704 research outputs found
A Neural Network model with Bidirectional Whitening
We present here a new model and algorithm which performs an efficient Natural
gradient descent for Multilayer Perceptrons. Natural gradient descent was
originally proposed from a point of view of information geometry, and it
performs the steepest descent updates on manifolds in a Riemannian space. In
particular, we extend an approach taken by the "Whitened neural networks"
model. We make the whitening process not only in feed-forward direction as in
the original model, but also in the back-propagation phase. Its efficacy is
shown by an application of this "Bidirectional whitened neural networks" model
to a handwritten character recognition data (MNIST data).Comment: 16page
Laplace's rule of succession in information geometry
Laplace's "add-one" rule of succession modifies the observed frequencies in a
sequence of heads and tails by adding one to the observed counts. This improves
prediction by avoiding zero probabilities and corresponds to a uniform Bayesian
prior on the parameter. The canonical Jeffreys prior corresponds to the
"add-one-half" rule. We prove that, for exponential families of distributions,
such Bayesian predictors can be approximated by taking the average of the
maximum likelihood predictor and the \emph{sequential normalized maximum
likelihood} predictor from information theory. Thus in this case it is possible
to approximate Bayesian predictors without the cost of integrating or sampling
in parameter space
Information geometry of density matrices and state estimation
Given a pure state vector |x> and a density matrix rho, the function
p(x|rho)= defines a probability density on the space of pure states
parameterised by density matrices. The associated Fisher-Rao information
measure is used to define a unitary invariant Riemannian metric on the space of
density matrices. An alternative derivation of the metric, based on square-root
density matrices and trace norms, is provided. This is applied to the problem
of quantum-state estimation. In the simplest case of unitary parameter
estimation, new higher-order corrections to the uncertainty relations,
applicable to general mixed states, are derived.Comment: published versio
Complexity Measures from Interaction Structures
We evaluate new complexity measures on the symbolic dynamics of coupled tent
maps and cellular automata. These measures quantify complexity in terms of
-th order statistical dependencies that cannot be reduced to interactions
between units. We demonstrate that these measures are able to identify
complex dynamical regimes.Comment: 11 pages, figures improved, minor changes to the tex
Divergence functions in Information Geometry
A recently introduced canonical divergence for a dual structure
is discussed in connection to other divergence
functions. Finally, open problems concerning symmetry properties are outlined.Comment: 10 page
The volume of Gaussian states by information geometry
We formulate the problem of determining the volume of the set of Gaussian
physical states in the framework of information geometry. That is, by
considering phase space probability distributions parametrized by the
covariances and supplying this resulting statistical manifold with the
Fisher-Rao metric. We then evaluate the volume of classical, quantum and
quantum entangled states for two-mode systems showing chains of strict
inclusion
From neurons to epidemics: How trophic coherence affects spreading processes
Trophic coherence, a measure of the extent to which the nodes of a directed
network are organised in levels, has recently been shown to be closely related
to many structural and dynamical aspects of complex systems, including graph
eigenspectra, the prevalence or absence of feed-back cycles, and linear
stability. Furthermore, non-trivial trophic structures have been observed in
networks of neurons, species, genes, metabolites, cellular signalling,
concatenated words, P2P users, and world trade. Here we consider two simple yet
apparently quite different dynamical models -- one a
Susceptible-Infected-Susceptible (SIS) epidemic model adapted to include
complex contagion, the other an Amari-Hopfield neural network -- and show that
in both cases the related spreading processes are modulated in similar ways by
the trophic coherence of the underlying networks. To do this, we propose a
network assembly model which can generate structures with tunable trophic
coherence, limiting in either perfectly stratified networks or random graphs.
We find that trophic coherence can exert a qualitative change in spreading
behaviour, determining whether a pulse of activity will percolate through the
entire network or remain confined to a subset of nodes, and whether such
activity will quickly die out or endure indefinitely. These results could be
important for our understanding of phenomena such as epidemics, rumours, shocks
to ecosystems, neuronal avalanches, and many other spreading processes
Geometric derivation of the quantum speed limit
The Mandelstam-Tamm and Margolus-Levitin inequalities play an important role
in the study of quantum mechanical processes in Nature, since they provide
general limits on the speed of dynamical evolution. However, to date there has
been only one derivation of the Margolus-Levitin inequality. In this paper,
alternative geometric derivations for both inequalities are obtained from the
statistical distance between quantum states. The inequalities are shown to hold
for unitary evolution of pure and mixed states, and a counterexample to the
inequalities is given for evolution described by completely positive
trace-preserving maps. The counterexample shows that there is no quantum speed
limit for non-unitary evolution.Comment: 8 pages, 1 figure
An Information-Geometric Reconstruction of Quantum Theory, I: The Abstract Quantum Formalism
In this paper and a companion paper, we show how the framework of information
geometry, a geometry of discrete probability distributions, can form the basis
of a derivation of the quantum formalism. The derivation rests upon a few
elementary features of quantum phenomena, such as the statistical nature of
measurements, complementarity, and global gauge invariance. It is shown that
these features can be traced to experimental observations characteristic of
quantum phenomena and to general theoretical principles, and thus can
reasonably be taken as a starting point of the derivation. When appropriately
formulated within an information geometric framework, these features lead to
(i) the abstract quantum formalism for finite-dimensional quantum systems, (ii)
the result of Wigner's theorem, and (iii) the fundamental correspondence rules
of quantum theory, such as the canonical commutation relationships. The
formalism also comes naturally equipped with a metric (and associated measure)
over the space of pure states which is unitarily- and anti-unitarily invariant.
The derivation suggests that the information geometric framework is directly or
indirectly responsible for many of the central structural features of the
quantum formalism, such as the importance of square-roots of probability and
the occurrence of sinusoidal functions of phases in a pure quantum state.
Global gauge invariance is seen to play a crucial role in the emergence of the
formalism in its complex form.Comment: 26 page
Generalized geometric quantum speed limits
The attempt to gain a theoretical understanding of the concept of time in quantum mechanics has triggered significant progress towards the search for faster and more efficient quantum technologies. One of such advances consists in the interpretation of the time-energy uncertainty relations as lower bounds for the minimal evolution time between two distinguishable states of a quantum system, also known as quantum speed limits. We investigate how the nonuniqueness of a bona fide measure of distinguishability defined on the quantum-state space affects the quantum speed limits and can be exploited in order to derive improved bounds. Specifically, we establish an infinite family of quantum speed limits valid for unitary and nonunitary evolutions, based on an elegant information geometric formalism. Our work unifies and generalizes existing results on quantum speed limits and provides instances of novel bounds that are tighter than any established one based on the conventional quantum Fisher information. We illustrate our findings with relevant examples, demonstrating the importance of choosing different information metrics for open system dynamics, as well as clarifying the roles of classical populations versus quantum coherences, in the determination and saturation of the speed limits. Our results can find applications in the optimization and control of quantum technologies such as quantum computation and metrology, and might provide new insights in fundamental investigations of quantum thermodynamics
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