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This article analyses a new class of advanced particle Markov chain Monte Carlo algorithms recently introduced by Andrieu, Doucet, and Holenstein (2010). We present a natural interpretation of these methods in terms of well known…

Probability · Mathematics 2014-10-28 P. Del Moral , R. Kohn , F. Patras

We design a particle interpretation of Feynman-Kac measures on path spaces based on a backward Markovian representation combined with a traditional mean field particle interpretation of the flow of their final time marginals. In contrast to…

Statistics Theory · Mathematics 2009-08-19 Pierre Del Moral , Arnaud Doucet , Sumeetpal S. Singh

We revisit the work of Mitter and Newton on an information-theoretic interpretation of Bayes' formula through the Gibbs variational principle. This formulation allowed them to pose nonlinear estimation for diffusion processes as a problem…

Optimization and Control · Mathematics 2024-05-02 Maxim Raginsky

This article provides a new theory for the analysis of forward and backward particle approximations of Feynman-Kac models. Such formulae are found in a wide variety of applications and their numerical (particle) approximation are required…

Statistics Theory · Mathematics 2014-11-17 Hock Peng Chan , Pierre Del Moral , Ajay Jasra

This article develops a methodology allowing application of the complete machinery of particle-based inference methods upon the class of continuous-discrete State Space Models (CD-SSMs). Such models correspond to a latent continuous-time…

Methodology · Statistics 2025-11-17 Christopher Stanton , Alexandros Beskos

Discretizations of the Feynman-Kac path integral representation of the quantum mechanical density matrix are investigated. Each infinite-dimensional path integral is approximated by a Riemann integral over a finite-dimensional function…

Statistical Mechanics · Physics 2007-05-23 Stephen D. Bond , Brian B. Laird , Benedict J. Leimkuhler

Score-based diffusion models have proven effective in image generation and have gained widespread usage; however, the underlying factors contributing to the performance disparity between stochastic and deterministic (i.e., the probability…

Machine Learning · Computer Science 2024-03-19 Yuji Hirono , Akinori Tanaka , Kenji Fukushima

In the path integral expression for a Feynman propagator of a spinless particle of mass $m$, the path integral amplitude for a path of proper length ${\cal R}(x,x'| g_{\mu\nu})$ connecting events $x$ and $x'$ in a spacetime described by the…

General Relativity and Quantum Cosmology · Physics 2009-10-30 K. Srinivasan , L. Sriramkumar , T. Padmanabhan

A generalized Feynman-Kac formula based on the Wiener measure is presented. Within the setting of a quantum particle in an electromagnetic field it yields the standard Feynman-Kac formula for the corresponding Schr\"odinger semigroup. In…

Quantum Physics · Physics 2007-05-23 B. Bodmann , H. Leschke , S. Warzel

In the Feynman-Kac[1] path integral approach the eigenvalues of a quantum system can be computed using Wiener measure which uses Brownian particle motion. In our previous work[2-3] on such systems we have observed that the Wiener process…

Quantum Physics · Physics 2017-03-28 S Datta , J M Rejcek , J. L. Fry

We present a new formulation for the emergence of classical dynamics in a quantum world by considering a path integral approach that also incorporates continuous measurements. Our program is conceptually different from the decoherence…

Quantum Physics · Physics 2025-05-23 Harsh Arora , Bishal Kumar Das , Baladitya Suri , Vaibhav Madhok

We propose a new solvable class of multidimensional quantum harmonic oscillators for a linear diffusive particle and a quadratic energy absorbing well associated with a semi-definite positive matrix force. Under natural and easily checked…

Probability · Mathematics 2023-07-26 Pierre del Moral , Emma Horton

Sampling from the full posterior distribution of high-dimensional non-linear, non-Gaussian latent dynamical models presents significant computational challenges. While Particle Gibbs (also known as conditional sequential Monte Carlo) is…

Computation · Statistics 2025-03-05 Adrien Corenflos , Simo Särkkä

In 1905, Einstein's theory of Brownian motion supported the molecular basis of the diffusion equation and introduced two complementary viewpoints: a deterministic field description and a probabilistic formulation based on stochastic…

This article is concerned with the design and analysis of discrete time Feynman-Kac particle integration models with geometric interacting jump processes. We analyze two general types of model, corresponding to whether the reference process…

Probability · Mathematics 2012-12-03 Pierre Del Moral , Pierre E. Jacob , Anthony Lee , Lawrence Murray , Gareth W. Peters

We present a new notion of probabilistic duality for random variables involving mixture distributions. Using this notion, we show how to implement a highly-parallelizable Gibbs sampler for weakly coupled discrete pairwise graphical models…

Machine Learning · Computer Science 2016-11-23 Lars Mescheder , Sebastian Nowozin , Andreas Geiger

We explore the connections between the theories of stochastic analysis and discrete quantum mechanical systems. Naturally these connections include the Feynman-Kac formula, and the Cameron-Martin-Girsanov theorem. More precisely, the notion…

Mathematical Physics · Physics 2019-06-11 Anastasia Doikou , Simon J. A. Malham , Anke Wiese

We study large deviations principles for $ N $ random processes on the lattice $ \Z^d $ with finite time horizon $ [0,\beta] $ under a symmetrised measure where all initial and terminal points are uniformly given by a random permutation.…

Mathematical Physics · Physics 2007-05-23 Stefan Adams , Tony Dorlas

We study mean-field particle approximations of normalized Feynman-Kac semi-groups, usually called Fleming-Viot or Feynman-Kac particle systems. Assuming various large time stability properties of the semi-group uniformly in the initial…

Probability · Mathematics 2024-12-23 Lucas Journel , Mathias Rousset

Feynman path integrals are now a standard tool in quantum physics and their use in differential geometry leads to new mathematical insights. A logical treatment of quantum phenomena seems to require a sustained mathematical analysis of path…

Mathematical Physics · Physics 2022-04-18 B. R. F. Jefferies
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