The problem of expanding a density operator $\ensuremath{\rho}$ in forms that simplify the evaluation of important classes of quantum-mechanical expectation values is studied. The weight function $P(\ensuremath{\alpha})$ of the $P$ representation, the Wigner distribution $W(\ensuremath{\alpha})$, and the function $〈\ensuremath{\alpha}|\ensuremath{\rho}|\ensuremath{\alpha}〉$, where $|\ensuremath{\alpha}〉$ is a coherent state, are discussed from a unified point of view. Each of these quasiprobability distributions is examined as the expectation value of a Hermitian operator, as the weight function of an integral representation for the density operator and as the function associated with the density operator by one of the operator-function correspondences defined in the preceding paper. The weight function $P(\ensuremath{\alpha})$ of the $P$ representation is shown to be the expectation value of a Hermitian operator all of whose eigenvalues are infinite. The existence of the function $P(\ensuremath{\alpha})$ as an infinitely differentiable function is found to be equivalent to the existence of a well-defined antinormally ordered series expansion for the density operator in powers of the annihilation and creation operators $a$ and ${a}^{\ifmmode\dagger\else\textdagger\fi{}}$. The Wigner distribution $W(\ensuremath{\alpha})$ is shown to be a continuous, uniformly bounded, square-integrable weight function for an integral expansion of the density operator and to be the function associated with the symmetrically ordered power-series expansion of the density operator. The function $〈\ensuremath{\alpha}|\ensuremath{\rho}|\ensuremath{\alpha}〉$, which is infinitely differentiable, corresponds to the normally ordered form of the density operator. Its use as a weight function in an integral expansion of the density operator is shown to involve singularities that are closely related to those which occur in the $P$ representation. A parametrized integral expansion of the density operator is introduced in which the weight function $W(\ensuremath{\alpha},s)$ may be identified with the weight function $P(\ensuremath{\alpha})$ of the $P$ representation, with the Wigner distribution $W(\ensuremath{\alpha})$, and with the function $〈\ensuremath{\alpha}|\ensuremath{\rho}|\ensuremath{\alpha}〉$ when the order parameter $s$ assumes the values $s=+1, 0, \ensuremath{-}1$, respectively. The function $W(\ensuremath{\alpha},s)$ is shown to be the expectation value of the ordered operator analog of the $\ensuremath{\delta}$ function defined in the preceding paper. This operator is in the trace class for $\mathrm{Res}<0$, has bounded eigenvalues for $\mathrm{Res}=0$, and has infinite eigenvalues for $s=1$. Marked changes in the properties of the quasiprobability distribution $W(\ensuremath{\alpha},s)$ are exhibited as the order parameter $s$ is varied continuously from $s=\ensuremath{-}1$, corresponding to the function $〈\ensuremath{\alpha}|\ensuremath{\rho}|\ensuremath{\alpha}〉$, to $s=+1$, corresponding to the function $P(\ensuremath{\alpha})$. Methods for constructing these functions and for using them to compute expectation values are presented and illustrated with several examples. One of these examples leads to a physical characterization of the density operators for which the $P$ representation is appropriate.
1 Homogenization of Second Order Elliptic Operators with Periodic Coefficients.- 1.1 Preliminaries.- 1.2 Setting of the Homogenization Problem.- 1.3 Problems of Justification Further Examples.- 1.4 The Method of Asymptotic Expansions.- 1.5 Explicit Formulas for the Homogenized Matrix in the Two-Dimensional Case.- 1.6 Estimates and Approximations for the Homogenized Matrix.- 1.7 The Rayleigh-Maxwell Formulas.- Comments.- 2 An Introduction to the Problems of Diffusion.- 2.1 Homogenization of Parabolic Operators.- 2.2 Homogenization and the Central Limit Theorem.- 2.3 Stabilization of Solutions of Parabolic Equations.- 2.4 Diffusion in a Solenoidal Flow.- 2.5 Diffusion in an Arbitrary Periodic Flow.- 2.6 Spectral Approach to the Asymptotic Problems of Diffusion.- 2.7 Diffusion with Absorption.- Comments.- 3 Elementary Soft and Stiff Problems.- 3.1 Homogenization of Soft Inclusions.- 3.2 Homogenization of Stiff Inclusions.- 3.3 Virtual Mass.- 3.4 The Method of Asymptotic Expansions.- 3.5 On a Dense Cubic Packing of Balls.- 3.6 The Dirichlet Problem in a Perforated Domain.- Comments.- 4 Homogenization of Maxwell Equations.- 4.1 Preliminary Results.- 4.2 A Lemma on Compensated Compactness.- 4.3 Homogenization.- 4.4 The Problem of an Artificial Dielectric.- Comments.- 5 G-Convergence of Differential Operators.- 5.1 Basic Properties of G-Convergence.- 5.2 A Sufficient Condition of G-Convergence.- 5.3 G-Convergence of Abstract Operators.- 5.4 Compactness Theorem and Its Implications.- 5.5 G-Convergence and Duality.- 5.6 Stratified Media.- 5.7 G-Convergence of Divergent Elliptic Operators of Higher Order.- Comments.- 6 Estimates for the Homogenized Matrix.- 6.1 The Hashin-Shtrikman Bounds.- 6.2 Attainability of Bounds. The Hashin Structure.- 6.3 Extremum Principles.- 6.4 The Variational Method.- 6.5 G-Limit Media Attainment of the Bounds on Stratified Composites.- 6.6 The Method of Quasi-Convexity.- 6.7 The Method of Null Lagrangians.- 6.8 The Method of Integral Representation.- Comments.- 7 Homogenization of Elliptic Operators with Random Coefficients.- 7.1 Probabilistic Description of Non-Homogeneous Media.- 7.2 Homogenization.- 7.3 Explicit Formulas in Two-Dimensional Problems.- 7.4 Homogenization of Almost-Periodic Operators.- 7.5 The General Theorem of Individual Homogenization.- Comments.- 8 Homogenization in Perforated Random Domains.- 8.1 Homogenization.- 8.2 Remarks on Positive Definiteness of the Homogenized Matrix.- 8.3 Central Limit Theorem.- 8.4 Disperse Media.- 8.5 Criterion of Pointwise Stabilization A Refinement of the Central Limit Theorem.- 8.6 Stiff Problem for a Random Spherical Structure.- 8.7 Random Spherical Structure with Small Concentration.- Comments.- 9 Homogenization and Percolation.- 9.1 Existence of the Effective Conductivity.- 9.2 Random Structure of Chess-Board Type.- 9.3 The Method of Percolation Channels.- 9.4 Conductivity Threshold for a Random Cubic Structure in ?3.- 9.5 Resistance Threshold for a Random Cubic Structure in ?3.- 9.6 Central Limit Theorem for Random Motion in an Infinite Two-Dimensional Cluster.- Comments.- 10 Some Asymptotic Problems for a Non-Divergent Parabolic Equation with Random Stationary Coefficients.- 10.1 Preliminary Remarks.- 10.2 Auxiliary Equation A*p = 0 on a Probability Space.- 10.3 Homogenization and the Central Limit Theorem.- 10.4 Criterion of Pointwise Stabilization.- Comments.- 11 Spectral Problems in Homogenization Theory.- 11.1 Spectral Properties of Abstract Operators Forming a Sequence.- 11.2 On the Spectrum of G-Convergent Operators.- 11.3 The Sturm-Liouville Problem.- 11.4 Spectral Properties of Stratified Media.- 11.5 Density of States for Random Elliptic Operators.- 11.6 Asymptotics of the Density of States.- Comments.- 12 Homogenization in Linear Elasticity.- 12.1 Some General Facts from the Theory of Elasticity.- 12.2 G-Convergence of Elasticity Tensors.- 12.3 Homogenization of Periodic and Random Tensors.- 12.4 Fourth Order Operators.- 12.5 Linear Problems of Incompressible Elasticity.- 12.6 Explicit Formulas for Two-Dimensional Incompressible Composites.- 12.7 Some Questions of Analysis on a Probability Space.- 13 Estimates for the Homogenized Elasticity Tensor.- 13.1 Basic Estimates.- 13.2 The Variational Method.- 13.3 Two-Phase Media Attainability of Bounds on Stratified Composites.- 13.4 On the Hashin Structure.- 13.5 Disperse Media with Inclusions of Small Concentration.- 13.6 Fourth Order Operators Systems of Stokes Type.- Comments.- 14 Elements of the Duality Theory.- 14.1 Convex Functions.- 14.2 Integral Functionals.- 14.3 On Two Types of Boundary Value Problems.- 14.4 Dual Boundary Value Problems.- 14.5 Extremal Relations.- 14.6 Examples of Regular Lagrangians.- Comments.- 15 Homogenization of Nonlinear Variational Problems.- 15.1 Random Lagrangians.- 15.2 Two Principal Lemmas.- 15.3 Homogenization Theorems.- 15.4 Applications to Boundary Value Problems in Perforated Domains.- 15.5 Chess Lagrangians Dychne's Formula.- Comments.- 16 Passing to the Limit in Nonlinear Variational Problems.- 16.1 Definition of ?-Convergence of Lagrangians Formulation of the Compactness Theorems.- 16.2 Convergence of Energies and Minimizers.- 16.3 Proof of the Compactness Theorems.- 16.4 Two Examples: Ulam's Problem Homogenization Problem.- 16.5 Compactness of Lagrangians in Plasticity Problems Application to Ll-Closedness.- 16.6 Remarks on Non-Convex Functionals.- Comments.- 17 Basic Properties of Abstract ?-Convergence.- 17.1 ?-Convergence of Functions on a Metric Space.- 17.2 ?-Convergence of Functions Defined in a Banach Space.- 17.3 ?-Convergence of Integral Functionals.- Comments.- 18 Limit Load.- 18.1 The Notion of Limit Load.- 18.2 Dual Definition of Limit Load.- 18.3 Equivalence Principle.- 18.4 Convergence of Limit Loads in Homogenization Problems.- 18.5 Surface Loads.- 18.6 Representation of the Functional $$\bar F$$ on BV0.- 18.7 ?-Convergence in BV0.- Comments.- Appendix A. Proof of the Nash-Aronson Estimate.- Appendix C. A Property of Bounded Lipschitz Domains.- References.
The weighted geometric (WG) operator and the ordered weighted geometric (OWG) operator are two common aggregation operators in the field of information fusion. But these two aggregation operators are usually used in situations where the given arguments are expressed as crisp numbers or linguistic values. In this paper, we develop some new geometric aggregation operators, such as the intuitionistic fuzzy weighted geometric (IFWG) operator, the intuitionistic fuzzy ordered weighted geometric (IFOWG) operator, and the intuitionistic fuzzy hybrid geometric (IFHG) operator, which extend the WG and OWG operators to accommodate the environment in which the given arguments are intuitionistic fuzzy sets which are characterized by a membership function and a non-membership function. Some numerical examples are given to illustrate the developed operators. Finally, we give an application of the IFHG operator to multiple attribute decision making based on intuitionistic fuzzy sets.
We describe the use of gel electrophoresis in studies of equilibrium binding, site distribution, and kinetics of protein-DNA interactions. The method, which we call protein distribution analysis, is simple, sensitive and yields thermodynamically rigorous results. It is particularly well suited to studies of simultaneous binding of several proteins to a single nucleic acid. In studies of the lac repressor-operator interaction, we found that binding to the so-called third operator site (03) is 15-18 fold weaker than operator binding, and that the binding reactions with the first and third operators are uncoupled, implying that there is no communication between the sites. Pseudo-first order dissociation kinetics of the repressor-203 bp operator complex were found to be temperature sensitive, with delta E of 80 kcal mol-1 above 29 degrees C and 26 kcal mol-1 below. The half life of the complex (5 min at 21 degrees C) is shorter than that reported for very high molecular weight operator-containing DNAs, but longer than values reported for much shorter fragments. The binding of lac repressor core to DNA could not be detected by this technique: the maximum binding constant consistent with this finding is 10(5) M-1.
Pseudo-differential operators have been developed as a tool for the study of elliptic differential equations. Suitably extended versions are also applicable to hypoelliptic equations, but their value is rather limited in genuinely non-elliptic problems. In this paper we shall therefore discuss some more general classes of operators which are adapted to such applications. For these operators we shall develop a calculus which is almost as smooth as that of pseudo-differential operators. It also seems that one gains some more insight into the theory of pseudo-differential operators by considering them from the point of view of the wider classes of operators to be discussed here so we shall take the opportunity to include a short exposition.
Introduction Analysis Background A Menagerie of Spaces Some Theorems on Integration Geometric Function Theory in the Disk Iteration of Functions in the Disk The Automorphisms of the Ball Julia-Caratheodory Theory in the Ball Norms Boundedness in Classical Spaces on the Disk Compactness and Essential Norms in Classical Spaces on the Disk Hilbert-Schmidt Operators Composition Operators with Closed Range Boundedness on Hp (BN) Small Spaces Compactness on Small Spaces Boundedness on Small Spaces Large Spaces Boundedness on Large Spaces Compactness on Large Spaces Hilbert-Schmidt Operators Special Results for Several Variables Compactness Revisited Wogen's Theorem Spectral Properties Introduction Invertible Operators on the Classical Spaces on the Disk Invertible Operators on the Classical Spaces on the Ball Spectra of Compact Composition Operators Spectra: Boundary Fixed Point, j'(a)
The author is primarily concerned with the problem of aggregating multicriteria to form an overall decision function. He introduces a type of operator for aggregation called an ordered weighted aggregation (OWA) operator and investigates the properties of this operator. The OWA's performance is found to be between those obtained using the AND operator, which requires all criteria to be satisfied, and the OR operator, which requires at least one criteria to be satisfied.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
An intuitionistic fuzzy set, characterized by a membership function and a non-membership function, is a generalization of fuzzy set. In this paper, based on score function and accuracy function, we introduce a method for the comparison between two intuitionistic fuzzy values and then develop some aggregation operators, such as the intuitionistic fuzzy weighted averaging operator, intuitionistic fuzzy ordered weighted averaging operator, and intuitionistic fuzzy hybrid aggregation operator, for aggregating intuitionistic fuzzy values and establish various properties of these operators.
Abstract This book gives an account of those parts of the analysis of closed linear operators acting in Banach or Hilbert spaces that are relevant to spectral problems involving differential operators, and makes applications to such questions. After the exposition of the abstract theory in the first four chapters, Sobolev spaces are introduced and their main properties established. The remaining seven chapters are largely concerned with second-order elliptic differential operators and related boundary-value problems. Particular attention is paid to the spectrum of the Schrödinger operator. Its original form contains material of lasting importance that is relatively unaffected by advances in the theory since 1987, when the book was first published. The present edition differs from the old by virtue of the correction of minor errors and improvements of various proofs. In addition, it contains Notes at the ends of most chapters, intended to give the reader some idea of recent developments together with additional references that enable more detailed accounts to be accessed.
In this correspondence, a completed modeling of the local binary pattern (LBP) operator is proposed and an associated completed LBP (CLBP) scheme is developed for texture classification. A local region is represented by its center pixel and a local difference sign-magnitude transform (LDSMT). The center pixels represent the image gray level and they are converted into a binary code, namely CLBP-Center (CLBP_C), by global thresholding. LDSMT decomposes the image local differences into two complementary components: the signs and the magnitudes, and two operators, namely CLBP-Sign (CLBP_S) and CLBP-Magnitude (CLBP_M), are proposed to code them. The traditional LBP is equivalent to the CLBP_S part of CLBP, and we show that CLBP_S preserves more information of the local structure than CLBP_M, which explains why the simple LBP operator can extract the texture features reasonably well. By combining CLBP_S, CLBP_M, and CLBP_C features into joint or hybrid distributions, significant improvement can be made for rotation invariant texture classification.
The sequence of 72 base pairs of the rightward operator (O-R) of bacteriophage lambda is presented as determined with simple and rapid methods for direct DNA sequencing. The sequence of an operator mutant is also described. The methods are of general use in sequencing DNA fragments with unique 5' ends up to 50 base pairs in length. Previous experiments have shown that this operator contains multiple sites recognized by the lambda phage repressor. We believe we have identified three of these sites.
Splitting algorithms for the sum of two monotone operators. We study two splitting algorithms for (stationary and evolution) problems involving the sum of two monotone operators. These algorithms are well known in the linear case and are here extended to the case of multivalued monotone operators. We prove the convergence of these algorithms, we give some applications to the obstacle problem and to minimization problems; and finally we present numerical computations comparing these algorithms to some other classical methods.
In this book, first published in 2003, the reader is provided with a tour of the principal results and ideas in the theories of completely positive maps, completely bounded maps, dilation theory, operator spaces and operator algebras, together with some of their main applications. The author assumes only that the reader has a basic background in functional analysis, and the presentation is self-contained and paced appropriately for graduate students new to the subject. Experts will also want this book for their library since the author illustrates the power of methods he has developed with new and simpler proofs of some of the major results in the area, many of which have not appeared earlier in the literature. An indispensable introduction to the theory of operator spaces for all who want to know more.
This book studies observation and control operators for linear systems where the free evolution of the state can be described by an operator semigroup on a Hilbert space. The emphasis is on well-posedness, observability and controllability properties. The abstract results are supported by a large number of examples coming mostly from partial differential equations. These examples are worked out in detail. This book is meant to be an elementary introduction in this theory. The first meaning of "elementary'' is that the text is aimed to be accessible to any reader familiar with linear algebra, calculus, the basics of Hilbert spaces and differential equations. We introduce everything needed on operator semigroups and most of the background used is summarized in the Appendices, often with proofs. The second meaning of "elementary'' is that we only cover results for which we can provide complete proofs. In our bibliographic comments we mention some of the more advanced results, for example those based on microlocal analysis.
As is well known, operations on one particle of an Einstein-Podolsky-Rosen (EPR) pair cannot influence the marginal statistics of measurements on the other particle. We characterize the set of states accessible from an initial EPR state by one-particle operations and show that in a sense they allow two bits to be encoded reliably in one spin-1/2 particle: One party, ``Alice,'' prepares an EPR pair and sends one of the particles to another party, ``Bob,'' who applies one of four unitary operators to the particle, and then returns it to Alice. By measuring the two particles jointly, Alice can now reliably learn which operator Bob used.
This classic textbook by two mathematicians from the USSR's prestigious Kharkov Mathematics Institute introduces linear operators in Hilbert space, and presents in detail the geometry of Hilbert space and the spectral theory of unitary and self-adjoint operators. It is directed to students at graduate and advanced undergraduate levels, but because of the exceptional clarity of its theoretical presentation and the inclusion of results obtained by Soviet mathematicians, it should prove invaluable for every mathematician and physicist. 1961, 1963 edition.
For the problem of minimizing a lower semicontinuous proper convex function f on a Hilbert space, the proximal point algorithm in exact form generates a sequence $\{ z^k \} $ by taking $z^{k + 1} $ to be the minimizes of $f(z) + ({1 / {2c_k }})\| {z - z^k } \|^2 $, where $c_k > 0$. This algorithm is of interest for several reasons, but especially because of its role in certain computational methods based on duality, such as the Hestenes-Powell method of multipliers in nonlinear programming. It is investigated here in a more general form where the requirement for exact minimization at each iteration is weakened, and the subdifferential $\partial f$ is replaced by an arbitrary maximal monotone operator T. Convergence is established under several criteria amenable to implementation. The rate of convergence is shown to be “typically” linear with an arbitrarily good modulus if $c_k $ stays large enough, in fact superlinear if $c_k \to \infty $. The case of $T = \partial f$ is treated in extra detail. Application is also made to a related case corresponding to minimax problems.
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In recent years, Discriminative Correlation Filter (DCF) based methods have significantly advanced the state-of-the-art in tracking. However, in the pursuit of ever increasing tracking performance, their characteristic speed and real-time capability have gradually faded. Further, the increasingly complex models, with massive number of trainable parameters, have introduced the risk of severe over-fitting. In this work, we tackle the key causes behind the problems of computational complexity and over-fitting, with the aim of simultaneously improving both speed and performance. We revisit the core DCF formulation and introduce: (i) a factorized convolution operator, which drastically reduces the number of parameters in the model, (ii) a compact generative model of the training sample distribution, that significantly reduces memory and time complexity, while providing better diversity of samples, (iii) a conservative model update strategy with improved robustness and reduced complexity. We perform comprehensive experiments on four benchmarks: VOT2016, UAV123, OTB-2015, and TempleColor. When using expensive deep features, our tracker provides a 20-fold speedup and achieves a 13.0% relative gain in Expected Average Overlap compared to the top ranked method [12] in the VOT2016 challenge. Moreover, our fast variant, using hand-crafted features, operates at 60 Hz on a single CPU, while obtaining 65.0% AUC on OTB-2015.
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