurately than existing methods, with 58% lower error on simulated data and 63% lower error on real-world data compared to the best-performing baseline. CyHMMs can also perform functions which baselines cannot: they can model the progression of individual features/symptoms over the course of the cycle, identify the most variable features, and cluster individual time series into groups with distinct characteristics. Applying CyHMMs to two real-world health-tracking datasets-of human menstrual cycle symptoms and physical activity tracking data-yields important insights including which symptoms to expect at each point during the cycle. We also find that people fall into several groups with distinct cycle patterns, and that these groups differ along dimensions not provided to the model. For example, by modeling missing data in the menstrual cycles dataset, we are able to discover a medically relevant group of birth control users even though information on birth control is not given to the model.

On changes of measure in stochastic volatility models

Directory of Open Access Journals (Sweden)

Bernard Wong

2006-01-01

models. This had led many researchers to “assume the condition away,” even though the condition is not innocuous, and nonsensical results can occur if it is in fact not satisfied. We provide an applicable theorem to check the conditions for a general class of Markovian stochastic volatility models. As an example we will also provide a detailed analysis of the Stein and Stein and Heston stochastic volatility models.

Modelling of individual subject ozone exposure response kinetics.

Science.gov (United States)

Schelegle, Edward S; Adams, William C; Walby, William F; Marion, M Susan

2012-06-01

A better understanding of individual subject ozone (O(3)) exposure response kinetics will provide insight into how to improve models used in the risk assessment of ambient ozone exposure. To develop a simple two compartment exposure-response model that describes individual subject decrements in forced expiratory volume in one second (FEV(1)) induced by the acute inhalation of O(3) lasting up to 8 h. FEV(1) measurements of 220 subjects who participated in 14 previously completed studies were fit to the model using both particle swarm and nonlinear least squares optimization techniques to identify three subject-specific coefficients producing minimum "global" and local errors, respectively. Observed and predicted decrements in FEV(1) of the 220 subjects were used for validation of the model. Further validation was provided by comparing the observed O(3)-induced FEV(1) decrements in an additional eight studies with predicted values obtained using model coefficients estimated from the 220 subjects used in cross validation. Overall the individual subject measured and modeled FEV(1) decrements were highly correlated (mean R(2) of 0.69 ± 0.24). In addition, it was shown that a matrix of individual subject model coefficients can be used to predict the mean and variance of group decrements in FEV(1). This modeling approach provides insight into individual subject O(3) exposure response kinetics and provides a potential starting point for improving the risk assessment of environmental O(3) exposure.

Hoelder continuity properties of Euclidean fields in some models of Markovian and non-Markovian field theory

International Nuclear Information System (INIS)

Haba, Z.

1981-01-01

In the usual models of Euclidean field theory the Schwinger functions are moments of a positive measure. In this paper the author discusses the basic properties of the measure μ, i.e. properties of the sample paths of the random field. (Auth.)

An individual-based model of the evolution of pesticide resistance in heterogeneous environments: control of Meligethes aeneus population in oilseed rape crops.

Science.gov (United States)

Stratonovitch, Pierre; Elias, Jan; Denholm, Ian; Slater, Russell; Semenov, Mikhail A

2014-01-01

Preventing a pest population from damaging an agricultural crop and, at the same time, preventing the development of pesticide resistance is a major challenge in crop protection. Understanding how farming practices and environmental factors interact with pest characteristics to influence the spread of resistance is a difficult and complex task. It is extremely challenging to investigate such interactions experimentally at realistic spatial and temporal scales. Mathematical modelling and computer simulation have, therefore, been used to analyse resistance evolution and to evaluate potential resistance management tactics. Of the many modelling approaches available, individual-based modelling of a pest population offers most flexibility to include and analyse numerous factors and their interactions. Here, a pollen beetle (Meligethes aeneus) population was modelled as an aggregate of individual insects inhabiting a spatially heterogeneous landscape. The development of the pest and host crop (oilseed rape) was driven by climatic variables. The agricultural land of the landscape was managed by farmers applying a specific rotation and crop protection strategy. The evolution of a single resistance allele to the pyrethroid lambda cyhalothrin was analysed for different combinations of crop management practices and for a recessive, intermediate and dominant resistance allele. While the spread of a recessive resistance allele was severely constrained, intermediate or dominant resistance alleles showed a similar response to the management regime imposed. Calendar treatments applied irrespective of pest density accelerated the development of resistance compared to ones applied in response to prescribed pest density thresholds. A greater proportion of spring-sown oilseed rape was also found to increase the speed of resistance as it increased the period of insecticide exposure. Our study demonstrates the flexibility and power of an individual-based model to simulate how farming

An individual-based model of the evolution of pesticide resistance in heterogeneous environments: control of Meligethes aeneus population in oilseed rape crops.

Directory of Open Access Journals (Sweden)

Pierre Stratonovitch

Full Text Available Preventing a pest population from damaging an agricultural crop and, at the same time, preventing the development of pesticide resistance is a major challenge in crop protection. Understanding how farming practices and environmental factors interact with pest characteristics to influence the spread of resistance is a difficult and complex task. It is extremely challenging to investigate such interactions experimentally at realistic spatial and temporal scales. Mathematical modelling and computer simulation have, therefore, been used to analyse resistance evolution and to evaluate potential resistance management tactics. Of the many modelling approaches available, individual-based modelling of a pest population offers most flexibility to include and analyse numerous factors and their interactions. Here, a pollen beetle (Meligethes aeneus population was modelled as an aggregate of individual insects inhabiting a spatially heterogeneous landscape. The development of the pest and host crop (oilseed rape was driven by climatic variables. The agricultural land of the landscape was managed by farmers applying a specific rotation and crop protection strategy. The evolution of a single resistance allele to the pyrethroid lambda cyhalothrin was analysed for different combinations of crop management practices and for a recessive, intermediate and dominant resistance allele. While the spread of a recessive resistance allele was severely constrained, intermediate or dominant resistance alleles showed a similar response to the management regime imposed. Calendar treatments applied irrespective of pest density accelerated the development of resistance compared to ones applied in response to prescribed pest density thresholds. A greater proportion of spring-sown oilseed rape was also found to increase the speed of resistance as it increased the period of insecticide exposure. Our study demonstrates the flexibility and power of an individual-based model to

THE DYNAMIC MODEL FOR CONTROL OF STUDENT’S LEARNING INDIVIDUAL TRAJECTORY

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A. A. Mitsel

2015-01-01

Full Text Available In connection with the transition of the educational system to a competence-oriented approach, the problem of learning outcomes assessment and creating an individual learning trajectory of a student has become relevant. Its solution requires the application of modern information technologies. The third generation of Federal state educational standards of higher professional education (FSES HPE defines the requirements for the results of Mastering the basic educational programs (BEP. According to FSES HPE up to 50% of subjects have a variable character, i.e. depend on the choice of a student. It significantly influences on the results of developing various competencies. The problem of forming student’s learning trajectory is analyzed in general and the choice of an individual direction was studied in details. Various methods, models and algorithms of the student’s individual learning trajectory formation were described. The analysis of the model of educational process organization in terms of individual approach makes it possible to develop a decision support system (DSS. DSS is a set of interrelated programs and data used for analysis of situation, development of alternative solutions and selection of the most acceptable alternative. DSSs are often used when building individual learning path, because this task can be considered as a discrete multi-criteria problem, creating a significant burden on the decision maker. A new method of controlling the learning trajectory has been developed. The article discusses problem statement and solution of determining student’s optimal individual educational trajectory as a dynamic model of learning trajectory control, which uses score assessment to construct a sequence of studied subjects. A new model of management learning trajectory is based on dynamic models for tracking the reference trajectory. The task can be converted to an equivalent model of linear programming, for which a reliable solution

Cloud Shade by Dynamic Logistic Modeling

Czech Academy of Sciences Publication Activity Database

Brabec, Marek; Badescu, V.; Paulescu, M.

2014-01-01

Roč. 41, č. 6 (2014), s. 1174-1188 ISSN 0266-4763 R&D Projects: GA MŠk LD12009 Grant - others:European Cooperation in Science and Technology(XE) COST ES1002 Institutional support: RVO:67985807 Keywords : clouds * random process * sunshine number * Markovian logistic regression model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.417, year: 2014

FULLY AUTOMATED GIS-BASED INDIVIDUAL TREE CROWN DELINEATION BASED ON CURVATURE VALUES FROM A LIDAR DERIVED CANOPY HEIGHT MODEL IN A CONIFEROUS PLANTATION

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R. J. L. Argamosa

2016-06-01

Full Text Available The generation of high resolution canopy height model (CHM from LiDAR makes it possible to delineate individual tree crown by means of a fully-automated method using the CHM’s curvature through its slope. The local maxima are obtained by taking the maximum raster value in a 3 m x 3 m cell. These values are assumed as tree tops and therefore considered as individual trees. Based on the assumptions, thiessen polygons were generated to serve as buffers for the canopy extent. The negative profile curvature is then measured from the slope of the CHM. The results show that the aggregated points from a negative profile curvature raster provide the most realistic crown shape. The absence of field data regarding tree crown dimensions require accurate visual assessment after the appended delineated tree crown polygon was superimposed to the hill shaded CHM.

Explorations in combining cognitive models of individuals and system dynamics models of groups.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.

2008-07-01

This report documents a demonstration model of interacting insurgent leadership, military leadership, government leadership, and societal dynamics under a variety of interventions. The primary focus of the work is the portrayal of a token societal model that responds to leadership activities. The model also includes a linkage between leadership and society that implicitly represents the leadership subordinates as they directly interact with the population. The societal model is meant to demonstrate the efficacy and viability of using System Dynamics (SD) methods to simulate populations and that these can then connect to cognitive models depicting individuals. SD models typically focus on average behavior and thus have limited applicability to describe small groups or individuals. On the other hand, cognitive models readily describe individual behavior but can become cumbersome when used to describe populations. Realistic security situations are invariably a mix of individual and population dynamics. Therefore, the ability to tie SD models to cognitive models provides a critical capability that would be otherwise be unavailable.

Stochastic modeling of sunshine number data

Science.gov (United States)

Brabec, Marek; Paulescu, Marius; Badescu, Viorel

2013-11-01

In this paper, we will present a unified statistical modeling framework for estimation and forecasting sunshine number (SSN) data. Sunshine number has been proposed earlier to describe sunshine time series in qualitative terms (Theor Appl Climatol 72 (2002) 127-136) and since then, it was shown to be useful not only for theoretical purposes but also for practical considerations, e.g. those related to the development of photovoltaic energy production. Statistical modeling and prediction of SSN as a binary time series has been challenging problem, however. Our statistical model for SSN time series is based on an underlying stochastic process formulation of Markov chain type. We will show how its transition probabilities can be efficiently estimated within logistic regression framework. In fact, our logistic Markovian model can be relatively easily fitted via maximum likelihood approach. This is optimal in many respects and it also enables us to use formalized statistical inference theory to obtain not only the point estimates of transition probabilities and their functions of interest, but also related uncertainties, as well as to test of various hypotheses of practical interest, etc. It is straightforward to deal with non-homogeneous transition probabilities in this framework. Very importantly from both physical and practical points of view, logistic Markov model class allows us to test hypotheses about how SSN dependents on various external covariates (e.g. elevation angle, solar time, etc.) and about details of the dynamic model (order and functional shape of the Markov kernel, etc.). Therefore, using generalized additive model approach (GAM), we can fit and compare models of various complexity which insist on keeping physical interpretation of the statistical model and its parts. After introducing the Markovian model and general approach for identification of its parameters, we will illustrate its use and performance on high resolution SSN data from the Solar

Stochastic modeling of sunshine number data

Energy Technology Data Exchange (ETDEWEB)

Brabec, Marek, E-mail: mbrabec@cs.cas.cz [Department of Nonlinear Modeling, Institute of Computer Science, Academy of Sciences of the Czech Republic, Pod Vodarenskou vezi 2, 182 07 Prague 8 (Czech Republic); Paulescu, Marius [Physics Department, West University of Timisoara, V. Parvan 4, 300223 Timisoara (Romania); Badescu, Viorel [Candida Oancea Institute, Polytechnic University of Bucharest, Spl. Independentei 313, 060042 Bucharest (Romania)

2013-11-13

In this paper, we will present a unified statistical modeling framework for estimation and forecasting sunshine number (SSN) data. Sunshine number has been proposed earlier to describe sunshine time series in qualitative terms (Theor Appl Climatol 72 (2002) 127-136) and since then, it was shown to be useful not only for theoretical purposes but also for practical considerations, e.g. those related to the development of photovoltaic energy production. Statistical modeling and prediction of SSN as a binary time series has been challenging problem, however. Our statistical model for SSN time series is based on an underlying stochastic process formulation of Markov chain type. We will show how its transition probabilities can be efficiently estimated within logistic regression framework. In fact, our logistic Markovian model can be relatively easily fitted via maximum likelihood approach. This is optimal in many respects and it also enables us to use formalized statistical inference theory to obtain not only the point estimates of transition probabilities and their functions of interest, but also related uncertainties, as well as to test of various hypotheses of practical interest, etc. It is straightforward to deal with non-homogeneous transition probabilities in this framework. Very importantly from both physical and practical points of view, logistic Markov model class allows us to test hypotheses about how SSN dependents on various external covariates (e.g. elevation angle, solar time, etc.) and about details of the dynamic model (order and functional shape of the Markov kernel, etc.). Therefore, using generalized additive model approach (GAM), we can fit and compare models of various complexity which insist on keeping physical interpretation of the statistical model and its parts. After introducing the Markovian model and general approach for identification of its parameters, we will illustrate its use and performance on high resolution SSN data from the Solar

Stochastic modeling of sunshine number data

International Nuclear Information System (INIS)

Brabec, Marek; Paulescu, Marius; Badescu, Viorel

2013-01-01

In this paper, we will present a unified statistical modeling framework for estimation and forecasting sunshine number (SSN) data. Sunshine number has been proposed earlier to describe sunshine time series in qualitative terms (Theor Appl Climatol 72 (2002) 127-136) and since then, it was shown to be useful not only for theoretical purposes but also for practical considerations, e.g. those related to the development of photovoltaic energy production. Statistical modeling and prediction of SSN as a binary time series has been challenging problem, however. Our statistical model for SSN time series is based on an underlying stochastic process formulation of Markov chain type. We will show how its transition probabilities can be efficiently estimated within logistic regression framework. In fact, our logistic Markovian model can be relatively easily fitted via maximum likelihood approach. This is optimal in many respects and it also enables us to use formalized statistical inference theory to obtain not only the point estimates of transition probabilities and their functions of interest, but also related uncertainties, as well as to test of various hypotheses of practical interest, etc. It is straightforward to deal with non-homogeneous transition probabilities in this framework. Very importantly from both physical and practical points of view, logistic Markov model class allows us to test hypotheses about how SSN dependents on various external covariates (e.g. elevation angle, solar time, etc.) and about details of the dynamic model (order and functional shape of the Markov kernel, etc.). Therefore, using generalized additive model approach (GAM), we can fit and compare models of various complexity which insist on keeping physical interpretation of the statistical model and its parts. After introducing the Markovian model and general approach for identification of its parameters, we will illustrate its use and performance on high resolution SSN data from the Solar

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

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Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

“Space, the Final Frontier”: How Good are Agent-Based Models at Simulating Individuals and Space in Cities?

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Alison Heppenstall

2016-01-01

Full Text Available Cities are complex systems, comprising of many interacting parts. How we simulate and understand causality in urban systems is continually evolving. Over the last decade the agent-based modeling (ABM paradigm has provided a new lens for understanding the effects of interactions of individuals and how through such interactions macro structures emerge, both in the social and physical environment of cities. However, such a paradigm has been hindered due to computational power and a lack of large fine scale datasets. Within the last few years we have witnessed a massive increase in computational processing power and storage, combined with the onset of Big Data. Today geographers find themselves in a data rich era. We now have access to a variety of data sources (e.g., social media, mobile phone data, etc. that tells us how, and when, individuals are using urban spaces. These data raise several questions: can we effectively use them to understand and model cities as complex entities? How well have ABM approaches lent themselves to simulating the dynamics of urban processes? What has been, or will be, the influence of Big Data on increasing our ability to understand and simulate cities? What is the appropriate level of spatial analysis and time frame to model urban phenomena? Within this paper we discuss these questions using several examples of ABM applied to urban geography to begin a dialogue about the utility of ABM for urban modeling. The arguments that the paper raises are applicable across the wider research environment where researchers are considering using this approach.

Human mobility and time spent at destination: impact on spatial epidemic spreading.

Science.gov (United States)

Poletto, Chiara; Tizzoni, Michele; Colizza, Vittoria

2013-12-07

Host mobility plays a fundamental role in the spatial spread of infectious diseases. Previous theoretical works based on the integration of network theory into the metapopulation framework have shown that the heterogeneities that characterize real mobility networks favor the propagation of epidemics. Nevertheless, the studies conducted so far assumed the mobility process to be either Markovian (in which the memory of the origin of each traveler is lost) or non-Markovian with a fixed traveling time scale (in which individuals travel to a destination and come back at a constant rate). Available statistics however show that the time spent by travelers at destination is characterized by wide fluctuations, ranging from a single day up to several months. Such varying length of stay crucially affects the chance and duration of mixing events among hosts and may therefore have a strong impact on the spread of an emerging disease. Here, we present an analytical and a computational study of epidemic processes on a complex subpopulation network where travelers have memory of their origin and spend a heterogeneously distributed time interval at their destination. Through analytical calculations and numerical simulations we show that the heterogeneity of the length of stay alters the expression of the threshold between local outbreak and global invasion, and, moreover, it changes the epidemic behavior of the system in case of a global outbreak. Additionally, our theoretical framework allows us to study the effect of changes in the traveling behavior in response to the infection, by considering a scenario in which sick individuals do not leave their home location. Finally, we compare the results of our non-Markovian framework with those obtained with a classic Markovian approach and find relevant differences between the two, in the estimate of the epidemic invasion potential, as well as of the timing and the pattern of its spatial spread. These results highlight the importance of

R-warfarin clearances from plasma associated with polymorphic cytochrome P450 2C19 and simulated by individual physiologically based pharmacokinetic models for 11 cynomolgus monkeys.

Science.gov (United States)

Utoh, Masahiro; Kusama, Takashi; Miura, Tomonori; Mitsui, Marina; Kawano, Mirai; Hirano, Takahiro; Shimizu, Makiko; Uno, Yasuhiro; Yamazaki, Hiroshi

2018-02-01

1. Cynomolgus monkey cytochrome P450 2C19 (formerly known as P450 2C75), homologous to human P450 2C19, has been identified as R-warfarin 7-hydroxylase. In this study, simulations of R-warfarin clearance in individual cynomolgus monkeys genotyped for P450 2C19 p.[(Phe100Asn; Ala103Val; Ile112Leu)] were performed using individual simplified physiologically based pharmacokinetic (PBPK) modeling. 2. Pharmacokinetic parameters and absorption rate constants, volumes of the systemic circulation, and hepatic intrinsic clearances for individual PBPK models were estimated for eleven cynomolgus monkeys. 3. One-way ANOVA revealed significant effects of the genotype (p warfarin among the homozygous mutant, heterozygous mutant, and wild-type groups. R-Warfarin clearances in individual cynomolgus monkeys genotyped for P450 2C19 were simulated by simplified PBPK modeling. The modeled hepatic intrinsic clearances were significantly associated with the P450 2C19 genotypes. The liver microsomal elimination rates of R-warfarin for individual animals after in vivo administration showed significant reductions associated with the genotype (p warfarin and related medicines associated with polymorphic P450 2C19 in individual cynomolgus monkeys, thereby facilitating calculation of the fraction of hepatic clearance.

Individual discriminative face recognition models based on subsets of features

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder; Gomez, David Delgado; Ersbøll, Bjarne Kjær

2007-01-01

The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection is used to identify meaningful and important features in face recognition. Modelling the characteristics which distinguish one...... person from another using only subsets of features will both decrease the computational cost and increase the generalization capacity of the face recognition algorithm. Moreover, identifying which are the features that better discriminate between persons will also provide a deeper understanding...... of the face recognition problem. The elastic net model is able to select a subset of features with low computational effort compared to other state-of-the-art feature selection methods. Furthermore, the fact that the number of features usually is larger than the number of images in the data base makes feature...

Value of the distant future: Model-independent results

Science.gov (United States)

Katz, Yuri A.

2017-01-01

This paper shows that the model-independent account of correlations in an interest rate process or a log-consumption growth process leads to declining long-term tails of discount curves. Under the assumption of an exponentially decaying memory in fluctuations of risk-free real interest rates, I derive the analytical expression for an apt value of the long run discount factor and provide a detailed comparison of the obtained result with the outcome of the benchmark risk-free interest rate models. Utilizing the standard consumption-based model with an isoelastic power utility of the representative economic agent, I derive the non-Markovian generalization of the Ramsey discounting formula. Obtained analytical results allowing simple calibration, may augment the rigorous cost-benefit and regulatory impact analysis of long-term environmental and infrastructure projects.

A course on queueing models

CERN Document Server

Jain, Joti Lal; Böhm, Walter

2006-01-01

The application of engineering principles in divergent fields such as management science and communications as well as the advancement of several approaches in theory and computation have led to growing interest in queueing models, creating the need for a comprehensive text. Emphasizing Markovian structures and the techniques that occur in different models, A Course on Queueing Models discusses recent developments in the field, different methodological tools - some of which are not available elsewhere - and computational techniques.While most books essentially address the classical methods of

Characteristics and Diffusion Model of the Individual Knowledge in the WeChat Mode

Directory of Open Access Journals (Sweden)

Zhang Lingzhi

2017-12-01

Full Text Available [Purpose/significance] According to the model of the individual knowledge diffusion, we conduct a behavior research and analyze the characteristics of that based on WeChat which is the most popular communication platform in China.[Method/process] By analyzing the methods of the diffusion on WeChat, we analyzed the characteristics of the individual knowledge diffusion. [Result/conclusion]The characteristics of the individual knowledge diffusion include real-time, short-term, speciality, friendship and transmission.

A Network-Individual-Resource Model for HIV Prevention

Science.gov (United States)

Johnson, Blair T.; Redding, Colleen A.; DiClemente, Ralph J.; Mustanski, Brian S.; Dodge, Brian M.; Sheeran, Paschal; Warren, Michelle R.; Zimmerman, Rick S.; Fisher, William A.; Conner, Mark T.; Carey, Michael P.; Fisher, Jeffrey D.; Stall, Ronald D.; Fishbein, Martin

2014-01-01

HIV is transmitted through dyadic exchanges of individuals linked in transitory or permanent networks of varying sizes. To optimize prevention efficacy, a complementary theoretical perspective that bridges key individual level elements with important network elements can be a foundation for developing and implementing HIV interventions with outcomes that are more sustainable over time and have greater dissemination potential. Toward that end, we introduce a Network-Individual-Resource (NIR) model for HIV prevention that recognizes how exchanges of resources between individuals and their networks underlies and sustains HIV-risk behaviors. Individual behavior change for HIV prevention, then, may be dependent on increasing the supportiveness of that individual's relevant networks for such change. Among other implications, an NIR model predicts that the success of prevention efforts depends on whether the prevention efforts (1) prompt behavior changes that can be sustained by the resources the individual or their networks possess; (2) meet individual and network needs and are consistent with the individual's current situation/developmental stage; (3) are trusted and valued; and (4) target high HIV-prevalence networks. PMID:20862606

Legacy effects of wildfire on stream thermal regimes and rainbow trout ecology: an integrated analysis of observation and individual-based models

Science.gov (United States)

Rosenberger, Amanda E.; Dunham, Jason B.; Neuswanger, Jason R.; Railsback, Steven F.

2015-01-01

Management of aquatic resources in fire-prone areas requires understanding of fish species’ responses to wildfire and of the intermediate- and long-term consequences of these disturbances. We examined Rainbow Trout populations in 9 headwater streams 10 y after a major wildfire: 3 with no history of severe wildfire in the watershed (unburned), 3 in severely burned watersheds (burned), and 3 in severely burned watersheds subjected to immediate events that scoured the stream channel and eliminated streamside vegetation (burned and reorganized). Results of a previous study of this system suggested the primary lasting effects of this wildfire history on headwater stream habitat were differences in canopy cover and solar radiation, which led to higher summer stream temperatures. Nevertheless, trout were present throughout streams in burned watersheds. Older age classes were least abundant in streams draining watersheds with a burned and reorganized history, and individuals >1 y old were most abundant in streams draining watersheds with an unburned history. Burned history corresponded with fast growth, low lipid content, and early maturity of Rainbow Trout. We used an individual-based model of Rainbow Trout growth and demographic patterns to determine if temperature interactions with bioenergetics and competition among individuals could lead to observed phenotypic and ecological differences among populations in the absence of other plausible mechanisms. Modeling suggested that moderate warming associated with wildfire and channel disturbance history leads to faster individual growth, which exacerbates competition for limited food, leading to decreases in population densities. The inferred mechanisms from this modeling exercise suggest the transferability of ecological patterns to a variety of temperature-warming scenarios.

Classification of customer lifetime value models using Markov chain

Science.gov (United States)

Permana, Dony; Pasaribu, Udjianna S.; Indratno, Sapto W.; Suprayogi

2017-10-01

A firm’s potential reward in future time from a customer can be determined by customer lifetime value (CLV). There are some mathematic methods to calculate it. One method is using Markov chain stochastic model. Here, a customer is assumed through some states. Transition inter the states follow Markovian properties. If we are given some states for a customer and the relationships inter states, then we can make some Markov models to describe the properties of the customer. As Markov models, CLV is defined as a vector contains CLV for a customer in the first state. In this paper we make a classification of Markov Models to calculate CLV. Start from two states of customer model, we make develop in many states models. The development a model is based on weaknesses in previous model. Some last models can be expected to describe how real characters of customers in a firm.

Analytical models approximating individual processes: a validation method.

Science.gov (United States)

Favier, C; Degallier, N; Menkès, C E

2010-12-01

Upscaling population models from fine to coarse resolutions, in space, time and/or level of description, allows the derivation of fast and tractable models based on a thorough knowledge of individual processes. The validity of such approximations is generally tested only on a limited range of parameter sets. A more general validation test, over a range of parameters, is proposed; this would estimate the error induced by the approximation, using the original model's stochastic variability as a reference. This method is illustrated by three examples taken from the field of epidemics transmitted by vectors that bite in a temporally cyclical pattern, that illustrate the use of the method: to estimate if an approximation over- or under-fits the original model; to invalidate an approximation; to rank possible approximations for their qualities. As a result, the application of the validation method to this field emphasizes the need to account for the vectors' biology in epidemic prediction models and to validate these against finer scale models. Copyright © 2010 Elsevier Inc. All rights reserved.

Pricing Participating Products under a Generalized Jump-Diffusion Model

Directory of Open Access Journals (Sweden)

Tak Kuen Siu

2008-01-01

Full Text Available We propose a model for valuing participating life insurance products under a generalized jump-diffusion model with a Markov-switching compensator. It also nests a number of important and popular models in finance, including the classes of jump-diffusion models and Markovian regime-switching models. The Esscher transform is employed to determine an equivalent martingale measure. Simulation experiments are conducted to illustrate the practical implementation of the model and to highlight some features that can be obtained from our model.