Introduction to conformal invariance in statistical mechanics and to random surface models

International Nuclear Information System (INIS)

David, F.

1995-01-01

In the first part of these lectures I give a brief and somewhat superficial introduction to the techniques of conformal invariance and to a few applications in statistical mechanics in two dimensions. My purpose is to introduce the basic ideas and some standard results for the students who are not familiar with the theory, and to introduce concepts and tools which will be useful for the other lecturers, rather than to give a complete and up to date review of the subject. In the second part I discuss several problems in the statistical mechanics of two dimensional random surfaces and membranes. As an introduction, I present some basic facts about the statistical mechanics of one-dimensional objects and polymers, which are classical examples of objects with critical properties. Then I emphasize the special role of curvature energy and of the elastic energy associated with the internal structure of membranes, and the corresponding models of random surfaces. Finally, I discuss the specific problem of self-avoiding tethered surfaces, whose critical properties are still poorly understood, and for which the applicability of some basic techniques of field theory, such as renormalization group calculations, has been understood only recently. (orig.)

Is there a statistical mechanics of turbulence?

International Nuclear Information System (INIS)

Kraichnan, R.H.; Chen, S.Y.

1988-09-01

The statistical-mechanical treatment of turbulence is made questionable by strong nonlinearity and strong disequilibrium that result in the creation of ordered structures imbedded in disorder. Model systems are described which may provide some hope that a compact, yet faithful, statistical description of turbulence nevertheless is possible. Some essential dynamic features of the models are captured by low-order statistical approximations despite strongly non-Gaussian behavior. 31 refs., 5 figs

Zeno dynamics in quantum statistical mechanics

International Nuclear Information System (INIS)

Schmidt, Andreas U

2003-01-01

We study the quantum Zeno effect in quantum statistical mechanics within the operator algebraic framework. We formulate a condition for the appearance of the effect in W*-dynamical systems, in terms of the short-time behaviour of the dynamics. Examples of quantum spin systems show that this condition can be effectively applied to quantum statistical mechanical models. Furthermore, we derive an explicit form of the Zeno generator, and use it to construct Gibbs equilibrium states for the Zeno dynamics. As a concrete example, we consider the X-Y model, for which we show that a frequent measurement at a microscopic level, e.g. a single lattice site, can produce a macroscopic effect in changing the global equilibrium

Statistical mechanics

CERN Document Server

Davidson, Norman

2003-01-01

Clear and readable, this fine text assists students in achieving a grasp of the techniques and limitations of statistical mechanics. The treatment follows a logical progression from elementary to advanced theories, with careful attention to detail and mathematical development, and is sufficiently rigorous for introductory or intermediate graduate courses.Beginning with a study of the statistical mechanics of ideal gases and other systems of non-interacting particles, the text develops the theory in detail and applies it to the study of chemical equilibrium and the calculation of the thermody

Completely X-symmetric S-matrices corresponding to theta functions and models of statistical mechanics

International Nuclear Information System (INIS)

Chudnovsky, D.V.; Chudnovsky, G.V.

1981-01-01

We consider general expressions of factorized S-matrices with Abelian symmetry expressed in terms of theta-functions. These expressions arise from representations of the Heisenberg group. New examples of factorized S-matrices lead to a large class of completely integrable models of statistical mechanics which generalize the XYZ-model of the eight-vertex model. (orig.)

Statistical mechanics of sparse generalization and graphical model selection

International Nuclear Information System (INIS)

Lage-Castellanos, Alejandro; Pagnani, Andrea; Weigt, Martin

2009-01-01

One of the crucial tasks in many inference problems is the extraction of an underlying sparse graphical model from a given number of high-dimensional measurements. In machine learning, this is frequently achieved using, as a penalty term, the L p norm of the model parameters, with p≤1 for efficient dilution. Here we propose a statistical mechanics analysis of the problem in the setting of perceptron memorization and generalization. Using a replica approach, we are able to evaluate the relative performance of naive dilution (obtained by learning without dilution, following by applying a threshold to the model parameters), L 1 dilution (which is frequently used in convex optimization) and L 0 dilution (which is optimal but computationally hard to implement). Whereas both L p diluted approaches clearly outperform the naive approach, we find a small region where L 0 works almost perfectly and strongly outperforms the simpler to implement L 1 dilution

Statistical mechanics and field theory

International Nuclear Information System (INIS)

Samuel, S.A.

1979-05-01

Field theory methods are applied to statistical mechanics. Statistical systems are related to fermionic-like field theories through a path integral representation. Considered are the Ising model, the free-fermion model, and close-packed dimer problems on various lattices. Graphical calculational techniques are developed. They are powerful and yield a simple procedure to compute the vacuum expectation value of an arbitrary product of Ising spin variables. From a field theorist's point of view, this is the simplest most logical derivation of the Ising model partition function and correlation functions. This work promises to open a new area of physics research when the methods are used to approximate unsolved problems. By the above methods a new model named the 128 pseudo-free vertex model is solved. Statistical mechanics intuition is applied to field theories. It is shown that certain relativistic field theories are equivalent to classical interacting gases. Using this analogy many results are obtained, particularly for the Sine-Gordon field theory. Quark confinement is considered. Although not a proof of confinement, a logical, esthetic, and simple picture is presented of how confinement works. A key ingredient is the insight gained by using an analog statistical system consisting of a gas of macromolecules. This analogy allows the computation of Wilson loops in the presence of topological vortices and when symmetry breakdown occurs in the topological quantum number. Topological symmetry breakdown calculations are placed on approximately the same level of rigor as instanton calculations. The picture of confinement that emerges is similar to the dual Meissner type advocated by Mandelstam. Before topological symmetry breakdown, QCD has monopoles bound linearly together by three topological strings. Topological symmetry breakdown corresponds to a new phase where these monopoles are liberated. It is these liberated monopoles that confine quarks. 64 references

The Dirac equation in classical statistical mechanics

International Nuclear Information System (INIS)

Ord, G.N.

2002-01-01

The Dirac equation, usually obtained by 'quantizing' a classical stochastic model is here obtained directly within classical statistical mechanics. The special underlying space-time geometry of the random walk replaces the missing analytic continuation, making the model 'self-quantizing'. This provides a new context for the Dirac equation, distinct from its usual context in relativistic quantum mechanics

Statistical crack mechanics

International Nuclear Information System (INIS)

Dienes, J.K.

1993-01-01

Although it is possible to simulate the ground blast from a single explosive shot with a simple computer algorithm and appropriate constants, the most commonly used modelling methods do not account for major changes in geology or shot energy because mechanical features such as tectonic stresses, fault structure, microcracking, brittle-ductile transition, and water content are not represented in significant detail. An alternative approach for modelling called Statistical Crack Mechanics is presented in this paper. This method, developed in the seventies as a part of the oil shale program, accounts for crack opening, shear, growth, and coalescence. Numerous photographs and micrographs show that shocked materials tend to involve arrays of planar cracks. The approach described here provides a way to account for microstructure and give a representation of the physical behavior of a material at the microscopic level that can account for phenomena such as permeability, fragmentation, shear banding, and hot-spot formation in explosives

An introduction to thermodynamics and statistical mechanics

CERN Document Server

Saxena, A K

2016-01-01

An Introduction to Thermodynamics and Statistical Mechanics aims to serve as a text book for undergraduate hons.and postgraduate students of physics. The book covers First Law of Thermodynamics, Entropy and Second Law ofThermodynamics, Thermodynamic Relations, The Statistical Basis of Thermodynamics, Microcanonical Ensemble,Classical Statistical and Canonical Distribution, Grand Canonical Ensemble, Quantum Statistical Mechanics, PhaseTransitions, Fluctuations, Irreversible Processes and Transport Phenomena (Diffusion).SALIENT FEATURES:iC* Offers students a conceptual development of the subjectiC* Review questions at the end of chapters.NEW TO THE SECOND EDITIONiC* PVT SurfacesiC* Real Heat EnginesiC* Van der Waals Models (Qualitative Considerations)iC* Cluster ExpansioniC* Brownian Motion (Einstein's Theory)

Statistical mechanics of competitive resource allocation using agent-based models

Science.gov (United States)

Chakraborti, Anirban; Challet, Damien; Chatterjee, Arnab; Marsili, Matteo; Zhang, Yi-Cheng; Chakrabarti, Bikas K.

2015-01-01

Demand outstrips available resources in most situations, which gives rise to competition, interaction and learning. In this article, we review a broad spectrum of multi-agent models of competition (El Farol Bar problem, Minority Game, Kolkata Paise Restaurant problem, Stable marriage problem, Parking space problem and others) and the methods used to understand them analytically. We emphasize the power of concepts and tools from statistical mechanics to understand and explain fully collective phenomena such as phase transitions and long memory, and the mapping between agent heterogeneity and physical disorder. As these methods can be applied to any large-scale model of competitive resource allocation made up of heterogeneous adaptive agent with non-linear interaction, they provide a prospective unifying paradigm for many scientific disciplines.

Lectures on statistical mechanics

CERN Document Server

Bowler, M G

1982-01-01

Anyone dissatisfied with the almost ritual dullness of many 'standard' texts in statistical mechanics will be grateful for the lucid explanation and generally reassuring tone. Aimed at securing firm foundations for equilibrium statistical mechanics, topics of great subtlety are presented transparently and enthusiastically. Very little mathematical preparation is required beyond elementary calculus and prerequisites in physics are limited to some elementary classical thermodynamics. Suitable as a basis for a first course in statistical mechanics, the book is an ideal supplement to more convent

Statistical mechanics

CERN Document Server

Schwabl, Franz

2006-01-01

The completely revised new edition of the classical book on Statistical Mechanics covers the basic concepts of equilibrium and non-equilibrium statistical physics. In addition to a deductive approach to equilibrium statistics and thermodynamics based on a single hypothesis - the form of the microcanonical density matrix - this book treats the most important elements of non-equilibrium phenomena. Intermediate calculations are presented in complete detail. Problems at the end of each chapter help students to consolidate their understanding of the material. Beyond the fundamentals, this text demonstrates the breadth of the field and its great variety of applications. Modern areas such as renormalization group theory, percolation, stochastic equations of motion and their applications to critical dynamics, kinetic theories, as well as fundamental considerations of irreversibility, are discussed. The text will be useful for advanced students of physics and other natural sciences; a basic knowledge of quantum mechan...

Statistical mechanics of nonequilibrium liquids

CERN Document Server

Evans, Denis J; Craig, D P; McWeeny, R

1990-01-01

Statistical Mechanics of Nonequilibrium Liquids deals with theoretical rheology. The book discusses nonlinear response of systems and outlines the statistical mechanical theory. In discussing the framework of nonequilibrium statistical mechanics, the book explains the derivation of a nonequilibrium analogue of the Gibbsian basis for equilibrium statistical mechanics. The book reviews the linear irreversible thermodynamics, the Liouville equation, and the Irving-Kirkwood procedure. The text then explains the Green-Kubo relations used in linear transport coefficients, the linear response theory,

Semiclassical statistical mechanics

International Nuclear Information System (INIS)

Stratt, R.M.

1979-04-01

On the basis of an approach devised by Miller, a formalism is developed which allows the nonperturbative incorporation of quantum effects into equilibrium classical statistical mechanics. The resulting expressions bear a close similarity to classical phase space integrals and, therefore, are easily molded into forms suitable for examining a wide variety of problems. As a demonstration of this, three such problems are briefly considered: the simple harmonic oscillator, the vibrational state distribution of HCl, and the density-independent radial distribution function of He 4 . A more detailed study is then made of two more general applications involving the statistical mechanics of nonanalytic potentials and of fluids. The former, which is a particularly difficult problem for perturbative schemes, is treated with only limited success by restricting phase space and by adding an effective potential. The problem of fluids, however, is readily found to yield to a semiclassical pairwise interaction approximation, which in turn permits any classical many-body model to be expressed in a convenient form. The remainder of the discussion concentrates on some ramifications of having a phase space version of quantum mechanics. To test the breadth of the formulation, the task of constructing quantal ensemble averages of phase space functions is undertaken, and in the process several limitations of the formalism are revealed. A rather different approach is also pursued. The concept of quantum mechanical ergodicity is examined through the use of numerically evaluated eigenstates of the Barbanis potential, and the existence of this quantal ergodicity - normally associated with classical phase space - is verified. 21 figures, 4 tables

Statistical mechanics of superconductivity

CERN Document Server

Kita, Takafumi

2015-01-01

This book provides a theoretical, step-by-step comprehensive explanation of superconductivity for undergraduate and graduate students who have completed elementary courses on thermodynamics and quantum mechanics. To this end, it adopts the unique approach of starting with the statistical mechanics of quantum ideal gases and successively adding and clarifying elements and techniques indispensible for understanding it. They include the spin-statistics theorem, second quantization, density matrices, the Bloch–De Dominicis theorem, the variational principle in statistical mechanics, attractive interaction, and bound states. Ample examples of their usage are also provided in terms of topics from advanced statistical mechanics such as two-particle correlations of quantum ideal gases, derivation of the Hartree–Fock equations, and Landau’s Fermi-liquid theory, among others. With these preliminaries, the fundamental mean-field equations of superconductivity are derived with maximum mathematical clarity based on ...

Statistical mechanics in JINR

International Nuclear Information System (INIS)

Tonchev, N.; Shumovskij, A.S.

1986-01-01

The history of investigations, conducted at the JINR in the field of statistical mechanics, beginning with the fundamental works by Bogolyubov N.N. on superconductivity microscopic theory is presented. Ideas, introduced in these works and methods developed in them, have largely determined the ways for developing statistical mechanics in the JINR and Hartree-Fock-Bogolyubov variational principle has become an important method of the modern nucleus theory. A brief review of the main achievements, connected with the development of statistical mechanics methods and their application in different fields of physical science is given

Existence and uniqueness of Gibbs states for a statistical mechanical polyacetylene model

International Nuclear Information System (INIS)

Park, Y.M.

1987-01-01

One-dimensional polyacetylene is studied as a model of statistical mechanics. In a semiclassical approximation the system is equivalent to a quantum XY model interacting with unbounded classical spins in one-dimensional lattice space Z. By establishing uniform estimates, an infinite-volume-limit Hilbert space, a strongly continuous time evolution group of unitary operators, and an invariant vector are constructed. Moreover, it is proven that any infinite-limit state satisfies Gibbs conditions. Finally, a modification of Araki's relative entropy method is used to establish the uniqueness of Gibbs states

Statistical mechanics and dynamics of solvable models with long-range interactions

International Nuclear Information System (INIS)

Campa, Alessandro; Dauxois, Thierry; Ruffo, Stefano

2009-01-01

For systems with long-range interactions, the two-body potential decays at large distances as V(r)∼1/r α , with α≤d, where d is the space dimension. Examples are: gravitational systems, two-dimensional hydrodynamics, two-dimensional elasticity, charged and dipolar systems. Although such systems can be made extensive, they are intrinsically non additive: the sum of the energies of macroscopic subsystems is not equal to the energy of the whole system. Moreover, the space of accessible macroscopic thermodynamic parameters might be non convex. The violation of these two basic properties of the thermodynamics of short-range systems is at the origin of ensemble inequivalence. In turn, this inequivalence implies that specific heat can be negative in the microcanonical ensemble, and temperature jumps can appear at microcanonical first order phase transitions. The lack of convexity allows us to easily spot regions of parameter space where ergodicity may be broken. Historically, negative specific heat had been found for gravitational systems and was thought to be a specific property of a system for which the existence of standard equilibrium statistical mechanics itself was doubted. Realizing that such properties may be present for a wider class of systems has renewed the interest in long-range interactions. Here, we present a comprehensive review of the recent advances on the statistical mechanics and out-of-equilibrium dynamics of solvable systems with long-range interactions. The core of the review consists in the detailed presentation of the concept of ensemble inequivalence, as exemplified by the exact solution, in the microcanonical and canonical ensembles, of mean-field type models. Remarkably, the entropy of all these models can be obtained using the method of large deviations. Long-range interacting systems display an extremely slow relaxation towards thermodynamic equilibrium and, what is more striking, the convergence towards quasi-stationary states. The

Statistical mechanics in a nutshell

CERN Document Server

Peliti, Luca

2011-01-01

Statistical mechanics is one of the most exciting areas of physics today, and it also has applications to subjects as diverse as economics, social behavior, algorithmic theory, and evolutionary biology. Statistical Mechanics in a Nutshell offers the most concise, self-contained introduction to this rapidly developing field. Requiring only a background in elementary calculus and elementary mechanics, this book starts with the basics, introduces the most important developments in classical statistical mechanics over the last thirty years, and guides readers to the very threshold of today

Einstein's statistical mechanics

Energy Technology Data Exchange (ETDEWEB)

Baracca, A; Rechtman S, R

1985-08-01

The foundation of equilibrium classical statistical mechanics were laid down in 1902 independently by Gibbs and Einstein. The latter's contribution, developed in three papers published between 1902 and 1904, is usually forgotten and when not, rapidly dismissed as equivalent to Gibb's. We review in detail Einstein's ideas on the foundations of statistical mechanics and show that they constitute the beginning of a research program that led Einstein to quantum theory. We also show how these ideas may be used as a starting point for an introductory course on the subject.

Einstein's statistical mechanics

International Nuclear Information System (INIS)

Baracca, A.; Rechtman S, R.

1985-01-01

The foundation of equilibrium classical statistical mechanics were laid down in 1902 independently by Gibbs and Einstein. The latter's contribution, developed in three papers published between 1902 and 1904, is usually forgotten and when not, rapidly dismissed as equivalent to Gibb's. We review in detail Einstein's ideas on the foundations of statistical mechanics and show that they constitute the beginning of a research program that led Einstein to quantum theory. We also show how these ideas may be used as a starting point for an introductory course on the subject. (author)

Quantum mechanics and field theory with fractional spin and statistics

International Nuclear Information System (INIS)

Forte, S.

1992-01-01

Planar systems admit quantum states that are neither bosons nor fermions, i.e., whose angular momentum is neither integer nor half-integer. After a discussion of some examples of familiar models in which fractional spin may arise, the relevant (nonrelativistic) quantum mechanics is developed from first principles. The appropriate generalization of statistics is also discussed. Some physical effects of fractional spin and statistics are worked out explicitly. The group theory underlying relativistic models with fractional spin and statistics is then introduced and applied to relativistic particle mechanics and field theory. Field-theoretical models in 2+1 dimensions are presented which admit solitons that carry fractional statistics, and are discussed in a semiclassical approach, in the functional integral approach, and in the canonical approach. Finally, fundamental field theories whose Fock states carry fractional spin and statistics are discussed

Statistical fracture mechanics approach to the strength of brittle rock

International Nuclear Information System (INIS)

Ratigan, J.L.

1981-06-01

Statistical fracture mechanics concepts used in the past for rock are critically reviewed and modifications are proposed which are warranted by (1) increased understanding of fracture provided by modern fracture mechanics and (2) laboratory test data both from the literature and from this research. Over 600 direct and indirect tension tests have been performed on three different rock types; Stripa Granite, Sierra White Granite and Carrara Marble. In several instances assumptions which are common in the literature were found to be invalid. A three parameter statistical fracture mechanics model with Mode I critical strain energy release rate as the variant is presented. Methodologies for evaluating the parameters in this model as well as the more commonly employed two parameter models are discussed. The experimental results and analysis of this research indicate that surfacially distributed flaws, rather than volumetrically distributed flaws are responsible for rupture in many testing situations. For several of the rock types tested, anisotropy (both in apparent tensile strength and size effect) precludes the use of contemporary statistical fracture mechanics models

Quantum mechanics from classical statistics

International Nuclear Information System (INIS)

Wetterich, C.

2010-01-01

Quantum mechanics can emerge from classical statistics. A typical quantum system describes an isolated subsystem of a classical statistical ensemble with infinitely many classical states. The state of this subsystem can be characterized by only a few probabilistic observables. Their expectation values define a density matrix if they obey a 'purity constraint'. Then all the usual laws of quantum mechanics follow, including Heisenberg's uncertainty relation, entanglement and a violation of Bell's inequalities. No concepts beyond classical statistics are needed for quantum physics - the differences are only apparent and result from the particularities of those classical statistical systems which admit a quantum mechanical description. Born's rule for quantum mechanical probabilities follows from the probability concept for a classical statistical ensemble. In particular, we show how the non-commuting properties of quantum operators are associated to the use of conditional probabilities within the classical system, and how a unitary time evolution reflects the isolation of the subsystem. As an illustration, we discuss a classical statistical implementation of a quantum computer.

Statistical mechanics rigorous results

CERN Document Server

Ruelle, David

1999-01-01

This classic book marks the beginning of an era of vigorous mathematical progress in equilibrium statistical mechanics. Its treatment of the infinite system limit has not been superseded, and the discussion of thermodynamic functions and states remains basic for more recent work. The conceptual foundation provided by the Rigorous Results remains invaluable for the study of the spectacular developments of statistical mechanics in the second half of the 20th century.

Menzerath-Altmann Law: Statistical Mechanical Interpretation as Applied to a Linguistic Organization

Science.gov (United States)

Eroglu, Sertac

2014-10-01

The distribution behavior described by the empirical Menzerath-Altmann law is frequently encountered during the self-organization of linguistic and non-linguistic natural organizations at various structural levels. This study presents a statistical mechanical derivation of the law based on the analogy between the classical particles of a statistical mechanical organization and the distinct words of a textual organization. The derived model, a transformed (generalized) form of the Menzerath-Altmann model, was termed as the statistical mechanical Menzerath-Altmann model. The derived model allows interpreting the model parameters in terms of physical concepts. We also propose that many organizations presenting the Menzerath-Altmann law behavior, whether linguistic or not, can be methodically examined by the transformed distribution model through the properly defined structure-dependent parameter and the energy associated states.

Statistical Mechanics of Turbulent Flows

International Nuclear Information System (INIS)

Cambon, C

2004-01-01

This is a handbook for a computational approach to reacting flows, including background material on statistical mechanics. In this sense, the title is somewhat misleading with respect to other books dedicated to the statistical theory of turbulence (e.g. Monin and Yaglom). In the present book, emphasis is placed on modelling (engineering closures) for computational fluid dynamics. The probabilistic (pdf) approach is applied to the local scalar field, motivated first by the nonlinearity of chemical source terms which appear in the transport equations of reacting species. The probabilistic and stochastic approaches are also used for the velocity field and particle position; nevertheless they are essentially limited to Lagrangian models for a local vector, with only single-point statistics, as for the scalar. Accordingly, conventional techniques, such as single-point closures for RANS (Reynolds-averaged Navier-Stokes) and subgrid-scale models for LES (large-eddy simulations), are described and in some cases reformulated using underlying Langevin models and filtered pdfs. Even if the theoretical approach to turbulence is not discussed in general, the essentials of probabilistic and stochastic-processes methods are described, with a useful reminder concerning statistics at the molecular level. The book comprises 7 chapters. Chapter 1 briefly states the goals and contents, with a very clear synoptic scheme on page 2. Chapter 2 presents definitions and examples of pdfs and related statistical moments. Chapter 3 deals with stochastic processes, pdf transport equations, from Kramer-Moyal to Fokker-Planck (for Markov processes), and moments equations. Stochastic differential equations are introduced and their relationship to pdfs described. This chapter ends with a discussion of stochastic modelling. The equations of fluid mechanics and thermodynamics are addressed in chapter 4. Classical conservation equations (mass, velocity, internal energy) are derived from their

Statistical mechanics of complex networks

CERN Document Server

Rubi, Miguel; Diaz-Guilera, Albert

2003-01-01

Networks can provide a useful model and graphic image useful for the description of a wide variety of web-like structures in the physical and man-made realms, e.g. protein networks, food webs and the Internet. The contributions gathered in the present volume provide both an introduction to, and an overview of, the multifaceted phenomenology of complex networks. Statistical Mechanics of Complex Networks also provides a state-of-the-art picture of current theoretical methods and approaches.

The non-equilibrium statistical mechanics of a simple geophysical fluid dynamics model

Science.gov (United States)

Verkley, Wim; Severijns, Camiel

2014-05-01

Lorenz [1] has devised a dynamical system that has proved to be very useful as a benchmark system in geophysical fluid dynamics. The system in its simplest form consists of a periodic array of variables that can be associated with an atmospheric field on a latitude circle. The system is driven by a constant forcing, is damped by linear friction and has a simple advection term that causes the model to behave chaotically if the forcing is large enough. Our aim is to predict the statistics of Lorenz' model on the basis of a given average value of its total energy - obtained from a numerical integration - and the assumption of statistical stationarity. Our method is the principle of maximum entropy [2] which in this case reads: the information entropy of the system's probability density function shall be maximal under the constraints of normalization, a given value of the average total energy and statistical stationarity. Statistical stationarity is incorporated approximately by using `stationarity constraints', i.e., by requiring that the average first and possibly higher-order time-derivatives of the energy are zero in the maximization of entropy. The analysis [3] reveals that, if the first stationarity constraint is used, the resulting probability density function rather accurately reproduces the statistics of the individual variables. If the second stationarity constraint is used as well, the correlations between the variables are also reproduced quite adequately. The method can be generalized straightforwardly and holds the promise of a viable non-equilibrium statistical mechanics of the forced-dissipative systems of geophysical fluid dynamics. [1] E.N. Lorenz, 1996: Predictability - A problem partly solved, in Proc. Seminar on Predictability (ECMWF, Reading, Berkshire, UK), Vol. 1, pp. 1-18. [2] E.T. Jaynes, 2003: Probability Theory - The Logic of Science (Cambridge University Press, Cambridge). [3] W.T.M. Verkley and C.A. Severijns, 2014: The maximum entropy

Statistical mechanics of normal grain growth in one dimension: A partial integro-differential equation model

International Nuclear Information System (INIS)

Ng, Felix S.L.

2016-01-01

We develop a statistical-mechanical model of one-dimensional normal grain growth that does not require any drift-velocity parameterization for grain size, such as used in the continuity equation of traditional mean-field theories. The model tracks the population by considering grain sizes in neighbour pairs; the probability of a pair having neighbours of certain sizes is determined by the size-frequency distribution of all pairs. Accordingly, the evolution obeys a partial integro-differential equation (PIDE) over ‘grain size versus neighbour grain size’ space, so that the grain-size distribution is a projection of the PIDE's solution. This model, which is applicable before as well as after statistically self-similar grain growth has been reached, shows that the traditional continuity equation is invalid outside this state. During statistically self-similar growth, the PIDE correctly predicts the coarsening rate, invariant grain-size distribution and spatial grain size correlations observed in direct simulations. The PIDE is then reducible to the standard continuity equation, and we derive an explicit expression for the drift velocity. It should be possible to formulate similar parameterization-free models of normal grain growth in two and three dimensions.

Statistical mechanical model of gas adsorption in porous crystals with dynamic moieties.

Science.gov (United States)

Simon, Cory M; Braun, Efrem; Carraro, Carlo; Smit, Berend

2017-01-17

Some nanoporous, crystalline materials possess dynamic constituents, for example, rotatable moieties. These moieties can undergo a conformation change in response to the adsorption of guest molecules, which qualitatively impacts adsorption behavior. We pose and solve a statistical mechanical model of gas adsorption in a porous crystal whose cages share a common ligand that can adopt two distinct rotational conformations. Guest molecules incentivize the ligands to adopt a different rotational configuration than maintained in the empty host. Our model captures inflections, steps, and hysteresis that can arise in the adsorption isotherm as a signature of the rotating ligands. The insights disclosed by our simple model contribute a more intimate understanding of the response and consequence of rotating ligands integrated into porous materials to harness them for gas storage and separations, chemical sensing, drug delivery, catalysis, and nanoscale devices. Particularly, our model reveals design strategies to exploit these moving constituents and engineer improved adsorbents with intrinsic thermal management for pressure-swing adsorption processes.

Topics in statistical mechanics

International Nuclear Information System (INIS)

Elser, V.

1984-05-01

This thesis deals with four independent topics in statistical mechanics: (1) the dimer problem is solved exactly for a hexagonal lattice with general boundary using a known generating function from the theory of partitions. It is shown that the leading term in the entropy depends on the shape of the boundary; (2) continuum models of percolation and self-avoiding walks are introduced with the property that their series expansions are sums over linear graphs with intrinsic combinatorial weights and explicit dimension dependence; (3) a constrained SOS model is used to describe the edge of a simple cubic crystal. Low and high temperature results are derived as well as the detailed behavior near the crystal facet; (4) the microscopic model of the lambda-transition involving atomic permutation cycles is reexamined. In particular, a new derivation of the two-component field theory model of the critical behavior is presented. Results for a lattice model originally proposed by Kikuchi are extended with a high temperature series expansion and Monte Carlo simulation. 30 references

A statistical mechanical interpretation of algorithmic information theory: Total statistical mechanical interpretation based on physical argument

International Nuclear Information System (INIS)

Tadaki, Kohtaro

2010-01-01

The statistical mechanical interpretation of algorithmic information theory (AIT, for short) was introduced and developed by our former works [K. Tadaki, Local Proceedings of CiE 2008, pp. 425-434, 2008] and [K. Tadaki, Proceedings of LFCS'09, Springer's LNCS, vol. 5407, pp. 422-440, 2009], where we introduced the notion of thermodynamic quantities, such as partition function Z(T), free energy F(T), energy E(T), statistical mechanical entropy S(T), and specific heat C(T), into AIT. We then discovered that, in the interpretation, the temperature T equals to the partial randomness of the values of all these thermodynamic quantities, where the notion of partial randomness is a stronger representation of the compression rate by means of program-size complexity. Furthermore, we showed that this situation holds for the temperature T itself, which is one of the most typical thermodynamic quantities. Namely, we showed that, for each of the thermodynamic quantities Z(T), F(T), E(T), and S(T) above, the computability of its value at temperature T gives a sufficient condition for T is an element of (0,1) to satisfy the condition that the partial randomness of T equals to T. In this paper, based on a physical argument on the same level of mathematical strictness as normal statistical mechanics in physics, we develop a total statistical mechanical interpretation of AIT which actualizes a perfect correspondence to normal statistical mechanics. We do this by identifying a microcanonical ensemble in the framework of AIT. As a result, we clarify the statistical mechanical meaning of the thermodynamic quantities of AIT.

Exactly soluble problems in statistical mechanics

International Nuclear Information System (INIS)

Yang, C.N.

1983-01-01

In the last few years, a number of two-dimensional classical and one-dimensional quantum mechanical problems in statistical mechanics have been exactly solved. Although these problems range over models of diverse physical interest, their solutions were obtained using very similar mathematical methods. In these lectures, the main points of the methods are discussed. In this introductory lecture, an overall survey of all these problems without going into the detailed method of solution is given. In later lectures, they shall concentrate on one particular problem: the delta function interaction in one dimension, and go into the details of that problem

Statistical Mechanics of Disordered Systems - Series: Cambridge Series in Statistical and Probabilistic Mathematics (No. 18)

Science.gov (United States)

Bovier, Anton

2006-06-01

Our mathematical understanding of the statistical mechanics of disordered systems is going through a period of stunning progress. This self-contained book is a graduate-level introduction for mathematicians and for physicists interested in the mathematical foundations of the field, and can be used as a textbook for a two-semester course on mathematical statistical mechanics. It assumes only basic knowledge of classical physics and, on the mathematics side, a good working knowledge of graduate-level probability theory. The book starts with a concise introduction to statistical mechanics, proceeds to disordered lattice spin systems, and concludes with a presentation of the latest developments in the mathematical understanding of mean-field spin glass models. In particular, recent progress towards a rigorous understanding of the replica symmetry-breaking solutions of the Sherrington-Kirkpatrick spin glass models, due to Guerra, Aizenman-Sims-Starr and Talagrand, is reviewed in some detail. Comprehensive introduction to an active and fascinating area of research Clear exposition that builds to the state of the art in the mathematics of spin glasses Written by a well-known and active researcher in the field

Introduction to quantum statistical mechanics

CERN Document Server

Bogolyubov, N N

2010-01-01

Introduction to Quantum Statistical Mechanics (Second Edition) may be used as an advanced textbook by graduate students, even ambitious undergraduates in physics. It is also suitable for non experts in physics who wish to have an overview of some of the classic and fundamental quantum models in the subject. The explanation in the book is detailed enough to capture the interest of the reader, and complete enough to provide the necessary background material needed to dwell further into the subject and explore the research literature.

Quantum mechanics as applied mathematical statistics

International Nuclear Information System (INIS)

Skala, L.; Cizek, J.; Kapsa, V.

2011-01-01

Basic mathematical apparatus of quantum mechanics like the wave function, probability density, probability density current, coordinate and momentum operators, corresponding commutation relation, Schroedinger equation, kinetic energy, uncertainty relations and continuity equation is discussed from the point of view of mathematical statistics. It is shown that the basic structure of quantum mechanics can be understood as generalization of classical mechanics in which the statistical character of results of measurement of the coordinate and momentum is taken into account and the most important general properties of statistical theories are correctly respected.

Statistical mechanics principles and selected applications

CERN Document Server

Hill, Terrell L

1956-01-01

""Excellent … a welcome addition to the literature on the subject."" - ScienceBefore the publication of this standard, oft-cited book, there were few if any statistical-mechanics texts that incorporated reviews of both fundamental principles and recent developments in the field.In this volume, Professor Hill offers just such a dual presentation - a useful account of basic theory and of its applications, made accessible in a comprehensive format. The book opens with concise, unusually clear introductory chapters on classical statistical mechanics, quantum statistical mechanics and the relatio

Statistical mechanics and Lorentz violation

International Nuclear Information System (INIS)

Colladay, Don; McDonald, Patrick

2004-01-01

The theory of statistical mechanics is studied in the presence of Lorentz-violating background fields. The analysis is performed using the Standard-Model Extension (SME) together with a Jaynesian formulation of statistical inference. Conventional laws of thermodynamics are obtained in the presence of a perturbed hamiltonian that contains the Lorentz-violating terms. As an example, properties of the nonrelativistic ideal gas are calculated in detail. To lowest order in Lorentz violation, the scalar thermodynamic variables are only corrected by a rotationally invariant combination of parameters that mimics a (frame dependent) effective mass. Spin-couplings can induce a temperature-independent polarization in the classical gas that is not present in the conventional case. Precision measurements in the residual expectation values of the magnetic moment of Fermi gases in the limit of high temperature may provide interesting limits on these parameters

Establishing statistical models of manufacturing parameters

International Nuclear Information System (INIS)

Senevat, J.; Pape, J.L.; Deshayes, J.F.

1991-01-01

This paper reports on the effect of pilgering and cold-work parameters on contractile strain ratio and mechanical properties that were investigated using a large population of Zircaloy tubes. Statistical models were established between: contractile strain ratio and tooling parameters, mechanical properties (tensile test, creep test) and cold-work parameters, and mechanical properties and stress-relieving temperature

Statistical mechanics of spatial evolutionary games

International Nuclear Information System (INIS)

Miekisz, Jacek

2004-01-01

We discuss the long-run behaviour of stochastic dynamics of many interacting players in spatial evolutionary games. In particular, we investigate the effect of the number of players and the noise level on the stochastic stability of Nash equilibria. We discuss similarities and differences between systems of interacting players maximizing their individual payoffs and particles minimizing their interaction energy. We use concepts and techniques of statistical mechanics to study game-theoretic models. In order to obtain results in the case of the so-called potential games, we analyse the thermodynamic limit of the appropriate models of interacting particles

The scientifiv way of thinking in statistics, statistical physics and quantum mechanics

OpenAIRE

Săvoiu, Gheorghe

2008-01-01

This paper focuses on the way of thinking in both classical and modern Physics and Statistics, Statistical Mechanics or Statistical Physics and Quantum Mechanics. These different statistical ways of thinking and their specific methods have generated new fields for new activities and new scientific disciplines, like Econophysics (between Economics and Physics), Sociophysics (between Sociology and Physics), Mediaphysics (between all media and comunication sciences), etc. After describing some r...

The scientific way of thinking in statistics, statistical physics and quantum mechanics

OpenAIRE

Săvoiu, Gheorghe

2008-01-01

This paper focuses on the way of thinking in both classical and modern Physics and Statistics, Statistical Mechanics or Statistical Physics and Quantum Mechanics. These different statistical ways of thinking and their specific methods have generated new fields for new activities and new scientific disciplines, like Econophysics (between Economics and Physics), Sociophysics (between Sociology and Physics), Mediaphysics (between all media and comunication sciences), etc. After describing some r...

Statistical Mechanics Analysis of ATP Binding to a Multisubunit Enzyme

International Nuclear Information System (INIS)

Zhang Yun-Xin

2014-01-01

Due to inter-subunit communication, multisubunit enzymes usually hydrolyze ATP in a concerted fashion. However, so far the principle of this process remains poorly understood. In this study, from the viewpoint of statistical mechanics, a simple model is presented. In this model, we assume that the binding of ATP will change the potential of the corresponding enzyme subunit, and the degree of this change depends on the state of its adjacent subunits. The probability of enzyme in a given state satisfies the Boltzmann's distribution. Although it looks much simple, this model can fit the recent experimental data of chaperonin TRiC/CCT well. From this model, the dominant state of TRiC/CCT can be obtained. This study provide a new way to understand biophysical processe by statistical mechanics analysis. (interdisciplinary physics and related areas of science and technology)

Statistical mechanics of anyons

International Nuclear Information System (INIS)

Arovas, D.P.

1985-01-01

We study the statistical mechanics of a two-dimensional gas of free anyons - particles which interpolate between Bose-Einstein and Fermi-Dirac character. Thermodynamic quantities are discussed in the low-density regime. In particular, the second virial coefficient is evaluated by two different methods and is found to exhibit a simple, periodic, but nonanalytic behavior as a function of the statistics determining parameter. (orig.)

Statistical mechanics of two-dimensional and geophysical flows

International Nuclear Information System (INIS)

Bouchet, Freddy; Venaille, Antoine

2012-01-01

The theoretical study of the self-organization of two-dimensional and geophysical turbulent flows is addressed based on statistical mechanics methods. This review is a self-contained presentation of classical and recent works on this subject; from the statistical mechanics basis of the theory up to applications to Jupiter’s troposphere and ocean vortices and jets. Emphasize has been placed on examples with available analytical treatment in order to favor better understanding of the physics and dynamics. After a brief presentation of the 2D Euler and quasi-geostrophic equations, the specificity of two-dimensional and geophysical turbulence is emphasized. The equilibrium microcanonical measure is built from the Liouville theorem. Important statistical mechanics concepts (large deviations and mean field approach) and thermodynamic concepts (ensemble inequivalence and negative heat capacity) are briefly explained and described. On this theoretical basis, we predict the output of the long time evolution of complex turbulent flows as statistical equilibria. This is applied to make quantitative models of two-dimensional turbulence, the Great Red Spot and other Jovian vortices, ocean jets like the Gulf-Stream, and ocean vortices. A detailed comparison between these statistical equilibria and real flow observations is provided. We also present recent results for non-equilibrium situations, for the studies of either the relaxation towards equilibrium or non-equilibrium steady states. In this last case, forces and dissipation are in a statistical balance; fluxes of conserved quantity characterize the system and microcanonical or other equilibrium measures no longer describe the system.

Modern Thermodynamics with Statistical Mechanics

CERN Document Server

Helrich, Carl S

2009-01-01

With the aim of presenting thermodynamics in as simple and as unified a form as possible, this textbook starts with an introduction to the first and second laws and then promptly addresses the complete set of the potentials in a subsequent chapter and as a central theme throughout. Before discussing modern laboratory measurements, the book shows that the fundamental quantities sought in the laboratory are those which are required for determining the potentials. Since the subjects of thermodynamics and statistical mechanics are a seamless whole, statistical mechanics is treated as integral part of the text. Other key topics such as irreversibility, the ideas of Ilya Prigogine, chemical reaction rates, equilibrium of heterogeneous systems, and transition-state theory serve to round out this modern treatment. An additional chapter covers quantum statistical mechanics due to active current research in Bose-Einstein condensation. End-of-chapter exercises, chapter summaries, and an appendix reviewing fundamental pr...

Simple statistical model for branched aggregates

DEFF Research Database (Denmark)

Lemarchand, Claire; Hansen, Jesper Schmidt

2015-01-01

, given that it already has bonds with others. The model is applied here to asphaltene nanoaggregates observed in molecular dynamics simulations of Cooee bitumen. The variation with temperature of the probabilities deduced from this model is discussed in terms of statistical mechanics arguments....... The relevance of the statistical model in the case of asphaltene nanoaggregates is checked by comparing the predicted value of the probability for one molecule to have exactly i bonds with the same probability directly measured in the molecular dynamics simulations. The agreement is satisfactory......We propose a statistical model that can reproduce the size distribution of any branched aggregate, including amylopectin, dendrimers, molecular clusters of monoalcohols, and asphaltene nanoaggregates. It is based on the conditional probability for one molecule to form a new bond with a molecule...

Grassmann methods in lattice field theory and statistical mechanics

International Nuclear Information System (INIS)

Bilgici, E.; Gattringer, C.; Huber, P.

2006-01-01

Full text: In two dimensions models of loops can be represented as simple Grassmann integrals. In our work we explore the generalization of these techniques to lattice field theories and statistical mechanic systems in three and four dimensions. We discuss possible strategies and applications for representations of loop and surface models as Grassmann integrals. (author)

Three-Dimensional Color Code Thresholds via Statistical-Mechanical Mapping

Science.gov (United States)

Kubica, Aleksander; Beverland, Michael E.; Brandão, Fernando; Preskill, John; Svore, Krysta M.

2018-05-01

Three-dimensional (3D) color codes have advantages for fault-tolerant quantum computing, such as protected quantum gates with relatively low overhead and robustness against imperfect measurement of error syndromes. Here we investigate the storage threshold error rates for bit-flip and phase-flip noise in the 3D color code (3DCC) on the body-centered cubic lattice, assuming perfect syndrome measurements. In particular, by exploiting a connection between error correction and statistical mechanics, we estimate the threshold for 1D stringlike and 2D sheetlike logical operators to be p3DCC (1 )≃1.9 % and p3DCC (2 )≃27.6 % . We obtain these results by using parallel tempering Monte Carlo simulations to study the disorder-temperature phase diagrams of two new 3D statistical-mechanical models: the four- and six-body random coupling Ising models.

Statistical mechanics of the majority game

International Nuclear Information System (INIS)

Kozlowski, P; Marsili, M

2003-01-01

The majority game, modelling a system of heterogeneous agents trying to behave in a similar way, is introduced and studied using methods of statistical mechanics. The stationary states of the game are given by the (local) minima of a particular Hopfield-like Hamiltonian. On the basis of replica symmetric calculations, we draw the phase diagram, which contains the analogue of a retrieval phase. The number of metastable states is estimated using the annealed approximation. The results are confronted with extensive numerical simulations

Metastability in Field Theory and Statistical Mechanics

International Nuclear Information System (INIS)

Carvalho, C.A. de.

1984-01-01

After a phase transition analysis which can occur in the framework of a scalar field theory, at finite temperature and in presence of a external field, possibles metastable situations are studied and also how is their relationship with the transitions. In both cases it is used a semiclassical approximation to the theory which, in Statistical Mechanics, corresponds to the droplet-bubble model. (L.C.) [pt

Playing at Statistical Mechanics

Science.gov (United States)

Clark, Paul M.; And Others

1974-01-01

Discussed are the applications of counting techniques of a sorting game to distributions and concepts in statistical mechanics. Included are the following distributions: Fermi-Dirac, Bose-Einstein, and most probable. (RH)

Statistical mechanics of cellular automata

International Nuclear Information System (INIS)

Wolfram, S.

1983-01-01

Cellular automata are used as simple mathematical models to investigate self-organization in statistical mechanics. A detailed analysis is given of ''elementary'' cellular automata consisting of a sequence of sites with values 0 or 1 on a line, with each site evolving deterministically in discrete time steps according to p definite rules involving the values of its nearest neighbors. With simple initial configurations, the cellular automata either tend to homogeneous states, or generate self-similar patterns with fractal dimensions approx. =1.59 or approx. =1.69. With ''random'' initial configurations, the irreversible character of the cellular automaton evolution leads to several self-organization phenomena. Statistical properties of the structures generated are found to lie in two universality classes, independent of the details of the initial state or the cellular automaton rules. More complicated cellular automata are briefly considered, and connections with dynamical systems theory and the formal theory of computation are discussed

Generalized Statistical Mechanics at the Onset of Chaos

Directory of Open Access Journals (Sweden)

Alberto Robledo

2013-11-01

Full Text Available Transitions to chaos in archetypal low-dimensional nonlinear maps offer real and precise model systems in which to assess proposed generalizations of statistical mechanics. The known association of chaotic dynamics with the structure of Boltzmann–Gibbs (BG statistical mechanics has suggested the potential verification of these generalizations at the onset of chaos, when the only Lyapunov exponent vanishes and ergodic and mixing properties cease to hold. There are three well-known routes to chaos in these deterministic dissipative systems, period-doubling, quasi-periodicity and intermittency, which provide the setting in which to explore the limit of validity of the standard BG structure. It has been shown that there is a rich and intricate behavior for both the dynamics within and towards the attractors at the onset of chaos and that these two kinds of properties are linked via generalized statistical-mechanical expressions. Amongst the topics presented are: (i permanently growing sensitivity fluctuations and their infinite family of generalized Pesin identities; (ii the emergence of statistical-mechanical structures in the dynamics along the routes to chaos; (iii dynamical hierarchies with modular organization; and (iv limit distributions of sums of deterministic variables. The occurrence of generalized entropy properties in condensed-matter physical systems is illustrated by considering critical fluctuations, localization transition and glass formation. We complete our presentation with the description of the manifestations of the dynamics at the transitions to chaos in various kinds of complex systems, such as, frequency and size rank distributions and complex network images of time series. We discuss the results.

A statistical model of uplink inter-cell interference with slow and fast power control mechanisms

KAUST Repository

Tabassum, Hina; Yilmaz, Ferkan; Dawy, Zaher; Alouini, Mohamed-Slim

2013-01-01

Uplink power control is in essence an interference mitigation technique that aims at minimizing the inter-cell interference (ICI) in cellular networks by reducing the transmit power levels of the mobile users while maintaining their target received signal quality levels at base stations. Power control mechanisms directly impact the interference dynamics and, thus, affect the overall achievable capacity and consumed power in cellular networks. Due to the stochastic nature of wireless channels and mobile users' locations, it is important to derive theoretical models for ICI that can capture the impact of design alternatives related to power control mechanisms. To this end, we derive and verify a novel statistical model for uplink ICI in Generalized-K composite fading environments as a function of various slow and fast power control mechanisms. The derived expressions are then utilized to quantify numerically key network performance metrics that include average resource fairness, average reduction in power consumption, and ergodic capacity. The accuracy of the derived expressions is validated via Monte-Carlo simulations. Results are generated for multiple network scenarios, and insights are extracted to assess various power control mechanisms as a function of system parameters. © 1972-2012 IEEE.

A statistical model of uplink inter-cell interference with slow and fast power control mechanisms

KAUST Repository

Tabassum, Hina

2013-09-01

Uplink power control is in essence an interference mitigation technique that aims at minimizing the inter-cell interference (ICI) in cellular networks by reducing the transmit power levels of the mobile users while maintaining their target received signal quality levels at base stations. Power control mechanisms directly impact the interference dynamics and, thus, affect the overall achievable capacity and consumed power in cellular networks. Due to the stochastic nature of wireless channels and mobile users\\' locations, it is important to derive theoretical models for ICI that can capture the impact of design alternatives related to power control mechanisms. To this end, we derive and verify a novel statistical model for uplink ICI in Generalized-K composite fading environments as a function of various slow and fast power control mechanisms. The derived expressions are then utilized to quantify numerically key network performance metrics that include average resource fairness, average reduction in power consumption, and ergodic capacity. The accuracy of the derived expressions is validated via Monte-Carlo simulations. Results are generated for multiple network scenarios, and insights are extracted to assess various power control mechanisms as a function of system parameters. © 1972-2012 IEEE.

Quantum field theory and statistical mechanics

International Nuclear Information System (INIS)

Jegerlehner, F.

1975-01-01

At first a heuristic understanding is given how the relation between quantum field theory and statistical mechanics near phase transitions comes about. A long range scale invariant theory is constructed, critical indices are calculated and the relations among them are proved, field theoretical Kadanoff-scale transformations are formulated and scaling corrections calculated. A precise meaning to many of Kadanoffs considerations and a model matching Wegners phenomenological scheme is given. It is shown, that soft parametrization is most transparent for the discussion of scaling behaviour. (BJ) [de

Emergence of quantum mechanics from classical statistics

International Nuclear Information System (INIS)

Wetterich, C

2009-01-01

The conceptual setting of quantum mechanics is subject to an ongoing debate from its beginnings until now. The consequences of the apparent differences between quantum statistics and classical statistics range from the philosophical interpretations to practical issues as quantum computing. In this note we demonstrate how quantum mechanics can emerge from classical statistical systems. We discuss conditions and circumstances for this to happen. Quantum systems describe isolated subsystems of classical statistical systems with infinitely many states. While infinitely many classical observables 'measure' properties of the subsystem and its environment, the state of the subsystem can be characterized by the expectation values of only a few probabilistic observables. They define a density matrix, and all the usual laws of quantum mechanics follow. No concepts beyond classical statistics are needed for quantum physics - the differences are only apparent and result from the particularities of those classical statistical systems which admit a quantum mechanical description. In particular, we show how the non-commuting properties of quantum operators are associated to the use of conditional probabilities within the classical system, and how a unitary time evolution reflects the isolation of the subsystem.

Appplication of statistical mechanical methods to the modeling of social networks

Science.gov (United States)

Strathman, Anthony Robert

With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

Analogies between classical statistical mechanics and quantum mechanics

International Nuclear Information System (INIS)

Uehara, M.

1986-01-01

Some analogies between nonequilibrium classical statistical mechanics and quantum mechanics, at the level of the Liouville equation and at the kinetic level, are commented on. A theorem, related to the Vlasov equation applied to a plasma, is proved. The theorem presents an analogy with Ehrenfest's theorem of quantum mechanics. An analogy between the plasma kinetic theory and Bohm's quantum theory with 'hidden variables' is also shown. (Author) [pt

Multiple-shock initiation via statistical crack mechanics

Energy Technology Data Exchange (ETDEWEB)

Dienes, J.K.; Kershner, J.D.

1998-12-31

Statistical Crack Mechanics (SCRAM) is a theoretical approach to the behavior of brittle materials that accounts for the behavior of an ensemble of microcracks, including their opening, shear, growth, and coalescence. Mechanical parameters are based on measured strain-softening behavior. In applications to explosive and propellant sensitivity it is assumed that closed cracks act as hot spots, and that the heating due to interfacial friction initiates reactions which are modeled as one-dimensional heat flow with an Arrhenius source term, and computed in a subscale grid. Post-ignition behavior of hot spots is treated with the burn model of Ward, Son and Brewster. Numerical calculations using SCRAM-HYDROX are compared with the multiple-shock experiments of Mulford et al. in which the particle velocity in PBX 9501 is measured with embedded wires, and reactions are initiated and quenched.

The large deviation approach to statistical mechanics

International Nuclear Information System (INIS)

Touchette, Hugo

2009-01-01

The theory of large deviations is concerned with the exponential decay of probabilities of large fluctuations in random systems. These probabilities are important in many fields of study, including statistics, finance, and engineering, as they often yield valuable information about the large fluctuations of a random system around its most probable state or trajectory. In the context of equilibrium statistical mechanics, the theory of large deviations provides exponential-order estimates of probabilities that refine and generalize Einstein's theory of fluctuations. This review explores this and other connections between large deviation theory and statistical mechanics, in an effort to show that the mathematical language of statistical mechanics is the language of large deviation theory. The first part of the review presents the basics of large deviation theory, and works out many of its classical applications related to sums of random variables and Markov processes. The second part goes through many problems and results of statistical mechanics, and shows how these can be formulated and derived within the context of large deviation theory. The problems and results treated cover a wide range of physical systems, including equilibrium many-particle systems, noise-perturbed dynamics, nonequilibrium systems, as well as multifractals, disordered systems, and chaotic systems. This review also covers many fundamental aspects of statistical mechanics, such as the derivation of variational principles characterizing equilibrium and nonequilibrium states, the breaking of the Legendre transform for nonconcave entropies, and the characterization of nonequilibrium fluctuations through fluctuation relations.

The large deviation approach to statistical mechanics

Science.gov (United States)

Touchette, Hugo

2009-07-01

The theory of large deviations is concerned with the exponential decay of probabilities of large fluctuations in random systems. These probabilities are important in many fields of study, including statistics, finance, and engineering, as they often yield valuable information about the large fluctuations of a random system around its most probable state or trajectory. In the context of equilibrium statistical mechanics, the theory of large deviations provides exponential-order estimates of probabilities that refine and generalize Einstein’s theory of fluctuations. This review explores this and other connections between large deviation theory and statistical mechanics, in an effort to show that the mathematical language of statistical mechanics is the language of large deviation theory. The first part of the review presents the basics of large deviation theory, and works out many of its classical applications related to sums of random variables and Markov processes. The second part goes through many problems and results of statistical mechanics, and shows how these can be formulated and derived within the context of large deviation theory. The problems and results treated cover a wide range of physical systems, including equilibrium many-particle systems, noise-perturbed dynamics, nonequilibrium systems, as well as multifractals, disordered systems, and chaotic systems. This review also covers many fundamental aspects of statistical mechanics, such as the derivation of variational principles characterizing equilibrium and nonequilibrium states, the breaking of the Legendre transform for nonconcave entropies, and the characterization of nonequilibrium fluctuations through fluctuation relations.

BOOK REVIEW: Statistical Mechanics of Turbulent Flows

Science.gov (United States)

Cambon, C.

2004-10-01

This is a handbook for a computational approach to reacting flows, including background material on statistical mechanics. In this sense, the title is somewhat misleading with respect to other books dedicated to the statistical theory of turbulence (e.g. Monin and Yaglom). In the present book, emphasis is placed on modelling (engineering closures) for computational fluid dynamics. The probabilistic (pdf) approach is applied to the local scalar field, motivated first by the nonlinearity of chemical source terms which appear in the transport equations of reacting species. The probabilistic and stochastic approaches are also used for the velocity field and particle position; nevertheless they are essentially limited to Lagrangian models for a local vector, with only single-point statistics, as for the scalar. Accordingly, conventional techniques, such as single-point closures for RANS (Reynolds-averaged Navier-Stokes) and subgrid-scale models for LES (large-eddy simulations), are described and in some cases reformulated using underlying Langevin models and filtered pdfs. Even if the theoretical approach to turbulence is not discussed in general, the essentials of probabilistic and stochastic-processes methods are described, with a useful reminder concerning statistics at the molecular level. The book comprises 7 chapters. Chapter 1 briefly states the goals and contents, with a very clear synoptic scheme on page 2. Chapter 2 presents definitions and examples of pdfs and related statistical moments. Chapter 3 deals with stochastic processes, pdf transport equations, from Kramer-Moyal to Fokker-Planck (for Markov processes), and moments equations. Stochastic differential equations are introduced and their relationship to pdfs described. This chapter ends with a discussion of stochastic modelling. The equations of fluid mechanics and thermodynamics are addressed in chapter 4. Classical conservation equations (mass, velocity, internal energy) are derived from their

Statistical mechanical analysis of LMFBR fuel cladding tubes

International Nuclear Information System (INIS)

Poncelet, J.-P.; Pay, A.

1977-01-01

The most important design requirement on fuel pin cladding for LMFBR's is its mechanical integrity. Disruptive factors include internal pressure from mixed oxide fuel fission gas release, thermal stresses and high temperature creep, neutron-induced differential void-swelling as a source of stress in the cladding and irradiation creep of stainless steel material, corrosion by fission products. Under irradiation these load-restraining mechanisms are accentuated by stainless steel embrittlement and strength alterations. To account for the numerous uncertainties involved in the analysis by theoretical models and computer codes statistical tools are unavoidably requested, i.e. Monte Carlo simulation methods. Thanks to these techniques, uncertainties in nominal characteristics, material properties and environmental conditions can be linked up in a correct way and used for a more accurate conceptual design. First, a thermal creep damage index is set up through a sufficiently sophisticated clad physical analysis including arbitrary time dependence of power and neutron flux as well as effects of sodium temperature, burnup and steel mechanical behavior. Although this strain limit approach implies a more general but time consuming model., on the counterpart the net output is improved and e.g. clad temperature, stress and strain maxima may be easily assessed. A full spectrum of variables are statistically treated to account for their probability distributions. Creep damage probability may be obtained and can contribute to a quantitative fuel probability estimation

QUANTUM MECHANICS WITHOUT STATISTICAL POSTULATES

International Nuclear Information System (INIS)

Geiger, G.

2000-01-01

The Bohmian formulation of quantum mechanics describes the measurement process in an intuitive way without a reduction postulate. Due to the chaotic motion of the hidden classical particle all statistical features of quantum mechanics during a sequence of repeated measurements can be derived in the framework of a deterministic single system theory

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...

Statistical-mechanical entropy by the thin-layer method

International Nuclear Information System (INIS)

Feng, He; Kim, Sung Won

2003-01-01

G. Hooft first studied the statistical-mechanical entropy of a scalar field in a Schwarzschild black hole background by the brick-wall method and hinted that the statistical-mechanical entropy is the statistical origin of the Bekenstein-Hawking entropy of the black hole. However, according to our viewpoint, the statistical-mechanical entropy is only a quantum correction to the Bekenstein-Hawking entropy of the black-hole. The brick-wall method based on thermal equilibrium at a large scale cannot be applied to the cases out of equilibrium such as a nonstationary black hole. The statistical-mechanical entropy of a scalar field in a nonstationary black hole background is calculated by the thin-layer method. The condition of local equilibrium near the horizon of the black hole is used as a working postulate and is maintained for a black hole which evaporates slowly enough and whose mass is far greater than the Planck mass. The statistical-mechanical entropy is also proportional to the area of the black hole horizon. The difference from the stationary black hole is that the result relies on a time-dependent cutoff

Statistical physics of black holes as quantum-mechanical systems

OpenAIRE

Giddings, Steven B.

2013-01-01

Some basic features of black-hole statistical mechanics are investigated, assuming that black holes respect the principles of quantum mechanics. Care is needed in defining an entropy S_bh corresponding to the number of microstates of a black hole, given that the black hole interacts with its surroundings. An open question is then the relationship between this entropy and the Bekenstein-Hawking entropy S_BH. For a wide class of models with interactions needed to ensure unitary quantum evolutio...

Exact matrix treatment of statistical mechanical lattice model of adsorption induced gate opening in metal-organic frameworks

International Nuclear Information System (INIS)

Dunne, Lawrence J; Manos, George

2015-01-01

Here we present a statistical mechanical lattice model which is exactly solvable using a matrix method and allows treatment of adsorption induced gate opening structural transformations of metal-organic frameworks which are nanoporous materials with exceptional adsorption properties. Modelling of these structural changes presents a serious theoretical challenge when the solid and gas species are treated in an even handed way. This exactly solvable model complements other simulation based approaches. The methodology presented here highlights the competition between the potential for adsorption and the energy required for structural transition as a driving force for the features in the adsorption isotherms. (paper)

Early years of Computational Statistical Mechanics

Science.gov (United States)

Mareschal, Michel

2018-05-01

Evidence that a model of hard spheres exhibits a first-order solid-fluid phase transition was provided in the late fifties by two new numerical techniques known as Monte Carlo and Molecular Dynamics. This result can be considered as the starting point of computational statistical mechanics: at the time, it was a confirmation of a counter-intuitive (and controversial) theoretical prediction by J. Kirkwood. It necessitated an intensive collaboration between the Los Alamos team, with Bill Wood developing the Monte Carlo approach, and the Livermore group, where Berni Alder was inventing Molecular Dynamics. This article tells how it happened.

Statistical mechanics of lattice Boson field theory

International Nuclear Information System (INIS)

1976-01-01

A lattice approximation to Euclidean, boson quantum field theory is expressed in terms of the thermodynamic properties of a classical statistical mechanical system near its critical point in a sufficiently general way to permit the inclusion of an anomalous dimension of the vacuum. Using the thermodynamic properties of the Ising model, one can begin to construct nontrivial (containing scattering) field theories in 2, 3 and 4 dimensions. It is argued that, depending on the choice of the bare coupling constant, there are three types of behavior to be expected: the perturbation theory region, the renormalization group fixed point region, and the Ising model region

Statistical mechanics of lattice boson field theory

International Nuclear Information System (INIS)

Baker, G.A. Jr.

1977-01-01

A lattice approximation to Euclidean, boson quantum field theory is expressed in terms of the thermodynamic properties of a classical statistical mechanical system near its critical point in a sufficiently general way to permit the inclusion of an anomalous dimension of the vacuum. Using the thermodynamic properties of the Ising model, one can begin to construct nontrivial (containing scattering) field theories in 2, 3, and 4 dimensions. It is argued that, depending on the choice of the bare coupling constant, there are three types of behavior to be expected: the perturbation theory region, the renormalization group fixed point region, and the Ising model region. 24 references

Graphene Statistical Mechanics

Science.gov (United States)

Bowick, Mark; Kosmrlj, Andrej; Nelson, David; Sknepnek, Rastko

2015-03-01

Graphene provides an ideal system to test the statistical mechanics of thermally fluctuating elastic membranes. The high Young's modulus of graphene means that thermal fluctuations over even small length scales significantly stiffen the renormalized bending rigidity. We study the effect of thermal fluctuations on graphene ribbons of width W and length L, pinned at one end, via coarse-grained Molecular Dynamics simulations and compare with analytic predictions of the scaling of width-averaged root-mean-squared height fluctuations as a function of distance along the ribbon. Scaling collapse as a function of W and L also allows us to extract the scaling exponent eta governing the long-wavelength stiffening of the bending rigidity. A full understanding of the geometry-dependent mechanical properties of graphene, including arrays of cuts, may allow the design of a variety of modular elements with desired mechanical properties starting from pure graphene alone. Supported by NSF grant DMR-1435794

Statistical mechanics of driven diffusive systems

CERN Document Server

Schmittmann, B

1995-01-01

Far-from-equilibrium phenomena, while abundant in nature, are not nearly as well understood as their equilibrium counterparts. On the theoretical side, progress is slowed by the lack of a simple framework, such as the Boltzmann-Gbbs paradigm in the case of equilibrium thermodynamics. On the experimental side, the enormous structural complexity of real systems poses serious obstacles to comprehension. Similar difficulties have been overcome in equilibrium statistical mechanics by focusing on model systems. Even if they seem too simplistic for known physical systems, models give us considerable insight, provided they capture the essential physics. They serve as important theoretical testing grounds where the relationship between the generic physical behavior and the key ingredients of a successful theory can be identified and understood in detail. Within the vast realm of non-equilibrium physics, driven diffusive systems form a subset with particularly interesting properties. As a prototype model for these syst...

Nonequilibrium statistical mechanics ensemble method

CERN Document Server

Eu, Byung Chan

1998-01-01

In this monograph, nonequilibrium statistical mechanics is developed by means of ensemble methods on the basis of the Boltzmann equation, the generic Boltzmann equations for classical and quantum dilute gases, and a generalised Boltzmann equation for dense simple fluids The theories are developed in forms parallel with the equilibrium Gibbs ensemble theory in a way fully consistent with the laws of thermodynamics The generalised hydrodynamics equations are the integral part of the theory and describe the evolution of macroscopic processes in accordance with the laws of thermodynamics of systems far removed from equilibrium Audience This book will be of interest to researchers in the fields of statistical mechanics, condensed matter physics, gas dynamics, fluid dynamics, rheology, irreversible thermodynamics and nonequilibrium phenomena

Introduction to quantum statistical mechanics

International Nuclear Information System (INIS)

Bogolyubov, N.N.; Bogolyubov, N.N.

1980-01-01

In a set of lectures, which has been delivered at the Physical Department of Moscow State University as a special course for students represented are some basic ideas of quantum statistical mechanics. Considered are in particular, the Liouville equations in classical and quantum mechanics, canonical distribution and thermodynamical functions, two-time correlation functions and Green's functions in the theory of thermal equilibrium

Statistical mechanics of economics I

Energy Technology Data Exchange (ETDEWEB)

Kusmartsev, F.V., E-mail: F.Kusmartsev@lboro.ac.u [Department of Physics, Loughborough University, Leicestershire, LE11 3TU (United Kingdom)

2011-02-07

We show that statistical mechanics is useful in the description of financial crisis and economics. Taking a large amount of instant snapshots of a market over an interval of time we construct their ensembles and study their statistical interference. This results in a probability description of the market and gives capital, money, income, wealth and debt distributions, which in the most cases takes the form of the Bose-Einstein distribution. In addition, statistical mechanics provides the main market equations and laws which govern the correlations between the amount of money, debt, product, prices and number of retailers. We applied the found relations to a study of the evolution of the economics in USA between the years 1996 to 2008 and observe that over that time the income of a major population is well described by the Bose-Einstein distribution which parameters are different for each year. Each financial crisis corresponds to a peak in the absolute activity coefficient. The analysis correctly indicates the past crises and predicts the future one.

Statistical mechanics of economics I

International Nuclear Information System (INIS)

Kusmartsev, F.V.

2011-01-01

We show that statistical mechanics is useful in the description of financial crisis and economics. Taking a large amount of instant snapshots of a market over an interval of time we construct their ensembles and study their statistical interference. This results in a probability description of the market and gives capital, money, income, wealth and debt distributions, which in the most cases takes the form of the Bose-Einstein distribution. In addition, statistical mechanics provides the main market equations and laws which govern the correlations between the amount of money, debt, product, prices and number of retailers. We applied the found relations to a study of the evolution of the economics in USA between the years 1996 to 2008 and observe that over that time the income of a major population is well described by the Bose-Einstein distribution which parameters are different for each year. Each financial crisis corresponds to a peak in the absolute activity coefficient. The analysis correctly indicates the past crises and predicts the future one.

Statistical mechanical analysis of the linear vector channel in digital communication

International Nuclear Information System (INIS)

Takeda, Koujin; Hatabu, Atsushi; Kabashima, Yoshiyuki

2007-01-01

A statistical mechanical framework to analyze linear vector channel models in digital wireless communication is proposed for a large system. The framework is a generalization of that proposed for code-division multiple-access systems in Takeda et al (2006 Europhys. Lett. 76 1193) and enables the analysis of the system in which the elements of the channel transfer matrix are statistically correlated with each other. The significance of the proposed scheme is demonstrated by assessing the performance of an existing model of multi-input multi-output communication systems

Learning Predictive Statistics: Strategies and Brain Mechanisms.

Science.gov (United States)

Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew E; Kourtzi, Zoe

2017-08-30

When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory-motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions. SIGNIFICANCE STATEMENT Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. Past work has studied how humans identify repetitive patterns and associative pairings. However, the natural environment contains regularities that vary in complexity from simple repetition to complex probabilistic combinations. Here, we combine behavior and multisession fMRI to track the brain mechanisms that mediate our ability to adapt to

Statistical mechanics and applications in condensed matter

CERN Document Server

Di Castro, Carlo

2015-01-01

This innovative and modular textbook combines classical topics in thermodynamics, statistical mechanics and many-body theory with the latest developments in condensed matter physics research. Written by internationally renowned experts and logically structured to cater for undergraduate and postgraduate students and researchers, it covers the underlying theoretical principles and includes numerous problems and worked examples to put this knowledge into practice. Three main streams provide a framework for the book; beginning with thermodynamics and classical statistical mechanics, including mean field approximation, fluctuations and the renormalization group approach to critical phenomena. The authors then examine quantum statistical mechanics, covering key topics such as normal Fermi and Luttinger liquids, superfluidity and superconductivity. Finally, they explore classical and quantum kinetics, Anderson localization and quantum interference, and disordered Fermi liquids. Unique in providing a bridge between ...

Structural reliability in context of statistical uncertainties and modelling discrepancies

International Nuclear Information System (INIS)

Pendola, Maurice

2000-01-01

Structural reliability methods have been largely improved during the last years and have showed their ability to deal with uncertainties during the design stage or to optimize the functioning and the maintenance of industrial installations. They are based on a mechanical modeling of the structural behavior according to the considered failure modes and on a probabilistic representation of input parameters of this modeling. In practice, only limited statistical information is available to build the probabilistic representation and different sophistication levels of the mechanical modeling may be introduced. Thus, besides the physical randomness, other uncertainties occur in such analyses. The aim of this work is triple: 1. at first, to propose a methodology able to characterize the statistical uncertainties due to the limited number of data in order to take them into account in the reliability analyses. The obtained reliability index measures the confidence in the structure considering the statistical information available. 2. Then, to show a methodology leading to reliability results evaluated from a particular mechanical modeling but by using a less sophisticated one. The objective is then to decrease the computational efforts required by the reference modeling. 3. Finally, to propose partial safety factors that are evolving as a function of the number of statistical data available and as a function of the sophistication level of the mechanical modeling that is used. The concepts are illustrated in the case of a welded pipe and in the case of a natural draught cooling tower. The results show the interest of the methodologies in an industrial context. [fr

Statistical models based on conditional probability distributions

International Nuclear Information System (INIS)

Narayanan, R.S.

1991-10-01

We present a formulation of statistical mechanics models based on conditional probability distribution rather than a Hamiltonian. We show that it is possible to realize critical phenomena through this procedure. Closely linked with this formulation is a Monte Carlo algorithm, in which a configuration generated is guaranteed to be statistically independent from any other configuration for all values of the parameters, in particular near the critical point. (orig.)

Statistical mechanics of solitons

International Nuclear Information System (INIS)

Bishop, A.

1980-01-01

The status of statistical mechanics theory (classical and quantum, statics and dynamics) is reviewed for 1-D soliton or solitary-wave-bearing systems. Primary attention is given to (i) perspective for existing results with evaluation and representative literature guide; (ii) motivation and status report for remaining problems; (iii) discussion of connections with other 1-D topics

Statistical mechanics of socio-economic systems with heterogeneous agents

International Nuclear Information System (INIS)

De Martino, Andrea; Marsili, Matteo

2006-01-01

We review the statistical mechanics approach to the study of the emerging collective behaviour of systems of heterogeneous interacting agents. The general framework is presented through examples in such contexts as ecosystem dynamics and traffic modelling. We then focus on the analysis of the optimal properties of large random resource-allocation problems and on Minority Games and related models of speculative trading in financial markets, discussing a number of extensions including multi-asset models, majority games and models with asymmetric information. Finally, we summarize the main conclusions and outline the major open problems and limitations of the approach. (topical review)

Statistical model for the mechanical behavior of the tissue engineering non-woven fibrous matrices under large deformation.

Science.gov (United States)

Rizvi, Mohd Suhail; Pal, Anupam

2014-09-01

The fibrous matrices are widely used as scaffolds for the regeneration of load-bearing tissues due to their structural and mechanical similarities with the fibrous components of the extracellular matrix. These scaffolds not only provide the appropriate microenvironment for the residing cells but also act as medium for the transmission of the mechanical stimuli, essential for the tissue regeneration, from macroscopic scale of the scaffolds to the microscopic scale of cells. The requirement of the mechanical loading for the tissue regeneration requires the fibrous scaffolds to be able to sustain the complex three-dimensional mechanical loading conditions. In order to gain insight into the mechanical behavior of the fibrous matrices under large amount of elongation as well as shear, a statistical model has been formulated to study the macroscopic mechanical behavior of the electrospun fibrous matrix and the transmission of the mechanical stimuli from scaffolds to the cells via the constituting fibers. The study establishes the load-deformation relationships for the fibrous matrices for different structural parameters. It also quantifies the changes in the fiber arrangement and tension generated in the fibers with the deformation of the matrix. The model reveals that the tension generated in the fibers on matrix deformation is not homogeneous and hence the cells located in different regions of the fibrous scaffold might experience different mechanical stimuli. The mechanical response of fibrous matrices was also found to be dependent on the aspect ratio of the matrix. Therefore, the model establishes a structure-mechanics interdependence of the fibrous matrices under large deformation, which can be utilized in identifying the appropriate structure and external mechanical loading conditions for the regeneration of load-bearing tissues. Copyright © 2014 Elsevier Ltd. All rights reserved.

Representative volume size: A comparison of statistical continuum mechanics and statistical physics

Energy Technology Data Exchange (ETDEWEB)

AIDUN,JOHN B.; TRUCANO,TIMOTHY G.; LO,CHI S.; FYE,RICHARD M.

1999-05-01

In this combination background and position paper, the authors argue that careful work is needed to develop accurate methods for relating the results of fine-scale numerical simulations of material processes to meaningful values of macroscopic properties for use in constitutive models suitable for finite element solid mechanics simulations. To provide a definite context for this discussion, the problem is couched in terms of the lack of general objective criteria for identifying the size of the representative volume (RV) of a material. The objective of this report is to lay out at least the beginnings of an approach for applying results and methods from statistical physics to develop concepts and tools necessary for determining the RV size, as well as alternatives to RV volume-averaging for situations in which the RV is unmanageably large. The background necessary to understand the pertinent issues and statistical physics concepts is presented.

Statistical Mechanics of Coherent Ising Machine — The Case of Ferromagnetic and Finite-Loading Hopfield Models —

Science.gov (United States)

Aonishi, Toru; Mimura, Kazushi; Utsunomiya, Shoko; Okada, Masato; Yamamoto, Yoshihisa

2017-10-01

The coherent Ising machine (CIM) has attracted attention as one of the most effective Ising computing architectures for solving large scale optimization problems because of its scalability and high-speed computational ability. However, it is difficult to implement the Ising computation in the CIM because the theories and techniques of classical thermodynamic equilibrium Ising spin systems cannot be directly applied to the CIM. This means we have to adapt these theories and techniques to the CIM. Here we focus on a ferromagnetic model and a finite loading Hopfield model, which are canonical models sharing a common mathematical structure with almost all other Ising models. We derive macroscopic equations to capture nonequilibrium phase transitions in these models. The statistical mechanical methods developed here constitute a basis for constructing evaluation methods for other Ising computation models.

Statistical ensembles in quantum mechanics

International Nuclear Information System (INIS)

Blokhintsev, D.

1976-01-01

The interpretation of quantum mechanics presented in this paper is based on the concept of quantum ensembles. This concept differs essentially from the canonical one by that the interference of the observer into the state of a microscopic system is of no greater importance than in any other field of physics. Owing to this fact, the laws established by quantum mechanics are not of less objective character than the laws governing classical statistical mechanics. The paradoxical nature of some statements of quantum mechanics which result from the interpretation of the wave functions as the observer's notebook greatly stimulated the development of the idea presented. (Auth.)

Statistical Mechanics of Turbulent Dynamos

Science.gov (United States)

Shebalin, John V.

2014-01-01

Incompressible magnetohydrodynamic (MHD) turbulence and magnetic dynamos, which occur in magnetofluids with large fluid and magnetic Reynolds numbers, will be discussed. When Reynolds numbers are large and energy decays slowly, the distribution of energy with respect to length scale becomes quasi-stationary and MHD turbulence can be described statistically. In the limit of infinite Reynolds numbers, viscosity and resistivity become zero and if these values are used in the MHD equations ab initio, a model system called ideal MHD turbulence results. This model system is typically confined in simple geometries with some form of homogeneous boundary conditions, allowing for velocity and magnetic field to be represented by orthogonal function expansions. One advantage to this is that the coefficients of the expansions form a set of nonlinearly interacting variables whose behavior can be described by equilibrium statistical mechanics, i.e., by a canonical ensemble theory based on the global invariants (energy, cross helicity and magnetic helicity) of ideal MHD turbulence. Another advantage is that truncated expansions provide a finite dynamical system whose time evolution can be numerically simulated to test the predictions of the associated statistical mechanics. If ensemble predictions are the same as time averages, then the system is said to be ergodic; if not, the system is nonergodic. Although it had been implicitly assumed in the early days of ideal MHD statistical theory development that these finite dynamical systems were ergodic, numerical simulations provided sufficient evidence that they were, in fact, nonergodic. Specifically, while canonical ensemble theory predicted that expansion coefficients would be (i) zero-mean random variables with (ii) energy that decreased with length scale, it was found that although (ii) was correct, (i) was not and the expected ergodicity was broken. The exact cause of this broken ergodicity was explained, after much

Statistical mechanics of dense granular media

International Nuclear Information System (INIS)

Coniglio, A; Fierro, A; Nicodemi, M; Ciamarra, M Pica; Tarzia, M

2005-01-01

We discuss some recent results on the statistical mechanics approach to dense granular media. In particular, by analytical mean field investigation we derive the phase diagram of monodisperse and bidisperse granular assemblies. We show that 'jamming' corresponds to a phase transition from a 'fluid' to a 'glassy' phase, observed when crystallization is avoided. The nature of such a 'glassy' phase turns out to be the same as found in mean field models for glass formers. This gives quantitative evidence for the idea of a unified description of the 'jamming' transition in granular media and thermal systems, such as glasses. We also discuss mixing/segregation transitions in binary mixtures and their connections to phase separation and 'geometric' effects

A κ-generalized statistical mechanics approach to income analysis

Science.gov (United States)

Clementi, F.; Gallegati, M.; Kaniadakis, G.

2009-02-01

This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low-middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful.

A κ-generalized statistical mechanics approach to income analysis

International Nuclear Information System (INIS)

Clementi, F; Gallegati, M; Kaniadakis, G

2009-01-01

This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low–middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful

Some connections between relativistic classical mechanics, statistical mechanics, and quantum field theory

International Nuclear Information System (INIS)

Remler, E.A.

1977-01-01

A gauge-invariant version of the Wigner representation is used to relate relativistic mechanics, statistical mechanics, and quantum field theory in the context of the electrodynamics of scalar particles. A unified formulation of quantum field theory and statistical mechanics is developed which clarifies the physics interpretation of the single-particle Wigner function. A covariant form of Ehrenfest's theorem is derived. Classical electrodynamics is derived from quantum field theory after making a random-phase approximation. The validity of this approximation is discussed

Addressing the statistical mechanics of planet orbits in the solar system

Science.gov (United States)

Mogavero, Federico

2017-10-01

The chaotic nature of planet dynamics in the solar system suggests the relevance of a statistical approach to planetary orbits. In such a statistical description, the time-dependent position and velocity of the planets are replaced by the probability density function (PDF) of their orbital elements. It is natural to set up this kind of approach in the framework of statistical mechanics. In the present paper, I focus on the collisionless excitation of eccentricities and inclinations via gravitational interactions in a planetary system. The future planet trajectories in the solar system constitute the prototype of this kind of dynamics. I thus address the statistical mechanics of the solar system planet orbits and try to reproduce the PDFs numerically constructed by Laskar (2008, Icarus, 196, 1). I show that the microcanonical ensemble of the Laplace-Lagrange theory accurately reproduces the statistics of the giant planet orbits. To model the inner planets I then investigate the ansatz of equiprobability in the phase space constrained by the secular integrals of motion. The eccentricity and inclination PDFs of Earth and Venus are reproduced with no free parameters. Within the limitations of a stationary model, the predictions also show a reasonable agreement with Mars PDFs and that of Mercury inclination. The eccentricity of Mercury demands in contrast a deeper analysis. I finally revisit the random walk approach of Laskar to the time dependence of the inner planet PDFs. Such a statistical theory could be combined with direct numerical simulations of planet trajectories in the context of planet formation, which is likely to be a chaotic process.

Maximum entropy principle and hydrodynamic models in statistical mechanics

International Nuclear Information System (INIS)

Trovato, M.; Reggiani, L.

2012-01-01

This review presents the state of the art of the maximum entropy principle (MEP) in its classical and quantum (QMEP) formulation. Within the classical MEP we overview a general theory able to provide, in a dynamical context, the macroscopic relevant variables for carrier transport in the presence of electric fields of arbitrary strength. For the macroscopic variables the linearized maximum entropy approach is developed including full-band effects within a total energy scheme. Under spatially homogeneous conditions, we construct a closed set of hydrodynamic equations for the small-signal (dynamic) response of the macroscopic variables. The coupling between the driving field and the energy dissipation is analyzed quantitatively by using an arbitrary number of moments of the distribution function. Analogously, the theoretical approach is applied to many one-dimensional n + nn + submicron Si structures by using different band structure models, different doping profiles, different applied biases and is validated by comparing numerical calculations with ensemble Monte Carlo simulations and with available experimental data. Within the quantum MEP we introduce a quantum entropy functional of the reduced density matrix, the principle of quantum maximum entropy is then asserted as fundamental principle of quantum statistical mechanics. Accordingly, we have developed a comprehensive theoretical formalism to construct rigorously a closed quantum hydrodynamic transport within a Wigner function approach. The theory is formulated both in thermodynamic equilibrium and nonequilibrium conditions, and the quantum contributions are obtained by only assuming that the Lagrange multipliers can be expanded in powers of ħ 2 , being ħ the reduced Planck constant. In particular, by using an arbitrary number of moments, we prove that: i) on a macroscopic scale all nonlocal effects, compatible with the uncertainty principle, are imputable to high-order spatial derivatives both of the

Statistical learning and probabilistic prediction in music cognition: mechanisms of stylistic enculturation.

Science.gov (United States)

Pearce, Marcus T

2018-05-11

Music perception depends on internal psychological models derived through exposure to a musical culture. It is hypothesized that this musical enculturation depends on two cognitive processes: (1) statistical learning, in which listeners acquire internal cognitive models of statistical regularities present in the music to which they are exposed; and (2) probabilistic prediction based on these learned models that enables listeners to organize and process their mental representations of music. To corroborate these hypotheses, I review research that uses a computational model of probabilistic prediction based on statistical learning (the information dynamics of music (IDyOM) model) to simulate data from empirical studies of human listeners. The results show that a broad range of psychological processes involved in music perception-expectation, emotion, memory, similarity, segmentation, and meter-can be understood in terms of a single, underlying process of probabilistic prediction using learned statistical models. Furthermore, IDyOM simulations of listeners from different musical cultures demonstrate that statistical learning can plausibly predict causal effects of differential cultural exposure to musical styles, providing a quantitative model of cultural distance. Understanding the neural basis of musical enculturation will benefit from close coordination between empirical neuroimaging and computational modeling of underlying mechanisms, as outlined here. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.

Journey Through Statistical Mechanics

Science.gov (United States)

Yang, C. N.

2013-05-01

My first involvement with statistical mechanics and the many body problem was when I was a student at The National Southwest Associated University in Kunming during the war. At that time Professor Wang Zhu-Xi had just come back from Cambridge, England, where he was a student of Fowler, and his thesis was on phase transitions, a hot topic at that time, and still a very hot topic today...

Statistical mechanics of black holes

International Nuclear Information System (INIS)

Harms, B.; Leblanc, Y.

1992-01-01

We analyze the statistical mechanics of a gas of neutral and charged black holes. The microcanonical ensemble is the only possible approach to this system, and the equilibrium configuration is the one for which most of the energy is carried by a single black hole. Schwarzschild black holes are found to obey the statistical bootstrap condition. In all cases, the microcanonical temperature is identical to the Hawking temperature of the most massive black hole in the gas. U(1) charges in general break the bootstrap property. The problems of black-hole decay and of quantum coherence are also addressed

Is quantum theory a form of statistical mechanics?

Science.gov (United States)

Adler, S. L.

2007-05-01

We give a review of the basic themes of my recent book: Adler S L 2004 Quantum Theory as an Emergent Phenomenon (Cambridge: Cambridge University Press). We first give motivations for considering the possibility that quantum mechanics is not exact, but is instead an accurate asymptotic approximation to a deeper level theory. For this deeper level, we propose a non-commutative generalization of classical mechanics, that we call "trace dynamics", and we give a brief survey of how it works, considering for simplicity only the bosonic case. We then discuss the statistical mechanics of trace dynamics and give our argument that with suitable approximations, the Ward identities for trace dynamics imply that ensemble averages in the canonical ensemble correspond to Wightman functions in quantum field theory. Thus, quantum theory emerges as the statistical thermodynamics of trace dynamics. Finally, we argue that Brownian motion corrections to this thermodynamics lead to stochastic corrections to the Schrödinger equation, of the type that have been much studied in the "continuous spontaneous localization" model of objective state vector reduction. In appendices to the talk, we give details of the existence of a conserved operator in trace dynamics that encodes the structure of the canonical algebra, of the derivation of the Ward identities, and of the proof that the stochastically-modified Schrödinger equation leads to state vector reduction with Born rule probabilities.

Statistical mechanics of multipartite entanglement

Science.gov (United States)

Facchi, P.; Florio, G.; Marzolino, U.; Parisi, G.; Pascazio, S.

2009-02-01

We characterize the multipartite entanglement of a system of n qubits in terms of the distribution function of the bipartite purity over all balanced bipartitions. We search for those (maximally multipartite entangled) states whose purity is minimum for all bipartitions and recast this optimization problem into a problem of statistical mechanics.

Statistical mechanics of multipartite entanglement

Energy Technology Data Exchange (ETDEWEB)

Facchi, P [Dipartimento di Matematica, Universita di Bari, I-70125 Bari (Italy); Florio, G; Pascazio, S [Istituto Nazionale di Fisica Nucleare, Sezione di Bari, I-70126 Bari (Italy); Marzolino, U [Dipartimento di Fisica Teorica, Universita di Trieste, Strada Costiera 11, 34014 Trieste (Italy); Parisi, G [Dipartimento di Fisica, Universita di Roma ' La Sapienza' , Piazzale Aldo Moro 2, 00185 Roma, Italy, Centre for Statistical Mechanics and Complexity (SMC), CNR-INFM, 00185 Roma (Italy)

2009-02-06

We characterize the multipartite entanglement of a system of n qubits in terms of the distribution function of the bipartite purity over all balanced bipartitions. We search for those (maximally multipartite entangled) states whose purity is minimum for all bipartitions and recast this optimization problem into a problem of statistical mechanics.

Statistical mechanics of multipartite entanglement

International Nuclear Information System (INIS)

Facchi, P; Florio, G; Pascazio, S; Marzolino, U; Parisi, G

2009-01-01

We characterize the multipartite entanglement of a system of n qubits in terms of the distribution function of the bipartite purity over all balanced bipartitions. We search for those (maximally multipartite entangled) states whose purity is minimum for all bipartitions and recast this optimization problem into a problem of statistical mechanics

Statistical mechanics in the context of special relativity.

Science.gov (United States)

Kaniadakis, G

2002-11-01

In Ref. [Physica A 296, 405 (2001)], starting from the one parameter deformation of the exponential function exp(kappa)(x)=(sqrt[1+kappa(2)x(2)]+kappax)(1/kappa), a statistical mechanics has been constructed which reduces to the ordinary Boltzmann-Gibbs statistical mechanics as the deformation parameter kappa approaches to zero. The distribution f=exp(kappa)(-beta E+betamu) obtained within this statistical mechanics shows a power law tail and depends on the nonspecified parameter beta, containing all the information about the temperature of the system. On the other hand, the entropic form S(kappa)= integral d(3)p(c(kappa) f(1+kappa)+c(-kappa) f(1-kappa)), which after maximization produces the distribution f and reduces to the standard Boltzmann-Shannon entropy S0 as kappa-->0, contains the coefficient c(kappa) whose expression involves, beside the Boltzmann constant, another nonspecified parameter alpha. In the present effort we show that S(kappa) is the unique existing entropy obtained by a continuous deformation of S0 and preserving unaltered its fundamental properties of concavity, additivity, and extensivity. These properties of S(kappa) permit to determine unequivocally the values of the above mentioned parameters beta and alpha. Subsequently, we explain the origin of the deformation mechanism introduced by kappa and show that this deformation emerges naturally within the Einstein special relativity. Furthermore, we extend the theory in order to treat statistical systems in a time dependent and relativistic context. Then, we show that it is possible to determine in a self consistent scheme within the special relativity the values of the free parameter kappa which results to depend on the light speed c and reduces to zero as c--> infinity recovering in this way the ordinary statistical mechanics and thermodynamics. The statistical mechanics here presented, does not contain free parameters, preserves unaltered the mathematical and epistemological structure of

Statistical mechanics of low-density parity-check codes

Energy Technology Data Exchange (ETDEWEB)

Kabashima, Yoshiyuki [Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama 2268502 (Japan); Saad, David [Neural Computing Research Group, Aston University, Birmingham B4 7ET (United Kingdom)

2004-02-13

We review recent theoretical progress on the statistical mechanics of error correcting codes, focusing on low-density parity-check (LDPC) codes in general, and on Gallager and MacKay-Neal codes in particular. By exploiting the relation between LDPC codes and Ising spin systems with multi-spin interactions, one can carry out a statistical mechanics based analysis that determines the practical and theoretical limitations of various code constructions, corresponding to dynamical and thermodynamical transitions, respectively, as well as the behaviour of error-exponents averaged over the corresponding code ensemble as a function of channel noise. We also contrast the results obtained using methods of statistical mechanics with those derived in the information theory literature, and show how these methods can be generalized to include other channel types and related communication problems. (topical review)

Statistical mechanics of low-density parity-check codes

International Nuclear Information System (INIS)

Kabashima, Yoshiyuki; Saad, David

2004-01-01

We review recent theoretical progress on the statistical mechanics of error correcting codes, focusing on low-density parity-check (LDPC) codes in general, and on Gallager and MacKay-Neal codes in particular. By exploiting the relation between LDPC codes and Ising spin systems with multi-spin interactions, one can carry out a statistical mechanics based analysis that determines the practical and theoretical limitations of various code constructions, corresponding to dynamical and thermodynamical transitions, respectively, as well as the behaviour of error-exponents averaged over the corresponding code ensemble as a function of channel noise. We also contrast the results obtained using methods of statistical mechanics with those derived in the information theory literature, and show how these methods can be generalized to include other channel types and related communication problems. (topical review)

Generalized statistical mechanics approaches to earthquakes and tectonics

Science.gov (United States)

Papadakis, Giorgos; Michas, Georgios

2016-01-01

Despite the extreme complexity that characterizes the mechanism of the earthquake generation process, simple empirical scaling relations apply to the collective properties of earthquakes and faults in a variety of tectonic environments and scales. The physical characterization of those properties and the scaling relations that describe them attract a wide scientific interest and are incorporated in the probabilistic forecasting of seismicity in local, regional and planetary scales. Considerable progress has been made in the analysis of the statistical mechanics of earthquakes, which, based on the principle of entropy, can provide a physical rationale to the macroscopic properties frequently observed. The scale-invariant properties, the (multi) fractal structures and the long-range interactions that have been found to characterize fault and earthquake populations have recently led to the consideration of non-extensive statistical mechanics (NESM) as a consistent statistical mechanics framework for the description of seismicity. The consistency between NESM and observations has been demonstrated in a series of publications on seismicity, faulting, rock physics and other fields of geosciences. The aim of this review is to present in a concise manner the fundamental macroscopic properties of earthquakes and faulting and how these can be derived by using the notions of statistical mechanics and NESM, providing further insights into earthquake physics and fault growth processes. PMID:28119548

Statistical and stochastic aspects of the delocalization problem in quantum mechanics

International Nuclear Information System (INIS)

Claverie, P.; Diner, S.

1976-01-01

The space-time behaviour of electrons in atoms and molecules is reviewed. The wave conception of the electron is criticized and the poverty of the non-reductionist attitude is underlined. Further, the two main interpretations of quantum mechanics are recalled: the Copenhagen and the Statistical Interpretations. The meaning and the successes of the Statistical Interpretation are explained and it is shown that it does not solve all problems because quantum mechanics is irreducible to a classical statistical theory. The fluctuation of the particle number and its relationship to loge theory, delocalization and correlation is studied. Finally, different stochastic models for microphysics are reviewed. The markovian Fenyes-Nelson process allows an interpretation of the original heuristic considerations of Schroedinger. Non-markov processes with Schroedinger time evolution are shown to be equivalent to the base state analysis of Feynmann but they are unsatisfactory from a probabilistic point of view. Stochastic electrodynamics is presented as the most satisfactory conception nowadays

Metamodelling Messages Conveyed in Five Statistical Mechanical Textbooks from 1936 to 2001

Science.gov (United States)

Niss, Martin

2009-01-01

Modelling is a significant aspect of doing physics and it is important how this activity is taught. This paper focuses on the explicit or implicit messages about modelling conveyed to the student in the treatments of phase transitions in statistical mechanics textbooks at beginning graduate level. Five textbooks from the 1930s to the present are…

A quantum information approach to statistical mechanics

International Nuclear Information System (INIS)

Cuevas, G.

2011-01-01

The field of quantum information and computation harnesses and exploits the properties of quantum mechanics to perform tasks more efficiently than their classical counterparts, or that may uniquely be possible in the quantum world. Its findings and techniques have been applied to a number of fields, such as the study of entanglement in strongly correlated systems, new simulation techniques for many-body physics or, generally, to quantum optics. This thesis aims at broadening the scope of quantum information theory by applying it to problems in statistical mechanics. We focus on classical spin models, which are toy models used in a variety of systems, ranging from magnetism, neural networks, to quantum gravity. We tackle these models using quantum information tools from three different angles. First, we show how the partition function of a class of widely different classical spin models (models in different dimensions, different types of many-body interactions, different symmetries, etc) can be mapped to the partition function of a single model. We prove this by first establishing a relation between partition functions and quantum states, and then transforming the corresponding quantum states to each other. Second, we give efficient quantum algorithms to estimate the partition function of various classical spin models, such as the Ising or the Potts model. The proof is based on a relation between partition functions and quantum circuits, which allows us to determine the quantum computational complexity of the partition function by studying the corresponding quantum circuit. Finally, we outline the possibility of applying quantum information concepts and tools to certain models of dis- crete quantum gravity. The latter provide a natural route to generalize our results, insofar as the central quantity has the form of a partition function, and as classical spin models are used as toy models of matter. (author)

Quantum mechanics as a natural generalization of classical statistical mechanics

International Nuclear Information System (INIS)

Xu Laizi; Qian Shangwu

1994-01-01

By comparison between equations of motion of geometrical optics (GO) and that of classical statistical mechanics (CSM), it is found that there should be an analogy between GO and CSM instead of GO and classical mechanics (CM). Furthermore, by comparison between the classical limit (CL) of quantum mechanics (QM) and CSM, the authors find that CL of QM is CSM not CM, hence they demonstrated that QM is a natural generalization of CSM instead of CM

Modeling and Analysis of Mechanical Properties of Aluminium Alloy (A413 Processed through Squeeze Casting Route Using Artificial Neural Network Model and Statistical Technique

Directory of Open Access Journals (Sweden)

R. Soundararajan

2015-01-01

Full Text Available Artificial Neural Network (ANN approach was used for predicting and analyzing the mechanical properties of A413 aluminum alloy produced by squeeze casting route. The experiments are carried out with different controlled input variables such as squeeze pressure, die preheating temperature, and melt temperature as per Full Factorial Design (FFD. The accounted absolute process variables produce a casting with pore-free and ideal fine grain dendritic structure resulting in good mechanical properties such as hardness, ultimate tensile strength, and yield strength. As a primary objective, a feed forward back propagation ANN model has been developed with different architectures for ensuring the definiteness of the values. The developed model along with its predicted data was in good agreement with the experimental data, inferring the valuable performance of the optimal model. From the work it was ascertained that, for castings produced by squeeze casting route, the ANN is an alternative method for predicting the mechanical properties and appropriate results can be estimated rather than measured, thereby reducing the testing time and cost. As a secondary objective, quantitative and statistical analysis was performed in order to evaluate the effect of process parameters on the mechanical properties of the castings.

Advanced data analysis in neuroscience integrating statistical and computational models

CERN Document Server

Durstewitz, Daniel

2017-01-01

This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification, to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering.  Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanat ory frameworks, but become powerfu...

A statistical mechanical approach to restricted integer partition functions

Science.gov (United States)

Zhou, Chi-Chun; Dai, Wu-Sheng

2018-05-01

The main aim of this paper is twofold: (1) suggesting a statistical mechanical approach to the calculation of the generating function of restricted integer partition functions which count the number of partitions—a way of writing an integer as a sum of other integers under certain restrictions. In this approach, the generating function of restricted integer partition functions is constructed from the canonical partition functions of various quantum gases. (2) Introducing a new type of restricted integer partition functions corresponding to general statistics which is a generalization of Gentile statistics in statistical mechanics; many kinds of restricted integer partition functions are special cases of this restricted integer partition function. Moreover, with statistical mechanics as a bridge, we reveal a mathematical fact: the generating function of restricted integer partition function is just the symmetric function which is a class of functions being invariant under the action of permutation groups. Using this approach, we provide some expressions of restricted integer partition functions as examples.

Equilibrium statistical mechanics for self-gravitating systems: local ergodicity and extended Boltzmann-Gibbs/White-Narayan statistics

Science.gov (United States)

He, Ping

2012-01-01

The long-standing puzzle surrounding the statistical mechanics of self-gravitating systems has not yet been solved successfully. We formulate a systematic theoretical framework of entropy-based statistical mechanics for spherically symmetric collisionless self-gravitating systems. We use an approach that is very different from that of the conventional statistical mechanics of short-range interaction systems. We demonstrate that the equilibrium states of self-gravitating systems consist of both mechanical and statistical equilibria, with the former characterized by a series of velocity-moment equations and the latter by statistical equilibrium equations, which should be derived from the entropy principle. The velocity-moment equations of all orders are derived from the steady-state collisionless Boltzmann equation. We point out that the ergodicity is invalid for the whole self-gravitating system, but it can be re-established locally. Based on the local ergodicity, using Fermi-Dirac-like statistics, with the non-degenerate condition and the spatial independence of the local microstates, we rederive the Boltzmann-Gibbs entropy. This is consistent with the validity of the collisionless Boltzmann equation, and should be the correct entropy form for collisionless self-gravitating systems. Apart from the usual constraints of mass and energy conservation, we demonstrate that the series of moment or virialization equations must be included as additional constraints on the entropy functional when performing the variational calculus; this is an extension to the original prescription by White & Narayan. Any possible velocity distribution can be produced by the statistical-mechanical approach that we have developed with the extended Boltzmann-Gibbs/White-Narayan statistics. Finally, we discuss the questions of negative specific heat and ensemble inequivalence for self-gravitating systems.

Statistical mechanical analysis of LMFBR fuel cladding tubes

International Nuclear Information System (INIS)

Poncelet, J.-P.; Pay, A.

1977-01-01

The most important design requirement on fuel pin cladding for LMFBR's is its mechanical integrity. Disruptive factors include internal pressure from mixed oxide fuel fission gas release, thermal stresses and high temperature creep, neutron-induced differential void-swelling as a source of stress in the cladding and irradiation creep of stainless steel material, corrosion by fission products. Under irradiation these load-restraining mechanisms are accentuated by stainless steel embrittlement and strength alterations. To account for the numerous uncertainties involved in the analysis by theoretical models and computer codes statistical tools are unavoidably requested, i.e. Monte Carlo simulation methods. Thanks to these techniques, uncertainties in nominal characteristics, material properties and environmental conditions can be linked up in a correct way and used for a more accurate conceptual design. (Auth.)

Growth Curve Models and Applications : Indian Statistical Institute

CERN Document Server

2017-01-01

Growth curve models in longitudinal studies are widely used to model population size, body height, biomass, fungal growth, and other variables in the biological sciences, but these statistical methods for modeling growth curves and analyzing longitudinal data also extend to general statistics, economics, public health, demographics, epidemiology, SQC, sociology, nano-biotechnology, fluid mechanics, and other applied areas.   There is no one-size-fits-all approach to growth measurement. The selected papers in this volume build on presentations from the GCM workshop held at the Indian Statistical Institute, Giridih, on March 28-29, 2016. They represent recent trends in GCM research on different subject areas, both theoretical and applied. This book includes tools and possibilities for further work through new techniques and modification of existing ones. The volume includes original studies, theoretical findings and case studies from a wide range of app lied work, and these contributions have been externally r...

Thermalized solutions, statistical mechanics and turbulence

Indian Academy of Sciences (India)

2015-02-20

Feb 20, 2015 ... In this study, we examine the intriguing connection between turbulence and equilibrium statistical mechanics. There are several recent works which emphasize this connection. Thus in the last ... Current Issue : Vol. 90, Issue 6.

Statistical mechanical analysis of linear programming relaxation for combinatorial optimization problems

Science.gov (United States)

Takabe, Satoshi; Hukushima, Koji

2016-05-01

Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α -uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α =2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c =e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c =1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α ≥3 , minimum vertex covers on α -uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c =e /(α -1 ) where the replica symmetry is broken.

Statistical mechanical analysis of linear programming relaxation for combinatorial optimization problems.

Science.gov (United States)

Takabe, Satoshi; Hukushima, Koji

2016-05-01

Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α-uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α=2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c=e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c=1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α≥3, minimum vertex covers on α-uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c=e/(α-1) where the replica symmetry is broken.

Annotations to quantum statistical mechanics

CERN Document Server

Kim, In-Gee

2018-01-01

This book is a rewritten and annotated version of Leo P. Kadanoff and Gordon Baym’s lectures that were presented in the book Quantum Statistical Mechanics: Green’s Function Methods in Equilibrium and Nonequilibrium Problems. The lectures were devoted to a discussion on the use of thermodynamic Green’s functions in describing the properties of many-particle systems. The functions provided a method for discussing finite-temperature problems with no more conceptual difficulty than ground-state problems, and the method was equally applicable to boson and fermion systems and equilibrium and nonequilibrium problems. The lectures also explained nonequilibrium statistical physics in a systematic way and contained essential concepts on statistical physics in terms of Green’s functions with sufficient and rigorous details. In-Gee Kim thoroughly studied the lectures during one of his research projects but found that the unspecialized method used to present them in the form of a book reduced their readability. He st...

Applying Statistical Mechanics to pixel detectors

International Nuclear Information System (INIS)

Pindo, Massimiliano

2002-01-01

Pixel detectors, being made of a large number of active cells of the same kind, can be considered as significant sets to which Statistical Mechanics variables and methods can be applied. By properly redefining well known statistical parameters in order to let them match the ones that actually characterize pixel detectors, an analysis of the way they work can be performed in a totally new perspective. A deeper understanding of pixel detectors is attained, helping in the evaluation and comparison of their intrinsic characteristics and performance

Projection operator techniques in nonequilibrium statistical mechanics

International Nuclear Information System (INIS)

Grabert, H.

1982-01-01

This book is an introduction to the application of the projection operator technique to the statistical mechanics of irreversible processes. After a general introduction to the projection operator technique and statistical thermodynamics the Fokker-Planck and the master equation approach are described together with the response theory. Then, as applications the damped harmonic oscillator, simple fluids, and the spin relaxation are considered. (HSI)

Thermodynamics and statistical mechanics an integrated approach

CERN Document Server

Shell, M Scott

2015-01-01

Learn classical thermodynamics alongside statistical mechanics with this fresh approach to the subjects. Molecular and macroscopic principles are explained in an integrated, side-by-side manner to give students a deep, intuitive understanding of thermodynamics and equip them to tackle future research topics that focus on the nanoscale. Entropy is introduced from the get-go, providing a clear explanation of how the classical laws connect to the molecular principles, and closing the gap between the atomic world and thermodynamics. Notation is streamlined throughout, with a focus on general concepts and simple models, for building basic physical intuition and gaining confidence in problem analysis and model development. Well over 400 guided end-of-chapter problems are included, addressing conceptual, fundamental, and applied skill sets. Numerous worked examples are also provided together with handy shaded boxes to emphasize key concepts, making this the complete teaching package for students in chemical engineer...

A statistical model for mapping morphological shape

Directory of Open Access Journals (Sweden)

Li Jiahan

2010-07-01

Full Text Available Abstract Background Living things come in all shapes and sizes, from bacteria, plants, and animals to humans. Knowledge about the genetic mechanisms for biological shape has far-reaching implications for a range spectrum of scientific disciplines including anthropology, agriculture, developmental biology, evolution and biomedicine. Results We derived a statistical model for mapping specific genes or quantitative trait loci (QTLs that control morphological shape. The model was formulated within the mixture framework, in which different types of shape are thought to result from genotypic discrepancies at a QTL. The EM algorithm was implemented to estimate QTL genotype-specific shapes based on a shape correspondence analysis. Computer simulation was used to investigate the statistical property of the model. Conclusion By identifying specific QTLs for morphological shape, the model developed will help to ask, disseminate and address many major integrative biological and genetic questions and challenges in the genetic control of biological shape and function.

Limiting processes in non-equilibrium classical statistical mechanics

International Nuclear Information System (INIS)

Jancel, R.

1983-01-01

After a recall of the basic principles of the statistical mechanics, the results of ergodic theory, the transient at the thermodynamic limit and his link with the transport theory near the equilibrium are analyzed. The fundamental problems put by the description of non-equilibrium macroscopic systems are investigated and the kinetic methods are stated. The problems of the non-equilibrium statistical mechanics are analyzed: irreversibility and coarse-graining, macroscopic variables and kinetic description, autonomous reduced descriptions, limit processes, BBGKY hierarchy, limit theorems [fr

Multiparticle quantum mechanics obeying fractional statistics

International Nuclear Information System (INIS)

Wu, Y.

1984-01-01

We obtain the rule governing many-body wave functions for particles obeying fractional statistics in two (space) dimensions. It generalizes and continuously interpolates the usual symmetrization and antisymmetrization. Quantum mechanics of more than two particles is discussed and some new features are found

Bayesian approach to inverse statistical mechanics

Science.gov (United States)

Habeck, Michael

2014-05-01

Inverse statistical mechanics aims to determine particle interactions from ensemble properties. This article looks at this inverse problem from a Bayesian perspective and discusses several statistical estimators to solve it. In addition, a sequential Monte Carlo algorithm is proposed that draws the interaction parameters from their posterior probability distribution. The posterior probability involves an intractable partition function that is estimated along with the interactions. The method is illustrated for inverse problems of varying complexity, including the estimation of a temperature, the inverse Ising problem, maximum entropy fitting, and the reconstruction of molecular interaction potentials.

Nonextensive statistical mechanics and high energy physics

Directory of Open Access Journals (Sweden)

Tsallis Constantino

2014-04-01

Full Text Available The use of the celebrated Boltzmann-Gibbs entropy and statistical mechanics is justified for ergodic-like systems. In contrast, complex systems typically require more powerful theories. We will provide a brief introduction to nonadditive entropies (characterized by indices like q, which, in the q → 1 limit, recovers the standard Boltzmann-Gibbs entropy and associated nonextensive statistical mechanics. We then present somerecent applications to systems such as high-energy collisions, black holes and others. In addition to that, we clarify and illustrate the neat distinction that exists between Lévy distributions and q-exponential ones, a point which occasionally causes some confusion in the literature, very particularly in the LHC literature

Statistical mechanical lattice model of the dual-peak electrocaloric effect in ferroelectric relaxors and the role of pressure

International Nuclear Information System (INIS)

Dunne, Lawrence J; Axelsson, Anna-Karin; Alford, Neil McN; Valant, Matjaz; Manos, George

2011-01-01

Despite considerable effort, the microscopic origin of the electrocaloric (EC) effect in ferroelectric relaxors is still intensely discussed. Ferroelectric relaxors typically display a dual-peak EC effect, whose origin is uncertain. Here we present an exact statistical mechanical matrix treatment of a lattice model of polar nanoregions forming in a neutral background and use this approach to study the characteristics of the EC effect in ferroelectric relaxors under varying electric field and pressure. The dual peaks seen in the EC properties of ferroelectric relaxors are due to the formation and ordering of polar nanoregions. The model predicts significant enhancement of the EC temperature rise with pressure which may have some contribution to the giant EC effect.

Statistical Property and Model for the Inter-Event Time of Terrorism Attacks

Science.gov (United States)

Zhu, Jun-Fang; Han, Xiao-Pu; Wang, Bing-Hong

2010-06-01

The inter-event time of terrorism attack events is investigated by empirical data and model analysis. Empirical evidence shows that it follows a scale-free property. In order to understand the dynamic mechanism of such a statistical feature, an opinion dynamic model with a memory effect is proposed on a two-dimensional lattice network. The model mainly highlights the role of individual social conformity and self-affirmation psychology. An attack event occurs when the order parameter indicating the strength of public opposition opinion is smaller than a critical value. Ultimately, the model can reproduce the same statistical property as the empirical data and gives a good understanding for the possible dynamic mechanism of terrorism attacks.

Sampling, Probability Models and Statistical Reasoning Statistical

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 5. Sampling, Probability Models and Statistical Reasoning Statistical Inference. Mohan Delampady V R Padmawar. General Article Volume 1 Issue 5 May 1996 pp 49-58 ...

Renyi statistics in equilibrium statistical mechanics

International Nuclear Information System (INIS)

Parvan, A.S.; Biro, T.S.

2010-01-01

The Renyi statistics in the canonical and microcanonical ensembles is examined both in general and in particular for the ideal gas. In the microcanonical ensemble the Renyi statistics is equivalent to the Boltzmann-Gibbs statistics. By the exact analytical results for the ideal gas, it is shown that in the canonical ensemble, taking the thermodynamic limit, the Renyi statistics is also equivalent to the Boltzmann-Gibbs statistics. Furthermore it satisfies the requirements of the equilibrium thermodynamics, i.e. the thermodynamical potential of the statistical ensemble is a homogeneous function of first degree of its extensive variables of state. We conclude that the Renyi statistics arrives at the same thermodynamical relations, as those stemming from the Boltzmann-Gibbs statistics in this limit.

Statistical state dynamics-based analysis of the physical mechanisms sustaining and regulating turbulence in Couette flow

Science.gov (United States)

Farrell, Brian F.; Ioannou, Petros J.

2017-08-01

This paper describes a study of the self-sustaining process in wall turbulence. The study is based on a second order statistical state dynamics model of Couette flow in which the state variables are the streamwise mean flow (first cumulant) and perturbation covariance (second cumulant). This statistical state dynamics model is closed by either setting the third cumulant to zero or by replacing it with a stochastic parametrization. Statistical state dynamics models with this form are referred to as S3T models. S3T models have been shown to self-sustain turbulence with a mean flow and second order perturbation structure similar to that obtained by direct numerical simulation of the equations of motion. The use of a statistical state dynamics model to study the physical mechanisms underlying turbulence has important advantages over the traditional approach of studying the dynamics of individual realizations of turbulence. One advantage is that the analytical structure of S3T statistical state dynamics models isolates the interaction between the mean flow and the perturbation components of the turbulence. Isolation of the interaction between these components reveals how this interaction underlies both the maintenance of the turbulence variance by transfer of energy from the externally driven flow to the perturbation components as well as the enforcement of the observed statistical mean turbulent state by feedback regulation between the mean and perturbation fields. Another advantage of studying turbulence using statistical state dynamics models of S3T form is that the analytical structure of S3T turbulence can be completely characterized. For example, the perturbation component of turbulence in the S3T system is demonstrably maintained by a parametric perturbation growth mechanism in which fluctuation of the mean flow maintains the perturbation field which in turn maintains the mean flow fluctuations in a synergistic interaction. Furthermore, the equilibrium

Mathematical methods in quantum and statistical mechanics

International Nuclear Information System (INIS)

Fishman, L.

1977-01-01

The mathematical structure and closed-form solutions pertaining to several physical problems in quantum and statistical mechanics are examined in some detail. The J-matrix method, introduced previously for s-wave scattering and based upon well-established Hilbert Space theory and related generalized integral transformation techniques, is extended to treat the lth partial wave kinetic energy and Coulomb Hamiltonians within the context of square integrable (L 2 ), Laguerre (Slater), and oscillator (Gaussian) basis sets. The theory of relaxation in statistical mechanics within the context of the theory of linear integro-differential equations of the Master Equation type and their corresponding Markov processes is examined. Several topics of a mathematical nature concerning various computational aspects of the L 2 approach to quantum scattering theory are discussed

Introductory statistical mechanics for electron storage rings

International Nuclear Information System (INIS)

Jowett, J.M.

1986-07-01

These lectures introduce the beam dynamics of electron-positron storage rings with particular emphasis on the effects due to synchrotron radiation. They differ from most other introductions in their systematic use of the physical principles and mathematical techniques of the non-equilibrium statistical mechanics of fluctuating dynamical systems. A self-contained exposition of the necessary topics from this field is included. Throughout the development, a Hamiltonian description of the effects of the externally applied fields is maintained in order to preserve the links with other lectures on beam dynamics and to show clearly the extent to which electron dynamics in non-Hamiltonian. The statistical mechanical framework is extended to a discussion of the conceptual foundations of the treatment of collective effects through the Vlasov equation

Statistical algebraic approach to quantum mechanics

International Nuclear Information System (INIS)

Slavnov, D.A.

2001-01-01

The scheme for plotting the quantum theory with application of the statistical algebraic approach is proposed. The noncommutative algebra elements (observed ones) and nonlinear functionals on this algebra (physical state) are used as the primary constituents. The latter ones are associated with the single-unit measurement results. Certain physical state groups are proposed to consider as quantum states of the standard quantum mechanics. It is shown that the mathematical apparatus of the standard quantum mechanics may be reproduced in such a scheme in full volume [ru

Nonextensive statistical mechanics of ionic solutions

International Nuclear Information System (INIS)

Varela, L.M.; Carrete, J.; Munoz-Sola, R.; Rodriguez, J.R.; Gallego, J.

2007-01-01

Classical mean-field Poisson-Boltzmann theory of ionic solutions is revisited in the theoretical framework of nonextensive Tsallis statistics. The nonextensive equivalent of Poisson-Boltzmann equation is formulated revisiting the statistical mechanics of liquids and the Debye-Hueckel framework is shown to be valid for highly diluted solutions even under circumstances where nonextensive thermostatistics must be applied. The lowest order corrections associated to nonadditive effects are identified for both symmetric and asymmetric electrolytes and the behavior of the average electrostatic potential in a homogeneous system is analytically and numerically analyzed for various values of the complexity measurement nonextensive parameter q

To the problem of the statistical basis of evaluation of the mechanical safety factor

International Nuclear Information System (INIS)

Tsyganov, S.V.

2009-01-01

The methodology applied for the safety factor assessment of the WWER fuel cycles uses methods and terms of statistics. Value of the factor is calculated on the basis of estimation of probability to meet predefined limits. Such approach demands the special attention to the statistical properties of parameters of interest. Considering the mechanical constituents of the engineering factor it is assumed uncertainty factors of safety parameters are stochastic values. It characterized by probabilistic distributions that can be unknown. Traditionally in the safety factor assessment process the unknown parameters are estimated from the conservative points of view. This paper analyses how the refinement of the factors distribution parameters is important for the assessment of the mechanical safety factor. For the analysis the statistical approach is applied for modelling of different type of factor probabilistic distributions. It is shown the significant influence of the shape and parameters of distributions for some factors on the value of mechanical safety factor. (Authors)

To the problem of the statistical basis of evaluation of the mechanical safety factor

International Nuclear Information System (INIS)

Tsyganov, S.

2009-01-01

The methodology applied for the safety factor assessment of the VVER fuel cycles uses methods and terms of statistics. Value of the factor is calculated on the basis of estimation of probability to meet predefined limits. Such approach demands the special attention to the statistical properties of parameters of interest. Considering the mechanical constituents of the engineering factor it is assumed uncertainty factors of safety parameters are stochastic values. It characterized by probabilistic distributions that can be unknown. Traditionally in the safety factor assessment process the unknown parameters are estimated from the conservative points of view. This paper analyses how the refinement of the factors distribution parameters is important for the assessment of the mechanical safety factor. For the analysis the statistical approach is applied for modelling of different type of factor probabilistic distributions. It is shown the significant influence of the shape and parameters of distributions for some factors on the value of mechanical safety factor. (author)

Statistical-mechanical formulation of Lyapunov exponents

International Nuclear Information System (INIS)

Tanase-Nicola, Sorin; Kurchan, Jorge

2003-01-01

We show how the Lyapunov exponents of a dynamic system can, in general, be expressed in terms of the free energy of a (non-Hermitian) quantum many-body problem. This puts their study as a problem of statistical mechanics, whose intuitive concepts and techniques of approximation can hence be borrowed

Statistical Model of Extreme Shear

DEFF Research Database (Denmark)

Larsen, Gunner Chr.; Hansen, Kurt Schaldemose

2004-01-01

In order to continue cost-optimisation of modern large wind turbines, it is important to continously increase the knowledge on wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... by a model that, on a statistically consistent basis, describe the most likely spatial shape of an extreme wind shear event. Predictions from the model have been compared with results from an extreme value data analysis, based on a large number of high-sampled full-scale time series measurements...... are consistent, given the inevitabel uncertainties associated with model as well as with the extreme value data analysis. Keywords: Statistical model, extreme wind conditions, statistical analysis, turbulence, wind loading, statistical analysis, turbulence, wind loading, wind shear, wind turbines....

Using statistical compatibility to derive advanced probabilistic fatigue models

Czech Academy of Sciences Publication Activity Database

Fernández-Canteli, A.; Castillo, E.; López-Aenlle, M.; Seitl, Stanislav

2010-01-01

Roč. 2, č. 1 (2010), s. 1131-1140 E-ISSN 1877-7058. [Fatigue 2010. Praha, 06.06.2010-11.06.2010] Institutional research plan: CEZ:AV0Z20410507 Keywords : Fatigue models * Statistical compatibility * Functional equations Subject RIV: JL - Materials Fatigue, Friction Mechanics

Statistical mechanics of lattice systems a concrete mathematical introduction

CERN Document Server

Friedli, Sacha

2017-01-01

This motivating textbook gives a friendly, rigorous introduction to fundamental concepts in equilibrium statistical mechanics, covering a selection of specific models, including the Curie–Weiss and Ising models, the Gaussian free field, O(n) models, and models with Kać interactions. Using classical concepts such as Gibbs measures, pressure, free energy, and entropy, the book exposes the main features of the classical description of large systems in equilibrium, in particular the central problem of phase transitions. It treats such important topics as the Peierls argument, the Dobrushin uniqueness, Mermin–Wagner and Lee–Yang theorems, and develops from scratch such workhorses as correlation inequalities, the cluster expansion, Pirogov–Sinai Theory, and reflection positivity. Written as a self-contained course for advanced undergraduate or beginning graduate students, the detailed explanations, large collection of exercises (with solutions), and appendix of mathematical results and concepts also make i...

Statistical shear lag model - unraveling the size effect in hierarchical composites.

Science.gov (United States)

Wei, Xiaoding; Filleter, Tobin; Espinosa, Horacio D

2015-05-01

Numerous experimental and computational studies have established that the hierarchical structures encountered in natural materials, such as the brick-and-mortar structure observed in sea shells, are essential for achieving defect tolerance. Due to this hierarchy, the mechanical properties of natural materials have a different size dependence compared to that of typical engineered materials. This study aimed to explore size effects on the strength of bio-inspired staggered hierarchical composites and to define the influence of the geometry of constituents in their outstanding defect tolerance capability. A statistical shear lag model is derived by extending the classical shear lag model to account for the statistics of the constituents' strength. A general solution emerges from rigorous mathematical derivations, unifying the various empirical formulations for the fundamental link length used in previous statistical models. The model shows that the staggered arrangement of constituents grants composites a unique size effect on mechanical strength in contrast to homogenous continuous materials. The model is applied to hierarchical yarns consisting of double-walled carbon nanotube bundles to assess its predictive capabilities for novel synthetic materials. Interestingly, the model predicts that yarn gauge length does not significantly influence the yarn strength, in close agreement with experimental observations. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Generalized bond percolation and statistical mechanics

International Nuclear Information System (INIS)

Tsallis, C.

1978-05-01

A generalization of traditional bond percolation is performed, in the sens that bonds have now the possibility of partially transmitting the information (a fact which leads to the concept of 'fidelity' of the bond), and also in the sens that, besides the normal tendency to equiprobability, the bonds are allowed to substantially change the information. Furthermore the fidelity is allowed, to become an aleatory variable, and the operational rules concerning the associated distribution laws are determined. Thermally quenched random bonds and the whole body of Statistical Mechanics become particular cases of this formalism, which is in general adapted to the treatment of all problems whose main characteristic is to preserve a part of the information through a long path or array (critical phenomena, regime changements, thermal random models, etc). Operationally it provides a quick method for the calculation of the equivalent probability of complex clusters within the traditional bond percolation problem [pt

A reductionist perspective on quantum statistical mechanics: Coarse-graining of path integrals.

Science.gov (United States)

Sinitskiy, Anton V; Voth, Gregory A

2015-09-07

Computational modeling of the condensed phase based on classical statistical mechanics has been rapidly developing over the last few decades and has yielded important information on various systems containing up to millions of atoms. However, if a system of interest contains important quantum effects, well-developed classical techniques cannot be used. One way of treating finite temperature quantum systems at equilibrium has been based on Feynman's imaginary time path integral approach and the ensuing quantum-classical isomorphism. This isomorphism is exact only in the limit of infinitely many classical quasiparticles representing each physical quantum particle. In this work, we present a reductionist perspective on this problem based on the emerging methodology of coarse-graining. This perspective allows for the representations of one quantum particle with only two classical-like quasiparticles and their conjugate momenta. One of these coupled quasiparticles is the centroid particle of the quantum path integral quasiparticle distribution. Only this quasiparticle feels the potential energy function. The other quasiparticle directly provides the observable averages of quantum mechanical operators. The theory offers a simplified perspective on quantum statistical mechanics, revealing its most reductionist connection to classical statistical physics. By doing so, it can facilitate a simpler representation of certain quantum effects in complex molecular environments.

A reductionist perspective on quantum statistical mechanics: Coarse-graining of path integrals

International Nuclear Information System (INIS)

Sinitskiy, Anton V.; Voth, Gregory A.

2015-01-01

Computational modeling of the condensed phase based on classical statistical mechanics has been rapidly developing over the last few decades and has yielded important information on various systems containing up to millions of atoms. However, if a system of interest contains important quantum effects, well-developed classical techniques cannot be used. One way of treating finite temperature quantum systems at equilibrium has been based on Feynman’s imaginary time path integral approach and the ensuing quantum-classical isomorphism. This isomorphism is exact only in the limit of infinitely many classical quasiparticles representing each physical quantum particle. In this work, we present a reductionist perspective on this problem based on the emerging methodology of coarse-graining. This perspective allows for the representations of one quantum particle with only two classical-like quasiparticles and their conjugate momenta. One of these coupled quasiparticles is the centroid particle of the quantum path integral quasiparticle distribution. Only this quasiparticle feels the potential energy function. The other quasiparticle directly provides the observable averages of quantum mechanical operators. The theory offers a simplified perspective on quantum statistical mechanics, revealing its most reductionist connection to classical statistical physics. By doing so, it can facilitate a simpler representation of certain quantum effects in complex molecular environments

Probabilistic cellular automata: Some statistical mechanical considerations

International Nuclear Information System (INIS)

Lebowitz, J.L.; Maes, C.; Speer, E.R.

1990-01-01

Spin systems evolving in continuous or discrete time under the action of stochastic dynamics are used to model phenomena as diverse as the structure of alloys and the functioning of neural networks. While in some cases the dynamics are secondary, designed to produce a specific stationary measure whose properties one is interested in studying, there are other cases in which the only available information is the dynamical rule. Prime examples of the former are computer simulations, via Glauber dynamics, of equilibrium Gibbs measures with a specified interaction potential. Examples of the latter include various types of majority rule dynamics used as models for pattern recognition and for error-tolerant computations. The present note discusses ways in which techniques found useful in equilibrium statistical mechanics can be applied to a particular class of models of the latter types. These are cellular automata with noise: systems in which the spins are updated stochastically at integer times, simultaneously at all sites of some regular lattice. These models were first investigated in detail in the Soviet literature of the late sixties and early seventies. They are now generally referred to as Stochastic or Probabilistic Cellular Automata (PCA), and may be considered to include deterministic automata (CA) as special limits. 16 refs., 3 figs

Science Academies' Refresher Course in Statistical Mechanics

Indian Academy of Sciences (India)

2018-02-27

Feb 27, 2018 ... Post Graduate and Research Department of Physics. Bishop Moore ... The Course will cover the basic and advanced topics of Statistical. Mechanics ... Courses of good standing for promotion, vide notification. F3-1/2009 ...

Quantum mechanics as classical statistical mechanics with an ontic extension and an epistemic restriction.

Science.gov (United States)

Budiyono, Agung; Rohrlich, Daniel

2017-11-03

Where does quantum mechanics part ways with classical mechanics? How does quantum randomness differ fundamentally from classical randomness? We cannot fully explain how the theories differ until we can derive them within a single axiomatic framework, allowing an unambiguous account of how one theory is the limit of the other. Here we derive non-relativistic quantum mechanics and classical statistical mechanics within a common framework. The common axioms include conservation of average energy and conservation of probability current. But two axioms distinguish quantum mechanics from classical statistical mechanics: an "ontic extension" defines a nonseparable (global) random variable that generates physical correlations, and an "epistemic restriction" constrains allowed phase space distributions. The ontic extension and epistemic restriction, with strength on the order of Planck's constant, imply quantum entanglement and uncertainty relations. This framework suggests that the wave function is epistemic, yet it does not provide an ontic dynamics for individual systems.

Principles of classical statistical mechanics: A perspective from the notion of complementarity

International Nuclear Information System (INIS)

Velazquez Abad, Luisberis

2012-01-01

Quantum mechanics and classical statistical mechanics are two physical theories that share several analogies in their mathematical apparatus and physical foundations. In particular, classical statistical mechanics is hallmarked by the complementarity between two descriptions that are unified in thermodynamics: (i) the parametrization of the system macrostate in terms of mechanical macroscopic observablesI=(I i ), and (ii) the dynamical description that explains the evolution of a system towards the thermodynamic equilibrium. As expected, such a complementarity is related to the uncertainty relations of classical statistical mechanics ΔI i Δη i ≥k. Here, k is the Boltzmann constant, η i =∂S(I|θ)/∂I i are the restituting generalized forces derived from the entropy S(I|θ) of a closed system, which is found in an equilibrium situation driven by certain control parameters θ=(θ α ). These arguments constitute the central ingredients of a reformulation of classical statistical mechanics from the notion of complementarity. In this new framework, Einstein postulate of classical fluctuation theory dp(I|θ)∼exp[S(I|θ)/k]dI appears as the correspondence principle between classical statistical mechanics and thermodynamics in the limit k→0, while the existence of uncertainty relations can be associated with the non-commuting character of certain operators. - Highlights: ► There exists a direct analogy between quantum and classical statistical mechanics. ► Statistical form of Le Chatellier principle leads to the uncertainty principle. ► Einstein postulate is simply the correspondence principle. ► Complementary quantities are associated with non-commuting operators.

Portfolio selection problem with liquidity constraints under non-extensive statistical mechanics

International Nuclear Information System (INIS)

Zhao, Pan; Xiao, Qingxian

2016-01-01

In this study, we consider the optimal portfolio selection problem with liquidity limits. A portfolio selection model is proposed in which the risky asset price is driven by the process based on non-extensive statistical mechanics instead of the classic Wiener process. Using dynamic programming and Lagrange multiplier methods, we obtain the optimal policy and value function. Moreover, the numerical results indicate that this model is considerably different from the model based on the classic Wiener process, the optimal strategy is affected by the non-extensive parameter q, the increase in the investment in the risky asset is faster at a larger parameter q and the increase in wealth is similar.

Statistical mechanics for a system with imperfections: pt. 1

International Nuclear Information System (INIS)

Choh, S.T.; Kahng, W.H.; Um, C.I.

1982-01-01

Statistical mechanics is extended to treat a system where parts of the Hamiltonian are randomly varying. As the starting point of the theory, the statistical correlation among energy levels is neglected, allowing use of the central limit theorem of the probability theory. (Author)

Exclusion statistics and integrable models

International Nuclear Information System (INIS)

Mashkevich, S.

1998-01-01

The definition of exclusion statistics that was given by Haldane admits a 'statistical interaction' between distinguishable particles (multispecies statistics). For such statistics, thermodynamic quantities can be evaluated exactly; explicit expressions are presented here for cluster coefficients. Furthermore, single-species exclusion statistics is realized in one-dimensional integrable models of the Calogero-Sutherland type. The interesting questions of generalizing this correspondence to the higher-dimensional and the multispecies cases remain essentially open; however, our results provide some hints as to searches for the models in question

Statistical mechanics of the fashion game on random networks

International Nuclear Information System (INIS)

Sun, YiFan

2016-01-01

A model of fashion on networks is studied. This model consists of two groups of agents that are located on a network and have opposite viewpoints towards being fashionable: behaving consistently with either the majority or the minority of adjacent agents. Checking whether the fashion game has a pure Nash equilibrium (pure NE) is a non-deterministic polynomial complete problem. Using replica-symmetric mean field theory, the largest proportion of satisfied agents and the region where at least one pure NE should exist are determined for several types of random networks. Furthermore, a quantitive analysis of the asynchronous best response dynamics yields the phase diagram of existence and detectability of pure NE in the fashion game on some random networks. (paper: classical statistical mechanics, equilibrium and non-equilibrium).

An introduction to statistical mechanics and thermodynamics

CERN Document Server

Swendsen, Robert H

2012-01-01

This text presents the two complementary aspects of thermal physics as an integrated theory of the properties of matter. Conceptual understanding is promoted by thorough development of basic concepts. In contrast to many texts, statistical mechanics, including discussion of the required probability theory, is presented first. This provides a statistical foundation for the concept of entropy, which is central to thermal physics. A unique feature of the book is the development ofentropy based on Boltzmann's 1877 definition; this avoids contradictions or ad hoc corrections found in other texts. D

Statistical mechanics of violent relaxation

International Nuclear Information System (INIS)

Shu, F.H.

1978-01-01

We reexamine the foundations of Lynden-Bell's statistical mechanical discussion of violent relaxation in collisionless stellar systems. We argue that Lynden-Bell's formulation in terms of a continuum description introduces unnecessary complications, and we consider a more conventional formulation in terms of particles. We then find the exclusion principle discovered by Lynden-Bell to be quantitatively important only at phase densities where two-body encounters are no longer negligible. Since the edynamical basis for the exclusion principle vanishes in such cases anyway, Lynden-Bell statistics always reduces in practice to Maxwell-Boltzmann statistics when applied to stellar systems. Lynden-Bell also found the equilibrium distribution function generally to be a sum of Maxwellians with velocity dispersions dependent on the phase density at star formation. We show that this difficulty vanishes in the particulate description for an encounterless stellar system as long as stars of different masses are initially well mixed in phase space. Our methods also demonstrate the equivalence between Gibbs's formalism which uses the microcanonical ensemble and Boltzmann's formalism which uses a coarse-grained continuum description. In addition, we clarify the concept of irreversible behavior on a macroscopic scale for an encounterless stellar system. Finally, we comment on the use of unusual macroscopic constraints to simulate the effects of incomplete relaxation

The road to Maxwell's demon conceptual foundations of statistical mechanics

CERN Document Server

Hemmo, Meir

2012-01-01

Time asymmetric phenomena are successfully predicted by statistical mechanics. Yet the foundations of this theory are surprisingly shaky. Its explanation for the ease of mixing milk with coffee is incomplete, and even implies that un-mixing them should be just as easy. In this book the authors develop a new conceptual foundation for statistical mechanics that addresses this difficulty. Explaining the notions of macrostates, probability, measurement, memory, and the arrow of time in statistical mechanics, they reach the startling conclusion that Maxwell's Demon, the famous perpetuum mobile, is consistent with the fundamental physical laws. Mathematical treatments are avoided where possible, and instead the authors use novel diagrams to illustrate the text. This is a fascinating book for graduate students and researchers interested in the foundations and philosophy of physics.

Statistical mechanics of systems of unbounded spins

Energy Technology Data Exchange (ETDEWEB)

Lebowitz, J L [Yeshiva Univ., New York (USA). Belfer Graduate School of Science; Presutti, E [L' Aquila Univ. (Italy). Istituto di Matematica

1976-11-01

We develop the statistical mechanics of unbounded n-component spin systems interacting via potentials which are superstable and strongly tempered. The uniqueness of the equilibrium state is then proven for one component ferromagnetic spins whose free energy is differentiable with respect to the magnetic field.

Statistical methods in the mechanical design of fuel assemblies

Energy Technology Data Exchange (ETDEWEB)

Radsak, C.; Streit, D.; Muench, C.J. [AREVA NP GmbH, Erlangen (Germany)

2013-07-01

The mechanical design of a fuel assembly is still being mainly performed in a de terministic way. This conservative approach is however not suitable to provide a realistic quantification of the design margins with respect to licensing criter ia for more and more demanding operating conditions (power upgrades, burnup increase,..). This quantification can be provided by statistical methods utilizing all available information (e.g. from manufacturing, experience feedback etc.) of the topic under consideration. During optimization e.g. of the holddown system certain objectives in the mechanical design of a fuel assembly (FA) can contradict each other, such as sufficient holddown forces enough to prevent fuel assembly lift-off and reducing the holddown forces to minimize axial loads on the fuel assembly structure to ensure no negative effect on the control rod movement.By u sing a statistical method the fuel assembly design can be optimized much better with respect to these objectives than it would be possible based on a deterministic approach. This leads to a more realistic assessment and safer way of operating fuel assemblies. Statistical models are defined on the one hand by the quanti le that has to be maintained concerning the design limit requirements (e.g. one FA quantile) and on the other hand by the confidence level which has to be met. Using the above example of the holddown force, a feasible quantile can be define d based on the requirement that less than one fuel assembly (quantile > 192/19 3 [%] = 99.5 %) in the core violates the holddown force limit w ith a confidence of 95%. (orig.)

Statistical modelling with quantile functions

CERN Document Server

Gilchrist, Warren

2000-01-01

Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.Statistical Modelling with Quantile Functions adds a new dimension to the practice of stati...

A Statistical Programme Assignment Model

DEFF Research Database (Denmark)

Rosholm, Michael; Staghøj, Jonas; Svarer, Michael

When treatment effects of active labour market programmes are heterogeneous in an observable way  across the population, the allocation of the unemployed into different programmes becomes a particularly  important issue. In this paper, we present a statistical model designed to improve the present...... duration of unemployment spells may result if a statistical programme assignment model is introduced. We discuss several issues regarding the  plementation of such a system, especially the interplay between the statistical model and  case workers....

Fluctuations of physical values in statistical mechanics

International Nuclear Information System (INIS)

Zaripov, R.G.

1999-01-01

The new matrix inequalities for the boundary of measurement accuracy of physical values in the ensemble of quantum systems were obtained. The multidimensional thermodynamical parameter measurement is estimated. The matrix inequalities obtained are quantum analogs of the Cramer-Rao information inequalities in mathematical statistics. The quantity of information in quantum mechanical measurement, connected with the boundaries of jointly measurable values in one macroscopic experiment was determined. The lower boundary of the variance of estimation of multidimensional quantum mechanical parameter was found. (author)

Fundamental link between system theory and statistical mechanics

International Nuclear Information System (INIS)

Atmanspacher, H.; Scheingraber, H.

1987-01-01

A fundamental link between system theory and statistical mechanics has been found to be established by the Kolmogorov entropy. By this quantity the temporal evolution of dynamical systems can be classified into regular, chaotic, and stochastic processes. Since K represents a measure for the internal information creation rate of dynamical systems, it provides an approach to irreversibility. The formal relationship to statistical mechanics is derived by means of an operator formalism originally introduced by Prigogine. For a Liouville operator L and an information operator M tilde acting on a distribution in phase space, it is shown that i[L, M tilde] = KI (I = identity operator). As a first consequence of this equivalence, a relation is obtained between the chaotic correlation time of a system and Prigogine's concept of a finite duration of presence. Finally, the existence of chaos in quantum systems is discussed with respect to the existence of a quantum mechanical time operator

Statistical mechanics and the physics of fluids

CERN Document Server

Tosi, Mario

This volume collects the lecture notes of a course on statistical mechanics, held at Scuola Normale Superiore di Pisa for third-to-fifth year students in physics and chemistry. Three main themes are covered in the book. The first part gives a compact presentation of the foundations of statistical mechanics and their connections with thermodynamics. Applications to ideal gases of material particles and of excitation quanta are followed by a brief introduction to a real classical gas and to a weakly coupled classical plasma, and by a broad overview on the three states of matter.The second part is devoted to fluctuations around equilibrium and their correlations. Coverage of liquid structure and critical phenomena is followed by a discussion of irreversible processes as exemplified by diffusive motions and by the dynamics of density and heat fluctuations. Finally, the third part is an introduction to some advanced themes: supercooling and the glassy state, non-Newtonian fluids including polymers and liquid cryst...

On the statistical-mechanical meaning of the Bousso bound

International Nuclear Information System (INIS)

Pesci, Alessandro

2008-01-01

The Bousso entropy bound, in its generalized form, is investigated for the case of perfect fluids at local thermodynamic equilibrium and evidence is found that the bound is satisfied if and only if a certain local thermodynamic property holds, emerging when the attempt is made to apply the bound to thin layers of matter. This property consists of the existence of an ultimate lower limit l* to the thickness of the slices for which a statistical-mechanical description is viable, depending l* on the thermodynamical variables which define the state of the system locally. This limiting scale, found to be in general much larger than the Planck scale (so that no Planck scale physics must be necessarily invoked to justify it), appears not related to gravity and this suggests that the generalized entropy bound is likely to be rooted on conventional flat-spacetime statistical mechanics, with the maximum admitted entropy being however actually determined also by gravity. Some examples of ideal fluids are considered in order to identify the mechanisms which can set a lower limit to the statistical-mechanical description and these systems are found to respect the lower limiting scale l*. The photon gas, in particular, appears to seemingly saturate this limiting scale and the consequence is drawn that for systems consisting of a single slice of a photon gas with thickness l*, the generalized Bousso bound is saturated. It is argued that this seems to open the way to a peculiar understanding of black hole entropy: if an entropy can meaningfully (i.e. with a second law) be assigned to a black hole, the value A/4 for it (where A is the area of the black hole) is required simply by (conventional) statistical mechanics coupled to general relativity

Statistical mechanics and the foundations of thermodynamics

International Nuclear Information System (INIS)

Loef, A.M.

1979-01-01

An introduction to classical statistical mechanics and its relation to thermodynamics is presented. Emphasis is put on getting a detailed and logical presentation of the foundations of thermodynamics based on the maximum entropy principles which govern the values taken by macroscopic variables according to the laws of large numbers

The statistical mechanics of the classical two-dimensional Coulomb gas is exactly solved

International Nuclear Information System (INIS)

Samaj, L

2003-01-01

The model under consideration is a classical 2D Coulomb gas of pointlike positive and negative unit charges, interacting via a logarithmic potential. In the whole stability range of temperatures, the equilibrium statistical mechanics of this fluid model is exactly solvable via an equivalence with the integrable 2D sine-Gordon field theory. The exact solution includes the bulk thermodynamics, special cases of the surface thermodynamics and the large-distance asymptotic behaviour of the two-body correlation functions

Computational Modeling of Statistical Learning: Effects of Transitional Probability versus Frequency and Links to Word Learning

Science.gov (United States)

Mirman, Daniel; Estes, Katharine Graf; Magnuson, James S.

2010-01-01

Statistical learning mechanisms play an important role in theories of language acquisition and processing. Recurrent neural network models have provided important insights into how these mechanisms might operate. We examined whether such networks capture two key findings in human statistical learning. In Simulation 1, a simple recurrent network…

A statistical mechanical model for equilibrium ionization

International Nuclear Information System (INIS)

Macris, N.; Martin, P.A.; Pule, J.

1990-01-01

A quantum electron interacts with a classical gas of hard spheres and is in thermal equilibrium with it. The interaction is attractive and the electron can form a bound state with the classical particles. It is rigorously shown that in a well defined low density and low temperature limit, the ionization probability for the electron tends to the value predicted by the Saha formula for thermal ionization. In this regime, the electron is found to be in a statistical mixture of a bound and a free state. (orig.)

Stability and equilibrium in quantum statistical mechanics

International Nuclear Information System (INIS)

Kastler, Daniel.

1975-01-01

A derivation of the Gibbs Ansatz, base of the equilibrium statistical mechanics is provided from a stability requirements, in technical connection with the harmonic analysis of non-commutative dynamical systems. By the same token a relation is established between stability and the positivity of Hamiltonian in the zero temperature case [fr

Statistical mechanics of neocortical interactions: A scaling paradigm applied to electroencephalography

Science.gov (United States)

Ingber, Lester

1991-09-01

A series of papers has developed a statistical mechanics of neocortical interactions (SMNI), deriving aggregate behavior of experimentally observed columns of neurons from statistical electrical-chemical properties of synaptic interactions. While not useful to yield insights at the single-neuron level, SMNI has demonstrated its capability in describing large-scale properties of short-term memory and electroencephalographic (EEG) systematics. The necessity of including nonlinear and stochastic structures in this development has been stressed. In this paper, a more stringent test is placed on SMNI: The algebraic and numerical algorithms previously developed in this and similar systems are brought to bear to fit large sets of EEG and evoked-potential data being collected to investigate genetic predispositions to alcoholism and to extract brain ``signatures'' of short-term memory. Using the numerical algorithm of very fast simulated reannealing, it is demonstrated that SMNI can indeed fit these data within experimentally observed ranges of its underlying neuronal-synaptic parameters, and the quantitative modeling results are used to examine physical neocortical mechanisms to discriminate high-risk and low-risk populations genetically predisposed to alcoholism. Since this study is a control to span relatively long time epochs, similar to earlier attempts to establish such correlations, this discrimination is inconclusive because of other neuronal activity which can mask such effects. However, the SMNI model is shown to be consistent with EEG data during selective attention tasks and with neocortical mechanisms describing short-term memory previously published using this approach. This paper explicitly identifies similar nonlinear stochastic mechanisms of interaction at the microscopic-neuronal, mesoscopic-columnar, and macroscopic-regional scales of neocortical interactions. These results give strong quantitative support for an accurate intuitive picture, portraying

Hadronic equation of state in the statistical bootstrap model and linear graph theory

International Nuclear Information System (INIS)

Fre, P.; Page, R.

1976-01-01

Taking a statistical mechanical point og view, the statistical bootstrap model is discussed and, from a critical analysis of the bootstrap volume comcept, it is reached a physical ipothesis, which leads immediately to the hadronic equation of state provided by the bootstrap integral equation. In this context also the connection between the statistical bootstrap and the linear graph theory approach to interacting gases is analyzed

Statistical models for expert judgement and wear prediction

International Nuclear Information System (INIS)

Pulkkinen, U.

1994-01-01

This thesis studies the statistical analysis of expert judgements and prediction of wear. The point of view adopted is the one of information theory and Bayesian statistics. A general Bayesian framework for analyzing both the expert judgements and wear prediction is presented. Information theoretic interpretations are given for some averaging techniques used in the determination of consensus distributions. Further, information theoretic models are compared with a Bayesian model. The general Bayesian framework is then applied in analyzing expert judgements based on ordinal comparisons. In this context, the value of information lost in the ordinal comparison process is analyzed by applying decision theoretic concepts. As a generalization of the Bayesian framework, stochastic filtering models for wear prediction are formulated. These models utilize the information from condition monitoring measurements in updating the residual life distribution of mechanical components. Finally, the application of stochastic control models in optimizing operational strategies for inspected components are studied. Monte-Carlo simulation methods, such as the Gibbs sampler and the stochastic quasi-gradient method, are applied in the determination of posterior distributions and in the solution of stochastic optimization problems. (orig.) (57 refs., 7 figs., 1 tab.)

Statistical mechanics of budget-constrained auctions

OpenAIRE

Altarelli, F.; Braunstein, A.; Realpe-Gomez, J.; Zecchina, R.

2009-01-01

Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). Based on the cavity method of statistical mechanics, we introduce a message passing algorithm that is capable of solving efficiently random instances of the problem extracted from a natural distribution,...

Diffeomorphic Statistical Deformation Models

DEFF Research Database (Denmark)

Hansen, Michael Sass; Hansen, Mads/Fogtman; Larsen, Rasmus

2007-01-01

In this paper we present a new method for constructing diffeomorphic statistical deformation models in arbitrary dimensional images with a nonlinear generative model and a linear parameter space. Our deformation model is a modified version of the diffeomorphic model introduced by Cootes et al....... The modifications ensure that no boundary restriction has to be enforced on the parameter space to prevent folds or tears in the deformation field. For straightforward statistical analysis, principal component analysis and sparse methods, we assume that the parameters for a class of deformations lie on a linear...... with ground truth in form of manual expert annotations, and compared to Cootes's model. We anticipate applications in unconstrained diffeomorphic synthesis of images, e.g. for tracking, segmentation, registration or classification purposes....

Generic skills requirements (KSA model) towards future mechanical ...

African Journals Online (AJOL)

... Statistics and Discriminant Analysis (DA) as required to achieve the objective of the study. This study will guide all future engineers, especially in the field of Mechanical Engineering in Malaysia to penetrate the job market according to the current market needs. Keywords: generic skills; KSA model; mechanical engineers; ...

Statistical mechanics of the vertex-cover problem

Science.gov (United States)

Hartmann, Alexander K.; Weigt, Martin

2003-10-01

We review recent progress in the study of the vertex-cover problem (VC). The VC belongs to the class of NP-complete graph theoretical problems, which plays a central role in theoretical computer science. On ensembles of random graphs, VC exhibits a coverable-uncoverable phase transition. Very close to this transition, depending on the solution algorithm, easy-hard transitions in the typical running time of the algorithms occur. We explain a statistical mechanics approach, which works by mapping the VC to a hard-core lattice gas, and then applying techniques such as the replica trick or the cavity approach. Using these methods, the phase diagram of the VC could be obtained exactly for connectivities c e, the solution of the VC exhibits full replica symmetry breaking. The statistical mechanics approach can also be used to study analytically the typical running time of simple complete and incomplete algorithms for the VC. Finally, we describe recent results for the VC when studied on other ensembles of finite- and infinite-dimensional graphs.

Statistical mechanics of the vertex-cover problem

International Nuclear Information System (INIS)

Hartmann, Alexander K; Weigt, Martin

2003-01-01

We review recent progress in the study of the vertex-cover problem (VC). The VC belongs to the class of NP-complete graph theoretical problems, which plays a central role in theoretical computer science. On ensembles of random graphs, VC exhibits a coverable-uncoverable phase transition. Very close to this transition, depending on the solution algorithm, easy-hard transitions in the typical running time of the algorithms occur. We explain a statistical mechanics approach, which works by mapping the VC to a hard-core lattice gas, and then applying techniques such as the replica trick or the cavity approach. Using these methods, the phase diagram of the VC could be obtained exactly for connectivities c e, the solution of the VC exhibits full replica symmetry breaking. The statistical mechanics approach can also be used to study analytically the typical running time of simple complete and incomplete algorithms for the VC. Finally, we describe recent results for the VC when studied on other ensembles of finite- and infinite-dimensional graphs

Aftershock Energy Distribution by Statistical Mechanics Approach

Science.gov (United States)

Daminelli, R.; Marcellini, A.

2015-12-01

The aim of our work is to research the most probable distribution of the energy of aftershocks. We started by applying one of the fundamental principles of statistical mechanics that, in case of aftershock sequences, it could be expressed as: the greater the number of different ways in which the energy of aftershocks can be arranged among the energy cells in phase space the more probable the distribution. We assume that each cell in phase space has the same possibility to be occupied, and that more than one cell in the phase space can have the same energy. Seeing that seismic energy is proportional to products of different parameters, a number of different combinations of parameters can produce different energies (e.g., different combination of stress drop and fault area can release the same seismic energy). Let us assume that there are gi cells in the aftershock phase space characterised by the same energy released ɛi. Therefore we can assume that the Maxwell-Boltzmann statistics can be applied to aftershock sequences with the proviso that the judgment on the validity of this hypothesis is the agreement with the data. The aftershock energy distribution can therefore be written as follow: n(ɛ)=Ag(ɛ)exp(-βɛ)where n(ɛ) is the number of aftershocks with energy, ɛ, A and β are constants. Considering the above hypothesis, we can assume g(ɛ) is proportional to ɛ. We selected and analysed different aftershock sequences (data extracted from Earthquake Catalogs of SCEC, of INGV-CNT and other institutions) with a minimum magnitude retained ML=2 (in some cases ML=2.6) and a time window of 35 days. The results of our model are in agreement with the data, except in the very low energy band, where our model resulted in a moderate overestimation.

Statistical Mechanics and Black Hole Thermodynamics

OpenAIRE

Carlip, Steven

1997-01-01

Black holes are thermodynamic objects, but despite recent progress, the ultimate statistical mechanical origin of black hole temperature and entropy remains mysterious. Here I summarize an approach in which the entropy is viewed as arising from ``would-be pure gauge'' degrees of freedom that become dynamical at the horizon. For the (2+1)-dimensional black hole, these degrees of freedom can be counted, and yield the correct Bekenstein-Hawking entropy; the corresponding problem in 3+1 dimension...

Statistical modeling for degradation data

CERN Document Server

Lio, Yuhlong; Ng, Hon; Tsai, Tzong-Ru

2017-01-01

This book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines such as reliability, public health sciences, and finance. For example, information on products’ reliability can be obtained by analyzing degradation data. In addition, statistical modeling and inference techniques have been developed on the basis of different degradation measures. The book brings together experts engaged in statistical modeling and inference, presenting and discussing important recent advances in degradation data analysis and related applications. The topics covered are timely and have considerable potential to impact both statistics and reliability engineering.

Exclusion statistics and integrable models

International Nuclear Information System (INIS)

Mashkevich, S.

1998-01-01

The definition of exclusion statistics, as given by Haldane, allows for a statistical interaction between distinguishable particles (multi-species statistics). The thermodynamic quantities for such statistics ca be evaluated exactly. The explicit expressions for the cluster coefficients are presented. Furthermore, single-species exclusion statistics is realized in one-dimensional integrable models. The interesting questions of generalizing this correspondence onto the higher-dimensional and the multi-species cases remain essentially open

Optimizing refiner operation with statistical modelling

Energy Technology Data Exchange (ETDEWEB)

Broderick, G [Noranda Research Centre, Pointe Claire, PQ (Canada)

1997-02-01

The impact of refining conditions on the energy efficiency of the process and on the handsheet quality of a chemi-mechanical pulp was studied as part of a series of pilot scale refining trials. Statistical models of refiner performance were constructed from these results and non-linear optimization of process conditions were conducted. Optimization results indicated that increasing the ratio of specific energy applied in the first stage led to a reduction of some 15 per cent in the total energy requirement. The strategy can also be used to obtain significant increases in pulp quality for a given energy input. 20 refs., 6 tabs.

A statistical mechanics approach to Granovetter theory

Science.gov (United States)

Barra, Adriano; Agliari, Elena

2012-05-01

In this paper we try to bridge breakthroughs in quantitative sociology/econometrics, pioneered during the last decades by Mac Fadden, Brock-Durlauf, Granovetter and Watts-Strogatz, by introducing a minimal model able to reproduce essentially all the features of social behavior highlighted by these authors. Our model relies on a pairwise Hamiltonian for decision-maker interactions which naturally extends the multi-populations approaches by shifting and biasing the pattern definitions of a Hopfield model of neural networks. Once introduced, the model is investigated through graph theory (to recover Granovetter and Watts-Strogatz results) and statistical mechanics (to recover Mac-Fadden and Brock-Durlauf results). Due to the internal symmetries of our model, the latter is obtained as the relaxation of a proper Markov process, allowing even to study its out-of-equilibrium properties. The method used to solve its equilibrium is an adaptation of the Hamilton-Jacobi technique recently introduced by Guerra in the spin-glass scenario and the picture obtained is the following: shifting the patterns from [-1,+1]→[0.+1] implies that the larger the amount of similarities among decision makers, the stronger their relative influence, and this is enough to explain both the different role of strong and weak ties in the social network as well as its small-world properties. As a result, imitative interaction strengths seem essentially a robust request (enough to break the gauge symmetry in the couplings), furthermore, this naturally leads to a discrete choice modelization when dealing with the external influences and to imitative behavior à la Curie-Weiss as the one introduced by Brock and Durlauf.

Mathematics of statistical mechanics and the chaos theory

International Nuclear Information System (INIS)

Llave, R. de la; Haro, A.

2000-01-01

Statistical mechanics requires a language that unifies probabilistic and deterministic description of physical systems. We describe briefly some of the mathematical ideas needed for this unification. These ideas have also proved important in the study of chaotic systems. (Author) 17 refs

Brief introduction to Lie-admissible formulations in statistical mechanics

International Nuclear Information System (INIS)

Fronteau, J.

1981-01-01

The present article is a summary of the essential ideas and results published in previous articles, the aim here being to describe the situation in a schematic way for the benefit of non-specialists. The non-truncated Liouville theorem and equation, natural introduction of Lie-admissible formulations into statistical mechanics, the notion of a statistical quasi-particle, and transition towards the notion of fine thermodynamics are discussed

Plasma Soliton Turbulence and Statistical Mechanics

International Nuclear Information System (INIS)

Treumann, R.A.; Pottelette, R.

1999-01-01

Collisionless kinetic plasma turbulence is described approximately in terms of a superposition of non-interacting solitary waves. We discuss the relevance of such a description under astrophysical conditions. Several types of solitary waves may be of interest in this relation as generators of turbulence and turbulent transport. A consistent theory of turbulence can be given only in a few particular cases when the description can be reduced to the Korteweg-de Vries equation or some other simple equation like the Kadomtsev-Petviashvili equation. It turns out that the soliton turbulence is usually energetically harder than the ordinary weakly turbulent plasma description. This implies that interaction of particles with such kinds of turbulence can lead to stronger acceleration than in ordinary turbulence. However, the description in our model is only classical and non-relativistic. Transport in solitary turbulence is most important for drift wave turbulence. Such waves form solitary drift wave vortices which may provide cross-field transport. A more general discussion is given on transport. In a model of Levy flight trapping of particles in solitons (or solitary turbulence) one finds that the residence time of particles in the region of turbulence may be described by a generalized Lorentzian probability distribution. It is shown that under collisionless equilibrium conditions far away from thermal equilibrium such distributions are natural equilibrium distributions. A consistent thermodynamic description of such media can be given in terms of a generalized Lorentzian statistical mechanics and thermodynamics. (author)

Fracture mechanics and statistical modeling of ternary blends of polylactide/ethylene-acrylate copolymer /wood-flour composites

Science.gov (United States)

Afrifah, Kojo Agyapong

This study examined the mechanisms of toughening the brittle bio-based poly(lactic acid) (PLA) with a biodegradable rubbery impact modifier to develop biodegradable and cost effective PLA/wood-flour composites with improved impact strength, toughness, high ductility, and flexibility. Semicrystalline and amorphous PLA grades were impact modified by melt blending with an ethylene-acrylate copolymer (EAC) impact modifier. EAC content was varied to study the effectiveness and efficiency of the impact modifier in toughening the semicrystalline and amorphous grades of the PLA. Impact strength was used to assess the effectiveness and efficiency of the EAC in toughening the blends, whereas the toughening mechanisms were determined with the phase morphologies and the miscibilities of the blends. Subsequent tensile property analyses were performed on the most efficiently toughened PLA grade. Composites were made from PLA, wood flour of various particle sizes, and EAC. Using two-level factorial design the interaction between wood flour content, wood flour particle size, and EAC content and its effect on the mechanical properties of the PLA/wood-flour composites was statistically studied. Numerical optimization was also performed to statistically model and optimize material compositions to attain mechanical properties for the PLA/wood-flour composites equivalent to at least those of unfilled PLA. The J-integral method of fracture mechanics was applied to assess the crack initiation (Jin) and complete fracture (J f) energies of the composites to account for imperfections in the composites and generate data useful for engineering designs. Morphologies of the fractured surfaces of the composites were analyzed to elucidate the failure and toughening mechanisms of the composites. The EAC impact modifier effectively improved the impact strength of the PLA/EAC blends, regardless of the PLA type. However, the EAC was more efficient in the semicrystalline grades of PLA compared to the

Statistical-Mechanical Analysis of Pre-training and Fine Tuning in Deep Learning

Science.gov (United States)

Ohzeki, Masayuki

2015-03-01

In this paper, we present a statistical-mechanical analysis of deep learning. We elucidate some of the essential components of deep learning — pre-training by unsupervised learning and fine tuning by supervised learning. We formulate the extraction of features from the training data as a margin criterion in a high-dimensional feature-vector space. The self-organized classifier is then supplied with small amounts of labelled data, as in deep learning. Although we employ a simple single-layer perceptron model, rather than directly analyzing a multi-layer neural network, we find a nontrivial phase transition that is dependent on the number of unlabelled data in the generalization error of the resultant classifier. In this sense, we evaluate the efficacy of the unsupervised learning component of deep learning. The analysis is performed by the replica method, which is a sophisticated tool in statistical mechanics. We validate our result in the manner of deep learning, using a simple iterative algorithm to learn the weight vector on the basis of belief propagation.

Atmospheric statistical dynamic models. Model performance: the Lawrence Livermore Laboratoy Zonal Atmospheric Model

International Nuclear Information System (INIS)

Potter, G.L.; Ellsaesser, H.W.; MacCracken, M.C.; Luther, F.M.

1978-06-01

Results from the zonal model indicate quite reasonable agreement with observation in terms of the parameters and processes that influence the radiation and energy balance calculations. The model produces zonal statistics similar to those from general circulation models, and has also been shown to produce similar responses in sensitivity studies. Further studies of model performance are planned, including: comparison with July data; comparison of temperature and moisture transport and wind fields for winter and summer months; and a tabulation of atmospheric energetics. Based on these preliminary performance studies, however, it appears that the zonal model can be used in conjunction with more complex models to help unravel the problems of understanding the processes governing present climate and climate change. As can be seen in the subsequent paper on model sensitivity studies, in addition to reduced cost of computation, the zonal model facilitates analysis of feedback mechanisms and simplifies analysis of the interactions between processes

Online Statistical Modeling (Regression Analysis) for Independent Responses

Science.gov (United States)

Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus

2017-06-01

Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.

Statistical Mechanics and Applications in Condensed Matter

Science.gov (United States)

Di Castro, Carlo; Raimondi, Roberto

2015-08-01

Preface; 1. Thermodynamics: a brief overview; 2. Kinetics; 3. From Boltzmann to Gibbs; 4. More ensembles; 5. The thermodynamic limit and its thermodynamic stability; 6. Density matrix and quantum statistical mechanics; 7. The quantum gases; 8. Mean-field theories and critical phenomena; 9. Second quantization and Hartree-Fock approximation; 10. Linear response and fluctuation-dissipation theorem in quantum systems: equilibrium and small deviations; 11. Brownian motion and transport in disordered systems; 12. Fermi liquids; 13. The Landau theory of the second order phase transitions; 14. The Landau-Wilson model for critical phenomena; 15. Superfluidity and superconductivity; 16. The scaling theory; 17. The renormalization group approach; 18. Thermal Green functions; 19. The microscopic foundations of Fermi liquids; 20. The Luttinger liquid; 21. Quantum interference effects in disordered electron systems; Appendix A. The central limit theorem; Appendix B. Some useful properties of the Euler Gamma function; Appendix C. Proof of the second theorem of Yang and Lee; Appendix D. The most probable distribution for the quantum gases; Appendix E. Fermi-Dirac and Bose-Einstein integrals; Appendix F. The Fermi gas in a uniform magnetic field: Landau diamagnetism; Appendix G. Ising and gas-lattice models; Appendix H. Sum over discrete Matsubara frequencies; Appendix I. Hydrodynamics of the two-fluid model of superfluidity; Appendix J. The Cooper problem in the theory of superconductivity; Appendix K. Superconductive fluctuations phenomena; Appendix L. Diagrammatic aspects of the exact solution of the Tomonaga Luttinger model; Appendix M. Details on the theory of the disordered Fermi liquid; References; Author index; Index.

Statistical 3D damage accumulation model for ion implant simulators

CERN Document Server

Hernandez-Mangas, J M; Enriquez, L E; Bailon, L; Barbolla, J; Jaraiz, M

2003-01-01

A statistical 3D damage accumulation model, based on the modified Kinchin-Pease formula, for ion implant simulation has been included in our physically based ion implantation code. It has only one fitting parameter for electronic stopping and uses 3D electron density distributions for different types of targets including compound semiconductors. Also, a statistical noise reduction mechanism based on the dose division is used. The model has been adapted to be run under parallel execution in order to speed up the calculation in 3D structures. Sequential ion implantation has been modelled including previous damage profiles. It can also simulate the implantation of molecular and cluster projectiles. Comparisons of simulated doping profiles with experimental SIMS profiles are presented. Also comparisons between simulated amorphization and experimental RBS profiles are shown. An analysis of sequential versus parallel processing is provided.

Statistical 3D damage accumulation model for ion implant simulators

International Nuclear Information System (INIS)

Hernandez-Mangas, J.M.; Lazaro, J.; Enriquez, L.; Bailon, L.; Barbolla, J.; Jaraiz, M.

2003-01-01

A statistical 3D damage accumulation model, based on the modified Kinchin-Pease formula, for ion implant simulation has been included in our physically based ion implantation code. It has only one fitting parameter for electronic stopping and uses 3D electron density distributions for different types of targets including compound semiconductors. Also, a statistical noise reduction mechanism based on the dose division is used. The model has been adapted to be run under parallel execution in order to speed up the calculation in 3D structures. Sequential ion implantation has been modelled including previous damage profiles. It can also simulate the implantation of molecular and cluster projectiles. Comparisons of simulated doping profiles with experimental SIMS profiles are presented. Also comparisons between simulated amorphization and experimental RBS profiles are shown. An analysis of sequential versus parallel processing is provided

Bayesian Sensitivity Analysis of Statistical Models with Missing Data.

Science.gov (United States)

Zhu, Hongtu; Ibrahim, Joseph G; Tang, Niansheng

2014-04-01

Methods for handling missing data depend strongly on the mechanism that generated the missing values, such as missing completely at random (MCAR) or missing at random (MAR), as well as other distributional and modeling assumptions at various stages. It is well known that the resulting estimates and tests may be sensitive to these assumptions as well as to outlying observations. In this paper, we introduce various perturbations to modeling assumptions and individual observations, and then develop a formal sensitivity analysis to assess these perturbations in the Bayesian analysis of statistical models with missing data. We develop a geometric framework, called the Bayesian perturbation manifold, to characterize the intrinsic structure of these perturbations. We propose several intrinsic influence measures to perform sensitivity analysis and quantify the effect of various perturbations to statistical models. We use the proposed sensitivity analysis procedure to systematically investigate the tenability of the non-ignorable missing at random (NMAR) assumption. Simulation studies are conducted to evaluate our methods, and a dataset is analyzed to illustrate the use of our diagnostic measures.

An introduction to mathematical modeling a course in mechanics

CERN Document Server

Oden, Tinsley J

2011-01-01

A modern approach to mathematical modeling, featuring unique applications from the field of mechanics An Introduction to Mathematical Modeling: A Course in Mechanics is designed to survey the mathematical models that form the foundations of modern science and incorporates examples that illustrate how the most successful models arise from basic principles in modern and classical mathematical physics. Written by a world authority on mathematical theory and computational mechanics, the book presents an account of continuum mechanics, electromagnetic field theory, quantum mechanics, and statistical mechanics for readers with varied backgrounds in engineering, computer science, mathematics, and physics. The author streamlines a comprehensive understanding of the topic in three clearly organized sections: Nonlinear Continuum Mechanics introduces kinematics as well as force and stress in deformable bodies; mass and momentum; balance of linear and angular momentum; conservation of energy; and constitutive equation...

Statistical mechanics of program systems

International Nuclear Information System (INIS)

Neirotti, Juan P; Caticha, Nestor

2006-01-01

We discuss the collective behaviour of a set of operators and variables that constitute a program and the emergence of meaningful computational properties in the language of statistical mechanics. This is done by appropriately modifying available Monte Carlo methods to deal with hierarchical structures. The study suggests, in analogy with simulated annealing, a method to automatically design programs. Reasonable solutions can be found, at low temperatures, when the method is applied to simple toy problems such as finding an algorithm that determines the roots of a function or one that makes a nonlinear regression. Peaks in the specific heat are interpreted as signalling phase transitions which separate regions where different algorithmic strategies are used to solve the problem

The statistical mechanics of learning a rule

International Nuclear Information System (INIS)

Watkin, T.L.H.; Rau, A.; Biehl, M.

1993-01-01

A summary is presented of the statistical mechanical theory of learning a rule with a neural network, a rapidly advancing area which is closely related to other inverse problems frequently encountered by physicists. By emphasizing the relationship between neural networks and strongly interacting physical systems, such as spin glasses, the authors show how learning theory has provided a workshop in which to develop new, exact analytical techniques

Statistical models for thermal ageing of steel materials in nuclear power plants

International Nuclear Information System (INIS)

Persoz, M.

1996-01-01

Some category of steel materials in nuclear power plants may be subjected to thermal ageing, whose extent depends on the steel chemical composition and the ageing parameters, i.e. temperature and duration. This ageing affects the 'impact strength' of the materials, which is a mechanical property. In order to assess the residual lifetime of these components, a probabilistic study has been launched, which takes into account the scatter over the input parameters of the mechanical model. Predictive formulae for estimating the impact strength of aged materials are important input data of the model. A data base has been created with impact strength results obtained from an ageing program in laboratory and statistical treatments have been undertaken. Two kinds of model have been developed, with non linear regression methods (PROC NLIN, available in SAS/STAT). The first one, using a hyperbolic tangent function, is partly based on physical considerations, and the second one, of an exponential type, is purely statistically built. The difficulties consist in selecting the significant parameters and attributing initial values to the coefficients, which is a requirement of the NLIN procedure. This global statistical analysis has led to general models that are unction of the chemical variables and the ageing parameters. These models are as precise (if not more) as local models that had been developed earlier for some specific values of ageing temperature and ageing duration. This paper describes the data and the methodology used to build the models and analyses the results given by the SAS system. (author)

Principles of thermodynamics and statistical mechanics

CERN Document Server

Lawden, D F

2005-01-01

A thorough exploration of the universal principles of thermodynamics and statistical mechanics, this volume explains the applications of these essential rules to a multitude of situations arising in physics and engineering. It develops their use in a variety of circumstances-including those involving gases, crystals, and magnets-in order to illustrate general methods of analysis and to provide readers with all the necessary background to continue in greater depth with specific topics.Author D. F. Lawden has considerable experience in teaching this subject to university students of varied abili

Classical model of intermediate statistics

International Nuclear Information System (INIS)

Kaniadakis, G.

1994-01-01

In this work we present a classical kinetic model of intermediate statistics. In the case of Brownian particles we show that the Fermi-Dirac (FD) and Bose-Einstein (BE) distributions can be obtained, just as the Maxwell-Boltzmann (MD) distribution, as steady states of a classical kinetic equation that intrinsically takes into account an exclusion-inclusion principle. In our model the intermediate statistics are obtained as steady states of a system of coupled nonlinear kinetic equations, where the coupling constants are the transmutational potentials η κκ' . We show that, besides the FD-BE intermediate statistics extensively studied from the quantum point of view, we can also study the MB-FD and MB-BE ones. Moreover, our model allows us to treat the three-state mixing FD-MB-BE intermediate statistics. For boson and fermion mixing in a D-dimensional space, we obtain a family of FD-BE intermediate statistics by varying the transmutational potential η BF . This family contains, as a particular case when η BF =0, the quantum statistics recently proposed by L. Wu, Z. Wu, and J. Sun [Phys. Lett. A 170, 280 (1992)]. When we consider the two-dimensional FD-BE statistics, we derive an analytic expression of the fraction of fermions. When the temperature T→∞, the system is composed by an equal number of bosons and fermions, regardless of the value of η BF . On the contrary, when T=0, η BF becomes important and, according to its value, the system can be completely bosonic or fermionic, or composed both by bosons and fermions

Probing NWP model deficiencies by statistical postprocessing

DEFF Research Database (Denmark)

Rosgaard, Martin Haubjerg; Nielsen, Henrik Aalborg; Nielsen, Torben S.

2016-01-01

The objective in this article is twofold. On one hand, a Model Output Statistics (MOS) framework for improved wind speed forecast accuracy is described and evaluated. On the other hand, the approach explored identifies unintuitive explanatory value from a diagnostic variable in an operational....... Based on the statistical model candidates inferred from the data, the lifted index NWP model diagnostic is consistently found among the NWP model predictors of the best performing statistical models across sites....

Braid group, knot theory and statistical mechanics II

CERN Document Server

Yang Chen Ning

1994-01-01

The present volume is an updated version of the book edited by C N Yang and M L Ge on the topics of braid groups and knot theory, which are related to statistical mechanics. This book is based on the 1989 volume but has new material included and new contributors.

Statistical-mechanics analysis of Gaussian labeled-unlabeled classification problems

International Nuclear Information System (INIS)

Tanaka, Toshiyuki

2013-01-01

The labeled-unlabeled classification problem in semi-supervised learning is studied via statistical-mechanics approach. We analytically investigate performance of a learner with an equal-weight mixture of two symmetrically-located Gaussians, performing posterior mean estimation of the parameter vector on the basis of a dataset consisting of labeled and unlabeled data generated from the same probability model as that assumed by the learner. Under the assumption of replica symmetry, we have analytically obtained a set of saddle-point equations, which allows us to numerically evaluate performance of the learner. On the basis of the analytical result we have observed interesting phenomena, in particular the coexistence of good and bad solutions, which may happen when the number of unlabeled data is relatively large compared with that of labeled data

Statistical Model of Extreme Shear

DEFF Research Database (Denmark)

Hansen, Kurt Schaldemose; Larsen, Gunner Chr.

2005-01-01

In order to continue cost-optimisation of modern large wind turbines, it is important to continuously increase the knowledge of wind field parameters relevant to design loads. This paper presents a general statistical model that offers site-specific prediction of the probability density function...... by a model that, on a statistically consistent basis, describes the most likely spatial shape of an extreme wind shear event. Predictions from the model have been compared with results from an extreme value data analysis, based on a large number of full-scale measurements recorded with a high sampling rate...

Aspects of statistical model for multifragmentation

International Nuclear Information System (INIS)

Bhattacharyya, P.; Das Gupta, S.; Mekjian, A. Z.

1999-01-01

We deal with two different aspects of an exactly soluble statistical model of fragmentation. First we show, using zero range force and finite temperature Thomas-Fermi theory, that a common link can be found between finite temperature mean field theory and the statistical fragmentation model. We show the latter naturally arises in the spinodal region. Next we show that although the exact statistical model is a canonical model and uses temperature, microcanonical results which use constant energy rather than constant temperature can also be obtained from the canonical model using saddle-point approximation. The methodology is extremely simple to implement and at least in all the examples studied in this work is very accurate. (c) 1999 The American Physical Society

Statistical analysis of the factors that influenced the mechanical properties improvement of cassava starch films

Science.gov (United States)

Monteiro, Mayra; Oliveira, Victor; Santos, Francisco; Barros Neto, Eduardo; Silva, Karyn; Silva, Rayane; Henrique, João; Chibério, Abimaelle

2017-08-01

In order to obtain cassava starch films with improved mechanical properties in relation to the synthetic polymer in the packaging production, a complete factorial design 23 was carried out in order to investigate which factor significantly influences the tensile strength of the biofilm. The factors to be investigated were cassava starch, glycerol and modified clay contents. Modified bentonite clay was used as a filling material of the biofilm. Glycerol was the plasticizer used to thermoplastify cassava starch. The factorial analysis suggested a regression model capable of predicting the optimal mechanical property of the cassava starch film from the maximization of the tensile strength. The reliability of the regression model was tested by the correlation established with the experimental data through the following statistical analyse: Pareto graph. The modified clay was the factor of greater statistical significance on the observed response variable, being the factor that contributed most to the improvement of the mechanical property of the starch film. The factorial experiments showed that the interaction of glycerol with both modified clay and cassava starch was significant for the reduction of biofilm ductility. Modified clay and cassava starch contributed to the maximization of biofilm ductility, while glycerol contributed to the minimization.

Statistical Compression for Climate Model Output

Science.gov (United States)

Hammerling, D.; Guinness, J.; Soh, Y. J.

2017-12-01

Numerical climate model simulations run at high spatial and temporal resolutions generate massive quantities of data. As our computing capabilities continue to increase, storing all of the data is not sustainable, and thus is it important to develop methods for representing the full datasets by smaller compressed versions. We propose a statistical compression and decompression algorithm based on storing a set of summary statistics as well as a statistical model describing the conditional distribution of the full dataset given the summary statistics. We decompress the data by computing conditional expectations and conditional simulations from the model given the summary statistics. Conditional expectations represent our best estimate of the original data but are subject to oversmoothing in space and time. Conditional simulations introduce realistic small-scale noise so that the decompressed fields are neither too smooth nor too rough compared with the original data. Considerable attention is paid to accurately modeling the original dataset-one year of daily mean temperature data-particularly with regard to the inherent spatial nonstationarity in global fields, and to determining the statistics to be stored, so that the variation in the original data can be closely captured, while allowing for fast decompression and conditional emulation on modest computers.

Automated statistical modeling of analytical measurement systems

International Nuclear Information System (INIS)

Jacobson, J.J.

1992-01-01

The statistical modeling of analytical measurement systems at the Idaho Chemical Processing Plant (ICPP) has been completely automated through computer software. The statistical modeling of analytical measurement systems is one part of a complete quality control program used by the Remote Analytical Laboratory (RAL) at the ICPP. The quality control program is an integration of automated data input, measurement system calibration, database management, and statistical process control. The quality control program and statistical modeling program meet the guidelines set forth by the American Society for Testing Materials and American National Standards Institute. A statistical model is a set of mathematical equations describing any systematic bias inherent in a measurement system and the precision of a measurement system. A statistical model is developed from data generated from the analysis of control standards. Control standards are samples which are made up at precise known levels by an independent laboratory and submitted to the RAL. The RAL analysts who process control standards do not know the values of those control standards. The object behind statistical modeling is to describe real process samples in terms of their bias and precision and, to verify that a measurement system is operating satisfactorily. The processing of control standards gives us this ability

Statistical mechanics for a class of quantum statistics

International Nuclear Information System (INIS)

Isakov, S.B.

1994-01-01

Generalized statistical distributions for identical particles are introduced for the case where filling a single-particle quantum state by particles depends on filling states of different momenta. The system of one-dimensional bosons with a two-body potential that can be solved by means of the thermodynamic Bethe ansatz is shown to be equivalent thermodynamically to a system of free particles obeying statistical distributions of the above class. The quantum statistics arising in this way are completely determined by the two-particle scattering phases of the corresponding interacting systems. An equation determining the statistical distributions for these statistics is derived

Statistical modelling for ship propulsion efficiency

DEFF Research Database (Denmark)

Petersen, Jóan Petur; Jacobsen, Daniel J.; Winther, Ole

2012-01-01

This paper presents a state-of-the-art systems approach to statistical modelling of fuel efficiency in ship propulsion, and also a novel and publicly available data set of high quality sensory data. Two statistical model approaches are investigated and compared: artificial neural networks...

Ants in a labyrinth: a statistical mechanics approach to the division of labour.

Directory of Open Access Journals (Sweden)

Thomas Owen Richardson

2011-04-01

Full Text Available Division of labour (DoL is a fundamental organisational principle in human societies, within virtual and robotic swarms and at all levels of biological organisation. DoL reaches a pinnacle in the insect societies where the most widely used model is based on variation in response thresholds among individuals, and the assumption that individuals and stimuli are well-mixed. Here, we present a spatially explicit model of DoL. Our model is inspired by Pierre de Gennes' 'Ant in a Labyrinth' which laid the foundations of an entire new field in statistical mechanics. We demonstrate the emergence, even in a simplified one-dimensional model, of a spatial patterning of individuals and a right-skewed activity distribution, both of which are characteristics of division of labour in animal societies. We then show using a two-dimensional model that the work done by an individual within an activity bout is a sigmoidal function of its response threshold. Furthermore, there is an inverse relationship between the overall stimulus level and the skewness of the activity distribution. Therefore, the difference in the amount of work done by two individuals with different thresholds increases as the overall stimulus level decreases. Indeed, spatial fluctuations of task stimuli are minimised at these low stimulus levels. Hence, the more unequally labour is divided amongst individuals, the greater the ability of the colony to maintain homeostasis. Finally, we show that the non-random spatial distribution of individuals within biological and social systems could be caused by indirect (stigmergic interactions, rather than direct agent-to-agent interactions. Our model links the principle of DoL with principles in the statistical mechanics and provides testable hypotheses for future experiments.

Neocortical dynamics at multiple scales: EEG standing waves, statistical mechanics, and physical analogs.

Science.gov (United States)

Ingber, Lester; Nunez, Paul L

2011-02-01

The dynamic behavior of scalp potentials (EEG) is apparently due to some combination of global and local processes with important top-down and bottom-up interactions across spatial scales. In treating global mechanisms, we stress the importance of myelinated axon propagation delays and periodic boundary conditions in the cortical-white matter system, which is topologically close to a spherical shell. By contrast, the proposed local mechanisms are multiscale interactions between cortical columns via short-ranged non-myelinated fibers. A mechanical model consisting of a stretched string with attached nonlinear springs demonstrates the general idea. The string produces standing waves analogous to large-scale coherent EEG observed in some brain states. The attached springs are analogous to the smaller (mesoscopic) scale columnar dynamics. Generally, we expect string displacement and EEG at all scales to result from both global and local phenomena. A statistical mechanics of neocortical interactions (SMNI) calculates oscillatory behavior consistent with typical EEG, within columns, between neighboring columns via short-ranged non-myelinated fibers, across cortical regions via myelinated fibers, and also derives a string equation consistent with the global EEG model. Copyright © 2010 Elsevier Inc. All rights reserved.

Realistic thermodynamic and statistical-mechanical measures for neural synchronization.

Science.gov (United States)

Kim, Sang-Yoon; Lim, Woochang

2014-04-15

Synchronized brain rhythms, associated with diverse cognitive functions, have been observed in electrical recordings of brain activity. Neural synchronization may be well described by using the population-averaged global potential VG in computational neuroscience. The time-averaged fluctuation of VG plays the role of a "thermodynamic" order parameter O used for describing the synchrony-asynchrony transition in neural systems. Population spike synchronization may be well visualized in the raster plot of neural spikes. The degree of neural synchronization seen in the raster plot is well measured in terms of a "statistical-mechanical" spike-based measure Ms introduced by considering the occupation and the pacing patterns of spikes. The global potential VG is also used to give a reference global cycle for the calculation of Ms. Hence, VG becomes an important collective quantity because it is associated with calculation of both O and Ms. However, it is practically difficult to directly get VG in real experiments. To overcome this difficulty, instead of VG, we employ the instantaneous population spike rate (IPSR) which can be obtained in experiments, and develop realistic thermodynamic and statistical-mechanical measures, based on IPSR, to make practical characterization of the neural synchronization in both computational and experimental neuroscience. Particularly, more accurate characterization of weak sparse spike synchronization can be achieved in terms of realistic statistical-mechanical IPSR-based measure, in comparison with the conventional measure based on VG. Copyright © 2014. Published by Elsevier B.V.

Thermodynamics and statistical mechanics. [thermodynamic properties of gases

Science.gov (United States)

1976-01-01

The basic thermodynamic properties of gases are reviewed and the relations between them are derived from the first and second laws. The elements of statistical mechanics are then formulated and the partition function is derived. The classical form of the partition function is used to obtain the Maxwell-Boltzmann distribution of kinetic energies in the gas phase and the equipartition of energy theorem is given in its most general form. The thermodynamic properties are all derived as functions of the partition function. Quantum statistics are reviewed briefly and the differences between the Boltzmann distribution function for classical particles and the Fermi-Dirac and Bose-Einstein distributions for quantum particles are discussed.

Geometric Approach to Quantum Statistical Mechanics and Application to Casimir Energy and Friction Properties

International Nuclear Information System (INIS)

Ichinose, Shoichi

2010-01-01

A geometric approach to general quantum statistical systems (including the harmonic oscillator) is presented. It is applied to Casimir energy and the dissipative system with friction. We regard the (N+1)-dimensional Euclidean coordinate system (X i ,τ) as the quantum statistical system of N quantum (statistical) variables (X τ ) and one Euclidean time variable (t). Introducing paths (lines or hypersurfaces) in this space (X τ ,t), we adopt the path-integral method to quantize the mechanical system. This is a new view of (statistical) quantization of the mechanical system. The system Hamiltonian appears as the area. We show quantization is realized by the minimal area principle in the present geometric approach. When we take a line as the path, the path-integral expressions of the free energy are shown to be the ordinary ones (such as N harmonic oscillators) or their simple variation. When we take a hyper-surface as the path, the system Hamiltonian is given by the area of the hyper-surface which is defined as a closed-string configuration in the bulk space. In this case, the system becomes a O(N) non-linear model. We show the recently-proposed 5 dimensional Casimir energy (ArXiv:0801.3064,0812.1263) is valid. We apply this approach to the visco-elastic system, and present a new method using the path-integral for the calculation of the dissipative properties.

Sensometrics: Thurstonian and Statistical Models

DEFF Research Database (Denmark)

Christensen, Rune Haubo Bojesen

. sensR is a package for sensory discrimination testing with Thurstonian models and ordinal supports analysis of ordinal data with cumulative link (mixed) models. While sensR is closely connected to the sensometrics field, the ordinal package has developed into a generic statistical package applicable......This thesis is concerned with the development and bridging of Thurstonian and statistical models for sensory discrimination testing as applied in the scientific discipline of sensometrics. In sensory discrimination testing sensory differences between products are detected and quantified by the use...... and sensory discrimination testing in particular in a series of papers by advancing Thurstonian models for a range of sensory discrimination protocols in addition to facilitating their application by providing software for fitting these models. The main focus is on identifying Thurstonian models...

Molecular dynamics and Monte Carlo calculations in statistical mechanics

International Nuclear Information System (INIS)

Wood, W.W.; Erpenbeck, J.J.

1976-01-01

Monte Carlo and molecular dynamics calculations on statistical mechanical systems is reviewed giving some of the more significant recent developments. It is noted that the term molecular dynamics refers to the time-averaging technique for hard-core and square-well interactions and for continuous force-law interactions. Ergodic questions, methodology, quantum mechanical, Lorentz, and one-dimensional, hard-core, and square and triangular-well systems, short-range soft potentials, and other systems are included. 268 references

Statistical modelling of transcript profiles of differentially regulated genes

Directory of Open Access Journals (Sweden)

Sergeant Martin J

2008-07-01

allowed 11% of the Escherichia coli features to be fitted by an exponential function, and 25% of the Rattus norvegicus features could be described by the critical exponential model, all with statistical significance of p Conclusion The statistical non-linear regression approaches presented in this study provide detailed biologically oriented descriptions of individual gene expression profiles, using biologically variable data to generate a set of defining parameters. These approaches have application to the modelling and greater interpretation of profiles obtained across a wide range of platforms, such as microarrays. Through careful choice of appropriate model forms, such statistical regression approaches allow an improved comparison of gene expression profiles, and may provide an approach for the greater understanding of common regulatory mechanisms between genes.

Introduction to nonequilibrium statistical mechanics with quantum field theory

International Nuclear Information System (INIS)

Kita, Takafumi

2010-01-01

In this article, we present a concise and self-contained introduction to nonequilibrium statistical mechanics with quantum field theory by considering an ensemble of interacting identical bosons or fermions as an example. Readers are assumed to be familiar with the Matsubara formalism of equilibrium statistical mechanics such as Feynman diagrams, the proper self-energy, and Dyson's equation. The aims are threefold: (1) to explain the fundamentals of nonequilibrium quantum field theory as simple as possible on the basis of the knowledge of the equilibrium counterpart; (2) to elucidate the hierarchy in describing nonequilibrium systems from Dyson's equation on the Keldysh contour to the Navier-Stokes equation in fluid mechanics via quantum transport equations and the Boltzmann equation; (3) to derive an expression of nonequilibrium entropy that evolves with time. In stage (1), we introduce nonequilibrium Green's function and the self-energy uniquely on the round-trip Keldysh contour, thereby avoiding possible confusions that may arise from defining multiple Green's functions at the very beginning. We try to present the Feynman rules for the perturbation expansion as simple as possible. In particular, we focus on the self-consistent perturbation expansion with the Luttinger-Ward thermodynamic functional, i.e., Baym's Φ-derivable approximation, which has a crucial property for nonequilibrium systems of obeying various conservation laws automatically. We also show how the two-particle correlations can be calculated within the Φ-derivable approximation, i.e., an issue of how to handle the 'Bogoliubov-Born-Green-Kirkwood-Yvons (BBGKY) hierarchy'. Aim (2) is performed through successive reductions of relevant variables with the Wigner transformation, the gradient expansion based on the Groenewold-Moyal product, and Enskog's expansion from local equilibrium. This part may be helpful for convincing readers that nonequilibrium systems can be handled microscopically with

Statistical modelling for social researchers principles and practice

CERN Document Server

Tarling, Roger

2008-01-01

This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-l...

Topology for statistical modeling of petascale data.

Energy Technology Data Exchange (ETDEWEB)

Pascucci, Valerio (University of Utah, Salt Lake City, UT); Mascarenhas, Ajith Arthur; Rusek, Korben (Texas A& M University, College Station, TX); Bennett, Janine Camille; Levine, Joshua (University of Utah, Salt Lake City, UT); Pebay, Philippe Pierre; Gyulassy, Attila (University of Utah, Salt Lake City, UT); Thompson, David C.; Rojas, Joseph Maurice (Texas A& M University, College Station, TX)

2011-07-01

This document presents current technical progress and dissemination of results for the Mathematics for Analysis of Petascale Data (MAPD) project titled 'Topology for Statistical Modeling of Petascale Data', funded by the Office of Science Advanced Scientific Computing Research (ASCR) Applied Math program. Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is thus to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, our approach is based on the complementary techniques of combinatorial topology and statistical modeling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modeling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. This document summarizes the technical advances we have made to date that were made possible in whole or in part by MAPD funding. These technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modeling, and (3) new integrated topological and statistical methods.

Bayesian models: A statistical primer for ecologists

Science.gov (United States)

Hobbs, N. Thompson; Hooten, Mevin B.

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models

Statistical Model-Based Face Pose Estimation

Institute of Scientific and Technical Information of China (English)

GE Xinliang; YANG Jie; LI Feng; WANG Huahua

2007-01-01

A robust face pose estimation approach is proposed by using face shape statistical model approach and pose parameters are represented by trigonometric functions. The face shape statistical model is firstly built by analyzing the face shapes from different people under varying poses. The shape alignment is vital in the process of building the statistical model. Then, six trigonometric functions are employed to represent the face pose parameters. Lastly, the mapping function is constructed between face image and face pose by linearly relating different parameters. The proposed approach is able to estimate different face poses using a few face training samples. Experimental results are provided to demonstrate its efficiency and accuracy.

Predicting the lung compliance of mechanically ventilated patients via statistical modeling

International Nuclear Information System (INIS)

Ganzert, Steven; Kramer, Stefan; Guttmann, Josef

2012-01-01

To avoid ventilator associated lung injury (VALI) during mechanical ventilation, the ventilator is adjusted with reference to the volume distensibility or ‘compliance’ of the lung. For lung-protective ventilation, the lung should be inflated at its maximum compliance, i.e. when during inspiration a maximal intrapulmonary volume change is achieved by a minimal change of pressure. To accomplish this, one of the main parameters is the adjusted positive end-expiratory pressure (PEEP). As changing the ventilator settings usually produces an effect on patient's lung mechanics with a considerable time delay, the prediction of the compliance change associated with a planned change of PEEP could assist the physician at the bedside. This study introduces a machine learning approach to predict the nonlinear lung compliance for the individual patient by Gaussian processes, a probabilistic modeling technique. Experiments are based on time series data obtained from patients suffering from acute respiratory distress syndrome (ARDS). With a high hit ratio of up to 93%, the learned models could predict whether an increase/decrease of PEEP would lead to an increase/decrease of the compliance. However, the prediction of the complete pressure–volume relation for an individual patient has to be improved. We conclude that the approach is well suitable for the given problem domain but that an individualized feature selection should be applied for a precise prediction of individual pressure–volume curves. (paper)

Statistical mechanics and the foundations of thermodynamics

International Nuclear Information System (INIS)

Martin-Loef, A.

1979-01-01

These lectures are designed as an introduction to classical statistical mechanics and its relation to thermodynamics. They are intended to bridge the gap between the treatment of the subject in physics text books and the modern presentations of mathematically rigorous results. We shall first introduce the probability distributions, ensembles, appropriate for describing systems in equilibrium and consider some of their basic physical applications. We also discuss the problem of approach to equilibrium and how irreversibility comes into the dynamics. We then give a detailed description of how the law of large numbers for macrovariables in equilibrium is derived from the fact that entropy is an extensive quantity in the thermodynamic limit. We show in a natural way how to split the energy changes in an thermodynamical process into work and heat leading to a derivation of the first and second laws of thermodynamics from the rules of thermodynamical equilibrium. We have elaborated this part in detail because we feel it is quite satisfactory, that the establishment of the limit of thermodynamic functions as achieved in the modern development of the mathematical aspects of statistical mechanics allows a more general and logically clearer presentation of the bases of thermodynamics. We close these lectures by presenting the basic facts about fluctuation theory. The treatment aims to be reasonably self-contained both concerning the physics and mathematics needed. No knowledge of quantum mechanics is presupposed. Since we spent a large part on mathematical proofs and give many technical facts these lectures are probably most digestive for the mathematically inclined reader who wants to understand the physics of the subject. (HJ)

Statistical mechanics and the evolution of polygenic quantitative traits

NARCIS (Netherlands)

Barton, N.H.; De Vladar, H.P.

The evolution of quantitative characters depends on the frequencies of the alleles involved, yet these frequencies cannot usually be measured. Previous groups have proposed an approximation to the dynamics of quantitative traits, based on an analogy with statistical mechanics. We present a modified

STATISTICAL DISTRIBUTION PATTERNS IN MECHANICAL AND FATIGUE PROPERTIES OF METALLIC MATERIALS

OpenAIRE

Tatsuo, SAKAI; Masaki, NAKAJIMA; Keiro, TOKAJI; Norihiko, HASEGAWA; Department of Mechanical Engineering, Ritsumeikan University; Department of Mechanical Engineering, Toyota College of Technology; Department of Mechanical Engineering, Gifu University; Department of Mechanical Engineering, Gifu University

1997-01-01

Many papers on the statistical aspect of materials strength have been collected and reviewed by The Research Group for Statistical Aspects of Materials Strength.A book of "Statistical Aspects of Materials Strength" was written by this group, and published in 1992.Based on the experimental data compiled in this book, distribution patterns of mechanical properties are systematically surveyed paying an attention to metallic materials.Thus one can obtain the fundamental knowledge for a reliabilit...

Statistical mechanics of high-density bond percolation

Science.gov (United States)

Timonin, P. N.

2018-05-01

High-density (HD) percolation describes the percolation of specific κ -clusters, which are the compact sets of sites each connected to κ nearest filled sites at least. It takes place in the classical patterns of independently distributed sites or bonds in which the ordinary percolation transition also exists. Hence, the study of series of κ -type HD percolations amounts to the description of classical clusters' structure for which κ -clusters constitute κ -cores nested one into another. Such data are needed for description of a number of physical, biological, and information properties of complex systems on random lattices, graphs, and networks. They range from magnetic properties of semiconductor alloys to anomalies in supercooled water and clustering in biological and social networks. Here we present the statistical mechanics approach to study HD bond percolation on an arbitrary graph. It is shown that the generating function for κ -clusters' size distribution can be obtained from the partition function of the specific q -state Potts-Ising model in the q →1 limit. Using this approach we find exact κ -clusters' size distributions for the Bethe lattice and Erdos-Renyi graph. The application of the method to Euclidean lattices is also discussed.

A statistical mechanics approach to mixing in stratified fluids

OpenAIRE

Venaille , Antoine; Gostiaux , Louis; Sommeria , Joël

2016-01-01

Accepted for the Journal of Fluid Mechanics; Predicting how much mixing occurs when a given amount of energy is injected into a Boussinesq fluid is a longstanding problem in stratified turbulence. The huge number of degrees of freedom involved in these processes renders extremely difficult a deterministic approach to the problem. Here we present a statistical mechanics approach yielding a prediction for a cumulative, global mixing efficiency as a function of a global Richard-son number and th...

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.

Matrix Tricks for Linear Statistical Models

CERN Document Server

Puntanen, Simo; Styan, George PH

2011-01-01

In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebra; their use is really essential. Our experience is that making some particular matrix tricks very familiar to students can substantially increase their insight into linear statistical models (and also multivariate statistical analysis). In matrix algebra, there are handy, sometimes even very simple "tricks" which simplify and clarify the treatment of a problem - both for the student and

Classical statistical mechanics approach to multipartite entanglement

Energy Technology Data Exchange (ETDEWEB)

Facchi, P [Dipartimento di Matematica, Universita di Bari, I-70125 Bari (Italy); Florio, G; Pascazio, S [Istituto Nazionale di Fisica Nucleare, Sezione di Bari, I-70126 Bari (Italy); Marzolino, U [Dipartimento di Fisica, Universita di Trieste, and Istituto Nazionale di Fisica Nucleare, Sezione di Trieste, I-34014 Trieste (Italy); Parisi, G [Dipartimento di Fisica, Universita di Roma ' La Sapienza' , Piazzale Aldo Moro 2, Centre for Statistical Mechanics and Complexity (SMC), CNR-INFM (Italy)

2010-06-04

We characterize the multipartite entanglement of a system of n qubits in terms of the distribution function of the bipartite purity over balanced bipartitions. We search for maximally multipartite entangled states, whose average purity is minimal, and recast this optimization problem into a problem of statistical mechanics, by introducing a cost function, a fictitious temperature and a partition function. By investigating the high-temperature expansion, we obtain the first three moments of the distribution. We find that the problem exhibits frustration.

Classical statistical mechanics approach to multipartite entanglement

Science.gov (United States)

Facchi, P.; Florio, G.; Marzolino, U.; Parisi, G.; Pascazio, S.

2010-06-01

We characterize the multipartite entanglement of a system of n qubits in terms of the distribution function of the bipartite purity over balanced bipartitions. We search for maximally multipartite entangled states, whose average purity is minimal, and recast this optimization problem into a problem of statistical mechanics, by introducing a cost function, a fictitious temperature and a partition function. By investigating the high-temperature expansion, we obtain the first three moments of the distribution. We find that the problem exhibits frustration.

Classical statistical mechanics approach to multipartite entanglement

International Nuclear Information System (INIS)

Facchi, P; Florio, G; Pascazio, S; Marzolino, U; Parisi, G

2010-01-01

We characterize the multipartite entanglement of a system of n qubits in terms of the distribution function of the bipartite purity over balanced bipartitions. We search for maximally multipartite entangled states, whose average purity is minimal, and recast this optimization problem into a problem of statistical mechanics, by introducing a cost function, a fictitious temperature and a partition function. By investigating the high-temperature expansion, we obtain the first three moments of the distribution. We find that the problem exhibits frustration.

Statistical Model Checking of Rich Models and Properties

DEFF Research Database (Denmark)

Poulsen, Danny Bøgsted

in undecidability issues for the traditional model checking approaches. Statistical model checking has proven itself a valuable supplement to model checking and this thesis is concerned with extending this software validation technique to stochastic hybrid systems. The thesis consists of two parts: the first part...... motivates why existing model checking technology should be supplemented by new techniques. It also contains a brief introduction to probability theory and concepts covered by the six papers making up the second part. The first two papers are concerned with developing online monitoring techniques...... systems. The fifth paper shows how stochastic hybrid automata are useful for modelling biological systems and the final paper is concerned with showing how statistical model checking is efficiently distributed. In parallel with developing the theory contained in the papers, a substantial part of this work...

Statistical Modelling of Wind Proles - Data Analysis and Modelling

DEFF Research Database (Denmark)

Jónsson, Tryggvi; Pinson, Pierre

The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....

Brownian motion or Lévy walk? Stepping towards an extended statistical mechanics for animal locomotion.

Science.gov (United States)

Gautestad, Arild O

2012-09-07

Animals moving under the influence of spatio-temporal scaling and long-term memory generate a kind of space-use pattern that has proved difficult to model within a coherent theoretical framework. An extended kind of statistical mechanics is needed, accounting for both the effects of spatial memory and scale-free space use, and put into a context of ecological conditions. Simulations illustrating the distinction between scale-specific and scale-free locomotion are presented. The results show how observational scale (time lag between relocations of an individual) may critically influence the interpretation of the underlying process. In this respect, a novel protocol is proposed as a method to distinguish between some main movement classes. For example, the 'power law in disguise' paradox-from a composite Brownian motion consisting of a superposition of independent movement processes at different scales-may be resolved by shifting the focus from pattern analysis at one particular temporal resolution towards a more process-oriented approach involving several scales of observation. A more explicit consideration of system complexity within a statistical mechanical framework, supplementing the more traditional mechanistic modelling approach, is advocated.

Skewed factor models using selection mechanisms

KAUST Repository

Kim, Hyoung-Moon

2015-12-21

Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

Skewed factor models using selection mechanisms

KAUST Repository

Kim, Hyoung-Moon; Maadooliat, Mehdi; Arellano-Valle, Reinaldo B.; Genton, Marc G.

2015-01-01

Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

Statistical physics of pairwise probability models

DEFF Research Database (Denmark)

Roudi, Yasser; Aurell, Erik; Hertz, John

2009-01-01

(dansk abstrakt findes ikke) Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of  data......: knowledge of the means and correlations between pairs of elements in the system is sufficient. Not surprisingly, then, using pairwise models for studying neural data has been the focus of many studies in recent years. In this paper, we describe how tools from statistical physics can be employed for studying...

Spatio-temporal statistical models with applications to atmospheric processes

International Nuclear Information System (INIS)

Wikle, C.K.

1996-01-01

This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model

The nano-mechanical signature of Ultra High Performance Concrete by statistical nanoindentation techniques

International Nuclear Information System (INIS)

Sorelli, Luca; Constantinides, Georgios; Ulm, Franz-Josef; Toutlemonde, Francois

2008-01-01

Advances in engineering the microstructure of cementitious composites have led to the development of fiber reinforced Ultra High Performance Concretes (UHPC). The scope of this paper is twofold, first to characterize the nano-mechanical properties of the phases governing the UHPC microstructure by means of a novel statistical nanoindentation technique; then to upscale those nanoscale properties, by means of continuum micromechanics, to the macroscopic scale of engineering applications. In particular, a combined investigation of nanoindentation, scanning electron microscope (SEM) and X-ray Diffraction (XRD) indicates that the fiber-matrix transition zone is relatively defect free. On this basis, a four-level multiscale model with defect free interfaces allows to accurately determine the composite stiffness from the measured nano-mechanical properties. Besides evidencing the dominant role of high density calcium silicate hydrates and the stiffening effect of residual clinker, the suggested model may become a useful tool for further optimizing cement-based engineered composites

Alternative derivations of the statistical mechanical distribution laws.

Science.gov (United States)

Wall, F T

1971-08-01

A new approach is presented for the derivation of statistical mechanical distribution laws. The derivations are accomplished by minimizing the Helmholtz free energy under constant temperature and volume, instead of maximizing the entropy under constant energy and volume. An alternative method involves stipulating equality of chemical potential, or equality of activity, for particles in different energy levels. This approach leads to a general statement of distribution laws applicable to all systems for which thermodynamic probabilities can be written. The methods also avoid use of the calculus of variations, Lagrangian multipliers, and Stirling's approximation for the factorial. The results are applied specifically to Boltzmann, Fermi-Dirac, and Bose-Einstein statistics. The special significance of chemical potential and activity is discussed for microscopic systems.

Algebraic methods in statistical mechanics and quantum field theory

CERN Document Server

Emch, Dr Gérard G

2009-01-01

This systematic algebraic approach concerns problems involving a large number of degrees of freedom. It extends the traditional formalism of quantum mechanics, and it eliminates conceptual and mathematical difficulties common to the development of statistical mechanics and quantum field theory. Further, the approach is linked to research in applied and pure mathematics, offering a reflection of the interplay between formulation of physical motivations and self-contained descriptions of the mathematical methods.The four-part treatment begins with a survey of algebraic approaches to certain phys

Geometry and topology in hamiltonian dynamics and statistical mechanics

CERN Document Server

Pettini, Marco

2007-01-01

Explores the foundations of hamiltonian dynamical systems and statistical mechanics, in particular phase transitions, from the point of view of geometry and topology. This book provides an overview of the research in the area. Using geometrical thinking to solve fundamental problems in these areas could be highly productive

Fractional statistics and quantum theory

CERN Document Server

Khare, Avinash

1997-01-01

This book explains the subtleties of quantum statistical mechanics in lower dimensions and their possible ramifications in quantum theory. The discussion is at a pedagogical level and is addressed to both graduate students and advanced research workers with a reasonable background in quantum and statistical mechanics. The main emphasis will be on explaining new concepts. Topics in the first part of the book includes the flux tube model of anyons, the braid group and quantum and statistical mechanics of noninteracting anyon gas. The second part of the book provides a detailed discussion about f

Multiscale Monte Carlo algorithms in statistical mechanics and quantum field theory

Energy Technology Data Exchange (ETDEWEB)

Lauwers, P G

1990-12-01

Conventional Monte Carlo simulation algorithms for models in statistical mechanics and quantum field theory are afflicted by problems caused by their locality. They become highly inefficient if investigations of critical or nearly-critical systems, i.e., systems with important large scale phenomena, are undertaken. We present two types of multiscale approaches that alleveate problems of this kind: Stochastic cluster algorithms and multigrid Monte Carlo simulation algorithms. Another formidable computational problem in simulations of phenomenologically relevant field theories with fermions is the need for frequently inverting the Dirac operator. This inversion can be accelerated considerably by means of deterministic multigrid methods, very similar to the ones used for the numerical solution of differential equations. (orig.).

Statistical Physics An Introduction

CERN Document Server

Yoshioka, Daijiro

2007-01-01

This book provides a comprehensive presentation of the basics of statistical physics. The first part explains the essence of statistical physics and how it provides a bridge between microscopic and macroscopic phenomena, allowing one to derive quantities such as entropy. Here the author avoids going into details such as Liouville’s theorem or the ergodic theorem, which are difficult for beginners and unnecessary for the actual application of the statistical mechanics. In the second part, statistical mechanics is applied to various systems which, although they look different, share the same mathematical structure. In this way readers can deepen their understanding of statistical physics. The book also features applications to quantum dynamics, thermodynamics, the Ising model and the statistical dynamics of free spins.

Statistical mechanics of budget-constrained auctions

International Nuclear Information System (INIS)

Altarelli, F; Braunstein, A; Realpe-Gomez, J; Zecchina, R

2009-01-01

Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being in the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). On the basis of the cavity method of statistical mechanics, we introduce a message-passing algorithm that is capable of solving efficiently random instances of the problem extracted from a natural distribution, and we derive from its properties the phase diagram of the problem. As the control parameter (average value of the budgets) is varied, we find two phase transitions delimiting a region in which long-range correlations arise

Statistical mechanics of budget-constrained auctions

Science.gov (United States)

Altarelli, F.; Braunstein, A.; Realpe-Gomez, J.; Zecchina, R.

2009-07-01

Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being in the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). On the basis of the cavity method of statistical mechanics, we introduce a message-passing algorithm that is capable of solving efficiently random instances of the problem extracted from a natural distribution, and we derive from its properties the phase diagram of the problem. As the control parameter (average value of the budgets) is varied, we find two phase transitions delimiting a region in which long-range correlations arise.

SRB states and nonequilibrium statistical mechanics close to equilibrium

OpenAIRE

Gallavotti, Giovannni; Ruelle, David

1996-01-01

Nonequilibrium statistical mechanics close to equilibrium is studied using SRB states and a formula for their derivatives with respect to parameters. We write general expressions for the thermodynamic fluxes (or currents) and the transport coefficients, generalizing previous results. In this framework we give a general proof of the Onsager reciprocity relations.

Uncertainty the soul of modeling, probability & statistics

CERN Document Server

Briggs, William

2016-01-01

This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance". The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, suc...

Thermodynamics and statistical mechanics an integrated approach

CERN Document Server

Hardy, Robert J

2014-01-01

This textbook brings together the fundamentals of the macroscopic and microscopic aspects of thermal physics by presenting thermodynamics and statistical mechanics as complementary theories based on small numbers of postulates. The book is designed to give the instructor flexibility in structuring courses for advanced undergraduates and/or beginning graduate students and is written on the principle that a good text should also be a good reference. The presentation of thermodynamics follows the logic of Clausius and Kelvin while relating the concepts involved to familiar phenomena and the mod

Statistical mechanics out of equilibrium the irreversibility

International Nuclear Information System (INIS)

Alvarez Estrada, R. F.

2001-01-01

A Round Table about the issue of Irreversibility and related matters has taken place during the last (20th) Statistical Mechanics Conference, held in Paris (July 1998). This article tries to provide a view (necessarily limited, and hence, uncompleted) of some approaches to the subject: the one based upon deterministic chaos (which is currently giving rise to a very active research) and the classical interpretation due to Boltzmann. An attempt has been made to write this article in a self-contained way, and to avoid a technical presentation wherever possible. (Author) 29 refs

Statistical modeling of the response characteristics of mechanosensitive stimuli in the human esophagus

DEFF Research Database (Denmark)

Drewes, A.M.; Reddy, H.; Staahl, C.

2005-01-01

by using a statistical model based on correlation analysis. The esophagus was distended with a bag in 32 healthy subjects by using an inflation rate of 25 mL/min. The luminal cross-sectional areas and sensory ratings were determined during the distentions. The stimuli were repeated after relaxation...... of mechanical gut stimuli in human beings. This might increase our understanding of visceral pain in health and disease and guide the statistical analysis of experimental data obtained in the gastrointestinal tract....

Statistical Models for Social Networks

NARCIS (Netherlands)

Snijders, Tom A. B.; Cook, KS; Massey, DS

2011-01-01

Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

Functional summary statistics for the Johnson-Mehl model

DEFF Research Database (Denmark)

Møller, Jesper; Ghorbani, Mohammad

The Johnson-Mehl germination-growth model is a spatio-temporal point process model which among other things have been used for the description of neurotransmitters datasets. However, for such datasets parametric Johnson-Mehl models fitted by maximum likelihood have yet not been evaluated by means...... of functional summary statistics. This paper therefore invents four functional summary statistics adapted to the Johnson-Mehl model, with two of them based on the second-order properties and the other two on the nuclei-boundary distances for the associated Johnson-Mehl tessellation. The functional summary...... statistics theoretical properties are investigated, non-parametric estimators are suggested, and their usefulness for model checking is examined in a simulation study. The functional summary statistics are also used for checking fitted parametric Johnson-Mehl models for a neurotransmitters dataset....

Statistical limitations in functional neuroimaging. I. Non-inferential methods and statistical models.

Science.gov (United States)

Petersson, K M; Nichols, T E; Poline, J B; Holmes, A P

1999-01-01

Functional neuroimaging (FNI) provides experimental access to the intact living brain making it possible to study higher cognitive functions in humans. In this review and in a companion paper in this issue, we discuss some common methods used to analyse FNI data. The emphasis in both papers is on assumptions and limitations of the methods reviewed. There are several methods available to analyse FNI data indicating that none is optimal for all purposes. In order to make optimal use of the methods available it is important to know the limits of applicability. For the interpretation of FNI results it is also important to take into account the assumptions, approximations and inherent limitations of the methods used. This paper gives a brief overview over some non-inferential descriptive methods and common statistical models used in FNI. Issues relating to the complex problem of model selection are discussed. In general, proper model selection is a necessary prerequisite for the validity of the subsequent statistical inference. The non-inferential section describes methods that, combined with inspection of parameter estimates and other simple measures, can aid in the process of model selection and verification of assumptions. The section on statistical models covers approaches to global normalization and some aspects of univariate, multivariate, and Bayesian models. Finally, approaches to functional connectivity and effective connectivity are discussed. In the companion paper we review issues related to signal detection and statistical inference. PMID:10466149

Predicting tube repair at French nuclear steam generators using statistical modeling

Energy Technology Data Exchange (ETDEWEB)

Mathon, C., E-mail: cedric.mathon@edf.fr [EDF Generation, Basic Design Department (SEPTEN), 69628 Villeurbanne (France); Chaudhary, A. [EDF Generation, Basic Design Department (SEPTEN), 69628 Villeurbanne (France); Gay, N.; Pitner, P. [EDF Generation, Nuclear Operation Division (UNIE), Saint-Denis (France)

2014-04-01

Electricité de France (EDF) currently operates a total of 58 Nuclear Pressurized Water Reactors (PWR) which are composed of 34 units of 900 MWe, 20 units of 1300 MWe and 4 units of 1450 MWe. This report provides an overall status of SG tube bundles on the 1300 MWe units. These units are 4 loop reactors using the AREVA 68/19 type SG model which are equipped either with Alloy 600 thermally treated (TT) tubes or Alloy 690 TT tubes. As of 2011, the effective full power years of operation (EFPY) ranges from 13 to 20 and during this time, the main degradation mechanisms observed on SG tubes are primary water stress corrosion cracking (PWSCC) and wear at anti-vibration bars (AVB) level. Statistical models have been developed for each type of degradation in order to predict the growth rate and number of affected tubes. Additional plugging is also performed to prevent other degradations such as tube wear due to foreign objects or high-cycle flow-induced fatigue. The contribution of these degradation mechanisms on the rate of tube plugging is described. The results from the statistical models are then used in predicting the long-term life of the steam generators and therefore providing a useful tool toward their effective life management and possible replacement.

Distributions with given marginals and statistical modelling

CERN Document Server

Fortiana, Josep; Rodriguez-Lallena, José

2002-01-01

This book contains a selection of the papers presented at the meeting `Distributions with given marginals and statistical modelling', held in Barcelona (Spain), July 17-20, 2000. In 24 chapters, this book covers topics such as the theory of copulas and quasi-copulas, the theory and compatibility of distributions, models for survival distributions and other well-known distributions, time series, categorical models, definition and estimation of measures of dependence, monotonicity and stochastic ordering, shape and separability of distributions, hidden truncation models, diagonal families, orthogonal expansions, tests of independence, and goodness of fit assessment. These topics share the use and properties of distributions with given marginals, this being the fourth specialised text on this theme. The innovative aspect of the book is the inclusion of statistical aspects such as modelling, Bayesian statistics, estimation, and tests.

Statistical mechanics of few-particle systems: exact results for two useful models

Science.gov (United States)

Miranda, Enrique N.

2017-11-01

The statistical mechanics of small clusters (n ˜ 10-50 elements) of harmonic oscillators and two-level systems is studied exactly, following the microcanonical, canonical and grand canonical formalisms. For clusters with several hundred particles, the results from the three formalisms coincide with those found in the thermodynamic limit. However, for clusters formed by a few tens of elements, the three ensembles yield different results. For a cluster with a few tens of harmonic oscillators, when the heat capacity per oscillator is evaluated within the canonical formalism, it reaches a limit value equal to k B , as in the thermodynamic case, while within the microcanonical formalism the limit value is k B (1-1/n). This difference could be measured experimentally. For a cluster with a few tens of two-level systems, the heat capacity evaluated within the canonical and microcanonical ensembles also presents differences that could be detected experimentally. Both the microcanonical and grand canonical formalism show that the entropy is non-additive for systems this small, while the canonical ensemble reaches the opposite conclusion. These results suggest that the microcanonical ensemble is the most appropriate for dealing with systems with tens of particles.

Derivation of some new distributions in statistical mechanics using maximum entropy approach

Directory of Open Access Journals (Sweden)

Ray Amritansu

2014-01-01

Full Text Available The maximum entropy principle has been earlier used to derive the Bose Einstein(B.E., Fermi Dirac(F.D. & Intermediate Statistics(I.S. distribution of statistical mechanics. The central idea of these distributions is to predict the distribution of the microstates, which are the particle of the system, on the basis of the knowledge of some macroscopic data. The latter information is specified in the form of some simple moment constraints. One distribution differs from the other in the way in which the constraints are specified. In the present paper, we have derived some new distributions similar to B.E., F.D. distributions of statistical mechanics by using maximum entropy principle. Some proofs of B.E. & F.D. distributions are shown, and at the end some new results are discussed.

Actuarial statistics with generalized linear mixed models

NARCIS (Netherlands)

Antonio, K.; Beirlant, J.

2007-01-01

Over the last decade the use of generalized linear models (GLMs) in actuarial statistics has received a lot of attention, starting from the actuarial illustrations in the standard text by McCullagh and Nelder [McCullagh, P., Nelder, J.A., 1989. Generalized linear models. In: Monographs on Statistics

Moral foundations in an interacting neural networks society: A statistical mechanics analysis

Science.gov (United States)

Vicente, R.; Susemihl, A.; Jericó, J. P.; Caticha, N.

2014-04-01

The moral foundations theory supports that people, across cultures, tend to consider a small number of dimensions when classifying issues on a moral basis. The data also show that the statistics of weights attributed to each moral dimension is related to self-declared political affiliation, which in turn has been connected to cognitive learning styles by the recent literature in neuroscience and psychology. Inspired by these data, we propose a simple statistical mechanics model with interacting neural networks classifying vectors and learning from members of their social neighbourhood about their average opinion on a large set of issues. The purpose of learning is to reduce dissension among agents when disagreeing. We consider a family of learning algorithms parametrized by δ, that represents the importance given to corroborating (same sign) opinions. We define an order parameter that quantifies the diversity of opinions in a group with homogeneous learning style. Using Monte Carlo simulations and a mean field approximation we find the relation between the order parameter and the learning parameter δ at a temperature we associate with the importance of social influence in a given group. In concordance with data, groups that rely more strongly on corroborating evidence sustain less opinion diversity. We discuss predictions of the model and propose possible experimental tests.

Structured statistical models of inductive reasoning.

Science.gov (United States)

Kemp, Charles; Tenenbaum, Joshua B

2009-01-01

Everyday inductive inferences are often guided by rich background knowledge. Formal models of induction should aim to incorporate this knowledge and should explain how different kinds of knowledge lead to the distinctive patterns of reasoning found in different inductive contexts. This article presents a Bayesian framework that attempts to meet both goals and describes [corrected] 4 applications of the framework: a taxonomic model, a spatial model, a threshold model, and a causal model. Each model makes probabilistic inferences about the extensions of novel properties, but the priors for the 4 models are defined over different kinds of structures that capture different relationships between the categories in a domain. The framework therefore shows how statistical inference can operate over structured background knowledge, and the authors argue that this interaction between structure and statistics is critical for explaining the power and flexibility of human reasoning.

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

Science.gov (United States)

Pohorille, Andrew

2006-01-01

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described

Statistical models of a gas diffusion electrode: II. Current resistent

Energy Technology Data Exchange (ETDEWEB)

Proksch, D B; Winsel, O W

1965-07-01

The authors describe an apparatus for measuring the flow resistance of gas diffusion electrodes which is a mechanical analog of the Wheatstone bridge for measuring electric resistance. The flow resistance of a circular DSK electrode sheet, consisting of two covering layers and a working layer between them, was measured as a function of the gas pressure. While the pressure first was increased and then decreased, a hysteresis occurred, which is discussed and explained by a statistical model of a porous electrode.

What's statistical about learning? Insights from modelling statistical learning as a set of memory processes.

Science.gov (United States)

Thiessen, Erik D

2017-01-05

Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik

Statistical modelling in biostatistics and bioinformatics selected papers

CERN Document Server

Peng, Defen

2014-01-01

This book presents selected papers on statistical model development related mainly to the fields of Biostatistics and Bioinformatics. The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling. Innovations in statistical modelling are presented throughout each of the four areas, with some intriguing new ideas on hierarchical generalized non-linear models and on frailty models with structural dispersion, just to mention two examples. The contributors include distinguished international statisticians such as Philip Hougaard, John Hinde, Il Do Ha, Roger Payne and Alessandra Durio, among others, as well as promising newcomers. Some of the contributions have come from researchers working in the BIO-SI research programme on Biostatistics and Bioinformatics, centred on the Universities of Limerick and Galway in Ireland and fu...

Universal biology and the statistical mechanics of early life

Science.gov (United States)

Goldenfeld, Nigel; Biancalani, Tommaso; Jafarpour, Farshid

2017-11-01

All known life on the Earth exhibits at least two non-trivial common features: the canonical genetic code and biological homochirality, both of which emerged prior to the Last Universal Common Ancestor state. This article describes recent efforts to provide a narrative of this epoch using tools from statistical mechanics. During the emergence of self-replicating life far from equilibrium in a period of chemical evolution, minimal models of autocatalysis show that homochirality would have necessarily co-evolved along with the efficiency of early-life self-replicators. Dynamical system models of the evolution of the genetic code must explain its universality and its highly refined error-minimization properties. These have both been accounted for in a scenario where life arose from a collective, networked phase where there was no notion of species and perhaps even individuality itself. We show how this phase ultimately terminated during an event sometimes known as the Darwinian transition, leading to the present epoch of tree-like vertical descent of organismal lineages. These examples illustrate concrete examples of universal biology: the quest for a fundamental understanding of the basic properties of living systems, independent of precise instantiation in chemistry or other media. This article is part of the themed issue 'Reconceptualizing the origins of life'.

A generalized statistical model for the size distribution of wealth

International Nuclear Information System (INIS)

Clementi, F; Gallegati, M; Kaniadakis, G

2012-01-01

In a recent paper in this journal (Clementi et al 2009 J. Stat. Mech. P02037), we proposed a new, physically motivated, distribution function for modeling individual incomes, having its roots in the framework of the κ-generalized statistical mechanics. The performance of the κ-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the US household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature. (paper)

A generalized statistical model for the size distribution of wealth

Science.gov (United States)

Clementi, F.; Gallegati, M.; Kaniadakis, G.

2012-12-01

In a recent paper in this journal (Clementi et al 2009 J. Stat. Mech. P02037), we proposed a new, physically motivated, distribution function for modeling individual incomes, having its roots in the framework of the κ-generalized statistical mechanics. The performance of the κ-generalized distribution was checked against real data on personal income for the United States in 2003. In this paper we extend our previous model so as to be able to account for the distribution of wealth. Probabilistic functions and inequality measures of this generalized model for wealth distribution are obtained in closed form. In order to check the validity of the proposed model, we analyze the US household wealth distributions from 1984 to 2009 and conclude an excellent agreement with the data that is superior to any other model already known in the literature.

An accurate behavioral model for single-photon avalanche diode statistical performance simulation

Science.gov (United States)

Xu, Yue; Zhao, Tingchen; Li, Ding

2018-01-01

An accurate behavioral model is presented to simulate important statistical performance of single-photon avalanche diodes (SPADs), such as dark count and after-pulsing noise. The derived simulation model takes into account all important generation mechanisms of the two kinds of noise. For the first time, thermal agitation, trap-assisted tunneling and band-to-band tunneling mechanisms are simultaneously incorporated in the simulation model to evaluate dark count behavior of SPADs fabricated in deep sub-micron CMOS technology. Meanwhile, a complete carrier trapping and de-trapping process is considered in afterpulsing model and a simple analytical expression is derived to estimate after-pulsing probability. In particular, the key model parameters of avalanche triggering probability and electric field dependence of excess bias voltage are extracted from Geiger-mode TCAD simulation and this behavioral simulation model doesn't include any empirical parameters. The developed SPAD model is implemented in Verilog-A behavioral hardware description language and successfully operated on commercial Cadence Spectre simulator, showing good universality and compatibility. The model simulation results are in a good accordance with the test data, validating high simulation accuracy.

Statistical mechanics of binary mixture adsorption in metal-organic frameworks in the osmotic ensemble

Science.gov (United States)

Dunne, Lawrence J.; Manos, George

2018-03-01

Although crucial for designing separation processes little is known experimentally about multi-component adsorption isotherms in comparison with pure single components. Very few binary mixture adsorption isotherms are to be found in the literature and information about isotherms over a wide range of gas-phase composition and mechanical pressures and temperature is lacking. Here, we present a quasi-one-dimensional statistical mechanical model of binary mixture adsorption in metal-organic frameworks (MOFs) treated exactly by a transfer matrix method in the osmotic ensemble. The experimental parameter space may be very complex and investigations into multi-component mixture adsorption may be guided by theoretical insights. The approach successfully models breathing structural transitions induced by adsorption giving a good account of the shape of adsorption isotherms of CO2 and CH4 adsorption in MIL-53(Al). Binary mixture isotherms and co-adsorption-phase diagrams are also calculated and found to give a good description of the experimental trends in these properties and because of the wide model parameter range which reproduces this behaviour suggests that this is generic to MOFs. Finally, a study is made of the influence of mechanical pressure on the shape of CO2 and CH4 adsorption isotherms in MIL-53(Al). Quite modest mechanical pressures can induce significant changes to isotherm shapes in MOFs with implications for binary mixture separation processes. This article is part of the theme issue `Modern theoretical chemistry'.

Statistical mechanical perturbation theory of solid-vapor interfacial free energy

NARCIS (Netherlands)

Kalikmanov, Vitalij Iosifovitsj; Hagmeijer, Rob; Venner, Cornelis H.

2017-01-01

The solid–vapor interfacial free energy γsv plays an important role in a number of physical phenomena, such as adsorption, wetting, and adhesion. We propose a closed form expression for the orientation averaged value of this quantity using a statistical mechanical perturbation approach developed in

Statistical Mechanical Perturbation Theory of Solid−Vapor Interfacial Free Energy

NARCIS (Netherlands)

Kalikmanov, V.I.; Hagmeijer, R.; Venner, C.H.

2017-01-01

The solid–vapor interfacial free energy γsv plays an important role in a number of physical phenomena, such as adsorption, wetting, and adhesion. We propose a closed form expression for the orientation averaged value of this quantity using a statistical mechanical perturbation approach developed in

New statistical potential for quality assessment of protein models and a survey of energy functions

Directory of Open Access Journals (Sweden)

Rykunov Dmitry

2010-03-01

Full Text Available Abstract Background Scoring functions, such as molecular mechanic forcefields and statistical potentials are fundamentally important tools in protein structure modeling and quality assessment. Results The performances of a number of publicly available scoring functions are compared with a statistical rigor, with an emphasis on knowledge-based potentials. We explored the effect on accuracy of alternative choices for representing interaction center types and other features of scoring functions, such as using information on solvent accessibility, on torsion angles, accounting for secondary structure preferences and side chain orientation. Partially based on the observations made, we present a novel residue based statistical potential, which employs a shuffled reference state definition and takes into account the mutual orientation of residue side chains. Atom- and residue-level statistical potentials and Linux executables to calculate the energy of a given protein proposed in this work can be downloaded from http://www.fiserlab.org/potentials. Conclusions Among the most influential terms we observed a critical role of a proper reference state definition and the benefits of including information about the microenvironment of interaction centers. Molecular mechanical potentials were also tested and found to be over-sensitive to small local imperfections in a structure, requiring unfeasible long energy relaxation before energy scores started to correlate with model quality.

Modeling and forecasting energy consumption for heterogeneous buildings using a physical–statistical approach

International Nuclear Information System (INIS)

Lü, Xiaoshu; Lu, Tao; Kibert, Charles J.; Viljanen, Martti

2015-01-01

Highlights: • This paper presents a new modeling method to forecast energy demands. • The model is based on physical–statistical approach to improving forecast accuracy. • A new method is proposed to address the heterogeneity challenge. • Comparison with measurements shows accurate forecasts of the model. • The first physical–statistical/heterogeneous building energy modeling approach is proposed and validated. - Abstract: Energy consumption forecasting is a critical and necessary input to planning and controlling energy usage in the building sector which accounts for 40% of the world’s energy use and the world’s greatest fraction of greenhouse gas emissions. However, due to the diversity and complexity of buildings as well as the random nature of weather conditions, energy consumption and loads are stochastic and difficult to predict. This paper presents a new methodology for energy demand forecasting that addresses the heterogeneity challenges in energy modeling of buildings. The new method is based on a physical–statistical approach designed to account for building heterogeneity to improve forecast accuracy. The physical model provides a theoretical input to characterize the underlying physical mechanism of energy flows. Then stochastic parameters are introduced into the physical model and the statistical time series model is formulated to reflect model uncertainties and individual heterogeneity in buildings. A new method of model generalization based on a convex hull technique is further derived to parameterize the individual-level model parameters for consistent model coefficients while maintaining satisfactory modeling accuracy for heterogeneous buildings. The proposed method and its validation are presented in detail for four different sports buildings with field measurements. The results show that the proposed methodology and model can provide a considerable improvement in forecasting accuracy

A Stochastic Fractional Dynamics Model of Rainfall Statistics

Science.gov (United States)

Kundu, Prasun; Travis, James

2013-04-01

Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, that allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is designed to faithfully reflect the scale dependence and is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and times scales. The main restriction is the assumption that the statistics of the precipitation field is spatially homogeneous and isotropic and stationary in time. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and in Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to the second moment statistics of the radar data. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well without any further adjustment. Some data sets containing periods of non-stationary behavior that involves occasional anomalously correlated rain events, present a challenge for the model.

Statistical mechanics of human resource allocation

Science.gov (United States)

Inoue, Jun-Ichi; Chen, He

2014-03-01

We provide a mathematical platform to investigate the network topology of agents, say, university graduates who are looking for their positions in labor markets. The basic model is described by the so-called Potts spin glass which is well-known in the research field of statistical physics. In the model, each Potts spin (a tiny magnet in atomic scale length) represents the action of each student, and it takes a discrete variable corresponding to the company he/she applies for. We construct the energy to include three distinct effects on the students' behavior, namely, collective effect, market history and international ranking of companies. In this model system, the correlations (the adjacent matrix) between students are taken into account through the pairwise spin-spin interactions. We carry out computer simulations to examine the efficiency of the model. We also show that some chiral representation of the Potts spin enables us to obtain some analytical insights into our labor markets. This work was financially supported by Grant-in-Aid for Scientific Research (C) of Japan Society for the Promotion of Science No. 25330278.

Statistical Models and Methods for Lifetime Data

CERN Document Server

Lawless, Jerald F

2011-01-01

Praise for the First Edition"An indispensable addition to any serious collection on lifetime data analysis and . . . a valuable contribution to the statistical literature. Highly recommended . . ."-Choice"This is an important book, which will appeal to statisticians working on survival analysis problems."-Biometrics"A thorough, unified treatment of statistical models and methods used in the analysis of lifetime data . . . this is a highly competent and agreeable statistical textbook."-Statistics in MedicineThe statistical analysis of lifetime or response time data is a key tool in engineering,

Statistical Model Predictions for p+p and Pb+Pb Collisions at LHC

CERN Document Server

Kraus, I; Oeschler, H; Redlich, K; Wheaton, S

2009-01-01

Particle production in p+p and central Pb+Pb collisions at LHC is discussed in the context of the statistical thermal model. For heavy-ion collisions, predictions of various particle ratios are presented. The sensitivity of several ratios on the temperature and the baryon chemical potential is studied in detail, and some of them, which are particularly appropriate to determine the chemical freeze-out point experimentally, are indicated. Considering elementary interactions on the other hand, we focus on strangeness production and its possible suppression. Extrapolating the thermal parameters to LHC energy, we present predictions of the statistical model for particle yields in p+p collisions. We quantify the strangeness suppression by the correlation volume parameter and discuss its influence on particle production. We propose observables that can provide deeper insight into the mechanism of strangeness production and suppression at LHC.

Topology for Statistical Modeling of Petascale Data

Energy Technology Data Exchange (ETDEWEB)

Pascucci, Valerio [Univ. of Utah, Salt Lake City, UT (United States); Levine, Joshua [Univ. of Utah, Salt Lake City, UT (United States); Gyulassy, Attila [Univ. of Utah, Salt Lake City, UT (United States); Bremer, P. -T. [Univ. of Utah, Salt Lake City, UT (United States)

2013-10-31

Many commonly used algorithms for mathematical analysis do not scale well enough to accommodate the size or complexity of petascale data produced by computational simulations. The primary goal of this project is to develop new mathematical tools that address both the petascale size and uncertain nature of current data. At a high level, the approach of the entire team involving all three institutions is based on the complementary techniques of combinatorial topology and statistical modelling. In particular, we use combinatorial topology to filter out spurious data that would otherwise skew statistical modelling techniques, and we employ advanced algorithms from algebraic statistics to efficiently find globally optimal fits to statistical models. The overall technical contributions can be divided loosely into three categories: (1) advances in the field of combinatorial topology, (2) advances in statistical modelling, and (3) new integrated topological and statistical methods. Roughly speaking, the division of labor between our 3 groups (Sandia Labs in Livermore, Texas A&M in College Station, and U Utah in Salt Lake City) is as follows: the Sandia group focuses on statistical methods and their formulation in algebraic terms, and finds the application problems (and data sets) most relevant to this project, the Texas A&M Group develops new algebraic geometry algorithms, in particular with fewnomial theory, and the Utah group develops new algorithms in computational topology via Discrete Morse Theory. However, we hasten to point out that our three groups stay in tight contact via videconference every 2 weeks, so there is much synergy of ideas between the groups. The following of this document is focused on the contributions that had grater direct involvement from the team at the University of Utah in Salt Lake City.

Statistical models and methods for reliability and survival analysis

CERN Document Server

Couallier, Vincent; Huber-Carol, Catherine; Mesbah, Mounir; Huber -Carol, Catherine; Limnios, Nikolaos; Gerville-Reache, Leo

2013-01-01

Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are related to the work of Professor M. Nikulin in statistics over the past 30 years. The authors gather together various contributions with a broad array of techniques and results, divided into three parts - Statistical Models and Methods, Statistical

Bayesian Statistical Mechanics: Entropy-Enthalpy Compensation and Universal Equation of State at the Tip of Pen

Directory of Open Access Journals (Sweden)

Evgeni B. Starikov

2018-02-01

Full Text Available This work has shown the way to put the formal statistical-mechanical basement under the hotly debated notion of enthalpy-entropy compensation. The possibility of writing down the universal equation of state based upon the statistical mechanics is discussed here.

Applied statistical thermodynamics

CERN Document Server

Lucas, Klaus

1991-01-01

The book guides the reader from the foundations of statisti- cal thermodynamics including the theory of intermolecular forces to modern computer-aided applications in chemical en- gineering and physical chemistry. The approach is new. The foundations of quantum and statistical mechanics are presen- ted in a simple way and their applications to the prediction of fluid phase behavior of real systems are demonstrated. A particular effort is made to introduce the reader to expli- cit formulations of intermolecular interaction models and to show how these models influence the properties of fluid sy- stems. The established methods of statistical mechanics - computer simulation, perturbation theory, and numerical in- tegration - are discussed in a style appropriate for newcom- ers and are extensively applied. Numerous worked examples illustrate how practical calculations should be carried out.

TRACX2: a connectionist autoencoder using graded chunks to model infant visual statistical learning.

Science.gov (United States)

Mareschal, Denis; French, Robert M

2017-01-05

Even newborn infants are able to extract structure from a stream of sensory inputs; yet how this is achieved remains largely a mystery. We present a connectionist autoencoder model, TRACX2, that learns to extract sequence structure by gradually constructing chunks, storing these chunks in a distributed manner across its synaptic weights and recognizing these chunks when they re-occur in the input stream. Chunks are graded rather than all-or-nothing in nature. As chunks are learnt their component parts become more and more tightly bound together. TRACX2 successfully models the data from five experiments from the infant visual statistical learning literature, including tasks involving forward and backward transitional probabilities, low-salience embedded chunk items, part-sequences and illusory items. The model also captures performance differences across ages through the tuning of a single-learning rate parameter. These results suggest that infant statistical learning is underpinned by the same domain-general learning mechanism that operates in auditory statistical learning and, potentially, in adult artificial grammar learning.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).

A Statistical Approach For Modeling Tropical Cyclones. Synthetic Hurricanes Generator Model

Energy Technology Data Exchange (ETDEWEB)

Pasqualini, Donatella [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-05-11

This manuscript brie y describes a statistical ap- proach to generate synthetic tropical cyclone tracks to be used in risk evaluations. The Synthetic Hur- ricane Generator (SynHurG) model allows model- ing hurricane risk in the United States supporting decision makers and implementations of adaptation strategies to extreme weather. In the literature there are mainly two approaches to model hurricane hazard for risk prediction: deterministic-statistical approaches, where the storm key physical parameters are calculated using physi- cal complex climate models and the tracks are usually determined statistically from historical data; and sta- tistical approaches, where both variables and tracks are estimated stochastically using historical records. SynHurG falls in the second category adopting a pure stochastic approach.

Statistical modelling of compression and fatigue damage of unidirectional fiber reinforced composites

DEFF Research Database (Denmark)

Mishnaevsky, Leon; Brøndsted, Povl

2009-01-01

A statistical computational model of strength and damage of unidirectional carbon fiber reinforced composites under compressive and cyclic compressive loading is presented in this paper. The model is developed on the basis of the Budiansky–Fleck fiber kinking condition, continuum damage mechanics...... concept and the Monte-Carlo method. The effects of fiber misalignment variability, fiber clustering, load sharing rules on the damage in composite are studied numerically. It is demonstrated that the clustering of fibers has a negative effect of the damage resistance of a composite. Further, the static...

Model-generated air quality statistics for application in vegetation response models in Alberta

International Nuclear Information System (INIS)

McVehil, G.E.; Nosal, M.

1990-01-01

To test and apply vegetation response models in Alberta, air pollution statistics representative of various parts of the Province are required. At this time, air quality monitoring data of the requisite accuracy and time resolution are not available for most parts of Alberta. Therefore, there exists a need to develop appropriate air quality statistics. The objectives of the work reported here were to determine the applicability of model generated air quality statistics and to develop by modelling, realistic and representative time series of hourly SO 2 concentrations that could be used to generate the statistics demanded by vegetation response models

On the statistical mechanics of species abundance distributions.

Science.gov (United States)

Bowler, Michael G; Kelly, Colleen K

2012-09-01

A central issue in ecology is that of the factors determining the relative abundance of species within a natural community. The proper application of the principles of statistical physics to species abundance distributions (SADs) shows that simple ecological properties could account for the near universal features observed. These properties are (i) a limit on the number of individuals in an ecological guild and (ii) per capita birth and death rates. They underpin the neutral theory of Hubbell (2001), the master equation approach of Volkov et al. (2003, 2005) and the idiosyncratic (extreme niche) theory of Pueyo et al. (2007); they result in an underlying log series SAD, regardless of neutral or niche dynamics. The success of statistical mechanics in this application implies that communities are in dynamic equilibrium and hence that niches must be flexible and that temporal fluctuations on all sorts of scales are likely to be important in community structure. Copyright © 2012 Elsevier Inc. All rights reserved.

Performance modeling, loss networks, and statistical multiplexing

CERN Document Server

Mazumdar, Ravi

2009-01-01

This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I

Equilibration, thermalisation, and the emergence of statistical mechanics in closed quantum systems.

Science.gov (United States)

Gogolin, Christian; Eisert, Jens

2016-05-01

We review selected advances in the theoretical understanding of complex quantum many-body systems with regard to emergent notions of quantum statistical mechanics. We cover topics such as equilibration and thermalisation in pure state statistical mechanics, the eigenstate thermalisation hypothesis, the equivalence of ensembles, non-equilibration dynamics following global and local quenches as well as ramps. We also address initial state independence, absence of thermalisation, and many-body localisation. We elucidate the role played by key concepts for these phenomena, such as Lieb-Robinson bounds, entanglement growth, typicality arguments, quantum maximum entropy principles and the generalised Gibbs ensembles, and quantum (non-)integrability. We put emphasis on rigorous approaches and present the most important results in a unified language.

Hyperparameterization of soil moisture statistical models for North America with Ensemble Learning Models (Elm)

Science.gov (United States)

Steinberg, P. D.; Brener, G.; Duffy, D.; Nearing, G. S.; Pelissier, C.

2017-12-01

Hyperparameterization, of statistical models, i.e. automated model scoring and selection, such as evolutionary algorithms, grid searches, and randomized searches, can improve forecast model skill by reducing errors associated with model parameterization, model structure, and statistical properties of training data. Ensemble Learning Models (Elm), and the related Earthio package, provide a flexible interface for automating the selection of parameters and model structure for machine learning models common in climate science and land cover classification, offering convenient tools for loading NetCDF, HDF, Grib, or GeoTiff files, decomposition methods like PCA and manifold learning, and parallel training and prediction with unsupervised and supervised classification, clustering, and regression estimators. Continuum Analytics is using Elm to experiment with statistical soil moisture forecasting based on meteorological forcing data from NASA's North American Land Data Assimilation System (NLDAS). There Elm is using the NSGA-2 multiobjective optimization algorithm for optimizing statistical preprocessing of forcing data to improve goodness-of-fit for statistical models (i.e. feature engineering). This presentation will discuss Elm and its components, including dask (distributed task scheduling), xarray (data structures for n-dimensional arrays), and scikit-learn (statistical preprocessing, clustering, classification, regression), and it will show how NSGA-2 is being used for automate selection of soil moisture forecast statistical models for North America.

Statistical mechanics in the context of special relativity. II.

Science.gov (United States)

Kaniadakis, G

2005-09-01

The special relativity laws emerge as one-parameter (light speed) generalizations of the corresponding laws of classical physics. These generalizations, imposed by the Lorentz transformations, affect both the definition of the various physical observables (e.g., momentum, energy, etc.), as well as the mathematical apparatus of the theory. Here, following the general lines of [Phys. Rev. E 66, 056125 (2002)], we show that the Lorentz transformations impose also a proper one-parameter generalization of the classical Boltzmann-Gibbs-Shannon entropy. The obtained relativistic entropy permits us to construct a coherent and self-consistent relativistic statistical theory, preserving the main features of the ordinary statistical theory, which is recovered in the classical limit. The predicted distribution function is a one-parameter continuous deformation of the classical Maxwell-Boltzmann distribution and has a simple analytic form, showing power law tails in accordance with the experimental evidence. Furthermore, this statistical mechanics can be obtained as the stationary case of a generalized kinetic theory governed by an evolution equation obeying the H theorem and reproducing the Boltzmann equation of the ordinary kinetics in the classical limit.

Statistical Models of Adaptive Immune populations

Science.gov (United States)

Sethna, Zachary; Callan, Curtis; Walczak, Aleksandra; Mora, Thierry

The availability of large (104-106 sequences) datasets of B or T cell populations from a single individual allows reliable fitting of complex statistical models for naïve generation, somatic selection, and hypermutation. It is crucial to utilize a probabilistic/informational approach when modeling these populations. The inferred probability distributions allow for population characterization, calculation of probability distributions of various hidden variables (e.g. number of insertions), as well as statistical properties of the distribution itself (e.g. entropy). In particular, the differences between the T cell populations of embryonic and mature mice will be examined as a case study. Comparing these populations, as well as proposed mixed populations, provides a concrete exercise in model creation, comparison, choice, and validation.

Tropical geometry of statistical models.

Science.gov (United States)

Pachter, Lior; Sturmfels, Bernd

2004-11-16

This article presents a unified mathematical framework for inference in graphical models, building on the observation that graphical models are algebraic varieties. From this geometric viewpoint, observations generated from a model are coordinates of a point in the variety, and the sum-product algorithm is an efficient tool for evaluating specific coordinates. Here, we address the question of how the solutions to various inference problems depend on the model parameters. The proposed answer is expressed in terms of tropical algebraic geometry. The Newton polytope of a statistical model plays a key role. Our results are applied to the hidden Markov model and the general Markov model on a binary tree.

Multiscale representation of generating and correlation functions for some models of statistical mechanics and quantum field theory

International Nuclear Information System (INIS)

O'Carroll, M.

1993-01-01

The author considers models of statistical mechanics and quantum field theory (in the Euclidean formulation) which are treated using renormalization group methods and where the action is a small perturbation of a quadratic action. The author obtains multiscale formulas for the generating and correlation functions after n renormalization group transformations which bring out the relation with the nth effective action. The author derives and compares the formulas for different RGs. The formulas for correlation functions involve (1) two propagators which are determined by a sequence of approximate wave function renormalization constants and renormalization group operators associated with the decomposition into scales of the quadratic form and (2) field derivatives of the nth effective action. For the case of the block field open-quotes δ-functionclose quotes RG the formulas are especially simple and for asymptotic free theories only the derivatives at zero field are needed; the formulas have been previously used directly to obtain bounds on correlation functions using information obtained from the analysis of effective actions. The simplicity can be traced to an open-quotes orthogonality-of-scalesclose quotes property which follows from an implicit wavelet structure. Other commonly used RGs do not have the open-quotes orthogonality of scalesclose quotes property. 19 refs

Ergodic theory, interpretations of probability and the foundations of statistical mechanics

NARCIS (Netherlands)

van Lith, J.H.

2001-01-01

The traditional use of ergodic theory in the foundations of equilibrium statistical mechanics is that it provides a link between thermodynamic observables and microcanonical probabilities. First of all, the ergodic theorem demonstrates the equality of microcanonical phase averages and infinite time

12th Workshop on Stochastic Models, Statistics and Their Applications

CERN Document Server

Rafajłowicz, Ewaryst; Szajowski, Krzysztof

2015-01-01

This volume presents the latest advances and trends in stochastic models and related statistical procedures. Selected peer-reviewed contributions focus on statistical inference, quality control, change-point analysis and detection, empirical processes, time series analysis, survival analysis and reliability, statistics for stochastic processes, big data in technology and the sciences, statistical genetics, experiment design, and stochastic models in engineering. Stochastic models and related statistical procedures play an important part in furthering our understanding of the challenging problems currently arising in areas of application such as the natural sciences, information technology, engineering, image analysis, genetics, energy and finance, to name but a few. This collection arises from the 12th Workshop on Stochastic Models, Statistics and Their Applications, Wroclaw, Poland.

A Note on Burg’s Modified Entropy in Statistical Mechanics

Directory of Open Access Journals (Sweden)

Amritansu Ray

2016-02-01

Full Text Available Burg’s entropy plays an important role in this age of information euphoria, particularly in understanding the emergent behavior of a complex system such as statistical mechanics. For discrete or continuous variable, maximization of Burg’s Entropy subject to its only natural and mean constraint always provide us a positive density function though the Entropy is always negative. On the other hand, Burg’s modified entropy is a better measure than the standard Burg’s entropy measure since this is always positive and there is no computational problem for small probabilistic values. Moreover, the maximum value of Burg’s modified entropy increases with the number of possible outcomes. In this paper, a premium has been put on the fact that if Burg’s modified entropy is used instead of conventional Burg’s entropy in a maximum entropy probability density (MEPD function, the result yields a better approximation of the probability distribution. An important lemma in basic algebra and a suitable example with tables and graphs in statistical mechanics have been given to illustrate the whole idea appropriately.

Non-Gaussian Closed Form Solutions for Geometric Average Asian Options in the Framework of Non-Extensive Statistical Mechanics

Directory of Open Access Journals (Sweden)

Pan Zhao

2018-01-01

Full Text Available In this paper we consider pricing problems of the geometric average Asian options under a non-Gaussian model, in which the underlying stock price is driven by a process based on non-extensive statistical mechanics. The model can describe the peak and fat tail characteristics of returns. Thus, the description of underlying asset price and the pricing of options are more accurate. Moreover, using the martingale method, we obtain closed form solutions for geometric average Asian options. Furthermore, the numerical analysis shows that the model can avoid underestimating risks relative to the Black-Scholes model.

Growth Curve and Structural Equation Modeling : Topics from the Indian Statistical Institute

CERN Document Server

2015-01-01

This book describes some recent trends in GCM research on different subject areas, both theoretical and applied. This includes tools and possibilities for further work through new techniques and modification of existing ones. A growth curve is an empirical model of the evolution of a quantity over time. Growth curves in longitudinal studies are used in disciplines including biology, statistics, population studies, economics, biological sciences, sociology, nano-biotechnology, and fluid mechanics. The volume includes original studies, theoretical findings and case studies from a wide range of applied work. This volume builds on presentations from a GCM workshop held at the Indian Statistical Institute, Giridih, January 18-19, 2014. This book follows the volume Advances in Growth Curve Models, published by Springer in 2013. The results have meaningful application in health care, prediction of crop yield, child nutrition, poverty measurements, estimation of growth rate, and other research areas.

Statistical Validation of Engineering and Scientific Models: Background

International Nuclear Information System (INIS)

Hills, Richard G.; Trucano, Timothy G.

1999-01-01

A tutorial is presented discussing the basic issues associated with propagation of uncertainty analysis and statistical validation of engineering and scientific models. The propagation of uncertainty tutorial illustrates the use of the sensitivity method and the Monte Carlo method to evaluate the uncertainty in predictions for linear and nonlinear models. Four example applications are presented; a linear model, a model for the behavior of a damped spring-mass system, a transient thermal conduction model, and a nonlinear transient convective-diffusive model based on Burger's equation. Correlated and uncorrelated model input parameters are considered. The model validation tutorial builds on the material presented in the propagation of uncertainty tutoriaI and uses the damp spring-mass system as the example application. The validation tutorial illustrates several concepts associated with the application of statistical inference to test model predictions against experimental observations. Several validation methods are presented including error band based, multivariate, sum of squares of residuals, and optimization methods. After completion of the tutorial, a survey of statistical model validation literature is presented and recommendations for future work are made

Multiple commodities in statistical microeconomics: Model and market

Science.gov (United States)

Baaquie, Belal E.; Yu, Miao; Du, Xin

2016-11-01

A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.

Statistical models for optimizing mineral exploration

International Nuclear Information System (INIS)

Wignall, T.K.; DeGeoffroy, J.

1987-01-01

The primary purpose of mineral exploration is to discover ore deposits. The emphasis of this volume is on the mathematical and computational aspects of optimizing mineral exploration. The seven chapters that make up the main body of the book are devoted to the description and application of various types of computerized geomathematical models. These chapters include: (1) the optimal selection of ore deposit types and regions of search, as well as prospecting selected areas, (2) designing airborne and ground field programs for the optimal coverage of prospecting areas, and (3) delineating and evaluating exploration targets within prospecting areas by means of statistical modeling. Many of these statistical programs are innovative and are designed to be useful for mineral exploration modeling. Examples of geomathematical models are applied to exploring for six main types of base and precious metal deposits, as well as other mineral resources (such as bauxite and uranium)

An analysis of a large dataset on immigrant integration in Spain. The Statistical Mechanics perspective on Social Action

Science.gov (United States)

Barra, Adriano; Contucci, Pierluigi; Sandell, Rickard; Vernia, Cecilia

2014-02-01

How does immigrant integration in a country change with immigration density? Guided by a statistical mechanics perspective we propose a novel approach to this problem. The analysis focuses on classical integration quantifiers such as the percentage of jobs (temporary and permanent) given to immigrants, mixed marriages, and newborns with parents of mixed origin. We find that the average values of different quantifiers may exhibit either linear or non-linear growth on immigrant density and we suggest that social action, a concept identified by Max Weber, causes the observed non-linearity. Using the statistical mechanics notion of interaction to quantitatively emulate social action, a unified mathematical model for integration is proposed and it is shown to explain both growth behaviors observed. The linear theory instead, ignoring the possibility of interaction effects would underestimate the quantifiers up to 30% when immigrant densities are low, and overestimate them as much when densities are high. The capacity to quantitatively isolate different types of integration mechanisms makes our framework a suitable tool in the quest for more efficient integration policies.

Graphene growth process modeling: a physical-statistical approach

Science.gov (United States)

Wu, Jian; Huang, Qiang

2014-09-01

As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.

Statistical physics of pairwise probability models

Directory of Open Access Journals (Sweden)

Yasser Roudi

2009-11-01

Full Text Available Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of data: knowledge of the means and correlations between pairs of elements in the system is sufficient. Not surprisingly, then, using pairwise models for studying neural data has been the focus of many studies in recent years. In this paper, we describe how tools from statistical physics can be employed for studying and using pairwise models. We build on our previous work on the subject and study the relation between different methods for fitting these models and evaluating their quality. In particular, using data from simulated cortical networks we study how the quality of various approximate methods for inferring the parameters in a pairwise model depends on the time bin chosen for binning the data. We also study the effect of the size of the time bin on the model quality itself, again using simulated data. We show that using finer time bins increases the quality of the pairwise model. We offer new ways of deriving the expressions reported in our previous work for assessing the quality of pairwise models.

Usage of a statistical method of designing factorial experiments in the mechanical activation of a complex CuPbZn sulphide concentrate

Directory of Open Access Journals (Sweden)

BalហPeter

2003-09-01

Full Text Available Mechanical activation belongs to innovative procedures which intensify technological processes by creating new surfaces and making a defective structure of solid phase. Mechanical impact on the solid phase is a suitable procedure to ensure the mobility of its structure elements and to accumulate the mechanical energy that is later used in the processes of leaching.The aim of this study was to realize the mechanical activation of a complex CuPbZn sulphide concentrate (Slovak deposit in an attritor by using of statistical methods for the design of factorial experiments and to determine the conditions for preparing the optimum mechanically activated sample of studied concentrate.The following parameters of the attritor were studied as variables:the weight of sample/steel balls (degree of mill filling, the number of revolutions of the milling shaft and the time of mechanical activation. Interpretation of the chosen variables inducing the mechanical activation of the complex CuPbZn concentrate was also carried out by using statistical methods of factorial design experiments. The presented linear model (23 factorial experiment does not support directly the optimum search, therefore this model was extended to the nonlinear model by the utilization of second order ortogonal polynom. This nonlinear model does not describe adequately the process of new surface formation by the mechanical activation of the studied concentrate. It would be necessary to extend the presented nonlinear model to the nonlinear model of the third order or choose another model. In regard to the economy with the aspect of minimal energy input consumption, the sample with the value of 524 kWht-1 and with the maximum value of specific surface area 8.59 m2g-1 (as a response of the factorial experiment was chosen as the optimum mechanically activated sample of the studied concentrate. The optimum mechanically activated sample of the complex CuPbZn sulphide concentrate was prepared

Estimating preferential flow in karstic aquifers using statistical mixed models.

Science.gov (United States)

Anaya, Angel A; Padilla, Ingrid; Macchiavelli, Raul; Vesper, Dorothy J; Meeker, John D; Alshawabkeh, Akram N

2014-01-01

Karst aquifers are highly productive groundwater systems often associated with conduit flow. These systems can be highly vulnerable to contamination, resulting in a high potential for contaminant exposure to humans and ecosystems. This work develops statistical models to spatially characterize flow and transport patterns in karstified limestone and determines the effect of aquifer flow rates on these patterns. A laboratory-scale Geo-HydroBed model is used to simulate flow and transport processes in a karstic limestone unit. The model consists of stainless steel tanks containing a karstified limestone block collected from a karst aquifer formation in northern Puerto Rico. Experimental work involves making a series of flow and tracer injections, while monitoring hydraulic and tracer response spatially and temporally. Statistical mixed models (SMMs) are applied to hydraulic data to determine likely pathways of preferential flow in the limestone units. The models indicate a highly heterogeneous system with dominant, flow-dependent preferential flow regions. Results indicate that regions of preferential flow tend to expand at higher groundwater flow rates, suggesting a greater volume of the system being flushed by flowing water at higher rates. Spatial and temporal distribution of tracer concentrations indicates the presence of conduit-like and diffuse flow transport in the system, supporting the notion of both combined transport mechanisms in the limestone unit. The temporal response of tracer concentrations at different locations in the model coincide with, and confirms the preferential flow distribution generated with the SMMs used in the study. © 2013, National Ground Water Association.

Modeling abundance using N-mixture models: the importance of considering ecological mechanisms.

Science.gov (United States)

Joseph, Liana N; Elkin, Ché; Martin, Tara G; Possinghami, Hugh P

2009-04-01

Predicting abundance across a species' distribution is useful for studies of ecology and biodiversity management. Modeling of survey data in relation to environmental variables can be a powerful method for extrapolating abundances across a species' distribution and, consequently, calculating total abundances and ultimately trends. Research in this area has demonstrated that models of abundance are often unstable and produce spurious estimates, and until recently our ability to remove detection error limited the development of accurate models. The N-mixture model accounts for detection and abundance simultaneously and has been a significant advance in abundance modeling. Case studies that have tested these new models have demonstrated success for some species, but doubt remains over the appropriateness of standard N-mixture models for many species. Here we develop the N-mixture model to accommodate zero-inflated data, a common occurrence in ecology, by employing zero-inflated count models. To our knowledge, this is the first application of this method to modeling count data. We use four variants of the N-mixture model (Poisson, zero-inflated Poisson, negative binomial, and zero-inflated negative binomial) to model abundance, occupancy (zero-inflated models only) and detection probability of six birds in South Australia. We assess models by their statistical fit and the ecological realism of the parameter estimates. Specifically, we assess the statistical fit with AIC and assess the ecological realism by comparing the parameter estimates with expected values derived from literature, ecological theory, and expert opinion. We demonstrate that, despite being frequently ranked the "best model" according to AIC, the negative binomial variants of the N-mixture often produce ecologically unrealistic parameter estimates. The zero-inflated Poisson variant is preferable to the negative binomial variants of the N-mixture, as it models an ecological mechanism rather than a

On application of non—extensive statistical mechanics to studying ecological diversity

International Nuclear Information System (INIS)

Van Xuan, Le; Lan, Nguyen Tri; Viet, Nguyen Ai

2016-01-01

The concept of Tsallis entropy provides an extension of thermodynamics and statistical physics. In the ecology, Tsallis entropy is proposed to be a new class of diversity indices S_q which covers many common diversity indices found in ecological literature. As a new statistical model for the Whittaker plots describing species abundance distribution, the truncated exponential distribution is used to calculate the diversity and evenness indices. The obtained results in new model are graphically compared with those in previous publication in the same field of interests, and shows a good agreement. A further development of a thermodynamic theory of ecological systems that is consistent with entropic approach of statistical physics is motivated. (paper)

Probabilistic-Stochastic Model of Distribution of Physical and Mechanical Properties of Soft Mineral Rocks

Directory of Open Access Journals (Sweden)

O.O. Sdvizhkova

2017-12-01

Full Text Available The physical and mechanical characteristics of soils and soft rocks obtained as a result of laboratory tests are important initial parameters for assessing the stability of natural and artificial slopes. Such properties of rocks as adhesion and the angle of internal friction are due to the influence of a number of natural and technogenic factors. At the same time, from the set of factors influencing the stability of the slope, the most significant ones are singled out, which to a greater extent determine the properties of the rocks. The more factors are taken into account in the geotechnical model, the more closely the properties of the rocks are studied, which increases the accuracy of the scientific forecast of the landslide danger of the slope. On the other hand, an increase in the number of factors involved in the model complicates it and causes a decrease in the reliability of geotechnical calculations. The aim of the work is to construct a statistical distribution of the studied physical and mechanical properties of soft rocks and to substantiate a probabilistic statistical model. Based on the results of laboratory tests of rocks, the statistical distributions of the quantitative traits studied, the angle of internal friction φ and the cohesion, were constructed. It was established that the statistical distribution of physical mechanical properties of rocks is close to a uniform law.

Statistical mechanics, gravity, and Euclidean theory

International Nuclear Information System (INIS)

Fursaev, Dmitri V.

2002-01-01

A review of computations of free energy for Gibbs states on stationary but not static gravitational and gauge backgrounds is given. On these backgrounds wave equations for free fields are reduced to eigenvalue problems which depend non-linearly on the spectral parameter. We present a method to deal with such problems. In particular, we demonstrate how some results of the spectral theory of second-order elliptic operators, such as heat kernel asymptotics, can be extended to a class of non-linear spectral problems. The method is used to trace down the relation between the canonical definition of the free energy based on summation over the modes and the covariant definition given in Euclidean quantum gravity. As an application, high-temperature asymptotics of the free energy and of the thermal part of the stress-energy tensor in the presence of rotation are derived. We also discuss statistical mechanics in the presence of Killing horizons where canonical and Euclidean theories are related in a non-trivial way

Quantum Statistical Mechanics, L-Series and Anabelian Geometry I: Partition Functions

NARCIS (Netherlands)

Marcolli, Matilde; Cornelissen, Gunther

2014-01-01

The zeta function of a number field can be interpreted as the partition function of an associated quantum statistical mechanical (QSM) system, built from abelian class field theory. We introduce a general notion of isomorphism of QSM-systems and prove that it preserves (extremal) KMS equilibrium

Statistical transmutation in doped quantum dimer models.

Science.gov (United States)

Lamas, C A; Ralko, A; Cabra, D C; Poilblanc, D; Pujol, P

2012-07-06

We prove a "statistical transmutation" symmetry of doped quantum dimer models on the square, triangular, and kagome lattices: the energy spectrum is invariant under a simultaneous change of statistics (i.e., bosonic into fermionic or vice versa) of the holes and of the signs of all the dimer resonance loops. This exact transformation enables us to define the duality equivalence between doped quantum dimer Hamiltonians and provides the analytic framework to analyze dynamical statistical transmutations. We investigate numerically the doping of the triangular quantum dimer model with special focus on the topological Z(2) dimer liquid. Doping leads to four (instead of two for the square lattice) inequivalent families of Hamiltonians. Competition between phase separation, superfluidity, supersolidity, and fermionic phases is investigated in the four families.

PREFACE: Counting Complexity: An international workshop on statistical mechanics and combinatorics

Science.gov (United States)

de Gier, Jan; Warnaar, Ole

2006-07-01

On 10-15 July 2005 the conference `Counting Complexity: An international workshop on statistical mechanics and combinatorics' was held on Dunk Island, Queensland, Australia in celebration of Tony Guttmann's 60th birthday. Dunk Island provided the perfect setting for engaging in almost all of Tony's life-long passions: swimming, running, food, wine and, of course, plenty of mathematics and physics. The conference was attended by many of Tony's close scientific friends from all over the world, and most talks were presented by his past and present collaborators. This volume contains the proceedings of the meeting and consists of 24 refereed research papers in the fields of statistical mechanics, condensed matter physics and combinatorics. These papers provide an excellent illustration of the breadth and scope of Tony's work. The very first contribution, written by Stu Whittington, contains an overview of the many scientific achievements of Tony over the past 40 years in mathematics and physics. The organizing committee, consisting of Richard Brak, Aleks Owczarek, Jan de Gier, Emma Lockwood, Andrew Rechnitzer and Ole Warnaar, gratefully acknowledges the Australian Mathematical Society (AustMS), the Australian Mathematical Sciences Institute (AMSI), the ARC Centre of Excellence for Mathematics and Statistics of Complex Systems (MASCOS), the ARC Complex Open Systems Research Network (COSNet), the Institute of Physics (IOP) and the Department of Mathematics and Statistics of The University of Melbourne for financial support in organizing the conference. Tony, we hope that your future years in mathematics will be numerous. Count yourself lucky! Tony Guttman

Textual information access statistical models

CERN Document Server

Gaussier, Eric

2013-01-01

This book presents statistical models that have recently been developed within several research communities to access information contained in text collections. The problems considered are linked to applications aiming at facilitating information access:- information extraction and retrieval;- text classification and clustering;- opinion mining;- comprehension aids (automatic summarization, machine translation, visualization).In order to give the reader as complete a description as possible, the focus is placed on the probability models used in the applications

Statistics and thermodynamics of fracture

Science.gov (United States)

Chudnovsky, A.

1984-01-01

A probabilistic model of the fracture processes unifying the phenomenological study of long term strength of materials, fracture mechanics and statistical approaches to fracture is briefly outlined. The general framework of irreversible thermodynamics is employed to model the deterministic side of the failure phenomenon. The stochastic calculus is used to account for thg failure mechanisms controlled by chance; particularly, the random roughness of fracture surfaces.

Model for neural signaling leap statistics

International Nuclear Information System (INIS)

Chevrollier, Martine; Oria, Marcos

2011-01-01

We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.5 0 C, awaken regime) and Levy statistics (T = 35.5 0 C, sleeping period), characterized by rare events of long range connections.

Model for neural signaling leap statistics

Science.gov (United States)

Chevrollier, Martine; Oriá, Marcos

2011-03-01

We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T = 37.5°C, awaken regime) and Lévy statistics (T = 35.5°C, sleeping period), characterized by rare events of long range connections.

WE-A-201-02: Modern Statistical Modeling

Energy Technology Data Exchange (ETDEWEB)

Niemierko, A.

2016-06-15

Chris Marshall: Memorial Introduction Donald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”. Don developed an interest in chemistry at school by “reading a book” - a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self-taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio-Statistics and Epidemiology Core Unit working in part on a sickle-cell disease. After retirement he remained active as Professor Emeritus. Don served for several years as a consultant to the Nuclear

WE-A-201-02: Modern Statistical Modeling

International Nuclear Information System (INIS)

Niemierko, A.

2016-01-01

Chris Marshall: Memorial Introduction Donald Edmonds Herbert Jr., or Don to his colleagues and friends, exemplified the “big tent” vision of medical physics, specializing in Applied Statistics and Dynamical Systems theory. He saw, more clearly than most, that “Making models is the difference between doing science and just fooling around [ref Woodworth, 2004]”. Don developed an interest in chemistry at school by “reading a book” - a recurring theme in his story. He was awarded a Westinghouse Science scholarship and attended the Carnegie Institute of Technology (later Carnegie Mellon University) where his interest turned to physics and led to a BS in Physics after transfer to Northwestern University. After (voluntary) service in the Navy he earned his MS in Physics from the University of Oklahoma, which led him to Johns Hopkins University in Baltimore to pursue a PhD. The early death of his wife led him to take a salaried position in the Physics Department of Colorado College in Colorado Springs so as to better care for their young daughter. There, a chance invitation from Dr. Juan del Regato to teach physics to residents at the Penrose Cancer Hospital introduced him to Medical Physics, and he decided to enter the field. He received his PhD from the University of London (UK) under Prof. Joseph Rotblat, where I first met him, and where he taught himself statistics. He returned to Penrose as a clinical medical physicist, also largely self-taught. In 1975 he formalized an evolving interest in statistical analysis as Professor of Radiology and Head of the Division of Physics and Statistics at the College of Medicine of the University of South Alabama in Mobile, AL where he remained for the rest of his career. He also served as the first Director of their Bio-Statistics and Epidemiology Core Unit working in part on a sickle-cell disease. After retirement he remained active as Professor Emeritus. Don served for several years as a consultant to the Nuclear

Bayesian models a statistical primer for ecologists

CERN Document Server

Hobbs, N Thompson

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods-in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probabili

From inverse problems to learning: a Statistical Mechanics approach

Science.gov (United States)

Baldassi, Carlo; Gerace, Federica; Saglietti, Luca; Zecchina, Riccardo

2018-01-01

We present a brief introduction to the statistical mechanics approaches for the study of inverse problems in data science. We then provide concrete new results on inferring couplings from sampled configurations in systems characterized by an extensive number of stable attractors in the low temperature regime. We also show how these result are connected to the problem of learning with realistic weak signals in computational neuroscience. Our techniques and algorithms rely on advanced mean-field methods developed in the context of disordered systems.

On the geometry of the spin-statistics connection in quantum mechanics

Energy Technology Data Exchange (ETDEWEB)

Reyes, A.

2006-07-01

The Spin-Statistics theorem states that the statistics of a system of identical particles is determined by their spin: Particles of integer spin are Bosons (i.e. obey Bose-Einstein statistics), whereas particles of half-integer spin are Fermions (i.e. obey Fermi-Dirac statistics). Since the original proof by Fierz and Pauli, it has been known that the connection between Spin and Statistics follows from the general principles of relativistic Quantum Field Theory. In spite of this, there are different approaches to Spin-Statistics and it is not clear whether the theorem holds under assumptions that are different, and even less restrictive, than the usual ones (e.g. Lorentz-covariance). Additionally, in Quantum Mechanics there is a deep relation between indistinguishability and the geometry of the configuration space. This is clearly illustrated by Gibbs' paradox. Therefore, for many years efforts have been made in order to find a geometric proof of the connection between Spin and Statistics. Recently, various proposals have been put forward, in which an attempt is made to derive the Spin-Statistics connection from assumptions different from the ones used in the relativistic, quantum field theoretic proofs. Among these, there is the one due to Berry and Robbins (BR), based on the postulation of a certain single-valuedness condition, that has caused a renewed interest in the problem. In the present thesis, we consider the problem of indistinguishability in Quantum Mechanics from a geometric-algebraic point of view. An approach is developed to study configuration spaces Q having a finite fundamental group, that allows us to describe different geometric structures of Q in terms of spaces of functions on the universal cover of Q. In particular, it is shown that the space of complex continuous functions over the universal cover of Q admits a decomposition into C(Q)-submodules, labelled by the irreducible representations of the fundamental group of Q, that can be

Comparison of Artificial Neural Networks and ARIMA statistical models in simulations of target wind time series

Science.gov (United States)

Kolokythas, Kostantinos; Vasileios, Salamalikis; Athanassios, Argiriou; Kazantzidis, Andreas

2015-04-01

The wind is a result of complex interactions of numerous mechanisms taking place in small or large scales, so, the better knowledge of its behavior is essential in a variety of applications, especially in the field of power production coming from wind turbines. In the literature there is a considerable number of models, either physical or statistical ones, dealing with the problem of simulation and prediction of wind speed. Among others, Artificial Neural Networks (ANNs) are widely used for the purpose of wind forecasting and, in the great majority of cases, outperform other conventional statistical models. In this study, a number of ANNs with different architectures, which have been created and applied in a dataset of wind time series, are compared to Auto Regressive Integrated Moving Average (ARIMA) statistical models. The data consist of mean hourly wind speeds coming from a wind farm on a hilly Greek region and cover a period of one year (2013). The main goal is to evaluate the models ability to simulate successfully the wind speed at a significant point (target). Goodness-of-fit statistics are performed for the comparison of the different methods. In general, the ANN showed the best performance in the estimation of wind speed prevailing over the ARIMA models.

PREFACE: International Workshop on Statistical-Mechanical Informatics 2008 (IW-SMI 2008)

Science.gov (United States)

Hayashi, Masahito; Inoue, Jun-ichi; Kabashima, Yoshiyuki; Tanaka, Kazuyuki

2009-01-01

Statistical mechanical informatics (SMI) is an approach that applies physics to information science, in which many-body problems in information processing are tackled using statistical mechanics methods. In the last decade, the use of SMI has resulted in great advances in research into classical information processing, in particular, theories of information and communications, probabilistic inference and combinatorial optimization problems. It is expected that the success of SMI can be extended to quantum systems. The importance of many-body problems is also being recognized in quantum information theory (QIT), for which quantification of entanglement of bipartite systems has recently been almost completely established after considerable effort. SMI and QIT are sufficiently well developed that it is now appropriate to consider applying SMI to quantum systems and developing many-body theory in QIT. This combination of SMI and QIT is highly likely to contribute significantly to the development of both research fields. The International Workshop on Statistical-Mechanical Informatics has been organized in response to this situation. This workshop, held at Sendai International Conference Center, Sendai, Japan, 14-17 September 2008, and sponsored by the Grant-in-Aid for Scientific Research on Priority Areas `Deepening and Expansion of Statistical Mechanical Informatics (DEX-SMI)' (Head investigator: Yoshiyuki Kabashima, Tokyo Institute of Technology) (Project http://dex-smi.sp.dis.titech.ac.jp/DEX-SMI), was intended to provide leading researchers with strong interdisciplinary interests in QIT and SMI with the opportunity to engage in intensive discussions. The aim of the workshop was to expand SMI to quantum systems and QIT research on quantum (entangled) many-body systems, to discuss possible future directions, and to offer researchers the opportunity to exchange ideas that may lead to joint research initiatives. We would like to thank the contributors of the workshop

Computational and Statistical Models: A Comparison for Policy Modeling of Childhood Obesity

Science.gov (United States)

Mabry, Patricia L.; Hammond, Ross; Ip, Edward Hak-Sing; Huang, Terry T.-K.

As systems science methodologies have begun to emerge as a set of innovative approaches to address complex problems in behavioral, social science, and public health research, some apparent conflicts with traditional statistical methodologies for public health have arisen. Computational modeling is an approach set in context that integrates diverse sources of data to test the plausibility of working hypotheses and to elicit novel ones. Statistical models are reductionist approaches geared towards proving the null hypothesis. While these two approaches may seem contrary to each other, we propose that they are in fact complementary and can be used jointly to advance solutions to complex problems. Outputs from statistical models can be fed into computational models, and outputs from computational models can lead to further empirical data collection and statistical models. Together, this presents an iterative process that refines the models and contributes to a greater understanding of the problem and its potential solutions. The purpose of this panel is to foster communication and understanding between statistical and computational modelers. Our goal is to shed light on the differences between the approaches and convey what kinds of research inquiries each one is best for addressing and how they can serve complementary (and synergistic) roles in the research process, to mutual benefit. For each approach the panel will cover the relevant "assumptions" and how the differences in what is assumed can foster misunderstandings. The interpretations of the results from each approach will be compared and contrasted and the limitations for each approach will be delineated. We will use illustrative examples from CompMod, the Comparative Modeling Network for Childhood Obesity Policy. The panel will also incorporate interactive discussions with the audience on the issues raised here.

Spherical Process Models for Global Spatial Statistics

KAUST Repository

Jeong, Jaehong; Jun, Mikyoung; Genton, Marc G.

2017-01-01

Statistical models used in geophysical, environmental, and climate science applications must reflect the curvature of the spatial domain in global data. Over the past few decades, statisticians have developed covariance models that capture

Model for neural signaling leap statistics

Energy Technology Data Exchange (ETDEWEB)

Chevrollier, Martine; Oria, Marcos, E-mail: oria@otica.ufpb.br [Laboratorio de Fisica Atomica e Lasers Departamento de Fisica, Universidade Federal da ParaIba Caixa Postal 5086 58051-900 Joao Pessoa, Paraiba (Brazil)

2011-03-01

We present a simple model for neural signaling leaps in the brain considering only the thermodynamic (Nernst) potential in neuron cells and brain temperature. We numerically simulated connections between arbitrarily localized neurons and analyzed the frequency distribution of the distances reached. We observed qualitative change between Normal statistics (with T 37.5{sup 0}C, awaken regime) and Levy statistics (T = 35.5{sup 0}C, sleeping period), characterized by rare events of long range connections.

Analysis and Evaluation of Statistical Models for Integrated Circuits Design

Directory of Open Access Journals (Sweden)

Sáenz-Noval J.J.

2011-10-01

Full Text Available Statistical models for integrated circuits (IC allow us to estimate the percentage of acceptable devices in the batch before fabrication. Actually, Pelgrom is the statistical model most accepted in the industry; however it was derived from a micrometer technology, which does not guarantee reliability in nanometric manufacturing processes. This work considers three of the most relevant statistical models in the industry and evaluates their limitations and advantages in analog design, so that the designer has a better criterion to make a choice. Moreover, it shows how several statistical models can be used for each one of the stages and design purposes.

Statistical mechanics of neocortical interactions: Path-integral evolution of short-term memory

Science.gov (United States)

Ingber, Lester

1994-05-01

Previous papers in this series of statistical mechanics of neocortical interactions (SMNI) have detailed a development from the relatively microscopic scales of neurons up to the macroscopic scales as recorded by electroencephalography (EEG), requiring an intermediate mesocolumnar scale to be developed at the scale of minicolumns (~=102 neurons) and macrocolumns (~=105 neurons). Opportunity was taken to view SMNI as sets of statistical constraints, not necessarily describing specific synaptic or neuronal mechanisms, on neuronal interactions, on some aspects of short-term memory (STM), e.g., its capacity, stability, and duration. A recently developed c-language code, pathint, provides a non-Monte Carlo technique for calculating the dynamic evolution of arbitrary-dimension (subject to computer resources) nonlinear Lagrangians, such as derived for the two-variable SMNI problem. Here, pathint is used to explicitly detail the evolution of the SMNI constraints on STM.

The issue of statistical power for overall model fit in evaluating structural equation models

Directory of Open Access Journals (Sweden)

Richard HERMIDA

2015-06-01

Full Text Available Statistical power is an important concept for psychological research. However, examining the power of a structural equation model (SEM is rare in practice. This article provides an accessible review of the concept of statistical power for the Root Mean Square Error of Approximation (RMSEA index of overall model fit in structural equation modeling. By way of example, we examine the current state of power in the literature by reviewing studies in top Industrial-Organizational (I/O Psychology journals using SEMs. Results indicate that in many studies, power is very low, which implies acceptance of invalid models. Additionally, we examined methodological situations which may have an influence on statistical power of SEMs. Results showed that power varies significantly as a function of model type and whether or not the model is the main model for the study. Finally, results indicated that power is significantly related to model fit statistics used in evaluating SEMs. The results from this quantitative review imply that researchers should be more vigilant with respect to power in structural equation modeling. We therefore conclude by offering methodological best practices to increase confidence in the interpretation of structural equation modeling results with respect to statistical power issues.

Understanding and forecasting polar stratospheric variability with statistical models

Directory of Open Access Journals (Sweden)

C. Blume

2012-07-01

Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely the multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. The period from 2005 to 2011 can be hindcasted to a certain extent, where MLP performs significantly better than the remaining models. However, variability remains that cannot be statistically hindcasted within the current framework, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a winter 2011/12 with warm and weak vortex conditions. A vortex breakdown is predicted for late January, early February 2012.

Distinguishing Antimicrobial Models with Different Resistance Mechanisms via Population Pharmacodynamic Modeling.

Directory of Open Access Journals (Sweden)

Matthieu Jacobs

2016-03-01

Full Text Available Semi-mechanistic pharmacokinetic-pharmacodynamic (PK-PD modeling is increasingly used for antimicrobial drug development and optimization of dosage regimens, but systematic simulation-estimation studies to distinguish between competing PD models are lacking. This study compared the ability of static and dynamic in vitro infection models to distinguish between models with different resistance mechanisms and support accurate and precise parameter estimation. Monte Carlo simulations (MCS were performed for models with one susceptible bacterial population without (M1 or with a resting stage (M2, a one population model with adaptive resistance (M5, models with pre-existing susceptible and resistant populations without (M3 or with (M4 inter-conversion, and a model with two pre-existing populations with adaptive resistance (M6. For each model, 200 datasets of the total bacterial population were simulated over 24h using static antibiotic concentrations (256-fold concentration range or over 48h under dynamic conditions (dosing every 12h; elimination half-life: 1h. Twelve-hundred random datasets (each containing 20 curves for static or four curves for dynamic conditions were generated by bootstrapping. Each dataset was estimated by all six models via population PD modeling to compare bias and precision. For M1 and M3, most parameter estimates were unbiased (<10% and had good imprecision (<30%. However, parameters for adaptive resistance and inter-conversion for M2, M4, M5 and M6 had poor bias and large imprecision under static and dynamic conditions. For datasets that only contained viable counts of the total population, common statistical criteria and diagnostic plots did not support sound identification of the true resistance mechanism. Therefore, it seems advisable to quantify resistant bacteria and characterize their MICs and resistance mechanisms to support extended simulations and translate from in vitro experiments to animal infection models and

Improved model for statistical alignment

Energy Technology Data Exchange (ETDEWEB)

Miklos, I.; Toroczkai, Z. (Zoltan)

2001-01-01

The statistical approach to molecular sequence evolution involves the stochastic modeling of the substitution, insertion and deletion processes. Substitution has been modeled in a reliable way for more than three decades by using finite Markov-processes. Insertion and deletion, however, seem to be more difficult to model, and thc recent approaches cannot acceptably deal with multiple insertions and deletions. A new method based on a generating function approach is introduced to describe the multiple insertion process. The presented algorithm computes the approximate joint probability of two sequences in 0(13) running time where 1 is the geometric mean of the sequence lengths.

Daily precipitation statistics in regional climate models

DEFF Research Database (Denmark)

Frei, Christoph; Christensen, Jens Hesselbjerg; Déqué, Michel

2003-01-01

An evaluation is undertaken of the statistics of daily precipitation as simulated by five regional climate models using comprehensive observations in the region of the European Alps. Four limited area models and one variable-resolution global model are considered, all with a grid spacing of 50 km...

An R2 statistic for fixed effects in the linear mixed model.

Science.gov (United States)

Edwards, Lloyd J; Muller, Keith E; Wolfinger, Russell D; Qaqish, Bahjat F; Schabenberger, Oliver

2008-12-20

Statisticians most often use the linear mixed model to analyze Gaussian longitudinal data. The value and familiarity of the R(2) statistic in the linear univariate model naturally creates great interest in extending it to the linear mixed model. We define and describe how to compute a model R(2) statistic for the linear mixed model by using only a single model. The proposed R(2) statistic measures multivariate association between the repeated outcomes and the fixed effects in the linear mixed model. The R(2) statistic arises as a 1-1 function of an appropriate F statistic for testing all fixed effects (except typically the intercept) in a full model. The statistic compares the full model with a null model with all fixed effects deleted (except typically the intercept) while retaining exactly the same covariance structure. Furthermore, the R(2) statistic leads immediately to a natural definition of a partial R(2) statistic. A mixed model in which ethnicity gives a very small p-value as a longitudinal predictor of blood pressure (BP) compellingly illustrates the value of the statistic. In sharp contrast to the extreme p-value, a very small R(2) , a measure of statistical and scientific importance, indicates that ethnicity has an almost negligible association with the repeated BP outcomes for the study.

Mixed deterministic statistical modelling of regional ozone air pollution

KAUST Repository

Kalenderski, Stoitchko

2011-03-17

We develop a physically motivated statistical model for regional ozone air pollution by separating the ground-level pollutant concentration field into three components, namely: transport, local production and large-scale mean trend mostly dominated by emission rates. The model is novel in the field of environmental spatial statistics in that it is a combined deterministic-statistical model, which gives a new perspective to the modelling of air pollution. The model is presented in a Bayesian hierarchical formalism, and explicitly accounts for advection of pollutants, using the advection equation. We apply the model to a specific case of regional ozone pollution-the Lower Fraser valley of British Columbia, Canada. As a predictive tool, we demonstrate that the model vastly outperforms existing, simpler modelling approaches. Our study highlights the importance of simultaneously considering different aspects of an air pollution problem as well as taking into account the physical bases that govern the processes of interest. © 2011 John Wiley & Sons, Ltd..

Quantum statistical mechanics selected works of N N Bogolubov

CERN Document Server

Bogolyubov, N N

2015-01-01

In this book we have solved the complicated problem of constructing upper bounds for many-time averages for the case of a fairly broad class of model systems with four-fermion interaction. The methods proposed in this book for solving this problem will undoubtedly find application not only for the model systems associated with the theory of superconductivity considered here. The theoretical methods developed in Chapters 1 and 2 are already applicable to a much broader class of model systems from statistical physics and the theory of elementary particles. Contents: On the Theory of Superfluidit

Adaptive Maneuvering Frequency Method of Current Statistical Model

Institute of Scientific and Technical Information of China (English)

Wei Sun; Yongjian Yang

2017-01-01

Current statistical model(CSM) has a good performance in maneuvering target tracking. However, the fixed maneuvering frequency will deteriorate the tracking results, such as a serious dynamic delay, a slowly converging speedy and a limited precision when using Kalman filter(KF) algorithm. In this study, a new current statistical model and a new Kalman filter are proposed to improve the performance of maneuvering target tracking. The new model which employs innovation dominated subjection function to adaptively adjust maneuvering frequency has a better performance in step maneuvering target tracking, while a fluctuant phenomenon appears. As far as this problem is concerned, a new adaptive fading Kalman filter is proposed as well. In the new Kalman filter, the prediction values are amended in time by setting judgment and amendment rules,so that tracking precision and fluctuant phenomenon of the new current statistical model are improved. The results of simulation indicate the effectiveness of the new algorithm and the practical guiding significance.

Speech emotion recognition based on statistical pitch model

Institute of Scientific and Technical Information of China (English)

WANG Zhiping; ZHAO Li; ZOU Cairong

2006-01-01

A modified Parzen-window method, which keep high resolution in low frequencies and keep smoothness in high frequencies, is proposed to obtain statistical model. Then, a gender classification method utilizing the statistical model is proposed, which have a 98% accuracy of gender classification while long sentence is dealt with. By separation the male voice and female voice, the mean and standard deviation of speech training samples with different emotion are used to create the corresponding emotion models. Then the Bhattacharyya distance between the test sample and statistical models of pitch, are utilized for emotion recognition in speech.The normalization of pitch for the male voice and female voice are also considered, in order to illustrate them into a uniform space. Finally, the speech emotion recognition experiment based on K Nearest Neighbor shows that, the correct rate of 81% is achieved, where it is only 73.85%if the traditional parameters are utilized.

Statistical mechanics of dense plasmas and implications for the plasma polarization shift

International Nuclear Information System (INIS)

Rogers, F.J.

1984-01-01

A brief description of the statistical mechanics of reacting, dense, plasmas is given. The results do not support a Debye-like polarization shift at low density. It is shown that the electronic charge density factors into a strongly quantum mechanical part, that is not much affected by many body correlations and a weakly quantum mechanical part, that is considerably effected by many body correlations. The few body charge density is obtained from direct solution of the Schroedinger equation and the many body charge density is obtained from the hypernetted chain equation through the introduction of a pseudopotential

Statistical modelling of citation exchange between statistics journals.

Science.gov (United States)

Varin, Cristiano; Cattelan, Manuela; Firth, David

2016-01-01

Rankings of scholarly journals based on citation data are often met with scepticism by the scientific community. Part of the scepticism is due to disparity between the common perception of journals' prestige and their ranking based on citation counts. A more serious concern is the inappropriate use of journal rankings to evaluate the scientific influence of researchers. The paper focuses on analysis of the table of cross-citations among a selection of statistics journals. Data are collected from the Web of Science database published by Thomson Reuters. Our results suggest that modelling the exchange of citations between journals is useful to highlight the most prestigious journals, but also that journal citation data are characterized by considerable heterogeneity, which needs to be properly summarized. Inferential conclusions require care to avoid potential overinterpretation of insignificant differences between journal ratings. Comparison with published ratings of institutions from the UK's research assessment exercise shows strong correlation at aggregate level between assessed research quality and journal citation 'export scores' within the discipline of statistics.

Statistical mechanics of relativistic spin-1 bosons in a magnetic field

International Nuclear Information System (INIS)

Daicic, J.; Frankel, N.E.

1993-01-01

This paper investigates the statistical mechanics of a gas of spin-1 particles with pair creation in a homogeneous magnetic field. It is shown that expansions for the thermodynamic potential and magnetization in fields below the mass scale of the constituent particles are well behaved. However, when the field is at or above the mass scale, an intrinsic pathology of the single-particle energy spectrum manifests itself in the statistical mechanics of the system. Whilst for the spin-0 and spin-1/2 analog of this system there seemed to be no barrier ab initio to the field strength, the nature of the vacuum, and the role of interactions, were always borne in mind as matters to be considered in a high-order treatment, particularly when the field was at or above the mass scale. In the spin-1 case, the pathology in the single-particle energy spectrum heralds this from the beginning, and seems to be a warning that a single particle non-interacting picture of physics at high energies needs some reconsideration. 10 refs

A statistical model for investigating binding probabilities of DNA nucleotide sequences using microarrays.

Science.gov (United States)

Lee, Mei-Ling Ting; Bulyk, Martha L; Whitmore, G A; Church, George M

2002-12-01

There is considerable scientific interest in knowing the probability that a site-specific transcription factor will bind to a given DNA sequence. Microarray methods provide an effective means for assessing the binding affinities of a large number of DNA sequences as demonstrated by Bulyk et al. (2001, Proceedings of the National Academy of Sciences, USA 98, 7158-7163) in their study of the DNA-binding specificities of Zif268 zinc fingers using microarray technology. In a follow-up investigation, Bulyk, Johnson, and Church (2002, Nucleic Acid Research 30, 1255-1261) studied the interdependence of nucleotides on the binding affinities of transcription proteins. Our article is motivated by this pair of studies. We present a general statistical methodology for analyzing microarray intensity measurements reflecting DNA-protein interactions. The log probability of a protein binding to a DNA sequence on an array is modeled using a linear ANOVA model. This model is convenient because it employs familiar statistical concepts and procedures and also because it is effective for investigating the probability structure of the binding mechanism.

Statistical validation of normal tissue complication probability models.

Science.gov (United States)

Xu, Cheng-Jian; van der Schaaf, Arjen; Van't Veld, Aart A; Langendijk, Johannes A; Schilstra, Cornelis

2012-09-01

To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use. Copyright © 2012 Elsevier Inc. All rights reserved.

Statistical Validation of Normal Tissue Complication Probability Models

Energy Technology Data Exchange (ETDEWEB)

Xu Chengjian, E-mail: c.j.xu@umcg.nl [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schaaf, Arjen van der; Veld, Aart A. van' t; Langendijk, Johannes A. [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Schilstra, Cornelis [Department of Radiation Oncology, University of Groningen, University Medical Center Groningen, Groningen (Netherlands); Radiotherapy Institute Friesland, Leeuwarden (Netherlands)

2012-09-01

Purpose: To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. Methods and Materials: A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Results: Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Conclusion: Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use.

Shell model in large spaces and statistical spectroscopy

International Nuclear Information System (INIS)

Kota, V.K.B.

1996-01-01

For many nuclear structure problems of current interest it is essential to deal with shell model in large spaces. For this, three different approaches are now in use and two of them are: (i) the conventional shell model diagonalization approach but taking into account new advances in computer technology; (ii) the shell model Monte Carlo method. A brief overview of these two methods is given. Large space shell model studies raise fundamental questions regarding the information content of the shell model spectrum of complex nuclei. This led to the third approach- the statistical spectroscopy methods. The principles of statistical spectroscopy have their basis in nuclear quantum chaos and they are described (which are substantiated by large scale shell model calculations) in some detail. (author)

Advances in statistical models for data analysis

CERN Document Server

Minerva, Tommaso; Vichi, Maurizio

2015-01-01

This edited volume focuses on recent research results in classification, multivariate statistics and machine learning and highlights advances in statistical models for data analysis. The volume provides both methodological developments and contributions to a wide range of application areas such as economics, marketing, education, social sciences and environment. The papers in this volume were first presented at the 9th biannual meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in September 2013 at the University of Modena and Reggio Emilia, Italy.

An introduction to conformal invariance in quantum field theory and statistical mechanics

International Nuclear Information System (INIS)

Boyanovsky, D.; Naon, C.M.

1990-01-01

The subject of conformal invariance provides an extraordinarly successful and productive symbiosis between statistical mechanics and quantum field theory. The main goal of this paper, which is tailored to a wide audience, is to give an introduction to such vast subject (C.P.)

Statistical mechanics of magnetized pair Fermi gas

International Nuclear Information System (INIS)

Daicic, J.; Frankel, N.E.; Kowalenko, V.

1993-01-01

Following previous work on the magnetized pair Bose gas this contribution presents the statistical mechanics of the charged relativistic Fermi gas with pair creation in d spatial dimensions. Initially, the gas in no external fields is studied. As a result, expansions for the various thermodynamic functions are obtained in both the μ/m→0 (neutrino) limit, and about the point μ/m =1, where μ is the chemical potential. The thermodynamics of a gas of quantum-number conserving massless fermions is also discussed. Then a complete study of the pair Fermi gas in a homogeneous magnetic field, is presented investigating the behavior of the magnetization over a wide range of field strengths. The inclusion of pairs leads to new results for the net magnetization due to the paramagnetic moment of the spins and the diamagnetic Landau orbits. 20 refs

Two statistical mechanics aspects of complex networks

Science.gov (United States)

Thurner, Stefan; Biely, Christoly

2006-12-01

By adopting an ensemble interpretation of non-growing rewiring networks, network theory can be reduced to a counting problem of possible network states and an identification of their associated probabilities. We present two scenarios of how different rewirement schemes can be used to control the state probabilities of the system. In particular, we review how by generalizing the linking rules of random graphs, in combination with superstatistics and quantum mechanical concepts, one can establish an exact relation between the degree distribution of any given network and the nodes’ linking probability distributions. In a second approach, we control state probabilities by a network Hamiltonian, whose characteristics are motivated by biological and socio-economical statistical systems. We demonstrate that a thermodynamics of networks becomes a fully consistent concept, allowing to study e.g. ‘phase transitions’ and computing entropies through thermodynamic relations.

In silico environmental chemical science: properties and processes from statistical and computational modelling

Energy Technology Data Exchange (ETDEWEB)

Tratnyek, P. G.; Bylaska, Eric J.; Weber, Eric J.

2017-01-01

Quantitative structure–activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with “in silico” results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs using descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for “in silico environmental chemical science” are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.

In silico environmental chemical science: properties and processes from statistical and computational modelling.

Science.gov (United States)

Tratnyek, Paul G; Bylaska, Eric J; Weber, Eric J

2017-03-22

Quantitative structure-activity relationships (QSARs) have long been used in the environmental sciences. More recently, molecular modeling and chemoinformatic methods have become widespread. These methods have the potential to expand and accelerate advances in environmental chemistry because they complement observational and experimental data with "in silico" results and analysis. The opportunities and challenges that arise at the intersection between statistical and theoretical in silico methods are most apparent in the context of properties that determine the environmental fate and effects of chemical contaminants (degradation rate constants, partition coefficients, toxicities, etc.). The main example of this is the calibration of QSARs using descriptor variable data calculated from molecular modeling, which can make QSARs more useful for predicting property data that are unavailable, but also can make them more powerful tools for diagnosis of fate determining pathways and mechanisms. Emerging opportunities for "in silico environmental chemical science" are to move beyond the calculation of specific chemical properties using statistical models and toward more fully in silico models, prediction of transformation pathways and products, incorporation of environmental factors into model predictions, integration of databases and predictive models into more comprehensive and efficient tools for exposure assessment, and extending the applicability of all the above from chemicals to biologicals and materials.

Statistical learning: a powerful mechanism that operates by mere exposure.

Science.gov (United States)

Aslin, Richard N

2017-01-01

How do infants learn so rapidly and with little apparent effort? In 1996, Saffran, Aslin, and Newport reported that 8-month-old human infants could learn the underlying temporal structure of a stream of speech syllables after only 2 min of passive listening. This demonstration of what was called statistical learning, involving no instruction, reinforcement, or feedback, led to dozens of confirmations of this powerful mechanism of implicit learning in a variety of modalities, domains, and species. These findings reveal that infants are not nearly as dependent on explicit forms of instruction as we might have assumed from studies of learning in which children or adults are taught facts such as math or problem solving skills. Instead, at least in some domains, infants soak up the information around them by mere exposure. Learning and development in these domains thus appear to occur automatically and with little active involvement by an instructor (parent or teacher). The details of this statistical learning mechanism are discussed, including how exposure to specific types of information can, under some circumstances, generalize to never-before-observed information, thereby enabling transfer of learning. WIREs Cogn Sci 2017, 8:e1373. doi: 10.1002/wcs.1373 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

Towards an Industrial Application of Statistical Uncertainty Analysis Methods to Multi-physical Modelling and Safety Analyses

International Nuclear Information System (INIS)

Zhang, Jinzhao; Segurado, Jacobo; Schneidesch, Christophe

2013-01-01

Since 1980's, Tractebel Engineering (TE) has being developed and applied a multi-physical modelling and safety analyses capability, based on a code package consisting of the best estimate 3D neutronic (PANTHER), system thermal hydraulic (RELAP5), core sub-channel thermal hydraulic (COBRA-3C), and fuel thermal mechanic (FRAPCON/FRAPTRAN) codes. A series of methodologies have been developed to perform and to license the reactor safety analysis and core reload design, based on the deterministic bounding approach. Following the recent trends in research and development as well as in industrial applications, TE has been working since 2010 towards the application of the statistical sensitivity and uncertainty analysis methods to the multi-physical modelling and licensing safety analyses. In this paper, the TE multi-physical modelling and safety analyses capability is first described, followed by the proposed TE best estimate plus statistical uncertainty analysis method (BESUAM). The chosen statistical sensitivity and uncertainty analysis methods (non-parametric order statistic method or bootstrap) and tool (DAKOTA) are then presented, followed by some preliminary results of their applications to FRAPCON/FRAPTRAN simulation of OECD RIA fuel rod codes benchmark and RELAP5/MOD3.3 simulation of THTF tests. (authors)

Computationally efficient statistical differential equation modeling using homogenization

Science.gov (United States)

Hooten, Mevin B.; Garlick, Martha J.; Powell, James A.

2013-01-01

Statistical models using partial differential equations (PDEs) to describe dynamically evolving natural systems are appearing in the scientific literature with some regularity in recent years. Often such studies seek to characterize the dynamics of temporal or spatio-temporal phenomena such as invasive species, consumer-resource interactions, community evolution, and resource selection. Specifically, in the spatial setting, data are often available at varying spatial and temporal scales. Additionally, the necessary numerical integration of a PDE may be computationally infeasible over the spatial support of interest. We present an approach to impose computationally advantageous changes of support in statistical implementations of PDE models and demonstrate its utility through simulation using a form of PDE known as “ecological diffusion.” We also apply a statistical ecological diffusion model to a data set involving the spread of mountain pine beetle (Dendroctonus ponderosae) in Idaho, USA.

Statistical mechanics of complex neural systems and high dimensional data

International Nuclear Information System (INIS)

Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

2013-01-01

Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks. (paper)

Solvability of a class of systems of infinite-dimensional integral equations and their application in statistical mechanics

International Nuclear Information System (INIS)

Gonchar, N.S.

1986-01-01

This paper presents a mathematical method developed for investigating a class of systems of infinite-dimensional integral equations which have application in statistical mechanics. Necessary and sufficient conditions are obtained for the uniqueness and bifurcation of the solution of this class of systems of equations. Problems of equilibrium statistical mechanics are considered on the basis of this method

Models for probability and statistical inference theory and applications

CERN Document Server

Stapleton, James H

2007-01-01

This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses mo...

Fluctuations and correlations in statistical models of hadron production

International Nuclear Information System (INIS)

Gorenstein, M. I.

2012-01-01

An extension of the standard concept of the statistical ensembles is suggested. Namely, the statistical ensembles with extensive quantities fluctuating according to an externally given distribution are introduced. Applications in the statistical models of multiple hadron production in high energy physics are discussed.

From statistic mechanic outside equilibrium to transport equations

International Nuclear Information System (INIS)

Balian, R.

1995-01-01

This lecture notes give a synthetic view on the foundations of non-equilibrium statistical mechanics. The purpose is to establish the transport equations satisfied by the relevant variables, starting from the microscopic dynamics. The Liouville representation is introduced, and a projection associates with any density operator , for given choice of relevant observables, a reduced density operator. An exact integral-differential equation for the relevant variables is thereby derived. A short-memory approximation then yields the transport equations. A relevant entropy which characterizes the coarseness of the description is associated with each level of description. As an illustration, the classical gas, with its three levels of description and with the Chapman-Enskog method, is discussed. (author). 3 figs., 5 refs

Growth curve models and statistical diagnostics

CERN Document Server

Pan, Jian-Xin

2002-01-01

Growth-curve models are generalized multivariate analysis-of-variance models. These models are especially useful for investigating growth problems on short times in economics, biology, medical research, and epidemiology. This book systematically introduces the theory of the GCM with particular emphasis on their multivariate statistical diagnostics, which are based mainly on recent developments made by the authors and their collaborators. The authors provide complete proofs of theorems as well as practical data sets and MATLAB code.

The steady state of heterogeneous catalysis, studied by first-principles statistical mechanics

NARCIS (Netherlands)

Reuter, K.; Frenkel, D.; Scheffler, M.

2004-01-01

The turnover frequency of the catalytic oxidation of CO at RuO2(110) was calculated as a function of temperature and partial pressures using ab initio statistical mechanics. The underlying energetics of the gas-phase molecules, dissociation, adsorption, surface diffusion, surface chemical reactions,

Degradation model and application in life prediction of rotating-mechanism

International Nuclear Information System (INIS)

Zhou Yuhui

2009-01-01

The degradation data can provide additional information beyond that provided by the failure observations, both sets of observations need to be considered when doing inference on the statistical parameters of the product and system lifetime distributions. By the degradation model showing the wear out failure, the predicted results of mechanism life is more accurate. Strength is one of the important capabilities of the rotating mechanism. In this paper, the degradation data of strength are described as a stochastic process model. Accelerated tests expose the products to greater environmental stress levels so that we can obtain lifetime and degradation measurements in a more timely fashion. Using the Best Linear Unbiased Estimation (BLUE) Method, the parameters under the degradation path were estimated from the accelerated life test (ALT) data of the rotating mechanism. Based on solving the singularity of degradation equation, at any time the reliability is estimated by the using the strength-stress interference theory. So we can predict the life of the rotating mechanism. (authors)

Statistical Mechanics of Temporal and Interacting Networks

Science.gov (United States)

Zhao, Kun

In the last ten years important breakthroughs in the understanding of the topology of complexity have been made in the framework of network science. Indeed it has been found that many networks belong to the universality classes called small-world networks or scale-free networks. Moreover it was found that the complex architecture of real world networks strongly affects the critical phenomena defined on these structures. Nevertheless the main focus of the research has been the characterization of single and static networks. Recently, temporal networks and interacting networks have attracted large interest. Indeed many networks are interacting or formed by a multilayer structure. Example of these networks are found in social networks where an individual might be at the same time part of different social networks, in economic and financial networks, in physiology or in infrastructure systems. Moreover, many networks are temporal, i.e. the links appear and disappear on the fast time scale. Examples of these networks are social networks of contacts such as face-to-face interactions or mobile-phone communication, the time-dependent correlations in the brain activity and etc. Understanding the evolution of temporal and multilayer networks and characterizing critical phenomena in these systems is crucial if we want to describe, predict and control the dynamics of complex system. In this thesis, we investigate several statistical mechanics models of temporal and interacting networks, to shed light on the dynamics of this new generation of complex networks. First, we investigate a model of temporal social networks aimed at characterizing human social interactions such as face-to-face interactions and phone-call communication. Indeed thanks to the availability of data on these interactions, we are now in the position to compare the proposed model to the real data finding good agreement. Second, we investigate the entropy of temporal networks and growing networks , to provide

How to practise Bayesian statistics outside the Bayesian church: What philosophy for Bayesian statistical modelling?

NARCIS (Netherlands)

Borsboom, D.; Haig, B.D.

2013-01-01

Unlike most other statistical frameworks, Bayesian statistical inference is wedded to a particular approach in the philosophy of science (see Howson & Urbach, 2006); this approach is called Bayesianism. Rather than being concerned with model fitting, this position in the philosophy of science

A statistical model of macromolecules dynamics for Fluorescence Correlation Spectroscopy data analysis

Directory of Open Access Journals (Sweden)

Dmitri Koroliouk

2016-08-01

Full Text Available In this paper, we propose a new mathematical model to describe the mechanisms of biological macromolecules interactions. Our model consists of a discrete stationary random sequence given by a solution of difference stochastic equation, characterized by a drift predictive component and by a diffusion term. The relative statistical estimations are very simple and effective, promising to be a good tool for the mathematical description of collective biological reactions. This paper presents the mathematical model and its verification on a simulated data set, obtained on the basis of the well-known Stokes-Einsteinmodel. In particular, we considered several mix of particles of different diffusion coefficient, respectively: D1=10 mm2/sec and D2=100 mm2/sec. The parameters evaluated by this new mathematical model on simulated data show good estimation accuracy, in comparison with the prior parameters used in the simulations. Furthermore, when analyzing the data for the mix of particles with different diffusion coefficient, the proposed model parameters  (regression and  (square variance of the stochastic component have a good discriminative ability for the molar fraction determination.  In this paper, we propose a new mathematical model to describe the mechanisms of biological macromolecules interactions. Our model consists of a discrete stationary random sequence given by a solution of difference stochastic equation, characterized by a drift predictive component and by a diffusion term. The relative statistical estimations are very simple and effective, promising to be a good tool for mathematical description of collective biological reactions. This paper presents the mathematical model and its verification on simulated data set, obtained on the basis of the well-known Stokes-Einsteinmodel. In particular we considered several mix of particles of different diffusion coefficient, respectively: D1=10 mm2/sec and D2=100 mm2/sec. The parameters

Improving statistical reasoning theoretical models and practical implications

CERN Document Server

Sedlmeier, Peter

1999-01-01

This book focuses on how statistical reasoning works and on training programs that can exploit people''s natural cognitive capabilities to improve their statistical reasoning. Training programs that take into account findings from evolutionary psychology and instructional theory are shown to have substantially larger effects that are more stable over time than previous training regimens. The theoretical implications are traced in a neural network model of human performance on statistical reasoning problems. This book apppeals to judgment and decision making researchers and other cognitive scientists, as well as to teachers of statistics and probabilistic reasoning.

An integrated model of statistical process control and maintenance based on the delayed monitoring

International Nuclear Information System (INIS)

Yin, Hui; Zhang, Guojun; Zhu, Haiping; Deng, Yuhao; He, Fei

2015-01-01

This paper develops an integrated model of statistical process control and maintenance decision. The proposal of delayed monitoring policy postpones the sampling process till a scheduled time and contributes to ten-scenarios of the production process, where equipment failure may occur besides quality shift. The equipment failure and the control chart alert trigger the corrective maintenance and the predictive maintenance, respectively. The occurrence probability, the cycle time and the cycle cost of each scenario are obtained by integral calculation; therefore, a mathematical model is established to minimize the expected cost by using the genetic algorithm. A Monte Carlo simulation experiment is conducted and compared with the integral calculation in order to ensure the analysis of the ten-scenario model. Another ordinary integrated model without delayed monitoring is also established as comparison. The results of a numerical example indicate satisfactory economic performance of the proposed model. Finally, a sensitivity analysis is performed to investigate the effect of model parameters. - Highlights: • We develop an integrated model of statistical process control and maintenance. • We propose delayed monitoring policy and derive an economic model with 10 scenarios. • We consider two deterioration mechanisms, quality shift and equipment failure. • The delayed monitoring policy will help reduce the expected cost

Solar radiation data - statistical analysis and simulation models

Energy Technology Data Exchange (ETDEWEB)

Mustacchi, C; Cena, V; Rocchi, M; Haghigat, F

1984-01-01

The activities consisted in collecting meteorological data on magnetic tape for ten european locations (with latitudes ranging from 42/sup 0/ to 56/sup 0/ N), analysing the multi-year sequences, developing mathematical models to generate synthetic sequences having the same statistical properties of the original data sets, and producing one or more Short Reference Years (SRY's) for each location. The meteorological parameters examinated were (for all the locations) global + diffuse radiation on horizontal surface, dry bulb temperature, sunshine duration. For some of the locations additional parameters were available, namely, global, beam and diffuse radiation on surfaces other than horizontal, wet bulb temperature, wind velocity, cloud type, cloud cover. The statistical properties investigated were mean, variance, autocorrelation, crosscorrelation with selected parameters, probability density function. For all the meteorological parameters, various mathematical models were built: linear regression, stochastic models of the AR and the DAR type. In each case, the model with the best statistical behaviour was selected for the production of a SRY for the relevant parameter/location.

Nonequilibrium phase transitions and bifurcations of limit cycles and tori- a new research topic for statistical mechanics mechanics

International Nuclear Information System (INIS)

Haken, H.

1980-01-01

In the development of statistical mechanics we can more or less distinguish between two steps. First of all the main objective of statistical mechanics had been to give thermodynamics a solid theoretical basis starting from the microscopic world. The next step has then been performed in parallel with the development of irreversible thermodynamics dealing with processes close to thermal equilibrium. The problems dealt with here are mainly transport and relaxation processes. Over the past years it has become apparent that there is a third field, namely processes far away from thermal equilibrium. The particular interest in those processes stems from the fact that in such situations order can be generated on a macroscopic scale. The ordered states can be maintained by a flux of energy or matter through, these systems. In the realm of synergetjcs we have studied numerous examples and we now know that the occurrence of many of the ordered structures is governed by the same basic principles. (author)

Statistical Model Checking for Biological Systems

DEFF Research Database (Denmark)

David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel

2014-01-01

Statistical Model Checking (SMC) is a highly scalable simulation-based verification approach for testing and estimating the probability that a stochastic system satisfies a given linear temporal property. The technique has been applied to (discrete and continuous time) Markov chains, stochastic...

Right-sizing statistical models for longitudinal data.

Science.gov (United States)

Wood, Phillip K; Steinley, Douglas; Jackson, Kristina M

2015-12-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to "right-size" the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting, overly parsimonious models to more complex, better-fitting alternatives and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically underidentified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A 3-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation-covariation patterns. The orthogonal free curve slope intercept (FCSI) growth model is considered a general model that includes, as special cases, many models, including the factor mean (FM) model (McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, hierarchical linear models (HLMs), repeated-measures multivariate analysis of variance (MANOVA), and the linear slope intercept (linearSI) growth model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparing several candidate parametric growth and chronometric models in a Monte Carlo study. (c) 2015 APA, all rights reserved).

Nonequilibrium statistical mechanics and stochastic thermodynamics of small systems

International Nuclear Information System (INIS)

Tu Zhanchun

2014-01-01

Thermodynamics is an old subject. The research objects in conventional thermodynamics are macroscopic systems with huge number of particles. In recent 30 years, thermodynamics of small systems is a frontier topic in physics. Here we introduce nonequilibrium statistical mechanics and stochastic thermodynamics of small systems. As a case study, we construct a Canot-like cycle of a stochastic heat engine with a single particle controlled by a time-dependent harmonic potential. We find that the efficiency at maximum power is 1 - √T c /T h , where Tc and Th are the temperatures of cold bath and hot bath, respectively. (author)

Statistical mechanics of the cluster Ising model

International Nuclear Information System (INIS)

Smacchia, Pietro; Amico, Luigi; Facchi, Paolo; Fazio, Rosario; Florio, Giuseppe; Pascazio, Saverio; Vedral, Vlatko

2011-01-01

We study a Hamiltonian system describing a three-spin-1/2 clusterlike interaction competing with an Ising-like antiferromagnetic interaction. We compute free energy, spin-correlation functions, and entanglement both in the ground and in thermal states. The model undergoes a quantum phase transition between an Ising phase with a nonvanishing magnetization and a cluster phase characterized by a string order. Any two-spin entanglement is found to vanish in both quantum phases because of a nontrivial correlation pattern. Nevertheless, the residual multipartite entanglement is maximal in the cluster phase and dependent on the magnetization in the Ising phase. We study the block entropy at the critical point and calculate the central charge of the system, showing that the criticality of the system is beyond the Ising universality class.

Statistical mechanics of the cluster Ising model

Energy Technology Data Exchange (ETDEWEB)

Smacchia, Pietro [SISSA - via Bonomea 265, I-34136, Trieste (Italy); Amico, Luigi [CNR-MATIS-IMM and Dipartimento di Fisica e Astronomia Universita di Catania, C/O ed. 10, viale Andrea Doria 6, I-95125 Catania (Italy); Facchi, Paolo [Dipartimento di Matematica and MECENAS, Universita di Bari, I-70125 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); Fazio, Rosario [NEST, Scuola Normale Superiore and Istituto Nanoscienze - CNR, 56126 Pisa (Italy); Center for Quantum Technology, National University of Singapore, 117542 Singapore (Singapore); Florio, Giuseppe; Pascazio, Saverio [Dipartimento di Fisica and MECENAS, Universita di Bari, I-70126 Bari (Italy); INFN, Sezione di Bari, I-70126 Bari (Italy); Vedral, Vlatko [Center for Quantum Technology, National University of Singapore, 117542 Singapore (Singapore); Department of Physics, National University of Singapore, 2 Science Drive 3, Singapore 117542 (Singapore); Department of Physics, University of Oxford, Clarendon Laboratory, Oxford, OX1 3PU (United Kingdom)

2011-08-15

We study a Hamiltonian system describing a three-spin-1/2 clusterlike interaction competing with an Ising-like antiferromagnetic interaction. We compute free energy, spin-correlation functions, and entanglement both in the ground and in thermal states. The model undergoes a quantum phase transition between an Ising phase with a nonvanishing magnetization and a cluster phase characterized by a string order. Any two-spin entanglement is found to vanish in both quantum phases because of a nontrivial correlation pattern. Nevertheless, the residual multipartite entanglement is maximal in the cluster phase and dependent on the magnetization in the Ising phase. We study the block entropy at the critical point and calculate the central charge of the system, showing that the criticality of the system is beyond the Ising universality class.

Quantum statistical model for hot dense matter

International Nuclear Information System (INIS)

Rukhsana Kouser; Tasneem, G.; Saleem Shahzad, M.; Shafiq-ur-Rehman; Nasim, M.H.; Amjad Ali

2015-01-01

In solving numerous applied problems, one needs to know the equation of state, photon absorption coefficient and opacity of substances employed. We present a code for absorption coefficient and opacity calculation based on quantum statistical model. A self-consistent method for the calculation of potential is used. By solving Schrödinger equation with self-consistent potential we find energy spectrum of quantum mechanical system and corresponding wave functions. In addition we find mean occupation numbers of electron states and average charge state of the substance studied. The main processes of interaction of radiation with matter included in our opacity calculation are photon absorption in spectral lines (Bound-bound), photoionization (Bound-free), inverse bremsstrahlung (Free-free), Compton and Thomson scattering. Bound-bound line shape function has contribution from natural, Doppler, fine structure, collisional and stark broadening. To illustrate the main features of the code and its capabilities, calculation of average charge state, absorption coefficient, Rosseland and Planck mean and group opacities of aluminum and iron are presented. Results are satisfactorily compared with the published data. (authors)

Statistical evaluation of the mechanical properties of high-volume class F fly ash concretes

KAUST Repository

Yoon, Seyoon

2014-03-01

High-Volume Fly Ash (HVFA) concretes are seen by many as a feasible solution for sustainable, low embodied carbon construction. At the moment, fly ash is classified as a waste by-product, primarily of thermal power stations. In this paper the authors experimentally and statistically investigated the effects of mix-design factors on the mechanical properties of high-volume class F fly ash concretes. A total of 240 and 32 samples were produced and tested in the laboratory to measure compressive strength and Young\\'s modulus respectively. Applicability of the CEB-FIP (Comite Euro-international du Béton - Fédération Internationale de la Précontrainte) and ACI (American Concrete Institute) Building Model Code (Thomas, 2010; ACI Committee 209, 1982) [1,2] to the experimentally-derived mechanical property data for HVFA concretes was established. Furthermore, using multiple linear regression analysis, Mean Squared Residuals (MSRs) were obtained to determine whether a weight- or volume-based mix proportion is better to predict the mechanical properties of HVFA concrete. The significance levels of the design factors, which indicate how significantly the factors affect the HVFA concrete\\'s mechanical properties, were determined using analysis of variance (ANOVA) tests. The results show that a weight-based mix proportion is a slightly better predictor of mechanical properties than volume-based one. The significance level of fly ash substitution rate was higher than that of w/b ratio initially but reduced over time. © 2014 Elsevier Ltd. All rights reserved.

Statistics, synergy, and mechanism of multiple photogeneration of excitons in quantum dots: Fundamental and applied aspects

International Nuclear Information System (INIS)

Oksengendler, B. L.; Turaeva, N. N.; Uralov, I.; Marasulov, M. B.

2012-01-01

The effect of multiple exciton generation is analyzed based on statistical physics, quantum mechanics, and synergetics. Statistical problems of the effect of multiple exciton generation (MEG) are broadened and take into account not only exciton generation, but also background excitation. The study of the role of surface states of quantum dots is based on the synergy of self-catalyzed electronic reactions. An analysis of the MEG mechanism is based on the idea of electronic shaking using the sudden perturbation method in quantum mechanics. All of the above-mentioned results are applied to the problem of calculating the limiting efficiency to transform solar energy into electric energy. (authors)

Statistical model selection with “Big Data”

Directory of Open Access Journals (Sweden)

Jurgen A. Doornik

2015-12-01

Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.

Statistical shape and appearance models of bones.

Science.gov (United States)

Sarkalkan, Nazli; Weinans, Harrie; Zadpoor, Amir A

2014-03-01

When applied to bones, statistical shape models (SSM) and statistical appearance models (SAM) respectively describe the mean shape and mean density distribution of bones within a certain population as well as the main modes of variations of shape and density distribution from their mean values. The availability of this quantitative information regarding the detailed anatomy of bones provides new opportunities for diagnosis, evaluation, and treatment of skeletal diseases. The potential of SSM and SAM has been recently recognized within the bone research community. For example, these models have been applied for studying the effects of bone shape on the etiology of osteoarthritis, improving the accuracy of clinical osteoporotic fracture prediction techniques, design of orthopedic implants, and surgery planning. This paper reviews the main concepts, methods, and applications of SSM and SAM as applied to bone. Copyright © 2013 Elsevier Inc. All rights reserved.

Statistical fluid mechanics

CERN Document Server

Monin, A S

2007-01-01

""If ever a field needed a definitive book, it is the study of turbulence; if ever a book on turbulence could be called definitive, it is this book."" - ScienceWritten by two of Russia's most eminent and productive scientists in turbulence, oceanography, and atmospheric physics, this two-volume survey is renowned for its clarity as well as its comprehensive treatment. The first volume begins with an outline of laminar and turbulent flow. The remainder of the book treats a variety of aspects of turbulence: its statistical and Lagrangian descriptions, shear flows near surfaces and free turbulenc

A Statistical Thermodynamic Model for Ligands Interacting With Ion Channels: Theoretical Model and Experimental Validation of the KCNQ2 Channel

Directory of Open Access Journals (Sweden)

Fang Bai

2018-03-01

Full Text Available Ion channels are important therapeutic targets, and their pharmacology is becoming increasingly important. However, knowledge of the mechanism of interaction of the activators and ion channels is still limited due to the complexity of the mechanisms. A statistical thermodynamic model has been developed in this study to characterize the cooperative binding of activators to ion channels. By fitting experimental concentration-response data, the model gives eight parameters for revealing the mechanism of an activator potentiating an ion channel, i.e., the binding affinity (KA, the binding cooperative coefficients for two to four activator molecules interacting with one channel (γ, μ, and ν, and the channel conductance coefficients for four activator binding configurations of the channel (a, b, c, and d. Values for the model parameters and the mechanism underlying the interaction of ztz240, a proven KCNQ2 activator, with the wild-type channel have been obtained and revealed by fitting the concentration-response data of this activator potentiating the outward current amplitudes of KCNQ2. With these parameters, our model predicted an unexpected bi-sigmoid concentration-response curve of ztz240 activation of the WT-F137A mutant heteromeric channel that was in good agreement with the experimental data determined in parallel in this study, lending credence to the assumptions on which the model is based and to the model itself. Our model can provide a better fit to the measured data than the Hill equation and estimates the binding affinity, as well as the cooperative coefficients for the binding of activators and conductance coefficients for binding states, which validates its use in studying ligand-channel interaction mechanisms.

Workshop on Model Uncertainty and its Statistical Implications

CERN Document Server

1988-01-01

In this book problems related to the choice of models in such diverse fields as regression, covariance structure, time series analysis and multinomial experiments are discussed. The emphasis is on the statistical implications for model assessment when the assessment is done with the same data that generated the model. This is a problem of long standing, notorious for its difficulty. Some contributors discuss this problem in an illuminating way. Others, and this is a truly novel feature, investigate systematically whether sample re-use methods like the bootstrap can be used to assess the quality of estimators or predictors in a reliable way given the initial model uncertainty. The book should prove to be valuable for advanced practitioners and statistical methodologists alike.

Dimensionally regularized Tsallis' statistical mechanics and two-body Newton's gravitation

Science.gov (United States)

Zamora, J. D.; Rocca, M. C.; Plastino, A.; Ferri, G. L.

2018-05-01

Typical Tsallis' statistical mechanics' quantifiers like the partition function and the mean energy exhibit poles. We are speaking of the partition function Z and the mean energy 〈 U 〉 . The poles appear for distinctive values of Tsallis' characteristic real parameter q, at a numerable set of rational numbers of the q-line. These poles are dealt with dimensional regularization resources. The physical effects of these poles on the specific heats are studied here for the two-body classical gravitation potential.

Evaluation of mechanical properties of steel wire ropes by statistical methods

Directory of Open Access Journals (Sweden)

Boroška Ján

1999-12-01

Full Text Available The contribution deals with the evaluation of mechanical properties of steel wire ropes using statistical methods from the viewpoint of the quality of single wires as well as the internal construction of the wire ropes. The evaluation is based on the loading capacity calculated from the strength, number of folds and torsions. For the better ilustration, a box plot has been constructed.

Statistical metrology - measurement and modeling of variation for advanced process development and design rule generation