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arXiv:1202.5726

Mean-field equations for higher-order quantum statistical models : an information geometric approach

Nihal Yapage

Published Feb 26, 2012• 0 citations
arXivHTMLPDF

Abstract

This work is a simple extension of \cite{NNjpa}. We apply the concepts of information geometry to study the mean-field approximation for a general class of quantum statistical models namely the higher-order quantum Boltzmann machines (QBMs). The states we consider are assumed to have at most third-order interactions with deterministic coupling coefficients. Such states, taken together, can be shown to form a quantum exponential family and thus can be viewed as a smooth manifold. In our work, we explicitly obtain naive mean-field equations for the third-order classical and quantum Boltzmann machines and demonstrate how some information geometrical concepts, particularly, exponential and mixture projections used to study the naive mean-field approximation in \cite{NNjpa} can be extended to a more general case. Though our results do not differ much from those in \cite{NNjpa}, we emphasize the validity and the importance of information geometrical point of view for higher dimensional classical and quantum statistical models.

DOI
10.48550/arxiv.1202.5726

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This work is a simple extension of \cite{NNjpa}. We apply the concepts of information geometry to study the mean-field approximation for a general class of quantum statistical models namely the higher-order quantum Boltzmann machines (QBMs). The states we consider are assumed to have at most third-order interactions with deterministic coupling coefficients. Such states, taken together, can be shown to form a quantum exponential family and thus can be viewed as a smooth manifold. In our work, we explicitly obtain naive mean-field equations for the third-order classical and quantum Boltzmann machines and demonstrate how some information geometrical concepts, particularly, exponential and mixture projections used to study the naive mean-field approximation in \cite{NNjpa} can be extended to a more general case. Though our results do not differ much from those in \cite{NNjpa}, we emphasize the validity and the importance of information geometrical point of view for higher dimensional classical and quantum statistical models.
We study the mean-field approximation for a general class of quantum Ising spin states from an information geometrical point of view. The states we consider are assumed to have at most second-order interactions with arbitrary but deterministic coupling coefficients. We call such a state a quantum Boltzmann machine (QBM) for the reason that it can be regarded as a quantum extension of the equilibrium distribution of a (classical) Boltzmann machine (CBM), which is a well-known stochastic neural network model. The totality of QBMs is then shown to form a quantum exponential family and thus can be considered as a smooth manifold having similar geometrical structures to those of CBMs. We elaborate on the significance and usefulness of information geometrical concepts, in particular the e- and m-projections, in studying the naive mean-field approximation for QBMs. We also discuss the higher-order corrections to the naive mean-field approximation based on the idea of the Plefka expansion in statistical physics. We elucidate the geometrical essence of the corrections and provide the expansion coefficients with expressions in terms of information geometrical quantities. Here, one may note this work as the information geometrical interpretation of (Plefka T 2006 Phys. Rev. E 73 016129) and as the quantum extension of (Tanaka T 2000 Neural Comput. 12 1951–68).
In this thesis, we consider quantum extension of the well-known stochastic neuralnetwork model called (classical) Boltzmann machine (CBM) from an informationgeometrical point of view. The new model is called quantum Boltzmann machine(QBM).We investigate some properties and geometrical aspects of QBM analogous tothose of CBM. Furthermore, we study the mean-field approximation for such a modelfrom the information geometrical point of view. This is in some sense motivated bythe application of mean-field approximation for probabilistic inference in the graphicalmodels in the classical probability theory. Although the problem tackled in the presentthesis is somewhat deviated from the major field of quantum information theory, wehave elucidated the relationships among several well-known fields such as statisticalphysics, differential geometry, information theory and statistics using the concepts ofthe new emerging subject of quantum information geometry.We first define QBMs which can be considered as a general class of quantumIsing spin models. The states we consider are assumed to have at most secondorderinteractions with arbitrary but deterministic coupling coefficients. We call sucha state a QBM for the reason that it can be regarded as a quantum extension ofthe equilibrium distribution of CBM. The totality of QBMs is then shown to forma quantum exponential family and thus can be considered as a smooth manifoldhaving similar geometrical structures to those of CBMs. The information geometricalstructure of the manifold of QBMs is discussed and the problem of approximating agiven quantum state (density operator) by a QBM is also treated.We also define a restricted class of QBMs called the strongly separable QBMs(SSQBMs). We consider the dynamics of SSQBMs and propose a new state renewalrule based on that of CBM. The geometrical structure of the totality of SSQBMs isshown to be equivalent to that of the totality of CBMs. Approximation process forSSQBMs is also studied. Finally, we briefly discuss the parameter estimation of aSSQBM.Next, we study the mean-field approximation for QBMs from an information geometricalpoint of view. We elaborate on the significance and usefulness of informationgeometrical concepts, in particular the e-(exponential) and m-(mixture) projections,in studying the naive mean-field approximation for QBMs and derive the naive meanfieldequation explicitly. We also discuss the higher-order corrections to the naivemean-field approximation based on the idea of Plefka expansion in statistical physics.We elucidate the geometrical essence of the corrections and provide the expansioncoefficients with expressions in terms of information geometrical quantities. Here,one may note this work as the information geometrical interpretation of [Ple06] andas the quantum extension of [Tan00].
Quantum information geometry studies families of quantum states by means of differential geometry. A new approach is followed with the intention to facilitate the introduction of a more general theory in subsequent work. To this purpose, the emphasis is shifted from a manifold of strictly positive density matrices to a manifold of faithful quantum states on the C*-algebra of bounded linear operators. In addition, ideas from the parameter-free approach to information geometry are adopted. The underlying Hilbert space is assumed to be finite-dimensional. In this way, technicalities are avoided so that strong results are obtained, which one can hope to prove later on in a more general context. Two different atlases are introduced, one in which it is straightforward to show that the quantum states form a Banach manifold, the other which is compatible with the inner product of Bogoliubov and which yields affine coordinates for the exponential connection.
Abstract Our purpose here is to draw attention to an interesting relationship that can be shown to hold between (a) information geometry, and (b) quantum geometry. By ‘information geometry’, we mean the natural geometry associated with families of probability distributions. This is a subject that goes back more than half a century to the pioneering work of Rao (1945), who showed that the Fisher information matrix associated with a parametrised family of probability dis tributions gives rise to a natural Riemannian metric on the parameter space. This then allows one to speak in a precise way of the ‘distance’ between two probability distributions, an idea that turns out to be useful in problems of statistical inference. An extensive literature has thus developed, following this line of enquiry, on applications of differential geometry to statistics (see, e.g., Amari (1985), Barndorff-Nielsen et al. (1986), Murray and Rice (1993)). By ‘quantum geometry’, on the other hand, we mean the geometry of the manifold of states associated with a given quantum mechanical system. In particular, we consider the manifold of ‘pure’ states associated with a given complex Hilbert space. This is the space of ‘rays’ through the origin in the Hilbert space, which has the structure of a complex projective space. It is known that the usual rules of quantum mechanics allow one to construct a natural metric on this space, namely the Fubini-Study metric, the specification of which is equivalent to all the familiar structure associated with ordinary quantum mechanics.
Introduction The aim of information geometry is to introduce a suitable geometrical structure on families of probability distributions or quantum states. For parametrised statistical models, such structure is based on two fundamental notions: the Fisher information and the exponential family with its dual mixed parametrisation, see for example (Amari 1985, Amari and Nagaoka 2000). For the non-parametric situation, the solution was given by Pistone and Sempi (Pistone and Sempi 1995, Pistone and Rogantin 1999), who introduced a Banach manifold structure on the set P of probability distributions, equivalent to a given one. For each µ ∈ ρ, the authors considered the non-parametric exponential family at µ. As it turned out, this provides a C ∞ -atlas on ρ, with the exponential Orlicz spaces Lφ(µ) as the underlying Banach spaces, here φ is the Young function of the form φ(x) = cosh(x) — 1. The present contribution deals with the case of quantum states: we want to introduce a similar manifold structure on the set of faithful normal states of a von Neumann algebra M. Since there is no suitable definition of a non-commutative Orlicz space with respect to a state φ, it is not clear how to choose the Banach space for the manifold. Of course, there is a natural Banach space structure, inherited from the predualM. But, as it was already pointed out in (Streater 2004), this structure is not suitable to define the geometry of states: for example, any neighbourhood of a state φ contains states such that the relative entropy with respect to φ is infinite.