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Related papers: Non-Markov quantum belief propagation

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We revisit key notions related to the evolution of quantum information in few-body quantum mechanics (fbQM) and, for a wide class of dispersion relations, prove uniform bounds on the maximal speed of propagation of quantum information for…

Quantum Physics · Physics 2025-02-28 Israel Michael Sigal , Xiaoxu Wu

The purpose of this paper is to set out the problems of modeling quantum communication and signal processing where the communication between systems via a non-Markovian channel. This is a general feature of quantum transmission lines. Our…

Quantum Physics · Physics 2017-01-05 John Gough

Belief propagation is an algorithm that is known from statistical physics and computer science. It provides an efficient way of calculating marginals that involve large sums of products which are efficiently rearranged into nested products…

Artificial Intelligence · Computer Science 2020-12-22 Tim Ritmeester , Hildegard Meyer-Ortmanns

We prove the convergence of the law of grid-valued random walks, which can be seen as time-space Markov chains, to the law of a general diffusion process. This includes processes with sticky features, reflecting or absorbing boundaries and…

Probability · Mathematics 2024-11-15 Alexis Anagnostakis , Antoine Lejay , Denis Villemonais

The goal of this work is to formally abstract a Markov process evolving in discrete time over a general state space as a finite-state Markov chain, with the objective of precisely approximating its state probability distribution in time,…

Logic in Computer Science · Computer Science 2017-01-11 Sadegh Esmaeil Zadeh Soudjani , Alessandro Abate

It was argued [1] that there can be no extension of quantum mechanics with improved predictive power on a measurement freely chosen, independently of any event that is not in its future light cone. The assumption of measurement choice was…

Quantum Physics · Physics 2025-12-09 Yiruo Lin

After the discovery that fixed points of loopy belief propagation coincide with stationary points of the Bethe free energy, several researchers proposed provably convergent algorithms to directly minimize the Bethe free energy. These…

Computer Vision and Pattern Recognition · Computer Science 2011-12-23 Tomas Werner

We derive novel sufficient conditions for convergence of Loopy Belief Propagation (also known as the Sum-Product algorithm) to a unique fixed point. Our results improve upon previously known conditions. For binary variables with…

Artificial Intelligence · Computer Science 2012-07-09 Joris Mooij , Hilbert Kappen

Score-matching generative models have proven successful at sampling from complex high-dimensional data distributions. In many applications, this distribution is believed to concentrate on a much lower $d$-dimensional manifold embedded into…

Machine Learning · Statistics 2025-04-25 Peter Potaptchik , Iskander Azangulov , George Deligiannidis

It is now well-known that vacuum polarisation in QED can lead to superluminal low-frequency phase velocities for photons propagating in curved spacetimes. In a series of papers, we have shown that this quantum phenomenon is dispersive and…

High Energy Physics - Theory · Physics 2010-06-08 Timothy J. Hollowood , Graham M. Shore

The sum-product or belief propagation (BP) algorithm is a widely-used message-passing algorithm for computing marginal distributions in graphical models with discrete variables. At the core of the BP message updates, when applied to a…

Information Theory · Computer Science 2012-05-28 Nima Noorshams , Martin J. Wainwright

In this paper, we prove a particle approximation, in the sense of the propagation of chaos, of a Lagrangian stochastic model submitted to specular boundary condition and satisfying the mean no-permeability condition.

Probability · Mathematics 2018-03-13 Mireille Bossy , Jean-Francois Jabir

Langevin dynamics has found a large number of applications in sampling, optimization and estimation. Preconditioning the gradient in the dynamics with the covariance - an idea that originated in literature related to solving estimation and…

Probability · Mathematics 2025-04-28 Axel Ringh , Akash Sharma

Belief propagation is a fundamental message-passing algorithm for probabilistic reasoning and inference in graphical models. While it is known to be exact on trees, in most applications belief propagation is run on graphs with cycles.…

Machine Learning · Computer Science 2019-05-27 Frederic Koehler

A theoretical investigation on slow light propagation based on eletromagnetically induced transparency in a three-level quantum-dot system is performed including non-Markovian effects and correlated dephasing reservoirs. It is…

Quantum Physics · Physics 2016-01-08 D. Mogilevtsev , E. Reyes-Gomez , S. B. Cavalcanti , L. E. Oliveira

If the conditional information of a classical probability distribution of three random variables is zero, then it obeys a Markov chain condition. If the conditional information is close to zero, then it is known that the distance (minimum…

Quantum Physics · Physics 2017-08-02 Ben Ibinson , Noah Linden , Andreas Winter

In this work, we numerically verify the Jarzynski equality and Crook fluctuation theorem for a Brownian particle diffusing in a heterogeneous thermal bath and hence having a non-Gaussian position distribution. We use the…

Statistical Mechanics · Physics 2026-03-05 A. Saravanan , I. Iyyappan

We apply belief propagation (BP) to multi--user detection in a spread spectrum system, under the assumption of Gaussian symbols. We prove that BP is both convergent and allows to estimate the correct conditional expectation of the input…

Information Theory · Computer Science 2007-07-13 Andrea Montanari , Balaji Prabhakar , David Tse

Recently it was shown that, in an effective description motivated by loop quantum gravity, singularities of the Kruskal space-time are naturally resolved [1,2]. In this note we explore a few properties of this quantum corrected effective…

General Relativity and Quantum Cosmology · Physics 2021-01-14 Abhay Ashtekar , Javier Olmedo

Belief Propagation is a well-studied message-passing algorithm that runs over graphical models and can be used for approximate inference and approximation of local marginals. The resulting approximations are equivalent to the Bethe-Peierls…

Quantum Physics · Physics 2021-05-05 Roy Alkabetz , Itai Arad
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