Genuinely high-dimensional nonlocality optimized by complementary measurements

International Nuclear Information System (INIS)

Lim, James; Ryu, Junghee; Yoo, Seokwon; Lee, Changhyoup; Bang, Jeongho; Lee, Jinhyoung

2010-01-01

Qubits exhibit extreme nonlocality when their state is maximally entangled and this is observed by mutually unbiased local measurements. This criterion does not hold for the Bell inequalities of high-dimensional systems (qudits), recently proposed by Collins-Gisin-Linden-Massar-Popescu and Son-Lee-Kim. Taking an alternative approach, called the quantum-to-classical approach, we derive a series of Bell inequalities for qudits that satisfy the criterion as for the qubits. In the derivation each d-dimensional subsystem is assumed to be measured by one of d possible measurements with d being a prime integer. By applying to two qubits (d=2), we find that a derived inequality is reduced to the Clauser-Horne-Shimony-Holt inequality when the degree of nonlocality is optimized over all the possible states and local observables. Further applying to two and three qutrits (d=3), we find Bell inequalities that are violated for the three-dimensionally entangled states but are not violated by any two-dimensionally entangled states. In other words, the inequalities discriminate three-dimensional (3D) entanglement from two-dimensional (2D) entanglement and in this sense they are genuinely 3D. In addition, for the two qutrits we give a quantitative description of the relations among the three degrees of complementarity, entanglement and nonlocality. It is shown that the degree of complementarity jumps abruptly to very close to its maximum as nonlocality starts appearing. These characteristics imply that complementarity plays a more significant role in the present inequality compared with the previously proposed inequality.

Quantum key distribution session with 16-dimensional photonic states

Science.gov (United States)

Etcheverry, S.; Cañas, G.; Gómez, E. S.; Nogueira, W. A. T.; Saavedra, C.; Xavier, G. B.; Lima, G.

2013-01-01

The secure transfer of information is an important problem in modern telecommunications. Quantum key distribution (QKD) provides a solution to this problem by using individual quantum systems to generate correlated bits between remote parties, that can be used to extract a secret key. QKD with D-dimensional quantum channels provides security advantages that grow with increasing D. However, the vast majority of QKD implementations has been restricted to two dimensions. Here we demonstrate the feasibility of using higher dimensions for real-world quantum cryptography by performing, for the first time, a fully automated QKD session based on the BB84 protocol with 16-dimensional quantum states. Information is encoded in the single-photon transverse momentum and the required states are dynamically generated with programmable spatial light modulators. Our setup paves the way for future developments in the field of experimental high-dimensional QKD. PMID:23897033

Using High-Dimensional Image Models to Perform Highly Undetectable Steganography

Science.gov (United States)

Pevný, Tomáš; Filler, Tomáš; Bas, Patrick

This paper presents a complete methodology for designing practical and highly-undetectable stegosystems for real digital media. The main design principle is to minimize a suitably-defined distortion by means of efficient coding algorithm. The distortion is defined as a weighted difference of extended state-of-the-art feature vectors already used in steganalysis. This allows us to "preserve" the model used by steganalyst and thus be undetectable even for large payloads. This framework can be efficiently implemented even when the dimensionality of the feature set used by the embedder is larger than 107. The high dimensional model is necessary to avoid known security weaknesses. Although high-dimensional models might be problem in steganalysis, we explain, why they are acceptable in steganography. As an example, we introduce HUGO, a new embedding algorithm for spatial-domain digital images and we contrast its performance with LSB matching. On the BOWS2 image database and in contrast with LSB matching, HUGO allows the embedder to hide 7× longer message with the same level of security level.

Cooperative single-photon subradiant states in a three-dimensional atomic array

Energy Technology Data Exchange (ETDEWEB)

Jen, H.H., E-mail: sappyjen@gmail.com

2016-11-15

We propose a complete superradiant and subradiant states that can be manipulated and prepared in a three-dimensional atomic array. These subradiant states can be realized by absorbing a single photon and imprinting the spatially-dependent phases on the atomic system. We find that the collective decay rates and associated cooperative Lamb shifts are highly dependent on the phases we manage to imprint, and the subradiant state of long lifetime can be found for various lattice spacings and atom numbers. We also investigate both optically thin and thick atomic arrays, which can serve for systematic studies of super- and sub-radiance. Our proposal offers an alternative scheme for quantum memory of light in a three-dimensional array of two-level atoms, which is applicable and potentially advantageous in quantum information processing. - Highlights: • Cooperative single-photon subradiant states in a three-dimensional atomic array. • Subradiant state manipulation via spatially-increasing phase imprinting. • Quantum storage of light in the subradiant state in two-level atoms.

Generation of multiparticle three-dimensional entanglement state via adiabatic passage

International Nuclear Information System (INIS)

Wu Xi; Chen Zhi-Hua; Ye Ming-Yong; Chen Yue-Hua; Lin Xiu-Min

2013-01-01

A scheme is proposed for generating a multiparticle three-dimensional entangled state by appropriately adiabatic evolutions, where atoms are respectively trapped in separated cavities so that individual addressing is needless. In the ideal case, losses due to the spontaneous transition of an atom and the excitation of photons are efficiently suppressed since atoms are all in ground states and the fields remain in a vacuum state. Compared with the previous proposals, the present scheme reduces its required operation time via simultaneously controlling four classical fields. This advantage would become even more obvious as the number of atoms increases. The experimental feasibility is also discussed. The successful preparation of a high-dimensional multiparticle entangled state among distant atoms provides better prospects for quantum communication and distributed quantum computation. (general)

Clustering high dimensional data

DEFF Research Database (Denmark)

Assent, Ira

2012-01-01

High-dimensional data, i.e., data described by a large number of attributes, pose specific challenges to clustering. The so-called ‘curse of dimensionality’, coined originally to describe the general increase in complexity of various computational problems as dimensionality increases, is known...... to render traditional clustering algorithms ineffective. The curse of dimensionality, among other effects, means that with increasing number of dimensions, a loss of meaningful differentiation between similar and dissimilar objects is observed. As high-dimensional objects appear almost alike, new approaches...... for clustering are required. Consequently, recent research has focused on developing techniques and clustering algorithms specifically for high-dimensional data. Still, open research issues remain. Clustering is a data mining task devoted to the automatic grouping of data based on mutual similarity. Each cluster...

High-Dimensional Metrics in R

OpenAIRE

Chernozhukov, Victor; Hansen, Chris; Spindler, Martin

2016-01-01

The package High-dimensional Metrics (\\Rpackage{hdm}) is an evolving collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e.g., treatment or poli...

Interface between path and orbital angular momentum entanglement for high-dimensional photonic quantum information.

Science.gov (United States)

Fickler, Robert; Lapkiewicz, Radek; Huber, Marcus; Lavery, Martin P J; Padgett, Miles J; Zeilinger, Anton

2014-07-30

Photonics has become a mature field of quantum information science, where integrated optical circuits offer a way to scale the complexity of the set-up as well as the dimensionality of the quantum state. On photonic chips, paths are the natural way to encode information. To distribute those high-dimensional quantum states over large distances, transverse spatial modes, like orbital angular momentum possessing Laguerre Gauss modes, are favourable as flying information carriers. Here we demonstrate a quantum interface between these two vibrant photonic fields. We create three-dimensional path entanglement between two photons in a nonlinear crystal and use a mode sorter as the quantum interface to transfer the entanglement to the orbital angular momentum degree of freedom. Thus our results show a flexible way to create high-dimensional spatial mode entanglement. Moreover, they pave the way to implement broad complex quantum networks where high-dimensionally entangled states could be distributed over distant photonic chips.

Controlled teleportation of a 3-dimensional bipartite quantum state

International Nuclear Information System (INIS)

Cao Haijing; Chen Zhonghua; Song Heshan

2008-01-01

A controlled teleportation scheme of an unknown 3-dimensional (3D) two-particle quantum state is proposed, where a 3D Bell state and 3D GHZ state function as the quantum channel. This teleportation scheme can be directly generalized to teleport an unknown d-dimensional bipartite quantum state

High-Dimensional Quantum Information Processing with Linear Optics

Science.gov (United States)

Fitzpatrick, Casey A.

Quantum information processing (QIP) is an interdisciplinary field concerned with the development of computers and information processing systems that utilize quantum mechanical properties of nature to carry out their function. QIP systems have become vastly more practical since the turn of the century. Today, QIP applications span imaging, cryptographic security, computation, and simulation (quantum systems that mimic other quantum systems). Many important strategies improve quantum versions of classical information system hardware, such as single photon detectors and quantum repeaters. Another more abstract strategy engineers high-dimensional quantum state spaces, so that each successful event carries more information than traditional two-level systems allow. Photonic states in particular bring the added advantages of weak environmental coupling and data transmission near the speed of light, allowing for simpler control and lower system design complexity. In this dissertation, numerous novel, scalable designs for practical high-dimensional linear-optical QIP systems are presented. First, a correlated photon imaging scheme using orbital angular momentum (OAM) states to detect rotational symmetries in objects using measurements, as well as building images out of those interactions is reported. Then, a statistical detection method using chains of OAM superpositions distributed according to the Fibonacci sequence is established and expanded upon. It is shown that the approach gives rise to schemes for sorting, detecting, and generating the recursively defined high-dimensional states on which some quantum cryptographic protocols depend. Finally, an ongoing study based on a generalization of the standard optical multiport for applications in quantum computation and simulation is reported upon. The architecture allows photons to reverse momentum inside the device. This in turn enables realistic implementation of controllable linear-optical scattering vertices for

Hypergraph-based anomaly detection of high-dimensional co-occurrences.

Science.gov (United States)

Silva, Jorge; Willett, Rebecca

2009-03-01

This paper addresses the problem of detecting anomalous multivariate co-occurrences using a limited number of unlabeled training observations. A novel method based on using a hypergraph representation of the data is proposed to deal with this very high-dimensional problem. Hypergraphs constitute an important extension of graphs which allow edges to connect more than two vertices simultaneously. A variational Expectation-Maximization algorithm for detecting anomalies directly on the hypergraph domain without any feature selection or dimensionality reduction is presented. The resulting estimate can be used to calculate a measure of anomalousness based on the False Discovery Rate. The algorithm has O(np) computational complexity, where n is the number of training observations and p is the number of potential participants in each co-occurrence event. This efficiency makes the method ideally suited for very high-dimensional settings, and requires no tuning, bandwidth or regularization parameters. The proposed approach is validated on both high-dimensional synthetic data and the Enron email database, where p > 75,000, and it is shown that it can outperform other state-of-the-art methods.

Introduction to high-dimensional statistics

CERN Document Server

Giraud, Christophe

2015-01-01

Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise.Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for ha

Multi-dimensional photonic states from a quantum dot

Science.gov (United States)

Lee, J. P.; Bennett, A. J.; Stevenson, R. M.; Ellis, D. J. P.; Farrer, I.; Ritchie, D. A.; Shields, A. J.

2018-04-01

Quantum states superposed across multiple particles or degrees of freedom offer an advantage in the development of quantum technologies. Creating these states deterministically and with high efficiency is an ongoing challenge. A promising approach is the repeated excitation of multi-level quantum emitters, which have been shown to naturally generate light with quantum statistics. Here we describe how to create one class of higher dimensional quantum state, a so called W-state, which is superposed across multiple time bins. We do this by repeated Raman scattering of photons from a charged quantum dot in a pillar microcavity. We show this method can be scaled to larger dimensions with no reduction in coherence or single-photon character. We explain how to extend this work to enable the deterministic creation of arbitrary time-bin encoded qudits.

Dimensional scaling for quasistationary states

International Nuclear Information System (INIS)

Kais, S.; Herschbach, D.R.

1993-01-01

Complex energy eigenvalues which specify the location and width of quasibound or resonant states are computed to good approximation by a simple dimensional scaling method. As applied to bound states, the method involves minimizing an effective potential function in appropriately scaled coordinates to obtain exact energies in the D→∞ limit, then computing approximate results for D=3 by a perturbation expansion in 1/D about this limit. For resonant states, the same procedure is used, with the radial coordinate now allowed to be complex. Five examples are treated: the repulsive exponential potential (e - r); a squelched harmonic oscillator (r 2 e - r); the inverted Kratzer potential (r -1 repulsion plus r -2 attraction); the Lennard-Jones potential (r -12 repulsion, r -6 attraction); and quasibound states for the rotational spectrum of the hydrogen molecule (X 1 summation g + , v=0, J=0 to 50). Comparisons with numerical integrations and other methods show that the much simpler dimensional scaling method, carried to second-order (terms in 1/D 2 ), yields good results over an extremely wide range of the ratio of level widths to spacings. Other methods have not yet evaluated the very broad H 2 rotational resonances reported here (J>39), which lie far above the centrifugal barrier

K-dimensional trio coherent states

International Nuclear Information System (INIS)

Yi, Hyo Seok; Nguyen, Ba An; Kim, Jaewan

2004-01-01

We introduce a novel class of higher-order, three-mode states called K-dimensional trio coherent states. We study their mathematical properties and prove that they form a complete set in a truncated Fock space. We also study their physical content by explicitly showing that they exhibit nonclassical features such as oscillatory number distribution, sub-Poissonian statistics, Cauchy-Schwarz inequality violation and phase-space quantum interferences. Finally, we propose an experimental scheme to realize the state with K = 2 in the quantized vibronic motion of a trapped ion

Dynamics of the vortex state in high temperature superconductors

International Nuclear Information System (INIS)

Kapitulnik, A.

1991-01-01

The large thermal energy available, the strong anisotropy, and short coherence lengths of high temperature superconductors give rise to new phenomena in the mixed state. The author discusses transport and thermodynamic measurements of high-Tc materials and of model systems. In particular, he uses experiments on two dimensional films to compare and isolate two dimensional effects in the cuprates. By using multilayer systems with similar parameters, he identifies decoupling of the superconducting planes in magnetic fields at temperatures much above the irreversibility line. He shows that if the irreversibility line is to be considered a melting transition line, it implies melting of the solid state into a liquid of three dimensional flux lines. He further uses Monte Carlo simulations to study the structure of the vortex state as well as melting

One-dimensional metallic edge states in MoS2

DEFF Research Database (Denmark)

Bollinger, Mikkel; Lauritsen, J.V.; Jacobsen, Karsten Wedel

2001-01-01

By the use of density functional calculations it is shown that the edges of a two-dimensional slab of insulating MoS2 exhibit several metallic states. These edge states can be viewed as one-dimensional conducting wires, and we show that they can be observed directly using scanning tunneling...

High dimensional ICA analysis detects within-network functional connectivity damage of default mode and sensory motor networks in Alzheimer's disease

Directory of Open Access Journals (Sweden)

Ottavia eDipasquale

2015-02-01

Full Text Available High dimensional independent component analysis (ICA, compared to low dimensional ICA, allows performing a detailed parcellation of the resting state networks. The purpose of this study was to give further insight into functional connectivity (FC in Alzheimer’s disease (AD using high dimensional ICA. For this reason, we performed both low and high dimensional ICA analyses of resting state fMRI (rfMRI data of 20 healthy controls and 21 AD patients, focusing on the primarily altered default mode network (DMN and exploring the sensory motor network (SMN. As expected, results obtained at low dimensionality were in line with previous literature. Moreover, high dimensional results allowed us to observe either the presence of within-network disconnections and FC damage confined to some of the resting state sub-networks. Due to the higher sensitivity of the high dimensional ICA analysis, our results suggest that high-dimensional decomposition in sub-networks is very promising to better localize FC alterations in AD and that FC damage is not confined to the default mode network.

Two dimensional solid state NMR

International Nuclear Information System (INIS)

Kentgens, A.P.M.

1987-01-01

This thesis illustrates, by discussing some existing and newly developed 2D solid state experiments, that two-dimensional NMR of solids is a useful and important extension of NMR techniques. Chapter 1 gives an overview of spin interactions and averaging techniques important in solid state NMR. As 2D NMR is already an established technique in solutions, only the basics of two dimensional NMR are presented in chapter 2, with an emphasis on the aspects important for solid spectra. The following chapters discuss the theoretical background and applications of specific 2D solid state experiments. An application of 2D-J resolved NMR, analogous to J-resolved spectroscopy in solutions, to natural rubber is given in chapter 3. In chapter 4 the anisotropic chemical shift is mapped out against the heteronuclear dipolar interaction to obtain information about the orientation of the shielding tensor in poly-(oxymethylene). Chapter 5 concentrates on the study of super-slow molecular motions in polymers using a variant of the 2D exchange experiment developed by us. Finally chapter 6 discusses a new experiment, 2D nutation NMR, which makes it possible to study the quadrupole interaction of half-integer spins. 230 refs.; 48 figs.; 8 tabs

High magnetic field magnetoresistance anomalies in the charge density wave state of the quasi-two dimensional bronze KMo6O{17}

Science.gov (United States)

Guyot, H.; Dumas, J.; Marcus, J.; Schlenker, C.; Vignolles, D.

2005-12-01

We report high magnetic field magnetoresistance measurements performed in pulsed fields up to 55 T on the quasi-two dimensional charge density wave conductor KMo{6}O{17}. Magnetoresistance curves show several anomalies below 28 T. First order transitions to smaller gap states take place at low temperature above 30 T. A phase diagram T(B) has been obtained. The angular dependence of the anomalies is reported.

Two dimensional electron systems for solid state quantum computation

Science.gov (United States)

Mondal, Sumit

Two dimensional electron systems based on GaAs/AlGaAs heterostructures are extremely useful in various scientific investigations of recent times including the search for quantum computational schemes. Although significant strides have been made over the past few years to realize solid state qubits on GaAs/AlGaAs 2DEGs, there are numerous factors limiting the progress. We attempt to identify factors that have material and design-specific origin and develop ways to overcome them. The thesis is divided in two broad segments. In the first segment we describe the realization of a new field-effect induced two dimensional electron system on GaAs/AlGaAs heterostructure where the novel device-design is expected to suppress the level of charge noise present in the device. Modulation-doped GaAs/AlGaAs heterostructures are utilized extensively in the study of quantum transport in nanostructures, but charge fluctuations associated with remote ionized dopants often produce deleterious effects. Electric field-induced carrier systems offer an attractive alternative if certain challenges can be overcome. We demonstrate a field-effect transistor in which the active channel is locally devoid of modulation-doping, but silicon dopant atoms are retained in the ohmic contact region to facilitate low-resistance contacts. A high quality two-dimensional electron gas is induced by a field-effect that is tunable over a density range of 6.5x10 10cm-2 to 2.6x1011cm-2 . Device design, fabrication, and low temperature (T=0.3K) characterization results are discussed. The demonstrated device-design overcomes several existing limitations in the fabrication of field-induced 2DEGs and might find utility in hosting nanostructures required for making spin qubits. The second broad segment describes our effort to correlate transport parameters measured at T=0.3K to the strength of the fractional quantum Hall state observed at nu=5/2 in the second Landau level of high-mobility GaAs/AlGaAs two dimensional

Impurity states in two - and three-dimensional disordered systems

International Nuclear Information System (INIS)

Silva, A.F. da; Fabbri, M.

1984-01-01

We investigate the microscopic structure of the impurity states in two-and three-dimensional (2D and 3d) disordered systems. A cluster model is outlined for the donor impurity density of states (DIDS) of doped semiconductors. It is shown that the impurity states are very sensitive to a change in the dimensionality of the system, i.e from 3D to 2D system. It is found that all eigenstates become localized in 2D disordered system for a large range of concentration. (Author) [pt

Impurity states in two-and three-dimensional disordered systems

International Nuclear Information System (INIS)

Silva, A.F. da; Fabbri, M.

1984-04-01

The microscopic structure of the impurity states in two-and three-dimensional (2D and 3D) disordered systems is investigated. A cluster model is outlined for the donor impurity density of states (DIDS) of doped semiconductors. It is shown that the impurity states are very sensitive to a change in the dimensionality of the system, i.e., from 3D to 2D system. It is found that all eigenstates become localized in 2D disordered system for a large range of concentration. (Author) [pt

(d -2 ) -Dimensional Edge States of Rotation Symmetry Protected Topological States

Science.gov (United States)

Song, Zhida; Fang, Zhong; Fang, Chen

2017-12-01

We study fourfold rotation-invariant gapped topological systems with time-reversal symmetry in two and three dimensions (d =2 , 3). We show that in both cases nontrivial topology is manifested by the presence of the (d -2 )-dimensional edge states, existing at a point in 2D or along a line in 3D. For fermion systems without interaction, the bulk topological invariants are given in terms of the Wannier centers of filled bands and can be readily calculated using a Fu-Kane-like formula when inversion symmetry is also present. The theory is extended to strongly interacting systems through the explicit construction of microscopic models having robust (d -2 )-dimensional edge states.

Highly compressible three-dimensional graphene hydrogel for foldable all-solid-state supercapacitor

Science.gov (United States)

Liu, Xianbin; Zou, Shuai; Liu, Kaixi; Lv, Chao; Wu, Ziping; Yin, Yanhong; Liang, Tongxiang; Xie, Zailai

2018-04-01

The fabrication of three-dimensional (3D) graphene-based macroscopic materials with superior mechanical and electrical properties for flexible energy storage devices is still extremely challenging. Here, we report a novel 3D graphene hydrogel decorated by the biomass phytic acid (PAGH) with developed porosity and strengthen mechanical property via hydrothermal and freeze-drying methods. The phytic acid molecules are intercalated into the graphene sheets, enabling robust network structure. This induces the formation of materials with larger specific surface area, lower density and enhanced compressive strength compared with pure GH. When directly employed as an electrode, the PAGH exhibits a high specific capacitance of 248.8 F g-1 at 1 A g-1 and excellent rate performance of 67.9% as current density increasing to 20 A g-1. Furthermore, the all-solid-state supercapacitor based PAGH can deliver outstanding cycle life (86.2% after cycling 10,000 times), glorious energy density (26.5 Wh kg-1) and power density (5135.1 W kg-1). The prepared device shows stable electrochemical behaviors at random bending angles. Therefore, the present work will open a new avenue to design and fabricate new flexible and portable graphene-based electrodes for future applications in energy storage devices.

Profiling stem cell states in three-dimensional biomaterial niches using high content image informatics.

Science.gov (United States)

Dhaliwal, Anandika; Brenner, Matthew; Wolujewicz, Paul; Zhang, Zheng; Mao, Yong; Batish, Mona; Kohn, Joachim; Moghe, Prabhas V

2016-11-01

A predictive framework for the evolution of stem cell biology in 3-D is currently lacking. In this study we propose deep image informatics of the nuclear biology of stem cells to elucidate how 3-D biomaterials steer stem cell lineage phenotypes. The approach is based on high content imaging informatics to capture minute variations in the 3-D spatial organization of splicing factor SC-35 in the nucleoplasm as a marker to classify emergent cell phenotypes of human mesenchymal stem cells (hMSCs). The cells were cultured in varied 3-D culture systems including hydrogels, electrospun mats and salt leached scaffolds. The approach encompasses high resolution 3-D imaging of SC-35 domains and high content image analysis (HCIA) to compute quantitative 3-D nuclear metrics for SC-35 organization in single cells in concert with machine learning approaches to construct a predictive cell-state classification model. Our findings indicate that hMSCs cultured in collagen hydrogels and induced to differentiate into osteogenic or adipogenic lineages could be classified into the three lineages (stem, adipogenic, osteogenic) with ⩾80% precision and sensitivity, within 72h. Using this framework, the augmentation of osteogenesis by scaffold design exerted by porogen leached scaffolds was also profiled within 72h with ∼80% high sensitivity. Furthermore, by employing 3-D SC-35 organizational metrics, differential osteogenesis induced by novel electrospun fibrous polymer mats incorporating decellularized matrix could also be elucidated and predictably modeled at just 3days with high precision. We demonstrate that 3-D SC-35 organizational metrics can be applied to model the stem cell state in 3-D scaffolds. We propose that this methodology can robustly discern minute changes in stem cell states within complex 3-D architectures and map single cell biological readouts that are critical to assessing population level cell heterogeneity. The sustained development and validation of bioactive

Two-dimensionally confined topological edge states in photonic crystals

International Nuclear Information System (INIS)

Barik, Sabyasachi; Miyake, Hirokazu; DeGottardi, Wade; Waks, Edo; Hafezi, Mohammad

2016-01-01

We present an all-dielectric photonic crystal structure that supports two-dimensionally confined helical topological edge states. The topological properties of the system are controlled by the crystal parameters. An interface between two regions of differing band topologies gives rise to topological edge states confined in a dielectric slab that propagate around sharp corners without backscattering. Three-dimensional finite-difference time-domain calculations show these edges to be confined in the out-of-plane direction by total internal reflection. Such nanoscale photonic crystal architectures could enable strong interactions between photonic edge states and quantum emitters. (paper)

Three-dimensional stellarator equilibrium as an ohmic steady state

International Nuclear Information System (INIS)

Park, W.; Monticello, D.A.; Strauss, H.; Manickam, J.

1985-07-01

A stable three-dimensional stellarator equilibrium can be obtained numerically by a time-dependent relaxation method using small values of dissipation. The final state is an ohmic steady state which approaches an ohmic equilibrium in the limit of small dissipation coefficients. We describe a method to speed up the relaxation process and a method to implement the B vector . del p = 0 condition. These methods are applied to obtain three-dimensional heliac equilibria using the reduced heliac equations

A Shell Multi-dimensional Hierarchical Cubing Approach for High-Dimensional Cube

Science.gov (United States)

Zou, Shuzhi; Zhao, Li; Hu, Kongfa

The pre-computation of data cubes is critical for improving the response time of OLAP systems and accelerating data mining tasks in large data warehouses. However, as the sizes of data warehouses grow, the time it takes to perform this pre-computation becomes a significant performance bottleneck. In a high dimensional data warehouse, it might not be practical to build all these cuboids and their indices. In this paper, we propose a shell multi-dimensional hierarchical cubing algorithm, based on an extension of the previous minimal cubing approach. This method partitions the high dimensional data cube into low multi-dimensional hierarchical cube. Experimental results show that the proposed method is significantly more efficient than other existing cubing methods.

Sequentially generated states for the study of two dimensional systems

Energy Technology Data Exchange (ETDEWEB)

Banuls, Mari-Carmen; Cirac, J. Ignacio [Max-Planck-Institut fuer Quantenoptik, Garching (Germany); Perez-Garcia, David [Depto. Analisis Matematico, Universidad Complutense de Madrid (Spain); Wolf, Michael M. [Niels Bohr Institut, Copenhagen (Denmark); Verstraete, Frank [Fakultaet fuer Physik, Universitaet Wien (Austria)

2009-07-01

The family of Matrix Product States represents a powerful tool for the study of physical one-dimensional quantum many-body systems, such as spin chains. Besides, Matrix Product States can be defined as the family of quantum states that can be sequentially generated in a one-dimensional system. We have introduced a new family of states which extends this sequential definition to two dimensions. Like in Matrix Product States, expectation values of few body observables can be efficiently evaluated and, for the case of translationally invariant systems, the correlation functions decay exponentially with the distance. We show that such states are a subclass of Projected Entangled Pair States and investigate their suitability for approximating the ground states of local Hamiltonians.

Chimera states in two-dimensional networks of locally coupled oscillators

Science.gov (United States)

Kundu, Srilena; Majhi, Soumen; Bera, Bidesh K.; Ghosh, Dibakar; Lakshmanan, M.

2018-02-01

Chimera state is defined as a mixed type of collective state in which synchronized and desynchronized subpopulations of a network of coupled oscillators coexist and the appearance of such anomalous behavior has strong connection to diverse neuronal developments. Most of the previous studies on chimera states are not extensively done in two-dimensional ensembles of coupled oscillators by taking neuronal systems with nonlinear coupling function into account while such ensembles of oscillators are more realistic from a neurobiological point of view. In this paper, we report the emergence and existence of chimera states by considering locally coupled two-dimensional networks of identical oscillators where each node is interacting through nonlinear coupling function. This is in contrast with the existence of chimera states in two-dimensional nonlocally coupled oscillators with rectangular kernel in the coupling function. We find that the presence of nonlinearity in the coupling function plays a key role to produce chimera states in two-dimensional locally coupled oscillators. We analytically verify explicitly in the case of a network of coupled Stuart-Landau oscillators in two dimensions that the obtained results using Ott-Antonsen approach and our analytical finding very well matches with the numerical results. Next, we consider another type of important nonlinear coupling function which exists in neuronal systems, namely chemical synaptic function, through which the nearest-neighbor (locally coupled) neurons interact with each other. It is shown that such synaptic interacting function promotes the emergence of chimera states in two-dimensional lattices of locally coupled neuronal oscillators. In numerical simulations, we consider two paradigmatic neuronal oscillators, namely Hindmarsh-Rose neuron model and Rulkov map for each node which exhibit bursting dynamics. By associating various spatiotemporal behaviors and snapshots at particular times, we study the chimera

High-dimensional covariance estimation with high-dimensional data

CERN Document Server

Pourahmadi, Mohsen

2013-01-01

Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and mac

Thermality and excited state Rényi entropy in two-dimensional CFT

Energy Technology Data Exchange (ETDEWEB)

Lin, Feng-Li [Department of Physics, National Taiwan Normal University,Taipei 11677, Taiwan (China); Wang, Huajia [Department of Physics, University of Illinois,Urbana-Champaign, IL 61801 (United States); Zhang, Jia-ju [Dipartimento di Fisica, Università degli Studi di Milano-Bicocca,Piazza della Scienza 3, I-20126 Milano (Italy); Theoretical Physics Division, Institute of High Energy Physics, Chinese Academy of Sciences,19B Yuquan Rd, Beijing 100049 (China); Theoretical Physics Center for Science Facilities, Chinese Academy of Sciences,19B Yuquan Rd, Beijing 100049 (China)

2016-11-21

We evaluate one-interval Rényi entropy and entanglement entropy for the excited states of two-dimensional conformal field theory (CFT) on a cylinder, and examine their differences from the ones for the thermal state. We assume the interval to be short so that we can use operator product expansion (OPE) of twist operators to calculate Rényi entropy in terms of sum of one-point functions of OPE blocks. We find that the entanglement entropy for highly excited state and thermal state behave the same way after appropriate identification of the conformal weight of the state with the temperature. However, there exists no such universal identification for the Rényi entropy in the short-interval expansion. Therefore, the highly excited state does not look thermal when comparing its Rényi entropy to the thermal state one. As the Rényi entropy captures the higher moments of the reduced density matrix but the entanglement entropy only the average, our results imply that the emergence of thermality depends on how refined we look into the entanglement structure of the underlying pure excited state.

Three-dimensional skeleton networks of graphene wrapped polyaniline nanofibers: an excellent structure for high-performance flexible solid-state supercapacitors

Science.gov (United States)

Hu, Nantao; Zhang, Liling; Yang, Chao; Zhao, Jian; Yang, Zhi; Wei, Hao; Liao, Hanbin; Feng, Zhenxing; Fisher, Adrian; Zhang, Yafei; Xu, Zhichuan J.

2016-01-01

Thin, robust, lightweight, and flexible supercapacitors (SCs) have aroused growing attentions nowadays due to the rapid development of flexible electronics. Graphene-polyaniline (PANI) hybrids are attractive candidates for high performance SCs. In order to utilize them in real devices, it is necessary to improve the capacitance and the structure stability of PANI. Here we report a hierarchical three-dimensional structure, in which all of PANI nanofibers (NFs) are tightly wrapped inside reduced graphene oxide (rGO) nanosheet skeletons, for high-performance flexible SCs. The as-fabricated film electrodes with this unique structure showed a highest gravimetric specific capacitance of 921 F/g and volumetric capacitance of 391 F/cm3. The assembled solid-state SCs gave a high specific capacitance of 211 F/g (1 A/g), a high area capacitance of 0.9 F/cm2, and a competitive volumetric capacitance of 25.6 F/cm3. The SCs also exhibited outstanding rate capability (~75% retention at 20 A/g) as well as excellent cycling stability (100% retention at 10 A/g for 2000 cycles). Additionally, no structural failure and loss of performance were observed under the bending state. This structure design paves a new avenue for engineering rGO/PANI or other similar hybrids for high performance flexible energy storage devices. PMID:26795067

On the ground state of the two-dimensional non-ideal Bose gas

International Nuclear Information System (INIS)

Lozovik, Yu.E.; Yudson, V.I.

1978-01-01

The theory of the ground state of the two-dimensional non-ideal Bose gas is presented. The conditions for the validity of the ladder and the Bogolubov approximations are derived. These conditions ensure the existence of a Bose condensate in the ground state of two-dimensional systems. These conditions are different from the corresponding conditions for the three-dimensional case. The connection between the effective interaction and the two-dimensional scattering amplitude at some characteristic energy kappa 2 /2m (not equal to 0) is obtained (f(kappa = 0) = infinity in the two-dimensional case). (Auth.)

Efficient construction of two-dimensional cluster states with probabilistic quantum gates

International Nuclear Information System (INIS)

Chen Qing; Cheng Jianhua; Wang Kelin; Du Jiangfeng

2006-01-01

We propose an efficient scheme for constructing arbitrary two-dimensional (2D) cluster states using probabilistic entangling quantum gates. In our scheme, the 2D cluster state is constructed with starlike basic units generated from 1D cluster chains. By applying parallel operations, the process of generating 2D (or higher-dimensional) cluster states is significantly accelerated, which provides an efficient way to implement realistic one-way quantum computers

High magnetic field studies of the charge density wave state of the quasi-two-dimensional conductor KMO 6O 17

Science.gov (United States)

Dumas, Jean; Guyot, Hervé; Balaska, Hafid; Marcus, Jacques; Vignolles, David; Sheikin, Ilya; Audouard, Alain; Brossard, Luc; Schlenker, Claire

2004-04-01

Magnetic torque and magnetoresistance measurements have been performed in high magnetic field on the quasi-two-dimensional charge density wave (CDW) oxide bronze KMo 6O 17 . Several anomalies have been found below 28 T either on the torque or on the magnetoresistance data. They can be attributed predominantly to orbital effects. Magnetoresistance data obtained up to 55 T show that a transition takes place above 30 T. This transition may be due to the Pauli coupling. The new field-induced density wave state exhibits Shubnikov-de Haas (SdH) oscillations.

High magnetic field studies of the charge density wave state of the quasi-two-dimensional conductor KMO6O17

International Nuclear Information System (INIS)

Dumas, Jean; Guyot, Herve; Balaska, Hafid; Marcus, Jacques; Vignolles, David; Sheikin, Ilya; Audouard, Alain; Brossard, Luc; Schlenker, Claire

2004-01-01

Magnetic torque and magnetoresistance measurements have been performed in high magnetic field on the quasi-two-dimensional charge density wave (CDW) oxide bronze KMo 6 O 17 . Several anomalies have been found below 28 T either on the torque or on the magnetoresistance data. They can be attributed predominantly to orbital effects. Magnetoresistance data obtained up to 55 T show that a transition takes place above 30 T. This transition may be due to the Pauli coupling. The new field-induced density wave state exhibits Shubnikov-de Haas (SdH) oscillations

On final states of two-dimensional decaying turbulence

NARCIS (Netherlands)

Yin, Z.

2004-01-01

Numerical and analytical studies of final states of two-dimensional (2D) decaying turbulence are carried out. The first part of this work is trying to give a definition for final states of 2D decaying turbulence. The functional relation of ¿-¿, which is frequently adopted as the characterization of

Josephson plasma resonance in vortex filament state of high temperature superconductors

International Nuclear Information System (INIS)

Matsuda, Yuji; Gaifullin, M.B.

1996-01-01

High temperature superconductors have the crystalline structure in which two-dimensional CuO 2 planes are piled in layers, consequently, the anisotropy of electroconductivity arises, and this brings about stable and low energy Josephson plasma in superconducting state. Also as to the vortex filament state of high temperature superconductors, the effect of thermal fluctuation due to low dimensionality, short coherence length and high transition temperature becomes conspicuous. In reality, these plasma and vortex filament state are related closely. Light reflection and plasma edge in superconducting state, Josephson plasma resonance in the vortex filament state of BiO 2 Sr 2 CaCu 2 O 8+δ , the plasma vibration in Josephson junction, Josephson plasma in magnetic field, Josephson plasma in the liquid state of vortex filament, Josephson plasma in the solid state of vortex filament, and Josephson plasma in parallel magnetic field are reported. The Josephson plasma resonance is the experimental means for exploring vortex filament state from microscopic standpoint, and its development hereafter is expected. (K.I.)

Exploration of one-dimensional plasma current density profile for K-DEMO steady-state operation

Energy Technology Data Exchange (ETDEWEB)

Kang, J.S. [Seoul National University, Seoul 151-742 (Korea, Republic of); Jung, L. [National Fusion Research Institute, Daejeon (Korea, Republic of); Byun, C.-S.; Na, D.H.; Na, Y.-S. [Seoul National University, Seoul 151-742 (Korea, Republic of); Hwang, Y.S., E-mail: yhwang@snu.ac.kr [Seoul National University, Seoul 151-742 (Korea, Republic of)

2016-11-01

Highlights: • One-dimensional current density and its optimization for the K-DEMO are explored. • Plasma current density profile is calculated with an integrated simulation code. • The impact of self and external heating profiles is considered self-consistently. • Current density is identified as a reference profile by minimizing heating power. - Abstract: Concept study for Korean demonstration fusion reactor (K-DEMO) is in progress, and basic design parameters are proposed by targeting high magnetic field operation with ITER-sized machine. High magnetic field operation is a favorable approach to enlarge relative plasma performance without increasing normalized beta or plasma current. Exploration of one-dimensional current density profile and its optimization process for the K-DEMO steady-state operation are reported in this paper. Numerical analysis is conducted with an integrated plasma simulation code package incorporating a transport code with equilibrium and current drive modules. Operation regimes are addressed with zero-dimensional system analysis. One-dimensional plasma current density profile is calculated based on equilibrium, bootstrap current analysis, and thermal transport analysis. The impact of self and external heating profiles on those parameters is considered self-consistently, where thermal power balance and 100% non-inductive current drive are the main constraints during the whole exploration procedure. Current and pressure profiles are identified as a reference steady-state profile by minimizing the external heating power with desired fusion power.

High-dimensional quantum key distribution based on multicore fiber using silicon photonic integrated circuits

DEFF Research Database (Denmark)

Ding, Yunhong; Bacco, Davide; Dalgaard, Kjeld

2017-01-01

is intrinsically limited to 1 bit/photon. Here we propose and experimentally demonstrate, for the first time, a high-dimensional quantum key distribution protocol based on space division multiplexing in multicore fiber using silicon photonic integrated lightwave circuits. We successfully realized three mutually......-dimensional quantum states, and enables breaking the information efficiency limit of traditional quantum key distribution protocols. In addition, the silicon photonic circuits used in our work integrate variable optical attenuators, highly efficient multicore fiber couplers, and Mach-Zehnder interferometers, enabling...

Equilibrium states and ground state of two-dimensional fluid foams

International Nuclear Information System (INIS)

Graner, F.; Jiang, Y.; Janiaud, E.; Flament, C.

2001-01-01

We study the equilibrium energies of two-dimensional (2D) noncoarsening fluid foams, which consist of bubbles with fixed areas. The equilibrium states correspond to local minima of the total perimeter. We present a theoretical derivation of energy minima; experiments with ferrofluid foams, which can be either highly distorted, locally relaxed, or globally annealed; and Monte Carlo simulations using the extended large-Q Potts model. For a dry foam with small size variance we develop physical insight and an electrostatic analogy, which enables us to (i) find an approximate value of the global minimum perimeter, accounting for (small) area disorder, the topological distribution, and physical boundary conditions; (ii) conjecture the corresponding pattern and topology: small bubbles sort inward and large bubbles sort outward, topological charges of the same signs ''repel'' while charges of the opposite signs ''attract;'' (iii) define local and global markers to determine directly from an image how far a foam is from its ground state; (iv) conjecture that, in a local perimeter minimum at prescribed topology, the pressure distribution and thus the edge curvature are unique. Some results also apply to 3D foams

Intrinsic two-dimensional states on the pristine surface of tellurium

Science.gov (United States)

Li, Pengke; Appelbaum, Ian

2018-05-01

Atomic chains configured in a helical geometry have fascinating properties, including phases hosting localized bound states in their electronic structure. We show how the zero-dimensional state—bound to the edge of a single one-dimensional helical chain of tellurium atoms—evolves into two-dimensional bands on the c -axis surface of the three-dimensional trigonal bulk. We give an effective Hamiltonian description of its dispersion in k space by exploiting confinement to a virtual bilayer, and elaborate on the diminished role of spin-orbit coupling. These intrinsic gap-penetrating surface bands were neglected in the interpretation of seminal experiments, where two-dimensional transport was otherwise attributed to extrinsic accumulation layers.

Optical Tamm states in one-dimensional magnetophotonic structures.

Science.gov (United States)

Goto, T; Dorofeenko, A V; Merzlikin, A M; Baryshev, A V; Vinogradov, A P; Inoue, M; Lisyansky, A A; Granovsky, A B

2008-09-12

We demonstrate the existence of a spectrally narrow localized surface state, the so-called optical Tamm state, at the interface between one-dimensional magnetophotonic and nonmagnetic photonic crystals. The state is spectrally located inside the photonic band gaps of each of the photonic crystals comprising this magnetophotonic structure. This state is associated with a sharp transmission peak through the sample and is responsible for the substantial enhancement of the Faraday rotation for the corresponding wavelength. The experimental results are in excellent agreement with the theoretical predictions.

Elucidating high-dimensional cancer hallmark annotation via enriched ontology.

Science.gov (United States)

Yan, Shankai; Wong, Ka-Chun

2017-09-01

Cancer hallmark annotation is a promising technique that could discover novel knowledge about cancer from the biomedical literature. The automated annotation of cancer hallmarks could reveal relevant cancer transformation processes in the literature or extract the articles that correspond to the cancer hallmark of interest. It acts as a complementary approach that can retrieve knowledge from massive text information, advancing numerous focused studies in cancer research. Nonetheless, the high-dimensional nature of cancer hallmark annotation imposes a unique challenge. To address the curse of dimensionality, we compared multiple cancer hallmark annotation methods on 1580 PubMed abstracts. Based on the insights, a novel approach, UDT-RF, which makes use of ontological features is proposed. It expands the feature space via the Medical Subject Headings (MeSH) ontology graph and utilizes novel feature selections for elucidating the high-dimensional cancer hallmark annotation space. To demonstrate its effectiveness, state-of-the-art methods are compared and evaluated by a multitude of performance metrics, revealing the full performance spectrum on the full set of cancer hallmarks. Several case studies are conducted, demonstrating how the proposed approach could reveal novel insights into cancers. https://github.com/cskyan/chmannot. Copyright © 2017 Elsevier Inc. All rights reserved.

Engineering the Kondo state in two-dimensional semiconducting phosphorene

Science.gov (United States)

Babar, Rohit; Kabir, Mukul

2018-01-01

Correlated interaction between dilute localized impurity electrons and the itinerant host conduction electrons in metals gives rise to the conventional many-body Kondo effect below sufficiently low temperature. In sharp contrast to these conventional Kondo systems, we report an intrinsic, robust, and high-temperature Kondo state in two-dimensional semiconducting phosphorene. While absorbed at a thermodynamically stable lattice defect, Cr impurity triggers an electronic phase transition in phosphorene to provide conduction electrons, which strongly interact with the localized moment generated at the Cr site. These manifest into the intrinsic Kondo state, where the impurity moment is quenched in multiple stages and at temperatures in the 40-200 K range. Further, along with a much smaller extension of the Kondo cloud, the predicted Kondo state is shown to be robust under uniaxial strain and layer thickness, which greatly simplifies its future experimental realization. We predict the present study will open up new avenues in Kondo physics and trigger further theoretical and experimental studies.

The one-dimensional Gross-Pitaevskii equation and its some excitation states

Energy Technology Data Exchange (ETDEWEB)

Prayitno, T. B., E-mail: trunk-002@yahoo.com [Physics Department, Faculty of Mathematics and Natural Science, Universitas Negeri Jakarta, Jl. Pemuda Rawamangun no. 10, Jakarta, 13220 (Indonesia)

2015-04-16

We have derived some excitation states of the one-dimensional Gross-Pitaevskii equation coupled by the gravitational potential. The methods that we have used here are taken by pursuing the recent work of Kivshar et. al. by considering the equation as a macroscopic quantum oscillator. To obtain the states, we have made the appropriate transformation to reduce the three-dimensional Gross-Pitaevskii equation into the one-dimensional Gross-Pitaevskii equation and applying the time-independent perturbation theory in the general solution of the one-dimensional Gross-Pitaevskii equation as a linear superposition of the normalized eigenfunctions of the Schrödinger equation for the harmonic oscillator potential. Moreover, we also impose the condition by assuming that some terms in the equation should be so small in order to preserve the use of the perturbation method.

Many electron variational ground state of the two dimensional Anderson lattice

International Nuclear Information System (INIS)

Zhou, Y.; Bowen, S.P.; Mancini, J.D.

1991-02-01

A variational upper bound of the ground state energy of two dimensional finite Anderson lattices is determined as a function of lattice size (up to 16 x 16). Two different sets of many-electron basis vectors are used to determine the ground state for all values of the coulomb integral U. This variational scheme has been successfully tested for one dimensional models and should give good estimates in two dimensions

High-dimensional change-point estimation: Combining filtering with convex optimization

OpenAIRE

Soh, Yong Sheng; Chandrasekaran, Venkat

2017-01-01

We consider change-point estimation in a sequence of high-dimensional signals given noisy observations. Classical approaches to this problem such as the filtered derivative method are useful for sequences of scalar-valued signals, but they have undesirable scaling behavior in the high-dimensional setting. However, many high-dimensional signals encountered in practice frequently possess latent low-dimensional structure. Motivated by this observation, we propose a technique for high-dimensional...

Coherent states on horospheric three-dimensional Lobachevsky space

Energy Technology Data Exchange (ETDEWEB)

Kurochkin, Yu., E-mail: y.kurochkin@ifanbel.bas-net.by; Shoukavy, Dz., E-mail: shoukavy@ifanbel.bas-net.by [Institute of Physics, National Academy of Sciences of Belarus, 68 Nezalezhnasci Ave., Minsk 220072 (Belarus); Rybak, I., E-mail: Ivan.Rybak@astro.up.pt [Institute of Physics, National Academy of Sciences of Belarus, 68 Nezalezhnasci Ave., Minsk 220072 (Belarus); Instituto de Astrofísica e Ciências do Espaço, CAUP, Rua das Estrelas, 4150-762 Porto (Portugal); Faculdade de Ciências, Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto (Portugal)

2016-08-15

In the paper it is shown that due to separation of variables in the Laplace-Beltrami operator (Hamiltonian of a free quantum particle) in horospheric and quasi-Cartesian coordinates of three dimensional Lobachevsky space, it is possible to introduce standard (“conventional” according to Perelomov [Generalized Coherent States and Their Applications (Springer-Verlag, 1986), p. 320]) coherent states. Some problems (oscillator on horosphere, charged particle in analogy of constant uniform magnetic field) where coherent states are suitable for treating were considered.

State reconstruction of one-dimensional wave packets

Science.gov (United States)

Krähmer, D. S.; Leonhardt, U.

1997-12-01

We review and analyze the method [U. Leonhardt, M.G. Raymer: Phys. Rev. Lett. 76, 1985 (1996)] for quantum-state reconstruction of one-dimensional non-relativistic wave packets from position observations. We illuminate the theoretical background of the technique and show how to extend the procedure to the continuous part of the spectrum.

Multivariate statistics high-dimensional and large-sample approximations

CERN Document Server

Fujikoshi, Yasunori; Shimizu, Ryoichi

2010-01-01

A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field, the book focuses on high-dimensional and large-scale approximations and details the many basic multivariate methods used to achieve high levels of accuracy. The authors begin with a fundamental presentation of the basic

High dimensional neurocomputing growth, appraisal and applications

CERN Document Server

Tripathi, Bipin Kumar

2015-01-01

The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligenc...

High-Efficiency Dye-Sensitized Solar Cell with Three-Dimensional Photoanode

KAUST Repository

Tétreault, Nicolas

2011-11-09

Herein, we present a straightforward bottom-up synthesis of a high electron mobility and highly light scattering macroporous photoanode for dye-sensitized solar cells. The dense three-dimensional Al/ZnO, SnO2, or TiO 2 host integrates a conformal passivation thin film to reduce recombination and a large surface-area mesoporous anatase guest for high dye loading. This novel photoanode is designed to improve the charge extraction resulting in higher fill factor and photovoltage for DSCs. An increase in photovoltage of up to 110 mV over state-of-the-art DSC is demonstrated. © 2011 American Chemical Society.

High-Efficiency Dye-Sensitized Solar Cell with Three-Dimensional Photoanode

KAUST Repository

Té treault, Nicolas; Arsenault, É ric; Heiniger, Leo-Philipp; Soheilnia, Navid; Brillet, Jé ré mie; Moehl, Thomas; Zakeeruddin, Shaik; Ozin, Geoffrey A.; Grä tzel, Michael

2011-01-01

Herein, we present a straightforward bottom-up synthesis of a high electron mobility and highly light scattering macroporous photoanode for dye-sensitized solar cells. The dense three-dimensional Al/ZnO, SnO2, or TiO 2 host integrates a conformal passivation thin film to reduce recombination and a large surface-area mesoporous anatase guest for high dye loading. This novel photoanode is designed to improve the charge extraction resulting in higher fill factor and photovoltage for DSCs. An increase in photovoltage of up to 110 mV over state-of-the-art DSC is demonstrated. © 2011 American Chemical Society.

Creating cat states in one-dimensional quantum walks using delocalized initial states

International Nuclear Information System (INIS)

Zhang, Wei-Wei; Gao, Fei; Goyal, Sandeep K; Sanders, Barry C; Simon, Christoph

2016-01-01

Cat states are coherent quantum superpositions of macroscopically distinct states and are useful for understanding the boundary between the classical and the quantum world. Due to their macroscopic nature, cat states are difficult to prepare in physical systems. We propose a method to create cat states in one-dimensional quantum walks using delocalized initial states of the walker. Since the quantum walks can be performed on any quantum system, our proposal enables a platform-independent realization of the cat states. We further show that the linear dispersion relation of the effective quantum walk Hamiltonian, which governs the dynamics of the delocalized states, is responsible for the formation of the cat states. We analyze the robustness of these states against environmental interactions and present methods to control and manipulate the cat states in the photonic implementation of quantum walks. (paper)

Three-dimensional true FISP for high-resolution imaging of the whole brain

International Nuclear Information System (INIS)

Schmitz, B.; Hagen, T.; Reith, W.

2003-01-01

While high-resolution T1-weighted sequences, such as three-dimensional magnetization-prepared rapid gradient-echo imaging, are widely available, there is a lack of an equivalent fast high-resolution sequence providing T2 contrast. Using fast high-performance gradient systems we show the feasibility of three-dimensional true fast imaging with steady-state precession (FISP) to fill this gap. We applied a three-dimensional true-FISP protocol with voxel sizes down to 0.5 x 0.5 x 0.5 mm and acquisition times of approximately 8 min on a 1.5-T Sonata (Siemens, Erlangen, Germany) magnetic resonance scanner. The sequence was included into routine brain imaging protocols for patients with cerebrospinal-fluid-related intracranial pathology. Images from 20 patients and 20 healthy volunteers were evaluated by two neuroradiologists with respect to diagnostic image quality and artifacts. All true-FISP scans showed excellent imaging quality free of artifacts in patients and volunteers. They were valuable for the assessment of anatomical and pathologic aspects of the included patients. High-resolution true-FISP imaging is a valuable adjunct for the exploration and neuronavigation of intracranial pathologies especially if cerebrospinal fluid is involved. (orig.)

Two-Dimensional Polymer Synthesized via Solid-State Polymerization for High-Performance Supercapacitors.

Science.gov (United States)

Liu, Wei; Ulaganathan, Mani; Abdelwahab, Ibrahim; Luo, Xin; Chen, Zhongxin; Rong Tan, Sherman Jun; Wang, Xiaowei; Liu, Yanpeng; Geng, Dechao; Bao, Yang; Chen, Jianyi; Loh, Kian Ping

2018-01-23

Two-dimensional (2-D) polymer has properties that are attractive for energy storage applications because of its combination of heteroatoms, porosities and layered structure, which provides redox chemistry and ion diffusion routes through the 2-D planes and 1-D channels. Here, conjugated aromatic polymers (CAPs) were synthesized in quantitative yield via solid-state polymerization of phenazine-based precursor crystals. By choosing flat molecules (2-TBTBP and 3-TBQP) with different positions of bromine substituents on a phenazine-derived scaffold, C-C cross coupling was induced following thermal debromination. CAP-2 is polymerized from monomers that have been prepacked into layered structure (3-TBQP). It can be mechanically exfoliated into micrometer-sized ultrathin sheets that show sharp Raman peaks which reflect conformational ordering. CAP-2 has a dominant pore size of ∼0.8 nm; when applied as an asymmetric supercapacitor, it delivers a specific capacitance of 233 F g -1 at a current density of 1.0 A g -1 , and shows outstanding cycle performance.

Construction of high-dimensional universal quantum logic gates using a Λ system coupled with a whispering-gallery-mode microresonator.

Science.gov (United States)

He, Ling Yan; Wang, Tie-Jun; Wang, Chuan

2016-07-11

High-dimensional quantum system provides a higher capacity of quantum channel, which exhibits potential applications in quantum information processing. However, high-dimensional universal quantum logic gates is difficult to achieve directly with only high-dimensional interaction between two quantum systems and requires a large number of two-dimensional gates to build even a small high-dimensional quantum circuits. In this paper, we propose a scheme to implement a general controlled-flip (CF) gate where the high-dimensional single photon serve as the target qudit and stationary qubits work as the control logic qudit, by employing a three-level Λ-type system coupled with a whispering-gallery-mode microresonator. In our scheme, the required number of interaction times between the photon and solid state system reduce greatly compared with the traditional method which decomposes the high-dimensional Hilbert space into 2-dimensional quantum space, and it is on a shorter temporal scale for the experimental realization. Moreover, we discuss the performance and feasibility of our hybrid CF gate, concluding that it can be easily extended to a 2n-dimensional case and it is feasible with current technology.

High magnetic field studies of the charge density wave state of the quasi-two-dimensional conductor KMO{sub 6}O{sub 17}

Energy Technology Data Exchange (ETDEWEB)

Dumas, Jean; Guyot, Herve; Balaska, Hafid; Marcus, Jacques; Vignolles, David; Sheikin, Ilya; Audouard, Alain; Brossard, Luc; Schlenker, Claire

2004-04-30

Magnetic torque and magnetoresistance measurements have been performed in high magnetic field on the quasi-two-dimensional charge density wave (CDW) oxide bronze KMo{sub 6}O{sub 17} . Several anomalies have been found below 28 T either on the torque or on the magnetoresistance data. They can be attributed predominantly to orbital effects. Magnetoresistance data obtained up to 55 T show that a transition takes place above 30 T. This transition may be due to the Pauli coupling. The new field-induced density wave state exhibits Shubnikov-de Haas (SdH) oscillations.

State-space dimensionality in short-memory hidden-variable theories

International Nuclear Information System (INIS)

Montina, Alberto

2011-01-01

Recently we have presented a hidden-variable model of measurements for a qubit where the hidden-variable state-space dimension is one-half the quantum-state manifold dimension. The absence of a short memory (Markov) dynamics is the price paid for this dimensional reduction. The conflict between having the Markov property and achieving the dimensional reduction was proved by Montina [A. Montina, Phys. Rev. A 77, 022104 (2008)] using an additional hypothesis of trajectory relaxation. Here we analyze in more detail this hypothesis introducing the concept of invertible process and report a proof that makes clearer the role played by the topology of the hidden-variable space. This is accomplished by requiring suitable properties of regularity of the conditional probability governing the dynamics. In the case of minimal dimension the set of continuous hidden variables is identified with an object living an N-dimensional Hilbert space whose dynamics is described by the Schroedinger equation. A method for generating the economical non-Markovian model for the qubit is also presented.

An Exact, Compressible One-Dimensional Riemann Solver for General, Convex Equations of State

Energy Technology Data Exchange (ETDEWEB)

Kamm, James Russell [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2015-03-05

This note describes an algorithm with which to compute numerical solutions to the one- dimensional, Cartesian Riemann problem for compressible flow with general, convex equations of state. While high-level descriptions of this approach are to be found in the literature, this note contains most of the necessary details required to write software for this problem. This explanation corresponds to the approach used in the source code that evaluates solutions for the 1D, Cartesian Riemann problem with a JWL equation of state in the ExactPack package [16, 29]. Numerical examples are given with the proposed computational approach for a polytropic equation of state and for the JWL equation of state.

Controlled teleportation of high-dimension quantum-states with generalized Bell-state measurement

Institute of Scientific and Technical Information of China (English)

Zhan You-Bang

2007-01-01

In this paper a scheme for controlled teleportation of arbitrary high-dimensional unknown quantum states is proposed by using the generalized Bell-basis measurement and the generalized Hadamard transformation. As two special cases, two schemes of controlled teleportation of an unknown single-qutrit state and an unknown two-qutrit state are investigated in detail. In the first scheme, a maximally entangled three-qutrit state is used as the quantum channel, while in the second scheme, an entangled two-qutrit state and an entangled three-qutrit state are employed as the quantum channels. In these schemes, an unknown qutrit state can be teleported to either one of two receivers, but only one of them can reconstruct the qutrit state with the help of the other. Based on the case of qutrits, a scheme of controlled teleportation of an unknown qudit state is presented.

Hierarchical low-rank approximation for high dimensional approximation

KAUST Repository

Nouy, Anthony

2016-01-07

Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.

Hierarchical low-rank approximation for high dimensional approximation

KAUST Repository

Nouy, Anthony

2016-01-01

Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.

Three-dimensional polarization states of monochromatic light fields.

Science.gov (United States)

Azzam, R M A

2011-11-01

The 3×1 generalized Jones vectors (GJVs) [E(x) E(y) E(z)](t) (t indicates the transpose) that describe the linear, circular, and elliptical polarization states of an arbitrary three-dimensional (3-D) monochromatic light field are determined in terms of the geometrical parameters of the 3-D vibration of the time-harmonic electric field. In three dimensions, there are as many distinct linear polarization states as there are points on the surface of a hemisphere, and the number of distinct 3-D circular polarization states equals that of all two-dimensional (2-D) polarization states on the Poincaré sphere, of which only two are circular states. The subset of 3-D polarization states that results from the superposition of three mutually orthogonal x, y, and z field components of equal amplitude is considered as a function of their relative phases. Interesting contours of equal ellipticity and equal inclination of the normal to the polarization ellipse with respect to the x axis are obtained in 2-D phase space. Finally, the 3×3 generalized Jones calculus, in which elastic scattering (e.g., by a nano-object in the near field) is characterized by the 3-D linear transformation E(s)=T E(i), is briefly introduced. In such a matrix transformation, E(i) and E(s) are the 3×1 GJVs of the incident and scattered waves and T is the 3×3 generalized Jones matrix of the scatterer at a given frequency and for given directions of incidence and scattering.

Impact of high-frequency pumping on anomalous finite-size effects in three-dimensional topological insulators

Science.gov (United States)

Pervishko, Anastasiia A.; Yudin, Dmitry; Shelykh, Ivan A.

2018-02-01

Lowering of the thickness of a thin-film three-dimensional topological insulator down to a few nanometers results in the gap opening in the spectrum of topologically protected two-dimensional surface states. This phenomenon, which is referred to as the anomalous finite-size effect, originates from hybridization between the states propagating along the opposite boundaries. In this work, we consider a bismuth-based topological insulator and show how the coupling to an intense high-frequency linearly polarized pumping can further be used to manipulate the value of a gap. We address this effect within recently proposed Brillouin-Wigner perturbation theory that allows us to map a time-dependent problem into a stationary one. Our analysis reveals that both the gap and the components of the group velocity of the surface states can be tuned in a controllable fashion by adjusting the intensity of the driving field within an experimentally accessible range and demonstrate the effect of light-induced band inversion in the spectrum of the surface states for high enough values of the pump.

Quantum scattering theory of a single-photon Fock state in three-dimensional spaces.

Science.gov (United States)

Liu, Jingfeng; Zhou, Ming; Yu, Zongfu

2016-09-15

A quantum scattering theory is developed for Fock states scattered by two-level systems in three-dimensional free space. It is built upon the one-dimensional scattering theory developed in waveguide quantum electrodynamics. The theory fully quantizes the incident light as Fock states and uses a non-perturbative method to calculate the scattering matrix.

Degenerate ground states and multiple bifurcations in a two-dimensional q-state quantum Potts model.

Science.gov (United States)

Dai, Yan-Wei; Cho, Sam Young; Batchelor, Murray T; Zhou, Huan-Qiang

2014-06-01

We numerically investigate the two-dimensional q-state quantum Potts model on the infinite square lattice by using the infinite projected entangled-pair state (iPEPS) algorithm. We show that the quantum fidelity, defined as an overlap measurement between an arbitrary reference state and the iPEPS ground state of the system, can detect q-fold degenerate ground states for the Z_{q} broken-symmetry phase. Accordingly, a multiple bifurcation of the quantum ground-state fidelity is shown to occur as the transverse magnetic field varies from the symmetry phase to the broken-symmetry phase, which means that a multiple-bifurcation point corresponds to a critical point. A (dis)continuous behavior of quantum fidelity at phase transition points characterizes a (dis)continuous phase transition. Similar to the characteristic behavior of the quantum fidelity, the magnetizations, as order parameters, obtained from the degenerate ground states exhibit multiple bifurcation at critical points. Each order parameter is also explicitly demonstrated to transform under the Z_{q} subgroup of the symmetry group of the Hamiltonian. We find that the q-state quantum Potts model on the square lattice undergoes a discontinuous (first-order) phase transition for q=3 and q=4 and a continuous phase transition for q=2 (the two-dimensional quantum transverse Ising model).

Deterministic joint remote preparation of an equatorial hybrid state via high-dimensional Einstein-Podolsky-Rosen pairs: active versus passive receiver

Science.gov (United States)

Bich, Cao Thi; Dat, Le Thanh; Van Hop, Nguyen; An, Nguyen Ba

2018-04-01

Entanglement plays a vital and in many cases non-replaceable role in the quantum network communication. Here, we propose two new protocols to jointly and remotely prepare a special so-called bipartite equatorial state which is hybrid in the sense that it entangles two Hilbert spaces with arbitrary different dimensions D and N (i.e., a type of entanglement between a quDit and a quNit). The quantum channels required to do that are however not necessarily hybrid. In fact, we utilize four high-dimensional Einstein-Podolsky-Rosen pairs, two of which are quDit-quDit entanglements, while the other two are quNit-quNit ones. In the first protocol the receiver has to be involved actively in the process of remote state preparation, while in the second protocol the receiver is passive as he/she needs to participate only in the final step for reconstructing the target hybrid state. Each protocol meets a specific circumstance that may be encountered in practice and both can be performed with unit success probability. Moreover, the concerned equatorial hybrid entangled state can also be jointly prepared for two receivers at two separated locations by slightly modifying the initial particles' distribution, thereby establishing between them an entangled channel ready for a later use.

Flexible solid-state supercapacitors based on three-dimensional graphene hydrogel films.

Science.gov (United States)

Xu, Yuxi; Lin, Zhaoyang; Huang, Xiaoqing; Liu, Yuan; Huang, Yu; Duan, Xiangfeng

2013-05-28

Flexible solid-state supercapacitors are of considerable interest as mobile power supply for future flexible electronics. Graphene or carbon nanotubes based thin films have been used to fabricate flexible solid-state supercapacitors with high gravimetric specific capacitances (80-200 F/g), but usually with a rather low overall or areal specific capacitance (3-50 mF/cm(2)) due to the ultrasmall electrode thickness (typically a few micrometers) and ultralow mass loading, which is not desirable for practical applications. Here we report the exploration of a three-dimensional (3D) graphene hydrogel for the fabrication of high-performance solid-state flexible supercapacitors. With a highly interconnected 3D network structure, graphene hydrogel exhibits exceptional electrical conductivity and mechanical robustness to make it an excellent material for flexible energy storage devices. Our studies demonstrate that flexible supercapacitors with a 120 μm thick graphene hydrogel thin film can exhibit excellent capacitive characteristics, including a high gravimetric specific capacitance of 186 F/g (up to 196 F/g for a 42 μm thick electrode), an unprecedented areal specific capacitance of 372 mF/cm(2) (up to 402 mF/cm(2) for a 185 μm thick electrode), low leakage current (10.6 μA), excellent cycling stability, and extraordinary mechanical flexibility. This study demonstrates the exciting potential of 3D graphene macrostructures for high-performance flexible energy storage devices.

Supporting Dynamic Quantization for High-Dimensional Data Analytics.

Science.gov (United States)

Guzun, Gheorghi; Canahuate, Guadalupe

2017-05-01

Similarity searches are at the heart of exploratory data analysis tasks. Distance metrics are typically used to characterize the similarity between data objects represented as feature vectors. However, when the dimensionality of the data increases and the number of features is large, traditional distance metrics fail to distinguish between the closest and furthest data points. Localized distance functions have been proposed as an alternative to traditional distance metrics. These functions only consider dimensions close to query to compute the distance/similarity. Furthermore, in order to enable interactive explorations of high-dimensional data, indexing support for ad-hoc queries is needed. In this work we set up to investigate whether bit-sliced indices can be used for exploratory analytics such as similarity searches and data clustering for high-dimensional big-data. We also propose a novel dynamic quantization called Query dependent Equi-Depth (QED) quantization and show its effectiveness on characterizing high-dimensional similarity. When applying QED we observe improvements in kNN classification accuracy over traditional distance functions. Gheorghi Guzun and Guadalupe Canahuate. 2017. Supporting Dynamic Quantization for High-Dimensional Data Analytics. In Proceedings of Ex-ploreDB'17, Chicago, IL, USA, May 14-19, 2017, 6 pages. https://doi.org/http://dx.doi.org/10.1145/3077331.3077336.

Visualizing One-Dimensional Electronic States and their Scattering in Semi-conducting Nanowires

Science.gov (United States)

Beidenkopf, Haim; Reiner, Jonathan; Norris, Andrew; Nayak, Abhay Kumar; Avraham, Nurit; Shtrikman, Hadas

One-dimensional electronic systems constitute a fascinating playground for the emergence of exotic electronic effects and phases, within and beyond the Tomonaga-Luttinger liquid paradigm. More recently topological superconductivity and Majorana modes were added to that long list of phenomena. We report scanning tunneling microscopy and spectroscopy measurements conducted on pristine, epitaxialy grown InAs nanowires. We resolve the 1D electronic band structure manifested both via Van-Hove singularities in the local density-of-states, as well as by the quasi-particle interference patterns, induced by scattering from surface impurities. By studying the scattering of the one-dimensional electronic states off various scatterers, including crystallographic defects and the nanowire end, we identify new one-dimensional relaxation regimes and yet unexplored effects of interactions. Some of these may bear implications on the topological superconducting state and Majorana modes therein. The authors acknowledge support from the Israeli Science Foundation (ISF).

Zero- and two-dimensional hybrid carbon phosphors for high colorimetric purity white light-emission.

Science.gov (United States)

Ding, Yamei; Chang, Qing; Xiu, Fei; Chen, Yingying; Liu, Zhengdong; Ban, Chaoyi; Cheng, Shuai; Liu, Juqing; Huang, Wei

2018-03-01

Carbon nanomaterials are promising phosphors for white light emission. A facile single-step synthesis method has been developed to prepare zero- and two-dimensional hybrid carbon phosphors for the first time. Zero-dimensional carbon dots (C-dots) emit bright blue luminescence under 365 nm UV light and two-dimensional nanoplates improve the dispersity and film forming ability of C-dots. As a proof-of-concept application, the as-prepared hybrid carbon phosphors emit bright white luminescence in the solid state, and the phosphor-coated blue LEDs exhibit high colorimetric purity white light-emission with a color coordinate of (0.3308, 0.3312), potentially enabling the successful application of white emitting phosphors in the LED field.

Bayesian Multiresolution Variable Selection for Ultra-High Dimensional Neuroimaging Data.

Science.gov (United States)

Zhao, Yize; Kang, Jian; Long, Qi

2018-01-01

Ultra-high dimensional variable selection has become increasingly important in analysis of neuroimaging data. For example, in the Autism Brain Imaging Data Exchange (ABIDE) study, neuroscientists are interested in identifying important biomarkers for early detection of the autism spectrum disorder (ASD) using high resolution brain images that include hundreds of thousands voxels. However, most existing methods are not feasible for solving this problem due to their extensive computational costs. In this work, we propose a novel multiresolution variable selection procedure under a Bayesian probit regression framework. It recursively uses posterior samples for coarser-scale variable selection to guide the posterior inference on finer-scale variable selection, leading to very efficient Markov chain Monte Carlo (MCMC) algorithms. The proposed algorithms are computationally feasible for ultra-high dimensional data. Also, our model incorporates two levels of structural information into variable selection using Ising priors: the spatial dependence between voxels and the functional connectivity between anatomical brain regions. Applied to the resting state functional magnetic resonance imaging (R-fMRI) data in the ABIDE study, our methods identify voxel-level imaging biomarkers highly predictive of the ASD, which are biologically meaningful and interpretable. Extensive simulations also show that our methods achieve better performance in variable selection compared to existing methods.

High dimensional entanglement

CSIR Research Space (South Africa)

Mc

2012-07-01

Full Text Available stream_source_info McLaren_2012.pdf.txt stream_content_type text/plain stream_size 2190 Content-Encoding ISO-8859-1 stream_name McLaren_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 High dimensional... entanglement M. McLAREN1,2, F.S. ROUX1 & A. FORBES1,2,3 1. CSIR National Laser Centre, PO Box 395, Pretoria 0001 2. School of Physics, University of the Stellenbosch, Private Bag X1, 7602, Matieland 3. School of Physics, University of Kwazulu...

High-precision two-dimensional atom localization via quantum interference in a tripod-type system

International Nuclear Information System (INIS)

Wang, Zhiping; Yu, Benli

2014-01-01

A scheme is proposed for high-precision two-dimensional atom localization in a four-level tripod-type atomic system via measurement of the excited state population. It is found that because of the position-dependent atom–field interaction, the precision of 2D atom localization can be significantly improved by appropriately adjusting the system parameters. Our scheme may be helpful in laser cooling or atom nanolithography via high-precision and high-resolution atom localization. (letter)

Critical states and thermomagnetic instabilities in three-dimensional nanostructured superconductors

Energy Technology Data Exchange (ETDEWEB)

Tamegai, T., E-mail: tamegai@ap.t.u-tokyo.ac.jp [Department of Applied Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mine, A.; Tsuchiya, Y.; Miyano, S.; Pyon, S. [Department of Applied Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mawatari, Y.; Nagasawa, S.; Hidaka, M. [National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8568 (Japan)

2017-02-15

Highlights: • Critical state field profiles and thermomagnetic instabilities are studied in three-dimensional nanostructured superconductors. • We find that the critical state field profiles in bi-layer systems are not simple superpositions of critical states in the two layers. • We also studied flux avalanches in shifted strip arrays with layer numbers up to six. • Various forms of avalanches either perpendicular or parallel to the strip are observed when the overlap between layers is large. • We find that introduction of asymmetry to shifted strip arrays affects the shape of flux avalanches sensitively. - Abstract: Critical state field profiles and thermomagnetic instabilities are studied in two kinds of three-dimensional nanostructured superconductors. We find that the critical state field profiles in some simple bi-layer systems are not simple superpositions of critical states in the two layers. Competition between the divergence of the local field at the edges of the film and the shielding by the neighboring layer makes novel critical state field profiles. We also studied flux avalanches in shifted strip arrays (SSAs) with layer numbers up to six. Various forms of avalanches either perpendicular or parallel to the strip are observed when the overlap between strips in neighboring layers is large. We also find that introduction of asymmetry in various forms to SSA affects the shape of flux avalanches sensitively.

Highly accurate analytical energy of a two-dimensional exciton in a constant magnetic field

International Nuclear Information System (INIS)

Hoang, Ngoc-Tram D.; Nguyen, Duy-Anh P.; Hoang, Van-Hung; Le, Van-Hoang

2016-01-01

Explicit expressions are given for analytically describing the dependence of the energy of a two-dimensional exciton on magnetic field intensity. These expressions are highly accurate with the precision of up to three decimal places for the whole range of the magnetic field intensity. The results are shown for the ground state and some excited states; moreover, we have all formulae to obtain similar expressions of any excited state. Analysis of numerical results shows that the precision of three decimal places is maintained for the excited states with the principal quantum number of up to n=100.

Highly accurate analytical energy of a two-dimensional exciton in a constant magnetic field

Energy Technology Data Exchange (ETDEWEB)

Hoang, Ngoc-Tram D. [Department of Physics, Ho Chi Minh City University of Pedagogy 280, An Duong Vuong Street, District 5, Ho Chi Minh City (Viet Nam); Nguyen, Duy-Anh P. [Department of Natural Science, Thu Dau Mot University, 6, Tran Van On Street, Thu Dau Mot City, Binh Duong Province (Viet Nam); Hoang, Van-Hung [Department of Physics, Ho Chi Minh City University of Pedagogy 280, An Duong Vuong Street, District 5, Ho Chi Minh City (Viet Nam); Le, Van-Hoang, E-mail: levanhoang@tdt.edu.vn [Atomic Molecular and Optical Physics Research Group, Ton Duc Thang University, 19 Nguyen Huu Tho Street, Tan Phong Ward, District 7, Ho Chi Minh City (Viet Nam); Faculty of Applied Sciences, Ton Duc Thang University, 19 Nguyen Huu Tho Street, Tan Phong Ward, District 7, Ho Chi Minh City (Viet Nam)

2016-08-15

Explicit expressions are given for analytically describing the dependence of the energy of a two-dimensional exciton on magnetic field intensity. These expressions are highly accurate with the precision of up to three decimal places for the whole range of the magnetic field intensity. The results are shown for the ground state and some excited states; moreover, we have all formulae to obtain similar expressions of any excited state. Analysis of numerical results shows that the precision of three decimal places is maintained for the excited states with the principal quantum number of up to n=100.

Clustering high dimensional data using RIA

Energy Technology Data Exchange (ETDEWEB)

Aziz, Nazrina [School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)

2015-05-15

Clustering may simply represent a convenient method for organizing a large data set so that it can easily be understood and information can efficiently be retrieved. However, identifying cluster in high dimensionality data sets is a difficult task because of the curse of dimensionality. Another challenge in clustering is some traditional functions cannot capture the pattern dissimilarity among objects. In this article, we used an alternative dissimilarity measurement called Robust Influence Angle (RIA) in the partitioning method. RIA is developed using eigenstructure of the covariance matrix and robust principal component score. We notice that, it can obtain cluster easily and hence avoid the curse of dimensionality. It is also manage to cluster large data sets with mixed numeric and categorical value.

Engineering topological edge states in two dimensional magnetic photonic crystal

Science.gov (United States)

Yang, Bing; Wu, Tong; Zhang, Xiangdong

2017-01-01

Based on a perturbative approach, we propose a simple and efficient method to engineer the topological edge states in two dimensional magnetic photonic crystals. The topological edge states in the microstructures can be constructed and varied by altering the parameters of the microstructure according to the field-energy distributions of the Bloch states at the related Bloch wave vectors. The validity of the proposed method has been demonstrated by exact numerical calculations through three concrete examples. Our method makes the topological edge states "designable."

Asymptotically Honest Confidence Regions for High Dimensional

DEFF Research Database (Denmark)

Caner, Mehmet; Kock, Anders Bredahl

While variable selection and oracle inequalities for the estimation and prediction error have received considerable attention in the literature on high-dimensional models, very little work has been done in the area of testing and construction of confidence bands in high-dimensional models. However...... develop an oracle inequality for the conservative Lasso only assuming the existence of a certain number of moments. This is done by means of the Marcinkiewicz-Zygmund inequality which in our context provides sharper bounds than Nemirovski's inequality. As opposed to van de Geer et al. (2014) we allow...

Edge states of a three-dimensional topological insulator

International Nuclear Information System (INIS)

Deb, Oindrila; Sen, Diptiman; Soori, Abhiram

2014-01-01

We use the bulk Hamiltonian for a three-dimensional topological insulator such as Bi 2 Se 3 to study the states which appear on its various surfaces and along the edge between two surfaces. We use both analytical methods based on the surface Hamiltonians (which are derived from the bulk Hamiltonian) and numerical methods based on a lattice discretization of the bulk Hamiltonian. We find that the application of a potential barrier along an edge can give rise to states localized at that edge. These states have an unusual energy-momentum dispersion which can be controlled by applying a potential along the edge; in particular, the velocity of these states can be tuned to zero. The scattering and conductance across the edge is studied as a function of the edge potential. We show that a magnetic field in a particular direction can also give rise to zero energy states on certain edges. We point out possible experimental ways of looking for the various edge states. (paper)

Relativistic bound-state problem of a one-dimensional system

International Nuclear Information System (INIS)

Sato, T.; Niwa, T.; Ohtsubo, H.; Tamura, K.

1991-01-01

A Poincare-covariant description of the two-body bound-state problem in one-dimensional space is studied by using the relativistic Schrodinger equation. We derive the many-body Hamiltonian, electromagnetic current and generators of the Poincare group in the framework of one-boson exchange. Our theory satisfies Poincare algebra within the one-boson-exchange approximation. We numerically study the relativistic effects on the bound-state wavefunction and the elastic electromagnetic form factor. The Lorentz boost of the bound-state wavefunction and the two-body exchange current are shown to play an important role in guaranteeing the Lorentz invariance of the form factor. (author)

Highly Efficient Broadband Yellow Phosphor Based on Zero-Dimensional Tin Mixed-Halide Perovskite.

Science.gov (United States)

Zhou, Chenkun; Tian, Yu; Yuan, Zhao; Lin, Haoran; Chen, Banghao; Clark, Ronald; Dilbeck, Tristan; Zhou, Yan; Hurley, Joseph; Neu, Jennifer; Besara, Tiglet; Siegrist, Theo; Djurovich, Peter; Ma, Biwu

2017-12-27

Organic-inorganic hybrid metal halide perovskites have emerged as a highly promising class of light emitters, which can be used as phosphors for optically pumped white light-emitting diodes (WLEDs). By controlling the structural dimensionality, metal halide perovskites can exhibit tunable narrow and broadband emissions from the free-exciton and self-trapped excited states, respectively. Here, we report a highly efficient broadband yellow light emitter based on zero-dimensional tin mixed-halide perovskite (C 4 N 2 H 14 Br) 4 SnBr x I 6-x (x = 3). This rare-earth-free ionically bonded crystalline material possesses a perfect host-dopant structure, in which the light-emitting metal halide species (SnBr x I 6-x 4- , x = 3) are completely isolated from each other and embedded in the wide band gap organic matrix composed of C 4 N 2 H 14 Br - . The strongly Stokes-shifted broadband yellow emission that peaked at 582 nm from this phosphor, which is a result of excited state structural reorganization, has an extremely large full width at half-maximum of 126 nm and a high photoluminescence quantum efficiency of ∼85% at room temperature. UV-pumped WLEDs fabricated using this yellow emitter together with a commercial europium-doped barium magnesium aluminate blue phosphor (BaMgAl 10 O 17 :Eu 2+ ) can exhibit high color rendering indexes of up to 85.

Classification of matrix-product ground states corresponding to one-dimensional chains of two-state sites of nearest neighbor interactions

International Nuclear Information System (INIS)

Fatollahi, Amir H.; Khorrami, Mohammad; Shariati, Ahmad; Aghamohammadi, Amir

2011-01-01

A complete classification is given for one-dimensional chains with nearest-neighbor interactions having two states in each site, for which a matrix product ground state exists. The Hamiltonians and their corresponding matrix product ground states are explicitly obtained.

Muon studies of low-dimensional solid state systems

International Nuclear Information System (INIS)

Jestaedt, T.

1999-04-01

of this spin-gap on the magnetic properties are investigated here. I also describe results of measurements on a material with even more reduced dimensionality, polybutadiene (PB). This is a non-conducting polymer without side-chains. Muons in this system can either be in a paramagnetic or a diamagnetic state (with a polymer radical state produced by reaction of muonium with a polymer bond). The nature of these states has been examined with a variety of μSR, techniques, and the influence of the polymer dynamics and the glass transition in PB is discussed. (author)

High Dimensional Classification Using Features Annealed Independence Rules.

Science.gov (United States)

Fan, Jianqing; Fan, Yingying

2008-01-01

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

Modeling High-Dimensional Multichannel Brain Signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert J.; Ombao, Hernando

2017-01-01

aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel

Quantum secret sharing based on modulated high-dimensional time-bin entanglement

International Nuclear Information System (INIS)

Takesue, Hiroki; Inoue, Kyo

2006-01-01

We propose a scheme for quantum secret sharing (QSS) that uses a modulated high-dimensional time-bin entanglement. By modulating the relative phase randomly by {0,π}, a sender with the entanglement source can randomly change the sign of the correlation of the measurement outcomes obtained by two distant recipients. The two recipients must cooperate if they are to obtain the sign of the correlation, which is used as a secret key. We show that our scheme is secure against intercept-and-resend (IR) and beam splitting attacks by an outside eavesdropper thanks to the nonorthogonality of high-dimensional time-bin entangled states. We also show that a cheating attempt based on an IR attack by one of the recipients can be detected by changing the dimension of the time-bin entanglement randomly and inserting two 'vacant' slots between the packets. Then, cheating attempts can be detected by monitoring the count rate in the vacant slots. The proposed scheme has better experimental feasibility than previously proposed entanglement-based QSS schemes

Single cell proteomics in biomedicine: High-dimensional data acquisition, visualization, and analysis.

Science.gov (United States)

Su, Yapeng; Shi, Qihui; Wei, Wei

2017-02-01

New insights on cellular heterogeneity in the last decade provoke the development of a variety of single cell omics tools at a lightning pace. The resultant high-dimensional single cell data generated by these tools require new theoretical approaches and analytical algorithms for effective visualization and interpretation. In this review, we briefly survey the state-of-the-art single cell proteomic tools with a particular focus on data acquisition and quantification, followed by an elaboration of a number of statistical and computational approaches developed to date for dissecting the high-dimensional single cell data. The underlying assumptions, unique features, and limitations of the analytical methods with the designated biological questions they seek to answer will be discussed. Particular attention will be given to those information theoretical approaches that are anchored in a set of first principles of physics and can yield detailed (and often surprising) predictions. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Long range order in the ground state of two-dimensional antiferromagnets

International Nuclear Information System (INIS)

Neves, E.J.; Perez, J.F.

1985-01-01

The existence of long range order is shown in the ground state of the two-dimensional isotropic Heisenberg antiferromagnet for S >= 3/2. The method yields also long range order for the ground state of a larger class of anisotropic quantum antiferromagnetic spin systems with or without transverse magnetic fields. (Author) [pt

Performance analysis of three-dimensional-triple-level cell and two-dimensional-multi-level cell NAND flash hybrid solid-state drives

Science.gov (United States)

Sakaki, Yukiya; Yamada, Tomoaki; Matsui, Chihiro; Yamaga, Yusuke; Takeuchi, Ken

2018-04-01

In order to improve performance of solid-state drives (SSDs), hybrid SSDs have been proposed. Hybrid SSDs consist of more than two types of NAND flash memories or NAND flash memories and storage-class memories (SCMs). However, the cost of hybrid SSDs adopting SCMs is more expensive than that of NAND flash only SSDs because of the high bit cost of SCMs. This paper proposes unique hybrid SSDs with two-dimensional (2D) horizontal multi-level cell (MLC)/three-dimensional (3D) vertical triple-level cell (TLC) NAND flash memories to achieve higher cost-performance. The 2D-MLC/3D-TLC hybrid SSD achieves up to 31% higher performance than the conventional 2D-MLC/2D-TLC hybrid SSD. The factors of different performance between the proposed hybrid SSD and the conventional hybrid SSD are analyzed by changing its block size, read/write/erase latencies, and write unit of 3D-TLC NAND flash memory, by means of a transaction-level modeling simulator.

A sparse grid based method for generative dimensionality reduction of high-dimensional data

Science.gov (United States)

Bohn, Bastian; Garcke, Jochen; Griebel, Michael

2016-03-01

Generative dimensionality reduction methods play an important role in machine learning applications because they construct an explicit mapping from a low-dimensional space to the high-dimensional data space. We discuss a general framework to describe generative dimensionality reduction methods, where the main focus lies on a regularized principal manifold learning variant. Since most generative dimensionality reduction algorithms exploit the representer theorem for reproducing kernel Hilbert spaces, their computational costs grow at least quadratically in the number n of data. Instead, we introduce a grid-based discretization approach which automatically scales just linearly in n. To circumvent the curse of dimensionality of full tensor product grids, we use the concept of sparse grids. Furthermore, in real-world applications, some embedding directions are usually more important than others and it is reasonable to refine the underlying discretization space only in these directions. To this end, we employ a dimension-adaptive algorithm which is based on the ANOVA (analysis of variance) decomposition of a function. In particular, the reconstruction error is used to measure the quality of an embedding. As an application, the study of large simulation data from an engineering application in the automotive industry (car crash simulation) is performed.

Dimensionality analysis of multiparticle production at high energies

International Nuclear Information System (INIS)

Chilingaryan, A.A.

1989-01-01

An algorithm of analysis of multiparticle final states is offered. By the Renyi dimensionalities, which were calculated according to experimental data, though it were hadron distribution over the rapidity intervals or particle distribution in an N-dimensional momentum space, we can judge about the degree of correlation of particles, separate the momentum space projections and areas where the probability measure singularities are observed. The method is tested in a series of calculations with samples of fractal object points and with samples obtained by means of different generators of pseudo- and quasi-random numbers. 27 refs.; 11 figs

Progress in high-dimensional percolation and random graphs

CERN Document Server

Heydenreich, Markus

2017-01-01

This text presents an engaging exposition of the active field of high-dimensional percolation that will likely provide an impetus for future work. With over 90 exercises designed to enhance the reader’s understanding of the material, as well as many open problems, the book is aimed at graduate students and researchers who wish to enter the world of this rich topic.  The text may also be useful in advanced courses and seminars, as well as for reference and individual study. Part I, consisting of 3 chapters, presents a general introduction to percolation, stating the main results, defining the central objects, and proving its main properties. No prior knowledge of percolation is assumed. Part II, consisting of Chapters 4–9, discusses mean-field critical behavior by describing the two main techniques used, namely, differential inequalities and the lace expansion. In Parts I and II, all results are proved, making this the first self-contained text discussing high-dimensiona l percolation.  Part III, consist...

High-efficiency one-dimensional atom localization via two parallel standing-wave fields

International Nuclear Information System (INIS)

Wang, Zhiping; Wu, Xuqiang; Lu, Liang; Yu, Benli

2014-01-01

We present a new scheme of high-efficiency one-dimensional (1D) atom localization via measurement of upper state population or the probe absorption in a four-level N-type atomic system. By applying two classical standing-wave fields, the localization peak position and number, as well as the conditional position probability, can be easily controlled by the system parameters, and the sub-half-wavelength atom localization is also observed. More importantly, there is 100% detecting probability of the atom in the subwavelength domain when the corresponding conditions are satisfied. The proposed scheme may open up a promising way to achieve high-precision and high-efficiency 1D atom localization. (paper)

Tonks-Girardeau and super-Tonks-Girardeau states of a trapped one-dimensional spinor Bose gas

International Nuclear Information System (INIS)

Girardeau, M. D.

2011-01-01

A harmonically trapped, ultracold, one-dimensional (1D) spin-1 Bose gas with strongly repulsive or attractive 1D even-wave interactions induced by a three-dimensional (3D) Feshbach resonance is studied. The exact ground state, a hybrid of Tonks-Girardeau (TG) and ideal Fermi gases, is constructed in the TG limit of infinite even-wave repulsion by a spinor Fermi-Bose mapping to a spinless ideal Fermi gas. It is then shown that in the limit of infinite even-wave attraction this same state remains an exact many-body eigenstate, now highly excited relative to the collapsed generalized McGuire-cluster ground state, showing that the hybrid TG state is completely stable against collapse to this cluster ground state under a sudden switch from infinite repulsion to infinite attraction. It is shown to be the TG limit of a hybrid super-Tonks-Girardeau (STG) state, which is metastable under a sudden switch from finite but very strong repulsion to finite but very strong attraction. It should be possible to create it experimentally by a sudden switch from strongly repulsive to strongly attractive interaction, as in the recent Innsbruck experiment on a spin-polarized bosonic STG gas. In the case of strong attraction, there should also exist another STG state of much lower energy, consisting of strongly bound dimers, a bosonic analog of a recently predicted STG state which is an ultracold gas of strongly bound bosonic dimers of fermionic atoms, but it is shown that this STG state cannot be created by such a switch from strong repulsion to strong attraction.

On infinite-dimensional state spaces

International Nuclear Information System (INIS)

Fritz, Tobias

2013-01-01

It is well known that the canonical commutation relation [x, p]=i can be realized only on an infinite-dimensional Hilbert space. While any finite set of experimental data can also be explained in terms of a finite-dimensional Hilbert space by approximating the commutation relation, Occam's razor prefers the infinite-dimensional model in which [x, p]=i holds on the nose. This reasoning one will necessarily have to make in any approach which tries to detect the infinite-dimensionality. One drawback of using the canonical commutation relation for this purpose is that it has unclear operational meaning. Here, we identify an operationally well-defined context from which an analogous conclusion can be drawn: if two unitary transformations U, V on a quantum system satisfy the relation V −1 U 2 V=U 3 , then finite-dimensionality entails the relation UV −1 UV=V −1 UVU; this implication strongly fails in some infinite-dimensional realizations. This is a result from combinatorial group theory for which we give a new proof. This proof adapts to the consideration of cases where the assumed relation V −1 U 2 V=U 3 holds only up to ε and then yields a lower bound on the dimension.

On infinite-dimensional state spaces

Science.gov (United States)

Fritz, Tobias

2013-05-01

It is well known that the canonical commutation relation [x, p] = i can be realized only on an infinite-dimensional Hilbert space. While any finite set of experimental data can also be explained in terms of a finite-dimensional Hilbert space by approximating the commutation relation, Occam's razor prefers the infinite-dimensional model in which [x, p] = i holds on the nose. This reasoning one will necessarily have to make in any approach which tries to detect the infinite-dimensionality. One drawback of using the canonical commutation relation for this purpose is that it has unclear operational meaning. Here, we identify an operationally well-defined context from which an analogous conclusion can be drawn: if two unitary transformations U, V on a quantum system satisfy the relation V-1U2V = U3, then finite-dimensionality entails the relation UV-1UV = V-1UVU; this implication strongly fails in some infinite-dimensional realizations. This is a result from combinatorial group theory for which we give a new proof. This proof adapts to the consideration of cases where the assumed relation V-1U2V = U3 holds only up to ɛ and then yields a lower bound on the dimension.

High-dimensional model estimation and model selection

CERN Multimedia

CERN. Geneva

2015-01-01

I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.

Edge state preparation in a one-dimensional lattice by quantum Lyapunov control

International Nuclear Information System (INIS)

Zhao, X L; Shi, Z C; Qin, M; Yi, X X

2017-01-01

Quantum Lyapunov control uses a feedback control methodology to determine control fields applied to control quantum systems in an open-loop way. In this work, we employ two Lyapunov control schemes to prepare an edge state for a fermionic chain consisting of cold atoms loaded in an optical lattice. Such a chain can be described by the Harper model. Corresponding to the two schemes, two types of quantum Lyapunov functions are considered. The results show that both the schemes are effective at preparing the edge state within a wide range of parameters. We found that the edge state can be prepared with high fidelity even if there are moderate fluctuations of on-site or hopping potentials. Both control schemes can be extended to similar chains (3 m + d , d = 2) of different lengths. Since a regular amplitude control field is easier to apply in practice, an amplitude-modulated control field is used to replace the unmodulated one. Such control approaches provide tools to explore the edge states of one-dimensional topological materials. (paper)

Determination of structure of oriented samples using two-dimensional solid state NMR techniques

International Nuclear Information System (INIS)

Jin Hong; Harbison, G.S.

1990-01-01

One dimensional and two-dimensional MAS techniques can give detailed information about the structure and dynamics of oriented systems. We describe the application of such techniques to the liquid-crystalline polymer poly(p-phenyleneterphtalimide) (PPTA), and thence deduce the solid-state structure of the material. (author). 9 refs.; 6 figs

Matrix correlations for high-dimensional data: The modified RV-coefficient

NARCIS (Netherlands)

Smilde, A.K.; Kiers, H.A.L.; Bijlsma, S.; Rubingh, C.M.; Erk, M.J. van

2009-01-01

Motivation: Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

Energy Technology Data Exchange (ETDEWEB)

Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)

2015-01-15

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming.

Science.gov (United States)

Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.

Approximating high-dimensional dynamics by barycentric coordinates with linear programming

International Nuclear Information System (INIS)

Hirata, Yoshito; Aihara, Kazuyuki; Suzuki, Hideyuki; Shiro, Masanori; Takahashi, Nozomu; Mas, Paloma

2015-01-01

The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data

A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data

Directory of Open Access Journals (Sweden)

Hongchao Song

2017-01-01

Full Text Available Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE and an ensemble k-nearest neighbor graphs- (K-NNG- based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.

One- and Two-dimensional Solitary Wave States in the Nonlinear Kramers Equation with Movement Direction as a Variable

Science.gov (United States)

Sakaguchi, Hidetsugu; Ishibashi, Kazuya

2018-06-01

We study self-propelled particles by direct numerical simulation of the nonlinear Kramers equation for self-propelled particles. In our previous paper, we studied self-propelled particles with velocity variables in one dimension. In this paper, we consider another model in which each particle exhibits directional motion. The movement direction is expressed with a variable ϕ. We show that one-dimensional solitary wave states appear in direct numerical simulations of the nonlinear Kramers equation in one- and two-dimensional systems, which is a generalization of our previous result. Furthermore, we find two-dimensionally localized states in the case that each self-propelled particle exhibits rotational motion. The center of mass of the two-dimensionally localized state exhibits circular motion, which implies collective rotating motion. Finally, we consider a simple one-dimensional model equation to qualitatively understand the formation of the solitary wave state.

Stable high efficiency two-dimensional perovskite solar cells via cesium doping

KAUST Repository

Zhang, Xu

2017-08-15

Two-dimensional (2D) organic-inorganic perovskites have recently emerged as one of the most important thin-film solar cell materials owing to their excellent environmental stability. The remaining major pitfall is their relatively poor photovoltaic performance in contrast to 3D perovskites. In this work we demonstrate cesium cation (Cs) doped 2D (BA)(MA)PbI perovskite solar cells giving a power conversion efficiency (PCE) as high as 13.7%, the highest among the reported 2D devices, with excellent humidity resistance. The enhanced efficiency from 12.3% (without Cs) to 13.7% (with 5% Cs) is attributed to perfectly controlled crystal orientation, an increased grain size of the 2D planes, superior surface quality, reduced trap-state density, enhanced charge-carrier mobility and charge-transfer kinetics. Surprisingly, it is found that the Cs doping yields superior stability for the 2D perovskite solar cells when subjected to a high humidity environment without encapsulation. The device doped using 5% Cs degrades only ca. 10% after 1400 hours of exposure in 30% relative humidity (RH), and exhibits significantly improved stability under heating and high moisture environments. Our results provide an important step toward air-stable and fully printable low dimensional perovskites as a next-generation renewable energy source.

On spectral distribution of high dimensional covariation matrices

DEFF Research Database (Denmark)

Heinrich, Claudio; Podolskij, Mark

In this paper we present the asymptotic theory for spectral distributions of high dimensional covariation matrices of Brownian diffusions. More specifically, we consider N-dimensional Itô integrals with time varying matrix-valued integrands. We observe n equidistant high frequency data points...... of the underlying Brownian diffusion and we assume that N/n -> c in (0,oo). We show that under a certain mixed spectral moment condition the spectral distribution of the empirical covariation matrix converges in distribution almost surely. Our proof relies on method of moments and applications of graph theory....

HSM: Heterogeneous Subspace Mining in High Dimensional Data

DEFF Research Database (Denmark)

Müller, Emmanuel; Assent, Ira; Seidl, Thomas

2009-01-01

Heterogeneous data, i.e. data with both categorical and continuous values, is common in many databases. However, most data mining algorithms assume either continuous or categorical attributes, but not both. In high dimensional data, phenomena due to the "curse of dimensionality" pose additional...... challenges. Usually, due to locally varying relevance of attributes, patterns do not show across the full set of attributes. In this paper we propose HSM, which defines a new pattern model for heterogeneous high dimensional data. It allows data mining in arbitrary subsets of the attributes that are relevant...... for the respective patterns. Based on this model we propose an efficient algorithm, which is aware of the heterogeneity of the attributes. We extend an indexing structure for continuous attributes such that HSM indexing adapts to different attribute types. In our experiments we show that HSM efficiently mines...

Quasi-one-dimensional density of states in a single quantum ring.

Science.gov (United States)

Kim, Heedae; Lee, Woojin; Park, Seongho; Kyhm, Kwangseuk; Je, Koochul; Taylor, Robert A; Nogues, Gilles; Dang, Le Si; Song, Jin Dong

2017-01-05

Generally confinement size is considered to determine the dimensionality of nanostructures. While the exciton Bohr radius is used as a criterion to define either weak or strong confinement in optical experiments, the binding energy of confined excitons is difficult to measure experimentally. One alternative is to use the temperature dependence of the radiative recombination time, which has been employed previously in quantum wells and quantum wires. A one-dimensional loop structure is often assumed to model quantum rings, but this approximation ceases to be valid when the rim width becomes comparable to the ring radius. We have evaluated the density of states in a single quantum ring by measuring the temperature dependence of the radiative recombination of excitons, where the photoluminescence decay time as a function of temperature was calibrated by using the low temperature integrated intensity and linewidth. We conclude that the quasi-continuous finely-spaced levels arising from the rotation energy give rise to a quasi-one-dimensional density of states, as long as the confined exciton is allowed to rotate around the opening of the anisotropic ring structure, which has a finite rim width.

Analysing spatially extended high-dimensional dynamics by recurrence plots

Energy Technology Data Exchange (ETDEWEB)

Marwan, Norbert, E-mail: marwan@pik-potsdam.de [Potsdam Institute for Climate Impact Research, 14412 Potsdam (Germany); Kurths, Jürgen [Potsdam Institute for Climate Impact Research, 14412 Potsdam (Germany); Humboldt Universität zu Berlin, Institut für Physik (Germany); Nizhny Novgorod State University, Department of Control Theory, Nizhny Novgorod (Russian Federation); Foerster, Saskia [GFZ German Research Centre for Geosciences, Section 1.4 Remote Sensing, Telegrafenberg, 14473 Potsdam (Germany)

2015-05-08

Recurrence plot based measures of complexity are capable tools for characterizing complex dynamics. In this letter we show the potential of selected recurrence plot measures for the investigation of even high-dimensional dynamics. We apply this method on spatially extended chaos, such as derived from the Lorenz96 model and show that the recurrence plot based measures can qualitatively characterize typical dynamical properties such as chaotic or periodic dynamics. Moreover, we demonstrate its power by analysing satellite image time series of vegetation cover with contrasting dynamics as a spatially extended and potentially high-dimensional example from the real world. - Highlights: • We use recurrence plots for analysing partially extended dynamics. • We investigate the high-dimensional chaos of the Lorenz96 model. • The approach distinguishes different spatio-temporal dynamics. • We use the method for studying vegetation cover time series.

Vapour-liquid equilibrium properties for two- and three-dimensional Lennard-Jones fluids from equations of state

International Nuclear Information System (INIS)

Mulero, A.; Cuadros, F; Faundez, C.A.

1999-01-01

Vapour-liquid equilibrium properties for both three- and two-dimensional Lennard-Jones fluids were obtained using simple cubic-in-density equations of state proposed by the authors. Results were compared with those obtained by other workers from computer simulations and also with results given by other more complex semi-theoretical or semi-empirical equations of state. In the three-dimensional case good agreement is found for all properties and all temperatures. In the two-dimensional case only the coexistence densities were compared, producing good agreement for low temperatures only. The present work is the first to give numerical data for the vapour-liquid equilibrium properties of Lennard-Jones fluids calculated from equations of state. Copyright (1999) CSIRO Australia

All-solid-state lithium-ion microbatteries: a review of various three-dimensional concepts

Energy Technology Data Exchange (ETDEWEB)

Oudenhoven, Jos F.M.; Baggetto, Loic; Notten, Peter H.L. [Eindhoven University of Technology, Department of Chemistry and Chemical Engineering, Postbus 513, 5600 MB Eindhoven (Netherlands)

2011-01-01

With the increasing importance of wireless microelectronic devices the need for on-board power supplies is evidently also increasing. Possible candidates for microenergy storage devices are planar all-solid-state Li-ion microbatteries, which are currently under development by several start-up companies. However, to increase the energy density of these microbatteries further and to ensure a high power delivery, three-dimensional (3D) designs are essential. Therefore, several concepts have been proposed for the design of 3D microbatteries and these are reviewed. In addition, an overview is given of the various electrode and electrolyte materials that are suitable for 3D all-solid-state microbatteries. Furthermore, methods are presented to produce films of these materials on a nano- and microscale. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Optimal conclusive teleportation of a d-dimensional two-particle unknown quantum state

Institute of Scientific and Technical Information of China (English)

Yang Yu-Guang; Wen Qiao-Yan; Zhu Fu-Chen

2006-01-01

A conclusive teleportation protocol of a d-dimensional two-particle unknown quantum state using three ddimensional particles in an arbitrary pure state is proposed. A sender teleports the unknown state conclusively to a receiver by using the positive operator valued measure(POVM) and introducing an ancillary qudit to perform the generalized Bell basis measurement. We calculate the optimal teleportation fidelity. We also discuss and analyse the reason why the information on the teleported state is lost in the course of the protocol.

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

International Nuclear Information System (INIS)

Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial

2016-01-01

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

Science.gov (United States)

Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial

2016-09-01

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation

Energy Technology Data Exchange (ETDEWEB)

Tripathy, Rohit, E-mail: rtripath@purdue.edu; Bilionis, Ilias, E-mail: ibilion@purdue.edu; Gonzalez, Marcial, E-mail: marcial-gonzalez@purdue.edu

2016-09-15

Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

High breakdown voltage quasi-two-dimensional β-Ga2O3 field-effect transistors with a boron nitride field plate

Science.gov (United States)

Bae, Jinho; Kim, Hyoung Woo; Kang, In Ho; Yang, Gwangseok; Kim, Jihyun

2018-03-01

We have demonstrated a β-Ga2O3 metal-semiconductor field-effect transistor (MESFET) with a high off-state breakdown voltage (344 V), based on a quasi-two-dimensional β-Ga2O3 field-plated with hexagonal boron nitride (h-BN). Both the β-Ga2O3 and h-BN were mechanically exfoliated from their respective crystal substrates, followed by dry-transfer onto a SiO2/Si substrate for integration into a high breakdown voltage quasi-two-dimensional β-Ga2O3 MESFETs. N-type conducting behavior was observed in the fabricated β-Ga2O3 MESFETs, along with a high on/off current ratio (>106) and excellent current saturation. A three-terminal off-state breakdown voltage of 344 V was obtained, with a threshold voltage of -7.3 V and a subthreshold swing of 84.6 mV/dec. The distribution of electric fields in the quasi-two-dimensional β-Ga2O3 MESFETs was simulated to analyze the role of the dielectric h-BN field plate in improving the off-state breakdown voltage. The stability of the field-plated β-Ga2O3 MESFET in air was confirmed after storing the MESFET in ambient air for one month. Our results pave the way for unlocking the full potential of β-Ga2O3 for use in a high-power nano-device with an ultrahigh breakdown voltage.

Rendering high charge density of states in ionic liquid-gated MoS 2 transistors

NARCIS (Netherlands)

Lee, Y.; Lee, J.; Kim, S.; Park, H.S.

2014-01-01

We investigated high charge density of states (DOS) in the bandgap of MoS2 nanosheets with variable temperature measurements on ionic liquid-gated MoS2 transistors. The thermally activated charge transport indicates that the electrical current in the two-dimensional MoS 2 nanosheets under high

Model-based Clustering of High-Dimensional Data in Astrophysics

Science.gov (United States)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

An Unbiased Distance-based Outlier Detection Approach for High-dimensional Data

DEFF Research Database (Denmark)

Nguyen, Hoang Vu; Gopalkrishnan, Vivekanand; Assent, Ira

2011-01-01

than a global property. Different from existing approaches, it is not grid-based and dimensionality unbiased. Thus, its performance is impervious to grid resolution as well as the curse of dimensionality. In addition, our approach ranks the outliers, allowing users to select the number of desired...... outliers, thus mitigating the issue of high false alarm rate. Extensive empirical studies on real datasets show that our approach efficiently and effectively detects outliers, even in high-dimensional spaces....

All-solid-state asymmetric supercapacitors based on Fe-doped mesoporous Co3O4 and three-dimensional reduced graphene oxide electrodes with high energy and power densities.

Science.gov (United States)

Zhang, Cheng; Wei, Jun; Chen, Leiyi; Tang, Shaolong; Deng, Mingsen; Du, Youwei

2017-10-19

An asymmetric supercapacitor offers opportunities to effectively utilize the full potential of the different potential windows of the two electrodes for a higher operating voltage, resulting in an enhanced specific capacitance and significantly improved energy without sacrificing the power delivery and cycle life. To achieve high energy and power densities, we have synthesized an all-solid-state asymmetric supercapacitor with a wider voltage range using Fe-doped Co 3 O 4 and three-dimensional reduced graphene oxide (3DrGO) as the positive and negative electrodes, respectively. In contrast to undoped Co 3 O 4 , the increased density of states and modified charge spatial separation endow the Fe-doped Co 3 O 4 electrode with greatly improved electrochemical capacitive performance, including high specific capacitance (1997 F g -1 and 1757 F g -1 at current densities of 1 and 20 A g -1 , respectively), excellent rate capability, and superior cycling stability. Remarkably, the optimized all-solid-state asymmetric supercapacitor can be cycled reversibly in a wide range of 0-1.8 V, thus delivering a high energy density (270.3 W h kg -1 ), high power density (9.0 kW kg -1 at 224.2 W h kg -1 ), and excellent cycling stability (91.8% capacitance retention after 10 000 charge-discharge cycles at a constant current density of 10 A g -1 ). The superior capacitive performance suggests that such an all-solid-state asymmetric supercapacitor shows great potential for developing energy storage systems with high levels of energy and power delivery.

Density of states of two-dimensional systems with long-range logarithmic interactions

Energy Technology Data Exchange (ETDEWEB)

Somoza, Andrés M.; Ortuño, Miguel; Baturina, Tatyana I.; Vinokur, Valerii M.

2015-08-03

We investigate a single-particle density of states (DOS) in strongly disordered two- dimensional high dielectric permittivity systems with logarithmic Coulomb interaction between particles. We derive self-consistent DOS at zero temperature and show that it is appreciably suppressed as compared to the DOS expected from the Efros-Shklovskii approach.We carry out zero- and finite-temperature Monte Carlo numerical studies of the DOS and find the perfect agreement between the numerical and analytical results at zero temperature, observing, in particular, a hardening of the Coulomb gap with the increasing electrostatic screening length. At finite temperatures, we reveal a striking scaling of the DOS as a function of energy normalized to the temperature of the system.

High-dimensional data in economics and their (robust) analysis

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2017-01-01

Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Institutional support: RVO:67985556 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BA - General Mathematics OBOR OECD: Business and management http://library.utia.cas.cz/separaty/2017/SI/kalina-0474076.pdf

Tunable states of interlayer cations in two-dimensional materials

International Nuclear Information System (INIS)

Sato, K.; Numata, K.; Dai, W.; Hunger, M.

2014-01-01

The local state of cations inside the Ångstrom-scale interlayer spaces is one of the controlling factors for designing sophisticated two-dimensional (2D) materials consisting of 2D nanosheets. In the present work, the molecular mechanism on how the interlayer cation states are induced by the local structures of the 2D nanosheets is highlighted. For this purpose, the local states of Na cations in inorganic 2D materials, in which the compositional fluctuations of a few percent are introduced in the tetrahedral and octahedral units of the 2D nanosheets, were systematically studied by means of 23 Na magic-angle-spinning (MAS) nuclear magnetic resonance (NMR) and 23 Na multiple-quantum MAS (MQMAS) NMR spectroscopy. In contrast with an uniform distribution of Na cations expected so far, various well-defined cation states sensitive to the local structures of the 2D nanosheets were identified. The tunability of the interlayer cation states along with the local structure of the 2D nanosheets, as the smallest structural unit of the 2D material, is discussed

Tunable states of interlayer cations in two-dimensional materials

Energy Technology Data Exchange (ETDEWEB)

Sato, K.; Numata, K. [Department of Environmental Sciences, Tokyo Gakugei University, Koganei, Tokyo 184-8501 (Japan); Dai, W. [Key Laboratory of Advanced Energy Materials Chemistry (Ministry of Education), College of Chemistry, Nankai University, Tianjin 300071 (China); Hunger, M. [Institute of Chemical Technology, University of Stuttgart, 70550 Stuttgart (Germany)

2014-03-31

The local state of cations inside the Ångstrom-scale interlayer spaces is one of the controlling factors for designing sophisticated two-dimensional (2D) materials consisting of 2D nanosheets. In the present work, the molecular mechanism on how the interlayer cation states are induced by the local structures of the 2D nanosheets is highlighted. For this purpose, the local states of Na cations in inorganic 2D materials, in which the compositional fluctuations of a few percent are introduced in the tetrahedral and octahedral units of the 2D nanosheets, were systematically studied by means of {sup 23}Na magic-angle-spinning (MAS) nuclear magnetic resonance (NMR) and {sup 23}Na multiple-quantum MAS (MQMAS) NMR spectroscopy. In contrast with an uniform distribution of Na cations expected so far, various well-defined cation states sensitive to the local structures of the 2D nanosheets were identified. The tunability of the interlayer cation states along with the local structure of the 2D nanosheets, as the smallest structural unit of the 2D material, is discussed.

Entanglement of arbitrary superpositions of modes within two-dimensional orbital angular momentum state spaces

International Nuclear Information System (INIS)

Jack, B.; Leach, J.; Franke-Arnold, S.; Ireland, D. G.; Padgett, M. J.; Yao, A. M.; Barnett, S. M.; Romero, J.

2010-01-01

We use spatial light modulators (SLMs) to measure correlations between arbitrary superpositions of orbital angular momentum (OAM) states generated by spontaneous parametric down-conversion. Our technique allows us to fully access a two-dimensional OAM subspace described by a Bloch sphere, within the higher-dimensional OAM Hilbert space. We quantify the entanglement through violations of a Bell-type inequality for pairs of modal superpositions that lie on equatorial, polar, and arbitrary great circles of the Bloch sphere. Our work shows that SLMs can be used to measure arbitrary spatial states with a fidelity sufficient for appropriate quantum information processing systems.

Compact Representation of High-Dimensional Feature Vectors for Large-Scale Image Recognition and Retrieval.

Science.gov (United States)

Zhang, Yu; Wu, Jianxin; Cai, Jianfei

2016-05-01

In large-scale visual recognition and image retrieval tasks, feature vectors, such as Fisher vector (FV) or the vector of locally aggregated descriptors (VLAD), have achieved state-of-the-art results. However, the combination of the large numbers of examples and high-dimensional vectors necessitates dimensionality reduction, in order to reduce its storage and CPU costs to a reasonable range. In spite of the popularity of various feature compression methods, this paper shows that the feature (dimension) selection is a better choice for high-dimensional FV/VLAD than the feature (dimension) compression methods, e.g., product quantization. We show that strong correlation among the feature dimensions in the FV and the VLAD may not exist, which renders feature selection a natural choice. We also show that, many dimensions in FV/VLAD are noise. Throwing them away using feature selection is better than compressing them and useful dimensions altogether using feature compression methods. To choose features, we propose an efficient importance sorting algorithm considering both the supervised and unsupervised cases, for visual recognition and image retrieval, respectively. Combining with the 1-bit quantization, feature selection has achieved both higher accuracy and less computational cost than feature compression methods, such as product quantization, on the FV and the VLAD image representations.

Saturated ideal kink/peeling formations described as three-dimensional magnetohydrodynamic tokamak equilibrium states

Energy Technology Data Exchange (ETDEWEB)

Cooper, W. A.; Brunetti, D.; Duval, B. P.; Faustin, J. M.; Graves, J. P.; Kleiner, A.; Patten, H.; Pfefferlé, D.; Porte, L.; Raghunathan, M.; Reimerdes, H.; Sauter, O.; Tran, T. M., E-mail: wilfred.cooper@epfl.ch [Ecole Polytechnique Fédérale de Lausanne (EPFL), Swiss Plasma Center (SPC), CH-1015 Lausanne (Switzerland)

2016-04-15

Free boundary magnetohydrodynamic equilibrium states with spontaneous three dimensional deformations of the plasma-vacuum interface are computed for the first time. The structures obtained have the appearance of saturated ideal external kink/peeling modes. High edge pressure gradients yield toroidal mode number n = 1 corrugations for a high edge bootstrap current and larger n distortions when this current is small. Deformations in the plasma boundary region induce a nonaxisymmetric Pfirsch-Schlüter current driving a field-aligned current ribbon consistent with reported experimental observations. A variation in the 3D equilibrium confirms that the n = 1 mode is a kink/peeling structure. We surmise that our calculated equilibrium structures constitute a viable model for the edge harmonic oscillations and outer modes associated with a quiescent H-mode operation in shaped tokamak plasmas.

High-dimensional Data in Economics and their (Robust) Analysis

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2017-01-01

Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability

High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps

International Nuclear Information System (INIS)

Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.; Chen, Xiao

2017-01-01

This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. It relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.

Enhanced, targeted sampling of high-dimensional free-energy landscapes using variationally enhanced sampling, with an application to chignolin.

Science.gov (United States)

Shaffer, Patrick; Valsson, Omar; Parrinello, Michele

2016-02-02

The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables. In this work we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the previously introduced variationally enhanced sampling, and we apply it to the miniprotein chignolin.

Enhanced, targeted sampling of high-dimensional free-energy landscapes using variationally enhanced sampling, with an application to chignolin

Science.gov (United States)

Shaffer, Patrick; Valsson, Omar; Parrinello, Michele

2016-01-01

The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables. In this work we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the previously introduced variationally enhanced sampling, and we apply it to the miniprotein chignolin. PMID:26787868

Wide applicability of high-Tc pairing originating from coexisting wide and incipient narrow bands in quasi-one-dimensional systems

Science.gov (United States)

Matsumoto, Karin; Ogura, Daisuke; Kuroki, Kazuhiko

2018-01-01

We study superconductivity in the Hubbard model on various quasi-one-dimensional lattices with coexisting wide and narrow bands originating from multiple sites within a unit cell, where each site corresponds to a single orbital. The systems studied are the two-leg and three-leg ladders, the diamond chain, and the crisscross ladder. These one-dimensional lattices are weakly coupled to form two-dimensional (quasi-one-dimensional) ones, and the fluctuation exchange approximation is adopted to study spin-fluctuation-mediated superconductivity. When one of the bands is perfectly flat and the Fermi level intersecting the wide band is placed in the vicinity of, but not within, the flat band, superconductivity arising from the interband scattering processes is found to be strongly enhanced owing to the combination of the light electron mass of the wide band and the strong pairing interaction due to the large density of states of the flat band. Even when the narrow band has finite bandwidth, the pairing mechanism still works since the edge of the narrow band, due to its large density of states, plays the role of the flat band. The results indicate the wide applicability of the high-Tc pairing mechanism due to coexisting wide and "incipient" narrow bands in quasi-one-dimensional systems.

High-Dimensional Function Approximation With Neural Networks for Large Volumes of Data.

Science.gov (United States)

Andras, Peter

2018-02-01

Approximation of high-dimensional functions is a challenge for neural networks due to the curse of dimensionality. Often the data for which the approximated function is defined resides on a low-dimensional manifold and in principle the approximation of the function over this manifold should improve the approximation performance. It has been show that projecting the data manifold into a lower dimensional space, followed by the neural network approximation of the function over this space, provides a more precise approximation of the function than the approximation of the function with neural networks in the original data space. However, if the data volume is very large, the projection into the low-dimensional space has to be based on a limited sample of the data. Here, we investigate the nature of the approximation error of neural networks trained over the projection space. We show that such neural networks should have better approximation performance than neural networks trained on high-dimensional data even if the projection is based on a relatively sparse sample of the data manifold. We also find that it is preferable to use a uniformly distributed sparse sample of the data for the purpose of the generation of the low-dimensional projection. We illustrate these results considering the practical neural network approximation of a set of functions defined on high-dimensional data including real world data as well.

Detection of Subtle Context-Dependent Model Inaccuracies in High-Dimensional Robot Domains.

Science.gov (United States)

Mendoza, Juan Pablo; Simmons, Reid; Veloso, Manuela

2016-12-01

Autonomous robots often rely on models of their sensing and actions for intelligent decision making. However, when operating in unconstrained environments, the complexity of the world makes it infeasible to create models that are accurate in every situation. This article addresses the problem of using potentially large and high-dimensional sets of robot execution data to detect situations in which a robot model is inaccurate-that is, detecting context-dependent model inaccuracies in a high-dimensional context space. To find inaccuracies tractably, the robot conducts an informed search through low-dimensional projections of execution data to find parametric Regions of Inaccurate Modeling (RIMs). Empirical evidence from two robot domains shows that this approach significantly enhances the detection power of existing RIM-detection algorithms in high-dimensional spaces.

High-Harmonic Generation in Solids with and without Topological Edge States

DEFF Research Database (Denmark)

Bauer, Dieter; Hansen, Kenneth Christian Klochmann

2018-01-01

High-harmonic generation in the two topological phases of a finite, one-dimensional, periodic structure is investigated using a self-consistent time-dependent density functional theory approach. For harmonic photon energies smaller than the band gap, the harmonic yield is found to differ by up...... to 14 orders of magnitude for the two topological phases. This giant topological effect is explained by the degree of destructive interference in the harmonic emission of all valence-band (and edge-state) electrons, which strongly depends on whether or not topological edge states are present...

A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

KAUST Repository

Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun

2017-01-01

The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.

A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix

KAUST Repository

Hu, Zongliang

2017-09-27

The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.

A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix.

Science.gov (United States)

Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun

2017-09-21

The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.

Numerical method for three dimensional steady-state two-phase flow calculations

International Nuclear Information System (INIS)

Raymond, P.; Toumi, I.

1992-01-01

This paper presents the numerical scheme which was developed for the FLICA-4 computer code to calculate three dimensional steady state two phase flows. This computer code is devoted to steady state and transient thermal hydraulics analysis of nuclear reactor cores 1,3 . The first section briefly describes the FLICA-4 flow modelling. Then in order to introduce the numerical method for steady state computations, some details are given about the implicit numerical scheme based upon an approximate Riemann solver which was developed for calculation of flow transients. The third section deals with the numerical method for steady state computations, which is derived from this previous general scheme and its optimization. We give some numerical results for steady state calculations and comparisons on required CPU time and memory for various meshing and linear system solvers

Three-dimensional simulation of grain mixing in three different rotating drum designs for solid-state fermentation

NARCIS (Netherlands)

Schutyser, M.A.I.; Weber, F.J.; Briels, W.J.; Boom, R.M.; Rinzema, A.

2002-01-01

A previously published two-dimensional discrete particle simulation model for radial mixing behavior of various slowly rotating drums for solid-state fermentation (SSF) has been extended to a three-dimensional model that also predicts axial mixing. Radial and axial mixing characteristics were

Resonant state expansion applied to three-dimensional open optical systems

OpenAIRE

Doost, M. B.; Langbein, W.; Muljarov, E. A.

2014-01-01

The resonant-state expansion (RSE), a rigorous perturbative method in electrodynamics, is developed for three-dimensional open optical systems. Results are presented using the analytically solvable homogeneous dielectric sphere as unperturbed system. Since any perturbation which breaks the spherical symmetry mixes transverse electric (TE) and transverse magnetic (TM) modes, the RSE is extended here to include TM modes and a zero-frequency pole of the Green's function. We demonstrate the valid...

Dimensional reduction from entanglement in Minkowski space

International Nuclear Information System (INIS)

Brustein, Ram; Yarom, Amos

2005-01-01

Using a quantum field theoretic setting, we present evidence for dimensional reduction of any sub-volume of Minkowksi space. First, we show that correlation functions of a class of operators restricted to a sub-volume of D-dimensional Minkowski space scale as its surface area. A simple example of such area scaling is provided by the energy fluctuations of a free massless quantum field in its vacuum state. This is reminiscent of area scaling of entanglement entropy but applies to quantum expectation values in a pure state, rather than to statistical averages over a mixed state. We then show, in a specific case, that fluctuations in the bulk have a lower-dimensional representation in terms of a boundary theory at high temperature. (author)

Equation of state of the one- and three-dimensional Bose-Bose gases

Science.gov (United States)

Chiquillo, Emerson

2018-06-01

We calculate the equation of state of Bose-Bose gases in one and three dimensions in the framework of an effective quantum field theory. The beyond-mean-field approximation at zero temperature and the one-loop finite-temperature results are obtained performing functional integration on a local effective action. The ultraviolet divergent zero-point quantum fluctuations are removed by means of dimensional regularization. We derive the nonlinear Schrödinger equation to describe one- and three-dimensional Bose-Bose mixtures and solve it analytically in the one-dimensional scenario. This equation supports self-trapped brightlike solitonic droplets and self-trapped darklike solitons. At low temperature, we also find that the pressure and the number of particles of symmetric quantum droplets have a nontrivial dependence on the chemical potential and the difference between the intra- and the interspecies coupling constants.

Three-dimensional reconstruction of highly complex microscopic samples using scanning electron microscopy and optical flow estimation.

Directory of Open Access Journals (Sweden)

Ahmadreza Baghaie

Full Text Available Scanning Electron Microscope (SEM as one of the major research and industrial equipment for imaging of micro-scale samples and surfaces has gained extensive attention from its emerge. However, the acquired micrographs still remain two-dimensional (2D. In the current work a novel and highly accurate approach is proposed to recover the hidden third-dimension by use of multi-view image acquisition of the microscopic samples combined with pre/post-processing steps including sparse feature-based stereo rectification, nonlocal-based optical flow estimation for dense matching and finally depth estimation. Employing the proposed approach, three-dimensional (3D reconstructions of highly complex microscopic samples were achieved to facilitate the interpretation of topology and geometry of surface/shape attributes of the samples. As a byproduct of the proposed approach, high-definition 3D printed models of the samples can be generated as a tangible means of physical understanding. Extensive comparisons with the state-of-the-art reveal the strength and superiority of the proposed method in uncovering the details of the highly complex microscopic samples.

Distribution of high-dimensional entanglement via an intra-city free-space link.

Science.gov (United States)

Steinlechner, Fabian; Ecker, Sebastian; Fink, Matthias; Liu, Bo; Bavaresco, Jessica; Huber, Marcus; Scheidl, Thomas; Ursin, Rupert

2017-07-24

Quantum entanglement is a fundamental resource in quantum information processing and its distribution between distant parties is a key challenge in quantum communications. Increasing the dimensionality of entanglement has been shown to improve robustness and channel capacities in secure quantum communications. Here we report on the distribution of genuine high-dimensional entanglement via a 1.2-km-long free-space link across Vienna. We exploit hyperentanglement, that is, simultaneous entanglement in polarization and energy-time bases, to encode quantum information, and observe high-visibility interference for successive correlation measurements in each degree of freedom. These visibilities impose lower bounds on entanglement in each subspace individually and certify four-dimensional entanglement for the hyperentangled system. The high-fidelity transmission of high-dimensional entanglement under real-world atmospheric link conditions represents an important step towards long-distance quantum communications with more complex quantum systems and the implementation of advanced quantum experiments with satellite links.

Statistical Analysis for High-Dimensional Data : The Abel Symposium 2014

CERN Document Server

Bühlmann, Peter; Glad, Ingrid; Langaas, Mette; Richardson, Sylvia; Vannucci, Marina

2016-01-01

This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on...

Modeling high dimensional multichannel brain signals

KAUST Repository

Hu, Lechuan

2017-03-27

In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

Modeling high dimensional multichannel brain signals

KAUST Repository

Hu, Lechuan; Fortin, Norbert; Ombao, Hernando

2017-01-01

In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.

All-Solid-State High-Energy Asymmetric Supercapacitors Enabled by Three-Dimensional Mixed-Valent MnOx Nanospike and Graphene Electrodes.

Science.gov (United States)

Yang, Jie; Li, Guizhu; Pan, Zhenghui; Liu, Meinan; Hou, Yuan; Xu, Yijun; Deng, Hong; Sheng, Leimei; Zhao, Xinluo; Qiu, Yongcai; Zhang, Yuegang

2015-10-14

Three-dimensional (3D) nanostructures enable high-energy storage devices. Here we report a 3D manganese oxide nanospike (NSP) array electrode fabricated by anodization and subsequent electrodeposition. All-solid-state asymmetric supercapacitors were assembled with the 3D Al@Ni@MnOx NSP as the positive electrode, chemically converted graphene (CCG) as the negative electrode, and Na2SO4/poly(vinyl alcohol) (PVA) as the polymer gel electrolyte. Taking advantage of the different potential windows of Al@Ni@MnOx NSP and CCG electrodes, the asymmetric supercapacitor showed an ideal capacitive behavior with a cell voltage up to 1.8 V, capable of lighting up a red LED indicator (nominal voltage of 1.8 V). The device could deliver an energy density of 23.02 W h kg(-1) at a current density of 1 A g(-1). It could also preserve 96.3% of its initial capacitance at a current density of 2 A g(-1) after 10000 charging/discharging cycles. The remarkable performance is attributed to the unique 3D NSP array structure that could play an important role in increasing the effective electrode surface area, facilitating electrolyte permeation, and shortening the electron pathway in the active materials.

Magnetic quantum tunneling: key insights from multi-dimensional high-field EPR.

Science.gov (United States)

Lawrence, J; Yang, E-C; Hendrickson, D N; Hill, S

2009-08-21

Multi-dimensional high-field/frequency electron paramagnetic resonance (HFEPR) spectroscopy is performed on single-crystals of the high-symmetry spin S = 4 tetranuclear single-molecule magnet (SMM) [Ni(hmp)(dmb)Cl](4), where hmp(-) is the anion of 2-hydroxymethylpyridine and dmb is 3,3-dimethyl-1-butanol. Measurements performed as a function of the applied magnetic field strength and its orientation within the hard-plane reveal the four-fold behavior associated with the fourth order transverse zero-field splitting (ZFS) interaction, (1/2)B(S + S), within the framework of a rigid spin approximation (with S = 4). This ZFS interaction mixes the m(s) = +/-4 ground states in second order of perturbation, generating a sizeable (12 MHz) tunnel splitting, which explains the fast magnetic quantum tunneling in this SMM. Meanwhile, multi-frequency measurements performed with the field parallel to the easy-axis reveal HFEPR transitions associated with excited spin multiplets (S spin s = 1 Ni(II) ions within the cluster, as well as a characterization of the ZFS within excited states. The combined experimental studies support recent work indicating that the fourth order anisotropy associated with the S = 4 state originates from second order ZFS interactions associated with the individual Ni(II) centers, but only as a result of higher-order processes that occur via S-mixing between the ground state and higher-lying (S spin multiplets. We argue that this S-mixing plays an important role in the low-temperature quantum dynamics associated with many other well known SMMs.

Topology of high-dimensional manifolds

Energy Technology Data Exchange (ETDEWEB)

Farrell, F T [State University of New York, Binghamton (United States); Goettshe, L [Abdus Salam ICTP, Trieste (Italy); Lueck, W [Westfaelische Wilhelms-Universitaet Muenster, Muenster (Germany)

2002-08-15

The School on High-Dimensional Manifold Topology took place at the Abdus Salam ICTP, Trieste from 21 May 2001 to 8 June 2001. The focus of the school was on the classification of manifolds and related aspects of K-theory, geometry, and operator theory. The topics covered included: surgery theory, algebraic K- and L-theory, controlled topology, homology manifolds, exotic aspherical manifolds, homeomorphism and diffeomorphism groups, and scalar curvature. The school consisted of 2 weeks of lecture courses and one week of conference. Thwo-part lecture notes volume contains the notes of most of the lecture courses.

Multiparty-controlled Joint Remote Preparation of an Arbitrary m-qudit State with d-dimensional Greenberger-Horne-Zeilinger States

Science.gov (United States)

Lv, Shu-Xin; Zhao, Zheng-Wei; Zhou, Ping

2018-01-01

We present a scheme for multiparty-controlled joint remote preparation of an arbitrary m-qudit state by using d-dimensional Greenberger-Horne-Zeilinger (GHZ) states as the quantum channel. An arbitrary m-qudit state can be transmitted from two senders to a remote receiver in a quantum communication network under the controller's control. The senders perform m-qudit measurements according to their information of prepared state, the controllers only need perform single-particle projective measurements. The receiver can prepare the original state on his quantum system by performing corresponding unitary operation according the measurement results of the senders and controllers. It is shown that an arbitrary m-qudit state in general form can be controlled joint remote prepared if and only if the receiver cooperates with all the senders and controllers.

Forming a three-dimensional porous organic network via solid-state explosion of organic single crystals.

Science.gov (United States)

Bae, Seo-Yoon; Kim, Dongwook; Shin, Dongbin; Mahmood, Javeed; Jeon, In-Yup; Jung, Sun-Min; Shin, Sun-Hee; Kim, Seok-Jin; Park, Noejung; Lah, Myoung Soo; Baek, Jong-Beom

2017-11-17

Solid-state reaction of organic molecules holds a considerable advantage over liquid-phase processes in the manufacturing industry. However, the research progress in exploring this benefit is largely staggering, which leaves few liquid-phase systems to work with. Here, we show a synthetic protocol for the formation of a three-dimensional porous organic network via solid-state explosion of organic single crystals. The explosive reaction is realized by the Bergman reaction (cycloaromatization) of three enediyne groups on 2,3,6,7,14,15-hexaethynyl-9,10-dihydro-9,10-[1,2]benzenoanthracene. The origin of the explosion is systematically studied using single-crystal X-ray diffraction and differential scanning calorimetry, along with high-speed camera and density functional theory calculations. The results suggest that the solid-state explosion is triggered by an abrupt change in lattice energy induced by release of primer molecules in the 2,3,6,7,14,15-hexaethynyl-9,10-dihydro-9,10-[1,2]benzenoanthracene crystal lattice.

A qualitative numerical study of high dimensional dynamical systems

Science.gov (United States)

Albers, David James

Since Poincare, the father of modern mathematical dynamical systems, much effort has been exerted to achieve a qualitative understanding of the physical world via a qualitative understanding of the functions we use to model the physical world. In this thesis, we construct a numerical framework suitable for a qualitative, statistical study of dynamical systems using the space of artificial neural networks. We analyze the dynamics along intervals in parameter space, separating the set of neural networks into roughly four regions: the fixed point to the first bifurcation; the route to chaos; the chaotic region; and a transition region between chaos and finite-state neural networks. The study is primarily with respect to high-dimensional dynamical systems. We make the following general conclusions as the dimension of the dynamical system is increased: the probability of the first bifurcation being of type Neimark-Sacker is greater than ninety-percent; the most probable route to chaos is via a cascade of bifurcations of high-period periodic orbits, quasi-periodic orbits, and 2-tori; there exists an interval of parameter space such that hyperbolicity is violated on a countable, Lebesgue measure 0, "increasingly dense" subset; chaos is much more likely to persist with respect to parameter perturbation in the chaotic region of parameter space as the dimension is increased; moreover, as the number of positive Lyapunov exponents is increased, the likelihood that any significant portion of these positive exponents can be perturbed away decreases with increasing dimension. The maximum Kaplan-Yorke dimension and the maximum number of positive Lyapunov exponents increases linearly with dimension. The probability of a dynamical system being chaotic increases exponentially with dimension. The results with respect to the first bifurcation and the route to chaos comment on previous results of Newhouse, Ruelle, Takens, Broer, Chenciner, and Iooss. Moreover, results regarding the high-dimensional

Two-Dimensional Steady-State Boundary Shape Inversion of CGM-SPSO Algorithm on Temperature Information

Directory of Open Access Journals (Sweden)

Shoubin Wang

2017-01-01

Full Text Available Addressing the problem of two-dimensional steady-state thermal boundary recognition, a hybrid algorithm of conjugate gradient method and social particle swarm optimization (CGM-SPSO algorithm is proposed. The global search ability of particle swarm optimization algorithm and local search ability of gradient algorithm are effectively combined, which overcomes the shortcoming that the conjugate gradient method tends to converge to the local solution and relies heavily on the initial approximation of the iterative process. The hybrid algorithm also avoids the problem that the particle swarm optimization algorithm requires a large number of iterative steps and a lot of time. The experimental results show that the proposed algorithm is feasible and effective in solving the problem of two-dimensional steady-state thermal boundary shape.

Two-dimensional impurity transport calculations for a high recycling divertor

International Nuclear Information System (INIS)

Brooks, J.N.

1986-04-01

Two dimensional analysis of impurity transport in a high recycling divertor shows asymmetric particle fluxes to the divertor plate, low helium pumping efficiency, and high scrapeoff zone shielding for sputtered impurities

Local density of states in two-dimensional topological superconductors under a magnetic field: Signature of an exterior Majorana bound state

Science.gov (United States)

Suzuki, Shu-Ichiro; Kawaguchi, Yuki; Tanaka, Yukio

2018-04-01

We study quasiparticle states on a surface of a topological insulator (TI) with proximity-induced superconductivity under an external magnetic field. An applied magnetic field creates two Majorana bound states: a vortex Majorana state localized inside a vortex core and an exterior Majorana state localized along a circle centered at the vortex core. We calculate the spin-resolved local density of states (LDOS) and demonstrate that the shrinking of the radius of the exterior Majorana state, predicted in R. S. Akzyanov et al., Phys. Rev. B 94, 125428 (2016), 10.1103/PhysRevB.94.125428, under a strong magnetic field can be seen in LDOS without smeared out by nonzero-energy states. The spin-resolved LDOS further reveals that the spin of the exterior Majorana state is strongly spin-polarized. Accordingly, the induced odd-frequency spin-triplet pairs are found to be spin-polarized as well. In order to detect the exterior Majorana states, however, the Fermi energy should be closed to the Dirac point to avoid contributions from continuum levels. We also study a different two-dimensional topological-superconducting system where a two-dimensional electron gas with the spin-orbit coupling is sandwiched between an s -wave superconductor and a ferromagnetic insulator. We show that the radius of an exterior Majorana state can be tuned by an applied magnetic field. However, on the contrary to the results at a TI surface, neither the exterior Majorana state nor the induced odd-frequency spin-triplet pairs are spin-polarized. We conclude that the spin polarization of the Majorana state is attributed to the spin-polarized Landau level, which is characteristic for systems with the Dirac-like dispersion.

Topological origin of edge states in two-dimensional inversion-symmetric insulators and semimetals

NARCIS (Netherlands)

Miert, Guido van|info:eu-repo/dai/nl/413490378; Ortix, Carmine|info:eu-repo/dai/nl/413315304; de Morais Smith, C.|info:eu-repo/dai/nl/304836346

2017-01-01

Symmetries play an essential role in identifying and characterizing topological states of matter. Here, we classify topologically two-dimensional (2D) insulators and semimetals with vanishing spin-orbit coupling using time-reversal ($\\mathcal{T}$) and inversion ($\\mathcal{I}$) symmetry. This allows

On the Zeeman Effect in highly excited atoms: 2. Three-dimensional case

International Nuclear Information System (INIS)

Baseia, B.; Medeiros e Silva Filho, J.

1984-01-01

A previous result, found in two-dimensional hydrogen-atoms, is extended to the three-dimensional case. A mapping of a four-dimensional space R 4 onto R 3 , that establishes an equivalence between Coulomb and harmonic potentials, is used to show that the exact solution of the Zeeman effect in highly excited atoms, cannot be reached. (Author) [pt

Multi-dimensional analysis of high resolution γ-ray data

International Nuclear Information System (INIS)

Flibotte, S.; Huttmeier, U.J.; France, G. de; Haas, B.; Romain, P.; Theisen, Ch.; Vivien, J.P.; Zen, J.; Bednarczyk, P.

1992-01-01

High resolution γ-ray multi-detectors capable of measuring high-fold coincidences with a large efficiency are presently under construction (EUROGAM, GASP, GAMMASPHERE). The future experimental progress in our understanding of nuclear structure at high spin critically depends on our ability to analyze the data in a multi-dimensional space and to resolve small photopeaks of interest from the generally large background. Development of programs to process such high-fold events is still in its infancy and only the 3-fold case has been treated so far. As a contribution to the software development associated with the EUROGAM spectrometer, we have written and tested the performances of computer codes designed to select multi-dimensional gates from 3-, 4- and 5-fold coincidence databases. The tests were performed on events generated with a Monte Carlo simulation and also on experimental data (triples) recorded with the 8π spectrometer and with a preliminary version of the EUROGAM array. (author). 7 refs., 3 tabs., 1 fig

Multi-dimensional analysis of high resolution {gamma}-ray data

Energy Technology Data Exchange (ETDEWEB)

Flibotte, S; Huttmeier, U J; France, G de; Haas, B; Romain, P; Theisen, Ch; Vivien, J P; Zen, J [Centre National de la Recherche Scientifique (CNRS), 67 - Strasbourg (France); Bednarczyk, P [Institute of Nuclear Physics, Cracow (Poland)

1992-08-01

High resolution {gamma}-ray multi-detectors capable of measuring high-fold coincidences with a large efficiency are presently under construction (EUROGAM, GASP, GAMMASPHERE). The future experimental progress in our understanding of nuclear structure at high spin critically depends on our ability to analyze the data in a multi-dimensional space and to resolve small photopeaks of interest from the generally large background. Development of programs to process such high-fold events is still in its infancy and only the 3-fold case has been treated so far. As a contribution to the software development associated with the EUROGAM spectrometer, we have written and tested the performances of computer codes designed to select multi-dimensional gates from 3-, 4- and 5-fold coincidence databases. The tests were performed on events generated with a Monte Carlo simulation and also on experimental data (triples) recorded with the 8{pi} spectrometer and with a preliminary version of the EUROGAM array. (author). 7 refs., 3 tabs., 1 fig.

On Robust Information Extraction from High-Dimensional Data

Czech Academy of Sciences Publication Activity Database

Kalina, Jan

2014-01-01

Roč. 9, č. 1 (2014), s. 131-144 ISSN 1452-4864 Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : data mining * high-dimensional data * robust econometrics * outliers * machine learning Subject RIV: IN - Informatics, Computer Science

Theory of the one- and two-dimensional electron gas

International Nuclear Information System (INIS)

Emery, V.J.

1987-01-01

Two topics are discussed: (1) the competition between 2k/sub F/ and 4k/sub F/ charge state waves in a one-dimensional electron gas and (2) a two-dimensional model of high T/sub c/ superconductivity in the oxides

Quantum optimal control pathways of ozone isomerization dynamics subject to competing dissociation: A two-state one-dimensional model

International Nuclear Information System (INIS)

Kurosaki, Yuzuru; Ho, Tak-San; Rabitz, Herschel

2014-01-01

We construct a two-state one-dimensional reaction-path model for ozone open → cyclic isomerization dynamics. The model is based on the intrinsic reaction coordinate connecting the cyclic and open isomers with the O 2 + O asymptote on the ground-state 1 A ′ potential energy surface obtained with the high-level ab initio method. Using this two-state model time-dependent wave packet optimal control simulations are carried out. Two possible pathways are identified along with their respective band-limited optimal control fields; for pathway 1 the wave packet initially associated with the open isomer is first pumped into a shallow well on the excited electronic state potential curve and then driven back to the ground electronic state to form the cyclic isomer, whereas for pathway 2 the corresponding wave packet is excited directly to the primary well of the excited state potential curve. The simulations reveal that the optimal field for pathway 1 produces a final yield of nearly 100% with substantially smaller intensity than that obtained in a previous study [Y. Kurosaki, M. Artamonov, T.-S. Ho, and H. Rabitz, J. Chem. Phys. 131, 044306 (2009)] using a single-state one-dimensional model. Pathway 2, due to its strong coupling to the dissociation channel, is less effective than pathway 1. The simulations also show that nonlinear field effects due to molecular polarizability and hyperpolarizability are small for pathway 1 but could become significant for pathway 2 because much higher field intensity is involved in the latter. The results suggest that a practical control may be feasible with the aid of a few lowly excited electronic states for ozone isomerization

Three-dimensional nitrogen and boron co-doped graphene for high-performance all-solid-state supercapacitors

Energy Technology Data Exchange (ETDEWEB)

Wu, Zhong-Shuai; Chen, Long; Sun, Yi; Muellen, Klaus [Max-Planck-Institut fuer Polymerforschung, Ackermannweg 10, 55128 Mainz (Germany); Winter, Andreas; Turchanin, Andrey [Universitaet Bielefeld, Fakultaet fuer Physik, Physik Supramolekularer Systeme und Oberflaechen, Universitaetsstr. 25D, 33615 Bielefeld (Germany); Feng, Xinliang [Max-Planck-Institut fuer Polymerforschung, Ackermannweg 10, 55128 Mainz (Germany); School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, 200240, Shanghai (China)

2012-09-25

A simplified prototype device of high-performance all-solid-state supercapacitors (ASSSs) based on 3D nitrogen and boron co-doped monolithic graphene aerogels (BN-GAs) is demonstrated for the first time. The resulting ASSSs show high specific capacitance, good rate capability, and enhanced energy density or power density. (Copyright copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

High performance top-gated ferroelectric field effect transistors based on two-dimensional ZnO nanosheets

Science.gov (United States)

Tian, Hongzheng; Wang, Xudong; Zhu, Yuankun; Liao, Lei; Wang, Xianying; Wang, Jianlu; Hu, Weida

2017-01-01

High quality ultrathin two-dimensional zinc oxide (ZnO) nanosheets (NSs) are synthesized, and the ZnO NS ferroelectric field effect transistors (FeFETs) are demonstrated based on the P(VDF-TrFE) polymer film used as the top gate insulating layer. The ZnO NSs exhibit a maximum field effect mobility of 588.9 cm2/Vs and a large transconductance of 2.5 μS due to their high crystalline quality and ultrathin two-dimensional structure. The polarization property of the P(VDF-TrFE) film is studied, and a remnant polarization of >100 μC/cm2 is achieved with a P(VDF-TrFE) thickness of 300 nm. Because of the ultrahigh remnant polarization field generated in the P(VDF-TrFE) film, the FeFETs show a large memory window of 16.9 V and a high source-drain on/off current ratio of more than 107 at zero gate voltage and a source-drain bias of 0.1 V. Furthermore, a retention time of >3000 s of the polarization state is obtained, inspiring a promising candidate for applications in data storage with non-volatile features.

Three-body problem in d-dimensional space: Ground state, (quasi)-exact-solvability

Science.gov (United States)

Turbiner, Alexander V.; Miller, Willard; Escobar-Ruiz, M. A.

2018-02-01

As a straightforward generalization and extension of our previous paper [A. V. Turbiner et al., "Three-body problem in 3D space: Ground state, (quasi)-exact-solvability," J. Phys. A: Math. Theor. 50, 215201 (2017)], we study the aspects of the quantum and classical dynamics of a 3-body system with equal masses, each body with d degrees of freedom, with interaction depending only on mutual (relative) distances. The study is restricted to solutions in the space of relative motion which are functions of mutual (relative) distances only. It is shown that the ground state (and some other states) in the quantum case and the planar trajectories (which are in the interaction plane) in the classical case are of this type. The quantum (and classical) Hamiltonian for which these states are eigenfunctions is derived. It corresponds to a three-dimensional quantum particle moving in a curved space with special d-dimension-independent metric in a certain d-dependent singular potential, while at d = 1, it elegantly degenerates to a two-dimensional particle moving in flat space. It admits a description in terms of pure geometrical characteristics of the interaction triangle which is defined by the three relative distances. The kinetic energy of the system is d-independent; it has a hidden sl(4, R) Lie (Poisson) algebra structure, alternatively, the hidden algebra h(3) typical for the H3 Calogero model as in the d = 3 case. We find an exactly solvable three-body S3-permutationally invariant, generalized harmonic oscillator-type potential as well as a quasi-exactly solvable three-body sextic polynomial type potential with singular terms. For both models, an extra first order integral exists. For d = 1, the whole family of 3-body (two-dimensional) Calogero-Moser-Sutherland systems as well as the Tremblay-Turbiner-Winternitz model is reproduced. It is shown that a straightforward generalization of the 3-body (rational) Calogero model to d > 1 leads to two primitive quasi

Quantum Key Distribution with High Order Fibonacci-like Orbital Angular Momentum States

Science.gov (United States)

Pan, Ziwen; Cai, Jiarui; Wang, Chuan

2017-08-01

The coding space in quantum communication could be expanded to high-dimensional space by using orbital angular momentum (OAM) states of photons, as both the capacity of the channel and security are enhanced. Here we present a novel approach to realize high-capacity quantum key distribution (QKD) by exploiting OAM states. The innovation of the proposed approach relies on a unique type of entangled-photon source which produces entangled photons with OAM randomly distributed among high order Fiboncci-like numbers and a new physical mechanism for efficiently sharing keys. This combination of entanglement with mathematical properties of high order Fibonacci sequences provides the QKD protocol immunity to photon-number-splitting attacks and allows secure generation of long keys from few photons. Unlike other protocols, reference frame alignment and active modulation of production and detection bases are unnecessary.

Establishing state of motion through two-dimensional foot and shoe print analysis: A pilot study.

Science.gov (United States)

Neves, Fernando Bueno; Arnold, Graham P; Nasir, Sadiq; Wang, Weijie; MacDonald, Calum; Christie, Ian; Abboud, Rami J

2018-03-01

According to the College of Podiatry, footprints rank among the most frequent forms of evidence found at crime scenes, and the recent ascension of forensic podiatry reflects the importance of footwear and barefoot traces in contemporary forensic practice. In this context, this pilot study focused on whether it is possible to distinguish between walking and running states using parameters derived from two-dimensional foot or shoe prints. Eleven subjects moved along four tracks (barefoot walking; barefoot running; footwear walking; footwear running) while having their bare feet or footwear stained with artificial blood and their footstep patterns recorded. Contact stains and associated bloodstain patterns were collected, and body movements were recorded through three-dimensional motion capture. Barefoot walking prints were found to be larger than barefoot static prints (1.789±0.481cm; pprints (0.635±0.405cm; p=0.006). No correlation was observed for footwear prints. Running trials were more associated with the presence of both passive and cast off stains than walking trials, and the quantity of additional associated stains surrounding individual foot and shoe prints was also higher in running states. Furthermore, a previously proposed equation predicted speed with a high degree of accuracy (within 6%) and may be used for clinical assessment of walking speed. Contact stains, associated bloodstain patterns and stride length measurements may serve to ascertain state of motion in real crime scene scenarios, and future studies may be capable of designing statistical frameworks which could be used in courts of law. Copyright © 2018 Elsevier B.V. All rights reserved.

High-resolution coherent three-dimensional spectroscopy of Br2.

Science.gov (United States)

Chen, Peter C; Wells, Thresa A; Strangfeld, Benjamin R

2013-07-25

In the past, high-resolution spectroscopy has been limited to small, simple molecules that yield relatively uncongested spectra. Larger and more complex molecules have a higher density of peaks and are susceptible to complications (e.g., effects from conical intersections) that can obscure the patterns needed to resolve and assign peaks. Recently, high-resolution coherent two-dimensional (2D) spectroscopy has been used to resolve and sort peaks into easily identifiable patterns for molecules where pattern-recognition has been difficult. For very highly congested spectra, however, the ability to resolve peaks using coherent 2D spectroscopy is limited by the bandwidth of instrumentation. In this article, we introduce and investigate high-resolution coherent three-dimensional spectroscopy (HRC3D) as a method for dealing with heavily congested systems. The resulting patterns are unlike those in high-resolution coherent 2D spectra. Analysis of HRC3D spectra could provide a means for exploring the spectroscopy of large and complex molecules that have previously been considered too difficult to study.

Energy Efficient MAC Scheme for Wireless Sensor Networks with High-Dimensional Data Aggregate

Directory of Open Access Journals (Sweden)

Seokhoon Kim

2015-01-01

Full Text Available This paper presents a novel and sustainable medium access control (MAC scheme for wireless sensor network (WSN systems that process high-dimensional aggregated data. Based on a preamble signal and buffer threshold analysis, it maximizes the energy efficiency of the wireless sensor devices which have limited energy resources. The proposed group management MAC (GM-MAC approach not only sets the buffer threshold value of a sensor device to be reciprocal to the preamble signal but also sets a transmittable group value to each sensor device by using the preamble signal of the sink node. The primary difference between the previous and the proposed approach is that existing state-of-the-art schemes use duty cycle and sleep mode to save energy consumption of individual sensor devices, whereas the proposed scheme employs the group management MAC scheme for sensor devices to maximize the overall energy efficiency of the whole WSN systems by minimizing the energy consumption of sensor devices located near the sink node. Performance evaluations show that the proposed scheme outperforms the previous schemes in terms of active time of sensor devices, transmission delay, control overhead, and energy consumption. Therefore, the proposed scheme is suitable for sensor devices in a variety of wireless sensor networking environments with high-dimensional data aggregate.

State switching kinetics for quasi-one-dimensional nanosystems: Effects of Finite length and irradiation

Energy Technology Data Exchange (ETDEWEB)

Petukhov, B. V., E-mail: petukhov@ns.crys.ras.ru [Russian Academy of Sciences, Shubnikov Institute of Crystallography, Federal Scientific Research Centre “Crystallography and Photonics,” (Russian Federation)

2017-01-15

The state switching in an extended quasi-one-dimensional material is modeled by the stochastic formation of local new-state nuclei and their subsequent growth along the system axis. An analytical approach is developed to describe the influence of defects, dividing a sample into an ensemble of finite-length segments, on its state switching kinetics. As applied to magnetic systems, the method makes it possible to calculate magnetization curves for different defect concentrations and parameters of material.

Highly mobile charge-transfer excitons in two-dimensional WS2/tetracene heterostructures

Science.gov (United States)

Zhu, Tong; Yuan, Long; Zhao, Yan; Zhou, Mingwei; Wan, Yan; Mei, Jianguo; Huang, Libai

2018-01-01

Charge-transfer (CT) excitons at heterointerfaces play a critical role in light to electricity conversion using organic and nanostructured materials. However, how CT excitons migrate at these interfaces is poorly understood. We investigate the formation and transport of CT excitons in two-dimensional WS2/tetracene van der Waals heterostructures. Electron and hole transfer occurs on the time scale of a few picoseconds, and emission of interlayer CT excitons with a binding energy of ~0.3 eV has been observed. Transport of the CT excitons is directly measured by transient absorption microscopy, revealing coexistence of delocalized and localized states. Trapping-detrapping dynamics between the delocalized and localized states leads to stretched-exponential photoluminescence decay with an average lifetime of ~2 ns. The delocalized CT excitons are remarkably mobile with a diffusion constant of ~1 cm2 s−1. These highly mobile CT excitons could have important implications in achieving efficient charge separation. PMID:29340303

Quantum phase transitions in matrix product states of one-dimensional spin-1 chains

International Nuclear Information System (INIS)

Zhu Jingmin

2014-01-01

We present a new model of quantum phase transitions in matrix product systems of one-dimensional spin-1 chains and study the phases coexistence phenomenon. We find that in the thermodynamic limit the proposed system has three different quantum phases and by adjusting the control parameters we are able to realize any phase, any two phases equal coexistence and the three phases equal coexistence. At every critical point the physical quantities including the entanglement are not discontinuous and the matrix product system has long-range correlation and N-spin maximal entanglement. We believe that our work is helpful for having a comprehensive understanding of quantum phase transitions in matrix product states of one-dimensional spin chains and of certain directive significance to the preparation and control of one-dimensional spin lattice models with stable coherence and N-spin maximal entanglement. (author)

Inference in High-dimensional Dynamic Panel Data Models

DEFF Research Database (Denmark)

Kock, Anders Bredahl; Tang, Haihan

We establish oracle inequalities for a version of the Lasso in high-dimensional fixed effects dynamic panel data models. The inequalities are valid for the coefficients of the dynamic and exogenous regressors. Separate oracle inequalities are derived for the fixed effects. Next, we show how one can...

Manifold learning to interpret JET high-dimensional operational space

International Nuclear Information System (INIS)

Cannas, B; Fanni, A; Pau, A; Sias, G; Murari, A

2013-01-01

In this paper, the problem of visualization and exploration of JET high-dimensional operational space is considered. The data come from plasma discharges selected from JET campaigns from C15 (year 2005) up to C27 (year 2009). The aim is to learn the possible manifold structure embedded in the data and to create some representations of the plasma parameters on low-dimensional maps, which are understandable and which preserve the essential properties owned by the original data. A crucial issue for the design of such mappings is the quality of the dataset. This paper reports the details of the criteria used to properly select suitable signals downloaded from JET databases in order to obtain a dataset of reliable observations. Moreover, a statistical analysis is performed to recognize the presence of outliers. Finally data reduction, based on clustering methods, is performed to select a limited and representative number of samples for the operational space mapping. The high-dimensional operational space of JET is mapped using a widely used manifold learning method, the self-organizing maps. The results are compared with other data visualization methods. The obtained maps can be used to identify characteristic regions of the plasma scenario, allowing to discriminate between regions with high risk of disruption and those with low risk of disruption. (paper)

Quantum Communication Through a Two-Dimensional Spin Network

International Nuclear Information System (INIS)

Wang Zhaoming; Gu Yongjian

2012-01-01

We investigate the state or entanglement transfer through a two-dimensional spin network. We show that for state transfer, better fidelity can be gained along the diagonal direction but for entanglement transfer, when the initial entanglement is created along the boundary, the concurrence is more inclined to propagate along the boundary. This behavior is produced by quantum mechanical interference and the communication quality depends on the precise size of the network. For some number of sites, the fidelity in a two-dimensional channel is higher than one-dimensional case. This is an important result for realizing quantum communication through high dimension spin chain networks.

Irreversible magnetization deep in the vortex-liquid state of a 2D superconductor at high magnetic fields

International Nuclear Information System (INIS)

Maniv, T; Zhuravlev, V; Wosnitza, J; Hagel, J

2004-01-01

The remarkable phenomenon of weak magnetization hysteresis loops, observed recently deep in the vortex-liquid state of a nearly two-dimensional (2D) superconductor at low temperatures and high magnetic fields, is shown to reflect the existence of an unusual vortex-liquid state, consisting of collectively pinned crystallites of easily sliding vortex chains. (letter to the editor)

Multifractal character of the electronic states in disordered two-dimensional systems

International Nuclear Information System (INIS)

Tit, N.; Schreiber, M.

1994-08-01

The nature of electronic states in disordered two-dimensional (2D) systems is investigated. To this aim, we present our calculations of both density of states and dc-conductivity for square lattices modelling the Anderson Hamiltonian with on-site energies randomly chosen from a box distribution of width W. For weak disorder (W), the eigenfunctions calculated by means of the Lanczos diagonalization algorithm display spatial fluctuations reflecting their (multi)fractal behaviour. For increasing disorder or energy the observed increase of the curdling of the wavefunction reflects its stronger localization. Our dc-conductivity results suggest a critical fractal dimension d * c =1.48±0.05 to discriminate between the exponentially and the power-law localized states. Consequences of the localization on transport properties are also discussed. (author). 30 refs, 10 figs, 1 tab

High-dimensional orbital angular momentum entanglement concentration based on Laguerre–Gaussian mode selection

International Nuclear Information System (INIS)

Zhang, Wuhong; Su, Ming; Wu, Ziwen; Lu, Meng; Huang, Bingwei; Chen, Lixiang

2013-01-01

Twisted photons enable the definition of a Hilbert space beyond two dimensions by orbital angular momentum (OAM) eigenstates. Here we propose a feasible entanglement concentration experiment, to enhance the quality of high-dimensional entanglement shared by twisted photon pairs. Our approach is started from the full characterization of entangled spiral bandwidth, and is then based on the careful selection of the Laguerre–Gaussian (LG) modes with specific radial and azimuthal indices p and ℓ. In particular, we demonstrate the possibility of high-dimensional entanglement concentration residing in the OAM subspace of up to 21 dimensions. By means of LabVIEW simulations with spatial light modulators, we show that the Shannon dimensionality could be employed to quantify the quality of the present concentration. Our scheme holds promise in quantum information applications defined in high-dimensional Hilbert space. (letter)

A Penalized Likelihood Framework For High-Dimensional Phylogenetic Comparative Methods And An Application To New-World Monkeys Brain Evolution.

Science.gov (United States)

Julien, Clavel; Leandro, Aristide; Hélène, Morlon

2018-06-19

Working with high-dimensional phylogenetic comparative datasets is challenging because likelihood-based multivariate methods suffer from low statistical performances as the number of traits p approaches the number of species n and because some computational complications occur when p exceeds n. Alternative phylogenetic comparative methods have recently been proposed to deal with the large p small n scenario but their use and performances are limited. Here we develop a penalized likelihood framework to deal with high-dimensional comparative datasets. We propose various penalizations and methods for selecting the intensity of the penalties. We apply this general framework to the estimation of parameters (the evolutionary trait covariance matrix and parameters of the evolutionary model) and model comparison for the high-dimensional multivariate Brownian (BM), Early-burst (EB), Ornstein-Uhlenbeck (OU) and Pagel's lambda models. We show using simulations that our penalized likelihood approach dramatically improves the estimation of evolutionary trait covariance matrices and model parameters when p approaches n, and allows for their accurate estimation when p equals or exceeds n. In addition, we show that penalized likelihood models can be efficiently compared using Generalized Information Criterion (GIC). We implement these methods, as well as the related estimation of ancestral states and the computation of phylogenetic PCA in the R package RPANDA and mvMORPH. Finally, we illustrate the utility of the new proposed framework by evaluating evolutionary models fit, analyzing integration patterns, and reconstructing evolutionary trajectories for a high-dimensional 3-D dataset of brain shape in the New World monkeys. We find a clear support for an Early-burst model suggesting an early diversification of brain morphology during the ecological radiation of the clade. Penalized likelihood offers an efficient way to deal with high-dimensional multivariate comparative data.

Signatures of Majorana bound states in one-dimensional topological superconductors

International Nuclear Information System (INIS)

Pientka, Falko

2014-01-01

Topological states of matter have fascinated condensed matter physicists for the past three decades. Famous examples include the integer and fractional quantum Hall states exhibiting a spectacular conductance quantization as well as topological insulators in two and three dimensions featuring gapless Dirac fermions at the boundary. Very recently, novel topological phases in superconductors have been subject of intense experimental and theoretical investigation. One-dimensional topological superconductors are particularly intriguing as they host exotic Majorana end states. These are zero-energy bound states with nonabelian exchange statistics potentially useful for topologically protected quantum computing. Recent theoretical and experimental advances have put the realization of Majorana states within reach of current measurement techniques. In this thesis we investigate signatures of Majorana bound states in realistic experiments aiming to improve the theoretical understanding of ongoing experimental efforts and to design novel measurement schemes, which exhibit convincing signatures of Majoranas. In particular we account for nonideal experimental conditions which can lead to qualitatively new features. Possible signatures of Majoranas can be accessed in the Josephson current through a weak link between two topological superconductors although the signatures in the dc Josephson effect are typically obscured by inevitable quasiparticle relaxation in the superconductor. Here we propose a measurement scheme in mesoscopic superconducting rings, where Majorana signatures persist even for infinitely fast relaxation. In a separate project we outline an alternative to the standard Josephson experiment in topological superconductors based on quantum wires. We delineate how Majoranas can be detected, when the Josephson current is induced by noncollinear magnetic fields applied to the two banks of the junction instead of a superconducting phase difference. Another important

High Dimensional Modulation and MIMO Techniques for Access Networks

DEFF Research Database (Denmark)

Binti Othman, Maisara

Exploration of advanced modulation formats and multiplexing techniques for next generation optical access networks are of interest as promising solutions for delivering multiple services to end-users. This thesis addresses this from two different angles: high dimensionality carrierless...... the capacity per wavelength of the femto-cell network. Bit rate up to 1.59 Gbps with fiber-wireless transmission over 1 m air distance is demonstrated. The results presented in this thesis demonstrate the feasibility of high dimensionality CAP in increasing the number of dimensions and their potentially......) optical access network. 2 X 2 MIMO RoF employing orthogonal frequency division multiplexing (OFDM) with 5.6 GHz RoF signaling over all-vertical cavity surface emitting lasers (VCSEL) WDM passive optical networks (PONs). We have employed polarization division multiplexing (PDM) to further increase...

High-dimensional single-cell cancer biology.

Science.gov (United States)

Irish, Jonathan M; Doxie, Deon B

2014-01-01

Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a "single-cell " view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy.

Pseudo-time-reversal symmetry and topological edge states in two-dimensional acoustic crystals

KAUST Repository

Mei, Jun

2016-09-02

We propose a simple two-dimensional acoustic crystal to realize topologically protected edge states for acoustic waves. The acoustic crystal is composed of a triangular array of core-shell cylinders embedded in a water host. By utilizing the point group symmetry of two doubly degenerate eigenstates at the Î

Pseudo-time-reversal symmetry and topological edge states in two-dimensional acoustic crystals

KAUST Repository

Mei, Jun; Chen, Zeguo; Wu, Ying

2016-01-01

We propose a simple two-dimensional acoustic crystal to realize topologically protected edge states for acoustic waves. The acoustic crystal is composed of a triangular array of core-shell cylinders embedded in a water host. By utilizing the point group symmetry of two doubly degenerate eigenstates at the Î

Cluster state generation in one-dimensional Kitaev honeycomb model via shortcut to adiabaticity

Science.gov (United States)

Kyaw, Thi Ha; Kwek, Leong-Chuan

2018-04-01

We propose a mean to obtain computationally useful resource states also known as cluster states, for measurement-based quantum computation, via transitionless quantum driving algorithm. The idea is to cool the system to its unique ground state and tune some control parameters to arrive at computationally useful resource state, which is in one of the degenerate ground states. Even though there is set of conserved quantities already present in the model Hamiltonian, which prevents the instantaneous state to go to any other eigenstate subspaces, one cannot quench the control parameters to get the desired state. In that case, the state will not evolve. With involvement of the shortcut Hamiltonian, we obtain cluster states in fast-forward manner. We elaborate our proposal in the one-dimensional Kitaev honeycomb model, and show that the auxiliary Hamiltonian needed for the counterdiabatic driving is of M-body interaction.

Estimating High-Dimensional Time Series Models

DEFF Research Database (Denmark)

Medeiros, Marcelo C.; Mendes, Eduardo F.

We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume both the number of covariates in the model and candidate variables can increase with the number of observations and the number of candidate variables is, possibly......, larger than the number of observations. We show the adaLASSO consistently chooses the relevant variables as the number of observations increases (model selection consistency), and has the oracle property, even when the errors are non-Gaussian and conditionally heteroskedastic. A simulation study shows...

State-space representation of instationary two-dimensional airfoil aerodynamics

Energy Technology Data Exchange (ETDEWEB)

Meyer, Marcus; Matthies, Hermann G. [Institute of Scientific Computing, Technical University Braunschweig, Hans-Sommer-Str. 65, Braunschweig 38106 (Germany)

2004-03-01

In the aero-elastic analysis of wind turbines the need to include a model of the local, two-dimensional instationary aerodynamic loads, commonly referred to as dynamic stall model, has become obvious in the last years. In this contribution an alternative choice for such a model is described, based on the DLR model. Its derivation is governed by the flow physics, thus enabling interpolation between different profile geometries. An advantage of the proposed model is its state-space form, i.e. a system of differential equations, which facilitates the important tasks of aeroelastic stability and sensitivity investigations. The model is validated with numerical calculations.

Similarity measurement method of high-dimensional data based on normalized net lattice subspace

Institute of Scientific and Technical Information of China (English)

Li Wenfa; Wang Gongming; Li Ke; Huang Su

2017-01-01

The performance of conventional similarity measurement methods is affected seriously by the curse of dimensionality of high-dimensional data.The reason is that data difference between sparse and noisy dimensionalities occupies a large proportion of the similarity, leading to the dissimilarities between any results.A similarity measurement method of high-dimensional data based on normalized net lattice subspace is proposed.The data range of each dimension is divided into several intervals, and the components in different dimensions are mapped onto the corresponding interval.Only the component in the same or adjacent interval is used to calculate the similarity.To validate this meth-od, three data types are used, and seven common similarity measurement methods are compared. The experimental result indicates that the relative difference of the method is increasing with the di-mensionality and is approximately two or three orders of magnitude higher than the conventional method.In addition, the similarity range of this method in different dimensions is [0, 1], which is fit for similarity analysis after dimensionality reduction.

Numerical evidence for two types of localized states in a two-dimensional disordered lattice

International Nuclear Information System (INIS)

Tit, N.; Kumar, N.

1992-06-01

We report results of our numerical calculations, based on the equation of motion method, of dc-electrical conductivity and of density of states up to 40x40 two-dimensional square lattices modelling a right-binding Hamiltonian for a binary (AB) compound, disordered by randomly distributed B vacancies up to 10%. Our results indicate strongly localized states away from band centers separated from the relatively weakly localized states toward midband. This is in qualitative agreement with the idea of a ''mobility edge'' separating exponentially localized states from the power-law localized states as suggested by the two-parameter scaling theory of Kaevh in two dimensions. (author). 7 refs, 4 figs

Non-intrusive low-rank separated approximation of high-dimensional stochastic models

KAUST Repository

Doostan, Alireza; Validi, AbdoulAhad; Iaccarino, Gianluca

2013-01-01

This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.

Non-intrusive low-rank separated approximation of high-dimensional stochastic models

KAUST Repository

Doostan, Alireza

2013-08-01

This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.

Infinite-Dimensional Boundary Observer for Lithium-Ion Battery State Estimation

DEFF Research Database (Denmark)

Hasan, Agus; Jouffroy, Jerome

2017-01-01

This paper presents boundary observer design for state-of-charge (SOC) estimation of lithium-ion batteries. The lithium-ion battery dynamics are governed by thermal-electrochemical principles, which mathematically modeled by partial differential equations (PDEs). In general, the model is a reaction......-diffusion equation with time-dependent coefficients. A Luenberger observer is developed using infinite-dimensional backstepping method and uses only a single measurement at the boundary of the battery. The observer gains are computed by solving the observer kernel equation. A numerical example is performed to show...

High dimensional model representation method for fuzzy structural dynamics

Science.gov (United States)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

Multigrid for high dimensional elliptic partial differential equations on non-equidistant grids

NARCIS (Netherlands)

bin Zubair, H.; Oosterlee, C.E.; Wienands, R.

2006-01-01

This work presents techniques, theory and numbers for multigrid in a general d-dimensional setting. The main focus is the multigrid convergence for high-dimensional partial differential equations (PDEs). As a model problem we have chosen the anisotropic diffusion equation, on a unit hypercube. We

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

Science.gov (United States)

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.

[The physiological classification of human thermal states under high environmental temperatures].

Science.gov (United States)

Bobrov, A F; Kuznets, E I

1995-01-01

The paper deals with the physiological classification of human thermal states in a hot environment. A review of the basic systems of classifications of thermal states is given, their main drawbacks are discussed. On the basis of human functional state research in a broad range of environmental temperatures the system of evaluation and classification of human thermal states is proposed. New integral one-dimensional multi-parametric criteria for evaluation are used. For the development of these criteria methods of factor, cluster and canonical correlation analyses are applied. Stochastic nomograms capable of identification of human thermal state for different intensity of influence are given. In this case evaluation of intensity is estimated according to one-dimensional criteria taking into account environmental temperature, physical load and time of man's staying in overheating conditions.

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain

2017-01-01

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive

Highly ordered three-dimensional macroporous carbon spheres for determination of heavy metal ions

International Nuclear Information System (INIS)

Zhang, Yuxiao; Zhang, Jianming; Liu, Yang; Huang, Hui; Kang, Zhenhui

2012-01-01

Highlights: ► Highly ordered three dimensional macroporous carbon spheres (MPCSs) were prepared. ► MPCS was covalently modified by cysteine (MPCS–CO–Cys). ► MPCS–CO–Cys was first time used in electrochemical detection of heavy metal ions. ► Heavy metal ions such as Pb 2+ and Cd 2+ can be simultaneously determined. -- Abstract: An effective voltammetric method for detection of trace heavy metal ions using chemically modified highly ordered three dimensional macroporous carbon spheres electrode surfaces is described. The highly ordered three dimensional macroporous carbon spheres were prepared by carbonization of glucose in silica crystal bead template, followed by removal of the template. The highly ordered three dimensional macroporous carbon spheres were covalently modified by cysteine, an amino acid with high affinities towards some heavy metals. The materials were characterized by physical adsorption of nitrogen, scanning electron microscopy, and transmission electron microscopy techniques. While the Fourier-transform infrared spectroscopy was used to characterize the functional groups on the surface of carbon spheres. High sensitivity was exhibited when this material was used in electrochemical detection (square wave anodic stripping voltammetry) of heavy metal ions due to the porous structure. And the potential application for simultaneous detection of heavy metal ions was also investigated.

Local imaging of high mobility two-dimensional electron systems with virtual scanning tunneling microscopy

Energy Technology Data Exchange (ETDEWEB)

Pelliccione, M. [Department of Applied Physics, Stanford University, 348 Via Pueblo Mall, Stanford, California 94305 (United States); Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025 (United States); Department of Physics, University of California, Santa Barbara, Santa Barbara, California 93106 (United States); Bartel, J.; Goldhaber-Gordon, D. [Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025 (United States); Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, California 94305 (United States); Sciambi, A. [Department of Applied Physics, Stanford University, 348 Via Pueblo Mall, Stanford, California 94305 (United States); Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025 (United States); Pfeiffer, L. N.; West, K. W. [Department of Electrical Engineering, Princeton University, Princeton, New Jersey 08544 (United States)

2014-11-03

Correlated electron states in high mobility two-dimensional electron systems (2DESs), including charge density waves and microemulsion phases intermediate between a Fermi liquid and Wigner crystal, are predicted to exhibit complex local charge order. Existing experimental studies, however, have mainly probed these systems at micron to millimeter scales rather than directly mapping spatial organization. Scanning probes should be well-suited to study the spatial structure of these states, but high mobility 2DESs are found at buried semiconductor interfaces, beyond the reach of conventional scanning tunneling microscopy. Scanning techniques based on electrostatic coupling to the 2DES deliver important insights, but generally with resolution limited by the depth of the 2DES. In this letter, we present our progress in developing a technique called “virtual scanning tunneling microscopy” that allows local tunneling into a high mobility 2DES. Using a specially designed bilayer GaAs/AlGaAs heterostructure where the tunnel coupling between two separate 2DESs is tunable via electrostatic gating, combined with a scanning gate, we show that the local tunneling can be controlled with sub-250 nm resolution.

New ab initio potential surfaces and three-dimensional quantum dynamics for transition state spectroscopy in ozone photodissociation

Science.gov (United States)

Yamashita, Koichi; Morokuma, Keiji; Le Quéré, Frederic; Leforestier, Claude

1992-04-01

New ab initio potential energy surfaces (PESs) of the ground and B ( 1B 2) states of ozone have been calculated with the CASSCF-SECI/DZP method to describe the three-dimensional photodissociation process. The dissociation energy of the ground state and the vertical barrier height of the B PES are obtained to be 0.88 and 1.34 eV, respectively, in better agreement with the experimental values than the previous calculation. The photodissociation autocorrelation function, calculated on the new B PES, based on exact three-dimensional quantum dynamics, reproduces well the main recurrence feature extracted from the experimental spectra.

Quantum limits to information about states for finite dimensional Hilbert space

International Nuclear Information System (INIS)

Jones, K.R.W.

1990-01-01

A refined bound for the correlation information of an N-trial apparatus is developed via an heuristic argument for Hilbert spaces of arbitrary finite dimensionality. Conditional upon the proof of an easily motivated inequality it was possible to find the optimal apparatus for large ensemble quantum Inference, thereby solving the asymptotic optimal state determination problem. In this way an alternative inferential uncertainty principle, is defined which is then contrasted with the usual Heisenberg uncertainty principle. 6 refs

Evaluation of aqueductal patency in patients with hydrocephalus: Three-dimensional high-sampling efficiency technique(SPACE) versus two-dimensional turbo spin echo at 3 Tesla

International Nuclear Information System (INIS)

Ucar, Murat; Guryildirim, Melike; Tokgoz, Nil; Kilic, Koray; Borcek, Alp; Oner, Yusuf; Akkan, Koray; Tali, Turgut

2014-01-01

To compare the accuracy of diagnosing aqueductal patency and image quality between high spatial resolution three-dimensional (3D) high-sampling-efficiency technique (sampling perfection with application optimized contrast using different flip angle evolutions [SPACE]) and T2-weighted (T2W) two-dimensional (2D) turbo spin echo (TSE) at 3-T in patients with hydrocephalus. This retrospective study included 99 patients diagnosed with hydrocephalus. T2W 3D-SPACE was added to the routine sequences which consisted of T2W 2D-TSE, 3D-constructive interference steady state (CISS), and cine phase-contrast MRI (PC-MRI). Two radiologists evaluated independently the patency of cerebral aqueduct and image quality on the T2W 2D-TSE and T2W 3D-SPACE. PC-MRI and 3D-CISS were used as the reference for aqueductal patency and image quality, respectively. Inter-observer agreement was calculated using kappa statistics. The evaluation of the aqueductal patency by T2W 3D-SPACE and T2W 2D-TSE were in agreement with PC-MRI in 100% (99/99; sensitivity, 100% [83/83]; specificity, 100% [16/16]) and 83.8% (83/99; sensitivity, 100% [67/83]; specificity, 100% [16/16]), respectively (p < 0.001). No significant difference in image quality between T2W 2D-TSE and T2W 3D-SPACE (p = 0.056) occurred. The kappa values for inter-observer agreement were 0.714 for T2W 2D-TSE and 0.899 for T2W 3D-SPACE. Three-dimensional-SPACE is superior to 2D-TSE for the evaluation of aqueductal patency in hydrocephalus. T2W 3D-SPACE may hold promise as a highly accurate alternative treatment to PC-MRI for the physiological and morphological evaluation of aqueductal patency.

Evaluation of aqueductal patency in patients with hydrocephalus: Three-dimensional high-sampling efficiency technique(SPACE) versus two-dimensional turbo spin echo at 3 Tesla

Energy Technology Data Exchange (ETDEWEB)

Ucar, Murat; Guryildirim, Melike; Tokgoz, Nil; Kilic, Koray; Borcek, Alp; Oner, Yusuf; Akkan, Koray; Tali, Turgut [School of Medicine, Gazi University, Ankara (Turkey)

2014-12-15

To compare the accuracy of diagnosing aqueductal patency and image quality between high spatial resolution three-dimensional (3D) high-sampling-efficiency technique (sampling perfection with application optimized contrast using different flip angle evolutions [SPACE]) and T2-weighted (T2W) two-dimensional (2D) turbo spin echo (TSE) at 3-T in patients with hydrocephalus. This retrospective study included 99 patients diagnosed with hydrocephalus. T2W 3D-SPACE was added to the routine sequences which consisted of T2W 2D-TSE, 3D-constructive interference steady state (CISS), and cine phase-contrast MRI (PC-MRI). Two radiologists evaluated independently the patency of cerebral aqueduct and image quality on the T2W 2D-TSE and T2W 3D-SPACE. PC-MRI and 3D-CISS were used as the reference for aqueductal patency and image quality, respectively. Inter-observer agreement was calculated using kappa statistics. The evaluation of the aqueductal patency by T2W 3D-SPACE and T2W 2D-TSE were in agreement with PC-MRI in 100% (99/99; sensitivity, 100% [83/83]; specificity, 100% [16/16]) and 83.8% (83/99; sensitivity, 100% [67/83]; specificity, 100% [16/16]), respectively (p < 0.001). No significant difference in image quality between T2W 2D-TSE and T2W 3D-SPACE (p = 0.056) occurred. The kappa values for inter-observer agreement were 0.714 for T2W 2D-TSE and 0.899 for T2W 3D-SPACE. Three-dimensional-SPACE is superior to 2D-TSE for the evaluation of aqueductal patency in hydrocephalus. T2W 3D-SPACE may hold promise as a highly accurate alternative treatment to PC-MRI for the physiological and morphological evaluation of aqueductal patency.

Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs

Energy Technology Data Exchange (ETDEWEB)

Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn [School of Information Science and Technology, ShanghaiTech University, Shanghai 200031 (China); Lin, Guang, E-mail: guanglin@purdue.edu [Department of Mathematics & School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States)

2016-07-15

In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.

Three-Dimensional Electromagnetic High Frequency Axisymmetric Cavity Scars.

Energy Technology Data Exchange (ETDEWEB)

Warne, Larry Kevin; Jorgenson, Roy Eberhardt

2014-10-01

This report examines the localization of high frequency electromagnetic fi elds in three-dimensional axisymmetric cavities along periodic paths between opposing sides of the cavity. The cases where these orbits lead to unstable localized modes are known as scars. This report treats both the case where the opposing sides, or mirrors, are convex, where there are no interior foci, and the case where they are concave, leading to interior foci. The scalar problem is treated fi rst but the approximations required to treat the vector fi eld components are also examined. Particular att ention is focused on the normalization through the electromagnetic energy theorem. Both projections of the fi eld along the scarred orbit as well as point statistics are examined. Statistical comparisons are m ade with a numerical calculation of the scars run with an axisymmetric simulation. This axisymmetric cas eformstheoppositeextreme(wherethetwomirror radii at each end of the ray orbit are equal) from the two -dimensional solution examined previously (where one mirror radius is vastly di ff erent from the other). The enhancement of the fi eldontheorbitaxiscanbe larger here than in the two-dimensional case. Intentionally Left Blank

High-Dimensional Adaptive Particle Swarm Optimization on Heterogeneous Systems

International Nuclear Information System (INIS)

Wachowiak, M P; Sarlo, B B; Foster, A E Lambe

2014-01-01

Much work has recently been reported in parallel GPU-based particle swarm optimization (PSO). Motivated by the encouraging results of these investigations, while also recognizing the limitations of GPU-based methods for big problems using a large amount of data, this paper explores the efficacy of employing other types of parallel hardware for PSO. Most commodity systems feature a variety of architectures whose high-performance capabilities can be exploited. In this paper, high-dimensional problems and those that employ a large amount of external data are explored within the context of heterogeneous systems. Large problems are decomposed into constituent components, and analyses are undertaken of which components would benefit from multi-core or GPU parallelism. The current study therefore provides another demonstration that ''supercomputing on a budget'' is possible when subtasks of large problems are run on hardware most suited to these tasks. Experimental results show that large speedups can be achieved on high dimensional, data-intensive problems. Cost functions must first be analysed for parallelization opportunities, and assigned hardware based on the particular task

A hybridized K-means clustering approach for high dimensional ...

African Journals Online (AJOL)

International Journal of Engineering, Science and Technology ... Due to incredible growth of high dimensional dataset, conventional data base querying methods are inadequate to extract useful information, so researchers nowadays ... Recently cluster analysis is a popularly used data analysis method in number of areas.

Asymptotics of empirical eigenstructure for high dimensional spiked covariance.

Science.gov (United States)

Wang, Weichen; Fan, Jianqing

2017-06-01

We derive the asymptotic distributions of the spiked eigenvalues and eigenvectors under a generalized and unified asymptotic regime, which takes into account the magnitude of spiked eigenvalues, sample size, and dimensionality. This regime allows high dimensionality and diverging eigenvalues and provides new insights into the roles that the leading eigenvalues, sample size, and dimensionality play in principal component analysis. Our results are a natural extension of those in Paul (2007) to a more general setting and solve the rates of convergence problems in Shen et al. (2013). They also reveal the biases of estimating leading eigenvalues and eigenvectors by using principal component analysis, and lead to a new covariance estimator for the approximate factor model, called shrinkage principal orthogonal complement thresholding (S-POET), that corrects the biases. Our results are successfully applied to outstanding problems in estimation of risks of large portfolios and false discovery proportions for dependent test statistics and are illustrated by simulation studies.

Can We Train Machine Learning Methods to Outperform the High-dimensional Propensity Score Algorithm?

Science.gov (United States)

Karim, Mohammad Ehsanul; Pang, Menglan; Platt, Robert W

2018-03-01

The use of retrospective health care claims datasets is frequently criticized for the lack of complete information on potential confounders. Utilizing patient's health status-related information from claims datasets as surrogates or proxies for mismeasured and unobserved confounders, the high-dimensional propensity score algorithm enables us to reduce bias. Using a previously published cohort study of postmyocardial infarction statin use (1998-2012), we compare the performance of the algorithm with a number of popular machine learning approaches for confounder selection in high-dimensional covariate spaces: random forest, least absolute shrinkage and selection operator, and elastic net. Our results suggest that, when the data analysis is done with epidemiologic principles in mind, machine learning methods perform as well as the high-dimensional propensity score algorithm. Using a plasmode framework that mimicked the empirical data, we also showed that a hybrid of machine learning and high-dimensional propensity score algorithms generally perform slightly better than both in terms of mean squared error, when a bias-based analysis is used.

Ground-state and dynamical properties of two-dimensional dipolar Fermi liquids

International Nuclear Information System (INIS)

Abedinpour, Saeed H.; Asgari, Reza; Tanatar, B.; Polini, Marco

2014-01-01

We study the ground-state properties of a two-dimensional spin-polarized fluid of dipolar fermions within the Euler–Lagrange Fermi-hypernetted-chain approximation. Our method is based on the solution of a scattering Schrödinger equation for the “pair amplitude” √(g(r)), where g(r) is the pair distribution function. A key ingredient in our theory is the effective pair potential, which includes a bosonic term from Jastrow–Feenberg correlations and a fermionic contribution from kinetic energy and exchange, which is tailored to reproduce the Hartree–Fock limit at weak coupling. Very good agreement with recent results based on quantum Monte Carlo simulations is achieved over a wide range of coupling constants up to the liquid-to-crystal quantum phase transition. Using the fluctuation–dissipation theorem and a static approximation for the effective inter-particle interactions, we calculate the dynamical density–density response function, and furthermore demonstrate that an undamped zero-sound mode exists for any value of the interaction strength, down to infinitesimally weak couplings. -- Highlights: •We have studied the ground state properties of a strongly correlated two-dimensional fluid of dipolar fermions. •We have calculated the effective inter-particle interaction and the dynamical density–density response function. •We have shown that an undamped zero sound mode exists at any value of the interaction strength

Tomography of the quantum state of photons entangled in high dimensions

CSIR Research Space (South Africa)

Agnew, M

2011-12-01

Full Text Available with unit trace [5]. By choosing the appropriate coefficients of the Gell-Mann matrices, we can minimize ?2, thus producing the closest physical density ma- trix that represents the high-dimensionally entangled quantum state. IV. RESULTS AND DISCUSSION.... Zeilinger, Phys. Rev. Lett. 94, 070402 (2005). [10] D. N. Matsukevich, P. Maunz, D. L. Moehring, S. Olmschenk, and C. Monroe, Phys. Rev. Lett. 100, 150404 (2008). [11] B. Jack, J. Leach, H. Ritsch, S. M. Barnett, M. J. Padgett, and S. Franke-Arnold, New...

Innovation Rather than Improvement: A Solvable High-Dimensional Model Highlights the Limitations of Scalar Fitness

Science.gov (United States)

Tikhonov, Mikhail; Monasson, Remi

2018-01-01

Much of our understanding of ecological and evolutionary mechanisms derives from analysis of low-dimensional models: with few interacting species, or few axes defining "fitness". It is not always clear to what extent the intuition derived from low-dimensional models applies to the complex, high-dimensional reality. For instance, most naturally occurring microbial communities are strikingly diverse, harboring a large number of coexisting species, each of which contributes to shaping the environment of others. Understanding the eco-evolutionary interplay in these systems is an important challenge, and an exciting new domain for statistical physics. Recent work identified a promising new platform for investigating highly diverse ecosystems, based on the classic resource competition model of MacArthur. Here, we describe how the same analytical framework can be used to study evolutionary questions. Our analysis illustrates how, at high dimension, the intuition promoted by a one-dimensional (scalar) notion of fitness can become misleading. Specifically, while the low-dimensional picture emphasizes organism cost or efficiency, we exhibit a regime where cost becomes irrelevant for survival, and link this observation to generic properties of high-dimensional geometry.

Highly ordered three-dimensional macroporous carbon spheres for determination of heavy metal ions

Energy Technology Data Exchange (ETDEWEB)

Zhang, Yuxiao; Zhang, Jianming [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Liu, Yang, E-mail: yangl@suda.edu.cn [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Huang, Hui [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China); Kang, Zhenhui, E-mail: zhkang@suda.edu.cn [Institute of Functional Nano and Soft Materials (FUNSOM) and Jiangsu Key Laboratory for Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123 (China)

2012-04-15

Highlights: Black-Right-Pointing-Pointer Highly ordered three dimensional macroporous carbon spheres (MPCSs) were prepared. Black-Right-Pointing-Pointer MPCS was covalently modified by cysteine (MPCS-CO-Cys). Black-Right-Pointing-Pointer MPCS-CO-Cys was first time used in electrochemical detection of heavy metal ions. Black-Right-Pointing-Pointer Heavy metal ions such as Pb{sup 2+} and Cd{sup 2+} can be simultaneously determined. -- Abstract: An effective voltammetric method for detection of trace heavy metal ions using chemically modified highly ordered three dimensional macroporous carbon spheres electrode surfaces is described. The highly ordered three dimensional macroporous carbon spheres were prepared by carbonization of glucose in silica crystal bead template, followed by removal of the template. The highly ordered three dimensional macroporous carbon spheres were covalently modified by cysteine, an amino acid with high affinities towards some heavy metals. The materials were characterized by physical adsorption of nitrogen, scanning electron microscopy, and transmission electron microscopy techniques. While the Fourier-transform infrared spectroscopy was used to characterize the functional groups on the surface of carbon spheres. High sensitivity was exhibited when this material was used in electrochemical detection (square wave anodic stripping voltammetry) of heavy metal ions due to the porous structure. And the potential application for simultaneous detection of heavy metal ions was also investigated.

Irregular grid methods for pricing high-dimensional American options

NARCIS (Netherlands)

Berridge, S.J.

2004-01-01

This thesis proposes and studies numerical methods for pricing high-dimensional American options; important examples being basket options, Bermudan swaptions and real options. Four new methods are presented and analysed, both in terms of their application to various test problems, and in terms of

Homogenization of steady-state creep of porous metals using three-dimensional microstructural reconstructions

DEFF Research Database (Denmark)

Kwok, Kawai; Boccaccini, Dino; Persson, Åsa Helen

2016-01-01

The effective steady-state creep response of porous metals is studied by numerical homogenization and analytical modeling in this paper. The numerical homogenization is based on finite element models of three-dimensional microstructures directly reconstructed from tomographic images. The effects ...... model, and closely matched by the Gibson-Ashby compression and the Ramakrishnan-Arunchalam creep models. [All rights reserved Elsevier]....

Generation of Arbitrary Pure States for Three-dimensional Motion of a Trapped Ion

International Nuclear Information System (INIS)

Li Dachuang; Dong Ping; Cao Zhuoliang; Wang Xianping; Yang Ming

2010-01-01

In this paper, we propose a scheme for generating an arbitrary three-dimensional pure state of vibrational motion of a trapped ion. Our scheme is based on a sequence of laser pulses, which are tuned to the appropriate vibrational sidebands with respect to the appropriate electronic transition. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

High-dimensional atom localization via spontaneously generated coherence in a microwave-driven atomic system.

Science.gov (United States)

Wang, Zhiping; Chen, Jinyu; Yu, Benli

2017-02-20

We investigate the two-dimensional (2D) and three-dimensional (3D) atom localization behaviors via spontaneously generated coherence in a microwave-driven four-level atomic system. Owing to the space-dependent atom-field interaction, it is found that the detecting probability and precision of 2D and 3D atom localization behaviors can be significantly improved via adjusting the system parameters, the phase, amplitude, and initial population distribution. Interestingly, the atom can be localized in volumes that are substantially smaller than a cubic optical wavelength. Our scheme opens a promising way to achieve high-precision and high-efficiency atom localization, which provides some potential applications in high-dimensional atom nanolithography.

Mitigating the Insider Threat Using High-Dimensional Search and Modeling

National Research Council Canada - National Science Library

Van Den Berg, Eric; Uphadyaya, Shambhu; Ngo, Phi H; Muthukrishnan, Muthu; Palan, Rajago

2006-01-01

In this project a system was built aimed at mitigating insider attacks centered around a high-dimensional search engine for correlating the large number of monitoring streams necessary for detecting insider attacks...

Topologically protected bound states in one-dimensional Floquet acoustic waveguide systems

Science.gov (United States)

Peng, Yu-Gui; Geng, Zhi-Guo; Zhu, Xue-Feng

2018-03-01

Topological manipulation of sound has recently been a hot spot in acoustics due to the fascinating property of defect immune transport. To the best of our knowledge, the studies on one-dimensional (1D) topological acoustic systems hitherto mainly focus on the case of the Su-Schrieffer-Heeger model. Here, we show that topologically protected bound states may also exist in 1D periodically modulated acoustic waveguide systems, viz., 1D Floquet topological insulators. The results show that tuning the coupling strength in a waveguide lattice could trigger topological phase transition, which gives rise to topologically protected interface states as we put together two waveguide lattices featured with different topological phases or winding numbers. However, for the combined lattice, input at the waveguides other than the interfacial ones will excite bulk states. We have further verified the robustness of interface bound states against the variation of coupling strengths between the two distinct waveguide lattices. This work extends the scope of topological acoustics and may promote potential applications for acoustic devices with topological functionalities.

Disorder effects in two-dimensional Fermi systems with conical spectrum: exact results for the density of states

International Nuclear Information System (INIS)

Nersesyan, A.A.; Tsvelik, A.M.; Wenger, F.

1995-01-01

The influence of weak non-magnetic disorder on the single-particle density of states ρ(ω) of two-dimensional electron systems with a conical spectrum is studied. We use a non-perturbative approach, based on the replica trick with subsequent mapping of the effective action onto a one-dimensional model of interacting fermions, the latter being treated by abelian and non-abelian bosonization methods. Specifically, we consider a weakly disordered p- or d-wave superconductor, in which case the problem reduces to a model of (2+1)-dimensional massless Dirac fermions coupled to random, static, generally non-abelian gauge fields. It is shown that the density of states of a two-dimensional p- or d-wave superconductor, averaged over randomness, follows a non-trivial power-law behavior near the Fermi energy: ρ(ω) similar vertical stroke ωvertical stroke α . The exponent α>0 is exactly calculated for several types of disorder. We demonstrate that the property ρ(0) = 0 is a direct consequence of a continuous symmetry of the effective fermionic model, whose breakdown is forbidden in two dimensions. As a counter example, we also discuss another model with a conical spectrum - a two-dimensional orbital antiferromagnet, where static disorder leads to a finite ρ(0) due to the breakdown of a discrete (particle-hole) symmetry. ((orig.))

Characterization of discontinuities in high-dimensional stochastic problems on adaptive sparse grids

International Nuclear Information System (INIS)

Jakeman, John D.; Archibald, Richard; Xiu Dongbin

2011-01-01

In this paper we present a set of efficient algorithms for detection and identification of discontinuities in high dimensional space. The method is based on extension of polynomial annihilation for discontinuity detection in low dimensions. Compared to the earlier work, the present method poses significant improvements for high dimensional problems. The core of the algorithms relies on adaptive refinement of sparse grids. It is demonstrated that in the commonly encountered cases where a discontinuity resides on a small subset of the dimensions, the present method becomes 'optimal', in the sense that the total number of points required for function evaluations depends linearly on the dimensionality of the space. The details of the algorithms will be presented and various numerical examples are utilized to demonstrate the efficacy of the method.

Pricing High-Dimensional American Options Using Local Consistency Conditions

NARCIS (Netherlands)

Berridge, S.J.; Schumacher, J.M.

2004-01-01

We investigate a new method for pricing high-dimensional American options. The method is of finite difference type but is also related to Monte Carlo techniques in that it involves a representative sampling of the underlying variables.An approximating Markov chain is built using this sampling and

High-Harmonic Generation in Solids with and without Topological Edge States

Science.gov (United States)

Bauer, Dieter; Hansen, Kenneth K.

2018-04-01

High-harmonic generation in the two topological phases of a finite, one-dimensional, periodic structure is investigated using a self-consistent time-dependent density functional theory approach. For harmonic photon energies smaller than the band gap, the harmonic yield is found to differ by up to 14 orders of magnitude for the two topological phases. This giant topological effect is explained by the degree of destructive interference in the harmonic emission of all valence-band (and edge-state) electrons, which strongly depends on whether or not topological edge states are present. The combination of strong-field laser physics with topological condensed matter opens up new possibilities to electronically control strong-field-based light or particle sources or—conversely—to steer by all optical means topological electronics.

Scanning three-dimensional x-ray diffraction microscopy using a high-energy microbeam

International Nuclear Information System (INIS)

Hayashi, Y.; Hirose, Y.; Seno, Y.

2016-01-01

A scanning three-dimensional X-ray diffraction (3DXRD) microscope apparatus with a high-energy microbeam was installed at the BL33XU Toyota beamline at SPring-8. The size of the 50 keV beam focused using Kirkpatrick-Baez mirrors was 1.3 μm wide and 1.6 μm high in full width at half maximum. The scanning 3DXRD method was tested for a cold-rolled carbon steel sheet sample. A three-dimensional orientation map with 37 "3 voxels was obtained.

Scanning three-dimensional x-ray diffraction microscopy using a high-energy microbeam

Energy Technology Data Exchange (ETDEWEB)

Hayashi, Y., E-mail: y-hayashi@mosk.tytlabs.co.jp; Hirose, Y.; Seno, Y. [Toyota Central R& D Toyota Central R& D Labs., Inc., 41-1 Nagakute Aichi 480-1192 Japan (Japan)

2016-07-27

A scanning three-dimensional X-ray diffraction (3DXRD) microscope apparatus with a high-energy microbeam was installed at the BL33XU Toyota beamline at SPring-8. The size of the 50 keV beam focused using Kirkpatrick-Baez mirrors was 1.3 μm wide and 1.6 μm high in full width at half maximum. The scanning 3DXRD method was tested for a cold-rolled carbon steel sheet sample. A three-dimensional orientation map with 37 {sup 3} voxels was obtained.

Entanglement properties of the two-dimensional SU(3) Affleck-Kennedy-Lieb-Tasaki state

Science.gov (United States)

Gauthé, Olivier; Poilblanc, Didier

2017-09-01

Two-dimensional (spin-2) Affleck-Kennedy-Lieb-Tasaki (AKLT) type valence bond solids on a square lattice are known to be symmetry-protected topological (SPT) gapped spin liquids [S. Takayoshi, P. Pujol, and A. Tanaka Phys. Rev. B 94, 235159 (2016), 10.1103/PhysRevB.94.235159]. Using the projected entangled pair state framework, we extend the construction of the AKLT state to the case of SU(3 ) , relevant for cold atom systems. The entanglement spectrum is shown to be described by an alternating SU(3 ) chain of "quarks" and "antiquarks", subject to exponentially decaying (with distance) Heisenberg interactions, in close similarity with its SU(2 ) analog. We discuss the SPT feature of the state.

Data analysis in high-dimensional sparse spaces

DEFF Research Database (Denmark)

Clemmensen, Line Katrine Harder

classification techniques for high-dimensional problems are presented: Sparse discriminant analysis, sparse mixture discriminant analysis and orthogonality constrained support vector machines. The first two introduces sparseness to the well known linear and mixture discriminant analysis and thereby provide low...... are applied to classifications of fish species, ear canal impressions used in the hearing aid industry, microbiological fungi species, and various cancerous tissues and healthy tissues. In addition, novel applications of sparse regressions (also called the elastic net) to the medical, concrete, and food...

Preface [HD3-2015: International meeting on high-dimensional data-driven science

International Nuclear Information System (INIS)

2016-01-01

A never-ending series of innovations in measurement technology and evolutions in information and communication technologies have led to the ongoing generation and accumulation of large quantities of high-dimensional data every day. While detailed data-centric approaches have been pursued in respective research fields, situations have been encountered where the same mathematical framework of high-dimensional data analysis can be found in a wide variety of seemingly unrelated research fields, such as estimation on the basis of undersampled Fourier transform in nuclear magnetic resonance spectroscopy in chemistry, in magnetic resonance imaging in medicine, and in astronomical interferometry in astronomy. In such situations, bringing diverse viewpoints together therefore becomes a driving force for the creation of innovative developments in various different research fields. This meeting focuses on “Sparse Modeling” (SpM) as a methodology for creation of innovative developments through the incorporation of a wide variety of viewpoints in various research fields. The objective of this meeting is to offer a forum where researchers with interest in SpM can assemble and exchange information on the latest results and newly established methodologies, and discuss future directions of the interdisciplinary studies for High-Dimensional Data-Driven science (HD 3 ). The meeting was held in Kyoto from 14-17 December 2015. We are pleased to publish 22 papers contributed by invited speakers in this volume of Journal of Physics: Conference Series. We hope that this volume will promote further development of High-Dimensional Data-Driven science. (paper)

State operator, constants of the motion, and Wigner functions: The two-dimensional isotropic harmonic oscillator

DEFF Research Database (Denmark)

Dahl, Jens Peder; Schleich, W. P.

2009-01-01

For a closed quantum system the state operator must be a function of the Hamiltonian. When the state is degenerate, additional constants of the motion enter the play. But although it is the Weyl transform of the state operator, the Wigner function is not necessarily a function of the Weyl...... transforms of the constants of the motion. We derive conditions for which this is actually the case. The Wigner functions of the energy eigenstates of a two-dimensional isotropic harmonic oscillator serve as an important illustration....

Two-particle correlations in the one-dimensional Hubbard model: a ground-state analytical solution

CERN Document Server

Vallejo, E; Espinosa, J E

2003-01-01

A solution to the extended Hubbard Hamiltonian for the case of two-particles in an infinite one-dimensional lattice is presented, using a real-space mapping method and the Green function technique. This Hamiltonian considers the on-site (U) and the nearest-neighbor (V) interactions. The method is based on mapping the correlated many-body problem onto an equivalent site-impurity tight-binding one in a higher dimensional space. In this new space we obtained the analytical solution for the ground state binding energy. Results are in agreement with the numerical solution obtained previously [1], and with those obtained in the reciprocal space [2]. (Author)

Two-dimensional electron states bound to an off-plane donor in a magnetic field

International Nuclear Information System (INIS)

Bruno-Alfonso, A; Candido, L; Hai, G-Q

2010-01-01

The states of an electron confined in a two-dimensional (2D) plane and bound to an off-plane donor impurity center, in the presence of a magnetic field, are investigated. The energy levels of the ground state and the first three excited states are calculated variationally. The binding energy and the mean orbital radius of these states are obtained as a function of the donor center position and the magnetic field strength. The limiting cases are discussed for an in-plane donor impurity (i.e. a 2D hydrogen atom) as well as for the donor center far away from the 2D plane in strong magnetic fields, which corresponds to a 2D harmonic oscillator.

C4N3H monolayer: A two-dimensional organic Dirac material with high Fermi velocity

Science.gov (United States)

Pan, Hongzhe; Zhang, Hongyu; Sun, Yuanyuan; Li, Jianfu; Du, Youwei; Tang, Nujiang

2017-11-01

Searching for two-dimensional (2D) organic Dirac materials, which have more adaptable practical applications compared with inorganic ones, is of great significance and has been ongoing. However, only two such materials with low Fermi velocity have been discovered so far. Herein, we report the design of an organic monolayer with C4N3H stoichiometry that possesses fascinating structure and good stability in its free-standing state. More importantly, we demonstrate that this monolayer is a semimetal with anisotropic Dirac cones and very high Fermi velocity. This Fermi velocity is roughly one order of magnitude larger than the largest velocity ever reported in 2D organic Dirac materials, and it is comparable to that in graphene. The Dirac states in this monolayer arise from the extended π -electron conjugation system formed by the overlapping 2 pz orbitals of carbon and nitrogen atoms. Our finding paves the way to a search for more 2D organic Dirac materials with high Fermi velocity.

Class prediction for high-dimensional class-imbalanced data

Directory of Open Access Journals (Sweden)

Lusa Lara

2010-10-01

Full Text Available Abstract Background The goal of class prediction studies is to develop rules to accurately predict the class membership of new samples. The rules are derived using the values of the variables available for each subject: the main characteristic of high-dimensional data is that the number of variables greatly exceeds the number of samples. Frequently the classifiers are developed using class-imbalanced data, i.e., data sets where the number of samples in each class is not equal. Standard classification methods used on class-imbalanced data often produce classifiers that do not accurately predict the minority class; the prediction is biased towards the majority class. In this paper we investigate if the high-dimensionality poses additional challenges when dealing with class-imbalanced prediction. We evaluate the performance of six types of classifiers on class-imbalanced data, using simulated data and a publicly available data set from a breast cancer gene-expression microarray study. We also investigate the effectiveness of some strategies that are available to overcome the effect of class imbalance. Results Our results show that the evaluated classifiers are highly sensitive to class imbalance and that variable selection introduces an additional bias towards classification into the majority class. Most new samples are assigned to the majority class from the training set, unless the difference between the classes is very large. As a consequence, the class-specific predictive accuracies differ considerably. When the class imbalance is not too severe, down-sizing and asymmetric bagging embedding variable selection work well, while over-sampling does not. Variable normalization can further worsen the performance of the classifiers. Conclusions Our results show that matching the prevalence of the classes in training and test set does not guarantee good performance of classifiers and that the problems related to classification with class

Two-dimensional systems from introduction to state of the art

CERN Document Server

Benzaouia, Abdellah; Tadeo, Fernando

2016-01-01

A solution permitting the stabilization of 2-dimensional (2-D) continuous-time saturated system under state feedback control is presented in this book. The problems of delay and saturation are treated at the same time. The authors obtain novel results on continuous 2-D systems using the unidirectional Lyapunov function. The control synthesis and the saturation and delay conditions are presented as linear matrix inequalities. Illustrative examples are worked through to show the effectiveness of the approach and many comparisons are made with existing results. The second half of the book moves on to consider robust stabilization and filtering of 2-D systems with particular consideration being given to 2-D fuzzy systems. Solutions for the filter-design problems are demonstrated by computer simulation. The text builds up to the development of state feedback control for 2-D Takagi–Sugeno systems with stochastic perturbation. Conservatism is reduced by using slack matrices and the coupling between the Lyapunov ma...

Control of two-dimensional electronic states at anatase Ti O2(001 ) surface by K adsorption

Science.gov (United States)

Yukawa, R.; Minohara, M.; Shiga, D.; Kitamura, M.; Mitsuhashi, T.; Kobayashi, M.; Horiba, K.; Kumigashira, H.

2018-04-01

The nature of the intriguing metallic electronic structures appearing at the surface of anatase titanium dioxide (a-Ti O2 ) remains to be elucidated, mainly owing to the difficulty of controlling the depth distribution of the oxygen vacancies generated by photoirradiation. In this study, K atoms were adsorbed onto the (001) surface of a-Ti O2 to dope electrons into the a-Ti O2 and to confine the electrons in the surface region. The success of the electron doping and its controllability were confirmed by performing in situ angle-resolved photoemission spectroscopy as well as core-level measurements. Clear subband structures were observed in the surface metallic states, indicating the creation of quasi-two-dimensional electron liquid (q2DEL) states in a controllable fashion. With increasing electron doping (K adsorption), the q2DEL states exhibited crossover from polaronic liquid states with multiple phonon-loss structures originating from the long-range Fröhlich interaction to "weakly correlated metallic" states. In the q2DEL states in the weakly correlated metallic region, a kink due to short-range electron-phonon coupling was clearly observed at about 80 ±10 meV . The characteristic energy is smaller than that previously observed for the metallic states of a-Ti O2 with three-dimensional nature (˜110 meV ) . These results suggest that the dominant electron-phonon coupling is modulated by anisotropic carrier screening in the q2DEL states.

Global communication schemes for the numerical solution of high-dimensional PDEs

DEFF Research Database (Denmark)

Hupp, Philipp; Heene, Mario; Jacob, Riko

2016-01-01

The numerical treatment of high-dimensional partial differential equations is among the most compute-hungry problems and in urgent need for current and future high-performance computing (HPC) systems. It is thus also facing the grand challenges of exascale computing such as the requirement...

High-resolution two-dimensional and three-dimensional modeling of wire grid polarizers and micropolarizer arrays

Science.gov (United States)

Vorobiev, Dmitry; Ninkov, Zoran

2017-11-01

Recent advances in photolithography allowed the fabrication of high-quality wire grid polarizers for the visible and near-infrared regimes. In turn, micropolarizer arrays (MPAs) based on wire grid polarizers have been developed and used to construct compact, versatile imaging polarimeters. However, the contrast and throughput of these polarimeters are significantly worse than one might expect based on the performance of large area wire grid polarizers or MPAs, alone. We investigate the parameters that affect the performance of wire grid polarizers and MPAs, using high-resolution two-dimensional and three-dimensional (3-D) finite-difference time-domain simulations. We pay special attention to numerical errors and other challenges that arise in models of these and other subwavelength optical devices. Our tests show that simulations of these structures in the visible and near-IR begin to converge numerically when the mesh size is smaller than ˜4 nm. The performance of wire grid polarizers is very sensitive to the shape, spacing, and conductivity of the metal wires. Using 3-D simulations of micropolarizer "superpixels," we directly study the cross talk due to diffraction at the edges of each micropolarizer, which decreases the contrast of MPAs to ˜200∶1.

Theoretical study on the cooperative exciton dissociation process based on dimensional and hot charge-transfer state effects in an organic photocell

International Nuclear Information System (INIS)

Shimazaki, Tomomi; Nakajima, Takahito

2016-01-01

This paper discusses the exciton dissociation process at the donor–acceptor interface in organic photocells. In our previous study, we introduced a local temperature to handle the hot charge-transfer (CT) state and calculated the exciton dissociation probability based on the 1D organic semiconductor model [T. Shimazaki and T. Nakajima, Phys. Chem. Chem. Phys. 17, 12538 (2015)]. Although the hot CT state plays an essential role in exciton dissociations, the probabilities calculated are not high enough to efficiently separate bound electron–hole pairs. This paper focuses on the dimensional (entropy) effect together with the hot CT state effect and shows that cooperative behavior between both effects can improve the exciton dissociation process. In addition, we discuss cooperative effects with site-disorders and external-electric-fields.

Ground-state projection multigrid for propagators in 4-dimensional SU(2) gauge fields

International Nuclear Information System (INIS)

Kalkreuter, T.

1991-09-01

The ground-state projection multigrid method is studied for computations of slowly decaying bosonic propagators in 4-dimensional SU(2) lattice gauge theory. The defining eigenvalue equation for the restriction operator is solved exactly. Although the critical exponent z is not reduced in nontrivial gauge fields, multigrid still yields considerable speedup compared with conventional relaxation. Multigrid is also able to outperform the conjugate gradient algorithm. (orig.)

Accuracy Assessment for the Three-Dimensional Coordinates by High-Speed Videogrammetric Measurement

Directory of Open Access Journals (Sweden)

Xianglei Liu

2018-01-01

Full Text Available High-speed CMOS camera is a new kind of transducer to make the videogrammetric measurement for monitoring the displacement of high-speed shaking table structure. The purpose of this paper is to validate the three-dimensional coordinate accuracy of the shaking table structure acquired from the presented high-speed videogrammetric measuring system. In the paper, all of the key intermediate links are discussed, including the high-speed CMOS videogrammetric measurement system, the layout of the control network, the elliptical target detection, and the accuracy validation of final 3D spatial results. Through the accuracy analysis, the submillimeter accuracy can be made for the final the three-dimensional spatial coordinates which certify that the proposed high-speed videogrammetric technique is a better alternative technique which can replace the traditional transducer technique for monitoring the dynamic response for the shaking table structure.

Secure data storage by three-dimensional absorbers in highly scattering volume medium

International Nuclear Information System (INIS)

Matoba, Osamu; Matsuki, Shinichiro; Nitta, Kouichi

2008-01-01

A novel data storage in a volume medium with highly scattering coefficient is proposed for data security application. Three-dimensional absorbers are used as data. These absorbers can not be measured by interferometer when the scattering in a volume medium is strong enough. We present a method to reconstruct three-dimensional absorbers and present numerical results to show the effectiveness of the proposed data storage.

High-Resolution Isotropic Three-Dimensional MR Imaging of the Extraforaminal Segments of the Cranial Nerves.

Science.gov (United States)

Wen, Jessica; Desai, Naman S; Jeffery, Dean; Aygun, Nafi; Blitz, Ari

2018-02-01

High-resolution isotropic 3-dimensional (D) MR imaging with and without contrast is now routinely used for imaging evaluation of cranial nerve anatomy and pathologic conditions. The anatomic details of the extraforaminal segments are well-visualized on these techniques. A wide range of pathologic entities may cause enhancement or displacement of the nerve, which is now visible to an extent not available on standard 2D imaging. This article highlights the anatomy of extraforaminal segments of the cranial nerves and uses select cases to illustrate the utility and power of these sequences, with a focus on constructive interference in steady-state. Copyright © 2017 Elsevier Inc. All rights reserved.

Generation and confirmation of a (100 x 100)-dimensional entangled quantum system.

Science.gov (United States)

Krenn, Mario; Huber, Marcus; Fickler, Robert; Lapkiewicz, Radek; Ramelow, Sven; Zeilinger, Anton

2014-04-29

Entangled quantum systems have properties that have fundamentally overthrown the classical worldview. Increasing the complexity of entangled states by expanding their dimensionality allows the implementation of novel fundamental tests of nature, and moreover also enables genuinely new protocols for quantum information processing. Here we present the creation of a (100 × 100)-dimensional entangled quantum system, using spatial modes of photons. For its verification we develop a novel nonlinear criterion which infers entanglement dimensionality of a global state by using only information about its subspace correlations. This allows very practical experimental implementation as well as highly efficient extraction of entanglement dimensionality information. Applications in quantum cryptography and other protocols are very promising.

Generation and confirmation of a (100 × 100)-dimensional entangled quantum system

Science.gov (United States)

Krenn, Mario; Huber, Marcus; Fickler, Robert; Lapkiewicz, Radek; Ramelow, Sven; Zeilinger, Anton

2014-01-01

Entangled quantum systems have properties that have fundamentally overthrown the classical worldview. Increasing the complexity of entangled states by expanding their dimensionality allows the implementation of novel fundamental tests of nature, and moreover also enables genuinely new protocols for quantum information processing. Here we present the creation of a (100 × 100)-dimensional entangled quantum system, using spatial modes of photons. For its verification we develop a novel nonlinear criterion which infers entanglement dimensionality of a global state by using only information about its subspace correlations. This allows very practical experimental implementation as well as highly efficient extraction of entanglement dimensionality information. Applications in quantum cryptography and other protocols are very promising. PMID:24706902

High-dimensional quantum cryptography with twisted light

International Nuclear Information System (INIS)

Mirhosseini, Mohammad; Magaña-Loaiza, Omar S; O’Sullivan, Malcolm N; Rodenburg, Brandon; Malik, Mehul; Boyd, Robert W; Lavery, Martin P J; Padgett, Miles J; Gauthier, Daniel J

2015-01-01

Quantum key distribution (QKD) systems often rely on polarization of light for encoding, thus limiting the amount of information that can be sent per photon and placing tight bounds on the error rates that such a system can tolerate. Here we describe a proof-of-principle experiment that indicates the feasibility of high-dimensional QKD based on the transverse structure of the light field allowing for the transfer of more than 1 bit per photon. Our implementation uses the orbital angular momentum (OAM) of photons and the corresponding mutually unbiased basis of angular position (ANG). Our experiment uses a digital micro-mirror device for the rapid generation of OAM and ANG modes at 4 kHz, and a mode sorter capable of sorting single photons based on their OAM and ANG content with a separation efficiency of 93%. Through the use of a seven-dimensional alphabet encoded in the OAM and ANG bases, we achieve a channel capacity of 2.05 bits per sifted photon. Our experiment demonstrates that, in addition to having an increased information capacity, multilevel QKD systems based on spatial-mode encoding can be more resilient against intercept-resend eavesdropping attacks. (paper)

A Near-linear Time Approximation Algorithm for Angle-based Outlier Detection in High-dimensional Data

DEFF Research Database (Denmark)

Pham, Ninh Dang; Pagh, Rasmus

2012-01-01

projection-based technique that is able to estimate the angle-based outlier factor for all data points in time near-linear in the size of the data. Also, our approach is suitable to be performed in parallel environment to achieve a parallel speedup. We introduce a theoretical analysis of the quality...... neighbor are deteriorated in high-dimensional data. Following up on the work of Kriegel et al. (KDD '08), we investigate the use of angle-based outlier factor in mining high-dimensional outliers. While their algorithm runs in cubic time (with a quadratic time heuristic), we propose a novel random......Outlier mining in d-dimensional point sets is a fundamental and well studied data mining task due to its variety of applications. Most such applications arise in high-dimensional domains. A bottleneck of existing approaches is that implicit or explicit assessments on concepts of distance or nearest...

A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

OpenAIRE

Zekić-Sušac, Marijana; Pfeifer, Sanja; Šarlija, Nataša

2014-01-01

Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART ...

Framework to model neutral particle flux in convex high aspect ratio structures using one-dimensional radiosity

Science.gov (United States)

Manstetten, Paul; Filipovic, Lado; Hössinger, Andreas; Weinbub, Josef; Selberherr, Siegfried

2017-02-01

We present a computationally efficient framework to compute the neutral flux in high aspect ratio structures during three-dimensional plasma etching simulations. The framework is based on a one-dimensional radiosity approach and is applicable to simulations of convex rotationally symmetric holes and convex symmetric trenches with a constant cross-section. The framework is intended to replace the full three-dimensional simulation step required to calculate the neutral flux during plasma etching simulations. Especially for high aspect ratio structures, the computational effort, required to perform the full three-dimensional simulation of the neutral flux at the desired spatial resolution, conflicts with practical simulation time constraints. Our results are in agreement with those obtained by three-dimensional Monte Carlo based ray tracing simulations for various aspect ratios and convex geometries. With this framework we present a comprehensive analysis of the influence of the geometrical properties of high aspect ratio structures as well as of the particle sticking probability on the neutral particle flux.

Spectrally-Corrected Estimation for High-Dimensional Markowitz Mean-Variance Optimization

NARCIS (Netherlands)

Z. Bai (Zhidong); H. Li (Hua); M.J. McAleer (Michael); W.-K. Wong (Wing-Keung)

2016-01-01

textabstractThis paper considers the portfolio problem for high dimensional data when the dimension and size are both large. We analyze the traditional Markowitz mean-variance (MV) portfolio by large dimension matrix theory, and find the spectral distribution of the sample covariance is the main

Linear stability theory as an early warning sign for transitions in high dimensional complex systems

International Nuclear Information System (INIS)

Piovani, Duccio; Grujić, Jelena; Jensen, Henrik Jeldtoft

2016-01-01

We analyse in detail a new approach to the monitoring and forecasting of the onset of transitions in high dimensional complex systems by application to the Tangled Nature model of evolutionary ecology and high dimensional replicator systems with a stochastic element. A high dimensional stability matrix is derived in the mean field approximation to the stochastic dynamics. This allows us to determine the stability spectrum about the observed quasi-stable configurations. From overlap of the instantaneous configuration vector of the full stochastic system with the eigenvectors of the unstable directions of the deterministic mean field approximation, we are able to construct a good early-warning indicator of the transitions occurring intermittently. (paper)

High-dimensional quantum channel estimation using classical light

CSIR Research Space (South Africa)

Mabena, Chemist M

2017-11-01

Full Text Available stream_source_info Mabena_20007_2017.pdf.txt stream_content_type text/plain stream_size 960 Content-Encoding UTF-8 stream_name Mabena_20007_2017.pdf.txt Content-Type text/plain; charset=UTF-8 PHYSICAL REVIEW A 96, 053860... (2017) High-dimensional quantum channel estimation using classical light Chemist M. Mabena CSIR National Laser Centre, P.O. Box 395, Pretoria 0001, South Africa and School of Physics, University of the Witwatersrand, Johannesburg 2000, South...

High dimensional classifiers in the imbalanced case

DEFF Research Database (Denmark)

Bak, Britta Anker; Jensen, Jens Ledet

We consider the binary classification problem in the imbalanced case where the number of samples from the two groups differ. The classification problem is considered in the high dimensional case where the number of variables is much larger than the number of samples, and where the imbalance leads...... to a bias in the classification. A theoretical analysis of the independence classifier reveals the origin of the bias and based on this we suggest two new classifiers that can handle any imbalance ratio. The analytical results are supplemented by a simulation study, where the suggested classifiers in some...

Relative entropy of excited states in two dimensional conformal field theories

Energy Technology Data Exchange (ETDEWEB)

Sárosi, Gábor [Department of Theoretical Physics, Institute of Physics, Budapest University of Technology,Budapest, H-1521 (Hungary); Ugajin, Tomonori [Kavli Institute for Theoretical Physics, University of California,Santa Barbara,CA 93106 (United States)

2016-07-21

We study the relative entropy and the trace square distance, both of which measure the distance between reduced density matrices of two excited states in two dimensional conformal field theories. We find a general formula for the relative entropy between two primary states with the same conformal dimension in the limit of a single small interval and find that in this case the relative entropy is proportional to the trace square distance. We check our general formulae by calculating the relative entropy between two generalized free fields and the trace square distance between the spin and disorder operators of the critical Ising model. We also give the leading term of the relative entropy in the small interval expansion when the two operators have different conformal dimensions. This turns out to be universal when the CFT has no primaires lighter than the stress tensor. The result reproduces the previously known special cases.

An irregular grid approach for pricing high-dimensional American options

NARCIS (Netherlands)

Berridge, S.J.; Schumacher, J.M.

2008-01-01

We propose and test a new method for pricing American options in a high-dimensional setting. The method is centered around the approximation of the associated complementarity problem on an irregular grid. We approximate the partial differential operator on this grid by appealing to the SDE

An Irregular Grid Approach for Pricing High-Dimensional American Options

NARCIS (Netherlands)

Berridge, S.J.; Schumacher, J.M.

2004-01-01

We propose and test a new method for pricing American options in a high-dimensional setting.The method is centred around the approximation of the associated complementarity problem on an irregular grid.We approximate the partial differential operator on this grid by appealing to the SDE

Applying recursive numerical integration techniques for solving high dimensional integrals

International Nuclear Information System (INIS)

Ammon, Andreas; Genz, Alan; Hartung, Tobias; Jansen, Karl; Volmer, Julia; Leoevey, Hernan

2016-11-01

The error scaling for Markov-Chain Monte Carlo techniques (MCMC) with N samples behaves like 1/√(N). This scaling makes it often very time intensive to reduce the error of computed observables, in particular for applications in lattice QCD. It is therefore highly desirable to have alternative methods at hand which show an improved error scaling. One candidate for such an alternative integration technique is the method of recursive numerical integration (RNI). The basic idea of this method is to use an efficient low-dimensional quadrature rule (usually of Gaussian type) and apply it iteratively to integrate over high-dimensional observables and Boltzmann weights. We present the application of such an algorithm to the topological rotor and the anharmonic oscillator and compare the error scaling to MCMC results. In particular, we demonstrate that the RNI technique shows an error scaling in the number of integration points m that is at least exponential.

Applying recursive numerical integration techniques for solving high dimensional integrals

Energy Technology Data Exchange (ETDEWEB)

Ammon, Andreas [IVU Traffic Technologies AG, Berlin (Germany); Genz, Alan [Washington State Univ., Pullman, WA (United States). Dept. of Mathematics; Hartung, Tobias [King' s College, London (United Kingdom). Dept. of Mathematics; Jansen, Karl; Volmer, Julia [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Leoevey, Hernan [Humboldt Univ. Berlin (Germany). Inst. fuer Mathematik

2016-11-15

The error scaling for Markov-Chain Monte Carlo techniques (MCMC) with N samples behaves like 1/√(N). This scaling makes it often very time intensive to reduce the error of computed observables, in particular for applications in lattice QCD. It is therefore highly desirable to have alternative methods at hand which show an improved error scaling. One candidate for such an alternative integration technique is the method of recursive numerical integration (RNI). The basic idea of this method is to use an efficient low-dimensional quadrature rule (usually of Gaussian type) and apply it iteratively to integrate over high-dimensional observables and Boltzmann weights. We present the application of such an algorithm to the topological rotor and the anharmonic oscillator and compare the error scaling to MCMC results. In particular, we demonstrate that the RNI technique shows an error scaling in the number of integration points m that is at least exponential.

Ground-state properties of anyons in a one-dimensional lattice

Science.gov (United States)

Tang, Guixin; Eggert, Sebastian; Pelster, Axel

2015-12-01

Using the Anyon-Hubbard Hamiltonian, we analyze the ground-state properties of anyons in a one-dimensional lattice. To this end we map the hopping dynamics of correlated anyons to an occupation-dependent hopping Bose-Hubbard model using the fractional Jordan-Wigner transformation. In particular, we calculate the quasi-momentum distribution of anyons, which interpolates between Bose-Einstein and Fermi-Dirac statistics. Analytically, we apply a modified Gutzwiller mean-field approach, which goes beyond a classical one by including the influence of the fractional phase of anyons within the many-body wavefunction. Numerically, we use the density-matrix renormalization group by relying on the ansatz of matrix product states. As a result it turns out that the anyonic quasi-momentum distribution reveals both a peak-shift and an asymmetry which mainly originates from the nonlocal string property. In addition, we determine the corresponding quasi-momentum distribution of the Jordan-Wigner transformed bosons, where, in contrast to the hard-core case, we also observe an asymmetry for the soft-core case, which strongly depends on the particle number density.

Four-dimensional (4D) tracking of high-temperature microparticles

International Nuclear Information System (INIS)

Wang, Zhehui; Liu, Q.; Waganaar, W.; Fontanese, J.; James, D.; Munsat, T.

2016-01-01

High-speed tracking of hot and molten microparticles in motion provides rich information about burning plasmas in magnetic fusion. An exploding-wire apparatus is used to produce moving high-temperature metallic microparticles and to develop four-dimensional (4D) or time-resolved 3D particle tracking techniques. The pinhole camera model and algorithms developed for computer vision are used for scene calibration and 4D reconstructions. 3D positions and velocities are then derived for different microparticles. Velocity resolution approaches 0.1 m/s by using the local constant velocity approximation.

Angular studies of the magnetoresistance in the density wave state of the quasi-two-dimensional purple bronze KMo6O17

Science.gov (United States)

Guyot, H.; Dumas, J.; Kartsovnik, M. V.; Marcus, J.; Schlenker, C.; Sheikin, I.; Vignolles, D.

2007-07-01

The purple molybdenum bronze KMo6O17 is a quasi-two-dimensional compound which shows a Peierls transition towards a commensurate metallic charge density wave (CDW) state. High magnetic field measurements have revealed several transitions at low temperature and have provided an unusual phase diagram “temperature-magnetic field”. Angular studies of the interlayer magnetoresistance are now reported. The results suggest that the orbital coupling of the magnetic field to the CDW is the most likely mechanism for the field induced transitions. The angular dependence of the magnetoresistance is discussed on the basis of a warped quasi-cylindrical Fermi surface and provides information on the geometry of the Fermi surface in the low temperature density wave state.

Multi-dimensional analysis of high resolution {gamma}-ray data

Energy Technology Data Exchange (ETDEWEB)

Flibotte, S.; Huettmeier, U.J.; France, G. de; Haas, B.; Romain, P.; Theisen, Ch.; Vivien, J.P.; Zen, J. [Strasbourg-1 Univ., 67 (France). Centre de Recherches Nucleaires

1992-12-31

A new generation of high resolution {gamma}-ray spectrometers capable of recording high-fold coincidence events with a large efficiency will soon be available. Algorithms are developed to analyze high-fold {gamma}-ray coincidences. As a contribution to the software development associated with the EUROGAM spectrometer, the performances of computer codes designed to select multi-dimensional gates from 3-, 4- and 5-fold coincidence databases were tested. The tests were performed on events generated with a Monte Carlo simulation and also on real experimental triple data recorded with the 8{pi} spectrometer and with a preliminary version of the EUROGAM array. (R.P.) 14 refs.; 3 figs.; 3 tabs.

Multi-dimensional analysis of high resolution γ-ray data

International Nuclear Information System (INIS)

Flibotte, S.; Huettmeier, U.J.; France, G. de; Haas, B.; Romain, P.; Theisen, Ch.; Vivien, J.P.; Zen, J.

1992-01-01

A new generation of high resolution γ-ray spectrometers capable of recording high-fold coincidence events with a large efficiency will soon be available. Algorithms are developed to analyze high-fold γ-ray coincidences. As a contribution to the software development associated with the EUROGAM spectrometer, the performances of computer codes designed to select multi-dimensional gates from 3-, 4- and 5-fold coincidence databases were tested. The tests were performed on events generated with a Monte Carlo simulation and also on real experimental triple data recorded with the 8π spectrometer and with a preliminary version of the EUROGAM array. (R.P.) 14 refs.; 3 figs.; 3 tabs

Three dimensional illustrating - three-dimensional vision and deception of sensibility

Directory of Open Access Journals (Sweden)

Anita Gánóczy

2009-03-01

Full Text Available The wide-spread digital photography and computer use gave the opportunity for everyone to make three-dimensional pictures and to make them public. The new opportunities with three-dimensional techniques give chance for the birth of new artistic photographs. We present in detail the biological roots of three-dimensional visualization, the phenomena of movement parallax, which can be used efficiently in making three-dimensional graphics, the Zöllner- and Corridor-illusion. There are present in this paper the visual elements, which contribute to define a plane two-dimensional image in three-dimension: coherent lines, the covering, the measurement changes, the relative altitude state, the abatement of detail profusion, the shadings and the perspective effects of colors.

Two-dimensional topological photonics

Science.gov (United States)

Khanikaev, Alexander B.; Shvets, Gennady

2017-12-01

Originating from the studies of two-dimensional condensed-matter states, the concept of topological order has recently been expanded to other fields of physics and engineering, particularly optics and photonics. Topological photonic structures have already overturned some of the traditional views on wave propagation and manipulation. The application of topological concepts to guided wave propagation has enabled novel photonic devices, such as reflection-free sharply bent waveguides, robust delay lines, spin-polarized switches and non-reciprocal devices. Discrete degrees of freedom, widely used in condensed-matter physics, such as spin and valley, are now entering the realm of photonics. In this Review, we summarize the latest advances in this highly dynamic field, with special emphasis on the experimental work on two-dimensional photonic topological structures.

Antibound states for a class of one-dimensional Schroedinger Operators

International Nuclear Information System (INIS)

Angeletti, A.

1980-01-01

Let delta(x) be the Dirac's delta, q(x) element of L 1 (R) L 2 (R) be a real valued function, and lambda, μ element of R; we will consider the following class of one-dimensional formal Schroedinger operators on L 2 (R) H(lambda,μ) = - (d 2 /dx 2 ) + lambdadelta(x) + μq(x). It is known that to the formal operator H(lambda, μ) may be associated a selfadjoint operator H(lambda, μ) on L 2 (R). If q is of finite range, for lambda < 0 and /μ/ is small enough, we prove that H(lambda,μ) has an antibound state; that is the resolvent of H(lambda,μ) has a pole on the negative real axis on the second Riemann sheet. (orig.)

One-Dimensionality and Whiteness

Science.gov (United States)

Calderon, Dolores

2006-01-01

This article is a theoretical discussion that links Marcuse's concept of one-dimensional society and the Great Refusal with critical race theory in order to achieve a more robust interrogation of whiteness. The author argues that in the context of the United States, the one-dimensionality that Marcuse condemns in "One-Dimensional Man" is best…

Network Reconstruction From High-Dimensional Ordinary Differential Equations.

Science.gov (United States)

Chen, Shizhe; Shojaie, Ali; Witten, Daniela M

2017-01-01

We consider the task of learning a dynamical system from high-dimensional time-course data. For instance, we might wish to estimate a gene regulatory network from gene expression data measured at discrete time points. We model the dynamical system nonparametrically as a system of additive ordinary differential equations. Most existing methods for parameter estimation in ordinary differential equations estimate the derivatives from noisy observations. This is known to be challenging and inefficient. We propose a novel approach that does not involve derivative estimation. We show that the proposed method can consistently recover the true network structure even in high dimensions, and we demonstrate empirical improvement over competing approaches. Supplementary materials for this article are available online.

HDclassif : An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data

Directory of Open Access Journals (Sweden)

Laurent Berge

2012-01-01

Full Text Available This paper presents the R package HDclassif which is devoted to the clustering and the discriminant analysis of high-dimensional data. The classification methods proposed in the package result from a new parametrization of the Gaussian mixture model which combines the idea of dimension reduction and model constraints on the covariance matrices. The supervised classification method using this parametrization is called high dimensional discriminant analysis (HDDA. In a similar manner, the associated clustering method iscalled high dimensional data clustering (HDDC and uses the expectation-maximization algorithm for inference. In order to correctly t the data, both methods estimate the specific subspace and the intrinsic dimension of the groups. Due to the constraints on the covariance matrices, the number of parameters to estimate is significantly lower than other model-based methods and this allows the methods to be stable and efficient in high dimensions. Two introductory examples illustrated with R codes allow the user to discover the hdda and hddc functions. Experiments on simulated and real datasets also compare HDDC and HDDA with existing classification methods on high-dimensional datasets. HDclassif is a free software and distributed under the general public license, as part of the R software project.

Spectral dimensionality of random superconducting networks

International Nuclear Information System (INIS)

Day, A.R.; Xia, W.; Thorpe, M.F.

1988-01-01

We compute the spectral dimensionality d of random superconducting-normal networks by directly examining the low-frequency density of states at the percolation threshold. We find that d = 4.1 +- 0.2 and 5.8 +- 0.3 in two and three dimensions, respectively, which confirms the scaling relation d = 2d/(2-s/ν), where s is the superconducting exponent and ν the correlation-length exponent for percolation. We also consider the one-dimensional problem where scaling arguments predict, and our numerical simulations confirm, that d = 0. A simple argument provides an expression for the density of states of the localized high-frequency modes in this special case. We comment on the connection between our calculations and the ''termite'' problem of a random walker on a random superconducting-normal network and point out difficulties in inferring d from simulations of the termite problem

One- and two-dimensional sublattices as preconditions for high-Tc superconductivity

International Nuclear Information System (INIS)

Krueger, E.

1989-01-01

In an earlier paper it was proposed describing superconductivity in the framework of a nonadiabatic Heisenberg model in order to interprete the outstanding symmetry proper ties of the (spin-dependent) Wannier functions in the conduction bands of superconductors. This new group-theoretical model suggests that Cooper pair formation can only be mediated by boson excitations carrying crystal-spin-angular momentum. While in the three-dimensionally isotropic lattices of the standard superconductors phonons are able to transport crystal-spin-angular momentum, this is not true for phonons propagating through the one- or two-dimensional Cu-O sublattices of the high-T c compounds. Therefore, if such an anisotropic material is superconducting, it is necessarily higher-energetic excitations (of well-defined symmetry) which mediate pair formation. This fact is proposed being responsible for the high transition temperatures of these compounds. (author)

Multivariate statistical analysis a high-dimensional approach

CERN Document Server

Serdobolskii, V

2000-01-01

In the last few decades the accumulation of large amounts of in­ formation in numerous applications. has stimtllated an increased in­ terest in multivariate analysis. Computer technologies allow one to use multi-dimensional and multi-parametric models successfully. At the same time, an interest arose in statistical analysis with a de­ ficiency of sample data. Nevertheless, it is difficult to describe the recent state of affairs in applied multivariate methods as satisfactory. Unimprovable (dominating) statistical procedures are still unknown except for a few specific cases. The simplest problem of estimat­ ing the mean vector with minimum quadratic risk is unsolved, even for normal distributions. Commonly used standard linear multivari­ ate procedures based on the inversion of sample covariance matrices can lead to unstable results or provide no solution in dependence of data. Programs included in standard statistical packages cannot process 'multi-collinear data' and there are no theoretical recommen­ ...

Two-Dimensional High Definition Versus Three-Dimensional Endoscopy in Endonasal Skull Base Surgery: A Comparative Preclinical Study.

Science.gov (United States)

Rampinelli, Vittorio; Doglietto, Francesco; Mattavelli, Davide; Qiu, Jimmy; Raffetti, Elena; Schreiber, Alberto; Villaret, Andrea Bolzoni; Kucharczyk, Walter; Donato, Francesco; Fontanella, Marco Maria; Nicolai, Piero

2017-09-01

Three-dimensional (3D) endoscopy has been recently introduced in endonasal skull base surgery. Only a relatively limited number of studies have compared it to 2-dimensional, high definition technology. The objective was to compare, in a preclinical setting for endonasal endoscopic surgery, the surgical maneuverability of 2-dimensional, high definition and 3D endoscopy. A group of 68 volunteers, novice and experienced surgeons, were asked to perform 2 tasks, namely simulating grasping and dissection surgical maneuvers, in a model of the nasal cavities. Time to complete the tasks was recorded. A questionnaire to investigate subjective feelings during tasks was filled by each participant. In 25 subjects, the surgeons' movements were continuously tracked by a magnetic-based neuronavigator coupled with dedicated software (ApproachViewer, part of GTx-UHN) and the recorded trajectories were analyzed by comparing jitter, sum of square differences, and funnel index. Total execution time was significantly lower with 3D technology (P < 0.05) in beginners and experts. Questionnaires showed that beginners preferred 3D endoscopy more frequently than experts. A minority (14%) of beginners experienced discomfort with 3D endoscopy. Analysis of jitter showed a trend toward increased effectiveness of surgical maneuvers with 3D endoscopy. Sum of square differences and funnel index analyses documented better values with 3D endoscopy in experts. In a preclinical setting for endonasal skull base surgery, 3D technology appears to confer an advantage in terms of time of execution and precision of surgical maneuvers. Copyright © 2017 Elsevier Inc. All rights reserved.

Diffraction limited focusing with controllable arbitrary three-dimensional polarization

International Nuclear Information System (INIS)

Chen, Weibin; Zhan, Qiwen

2010-01-01

We propose a new approach that enables full control over the three-dimensional state of polarization and the field distribution near the focus of a high numerical aperture objective lens. By combining the electric dipole radiation and a vectorial diffraction method, the input field at the pupil plane for generating arbitrary three-dimensionally oriented linear polarization at the focal point with a diffraction limited spot size is found analytically by solving the inverse problem. Arbitrary three-dimensional elliptical polarization can be obtained by introducing a second electric dipole oriented in the orthogonal plane with appropriate amplitude and phase differences

High thermoelectric power factor in two-dimensional crystals of Mo S2

Science.gov (United States)

Hippalgaonkar, Kedar; Wang, Ying; Ye, Yu; Qiu, Diana Y.; Zhu, Hanyu; Wang, Yuan; Moore, Joel; Louie, Steven G.; Zhang, Xiang

2017-03-01

The quest for high-efficiency heat-to-electricity conversion has been one of the major driving forces toward renewable energy production for the future. Efficient thermoelectric devices require high voltage generation from a temperature gradient and a large electrical conductivity while maintaining a low thermal conductivity. For a given thermal conductivity and temperature, the thermoelectric power factor is determined by the electronic structure of the material. Low dimensionality (1D and 2D) opens new routes to a high power factor due to the unique density of states (DOS) of confined electrons and holes. The 2D transition metal dichalcogenide (TMDC) semiconductors represent a new class of thermoelectric materials not only due to such confinement effects but especially due to their large effective masses and valley degeneracies. Here, we report a power factor of Mo S2 as large as 8.5 mW m-1K-2 at room temperature, which is among the highest measured in traditional, gapped thermoelectric materials. To obtain these high power factors, we perform thermoelectric measurements on few-layer Mo S2 in the metallic regime, which allows us to access the 2D DOS near the conduction band edge and exploit the effect of 2D confinement on electron scattering rates, resulting in a large Seebeck coefficient. The demonstrated high, electronically modulated power factor in 2D TMDCs holds promise for efficient thermoelectric energy conversion.

Quantifying high dimensional entanglement with two mutually unbiased bases

Directory of Open Access Journals (Sweden)

Paul Erker

2017-07-01

Full Text Available We derive a framework for quantifying entanglement in multipartite and high dimensional systems using only correlations in two unbiased bases. We furthermore develop such bounds in cases where the second basis is not characterized beyond being unbiased, thus enabling entanglement quantification with minimal assumptions. Furthermore, we show that it is feasible to experimentally implement our method with readily available equipment and even conservative estimates of physical parameters.

Exact Local Correlations and Full Counting Statistics for Arbitrary States of the One-Dimensional Interacting Bose Gas

Science.gov (United States)

Bastianello, Alvise; Piroli, Lorenzo; Calabrese, Pasquale

2018-05-01

We derive exact analytic expressions for the n -body local correlations in the one-dimensional Bose gas with contact repulsive interactions (Lieb-Liniger model) in the thermodynamic limit. Our results are valid for arbitrary states of the model, including ground and thermal states, stationary states after a quantum quench, and nonequilibrium steady states arising in transport settings. Calculations for these states are explicitly presented and physical consequences are critically discussed. We also show that the n -body local correlations are directly related to the full counting statistics for the particle-number fluctuations in a short interval, for which we provide an explicit analytic result.

Scalable Nearest Neighbor Algorithms for High Dimensional Data.

Science.gov (United States)

Muja, Marius; Lowe, David G

2014-11-01

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

The role of three-dimensional high-definition laparoscopic surgery for gynaecology.

Science.gov (United States)

Usta, Taner A; Gundogdu, Elif C

2015-08-01

This article reviews the potential benefits and disadvantages of new three-dimensional (3D) high-definition laparoscopic surgery for gynaecology. With the new-generation 3D high-definition laparoscopic vision systems (LVSs), operation time and learning period are reduced and procedural error margin is decreased. New-generation 3D high-definition LVSs enable to reduce operation time both for novice and experienced surgeons. Headache, eye fatigue or nausea reported with first-generation systems are not different than two-dimensional (2D) LVSs. The system's being more expensive, having the obligation to wear glasses, big and heavy camera probe in some of the devices are accounted for negative aspects of the system that need to be improved. Depth loss in tissues in 2D LVSs and associated adverse events can be eliminated with 3D high-definition LVSs. By virtue of faster learning curve, shorter operation time, reduced error margin and lack of side-effects reported by surgeons with first-generation systems, 3D LVSs seem to be a strong competition to classical laparoscopic imaging systems. Thanks to technological advancements, using lighter and smaller cameras and monitors without glasses is in the near future.

A New Ensemble Method with Feature Space Partitioning for High-Dimensional Data Classification

Directory of Open Access Journals (Sweden)

Yongjun Piao

2015-01-01

Full Text Available Ensemble data mining methods, also known as classifier combination, are often used to improve the performance of classification. Various classifier combination methods such as bagging, boosting, and random forest have been devised and have received considerable attention in the past. However, data dimensionality increases rapidly day by day. Such a trend poses various challenges as these methods are not suitable to directly apply to high-dimensional datasets. In this paper, we propose an ensemble method for classification of high-dimensional data, with each classifier constructed from a different set of features determined by partitioning of redundant features. In our method, the redundancy of features is considered to divide the original feature space. Then, each generated feature subset is trained by a support vector machine, and the results of each classifier are combined by majority voting. The efficiency and effectiveness of our method are demonstrated through comparisons with other ensemble techniques, and the results show that our method outperforms other methods.

High dimensional biological data retrieval optimization with NoSQL technology

Science.gov (United States)

2014-01-01

Background High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. Results In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. Conclusions The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data

High dimensional biological data retrieval optimization with NoSQL technology.

Science.gov (United States)

Wang, Shicai; Pandis, Ioannis; Wu, Chao; He, Sijin; Johnson, David; Emam, Ibrahim; Guitton, Florian; Guo, Yike

2014-01-01

High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating

Low-lying Photoexcited States of a One-Dimensional Ionic Extended Hubbard Model

Science.gov (United States)

Yokoi, Kota; Maeshima, Nobuya; Hino, Ken-ichi

2017-10-01

We investigate the properties of low-lying photoexcited states of a one-dimensional (1D) ionic extended Hubbard model at half-filling. Numerical analysis by using the full and Lanczos diagonalization methods shows that, in the ionic phase, there exist low-lying photoexcited states below the charge transfer gap. As a result of comparison with numerical data for the 1D antiferromagnetic (AF) Heisenberg model, it was found that, for a small alternating potential Δ, these low-lying photoexcited states are spin excitations, which is consistent with a previous analytical study [Katsura et al., link ext-link-type="uri" xlink:href="https://doi.org/10.1103/PhysRevLett.103.177402" xlink:type="simple">Phys. Rev. Lett. 103, 177402 (2009)link>]. As Δ increases, the spectral intensity of the 1D ionic extended Hubbard model rapidly deviates from that of the 1D AF Heisenberg model and it is clarified that this deviation is due to the neutral-ionic domain wall, an elementary excitation near the neutral-ionic transition point.

A new approach for assimilation of two-dimensional radar precipitation in a high resolution NWP model

Science.gov (United States)

Korsholm, Ulrik; Petersen, Claus; Hansen Sass, Bent; Woetman, Niels; Getreuer Jensen, David; Olsen, Bjarke Tobias; GIll, Rasphal; Vedel, Henrik

2014-05-01

The DMI nowcasting system has been running in a pre-operational state for the past year. The system consists of hourly simulations with the High Resolution Limited Area weather model combined with surface and three-dimensional variational assimilation at each restart and nudging of satellite cloud products and radar precipitation. Nudging of a two-dimensional radar reflectivity CAPPI product is achieved using a new method where low level horizontal divergence is nudged towards pseudo observations. Pseudo observations are calculated based on an assumed relation between divergence and precipitation rate and the strength of the nudging is proportional to the offset between observed and modelled precipitation leading to increased moisture convergence below cloud base if there is an under-production of precipitation relative to the CAPPI product. If the model over-predicts precipitation, the low level moisture source is reduced, and in-cloud moisture is nudged towards environmental values. In this talk results will be discussed based on calculation of the fractions skill score in cases with heavy precipitation over Denmark. Furthermore, results from simulations combining reflectivity nudging and extrapolation of reflectivity will be shown. Results indicate that the new method leads to fast adjustment of the dynamical state of the model to facilitate precipitation release when the model precipitation intensity is too low. Removal of precipitation is also shown to be of importance and strong improvements were found in the position of the precipitation systems. Bias is reduced for low and extreme precipitation rates.

The additive hazards model with high-dimensional regressors

DEFF Research Database (Denmark)

Martinussen, Torben; Scheike, Thomas

2009-01-01

This paper considers estimation and prediction in the Aalen additive hazards model in the case where the covariate vector is high-dimensional such as gene expression measurements. Some form of dimension reduction of the covariate space is needed to obtain useful statistical analyses. We study...... model. A standard PLS algorithm can also be constructed, but it turns out that the resulting predictor can only be related to the original covariates via time-dependent coefficients. The methods are applied to a breast cancer data set with gene expression recordings and to the well known primary biliary...

Antibound states for a class of one-dimensional Schroedinger Operators

Energy Technology Data Exchange (ETDEWEB)

Angeletti, A [Camerino Univ. (Italy). Ist. di Matematica

1980-11-01

Let delta(x) be the Dirac's delta, q(x) element of L/sup 1/(R) L/sup 2/(R) be a real valued function, and lambda, ..mu.. element of R; we will consider the following class of one-dimensional formal Schroedinger operators on L/sup 2/(R) H(lambda,..mu..) = - (d/sup 2//dx/sup 2/) + lambdadelta(x) + ..mu..q(x). It is known that to the formal operator H(lambda, ..mu..) may be associated a selfadjoint operator H(lambda, ..mu..) on L/sup 2/(R). If q is of finite range, for lambda < 0 and /..mu../ is small enough, we prove that H(lambda,..mu..) has an antibound state; that is the resolvent of H(lambda,..mu..) has a pole on the negative real axis on the second Riemann sheet.

Coupling effect of topological states and Chern insulators in two-dimensional triangular lattices

Science.gov (United States)

Zhang, Jiayong; Zhao, Bao; Xue, Yang; Zhou, Tong; Yang, Zhongqin

2018-03-01

We investigate topological states of two-dimensional (2D) triangular lattices with multiorbitals. Tight-binding model calculations of a 2D triangular lattice based on px and py orbitals exhibit very interesting doubly degenerate energy points at different positions (Γ and K /K' ) in momentum space, with quadratic non-Dirac and linear Dirac band dispersions, respectively. Counterintuitively, the system shows a global topologically trivial rather than nontrivial state with consideration of spin-orbit coupling due to the "destructive interference effect" between the topological states at the Γ and K /K' points. The topologically nontrivial state can emerge by introducing another set of triangular lattices to the system (bitriangular lattices) due to the breakdown of the interference effect. With first-principles calculations, we predict an intrinsic Chern insulating behavior (quantum anomalous Hall effect) in a family of the 2D triangular lattice metal-organic framework of Co(C21N3H15) (TPyB-Co) from this scheme. Our results provide a different path and theoretical guidance for the search for and design of new 2D topological quantum materials.

EPS-LASSO: Test for High-Dimensional Regression Under Extreme Phenotype Sampling of Continuous Traits.

Science.gov (United States)

Xu, Chao; Fang, Jian; Shen, Hui; Wang, Yu-Ping; Deng, Hong-Wen

2018-01-25

Extreme phenotype sampling (EPS) is a broadly-used design to identify candidate genetic factors contributing to the variation of quantitative traits. By enriching the signals in extreme phenotypic samples, EPS can boost the association power compared to random sampling. Most existing statistical methods for EPS examine the genetic factors individually, despite many quantitative traits have multiple genetic factors underlying their variation. It is desirable to model the joint effects of genetic factors, which may increase the power and identify novel quantitative trait loci under EPS. The joint analysis of genetic data in high-dimensional situations requires specialized techniques, e.g., the least absolute shrinkage and selection operator (LASSO). Although there are extensive research and application related to LASSO, the statistical inference and testing for the sparse model under EPS remain unknown. We propose a novel sparse model (EPS-LASSO) with hypothesis test for high-dimensional regression under EPS based on a decorrelated score function. The comprehensive simulation shows EPS-LASSO outperforms existing methods with stable type I error and FDR control. EPS-LASSO can provide a consistent power for both low- and high-dimensional situations compared with the other methods dealing with high-dimensional situations. The power of EPS-LASSO is close to other low-dimensional methods when the causal effect sizes are small and is superior when the effects are large. Applying EPS-LASSO to a transcriptome-wide gene expression study for obesity reveals 10 significant body mass index associated genes. Our results indicate that EPS-LASSO is an effective method for EPS data analysis, which can account for correlated predictors. The source code is available at https://github.com/xu1912/EPSLASSO. hdeng2@tulane.edu. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please

[Extraction of buildings three-dimensional information from high-resolution satellite imagery based on Barista software].

Science.gov (United States)

Zhang, Pei-feng; Hu, Yuan-man; He, Hong-shi

2010-05-01

The demand for accurate and up-to-date spatial information of urban buildings is becoming more and more important for urban planning, environmental protection, and other vocations. Today's commercial high-resolution satellite imagery offers the potential to extract the three-dimensional information of urban buildings. This paper extracted the three-dimensional information of urban buildings from QuickBird imagery, and validated the precision of the extraction based on Barista software. It was shown that the extraction of three-dimensional information of the buildings from high-resolution satellite imagery based on Barista software had the advantages of low professional level demand, powerful universality, simple operation, and high precision. One pixel level of point positioning and height determination accuracy could be achieved if the digital elevation model (DEM) and sensor orientation model had higher precision and the off-Nadir View Angle was relatively perfect.

Direct numerical simulation of steady state, three dimensional, laminar flow around a wall mounted cube

Science.gov (United States)

Liakos, Anastasios; Malamataris, Nikolaos

2014-11-01

The topology and evolution of flow around a surface mounted cubical object in three dimensional channel flow is examined for low to moderate Reynolds numbers. Direct numerical simulations were performed via a home made parallel finite element code. The computational domain has been designed according to actual laboratory experimental conditions. Analysis of the results is performed using the three dimensional theory of separation. Our findings indicate that a tornado-like vortex by the side of the cube is present for all Reynolds numbers for which flow was simulated. A horse-shoe vortex upstream from the cube was formed at Reynolds number approximately 1266. Pressure distributions are shown along with three dimensional images of the tornado-like vortex and the horseshoe vortex at selected Reynolds numbers. Finally, and in accordance to previous work, our results indicate that the upper limit for the Reynolds number for which steady state results are physically realizable is roughly 2000. Financial support of author NM from the Office of Naval Research Global (ONRG-VSP, N62909-13-1-V016) is acknowledged.

High-resolution three-dimensional mapping of semiconductor dopant potentials

DEFF Research Database (Denmark)

Twitchett, AC; Yates, TJV; Newcomb, SB

2007-01-01

Semiconductor device structures are becoming increasingly three-dimensional at the nanometer scale. A key issue that must be addressed to enable future device development is the three-dimensional mapping of dopant distributions, ideally under "working conditions". Here we demonstrate how a combin......Semiconductor device structures are becoming increasingly three-dimensional at the nanometer scale. A key issue that must be addressed to enable future device development is the three-dimensional mapping of dopant distributions, ideally under "working conditions". Here we demonstrate how...... a combination of electron holography and electron tomography can be used to determine quantitatively the three-dimensional electrostatic potential in an electrically biased semiconductor device with nanometer spatial resolution....

Self-organization phenomena and decaying self-similar state in two-dimensional incompressible viscous fluids

International Nuclear Information System (INIS)

Kondoh, Yoshiomi; Serizawa, Shunsuke; Nakano, Akihiro; Takahashi, Toshiki; Van Dam, James W.

2004-01-01

The final self-similar state of decaying two-dimensional (2D) turbulence in 2D incompressible viscous flow is analytically and numerically investigated for the case with periodic boundaries. It is proved by theoretical analysis and simulations that the sinh-Poisson state cω=-sinh(βψ) is not realized in the dynamical system of interest. It is shown by an eigenfunction spectrum analysis that a sufficient explanation for the self-organization to the decaying self-similar state is the faster energy decay of higher eigenmodes and the energy accumulation to the lowest eigenmode for given boundary conditions due to simultaneous normal and inverse cascading by nonlinear mode couplings. The theoretical prediction is demonstrated to be correct by simulations leading to the lowest eigenmode of {(1,0)+(0,1)} of the dissipative operator for the periodic boundaries. It is also clarified that an important process during nonlinear self-organization is an interchange between the dominant operators, which leads to the final decaying self-similar state

Three-dimensionality of field-induced magnetism in a high-temperature superconductor

DEFF Research Database (Denmark)

Lake, B.; Lefmann, K.; Christensen, N.B.

2005-01-01

Many physical properties of high-temperature superconductors are two-dimensional phenomena derived from their square-planar CuO(2) building blocks. This is especially true of the magnetism from the copper ions. As mobile charge carriers enter the CuO(2) layers, the antiferromagnetism of the parent...

Pricing and hedging high-dimensional American options : an irregular grid approach

NARCIS (Netherlands)

Berridge, S.; Schumacher, H.

2002-01-01

We propose and test a new method for pricing American options in a high dimensional setting. The method is centred around the approximation of the associated variational inequality on an irregular grid. We approximate the partial differential operator on this grid by appealing to the SDE

A Feature Subset Selection Method Based On High-Dimensional Mutual Information

Directory of Open Access Journals (Sweden)

Chee Keong Kwoh

2011-04-01

Full Text Available Feature selection is an important step in building accurate classifiers and provides better understanding of the data sets. In this paper, we propose a feature subset selection method based on high-dimensional mutual information. We also propose to use the entropy of the class attribute as a criterion to determine the appropriate subset of features when building classifiers. We prove that if the mutual information between a feature set X and the class attribute Y equals to the entropy of Y , then X is a Markov Blanket of Y . We show that in some cases, it is infeasible to approximate the high-dimensional mutual information with algebraic combinations of pairwise mutual information in any forms. In addition, the exhaustive searches of all combinations of features are prerequisite for finding the optimal feature subsets for classifying these kinds of data sets. We show that our approach outperforms existing filter feature subset selection methods for most of the 24 selected benchmark data sets.

Metallic and highly conducting two-dimensional atomic arrays of sulfur enabled by molybdenum disulfide nanotemplate

Science.gov (United States)

Zhu, Shuze; Geng, Xiumei; Han, Yang; Benamara, Mourad; Chen, Liao; Li, Jingxiao; Bilgin, Ismail; Zhu, Hongli

2017-10-01

Element sulfur in nature is an insulating solid. While it has been tested that one-dimensional sulfur chain is metallic and conducting, the investigation on two-dimensional sulfur remains elusive. We report that molybdenum disulfide layers are able to serve as the nanotemplate to facilitate the formation of two-dimensional sulfur. Density functional theory calculations suggest that confined in-between layers of molybdenum disulfide, sulfur atoms are able to form two-dimensional triangular arrays that are highly metallic. As a result, these arrays contribute to the high conductivity and metallic phase of the hybrid structures of molybdenum disulfide layers and two-dimensional sulfur arrays. The experimentally measured conductivity of such hybrid structures reaches up to 223 S/m. Multiple experimental results, including X-ray photoelectron spectroscopy (XPS), transition electron microscope (TEM), selected area electron diffraction (SAED), agree with the computational insights. Due to the excellent conductivity, the current density is linearly proportional to the scan rate until 30,000 mV s-1 without the attendance of conductive additives. Using such hybrid structures as electrode, the two-electrode supercapacitor cells yield a power density of 106 Wh kg-1 and energy density 47.5 Wh kg-1 in ionic liquid electrolytes. Our findings offer new insights into using two-dimensional materials and their Van der Waals heterostructures as nanotemplates to pattern foreign atoms for unprecedented material properties.

An adaptive ANOVA-based PCKF for high-dimensional nonlinear inverse modeling

Science.gov (United States)

Li, Weixuan; Lin, Guang; Zhang, Dongxiao

2014-02-01

The probabilistic collocation-based Kalman filter (PCKF) is a recently developed approach for solving inverse problems. It resembles the ensemble Kalman filter (EnKF) in every aspect-except that it represents and propagates model uncertainty by polynomial chaos expansion (PCE) instead of an ensemble of model realizations. Previous studies have shown PCKF is a more efficient alternative to EnKF for many data assimilation problems. However, the accuracy and efficiency of PCKF depends on an appropriate truncation of the PCE series. Having more polynomial chaos basis functions in the expansion helps to capture uncertainty more accurately but increases computational cost. Selection of basis functions is particularly important for high-dimensional stochastic problems because the number of polynomial chaos basis functions required to represent model uncertainty grows dramatically as the number of input parameters (random dimensions) increases. In classic PCKF algorithms, the PCE basis functions are pre-set based on users' experience. Also, for sequential data assimilation problems, the basis functions kept in PCE expression remain unchanged in different Kalman filter loops, which could limit the accuracy and computational efficiency of classic PCKF algorithms. To address this issue, we present a new algorithm that adaptively selects PCE basis functions for different problems and automatically adjusts the number of basis functions in different Kalman filter loops. The algorithm is based on adaptive functional ANOVA (analysis of variance) decomposition, which approximates a high-dimensional function with the summation of a set of low-dimensional functions. Thus, instead of expanding the original model into PCE, we implement the PCE expansion on these low-dimensional functions, which is much less costly. We also propose a new adaptive criterion for ANOVA that is more suited for solving inverse problems. The new algorithm was tested with different examples and demonstrated

CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets [version 1; referees: 2 approved

Directory of Open Access Journals (Sweden)

Malgorzata Nowicka

2017-05-01

Full Text Available High dimensional mass and flow cytometry (HDCyto experiments have become a method of choice for high throughput interrogation and characterization of cell populations.Here, we present an R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signaling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g. multi-dimensional scaling plots, reporting of clustering results (dimensionality reduction, heatmaps with dendrograms and differential analyses (e.g. plots of aggregated signals.

Workshop on low-dimensional quantum field theory and its applications

International Nuclear Information System (INIS)

Yamamoto, Hisashi

1990-02-01

The workshop on 'Low-Dimensional Quantum Field Theory and its Applications' was held at INS on December 18 - 20, 1989 with about seventy participants. Some pedagogical reviews and the latest results were delivered on the recent topics related to both solid-state and particle physics. Among them are quantum Hall effect, high T c superconductivity and related topics in low-dimensional quantum field theory. Many active discussions were made on these issues. (J.P.N.)

Three-dimensional simulations of low foot and high foot implosion experiments on the National Ignition Facility

International Nuclear Information System (INIS)

Clark, D. S.; Weber, C. R.; Milovich, J. L.; Salmonson, J. D.; Kritcher, A. L.; Haan, S. W.; Hammel, B. A.; Hinkel, D. E.; Hurricane, O. A.; Jones, O. S.; Marinak, M. M.; Patel, P. K.; Robey, H. F.; Sepke, S. M.; Edwards, M. J.

2016-01-01

In order to achieve the several hundred Gbar stagnation pressures necessary for inertial confinement fusion ignition, implosion experiments on the National Ignition Facility (NIF) [E. I. Moses et al., Phys. Plasmas 16, 041006 (2009)] require the compression of deuterium-tritium fuel layers by a convergence ratio as high as forty. Such high convergence implosions are subject to degradation by a range of perturbations, including the growth of small-scale defects due to hydrodynamic instabilities, as well as longer scale modulations due to radiation flux asymmetries in the enclosing hohlraum. Due to the broad range of scales involved, and also the genuinely three-dimensional (3D) character of the flow, accurately modeling NIF implosions remains at the edge of current simulation capabilities. This paper describes the current state of progress of 3D capsule-only simulations of NIF implosions aimed at accurately describing the performance of specific NIF experiments. Current simulations include the effects of hohlraum radiation asymmetries, capsule surface defects, the capsule support tent and fill tube, and use a grid resolution shown to be converged in companion two-dimensional simulations. The results of detailed simulations of low foot implosions from the National Ignition Campaign are contrasted against results for more recent high foot implosions. While the simulations suggest that low foot performance was dominated by ablation front instability growth, especially the defect seeded by the capsule support tent, high foot implosions appear to be dominated by hohlraum flux asymmetries, although the support tent still plays a significant role. For both implosion types, the simulations show reasonable, though not perfect, agreement with the data and suggest that a reliable predictive capability is developing to guide future implosions toward ignition.

Three-dimensional simulations of low foot and high foot implosion experiments on the National Ignition Facility

Energy Technology Data Exchange (ETDEWEB)

Clark, D. S.; Weber, C. R.; Milovich, J. L.; Salmonson, J. D.; Kritcher, A. L.; Haan, S. W.; Hammel, B. A.; Hinkel, D. E.; Hurricane, O. A.; Jones, O. S.; Marinak, M. M.; Patel, P. K.; Robey, H. F.; Sepke, S. M.; Edwards, M. J. [Lawrence Livermore National Laboratory, P.O. Box 808, Livermore, California 94550 (United States)

2016-05-15

In order to achieve the several hundred Gbar stagnation pressures necessary for inertial confinement fusion ignition, implosion experiments on the National Ignition Facility (NIF) [E. I. Moses et al., Phys. Plasmas 16, 041006 (2009)] require the compression of deuterium-tritium fuel layers by a convergence ratio as high as forty. Such high convergence implosions are subject to degradation by a range of perturbations, including the growth of small-scale defects due to hydrodynamic instabilities, as well as longer scale modulations due to radiation flux asymmetries in the enclosing hohlraum. Due to the broad range of scales involved, and also the genuinely three-dimensional (3D) character of the flow, accurately modeling NIF implosions remains at the edge of current simulation capabilities. This paper describes the current state of progress of 3D capsule-only simulations of NIF implosions aimed at accurately describing the performance of specific NIF experiments. Current simulations include the effects of hohlraum radiation asymmetries, capsule surface defects, the capsule support tent and fill tube, and use a grid resolution shown to be converged in companion two-dimensional simulations. The results of detailed simulations of low foot implosions from the National Ignition Campaign are contrasted against results for more recent high foot implosions. While the simulations suggest that low foot performance was dominated by ablation front instability growth, especially the defect seeded by the capsule support tent, high foot implosions appear to be dominated by hohlraum flux asymmetries, although the support tent still plays a significant role. For both implosion types, the simulations show reasonable, though not perfect, agreement with the data and suggest that a reliable predictive capability is developing to guide future implosions toward ignition.

Monte Carlo simulation of the three-state vector Potts model on a three-dimensional random lattice

International Nuclear Information System (INIS)

Jianbo Zhang; Heping Ying

1991-09-01

We have performed a numerical simulation of the three-state vector Potts model on a three-dimensional random lattice. The averages of energy density, magnetization, specific heat and susceptibility of the system in the N 3 (N=8,10,12) lattices were calculated. The results show that a first order nature of the Z(3) symmetry breaking transition appears, as characterized by a thermal hysterisis in the energy density as well as an abrupt drop of magnetization being sharper and discontinuous with increasing of volume in the cross-over region. The results obtained on the random lattice were consistent with those obtained on the three-dimensional cubic lattice. (author). 12 refs, 4 figs

Low-dimensional molecular metals

CERN Document Server

Toyota, Naoki; Muller, Jens

2007-01-01

Assimilating research in the field of low-dimensional metals, this monograph provides an overview of the status of research on quasi-one- and two-dimensional molecular metals, describing normal-state properties, magnetic field effects, superconductivity, and the phenomena of interacting p and d electrons.

Reduced order surrogate modelling (ROSM) of high dimensional deterministic simulations

Science.gov (United States)

Mitry, Mina

Often, computationally expensive engineering simulations can prohibit the engineering design process. As a result, designers may turn to a less computationally demanding approximate, or surrogate, model to facilitate their design process. However, owing to the the curse of dimensionality, classical surrogate models become too computationally expensive for high dimensional data. To address this limitation of classical methods, we develop linear and non-linear Reduced Order Surrogate Modelling (ROSM) techniques. Two algorithms are presented, which are based on a combination of linear/kernel principal component analysis and radial basis functions. These algorithms are applied to subsonic and transonic aerodynamic data, as well as a model for a chemical spill in a channel. The results of this thesis show that ROSM can provide a significant computational benefit over classical surrogate modelling, sometimes at the expense of a minor loss in accuracy.

Efficient and accurate nearest neighbor and closest pair search in high-dimensional space

KAUST Repository

Tao, Yufei

2010-07-01

Nearest Neighbor (NN) search in high-dimensional space is an important problem in many applications. From the database perspective, a good solution needs to have two properties: (i) it can be easily incorporated in a relational database, and (ii) its query cost should increase sublinearly with the dataset size, regardless of the data and query distributions. Locality-Sensitive Hashing (LSH) is a well-known methodology fulfilling both requirements, but its current implementations either incur expensive space and query cost, or abandon its theoretical guarantee on the quality of query results. Motivated by this, we improve LSH by proposing an access method called the Locality-Sensitive B-tree (LSB-tree) to enable fast, accurate, high-dimensional NN search in relational databases. The combination of several LSB-trees forms a LSB-forest that has strong quality guarantees, but improves dramatically the efficiency of the previous LSH implementation having the same guarantees. In practice, the LSB-tree itself is also an effective index which consumes linear space, supports efficient updates, and provides accurate query results. In our experiments, the LSB-tree was faster than: (i) iDistance (a famous technique for exact NN search) by two orders ofmagnitude, and (ii) MedRank (a recent approximate method with nontrivial quality guarantees) by one order of magnitude, and meanwhile returned much better results. As a second step, we extend our LSB technique to solve another classic problem, called Closest Pair (CP) search, in high-dimensional space. The long-term challenge for this problem has been to achieve subquadratic running time at very high dimensionalities, which fails most of the existing solutions. We show that, using a LSB-forest, CP search can be accomplished in (worst-case) time significantly lower than the quadratic complexity, yet still ensuring very good quality. In practice, accurate answers can be found using just two LSB-trees, thus giving a substantial

Morphological control of three-dimensional carbon nanotube anode for high-capacity lithium-ion battery

Science.gov (United States)

Kang, Chiwon; Lee, Hoo-Jeong

2018-05-01

In this paper, we report the results of modulating the processing conditions (mainly, temperature) of a two-step method consisting of sputtering deposition of a Ni catalytic layer and chemical vapor deposition (CVD) of carbon nanotubes (CNTs) on a three-dimensional (3D)-structured Cu mesh to control the morphology of CNTs for advanced Li-ion battery (LIB) applications. We disclosed that CNT growth at a low temperature (700 °C) produced small-diameter CNTs (CNT_S) with an average diameter of ∼20 nm, while that at a high temperature (750 °C) produced large-diameter CNTs (CNT_L) with an average diameter of 200–300 nm. The high-resolution transmission electron microscopy (HR-TEM) and Raman analyses manifested poorly crystalline CNTs for both samples. CNTS showed a specific capacity of 476 mAh g‑1, which is ∼176% superior to that of CNTL (271 mAh g‑1) and ∼128% higher than the theoretical capacity of the state-of-the-art graphites and recently reported nanostructured carbon-based anode materials.

Sufficient Controllability Condition for Affine Systems with Two-Dimensional Control and Two-Dimensional Zero Dynamics

Directory of Open Access Journals (Sweden)

D. A. Fetisov

2015-01-01

Full Text Available The controllability conditions are well known if we speak about linear stationary systems: a linear stationary system is controllable if and only if the dimension of the state vector is equal to the rank of the controllability matrix. The concept of the controllability matrix is extended to affine systems, but relations between affine systems controllability and properties of this matrix are more complicated. Various controllability conditions are set for affine systems, but they deal as usual either with systems of some special form or with controllability in some small neighborhood of the concerned point. An affine system is known to be controllable if the system is equivalent to a system of a canonical form, which is defined and regular in the whole space of states. In this case, the system is said to be feedback linearizable in the space of states. However there are examples, which illustrate that a system can be controllable even if it is not feedback linearizable in any open subset in the space of states. In this article we deal with such systems.Affine systems with two-dimensional control are considered. The system in question is assumed to be equivalent to a system of a quasicanonical form with two-dimensional zero dynamics which is defined and regular in the whole space of states. Therefore the controllability of the original system is equivalent to the controllability of the received system of a quasicanonical form. In this article the sufficient condition for an available solution of the terminal problem is proven for systems of a quasicanonical form with two-dimensional control and two-dimensional zero dynamics. The condition is valid in the case of an arbitrary time interval and arbitrary initial and finite states of the system. Therefore the controllability condition is set for systems of a quasicanonical form with two-dimensional control and two-dimensional zero dynamics. An example is given which illustrates how the proved

Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence

Directory of Open Access Journals (Sweden)

Thenmozhi Srinivasan

2015-01-01

Full Text Available Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM, with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets.

Advances in high-resolution imaging--techniques for three-dimensional imaging of cellular structures.

Science.gov (United States)

Lidke, Diane S; Lidke, Keith A

2012-06-01

A fundamental goal in biology is to determine how cellular organization is coupled to function. To achieve this goal, a better understanding of organelle composition and structure is needed. Although visualization of cellular organelles using fluorescence or electron microscopy (EM) has become a common tool for the cell biologist, recent advances are providing a clearer picture of the cell than ever before. In particular, advanced light-microscopy techniques are achieving resolutions below the diffraction limit and EM tomography provides high-resolution three-dimensional (3D) images of cellular structures. The ability to perform both fluorescence and electron microscopy on the same sample (correlative light and electron microscopy, CLEM) makes it possible to identify where a fluorescently labeled protein is located with respect to organelle structures visualized by EM. Here, we review the current state of the art in 3D biological imaging techniques with a focus on recent advances in electron microscopy and fluorescence super-resolution techniques.

Dynamic conductivity modified by impurity resonant states in doping three-dimensional Dirac semimetals

Science.gov (United States)

Li, Shuai; Wang, Chen; Zheng, Shi-Han; Wang, Rui-Qiang; Li, Jun; Yang, Mou

2018-04-01

The impurity effect is studied in three-dimensional Dirac semimetals in the framework of a T-matrix method to consider the multiple scattering events of Dirac electrons off impurities. It has been found that a strong impurity potential can significantly restructure the energy dispersion and the density of states of Dirac electrons. An impurity-induced resonant state emerges and significantly modifies the pristine optical response. It is shown that the impurity state disturbs the common longitudinal optical conductivity by creating either an optical conductivity peak or double absorption jumps, depending on the relative position of the impurity band and the Fermi level. More importantly, these conductivity features appear in the forbidden region between the Drude and interband transition, completely or partially filling the Pauli block region of optical response. The underlying physics is that the appearance of resonance states as well as the broadening of the bands leads to a more complicated selection rule for the optical transitions, making it possible to excite new electron-hole pairs in the forbidden region. These features in optical conductivity provide valuable information to understand the impurity behaviors in 3D Dirac materials.

An overview of techniques for linking high-dimensional molecular data to time-to-event endpoints by risk prediction models.

Science.gov (United States)

Binder, Harald; Porzelius, Christine; Schumacher, Martin

2011-03-01

Analysis of molecular data promises identification of biomarkers for improving prognostic models, thus potentially enabling better patient management. For identifying such biomarkers, risk prediction models can be employed that link high-dimensional molecular covariate data to a clinical endpoint. In low-dimensional settings, a multitude of statistical techniques already exists for building such models, e.g. allowing for variable selection or for quantifying the added value of a new biomarker. We provide an overview of techniques for regularized estimation that transfer this toward high-dimensional settings, with a focus on models for time-to-event endpoints. Techniques for incorporating specific covariate structure are discussed, as well as techniques for dealing with more complex endpoints. Employing gene expression data from patients with diffuse large B-cell lymphoma, some typical modeling issues from low-dimensional settings are illustrated in a high-dimensional application. First, the performance of classical stepwise regression is compared to stage-wise regression, as implemented by a component-wise likelihood-based boosting approach. A second issues arises, when artificially transforming the response into a binary variable. The effects of the resulting loss of efficiency and potential bias in a high-dimensional setting are illustrated, and a link to competing risks models is provided. Finally, we discuss conditions for adequately quantifying the added value of high-dimensional gene expression measurements, both at the stage of model fitting and when performing evaluation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Measurement of the quantum capacitance from two-dimensional surface state of a topological insulator at room temperature

Energy Technology Data Exchange (ETDEWEB)

Choi, Hyunwoo, E-mail: chw0089@gmail.com [Department of Electrical and Computer Engineering, University of Seoul, Seoul 02504 (Korea, Republic of); Kim, Tae Geun, E-mail: tgkim1@korea.ac.kr [School of Electrical Engineering, Korea University, Seoul 02841 (Korea, Republic of); Shin, Changhwan, E-mail: cshin@uos.ac.kr [Department of Electrical and Computer Engineering, University of Seoul, Seoul 02504 (Korea, Republic of)

2017-06-15

Highlights: • The quantum capacitance in topological insulator (TI) at room temperature is directly revealed. • The physical origin of quantum capacitance, the two dimensional surface state of TI, is experimentally validated. • Theoretically calculated results of ideal quantum capacitance can well predict the experimental data. - Abstract: A topological insulator (TI) is a new kind of material that exhibits unique electronic properties owing to its topological surface state (TSS). Previous studies focused on the transport properties of the TSS, since it can be used as the active channel layer in metal-oxide-semiconductor field-effect transistors (MOSFETs). However, a TI with a negative quantum capacitance (QC) effect can be used in the gate stack of MOSFETs, thereby facilitating the creation of ultra-low power electronics. Therefore, it is important to study the physics behind the QC in TIs in the absence of any external magnetic field, at room temperature. We fabricated a simple capacitor structure using a TI (TI-capacitor: Au-TI-SiO{sub 2}-Si), which shows clear evidence of QC at room temperature. In the capacitance-voltage (C-V) measurement, the total capacitance of the TI-capacitor increases in the accumulation regime, since QC is the dominant capacitive component in the series capacitor model (i.e., C{sub T}{sup −1} = C{sub Q}{sup −1} + C{sub SiO2}{sup −1}). Based on the QC model of the two-dimensional electron systems, we quantitatively calculated the QC, and observed that the simulated C-V curve theoretically supports the conclusion that the QC of the TI-capacitor is originated from electron–electron interaction in the two-dimensional surface state of the TI.

1D to 3D dimensional crossover in the superconducting transition of the quasi-one-dimensional carbide superconductor Sc3CoC4.

Science.gov (United States)

He, Mingquan; Wong, Chi Ho; Shi, Dian; Tse, Pok Lam; Scheidt, Ernst-Wilhelm; Eickerling, Georg; Scherer, Wolfgang; Sheng, Ping; Lortz, Rolf

2015-02-25

The transition metal carbide superconductor Sc(3)CoC(4) may represent a new benchmark system of quasi-one-dimensional (quasi-1D) superconducting behavior. We investigate the superconducting transition of a high-quality single crystalline sample by electrical transport experiments. Our data show that the superconductor goes through a complex dimensional crossover below the onset T(c) of 4.5 K. First, a quasi-1D fluctuating superconducting state with finite resistance forms in the [CoC(4)](∞) ribbons which are embedded in a Sc matrix in this material. At lower temperature, the transversal Josephson or proximity coupling of neighboring ribbons establishes a 3D bulk superconducting state. This dimensional crossover is very similar to Tl(2)Mo(6)Se(6), which for a long time has been regarded as the most appropriate model system of a quasi-1D superconductor. Sc(3)CoC(4) appears to be even more in the 1D limit than Tl(2)Mo(6)Se(6).

DataHigh: Graphical user interface for visualizing and interacting with high-dimensional neural activity

OpenAIRE

Cowley, Benjamin R.; Kaufman, Matthew T.; Churchland, Mark M.; Ryu, Stephen I.; Shenoy, Krishna V.; Yu, Byron M.

2012-01-01

The activity of tens to hundreds of neurons can be succinctly summarized by a smaller number of latent variables extracted using dimensionality reduction methods. These latent variables define a reduced-dimensional space in which we can study how population activity varies over time, across trials, and across experimental conditions. Ideally, we would like to visualize the population activity directly in the reduced-dimensional space, whose optimal dimensionality (as determined from the data)...

Collective oscillations of twin boundaries in high temperature superconductors as an acoustic analogue of two-dimensional plasmons

International Nuclear Information System (INIS)

Kosevich, Yu.A.; Syrkin, E.S.

1990-06-01

Low frequency collective oscillations in a superlattice consisting of alternating highly anisotropic layers are considered. Such superstructure may be formed in the ferroelastic near the structural phase transition by alternation of twins. For the surface waves, propagating along the layers, the conditions and the range of existence of those with the dispersion law ω∼K 1/2 , characteristics for two-dimensional plasmons, have been analyzed for a solid-state system with consideration for elastic anisotropy and retardation of acoustic waves. Such excitations ('dyadons') were used in an attempt to explain the anomalies of low temperature thermodynamic and kinetic characteristics of high-T c superconductors. We have shown that the similarity of the densities of the matching phases and the retardation of elastic waves in the crystal narrow the range of existence of dyadons, but high elastic anisotropy of the solid phases enlarges the range of existence of such excitations in solid-state systems. The example of possible crystalline geometry of the phase matching, for which there arise collective excitations of the type under consideration, is found. For transverse and longitudinal waves propagating across the layers, the existence is proved of low frequency acoustic branches separated by a wide gap from the nearest optical branches. (author). 18 refs

High-velocity two-phase flow two-dimensional modeling

International Nuclear Information System (INIS)

Mathes, R.; Alemany, A.; Thilbault, J.P.

1995-01-01

The two-phase flow in the nozzle of a LMMHD (liquid metal magnetohydrodynamic) converter has been studied numerically and experimentally. A two-dimensional model for two-phase flow has been developed including the viscous terms (dragging and turbulence) and the interfacial mass, momentum and energy transfer between the phases. The numerical results were obtained by a finite volume method based on the SIMPLE algorithm. They have been verified by an experimental facility using air-water as a simulation pair and a phase Doppler particle analyzer for velocity and droplet size measurement. The numerical simulation of a lithium-cesium high-temperature pair showed that a nearly homogeneous and isothermal expansion of the two phases is possible with small pressure losses and high kinetic efficiencies. In the throat region a careful profiling is necessary to reduce the inertial effects on the liquid velocity field

High-dimensional cluster analysis with the Masked EM Algorithm

Science.gov (United States)

Kadir, Shabnam N.; Goodman, Dan F. M.; Harris, Kenneth D.

2014-01-01

Cluster analysis faces two problems in high dimensions: first, the “curse of dimensionality” that can lead to overfitting and poor generalization performance; and second, the sheer time taken for conventional algorithms to process large amounts of high-dimensional data. We describe a solution to these problems, designed for the application of “spike sorting” for next-generation high channel-count neural probes. In this problem, only a small subset of features provide information about the cluster member-ship of any one data vector, but this informative feature subset is not the same for all data points, rendering classical feature selection ineffective. We introduce a “Masked EM” algorithm that allows accurate and time-efficient clustering of up to millions of points in thousands of dimensions. We demonstrate its applicability to synthetic data, and to real-world high-channel-count spike sorting data. PMID:25149694

Projective Synchronization of N-Dimensional Chaotic Fractional-Order Systems via Linear State Error Feedback Control

Directory of Open Access Journals (Sweden)

Baogui Xin

2012-01-01

Full Text Available Based on linear feedback control technique, a projective synchronization scheme of N-dimensional chaotic fractional-order systems is proposed, which consists of master and slave fractional-order financial systems coupled by linear state error variables. It is shown that the slave system can be projectively synchronized with the master system constructed by state transformation. Based on the stability theory of linear fractional order systems, a suitable controller for achieving synchronization is designed. The given scheme is applied to achieve projective synchronization of chaotic fractional-order financial systems. Numerical simulations are given to verify the effectiveness of the proposed projective synchronization scheme.

Dissecting high-dimensional phenotypes with bayesian sparse factor analysis of genetic covariance matrices.

Science.gov (United States)

Runcie, Daniel E; Mukherjee, Sayan

2013-07-01

Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection. For example, changes in gene expression can provide insight into developmental and physiological mechanisms that link genotype and phenotype. However, classical analytical techniques are poorly suited to quantitative genetic studies of gene expression where the number of traits assayed per individual can reach many thousand. Here, we derive a Bayesian genetic sparse factor model for estimating the genetic covariance matrix (G-matrix) of high-dimensional traits, such as gene expression, in a mixed-effects model. The key idea of our model is that we need consider only G-matrices that are biologically plausible. An organism's entire phenotype is the result of processes that are modular and have limited complexity. This implies that the G-matrix will be highly structured. In particular, we assume that a limited number of intermediate traits (or factors, e.g., variations in development or physiology) control the variation in the high-dimensional phenotype, and that each of these intermediate traits is sparse - affecting only a few observed traits. The advantages of this approach are twofold. First, sparse factors are interpretable and provide biological insight into mechanisms underlying the genetic architecture. Second, enforcing sparsity helps prevent sampling errors from swamping out the true signal in high-dimensional data. We demonstrate the advantages of our model on simulated data and in an analysis of a published Drosophila melanogaster gene expression data set.

TSAR: a program for automatic resonance assignment using 2D cross-sections of high dimensionality, high-resolution spectra

Energy Technology Data Exchange (ETDEWEB)

Zawadzka-Kazimierczuk, Anna; Kozminski, Wiktor [University of Warsaw, Faculty of Chemistry (Poland); Billeter, Martin, E-mail: martin.billeter@chem.gu.se [University of Gothenburg, Biophysics Group, Department of Chemistry and Molecular Biology (Sweden)

2012-09-15

While NMR studies of proteins typically aim at structure, dynamics or interactions, resonance assignments represent in almost all cases the initial step of the analysis. With increasing complexity of the NMR spectra, for example due to decreasing extent of ordered structure, this task often becomes both difficult and time-consuming, and the recording of high-dimensional data with high-resolution may be essential. Random sampling of the evolution time space, combined with sparse multidimensional Fourier transform (SMFT), allows for efficient recording of very high dimensional spectra ({>=}4 dimensions) while maintaining high resolution. However, the nature of this data demands for automation of the assignment process. Here we present the program TSAR (Tool for SMFT-based Assignment of Resonances), which exploits all advantages of SMFT input. Moreover, its flexibility allows to process data from any type of experiments that provide sequential connectivities. The algorithm was tested on several protein samples, including a disordered 81-residue fragment of the {delta} subunit of RNA polymerase from Bacillus subtilis containing various repetitive sequences. For our test examples, TSAR achieves a high percentage of assigned residues without any erroneous assignments.

Quantum localization in the three-dimensional kicked Rydberg atom

International Nuclear Information System (INIS)

Persson, Emil; Yoshida, Shuhei; Burgdoerfer, Joachim; Tong, X.-M.; Reinhold, Carlos O.

2003-01-01

We study the three-dimensional (3D) unidirectionally kicked Rydberg atom. For parabolic initial states elongated in the direction of the kicks we show that the ionization of the quantum system is suppressed as compared to the classical counterpart and that the quantum wave function is localized along all degrees of freedom, whereas the classical system is globally diffusive. We discuss the connection to the previously studied one-dimensional (1D) model of the kicked Rydberg atom and verify that the 1D model is a good approximation to the 3D quantum case in the limiting case of the most elongated initial states. We further study the quantum phase-space distribution (Husimi distribution) of the eigenstates of the period-one time-evolution (Floquet) operator and show that the eigenstates are localized in phase space. For the most elongated parabolic initial state, we are able to identify the unstable periodic orbits around which Floquet states localize. We discuss the possibility of observing quantum localization in high Rydberg states in n>100

Spin texture of the surface state of three-dimensional Dirac material Ca3PbO

Science.gov (United States)

Kariyado, Toshikaze

2015-04-01

The bulk and surface electronic structures of a candidate three-dimensional Dirac material Ca3PbO and its family are discussed especially focusing on the spin texture on the surface states. We first explain the basic features of the bulk band structure of Ca3PbO, such as emergence of Dirac fermions near the Fermi energy, and compare it with the other known three-dimensional Dirac semimetals. Then, the surface bands and spin-texture on them are investigated in detail. It is shown that the surface bands exhibit strong momentum-spin locking, which may be useful in some application for spin manipulation, induced by a combination of the inversion symmetry breaking at the surface and the strong spin-orbit coupling of Pb atoms. The surface band structure and the spin-textures are sensitive to the surface types.

Spin texture of the surface state of three-dimensional Dirac material Ca3PbO

International Nuclear Information System (INIS)

Kariyado, Toshikaze

2015-01-01

The bulk and surface electronic structures of a candidate three-dimensional Dirac material Ca 3 PbO and its family are discussed especially focusing on the spin texture on the surface states. We first explain the basic features of the bulk band structure of Ca 3 PbO, such as emergence of Dirac fermions near the Fermi energy, and compare it with the other known three-dimensional Dirac semimetals. Then, the surface bands and spin-texture on them are investigated in detail. It is shown that the surface bands exhibit strong momentum-spin locking, which may be useful in some application for spin manipulation, induced by a combination of the inversion symmetry breaking at the surface and the strong spin-orbit coupling of Pb atoms. The surface band structure and the spin-textures are sensitive to the surface types. (paper)

Assessing the detectability of antioxidants in two-dimensional high-performance liquid chromatography.

Science.gov (United States)

Bassanese, Danielle N; Conlan, Xavier A; Barnett, Neil W; Stevenson, Paul G

2015-05-01

This paper explores the analytical figures of merit of two-dimensional high-performance liquid chromatography for the separation of antioxidant standards. The cumulative two-dimensional high-performance liquid chromatography peak area was calculated for 11 antioxidants by two different methods--the areas reported by the control software and by fitting the data with a Gaussian model; these methods were evaluated for precision and sensitivity. Both methods demonstrated excellent precision in regards to retention time in the second dimension (%RSD below 1.16%) and cumulative second dimension peak area (%RSD below 3.73% from the instrument software and 5.87% for the Gaussian method). Combining areas reported by the high-performance liquid chromatographic control software displayed superior limits of detection, in the order of 1 × 10(-6) M, almost an order of magnitude lower than the Gaussian method for some analytes. The introduction of the countergradient eliminated the strong solvent mismatch between dimensions, leading to a much improved peak shape and better detection limits for quantification. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems

Directory of Open Access Journals (Sweden)

DimitrisG. Stavrakoudis

2012-04-01

Full Text Available This paper introduces the Fast Iterative Rule-based Linguistic Classifier (FaIRLiC, a Genetic Fuzzy Rule-Based Classification System (GFRBCS which targets at reducing the structural complexity of the resulting rule base, as well as its learning algorithm's computational requirements, especially when dealing with high-dimensional feature spaces. The proposed methodology follows the principles of the iterative rule learning (IRL approach, whereby a rule extraction algorithm (REA is invoked in an iterative fashion, producing one fuzzy rule at a time. The REA is performed in two successive steps: the first one selects the relevant features of the currently extracted rule, whereas the second one decides the antecedent part of the fuzzy rule, using the previously selected subset of features. The performance of the classifier is finally optimized through a genetic tuning post-processing stage. Comparative results in a hyperspectral remote sensing classification as well as in 12 real-world classification datasets indicate the effectiveness of the proposed methodology in generating high-performing and compact fuzzy rule-based classifiers, even for very high-dimensional feature spaces.

The validation and assessment of machine learning: a game of prediction from high-dimensional data

DEFF Research Database (Denmark)

Pers, Tune Hannes; Albrechtsen, A; Holst, C

2009-01-01

In applied statistics, tools from machine learning are popular for analyzing complex and high-dimensional data. However, few theoretical results are available that could guide to the appropriate machine learning tool in a new application. Initial development of an overall strategy thus often...... the ideas, the game is applied to data from the Nugenob Study where the aim is to predict the fat oxidation capacity based on conventional factors and high-dimensional metabolomics data. Three players have chosen to use support vector machines, LASSO, and random forests, respectively....

Minimax Rate-optimal Estimation of High-dimensional Covariance Matrices with Incomplete Data.

Science.gov (United States)

Cai, T Tony; Zhang, Anru

2016-09-01

Missing data occur frequently in a wide range of applications. In this paper, we consider estimation of high-dimensional covariance matrices in the presence of missing observations under a general missing completely at random model in the sense that the missingness is not dependent on the values of the data. Based on incomplete data, estimators for bandable and sparse covariance matrices are proposed and their theoretical and numerical properties are investigated. Minimax rates of convergence are established under the spectral norm loss and the proposed estimators are shown to be rate-optimal under mild regularity conditions. Simulation studies demonstrate that the estimators perform well numerically. The methods are also illustrated through an application to data from four ovarian cancer studies. The key technical tools developed in this paper are of independent interest and potentially useful for a range of related problems in high-dimensional statistical inference with missing data.

Minimax Rate-optimal Estimation of High-dimensional Covariance Matrices with Incomplete Data*

Science.gov (United States)

Cai, T. Tony; Zhang, Anru

2016-01-01

Missing data occur frequently in a wide range of applications. In this paper, we consider estimation of high-dimensional covariance matrices in the presence of missing observations under a general missing completely at random model in the sense that the missingness is not dependent on the values of the data. Based on incomplete data, estimators for bandable and sparse covariance matrices are proposed and their theoretical and numerical properties are investigated. Minimax rates of convergence are established under the spectral norm loss and the proposed estimators are shown to be rate-optimal under mild regularity conditions. Simulation studies demonstrate that the estimators perform well numerically. The methods are also illustrated through an application to data from four ovarian cancer studies. The key technical tools developed in this paper are of independent interest and potentially useful for a range of related problems in high-dimensional statistical inference with missing data. PMID:27777471

AucPR: an AUC-based approach using penalized regression for disease prediction with high-dimensional omics data.

Science.gov (United States)

Yu, Wenbao; Park, Taesung

2014-01-01

It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. We propose an AUC-based approach using penalized regression (AucPR), which is a parametric method used for obtaining a linear combination for maximizing the AUC. To obtain the AUC maximizer in a high-dimensional context, we transform a classical parametric AUC maximizer, which is used in a low-dimensional context, into a regression framework and thus, apply the penalization regression approach directly. Two kinds of penalization, lasso and elastic net, are considered. The parametric approach can avoid some of the difficulties of a conventional non-parametric AUC-based approach, such as the lack of an appropriate concave objective function and a prudent choice of the smoothing parameter. We apply the proposed AucPR for gene selection and classification using four real microarray and synthetic data. Through numerical studies, AucPR is shown to perform better than the penalized logistic regression and the nonparametric AUC-based method, in the sense of AUC and sensitivity for a given specificity, particularly when there are many correlated genes. We propose a powerful parametric and easily-implementable linear classifier AucPR, for gene selection and disease prediction for high-dimensional data. AucPR is recommended for its good prediction performance. Beside gene expression microarray data, AucPR can be applied to other types of high-dimensional omics data, such as miRNA and protein data.

Three-dimensional graphene/polyaniline composite material for high-performance supercapacitor applications

International Nuclear Information System (INIS)

Liu, Huili; Wang, Yi; Gou, Xinglong; Qi, Tao; Yang, Jun; Ding, Yulong

2013-01-01

Highlights: ► A novel 3D graphene showed high specific surface area and large mesopore volume. ► Aniline monomer was polymerized in the presence of 3D graphene at room temperature. ► The supercapacitive properties were studied by CV and charge–discharge tests. ► The composite show a high gravimetric capacitance and good cyclic stability. ► The 3D graphene/polyaniline has never been report before our work. -- Abstract: A novel three-dimensional (3D) graphene/polyaniline nanocomposite material which is synthesized using in situ polymerization of aniline monomer on the graphene surface is reported as an electrode for supercapacitors. The morphology and structure of the material are characterized by scanning electron microscopy (SEM), transmission electron microscope (TEM), Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The electrochemical properties of the resulting materials are systematically studied using cyclic voltammetry (CV) and constant current charge–discharge tests. A high gravimetric capacitance of 463 F g −1 at a scan rate of 1 mV s −1 is obtained by means of CVs with 3 mol L −1 KOH as the electrolyte. In addition, the composite material shows only 9.4% capacity loss after 500 cycles, indicating better cyclic stability for supercapacitor applications. The high specific surface area, large mesopore volume and three-dimensional nanoporous structure of 3D graphene could contribute to the high specific capacitance and good cyclic life

Simulating three-dimensional nonthermal high-energy photon emission in colliding-wind binaries

Energy Technology Data Exchange (ETDEWEB)

Reitberger, K.; Kissmann, R.; Reimer, A.; Reimer, O., E-mail: klaus.reitberger@uibk.ac.at [Institut für Astro- und Teilchenphysik and Institut für Theoretische Physik, Leopold-Franzens-Universität Innsbruck, A-6020 Innsbruck (Austria)

2014-07-01

Massive stars in binary systems have long been regarded as potential sources of high-energy γ rays. The emission is principally thought to arise in the region where the stellar winds collide and accelerate relativistic particles which subsequently emit γ rays. On the basis of a three-dimensional distribution function of high-energy particles in the wind collision region—as obtained by a numerical hydrodynamics and particle transport model—we present the computation of the three-dimensional nonthermal photon emission for a given line of sight. Anisotropic inverse Compton emission is modeled using the target radiation field of both stars. Photons from relativistic bremsstrahlung and neutral pion decay are computed on the basis of local wind plasma densities. We also consider photon-photon opacity effects due to the dense radiation fields of the stars. Results are shown for different stellar separations of a given binary system comprising of a B star and a Wolf-Rayet star. The influence of orbital orientation with respect to the line of sight is also studied by using different orbital viewing angles. For the chosen electron-proton injection ratio of 10{sup –2}, we present the ensuing photon emission in terms of two-dimensional projections maps, spectral energy distributions, and integrated photon flux values in various energy bands. Here, we find a transition from hadron-dominated to lepton-dominated high-energy emission with increasing stellar separations. In addition, we confirm findings from previous analytic modeling that the spectral energy distribution varies significantly with orbital orientation.

Approximation of High-Dimensional Rank One Tensors

KAUST Repository

Bachmayr, Markus

2013-11-12

Many real world problems are high-dimensional in that their solution is a function which depends on many variables or parameters. This presents a computational challenge since traditional numerical techniques are built on model classes for functions based solely on smoothness. It is known that the approximation of smoothness classes of functions suffers from the so-called \\'curse of dimensionality\\'. Avoiding this curse requires new model classes for real world functions that match applications. This has led to the introduction of notions such as sparsity, variable reduction, and reduced modeling. One theme that is particularly common is to assume a tensor structure for the target function. This paper investigates how well a rank one function f(x 1,...,x d)=f 1(x 1)⋯f d(x d), defined on Ω=[0,1]d can be captured through point queries. It is shown that such a rank one function with component functions f j in W∞ r([0,1]) can be captured (in L ∞) to accuracy O(C(d,r)N -r) from N well-chosen point evaluations. The constant C(d,r) scales like d dr. The queries in our algorithms have two ingredients, a set of points built on the results from discrepancy theory and a second adaptive set of queries dependent on the information drawn from the first set. Under the assumption that a point z∈Ω with nonvanishing f(z) is known, the accuracy improves to O(dN -r). © 2013 Springer Science+Business Media New York.

Approximation of High-Dimensional Rank One Tensors

KAUST Repository

Bachmayr, Markus; Dahmen, Wolfgang; DeVore, Ronald; Grasedyck, Lars

2013-01-01

Many real world problems are high-dimensional in that their solution is a function which depends on many variables or parameters. This presents a computational challenge since traditional numerical techniques are built on model classes for functions based solely on smoothness. It is known that the approximation of smoothness classes of functions suffers from the so-called 'curse of dimensionality'. Avoiding this curse requires new model classes for real world functions that match applications. This has led to the introduction of notions such as sparsity, variable reduction, and reduced modeling. One theme that is particularly common is to assume a tensor structure for the target function. This paper investigates how well a rank one function f(x 1,...,x d)=f 1(x 1)⋯f d(x d), defined on Ω=[0,1]d can be captured through point queries. It is shown that such a rank one function with component functions f j in W∞ r([0,1]) can be captured (in L ∞) to accuracy O(C(d,r)N -r) from N well-chosen point evaluations. The constant C(d,r) scales like d dr. The queries in our algorithms have two ingredients, a set of points built on the results from discrepancy theory and a second adaptive set of queries dependent on the information drawn from the first set. Under the assumption that a point z∈Ω with nonvanishing f(z) is known, the accuracy improves to O(dN -r). © 2013 Springer Science+Business Media New York.

Properties and modification of two-dimensional electronic states on noble metals; Eigenschaften und Modifikation zweidimensionaler Elektronenzustaende auf Edelmetallen

Energy Technology Data Exchange (ETDEWEB)

Forster, F.

2007-07-06

In this thesis investigations on two-dimensional electronic structures of (111)-noble metal surfaces and the influence of various adsorbates upon them is presented. It chiefly focuses on the surface-localized Shockley states of Cu, Ag and Au and their band dispersion (binding energy, band mass, and spin-orbit splitting) which turns out to be a sensitive probe for surface modifications induced by adsorption processes. Angular resolved photoelectron spectroscopy enables the observation of even subtle changes in the electronic band structure of these two dimensional systems. Different mechanisms taking place at surfaces and the substrate/adsorbate interfaces influence the Shockley state in a different manner and will be analyzed using suitable adsorbate model systems. The experimental results are matched with appropriate theoretical models like the phase accumulation model and the nearly-free electron model and - if possible - with ab initio calculations based on density functional theory. This allows for the integration of the results into a stringent overall picture. The influence of sub-monolayer adsorption of Na upon the surface state regarding the significant change in surface work function is determined. A systematic study of the physisorption of noble gases shows the effect of the repulsive adsorbate-substrate interaction upon the electrons of the surface state. A step-by-step coverage of the Cu and Au(111) surfaces by monolayers of Ag creates a gradual change in the surface potential and causes the surface state to become increasingly Ag-like. For N=7 ML thick and layer-by-layer growing Ag films on Au(111), new two-dimensional electronic structures can be observed, which are attributed to the quantum well states of the Ag adsorbate. The question whether they are localized within the Ag-layer or substantially within the substrate is resolved by the investigation of their energetic and spatial evolution with increasing Ag-film thicknesses N. For this, beside the

Estimating the effect of a variable in a high-dimensional regression model

DEFF Research Database (Denmark)

Jensen, Peter Sandholt; Wurtz, Allan

assume that the effect is identified in a high-dimensional linear model specified by unconditional moment restrictions. We consider  properties of the following methods, which rely on lowdimensional models to infer the effect: Extreme bounds analysis, the minimum t-statistic over models, Sala...

The magnetic flux dynamics in the critical state of one-dimensional discrete superconductor

International Nuclear Information System (INIS)

Ginzburg, S.L.; Nakin, A.V.; Savitskaya, N.E.

2006-01-01

We give a theoretical description of avalanche-like dynamics of magnetic flux in the critical state of discrete superconductors using a one-dimensional model of a multijunction SQUID. We show that the system under consideration demonstrates the self-organized criticality. The avalanches of vortices manifest themselves as jumps of the total magnetic flux in the sample. The sizes of these jumps have a power-law distribution. We argue that similarities in the behavior of discrete and usual type-II superconductors allows to extend our results for description of avalanche-like dynamics in type-II superconductors with strong pinning

Electron density of states in a one-dimensional distorted system with impurities: Coherent potential approximation

International Nuclear Information System (INIS)

Bulka, B.R.

1982-04-01

A tight-binding one-dimensional distorted system with impurities is considered and the electron density of states is calculated in the coherent potential approximation. It is shown that two types of impurities, an impurity built in a chain and a domain wall (a soliton), play the essential role and a drastic reduction of the energy gap is observed for a few per cent of impurities. The experimental situation in polyacetylene is also discussed. (author)

Interactive multimedia-based teaching material for 3-dimensional geometry

Science.gov (United States)

Prabowo, A.; Anggoro, R. P.; Astuti, D.; Fahmi, S.

2017-12-01

This study aims to develop the interactive multimedia-based teaching material for 3-dimensional geometry in junior high school. The product was produced through the stages of define, design, develop, and disseminate. Two media experts and two teaching experts had validated it. They judged that the product developed was valid. It had been revised based on their advice. It has been disseminated to 15 mathematics teachers and tried to 30 students of junior high school. Teachers stated that this product gives a new form of teaching material in 3-dimensional geometry. According to the student, the product is interesting. It can motivate them to study mathematics, help them to master the material and increase their interest in mathematics.

Pure zero-dimensional Cs4PbBr6 single crystal rhombohedral microdisks with high luminescence and stability.

Science.gov (United States)

Zhang, Haihua; Liao, Qing; Wu, Yishi; Chen, Jianwei; Gao, Qinggang; Fu, Hongbing

2017-11-08

Zero-dimensional (0D) perovskite Cs 4 PbBr 6 has been speculated to be an efficient solid-state emitter, exhibiting strong luminescense on achieving quantum confinement. Although several groups have reported strong green luminescence from Cs 4 PbBr 6 powders and nanocrystals, doubts that the origin of luminescence comes from Cs 4 PbBr 6 itself or CsPbBr 3 impurities have been a point of controversy in recent investigations. Herein, we developed a facile one-step solution self-assembly method to synthesize pure zero-dimensional rhombohedral Cs 4 PbBr 6 micro-disks (MDs) with a high PLQY of 52% ± 5% and photoluminescence full-width at half maximum (FWHM) of 16.8 nm. The obtained rhombohedral MDs were high quality single-crystalline as demonstrated by XRD and SAED patterns. We demonstrated that Cs 4 PbBr 6 MDs and CsPbBr 3 MDs were phase-separated from each other and the strong green emission comes from Cs 4 PbBr 6 . Power and temperature dependence spectra evidenced that the observed strong green luminescence of pure Cs 4 PbBr 6 MDs originated from direct exciton recombination in the isolated octahedra with a large binding energy of 303.9 meV. Significantly, isolated PbBr 6 4- octahedra separated by a Cs + ion insert in the crystal lattice is beneficial to maintaining the structural stability, depicting superior thermal and anion exchange stability. Our study provides an efficient approach to obtain high quality single-crystalline Cs 4 PbBr 6 MDs with highly efficient luminescence and stability for further optoelectronic applications.

High-dimensional chaos from self-sustained collisions of solitons

Energy Technology Data Exchange (ETDEWEB)

Yildirim, O. Ozgur, E-mail: donhee@seas.harvard.edu, E-mail: oozgury@gmail.com [Cavium, Inc., 600 Nickerson Rd., Marlborough, Massachusetts 01752 (United States); Ham, Donhee, E-mail: donhee@seas.harvard.edu, E-mail: oozgury@gmail.com [Harvard University, 33 Oxford St., Cambridge, Massachusetts 02138 (United States)

2014-06-16

We experimentally demonstrate chaos generation based on collisions of electrical solitons on a nonlinear transmission line. The nonlinear line creates solitons, and an amplifier connected to it provides gain to these solitons for their self-excitation and self-sustenance. Critically, the amplifier also provides a mechanism to enable and intensify collisions among solitons. These collisional interactions are of intrinsically nonlinear nature, modulating the phase and amplitude of solitons, thus causing chaos. This chaos generated by the exploitation of the nonlinear wave phenomena is inherently high-dimensional, which we also demonstrate.

Preparation of three-dimensional graphene foam for high performance supercapacitors

Directory of Open Access Journals (Sweden)

Yunjie Ping

2017-04-01

Full Text Available Supercapacitor is a new type of energy-storage device, and has been attracted widely attentions. As a two dimensional (2D nanomaterials, graphene is considered to be a promising material of supercapacitor because of its excellent properties involving high electrical conductivity and large surface area. In this paper, the large-scale graphene is successfully fabricated via environmental-friendly electrochemical exfoliation of graphite, and then, the three dimensional (3D graphene foam is prepared by using nickel foam as template and FeCl3/HCl solution as etchant. Compared with the regular 2D graphene paper, the 3D graphene foam electrode shows better electrochemical performance, and exhibits the largest specific capacitance of approximately 128 F/g at the current density of 1 A/g in 6 M KOH electrolyte. It is expected that the 3D graphene foam will have a potential application in the supercapacitors.

High Pressure ZZ-Exchange NMR Reveals Key Features of Protein Folding Transition States.

Science.gov (United States)

Zhang, Yi; Kitazawa, Soichiro; Peran, Ivan; Stenzoski, Natalie; McCallum, Scott A; Raleigh, Daniel P; Royer, Catherine A

2016-11-23

Understanding protein folding mechanisms and their sequence dependence requires the determination of residue-specific apparent kinetic rate constants for the folding and unfolding reactions. Conventional two-dimensional NMR, such as HSQC experiments, can provide residue-specific information for proteins. However, folding is generally too fast for such experiments. ZZ-exchange NMR spectroscopy allows determination of folding and unfolding rates on much faster time scales, yet even this regime is not fast enough for many protein folding reactions. The application of high hydrostatic pressure slows folding by orders of magnitude due to positive activation volumes for the folding reaction. We combined high pressure perturbation with ZZ-exchange spectroscopy on two autonomously folding protein domains derived from the ribosomal protein, L9. We obtained residue-specific apparent rates at 2500 bar for the N-terminal domain of L9 (NTL9), and rates at atmospheric pressure for a mutant of the C-terminal domain (CTL9) from pressure dependent ZZ-exchange measurements. Our results revealed that NTL9 folding is almost perfectly two-state, while small deviations from two-state behavior were observed for CTL9. Both domains exhibited large positive activation volumes for folding. The volumetric properties of these domains reveal that their transition states contain most of the internal solvent excluded voids that are found in the hydrophobic cores of the respective native states. These results demonstrate that by coupling it with high pressure, ZZ-exchange can be extended to investigate a large number of protein conformational transitions.

Dimensional and correlation effects of charged excitons in low-dimensional semiconductors

DEFF Research Database (Denmark)

Rønnow, Troels Frimodt; Pedersen, Thomas Garm; Cornean, Horia

2010-01-01

In this paper, we investigate the existence of bound trion states in fractional dimensional nanostructures, in terms of variational calculus. We start with trial states, then we refine the result with the help of the Hartree–Fock approximation and finally we use a partial basis expansion. We show...

Anonymous voting for multi-dimensional CV quantum system

International Nuclear Information System (INIS)

Shi Rong-Hua; Xiao Yi; Shi Jin-Jing; Guo Ying; Lee, Moon-Ho

2016-01-01

We investigate the design of anonymous voting protocols, CV-based binary-valued ballot and CV-based multi-valued ballot with continuous variables (CV) in a multi-dimensional quantum cryptosystem to ensure the security of voting procedure and data privacy. The quantum entangled states are employed in the continuous variable quantum system to carry the voting information and assist information transmission, which takes the advantage of the GHZ-like states in terms of improving the utilization of quantum states by decreasing the number of required quantum states. It provides a potential approach to achieve the efficient quantum anonymous voting with high transmission security, especially in large-scale votes. (paper)

High-dimensional free-space optical communications based on orbital angular momentum coding

Science.gov (United States)

Zou, Li; Gu, Xiaofan; Wang, Le

2018-03-01

In this paper, we propose a high-dimensional free-space optical communication scheme using orbital angular momentum (OAM) coding. In the scheme, the transmitter encodes N-bits information by using a spatial light modulator to convert a Gaussian beam to a superposition mode of N OAM modes and a Gaussian mode; The receiver decodes the information through an OAM mode analyser which consists of a MZ interferometer with a rotating Dove prism, a photoelectric detector and a computer carrying out the fast Fourier transform. The scheme could realize a high-dimensional free-space optical communication, and decodes the information much fast and accurately. We have verified the feasibility of the scheme by exploiting 8 (4) OAM modes and a Gaussian mode to implement a 256-ary (16-ary) coding free-space optical communication to transmit a 256-gray-scale (16-gray-scale) picture. The results show that a zero bit error rate performance has been achieved.

Three-Dimensional Porous Nitrogen-Doped NiO Nanostructures as Highly Sensitive NO2 Sensors

Directory of Open Access Journals (Sweden)

Van Hoang Luan

2017-10-01

Full Text Available Nickel oxide has been widely used in chemical sensing applications, because it has an excellent p-type semiconducting property with high chemical stability. Here, we present a novel technique of fabricating three-dimensional porous nitrogen-doped nickel oxide nanosheets as a highly sensitive NO2 sensor. The elaborate nanostructure was prepared by a simple and effective hydrothermal synthesis method. Subsequently, nitrogen doping was achieved by thermal treatment with ammonia gas. When the p-type dopant, i.e., nitrogen atoms, was introduced in the three-dimensional nanostructures, the nickel-oxide-nanosheet-based sensor showed considerable NO2 sensing ability with two-fold higher responsivity and sensitivity compared to non-doped nickel-oxide-based sensors.

Flooding Simulation of Extreme Event on Barnegat Bay by High-Resolution Two Dimensional Hydrodynamic Model

Science.gov (United States)

Wang, Y.; Ramaswamy, V.; Saleh, F.

2017-12-01

Barnegat Bay located on the east coast of New Jersey, United States and is separated from the Atlantic Ocean by the narrow Barnegat Peninsula which acts as a barrier island. The bay is fed by several rivers which empty through small estuaries along the inner shore. In terms of vulnerability from flooding, the Barnegat Peninsula is under the influence of both coastal storm surge and riverine flooding. Barnegat Bay was hit by Hurricane Sandy causing flood damages with extensive cross-island flow at many streets perpendicular to the shoreline. The objective of this work is to identify and quantify the sources of flooding using a two dimensional inland hydrodynamic model. The hydrodynamic model was forced by three observed coastal boundary conditions, and one hydrologic boundary condition from United States Geological Survey (USGS). The model reliability was evaluated with both FEMA spatial flooding extend and USGS High water marks. Simulated flooding extent showed good agreement with the reanalysis spatial inundation extents. Results offered important perspectives on the flow of the water into the bay, the velocity and the depth of the inundated areas. Using such information can enable emergency managers and decision makers identify evacuation and deploy flood defenses.

Electronic structure, Dirac points and Fermi arc surface states in three-dimensional Dirac semimetal Na3Bi from angle-resolved photoemission spectroscopy

International Nuclear Information System (INIS)

Liang Aiji; Chen Chaoyu; Wang Zhijun; Shi Youguo; Feng Ya; Yi Hemian; Xie Zhuojin; He Shaolong; He Junfeng; Peng Yingying; Liu Yan; Liu Defa; Hu Cheng; Zhao Lin; Liu Guodong; Dong Xiaoli; Zhang Jun; Nakatake, M; Iwasawa, H; Shimada, K

2016-01-01

The three-dimensional (3D) Dirac semimetals have linearly dispersive 3D Dirac nodes where the conduction band and valence band are connected. They have isolated 3D Dirac nodes in the whole Brillouin zone and can be viewed as a 3D counterpart of graphene. Recent theoretical calculations and experimental results indicate that the 3D Dirac semimetal state can be realized in a simple stoichiometric compound A 3 Bi ( A = Na, K, Rb). Here we report comprehensive high-resolution angle-resolved photoemission (ARPES) measurements on the two cleaved surfaces, (001) and (100), of Na 3 Bi. On the (001) surface, by comparison with theoretical calculations, we provide a proper assignment of the observed bands, and in particular, pinpoint the band that is responsible for the formation of the three-dimensional Dirac cones. We observe clear evidence of 3D Dirac cones in the three-dimensional momentum space by directly measuring on the k x – k y plane and by varying the photon energy to get access to different out-of-plane k z s. In addition, we reveal new features around the Brillouin zone corners that may be related with surface reconstruction. On the (100) surface, our ARPES measurements over a large momentum space raise an issue on the selection of the basic Brillouin zone in the (100) plane. We directly observe two isolated 3D Dirac nodes on the (100) surface. We observe the signature of the Fermi-arc surface states connecting the two 3D Dirac nodes that extend to a binding energy of ∼150 meV before merging into the bulk band. Our observations constitute strong evidence on the existence of the Dirac semimetal state in Na 3 Bi that are consistent with previous theoretical and experimental work. In addition, our results provide new information to clarify on the nature of the band that forms the 3D Dirac cones, on the possible formation of surface reconstruction of the (001) surface, and on the issue of basic Brillouin zone selection for the (100) surface. (rapid communication)

A study of low-dimensional inhomogeneous systems

International Nuclear Information System (INIS)

Arredondo Leon, Yesenia

2009-01-01

While the properties of homogeneous one-dimensional systems, even with disorder, are relatively well-understood, very little is known about the properties of strongly interacting inhomogeneous systems. Their high-energy physics is determined by the underlying chemistry which, in the atomic scale, introduces Coulomb correlations and local potentials. On the other hand, at large length scales, the physics has to be described by the Tomonaga-Luttinger liquid (TLL) model. In order to establish a connection between the low-energy TLL and the quasi-one-dimensional systems synthesized in the laboratory, we investigate the density-density correlation function in inhomogeneous one-dimensional systems in the asymptotic region. To investigate homogeneous as well as inhomogeneous systems, we use the density-matrix renormalization group (DMRG) method. We present results for ground state properties, such as the density-density correlation function and the parameter K c , which characterizes its decay at large distances. (orig.)

A study of low-dimensional inhomogeneous systems

Energy Technology Data Exchange (ETDEWEB)

Arredondo Leon, Yesenia

2009-01-15

While the properties of homogeneous one-dimensional systems, even with disorder, are relatively well-understood, very little is known about the properties of strongly interacting inhomogeneous systems. Their high-energy physics is determined by the underlying chemistry which, in the atomic scale, introduces Coulomb correlations and local potentials. On the other hand, at large length scales, the physics has to be described by the Tomonaga-Luttinger liquid (TLL) model. In order to establish a connection between the low-energy TLL and the quasi-one-dimensional systems synthesized in the laboratory, we investigate the density-density correlation function in inhomogeneous one-dimensional systems in the asymptotic region. To investigate homogeneous as well as inhomogeneous systems, we use the density-matrix renormalization group (DMRG) method. We present results for ground state properties, such as the density-density correlation function and the parameter K{sub c}, which characterizes its decay at large distances. (orig.)

Propagation of Elastic Waves in a One-Dimensional High Aspect Ratio Nanoridge Phononic Crystal

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Abdellatif Gueddida

2018-05-01

Full Text Available We investigate the propagation of elastic waves in a one-dimensional (1D phononic crystal constituted by high aspect ratio epoxy nanoridges that have been deposited at the surface of a glass substrate. With the help of the finite element method (FEM, we calculate the dispersion curves of the modes localized at the surface for propagation both parallel and perpendicular to the nanoridges. When the direction of the wave is parallel to the nanoridges, we find that the vibrational states coincide with the Lamb modes of an infinite plate that correspond to one nanoridge. When the direction of wave propagation is perpendicular to the 1D nanoridges, the localized modes inside the nanoridges give rise to flat branches in the band structure that interact with the surface Rayleigh mode, and possibly open narrow band gaps. Filling the nanoridge structure with a viscous liquid produces new modes that propagate along the 1D finite height multilayer array.

Ashkin-Teller criticality and weak first-order behavior of the phase transition to a fourfold degenerate state in two-dimensional frustrated Ising antiferromagnets

Science.gov (United States)

Liu, R. M.; Zhuo, W. Z.; Chen, J.; Qin, M. H.; Zeng, M.; Lu, X. B.; Gao, X. S.; Liu, J.-M.

2017-07-01

We study the thermal phase transition of the fourfold degenerate phases (the plaquette and single-stripe states) in the two-dimensional frustrated Ising model on the Shastry-Sutherland lattice using Monte Carlo simulations. The critical Ashkin-Teller-like behavior is identified both in the plaquette phase region and the single-stripe phase region. The four-state Potts critical end points differentiating the continuous transitions from the first-order ones are estimated based on finite-size-scaling analyses. Furthermore, a similar behavior of the transition to the fourfold single-stripe phase is also observed in the anisotropic triangular Ising model. Thus, this work clearly demonstrates that the transitions to the fourfold degenerate states of two-dimensional Ising antiferromagnets exhibit similar transition behavior.

Present state and future of CFD based on three-dimensional RANS analysis

International Nuclear Information System (INIS)

Kim, Kwang Yong

2004-01-01

Computational Fluid Dynamics (CFD) based on Navier-Stokes equations has been developed rapidly for several decades with the developments of high speed computers and numerical algorithms, and presently is regarded as an essential analysis tool in the engineering applications containing fluid flow and convective heat transfer. It is known that for turbulent flow the Navier-Stokes equations can be calculated precisely by Direct Numerical Simulation (DNS). However, DNS needs huge computing time even for simple low-Reynolds number flows, and thus is not practical. Large Eddy Simulation (LES) can be an alternative. But, LES also needs considerable computing time for the analysis of engineering flows, and have some problem in the methods. Therefore, the analysis methods using Reynolds-averaged Navier-stokes equations (RANS) and turbulence closure models are still regarded as the major techniques for the analysis of turbulent flows in spite of the inaccuracy of the prediction. In this presentation, the present state and the prospect of CFD based on three-dimensional RANS analysis are introduced for physical models and numerical algorithms with the engineering examples. Especially, for the analysis of two-phase flows in nuclear reactor, the recently developed techniques are also introduced. And, the presentation includes the methods of design optimization using RANS analysis and numerical optimization techniques with variety of the applications

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

Science.gov (United States)

Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

2016-02-07

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

AN EFFECTIVE MULTI-CLUSTERING ANONYMIZATION APPROACH USING DISCRETE COMPONENT TASK FOR NON-BINARY HIGH DIMENSIONAL DATA SPACES

Directory of Open Access Journals (Sweden)

L.V. Arun Shalin

2016-01-01

Full Text Available Clustering is a process of grouping elements together, designed in such a way that the elements assigned to similar data points in a cluster are more comparable to each other than the remaining data points in a cluster. During clustering certain difficulties related when dealing with high dimensional data are ubiquitous and abundant. Works concentrated using anonymization method for high dimensional data spaces failed to address the problem related to dimensionality reduction during the inclusion of non-binary databases. In this work we study methods for dimensionality reduction for non-binary database. By analyzing the behavior of dimensionality reduction for non-binary database, results in performance improvement with the help of tag based feature. An effective multi-clustering anonymization approach called Discrete Component Task Specific Multi-Clustering (DCTSM is presented for dimensionality reduction on non-binary database. To start with we present the analysis of attribute in the non-binary database and cluster projection identifies the sparseness degree of dimensions. Additionally with the quantum distribution on multi-cluster dimension, the solution for relevancy of attribute and redundancy on non-binary data spaces is provided resulting in performance improvement on the basis of tag based feature. Multi-clustering tag based feature reduction extracts individual features and are correspondingly replaced by the equivalent feature clusters (i.e. tag clusters. During training, the DCTSM approach uses multi-clusters instead of individual tag features and then during decoding individual features is replaced by corresponding multi-clusters. To measure the effectiveness of the method, experiments are conducted on existing anonymization method for high dimensional data spaces and compared with the DCTSM approach using Statlog German Credit Data Set. Improved tag feature extraction and minimum error rate compared to conventional anonymization

Catalystlike effect of orbital angular momentum on the conversion of transverse to three-dimensional spin states within tightly focused radially polarized beams

Science.gov (United States)

Han, Lei; Liu, Sheng; Li, Peng; Zhang, Yi; Cheng, Huachao; Zhao, Jianlin

2018-05-01

We report on the catalystlike effect of orbital angular momentum (OAM) on local spin-state conversion within the tightly focused radially polarized beams associated with optical spin-orbit interaction. It is theoretically demonstrated that the incident OAM can lead to a conversion of purely transverse spin state to a three-dimensional spin state on the focal plane. This conversion can be conveniently manipulated by altering the sign and value of the OAM. By comparing the total OAM and spin angular momentum (SAM) on the incident plane to those on the focal plane, it is indicated that the incident OAM have no participation in the angular momentum intertransfer, and just play a role as a catalyst of local SAM conversion. Such an effect of OAM sheds new light on the optical spin-orbit interaction in tight-focusing processes. The resultant three-dimensional spin states may provide more degrees of freedom in optical manipulation and spin-dependent directive coupling.

Three-dimensional porous graphene-Co{sub 3}O{sub 4} nanocomposites for high performance photocatalysts

Energy Technology Data Exchange (ETDEWEB)

Bin, Zeng, E-mail: 21467855@qq.com [College of Mechanical Engineering, Hunan University of Arts and Science, Changde 415000 (China); Hui, Long [Department of Applied Physics and Materials Research Center, The Hong Kong Polytechnic University, Hung Hom, Kowloon (Hong Kong)

2015-12-01

Highlights: • The three-dimensional porous graphene-Co{sub 3}O{sub 4} nanocomposites were synthesized. • Excellent photocatalytic performance. • Separated from the reaction medium by magnetic decantation. - Abstract: Novel three-dimensional porous graphene-Co{sub 3}O{sub 4} nanocomposites were synthesized by freeze-drying methods. Scanning and transmission electron microscopy revealed that the graphene formed a three-dimensional porous structure with Co{sub 3}O{sub 4} nanoparticles decorated surfaces. The as-obtained product showed high photocatalytic efficiency and could be easily separated from the reaction medium by magnetic decantation. This nanocomposite may be expected to have potential in water purification applications.

Dynamic colloidal assembly pathways via low dimensional models

Energy Technology Data Exchange (ETDEWEB)

Yang, Yuguang; Bevan, Michael A., E-mail: mabevan@jhu.edu [Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218 (United States); Thyagarajan, Raghuram; Ford, David M. [Chemical Engineering, University of Massachusetts, Amherst, Massachusetts 01003 (United States)

2016-05-28

Here we construct a low-dimensional Smoluchowski model for electric field mediated colloidal crystallization using Brownian dynamic simulations, which were previously matched to experiments. Diffusion mapping is used to infer dimensionality and confirm the use of two order parameters, one for degree of condensation and one for global crystallinity. Free energy and diffusivity landscapes are obtained as the coefficients of a low-dimensional Smoluchowski equation to capture the thermodynamics and kinetics of microstructure evolution. The resulting low-dimensional model quantitatively captures the dynamics of different assembly pathways between fluid, polycrystal, and single crystals states, in agreement with the full N-dimensional data as characterized by first passage time distributions. Numerical solution of the low-dimensional Smoluchowski equation reveals statistical properties of the dynamic evolution of states vs. applied field amplitude and system size. The low-dimensional Smoluchowski equation and associated landscapes calculated here can serve as models for predictive control of electric field mediated assembly of colloidal ensembles into two-dimensional crystalline objects.

Reduced-Dimensionality Semiclassical Transition State Theory: Application to Hydrogen Atom Abstraction and Exchange Reactions of Hydrocarbons.

Science.gov (United States)

Greene, Samuel M; Shan, Xiao; Clary, David C

2015-12-17

Quantum mechanical methods for calculating rate constants are often intractable for reactions involving many atoms. Semiclassical transition state theory (SCTST) offers computational advantages over these methods but nonetheless scales exponentially with the number of degrees of freedom (DOFs) of the system. Here we present a method with more favorable scaling, reduced-dimensionality SCTST (RD SCTST), that treats only a subset of DOFs of the system explicitly. We apply it to three H abstraction and exchange reactions for which two-dimensional potential energy surfaces (PESs) have previously been constructed and evaluated using RD quantum scattering calculations. We differentiated these PESs to calculate harmonic frequencies and anharmonic constants, which were then used to calculate cumulative reaction probabilities and rate constants by RD SCTST. This method yielded rate constants in good agreement with quantum scattering results. Notably, it performed well for a heavy-light-heavy reaction, even though it does not explicitly account for corner-cutting effects. Recent extensions to SCTST that improve its treatment of deep tunneling were also evaluated within the reduced-dimensionality framework. The success of RD SCTST in this study suggests its potential applicability to larger systems.

Dimensional Effects on the Momentum distribution of Bosonic Trimer States

DEFF Research Database (Denmark)

F. Bellotti, F.; Frederico, T.; T. Yamashita, M.

2013-01-01

-body contact parameter is universal and then demonstrate that the momentum distribution at next-to-leading order has a logarithmic dependence on momentum which is vastly different from the three-dimensional case. Based on this, we propose a scheme for measuring the effective dimensionality of a quantum many......-body system by exploiting the functional form of the momentum distribution....

Similarity-dissimilarity plot for visualization of high dimensional data in biomedical pattern classification.

Science.gov (United States)

Arif, Muhammad

2012-06-01

In pattern classification problems, feature extraction is an important step. Quality of features in discriminating different classes plays an important role in pattern classification problems. In real life, pattern classification may require high dimensional feature space and it is impossible to visualize the feature space if the dimension of feature space is greater than four. In this paper, we have proposed a Similarity-Dissimilarity plot which can project high dimensional space to a two dimensional space while retaining important characteristics required to assess the discrimination quality of the features. Similarity-dissimilarity plot can reveal information about the amount of overlap of features of different classes. Separable data points of different classes will also be visible on the plot which can be classified correctly using appropriate classifier. Hence, approximate classification accuracy can be predicted. Moreover, it is possible to know about whom class the misclassified data points will be confused by the classifier. Outlier data points can also be located on the similarity-dissimilarity plot. Various examples of synthetic data are used to highlight important characteristics of the proposed plot. Some real life examples from biomedical data are also used for the analysis. The proposed plot is independent of number of dimensions of the feature space.

Efficient and accurate nearest neighbor and closest pair search in high-dimensional space

KAUST Repository

Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos

2010-01-01

Nearest Neighbor (NN) search in high-dimensional space is an important problem in many applications. From the database perspective, a good solution needs to have two properties: (i) it can be easily incorporated in a relational database, and (ii

High-speed fan-beam reconstruction using direct two-dimensional Fourier transform method

International Nuclear Information System (INIS)

Niki, Noboru; Mizutani, Toshio; Takahashi, Yoshizo; Inouye, Tamon.

1984-01-01

Since the first development of X-ray computer tomography (CT), various efforts have been made to obtain high quality of high-speed image. However, the development of high resolution CT and the ultra-high speed CT to be applied to hearts is still desired. The X-ray beam scanning method was already changed from the parallel beam system to the fan-beam system in order to greatly shorten the scanning time. Also, the filtered back projection (DFBP) method has been employed to directly processing fan-beam projection data as reconstruction method. Although the two-dimensional Fourier transform (TFT) method significantly faster than FBP method was proposed, it has not been sufficiently examined for fan-beam projection data. Thus, the ITFT method was investigated, which first executes rebinning algorithm to convert the fan-beam projection data to the parallel beam projection data, thereafter, uses two-dimensional Fourier transform. By this method, although high speed is expected, the reconstructed images might be degraded due to the adoption of rebinning algorithm. Therefore, the effect of the interpolation error of rebinning algorithm on the reconstructed images has been analyzed theoretically, and finally, the result of the employment of spline interpolation which allows the acquisition of high quality images with less errors has been shown by the numerical and visual evaluation based on simulation and actual data. Computation time was reduced to 1/15 for the image matrix of 512 and to 1/30 for doubled matrix. (Wakatsuki, Y.)

State transfer in highly connected networks and a quantum Babinet principle

Science.gov (United States)

Tsomokos, D. I.; Plenio, M. B.; de Vega, I.; Huelga, S. F.

2008-12-01

The transfer of a quantum state between distant nodes in two-dimensional networks is considered. The fidelity of state transfer is calculated as a function of the number of interactions in networks that are described by regular graphs. It is shown that perfect state transfer is achieved in a network of size N , whose structure is that of an (N/2) -cross polytope graph, if N is a multiple of 4 . The result is reminiscent of the Babinet principle of classical optics. A quantum Babinet principle is derived, which allows for the identification of complementary graphs leading to the same fidelity of state transfer, in analogy with complementary screens providing identical diffraction patterns.

Compound Structure-Independent Activity Prediction in High-Dimensional Target Space.

Science.gov (United States)

Balfer, Jenny; Hu, Ye; Bajorath, Jürgen

2014-08-01

Profiling of compound libraries against arrays of targets has become an important approach in pharmaceutical research. The prediction of multi-target compound activities also represents an attractive task for machine learning with potential for drug discovery applications. Herein, we have explored activity prediction in high-dimensional target space. Different types of models were derived to predict multi-target activities. The models included naïve Bayesian (NB) and support vector machine (SVM) classifiers based upon compound structure information and NB models derived on the basis of activity profiles, without considering compound structure. Because the latter approach can be applied to incomplete training data and principally depends on the feature independence assumption, SVM modeling was not applicable in this case. Furthermore, iterative hybrid NB models making use of both activity profiles and compound structure information were built. In high-dimensional target space, NB models utilizing activity profile data were found to yield more accurate activity predictions than structure-based NB and SVM models or hybrid models. An in-depth analysis of activity profile-based models revealed the presence of correlation effects across different targets and rationalized prediction accuracy. Taken together, the results indicate that activity profile information can be effectively used to predict the activity of test compounds against novel targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dimensional measurement of micro parts with high aspect ratio in HIT-UOI

Science.gov (United States)

Dang, Hong; Cui, Jiwen; Feng, Kunpeng; Li, Junying; Zhao, Shiyuan; Zhang, Haoran; Tan, Jiubin

2016-11-01

Micro parts with high aspect ratios have been widely used in different fields including aerospace and defense industries, while the dimensional measurement of these micro parts becomes a challenge in the field of precision measurement and instrument. To deal with this contradiction, several probes for the micro parts precision measurement have been proposed by researchers in Center of Ultra-precision Optoelectronic Instrument (UOI), Harbin Institute of Technology (HIT). In this paper, optical fiber probes with structures of spherical coupling(SC) with double optical fibers, micro focal-length collimation (MFL-collimation) and fiber Bragg grating (FBG) are described in detail. After introducing the sensing principles, both advantages and disadvantages of these probes are analyzed respectively. In order to improve the performances of these probes, several approaches are proposed. A two-dimensional orthogonal path arrangement is propounded to enhance the dimensional measurement ability of MFL-collimation probes, while a high resolution and response speed interrogation method based on differential method is used to improve the accuracy and dynamic characteristics of the FBG probes. The experiments for these special structural fiber probes are given with a focus on the characteristics of these probes, and engineering applications will also be presented to prove the availability of them. In order to improve the accuracy and the instantaneity of the engineering applications, several techniques are used in probe integration. The effectiveness of these fiber probes were therefore verified through both the analysis and experiments.

Kernel based methods for accelerated failure time model with ultra-high dimensional data

Directory of Open Access Journals (Sweden)

Jiang Feng

2010-12-01

Full Text Available Abstract Background Most genomic data have ultra-high dimensions with more than 10,000 genes (probes. Regularization methods with L1 and Lp penalty have been extensively studied in survival analysis with high-dimensional genomic data. However, when the sample size n ≪ m (the number of genes, directly identifying a small subset of genes from ultra-high (m > 10, 000 dimensional data is time-consuming and not computationally efficient. In current microarray analysis, what people really do is select a couple of thousands (or hundreds of genes using univariate analysis or statistical tests, and then apply the LASSO-type penalty to further reduce the number of disease associated genes. This two-step procedure may introduce bias and inaccuracy and lead us to miss biologically important genes. Results The accelerated failure time (AFT model is a linear regression model and a useful alternative to the Cox model for survival analysis. In this paper, we propose a nonlinear kernel based AFT model and an efficient variable selection method with adaptive kernel ridge regression. Our proposed variable selection method is based on the kernel matrix and dual problem with a much smaller n × n matrix. It is very efficient when the number of unknown variables (genes is much larger than the number of samples. Moreover, the primal variables are explicitly updated and the sparsity in the solution is exploited. Conclusions Our proposed methods can simultaneously identify survival associated prognostic factors and predict survival outcomes with ultra-high dimensional genomic data. We have demonstrated the performance of our methods with both simulation and real data. The proposed method performs superbly with limited computational studies.

Hawking radiation of a high-dimensional rotating black hole

Energy Technology Data Exchange (ETDEWEB)

Zhao, Ren; Zhang, Lichun; Li, Huaifan; Wu, Yueqin [Shanxi Datong University, Institute of Theoretical Physics, Department of Physics, Datong (China)

2010-01-15

We extend the classical Damour-Ruffini method and discuss Hawking radiation spectrum of high-dimensional rotating black hole using Tortoise coordinate transformation defined by taking the reaction of the radiation to the spacetime into consideration. Under the condition that the energy and angular momentum are conservative, taking self-gravitation action into account, we derive Hawking radiation spectrums which satisfy unitary principle in quantum mechanics. It is shown that the process that the black hole radiates particles with energy {omega} is a continuous tunneling process. We provide a theoretical basis for further studying the physical mechanism of black-hole radiation. (orig.)

Current state of standardization in the field of dimensional computed tomography

International Nuclear Information System (INIS)

Bartscher, Markus; Härtig, Frank; Neuschaefer-Rube, Ulrich; Sato, Osamu

2014-01-01

Industrial x-ray computed tomography (CT) is a well-established non-destructive testing (NDT) technology and has been in use for decades. Moreover, CT has also started to become an important technology for dimensional metrology. But the requirements on dimensional CTs, i.e., on performing coordinate measurements with CT, are different from NDT. For dimensional measurements, the position of interfaces or surfaces is of importance, while this is often less critical in NDT. Standardization plays an important role here as it can create trust in new measurement technologies as is the case for dimensional CT. At the international standardization level, the ISO TC 213 WG 10 is working on specifications for dimensional CT. This paper highlights the demands on international standards in the field of dimensional CT and describes the current developments from the viewpoint of representatives of national and international standardization committees. Key aspects of the discussion are the material influence on the length measurement error E and how E can best be measured. A respective study was performed on hole plates as new reference standards for error testing of length measurements incorporating the material influence. We performed corresponding measurement data analysis and present a further elaborated hole plate design. The authors also comment on different approaches currently pursued and give an outlook on upcoming developments as far as they can be foreseen. (paper)

Three-Dimensional Elasticity Solutions for Sound Radiation of Functionally Graded Materials Plates considering State Space Method

Directory of Open Access Journals (Sweden)

Tieliang Yang

2016-01-01

Full Text Available This paper presents an analytical study for sound radiation of functionally graded materials (FGM plate based on the three-dimensional theory of elasticity. The FGM plate is a mixture of metal and ceramic, and its material properties are assumed to have smooth and continuous variation in the thickness direction according to a power-law distribution in terms of volume fractions of the constituents. Based on the three-dimensional theory of elasticity and state space method, the governing equations with variable coefficients of the FGM plate are derived. The sound radiation of the vibration plate is calculated with Rayleigh integral. Comparisons of the present results with those of solutions in the available literature are made and good agreements are achieved. Finally, some parametric studies are carried out to investigate the sound radiation properties of FGM plates.

Effect of strong disorder on three-dimensional chiral topological insulators: Phase diagrams, maps of the bulk invariant, and existence of topological extended bulk states

Science.gov (United States)

Song, Juntao; Fine, Carolyn; Prodan, Emil

2014-11-01

The effect of strong disorder on chiral-symmetric three-dimensional lattice models is investigated via analytical and numerical methods. The phase diagrams of the models are computed using the noncommutative winding number, as functions of disorder strength and model's parameters. The localized/delocalized characteristic of the quantum states is probed with level statistics analysis. Our study reconfirms the accurate quantization of the noncommutative winding number in the presence of strong disorder, and its effectiveness as a numerical tool. Extended bulk states are detected above and below the Fermi level, which are observed to undergo the so-called "levitation and pair annihilation" process when the system is driven through a topological transition. This suggests that the bulk invariant is carried by these extended states, in stark contrast with the one-dimensional case where the extended states are completely absent and the bulk invariant is carried by the localized states.

The Figured Worlds of High School Science Teachers: Uncovering Three-Dimensional Assessment Decisions

Science.gov (United States)

Ewald, Megan

As a result of recent mandates of the Next Generation Science Standards, assessments are a "system of meaning" amidst a paradigm shift toward three-dimensional assessments. This study is motivated by two research questions: 1) how do high school science teachers describe their processes of decision-making in the development and use of three-dimensional assessments and 2) how do high school science teachers negotiate their identities as assessors in designing three-dimensional assessments. An important factor in teachers' assessment decision making is how they identify themselves as assessors. Therefore, this study investigated the teachers' roles as assessors through the Sociocultural Identity Theory. The most important contribution from this study is the emergent teacher assessment sub-identities: the modifier-recycler , the feeler-finder, and the creator. Using a qualitative phenomenological research design, focus groups, three-series interviews, think-alouds, and document analysis were utilized in this study. These qualitative methods were chosen to elicit rich conversations among teachers, make meaning of the teachers' experiences through in-depth interviews, amplify the thought processes of individual teachers while making assessment decisions, and analyze assessment documents in relation to teachers' perspectives. The findings from this study suggest that--of the 19 participants--only two teachers could consistently be identified as creators and aligned their assessment practices with NGSS. However, assessment sub-identities are not static and teachers may negotiate their identities from one moment to the next within socially constructed realms of interpretation known as figured worlds. Because teachers are positioned in less powerful figured worlds within the dominant discourse of standardization, this study raises awareness as to how the external pressures from more powerful figured worlds socially construct teachers' identities as assessors. For teachers

AucPR: An AUC-based approach using penalized regression for disease prediction with high-dimensional omics data

OpenAIRE

Yu, Wenbao; Park, Taesung

2014-01-01

Motivation It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. Results We propose an AUC-based approach u...

Modeling High-Dimensional Multichannel Brain Signals

KAUST Repository

Hu, Lechuan

2017-12-12

Our goal is to model and measure functional and effective (directional) connectivity in multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The difficulties from analyzing these data mainly come from two aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with potentially high lag order so that complex lead-lag temporal dynamics between the channels can be captured. Estimates of the VAR model will be obtained by our proposed hybrid LASSLE (LASSO + LSE) method which combines regularization (to control for sparsity) and least squares estimation (to improve bias and mean-squared error). Then we employ some measures of connectivity but put an emphasis on partial directed coherence (PDC) which can capture the directional connectivity between channels. PDC is a frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative to all possible receivers in the network. The proposed modeling approach provided key insights into potential functional relationships among simultaneously recorded sites during performance of a complex memory task. Specifically, this novel method was successful in quantifying patterns of effective connectivity across electrode locations, and in capturing how these patterns varied across trial epochs and trial types.

HSTLBO: A hybrid algorithm based on Harmony Search and Teaching-Learning-Based Optimization for complex high-dimensional optimization problems.

Directory of Open Access Journals (Sweden)

Shouheng Tuo

Full Text Available Harmony Search (HS and Teaching-Learning-Based Optimization (TLBO as new swarm intelligent optimization algorithms have received much attention in recent years. Both of them have shown outstanding performance for solving NP-Hard optimization problems. However, they also suffer dramatic performance degradation for some complex high-dimensional optimization problems. Through a lot of experiments, we find that the HS and TLBO have strong complementarity each other. The HS has strong global exploration power but low convergence speed. Reversely, the TLBO has much fast convergence speed but it is easily trapped into local search. In this work, we propose a hybrid search algorithm named HSTLBO that merges the two algorithms together for synergistically solving complex optimization problems using a self-adaptive selection strategy. In the HSTLBO, both HS and TLBO are modified with the aim of balancing the global exploration and exploitation abilities, where the HS aims mainly to explore the unknown regions and the TLBO aims to rapidly exploit high-precision solutions in the known regions. Our experimental results demonstrate better performance and faster speed than five state-of-the-art HS variants and show better exploration power than five good TLBO variants with similar run time, which illustrates that our method is promising in solving complex high-dimensional optimization problems. The experiment on portfolio optimization problems also demonstrate that the HSTLBO is effective in solving complex read-world application.

Effects of Rashba and Dresselhaus spin-orbit interactions on the ground state of two-dimensional localized spins.

Science.gov (United States)

Oh, J H; Lee, K-J; Lee, Hyun-Woo; Shin, M

2014-05-14

Starting with the indirect exchange model influenced by the Rashba and the Dresselhaus spin-orbit interactions, we derive the Dzyaloshinskii-Moriya interaction of localized spins. The strength of the Dzyaloshinskii-Moriya interaction is compared with that of the Heisenberg exchange term as a function of atomic distance. Using the calculated interaction strengths, we discuss the formation of various atomic ground states as a function of temperature and external magnetic field. By plotting the magnetic field-temperature phase diagram, we present approximate phase boundaries between the spiral, Skyrmion and ferromagnetic states of the two-dimensional weak ferromagnetic system.

Effects of Rashba and Dresselhaus spin–orbit interactions on the ground state of two-dimensional localized spins

International Nuclear Information System (INIS)

Oh, J H; Shin, M; Lee, K-J; Lee, Hyun-Woo

2014-01-01

Starting with the indirect exchange model influenced by the Rashba and the Dresselhaus spin–orbit interactions, we derive the Dzyaloshinskii–Moriya interaction of localized spins. The strength of the Dzyaloshinskii–Moriya interaction is compared with that of the Heisenberg exchange term as a function of atomic distance. Using the calculated interaction strengths, we discuss the formation of various atomic ground states as a function of temperature and external magnetic field. By plotting the magnetic field–temperature phase diagram, we present approximate phase boundaries between the spiral, Skyrmion and ferromagnetic states of the two-dimensional weak ferromagnetic system. (paper)

Variance inflation in high dimensional Support Vector Machines

DEFF Research Database (Denmark)

Abrahamsen, Trine Julie; Hansen, Lars Kai

2013-01-01

Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors...... the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets....... follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including...

A Zero-Dimensional Organic Seesaw-Shaped Tin Bromide with Highly Efficient Strongly Stokes-Shifted Deep-Red Emission

Energy Technology Data Exchange (ETDEWEB)

Zhou, Chenkun [College of Engineering, Tallahassee, FL (United States). Dept. of Chemical and Biomedical Engineering; Lin, Haoran [College of Engineering, Tallahassee, FL (United States). Dept. of Chemical and Biomedical Engineering; Shi, Hongliang [Beihang Univ., Beijing (China). Dept. of Physics; Tian, Yu [Materials Science and Engineering Program, Florida State University, Tallahassee FL 32306 USA; Pak, Chongin [Florida State Univ., Tallahassee, FL (United States). Dept. of Chemistry and Biochemistry; Shatruk, Michael [Florida State Univ., Tallahassee, FL (United States). Dept. of Chemistry and Biochemistry; Zhou, Yan [Florida State Univ., Tallahassee, FL (United States). Dept. of Chemistry and Biochemistry; Djurovich, Peter [Univ. of Southern California, Los Angeles, CA (United States). Dept. of Chemistry; Du, Mao-Hua [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Materials Science and Technology Division, Center for Radiation Detection Materials and Systems; Ma, Biwu [College of Engineering, Tallahassee, FL (United States). Dept. of Chemical and Biomedical Engineering; Beihang Univ., Beijing (China). Dept. of Physics; Florida State Univ., Tallahassee, FL (United States). Dept. of Chemistry and Biochemistry

2017-12-21

The synthesis and characterization is reported of (C₉NH₂₀)₂SnBr₄, a novel organic metal halide hybrid with a zero-dimensional (0D) structure, in which individual seesaw-shaped tin (II) bromide anions (SnBr₄^2-) are co-crystallized with 1-butyl-1-methylpyrrolidinium cations (C₉NH₂₀⁺). Upon photoexcitation, the bulk crystals exhibit a highly efficient broadband deep-red emission peaked at 695 nm, with a large Stokes shift of 332 nm and a high quantum efficiency of around 46 %. Furthermore, the unique photophysical properties of this hybrid material are attributed to two major factors: 1) the 0D structure allowing the bulk crystals to exhibit the intrinsic properties of individual SnBr₄^2- species, and 2) the seesaw structure then enables a pronounced excited state structural deformation as confirmed by density functional theory (DFT) calculations.

Technical Report: Toward a Scalable Algorithm to Compute High-Dimensional Integrals of Arbitrary Functions

International Nuclear Information System (INIS)

Snyder, Abigail C.; Jiao, Yu

2010-01-01

Neutron experiments at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) frequently generate large amounts of data (on the order of 106-1012 data points). Hence, traditional data analysis tools run on a single CPU take too long to be practical and scientists are unable to efficiently analyze all data generated by experiments. Our goal is to develop a scalable algorithm to efficiently compute high-dimensional integrals of arbitrary functions. This algorithm can then be used to integrate the four-dimensional integrals that arise as part of modeling intensity from the experiments at the SNS. Here, three different one-dimensional numerical integration solvers from the GNU Scientific Library were modified and implemented to solve four-dimensional integrals. The results of these solvers on a final integrand provided by scientists at the SNS can be compared to the results of other methods, such as quasi-Monte Carlo methods, computing the same integral. A parallelized version of the most efficient method can allow scientists the opportunity to more effectively analyze all experimental data.

High-voltage, high-current, solid-state closing switch

Science.gov (United States)

Focia, Ronald Jeffrey

2017-08-22

A high-voltage, high-current, solid-state closing switch uses a field-effect transistor (e.g., a MOSFET) to trigger a high-voltage stack of thyristors. The switch can have a high hold-off voltage, high current carrying capacity, and high time-rate-of-change of current, di/dt. The fast closing switch can be used in pulsed power applications.

Resonant-state expansion applied to three-dimensional open optical systems

Science.gov (United States)

Doost, M. Â. B.; Langbein, W.; Muljarov, E. Â. A.

2014-07-01

The resonant-state expansion (RSE), a rigorous perturbative method in electrodynamics, is developed for three-dimensional open optical systems. Results are presented using the analytically solvable homogeneous dielectric sphere as unperturbed system. Since any perturbation which breaks the spherical symmetry mixes transverse electric (TE) and transverse magnetic (TM) modes, the RSE is extended here to include TM modes and a zero-frequency pole of the Green's function. We demonstrate the validity of the RSE for TM modes by verifying its convergence towards the exact result for a homogeneous perturbation of the sphere. We then apply the RSE to calculate the modes for a selection of perturbations sequentially reducing the remaining symmetry, given by a change of the dielectric constant of half-sphere and quarter-sphere shape. Since no exact solutions are known for these perturbations, we verify the RSE results by comparing them with the results of state of the art finite element method (FEM) and finite difference in time domain (FDTD) solvers. We find that for the selected perturbations, the RSE provides a significantly higher accuracy than the FEM and FDTD for a given computational effort, demonstrating its potential to supersede presently used methods. We furthermore show that in contrast to presently used methods, the RSE is able to determine the perturbation of a selected group of modes by using a limited basis local to these modes, which can further reduce the computational effort by orders of magnitude.

Computing stationary solutions of the two-dimensional Gross-Pitaevskii equation with deflated continuation

Science.gov (United States)

Charalampidis, E. G.; Kevrekidis, P. G.; Farrell, P. E.

2018-01-01

In this work we employ a recently proposed bifurcation analysis technique, the deflated continuation algorithm, to compute steady-state solitary waveforms in a one-component, two-dimensional nonlinear Schrödinger equation with a parabolic trap and repulsive interactions. Despite the fact that this system has been studied extensively, we discover a wide variety of previously unknown branches of solutions. We analyze the stability of the newly discovered branches and discuss the bifurcations that relate them to known solutions both in the near linear (Cartesian, as well as polar) and in the highly nonlinear regimes. While deflated continuation is not guaranteed to compute the full bifurcation diagram, this analysis is a potent demonstration that the algorithm can discover new nonlinear states and provide insights into the energy landscape of complex high-dimensional Hamiltonian dynamical systems.

Challenges and Approaches to Statistical Design and Inference in High Dimensional Investigations

Science.gov (United States)

Garrett, Karen A.; Allison, David B.

2015-01-01

Summary Advances in modern technologies have facilitated high-dimensional experiments (HDEs) that generate tremendous amounts of genomic, proteomic, and other “omic” data. HDEs involving whole-genome sequences and polymorphisms, expression levels of genes, protein abundance measurements, and combinations thereof have become a vanguard for new analytic approaches to the analysis of HDE data. Such situations demand creative approaches to the processes of statistical inference, estimation, prediction, classification, and study design. The novel and challenging biological questions asked from HDE data have resulted in many specialized analytic techniques being developed. This chapter discusses some of the unique statistical challenges facing investigators studying high-dimensional biology, and describes some approaches being developed by statistical scientists. We have included some focus on the increasing interest in questions involving testing multiple propositions simultaneously, appropriate inferential indicators for the types of questions biologists are interested in, and the need for replication of results across independent studies, investigators, and settings. A key consideration inherent throughout is the challenge in providing methods that a statistician judges to be sound and a biologist finds informative. PMID:19588106

Challenges and approaches to statistical design and inference in high-dimensional investigations.

Science.gov (United States)

Gadbury, Gary L; Garrett, Karen A; Allison, David B

2009-01-01

Advances in modern technologies have facilitated high-dimensional experiments (HDEs) that generate tremendous amounts of genomic, proteomic, and other "omic" data. HDEs involving whole-genome sequences and polymorphisms, expression levels of genes, protein abundance measurements, and combinations thereof have become a vanguard for new analytic approaches to the analysis of HDE data. Such situations demand creative approaches to the processes of statistical inference, estimation, prediction, classification, and study design. The novel and challenging biological questions asked from HDE data have resulted in many specialized analytic techniques being developed. This chapter discusses some of the unique statistical challenges facing investigators studying high-dimensional biology and describes some approaches being developed by statistical scientists. We have included some focus on the increasing interest in questions involving testing multiple propositions simultaneously, appropriate inferential indicators for the types of questions biologists are interested in, and the need for replication of results across independent studies, investigators, and settings. A key consideration inherent throughout is the challenge in providing methods that a statistician judges to be sound and a biologist finds informative.

Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction

Science.gov (United States)

Cui, Tiangang; Marzouk, Youssef; Willcox, Karen

2016-06-01

Two major bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computational cost of forward model evaluations. Yet incomplete or noisy data, the state variation and parameter dependence of the forward model, and correlations in the prior collectively provide useful structure that can be exploited for dimension reduction in this setting-both in the parameter space of the inverse problem and in the state space of the forward model. To this end, we show how to jointly construct low-dimensional subspaces of the parameter space and the state space in order to accelerate the Bayesian solution of the inverse problem. As a byproduct of state dimension reduction, we also show how to identify low-dimensional subspaces of the data in problems with high-dimensional observations. These subspaces enable approximation of the posterior as a product of two factors: (i) a projection of the posterior onto a low-dimensional parameter subspace, wherein the original likelihood is replaced by an approximation involving a reduced model; and (ii) the marginal prior distribution on the high-dimensional complement of the parameter subspace. We present and compare several strategies for constructing these subspaces using only a limited number of forward and adjoint model simulations. The resulting posterior approximations can rapidly be characterized using standard sampling techniques, e.g., Markov chain Monte Carlo. Two numerical examples demonstrate the accuracy and efficiency of our approach: inversion of an integral equation in atmospheric remote sensing, where the data dimension is very high; and the inference of a heterogeneous transmissivity field in a groundwater system, which involves a partial differential equation forward model with high dimensional state and parameters.

Determinable solutions for one-dimensional quantum potentials: scattering, quasi-bound and bound-state problems

International Nuclear Information System (INIS)

Lee, Hwasung; Lee, Y J

2007-01-01

We derive analytic expressions of the recursive solutions to Schroedinger's equation by means of a cutoff-potential technique for one-dimensional piecewise-constant potentials. These solutions provide a method for accurately determining the transmission probabilities as well as the wavefunction in both classically accessible regions and inaccessible regions for any barrier potentials. It is also shown that the energy eigenvalues and the wavefunctions of bound states can be obtained for potential-well structures by exploiting this method. Calculational results of illustrative examples are shown in order to verify this method for treating barrier and potential-well problems

High-dimensional data: p >> n in mathematical statistics and bio-medical applications

OpenAIRE

Van De Geer, Sara A.; Van Houwelingen, Hans C.

2004-01-01

The workshop 'High-dimensional data: p >> n in mathematical statistics and bio-medical applications' was held at the Lorentz Center in Leiden from 9 to 20 September 2002. This special issue of Bernoulli contains a selection of papers presented at that workshop. ¶ The introduction of high-throughput micro-array technology to measure gene-expression levels and the publication of the pioneering paper by Golub et al. (1999) has brought to life a whole new branch of data analysis under the name of...

TripAdvisor^{N-D}: A Tourism-Inspired High-Dimensional Space Exploration Framework with Overview and Detail.

Science.gov (United States)

Nam, Julia EunJu; Mueller, Klaus

2013-02-01

Gaining a true appreciation of high-dimensional space remains difficult since all of the existing high-dimensional space exploration techniques serialize the space travel in some way. This is not so foreign to us since we, when traveling, also experience the world in a serial fashion. But we typically have access to a map to help with positioning, orientation, navigation, and trip planning. Here, we propose a multivariate data exploration tool that compares high-dimensional space navigation with a sightseeing trip. It decomposes this activity into five major tasks: 1) Identify the sights: use a map to identify the sights of interest and their location; 2) Plan the trip: connect the sights of interest along a specifyable path; 3) Go on the trip: travel along the route; 4) Hop off the bus: experience the location, look around, zoom into detail; and 5) Orient and localize: regain bearings in the map. We describe intuitive and interactive tools for all of these tasks, both global navigation within the map and local exploration of the data distributions. For the latter, we describe a polygonal touchpad interface which enables users to smoothly tilt the projection plane in high-dimensional space to produce multivariate scatterplots that best convey the data relationships under investigation. Motion parallax and illustrative motion trails aid in the perception of these transient patterns. We describe the use of our system within two applications: 1) the exploratory discovery of data configurations that best fit a personal preference in the presence of tradeoffs and 2) interactive cluster analysis via cluster sculpting in N-D.

Bit-Table Based Biclustering and Frequent Closed Itemset Mining in High-Dimensional Binary Data

Directory of Open Access Journals (Sweden)

András Király

2014-01-01

Full Text Available During the last decade various algorithms have been developed and proposed for discovering overlapping clusters in high-dimensional data. The two most prominent application fields in this research, proposed independently, are frequent itemset mining (developed for market basket data and biclustering (applied to gene expression data analysis. The common limitation of both methodologies is the limited applicability for very large binary data sets. In this paper we propose a novel and efficient method to find both frequent closed itemsets and biclusters in high-dimensional binary data. The method is based on simple but very powerful matrix and vector multiplication approaches that ensure that all patterns can be discovered in a fast manner. The proposed algorithm has been implemented in the commonly used MATLAB environment and freely available for researchers.

Analysis of Operating Performance and Three Dimensional Magnetic Field of High Voltage Induction Motors with Stator Chute

Directory of Open Access Journals (Sweden)

WANG Qing-shan

2017-06-01

Full Text Available In view of the difficulties on technology of rotor chute in high voltage induction motor，the desig method adopted stator chute structure is put forward． The mathematical model of three dimensional nonlinear transient field for solving stator chute in high voltage induction motor is set up． Through the three dimensional entity model of motor，three dimensional finite element method based on T，ψ － ψ electromagnetic potential is adopted for the analysis and calculation of stator chute in high voltage induction motor under rated condition． The distributions long axial of fundamental wave magnetic field and tooth harmonic wave magnetic field are analyzed after stator chute，and the weakening effects on main tooth harmonic magnetic field are researched． Further more，the comparison analysis of main performance parameters of chute and straight slot is carried out under rated condition． The results show that the electrical performance of stator chute is better than that of straight slot in high voltage induction motor，and the tooth harmonic has been sharply decreased

High-dimensional statistical inference: From vector to matrix

Science.gov (United States)

Zhang, Anru

Statistical inference for sparse signals or low-rank matrices in high-dimensional settings is of significant interest in a range of contemporary applications. It has attracted significant recent attention in many fields including statistics, applied mathematics and electrical engineering. In this thesis, we consider several problems in including sparse signal recovery (compressed sensing under restricted isometry) and low-rank matrix recovery (matrix recovery via rank-one projections and structured matrix completion). The first part of the thesis discusses compressed sensing and affine rank minimization in both noiseless and noisy cases and establishes sharp restricted isometry conditions for sparse signal and low-rank matrix recovery. The analysis relies on a key technical tool which represents points in a polytope by convex combinations of sparse vectors. The technique is elementary while leads to sharp results. It is shown that, in compressed sensing, delta kA 0, delta kA < 1/3 + epsilon, deltak A + thetak,kA < 1 + epsilon, or deltatkA< √(t - 1) / t + epsilon are not sufficient to guarantee the exact recovery of all k-sparse signals for large k. Similar result also holds for matrix recovery. In addition, the conditions delta kA<1/3, deltak A+ thetak,kA<1, delta tkA < √(t - 1)/t and deltarM<1/3, delta rM+ thetar,rM<1, delta trM< √(t - 1)/ t are also shown to be sufficient respectively for stable recovery of approximately sparse signals and low-rank matrices in the noisy case. For the second part of the thesis, we introduce a rank-one projection model for low-rank matrix recovery and propose a constrained nuclear norm minimization method for stable recovery of low-rank matrices in the noisy case. The procedure is adaptive to the rank and robust against small perturbations. Both upper and lower bounds for the estimation accuracy under the Frobenius norm loss are obtained. The proposed estimator is shown to be rate-optimal under certain conditions. The

Ghosts in high dimensional non-linear dynamical systems: The example of the hypercycle

International Nuclear Information System (INIS)

Sardanyes, Josep

2009-01-01

Ghost-induced delayed transitions are analyzed in high dimensional non-linear dynamical systems by means of the hypercycle model. The hypercycle is a network of catalytically-coupled self-replicating RNA-like macromolecules, and has been suggested to be involved in the transition from non-living to living matter in the context of earlier prebiotic evolution. It is demonstrated that, in the vicinity of the saddle-node bifurcation for symmetric hypercycles, the persistence time before extinction, T ε , tends to infinity as n→∞ (being n the number of units of the hypercycle), thus suggesting that the increase in the number of hypercycle units involves a longer resilient time before extinction because of the ghost. Furthermore, by means of numerical analysis the dynamics of three large hypercycle networks is also studied, focusing in their extinction dynamics associated to the ghosts. Such networks allow to explore the properties of the ghosts living in high dimensional phase space with n = 5, n = 10 and n = 15 dimensions. These hypercyclic networks, in agreement with other works, are shown to exhibit self-maintained oscillations governed by stable limit cycles. The bifurcation scenarios for these hypercycles are analyzed, as well as the effect of the phase space dimensionality in the delayed transition phenomena and in the scaling properties of the ghosts near bifurcation threshold

Pure Cs4PbBr6: Highly Luminescent Zero-Dimensional Perovskite Solids

KAUST Repository

Saidaminov, Makhsud I.

2016-09-26

So-called zero-dimensional perovskites, such as Cs4PbBr6, promise outstanding emissive properties. However, Cs4PbBr6 is mostly prepared by melting of precursors that usually leads to a coformation of undesired phases. Here, we report a simple low-temperature solution-processed synthesis of pure Cs4PbBr6 with remarkable emission properties. We found that pure Cs4PbBr6 in solid form exhibits a 45% photoluminescence quantum yield (PLQY), in contrast to its three-dimensional counterpart, CsPbBr3, which exhibits more than 2 orders of magnitude lower PLQY. Such a PLQY of Cs4PbBr6 is significantly higher than that of other solid forms of lower-dimensional metal halide perovskite derivatives and perovskite nanocrystals. We attribute this dramatic increase in PL to the high exciton binding energy, which we estimate to be ∼353 meV, likely induced by the unique Bergerhoff–Schmitz–Dumont-type crystal structure of Cs4PbBr6, in which metal-halide-comprised octahedra are spatially confined. Our findings bring this class of perovskite derivatives to the forefront of color-converting and light-emitting applications.

Qualities of Wigner function and its applications to one-dimensional infinite potential and one-dimensional harmonic oscillator

International Nuclear Information System (INIS)

Xu Hao; Shi Tianjun

2011-01-01

In this article,the qualities of Wigner function and the corresponding stationary perturbation theory are introduced and applied to one-dimensional infinite potential well and one-dimensional harmonic oscillator, and then the particular Wigner function of one-dimensional infinite potential well is specified and a special constriction effect in its pure state Wigner function is discovered, to which,simultaneously, a detailed and reasonable explanation is elaborated from the perspective of uncertainty principle. Ultimately, the amendment of Wigner function and energy of one-dimensional infinite potential well and one-dimensional harmonic oscillator under perturbation are calculated according to stationary phase space perturbation theory. (authors)

A comprehensive analysis of earthquake damage patterns using high dimensional model representation feature selection

Science.gov (United States)

Taşkin Kaya, Gülşen

2013-10-01

Recently, earthquake damage assessment using satellite images has been a very popular ongoing research direction. Especially with the availability of very high resolution (VHR) satellite images, a quite detailed damage map based on building scale has been produced, and various studies have also been conducted in the literature. As the spatial resolution of satellite images increases, distinguishability of damage patterns becomes more cruel especially in case of using only the spectral information during classification. In order to overcome this difficulty, textural information needs to be involved to the classification to improve the visual quality and reliability of damage map. There are many kinds of textural information which can be derived from VHR satellite images depending on the algorithm used. However, extraction of textural information and evaluation of them have been generally a time consuming process especially for the large areas affected from the earthquake due to the size of VHR image. Therefore, in order to provide a quick damage map, the most useful features describing damage patterns needs to be known in advance as well as the redundant features. In this study, a very high resolution satellite image after Iran, Bam earthquake was used to identify the earthquake damage. Not only the spectral information, textural information was also used during the classification. For textural information, second order Haralick features were extracted from the panchromatic image for the area of interest using gray level co-occurrence matrix with different size of windows and directions. In addition to using spatial features in classification, the most useful features representing the damage characteristic were selected with a novel feature selection method based on high dimensional model representation (HDMR) giving sensitivity of each feature during classification. The method called HDMR was recently proposed as an efficient tool to capture the input

Explorations on High Dimensional Landscapes: Spin Glasses and Deep Learning

Science.gov (United States)

Sagun, Levent

This thesis deals with understanding the structure of high-dimensional and non-convex energy landscapes. In particular, its focus is on the optimization of two classes of functions: homogeneous polynomials and loss functions that arise in machine learning. In the first part, the notion of complexity of a smooth, real-valued function is studied through its critical points. Existing theoretical results predict that certain random functions that are defined on high dimensional domains have a narrow band of values whose pre-image contains the bulk of its critical points. This section provides empirical evidence for convergence of gradient descent to local minima whose energies are near the predicted threshold justifying the existing asymptotic theory. Moreover, it is empirically shown that a similar phenomenon may hold for deep learning loss functions. Furthermore, there is a comparative analysis of gradient descent and its stochastic version showing that in high dimensional regimes the latter is a mere speedup. The next study focuses on the halting time of an algorithm at a given stopping condition. Given an algorithm, the normalized fluctuations of the halting time follow a distribution that remains unchanged even when the input data is sampled from a new distribution. Two qualitative classes are observed: a Gumbel-like distribution that appears in Google searches, human decision times, and spin glasses and a Gaussian-like distribution that appears in conjugate gradient method, deep learning with MNIST and random input data. Following the universality phenomenon, the Hessian of the loss functions of deep learning is studied. The spectrum is seen to be composed of two parts, the bulk which is concentrated around zero, and the edges which are scattered away from zero. Empirical evidence is presented for the bulk indicating how over-parametrized the system is, and for the edges that depend on the input data. Furthermore, an algorithm is proposed such that it would

Selecting Optimal Feature Set in High-Dimensional Data by Swarm Search

Directory of Open Access Journals (Sweden)

Simon Fong

2013-01-01

Full Text Available Selecting the right set of features from data of high dimensionality for inducing an accurate classification model is a tough computational challenge. It is almost a NP-hard problem as the combinations of features escalate exponentially as the number of features increases. Unfortunately in data mining, as well as other engineering applications and bioinformatics, some data are described by a long array of features. Many feature subset selection algorithms have been proposed in the past, but not all of them are effective. Since it takes seemingly forever to use brute force in exhaustively trying every possible combination of features, stochastic optimization may be a solution. In this paper, we propose a new feature selection scheme called Swarm Search to find an optimal feature set by using metaheuristics. The advantage of Swarm Search is its flexibility in integrating any classifier into its fitness function and plugging in any metaheuristic algorithm to facilitate heuristic search. Simulation experiments are carried out by testing the Swarm Search over some high-dimensional datasets, with different classification algorithms and various metaheuristic algorithms. The comparative experiment results show that Swarm Search is able to attain relatively low error rates in classification without shrinking the size of the feature subset to its minimum.

Stable Graphene-Two-Dimensional Multiphase Perovskite Heterostructure Phototransistors with High Gain.

Science.gov (United States)

Shao, Yuchuan; Liu, Ye; Chen, Xiaolong; Chen, Chen; Sarpkaya, Ibrahim; Chen, Zhaolai; Fang, Yanjun; Kong, Jaemin; Watanabe, Kenji; Taniguchi, Takashi; Taylor, André; Huang, Jinsong; Xia, Fengnian

2017-12-13

Recently, two-dimensional (2D) organic-inorganic perovskites emerged as an alternative material for their three-dimensional (3D) counterparts in photovoltaic applications with improved moisture resistance. Here, we report a stable, high-gain phototransistor consisting of a monolayer graphene on hexagonal boron nitride (hBN) covered by a 2D multiphase perovskite heterostructure, which was realized using a newly developed two-step ligand exchange method. In this phototransistor, the multiple phases with varying bandgap in 2D perovskite thin films are aligned for the efficient electron-hole pair separation, leading to a high responsivity of ∼10 5 A W -1 at 532 nm. Moreover, the designed phase alignment method aggregates more hydrophobic butylammonium cations close to the upper surface of the 2D perovskite thin film, preventing the permeation of moisture and enhancing the device stability dramatically. In addition, faster photoresponse and smaller 1/f noise observed in the 2D perovskite phototransistors indicate a smaller density of deep hole traps in the 2D perovskite thin film compared with their 3D counterparts. These desirable properties not only improve the performance of the phototransistor, but also provide a new direction for the future enhancement of the efficiency of 2D perovskite photovoltaics.

Strongly correlated quasi-one-dimensional bands: Ground states, optical absorption, and phonons

International Nuclear Information System (INIS)

Campbell, D.K.; Gammel, J.T.; Loh, E.Y. Jr.

1989-01-01

Using the Lanczos method for exact diagonalization on systems up to 14 sites, combined with a novel ''phase randomization'' technique for extracting more information from these small systems, we investigate several aspects of the one-dimensional Peierls-Hubbard Hamiltonian, in the context of trans-polyacetylene: the dependence of the ground state dimerization on the strength of the electron-electron interactions, including the effects of ''off-diagonal'' Coulomb terms generally ignored in the Hubbard model; the phonon vibrational frequencies and dispersion relations, and the optical absorption properties, including the spectrum of absorptions as a function of photon energy. These three different observables provide considerable insight into the effects of electron-electron interactions on the properties of real materials and thus into the nature of strongly correlated electron systems. 29 refs., 11 figs

Generalized coherent states for the Coulomb problem in one dimension

International Nuclear Information System (INIS)

Nouri, S.

2002-01-01

A set of generalized coherent states for the one-dimensional Coulomb problem in coordinate representation is constructed. At first, we obtain a mapping for proper transformation of the one-dimensional Coulomb problem into a nonrotating four-dimensional isotropic harmonic oscillator in the hyperspherical space, and the generalized coherent states for the one-dimensional Coulomb problem is then obtained in exact closed form. This exactly soluble model can provide an adequate means for a quantum coherency description of the Coulomb problem in one dimension, sample for coherent aspects of the exciton model in one-dimension example in high-temperature superconductivity, semiconductors, and polymers. Also, it can be useful for investigating the coherent scattering of the Coulomb particles in one dimension

Characterization of differentially expressed genes using high-dimensional co-expression networks

DEFF Research Database (Denmark)

Coelho Goncalves de Abreu, Gabriel; Labouriau, Rodrigo S.

2010-01-01

We present a technique to characterize differentially expressed genes in terms of their position in a high-dimensional co-expression network. The set-up of Gaussian graphical models is used to construct representations of the co-expression network in such a way that redundancy and the propagation...... that allow to make effective inference in problems with high degree of complexity (e.g. several thousands of genes) and small number of observations (e.g. 10-100) as typically occurs in high throughput gene expression studies. Taking advantage of the internal structure of decomposable graphical models, we...... construct a compact representation of the co-expression network that allows to identify the regions with high concentration of differentially expressed genes. It is argued that differentially expressed genes located in highly interconnected regions of the co-expression network are less informative than...

Microwave-Induced Magneto-Oscillations and Signatures of Zero-Resistance States in Phonon-Drag Voltage in Two-Dimensional Electron Systems.

Science.gov (United States)

Levin, A D; Momtaz, Z S; Gusev, G M; Raichev, O E; Bakarov, A K

2015-11-13

We observe the phonon-drag voltage oscillations correlating with the resistance oscillations under microwave irradiation in a two-dimensional electron gas in perpendicular magnetic field. This phenomenon is explained by the influence of dissipative resistivity modified by microwaves on the phonon-drag voltage perpendicular to the phonon flux. When the lowest-order resistance minima evolve into zero-resistance states, the phonon-drag voltage demonstrates sharp features suggesting that current domains associated with these states can exist in the absence of external dc driving.

Three-dimensional printing of stem cell-laden hydrogels submerged in a hydrophobic high-density fluid

International Nuclear Information System (INIS)

Duarte Campos, Daniela F; Blaeser, Andreas; Weber, Michael; Fischer, Horst; Jäkel, Jörg; Neuss, Sabine; Jahnen-Dechent, Wilhelm

2013-01-01

Over the last decade, bioprinting technologies have begun providing important tissue engineering strategies for regenerative medicine and organ transplantation. The major drawback of past approaches has been poor or inadequate material-printing device and substrate combinations, as well as the relatively small size of the printed construct. Here, we hypothesise that cell-laden hydrogels can be printed when submerged in perfluorotributylamine (C 12 F 27 N), a hydrophobic high-density fluid, and that these cells placed within three-dimensional constructs remain viable allowing for cell proliferation and production of extracellular matrix. Human mesenchymal stem cells and MG-63 cells were encapsulated into agarose hydrogels, and subsequently printed in high aspect ratio in three dimensional structures that were supported in high density fluorocarbon. Three-dimensional structures with various shapes and sizes were manufactured and remained stable for more than six months. Live/dead and DAPI stainings showed viable cells 24 h after the printing process, as well as after 21 days in culture. Histological and immunohistochemical analyses after 14 and 21 days revealed viable cells with marked matrix production and signs of proliferation. The compressive strength values of the printed gels consequently increased during the two weeks in culture, revealing encouraging results for future applications in regenerative medicine. (paper)

Variable dimensionality in the uranium fluoride/2-methyl-piperazine system: Synthesis and structures of UFO-5, -6, and -7; Zero-, one-, and two-dimensional materials with unprecedented topologies

International Nuclear Information System (INIS)

Francis, R.J.; Halasyamani, P.S.; Bee, J.S.; O'Hare, D.

1999-01-01

Recently, low temperature (T < 300 C) hydrothermal reactions of inorganic precursors in the presence of organic cations have proven highly productive for the synthesis of novel solid-state materials. Interest in these materials is driven by the astonishingly diverse range of structures produced, as well as by their many potential materials chemistry applications. This report describes the high yield, phase pure hydrothermal syntheses of three new uranium fluoride phases with unprecedented structure types. Through the systematic control of the synthesis conditions the authors have successfully controlled the architecture and dimensionality of the phase formed and selectively synthesized novel zero-, one-, and two-dimensional materials

An Improved Ensemble Learning Method for Classifying High-Dimensional and Imbalanced Biomedicine Data.

Science.gov (United States)

Yu, Hualong; Ni, Jun

2014-01-01

Training classifiers on skewed data can be technically challenging tasks, especially if the data is high-dimensional simultaneously, the tasks can become more difficult. In biomedicine field, skewed data type often appears. In this study, we try to deal with this problem by combining asymmetric bagging ensemble classifier (asBagging) that has been presented in previous work and an improved random subspace (RS) generation strategy that is called feature subspace (FSS). Specifically, FSS is a novel method to promote the balance level between accuracy and diversity of base classifiers in asBagging. In view of the strong generalization capability of support vector machine (SVM), we adopt it to be base classifier. Extensive experiments on four benchmark biomedicine data sets indicate that the proposed ensemble learning method outperforms many baseline approaches in terms of Accuracy, F-measure, G-mean and AUC evaluation criterions, thus it can be regarded as an effective and efficient tool to deal with high-dimensional and imbalanced biomedical data.

Flow Visualization of Three-Dimensionality Inside the 12 cc Penn State Pulsatile Pediatric Ventricular Assist Device

OpenAIRE

Roszelle, Breigh N.; Deutsch, Steven; Manning, Keefe B.

2010-01-01

In order to aid the ongoing concern of limited organ availability for pediatric heart transplants, Penn State has continued development of a pulsatile Pediatric Ventricular Assist Device (PVAD). Initial studies of the PVAD observed an increase in thrombus formation due to differences in flow field physics when compared to adult sized devices, which included a higher degree of three-dimensionality. This unique flow field brings into question the use of 2D planar particle image velocimetry (PIV...

Quality and efficiency in high dimensional Nearest neighbor search

KAUST Repository

Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos

2009-01-01

Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational database, and (ii) its query cost should grow sub-linearly with the dataset size, regardless of the data and query distributions. Despite the bulk of NN literature, no solution fulfills both requirements, except locality sensitive hashing (LSH). The existing LSH implementations are either rigorous or adhoc. Rigorous-LSH ensures good quality of query results, but requires expensive space and query cost. Although adhoc-LSH is more efficient, it abandons quality control, i.e., the neighbor it outputs can be arbitrarily bad. As a result, currently no method is able to ensure both quality and efficiency simultaneously in practice. Motivated by this, we propose a new access method called the locality sensitive B-tree (LSB-tree) that enables fast highdimensional NN search with excellent quality. The combination of several LSB-trees leads to a structure called the LSB-forest that ensures the same result quality as rigorous-LSH, but reduces its space and query cost dramatically. The LSB-forest also outperforms adhoc-LSH, even though the latter has no quality guarantee. Besides its appealing theoretical properties, the LSB-tree itself also serves as an effective index that consumes linear space, and supports efficient updates. Our extensive experiments confirm that the LSB-tree is faster than (i) the state of the art of exact NN search by two orders of magnitude, and (ii) the best (linear-space) method of approximate retrieval by an order of magnitude, and at the same time, returns neighbors with much better quality. © 2009 ACM.

Inferring biological tasks using Pareto analysis of high-dimensional data.

Science.gov (United States)

Hart, Yuval; Sheftel, Hila; Hausser, Jean; Szekely, Pablo; Ben-Moshe, Noa Bossel; Korem, Yael; Tendler, Avichai; Mayo, Avraham E; Alon, Uri

2015-03-01

We present the Pareto task inference method (ParTI; http://www.weizmann.ac.il/mcb/UriAlon/download/ParTI) for inferring biological tasks from high-dimensional biological data. Data are described as a polytope, and features maximally enriched closest to the vertices (or archetypes) allow identification of the tasks the vertices represent. We demonstrate that human breast tumors and mouse tissues are well described by tetrahedrons in gene expression space, with specific tumor types and biological functions enriched at each of the vertices, suggesting four key tasks.

Transforming high-dimensional potential energy surfaces into sum-of-products form using Monte Carlo methods

Science.gov (United States)

Schröder, Markus; Meyer, Hans-Dieter

2017-08-01

We propose a Monte Carlo method, "Monte Carlo Potfit," for transforming high-dimensional potential energy surfaces evaluated on discrete grid points into a sum-of-products form, more precisely into a Tucker form. To this end we use a variational ansatz in which we replace numerically exact integrals with Monte Carlo integrals. This largely reduces the numerical cost by avoiding the evaluation of the potential on all grid points and allows a treatment of surfaces up to 15-18 degrees of freedom. We furthermore show that the error made with this ansatz can be controlled and vanishes in certain limits. We present calculations on the potential of HFCO to demonstrate the features of the algorithm. To demonstrate the power of the method, we transformed a 15D potential of the protonated water dimer (Zundel cation) in a sum-of-products form and calculated the ground and lowest 26 vibrationally excited states of the Zundel cation with the multi-configuration time-dependent Hartree method.

High-Dimensional Exploratory Item Factor Analysis by a Metropolis-Hastings Robbins-Monro Algorithm

Science.gov (United States)

Cai, Li

2010-01-01

A Metropolis-Hastings Robbins-Monro (MH-RM) algorithm for high-dimensional maximum marginal likelihood exploratory item factor analysis is proposed. The sequence of estimates from the MH-RM algorithm converges with probability one to the maximum likelihood solution. Details on the computer implementation of this algorithm are provided. The…

High-resolution and high-throughput multichannel Fourier transform spectrometer with two-dimensional interferogram warping compensation

Science.gov (United States)

Watanabe, A.; Furukawa, H.

2018-04-01

The resolution of multichannel Fourier transform (McFT) spectroscopy is insufficient for many applications despite its extreme advantage of high throughput. We propose an improved configuration to realise both performance using a two-dimensional area sensor. For the spectral resolution, we obtained the interferogram of a larger optical path difference by shifting the area sensor without altering any optical components. The non-linear phase error of the interferometer was successfully corrected using a phase-compensation calculation. Warping compensation was also applied to realise a higher throughput to accumulate the signal between vertical pixels. Our approach significantly improved the resolution and signal-to-noise ratio by factors of 1.7 and 34, respectively. This high-resolution and high-sensitivity McFT spectrometer will be useful for detecting weak light signals such as those in non-invasive diagnosis.

High-speed three-dimensional plasma temperature determination of axially symmetric free-burning arcs

International Nuclear Information System (INIS)

Bachmann, B; Ekkert, K; Bachmann, J-P; Marques, J-L; Schein, J; Kozakov, R; Gött, G; Schöpp, H; Uhrlandt, D

2013-01-01

In this paper we introduce an experimental technique that allows for high-speed, three-dimensional determination of electron density and temperature in axially symmetric free-burning arcs. Optical filters with narrow spectral bands of 487.5–488.5 nm and 689–699 nm are utilized to gain two-dimensional spectral information of a free-burning argon tungsten inert gas arc. A setup of mirrors allows one to image identical arc sections of the two spectral bands onto a single camera chip. Two-different Abel inversion algorithms have been developed to reconstruct the original radial distribution of emission coefficients detected with each spectral window and to confirm the results. With the assumption of local thermodynamic equilibrium we calculate emission coefficients as a function of temperature by application of the Saha equation, the ideal gas law, the quasineutral gas condition and the NIST compilation of spectral lines. Ratios of calculated emission coefficients are compared with measured ones yielding local plasma temperatures. In the case of axial symmetry the three-dimensional plasma temperature distributions have been determined at dc currents of 100, 125, 150 and 200 A yielding temperatures up to 20000 K in the hot cathode region. These measurements have been validated by four different techniques utilizing a high-resolution spectrometer at different positions in the plasma. Plasma temperatures show good agreement throughout the different methods. Additionally spatially resolved transient plasma temperatures have been measured of a dc pulsed process employing a high-speed frame rate of 33000 frames per second showing the modulation of the arc isothermals with time and providing information about the sensitivity of the experimental approach. (paper)

Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.

Science.gov (United States)

Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros

2018-05-01

We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.

Tunable Majorana corner states in a two-dimensional second-order topological superconductor induced by magnetic fields

Science.gov (United States)

Zhu, Xiaoyu

2018-05-01

A two-dimensional second-order topological superconductor exhibits a finite gap in both bulk and edges, with the nontrivial topology manifesting itself through Majorana zero modes localized at the corners, i.e., Majorana corner states. We investigate a time-reversal-invariant topological superconductor in two dimensions and demonstrate that an in-plane magnetic field could transform it into a second-order topological superconductor. A detailed analysis reveals that the magnetic field gives rise to mass terms which take distinct values among the edges, and Majorana corner states naturally emerge at the intersection of two adjacent edges with opposite masses. With the rotation of the magnetic field, Majorana corner states localized around the boundary may hop from one corner to a neighboring one and eventually make a full circle around the system when the field rotates by 2 π . In the end, we briefly discuss physical realizations of this system.

Metallic few-layered VS2 ultrathin nanosheets: high two-dimensional conductivity for in-plane supercapacitors.

Science.gov (United States)

Feng, Jun; Sun, Xu; Wu, Changzheng; Peng, Lele; Lin, Chenwen; Hu, Shuanglin; Yang, Jinlong; Xie, Yi

2011-11-09

With the rapid development of portable electronics, such as e-paper and other flexible devices, practical power sources with ultrathin geometries become an important prerequisite, in which supercapacitors with in-plane configurations are recently emerging as a favorable and competitive candidate. As is known, electrode materials with two-dimensional (2D) permeable channels, high-conductivity structural scaffolds, and high specific surface areas are the indispensible requirements for the development of in-plane supercapacitors with superior performance, while it is difficult for the presently available inorganic materials to make the best in all aspects. In this sense, vanadium disulfide (VS(2)) presents an ideal material platform due to its synergic properties of metallic nature and exfoliative characteristic brought by the conducting S-V-S layers stacked up by weak van der Waals interlayer interactions, offering great potential as high-performance in-plane supercapacitor electrodes. Herein, we developed a unique ammonia-assisted strategy to exfoliate bulk VS(2) flakes into ultrathin VS(2) nanosheets stacked with less than five S-V-S single layers, representing a brand new two-dimensional material having metallic behavior aside from graphene. Moreover, highly conductive VS(2) thin films were successfully assembled for constructing the electrodes of in-plane supercapacitors. As is expected, a specific capacitance of 4760 μF/cm(2) was realized here in a 150 nm in-plane configuration, of which no obvious degradation was observed even after 1000 charge/discharge cycles, offering as a new in-plane supercapacitor with high performance based on quasi-two-dimensional materials.

Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems?

Science.gov (United States)

Safaei, S.; Haghnegahdar, A.; Razavi, S.

2016-12-01

Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.

Comparison between arthroscopy and 3 dimensional double echo steady state 3D-DESS sequences in magnetic resonance imaging of internal derangements of the knee

International Nuclear Information System (INIS)

Dongola, Nagwa A.; Gishen, Philip

2004-01-01

This study was performed with the aim of evaluating the usefulness of 3 dimensional double-echo steady state sequences in examining the internal derangements of the knee. Arthroscopy was used as a referral standard. The study was performed in the Radiology and Arthroscopy Departments of Kings College Hospital, London, United Kingdom, during a 6-month period from January 1997 to June 1997. All patients who had knee magnetic resonance imaging within 3 months of arthroscopy were retrospectively studied. Thirty-three patients fulfilled these criteria and were selected. Three dimensional double-echo steady state sequences produced sensitivity for detecting meniscal tears of 87.5% for medial menisci (MM) and 75% for lateral menisci (LM). Specificity was 76% for MM and 96% for LM; positive predictive value (PPV) was 46.1% for MM and 85.7% for LM and negative predictive value (NPV) of 95% for MM and 96% for LM. The sensitivity for the anterior cruciate ligament was 83.3%, specificity was 77.7%, PPV was 45.4% and NPV was 95.4%. Three dimensional double-echo steady state sequences are useful in evaluating internal derangement of the knee, especially in advanced cartilage lesions. (author)

Usefullness of three-dimensional templating software to quantify the contact state between implant and femur in total hip arthroplasty.

Science.gov (United States)

Inoue, Daisuke; Kabata, Tamon; Maeda, Toru; Kajino, Yoshitomo; Fujita, Kenji; Hasegawa, Kazuhiro; Yamamoto, Takashi; Takagi, Tomoharu; Ohmori, Takaaki; Tsuchiya, Hiroyuki

2015-12-01

It would be ideal if surgeons could precisely confirm whether the planned femoral component achieves the best fit and fill of implant and femur. However, the cortico-cancellous interfaces can be difficult to standardize using plain radiography, and therefore, determining the contact state is a subjective decision by the examiner. Few reports have described the use of CT-based three-dimensional templating software to quantify the contact state of stem and femur in detail. The purpose of this study was to use three-dimensional templating software to quantify the implant-femur contact state and develop a technique to analyze the initial fixation pattern of a cementless femoral stem. We conducted a retrospective review of 55 hips in 53 patients using a short proximal fit-and-fill anatomical stem (APS Natural-Hip™ System). All femurs were examined by density mapping which can visualize and digitize the contact state. We evaluated the contact state of implant and femur by using density mapping. The varus group (cases that had changed varus 2° by 3 months after surgery) consisted of 11 hips. The varus group showed no significant difference with regard to cortical contact in the proximal medial portion (Gruen 7), but the contact area in the distal portion (Gruen 3 and Gruen 5) was significantly lower than that of non-varus group. Density mapping showed that the stem only has to be press-fit to the medial calcar, but also must fill the distal portion of the implant in order to achieve the ideal contact state. Our results indicated that quantifying the contact state of implant and femur by using density mapping is a useful technique to accurately analyze the fixation pattern of a cementless femoral stem.

Bound states of Dipolar Bosons in One-dimensional Systems

DEFF Research Database (Denmark)

G. Volosniev, A.; R. Armstrong, J.; V. Fedorov, D.

2013-01-01

that in the weakly-coupled limit the inter-tube interaction is similar to a zero-range term with a suitable rescaled strength. This allows us to address the corresponding many-body physics of the system by constructing a model where bound chains with one molecule in each tube are the effective degrees of freedom......We consider one-dimensional tubes containing bosonic polar molecules. The long-range dipole-dipole interactions act both within a single tube and between different tubes. We consider arbitrary values of the externally aligned dipole moments with respect to the symmetry axis of the tubes. The few....... This model can be mapped onto one-dimensional Hamiltonians for which exact solutions are known....

Hierarchical one-dimensional ammonium nickel phosphate microrods for high-performance pseudocapacitors

CSIR Research Space (South Africa)

Raju, K

2015-12-01

Full Text Available :17629 | DOI: 10.1038/srep17629 www.nature.com/scientificreports Hierarchical One-Dimensional Ammonium Nickel Phosphate Microrods for High-Performance Pseudocapacitors Kumar Raju1 & Kenneth I. Ozoemena1,2 High-performance electrochemical capacitors... OPEN w w w . n a t u r e . c o m / s c i e n t i f i c r e p o r t s / 2S C I E N T I F I C REPORTS | 5:17629 | DOI: 10.1038/srep17629 Hierarchical 1-D and 2-D materials maximize the supercapacitive properties due to their unique ability to permit ion...

The von Neumann entanglement entropy for Wigner-crystal states in one dimensional N-particle systems

International Nuclear Information System (INIS)

Kościk, Przemysław

2015-01-01

We study one-dimensional systems of N particles in a one-dimensional harmonic trap with an inverse power law interaction ∼|x| −d . Within the framework of the harmonic approximation we derive, in the strong interaction limit, the Schmidt decomposition of the one-particle reduced density matrix and investigate the nature of the degeneracy appearing in its spectrum. Furthermore, the ground-state asymptotic occupancies and their natural orbitals are derived in closed analytic form, which enables their easy determination for a wide range of values of N. A closed form asymptotic expression for the von Neumann entanglement entropy is also provided and its dependence on N is discussed for the systems with d=1 (charged particles) and with d=3 (dipolar particles). - Highlights: • We study confined systems of N particles with an inverse power law interaction. • We apply the harmonic approximation to the systems. • We derive closed form expressions for the asymptotic von Neumann entropy. • The asymptotic von Neumann entropy grows monotonically as N increases

High-resolution non-destructive three-dimensional imaging of integrated circuits.

Science.gov (United States)

Holler, Mirko; Guizar-Sicairos, Manuel; Tsai, Esther H R; Dinapoli, Roberto; Müller, Elisabeth; Bunk, Oliver; Raabe, Jörg; Aeppli, Gabriel

2017-03-15

Modern nanoelectronics has advanced to a point at which it is impossible to image entire devices and their interconnections non-destructively because of their small feature sizes and the complex three-dimensional structures resulting from their integration on a chip. This metrology gap implies a lack of direct feedback between design and manufacturing processes, and hampers quality control during production, shipment and use. Here we demonstrate that X-ray ptychography-a high-resolution coherent diffractive imaging technique-can create three-dimensional images of integrated circuits of known and unknown designs with a lateral resolution in all directions down to 14.6 nanometres. We obtained detailed device geometries and corresponding elemental maps, and show how the devices are integrated with each other to form the chip. Our experiments represent a major advance in chip inspection and reverse engineering over the traditional destructive electron microscopy and ion milling techniques. Foreseeable developments in X-ray sources, optics and detectors, as well as adoption of an instrument geometry optimized for planar rather than cylindrical samples, could lead to a thousand-fold increase in efficiency, with concomitant reductions in scan times and voxel sizes.

High-resolution non-destructive three-dimensional imaging of integrated circuits

Science.gov (United States)

Holler, Mirko; Guizar-Sicairos, Manuel; Tsai, Esther H. R.; Dinapoli, Roberto; Müller, Elisabeth; Bunk, Oliver; Raabe, Jörg; Aeppli, Gabriel

2017-03-01

Modern nanoelectronics has advanced to a point at which it is impossible to image entire devices and their interconnections non-destructively because of their small feature sizes and the complex three-dimensional structures resulting from their integration on a chip. This metrology gap implies a lack of direct feedback between design and manufacturing processes, and hampers quality control during production, shipment and use. Here we demonstrate that X-ray ptychography—a high-resolution coherent diffractive imaging technique—can create three-dimensional images of integrated circuits of known and unknown designs with a lateral resolution in all directions down to 14.6 nanometres. We obtained detailed device geometries and corresponding elemental maps, and show how the devices are integrated with each other to form the chip. Our experiments represent a major advance in chip inspection and reverse engineering over the traditional destructive electron microscopy and ion milling techniques. Foreseeable developments in X-ray sources, optics and detectors, as well as adoption of an instrument geometry optimized for planar rather than cylindrical samples, could lead to a thousand-fold increase in efficiency, with concomitant reductions in scan times and voxel sizes.

Searching for highly entangled multi-qubit states

International Nuclear Information System (INIS)

Brown, Iain D K; Stepney, Susan; Sudbery, Anthony; Braunstein, Samuel L

2005-01-01

We present a simple numerical optimization procedure to search for highly entangled states of 2, 3, 4 and 5 qubits. We develop a computationally tractable entanglement measure based on the negative partial transpose criterion, which can be applied to quantum systems of an arbitrary number of qubits. The search algorithm attempts to optimize this entanglement cost function to find the maximal entanglement in a quantum system. We present highly entangled 4-qubit and 5-qubit states discovered by this search. We show that the 4-qubit state is not quite as entangled, according to two separate measures, as the conjectured maximally entangled Higuchi-Sudbery state. Using this measure, these states are more highly entangled than the 4-qubit and 5-qubit GHZ states. We also present a conjecture about the NPT measure, inspired by some of our numerical results, that the single-qubit reduced states of maximally entangled states are all totally mixed

Three-Dimensional Numerical Analysis of an Operating Helical Rotor Pump at High Speeds and High Pressures including Cavitation

Directory of Open Access Journals (Sweden)

Zhou Yang

2017-01-01

Full Text Available High pressures, high speeds, low noise and miniaturization is the direction of development in hydraulic pump. According to the development trend, an operating helical rotor pump (HRP at high speeds and high pressures has been designed and produced, which rotational speed can reach 12000r/min and outlet pressure is as high as 25MPa. Three-dimensional simulation with and without cavitation inside the HRP is completed by the means of the computational fluid dynamics (CFD in this paper, which contributes to understand the complex fluid flow inside it. Moreover, the influences of the rotational speeds of the HRP with and without cavitation has been simulated at 25MPa.

Ground states and formal duality relations in the Gaussian core model

NARCIS (Netherlands)

Cohn, H.; Kumar, A.; Schürmann, A.

2009-01-01

We study dimensional trends in ground states for soft-matter systems. Specifically, using a high-dimensional version of Parrinello-Rahman dynamics, we investigate the behavior of the Gaussian core model in up to eight dimensions. The results include unexpected geometric structures, with surprising

Low-resistance gateless high electron mobility transistors using three-dimensional inverted pyramidal AlGaN/GaN surfaces

International Nuclear Information System (INIS)

So, Hongyun; Senesky, Debbie G.

2016-01-01

In this letter, three-dimensional gateless AlGaN/GaN high electron mobility transistors (HEMTs) were demonstrated with 54% reduction in electrical resistance and 73% increase in surface area compared with conventional gateless HEMTs on planar substrates. Inverted pyramidal AlGaN/GaN surfaces were microfabricated using potassium hydroxide etched silicon with exposed (111) surfaces and metal-organic chemical vapor deposition of coherent AlGaN/GaN thin films. In addition, electrical characterization of the devices showed that a combination of series and parallel connections of the highly conductive two-dimensional electron gas along the pyramidal geometry resulted in a significant reduction in electrical resistance at both room and high temperatures (up to 300 °C). This three-dimensional HEMT architecture can be leveraged to realize low-power and reliable power electronics, as well as harsh environment sensors with increased surface area

Low-resistance gateless high electron mobility transistors using three-dimensional inverted pyramidal AlGaN/GaN surfaces

Energy Technology Data Exchange (ETDEWEB)

So, Hongyun, E-mail: hyso@stanford.edu [Department of Aeronautics and Astronautics, Stanford University, Stanford, California 94305 (United States); Senesky, Debbie G. [Department of Aeronautics and Astronautics, Stanford University, Stanford, California 94305 (United States); Department of Electrical Engineering, Stanford University, Stanford, California 94305 (United States)

2016-01-04

In this letter, three-dimensional gateless AlGaN/GaN high electron mobility transistors (HEMTs) were demonstrated with 54% reduction in electrical resistance and 73% increase in surface area compared with conventional gateless HEMTs on planar substrates. Inverted pyramidal AlGaN/GaN surfaces were microfabricated using potassium hydroxide etched silicon with exposed (111) surfaces and metal-organic chemical vapor deposition of coherent AlGaN/GaN thin films. In addition, electrical characterization of the devices showed that a combination of series and parallel connections of the highly conductive two-dimensional electron gas along the pyramidal geometry resulted in a significant reduction in electrical resistance at both room and high temperatures (up to 300 °C). This three-dimensional HEMT architecture can be leveraged to realize low-power and reliable power electronics, as well as harsh environment sensors with increased surface area.