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We will revisit the classical questions of understanding the statistics of various deterministic dynamics of $N$ hard spheres of diameter $\varepsilon$ with random initial data in the Boltzmann-Grad scaling as $\varepsilon$ tends to zero…

Analysis of PDEs · Mathematics 2024-05-08 Karsten Matthies , Theodora Syntaka

The paper establishes a weak version of Horton self-similarity for a tree representation of Kingman's coalescent process. The proof is based on a Smoluchowski-type system of ordinary differential equations for the number of branches of a…

Probability · Mathematics 2015-09-29 Yevgeniy Kovchegov , Ilya Zaliapin

The hierarchical and recursive expressive capability of rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. On the other hand, such hierarchical…

Machine Learning · Computer Science 2022-01-25 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

The definition of weak equivalence principle of quantum matter is an open problem at present. In order to reflect the probability of quantum system in the quantum version of weak equivalence principle, we proposed a quantum weak equivalence…

General Relativity and Quantum Cosmology · Physics 2026-01-16 Xue-Nan Chen

We develop a new formalism to study nonlinear evolution in the growth of large-scale structure, by following the dynamics of gravitational clustering as it builds up in time. This approach is conveniently represented by Feynman diagrams…

Astrophysics · Physics 2009-11-13 M. Crocce , R. Scoccimarro

The recursive and hierarchical structure of full rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. In most of these cases, the full rooted tree is…

Machine Learning · Statistics 2022-03-24 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

A Feynman formula is a representation of a solution of an initial (or initial-boundary) value problem for an evolution equation (or, equivalently, a representation of the semigroup resolving the problem) by a limit of $n$-fold iterated…

Probability · Mathematics 2017-08-09 Yana A. Butko , René L. Schilling , Oleg G. Smolyanov

With good explanatory power and controllability, rule-based methods play an important role in many tasks such as knowledge reasoning and decision support. However, existing studies primarily focused on learning chain-like rules, which limit…

Artificial Intelligence · Computer Science 2025-01-07 Wangtao Sun , Shizhu He , Jun Zhao , Kang Liu

This paper provides a fully abstract semantics for value-passing CCS for trees (VCCTS). The operational semantics is given both in terms of a reduction semantics and in terms of a labelled transition semantics. The labelled transition…

Logic in Computer Science · Computer Science 2016-07-04 Shichao Liu , Thomas Ehrhard , Ying Jiang

We prove a version of the Feynman-Kac formula for Levy processes and integro-differential operators, with application to the momentum representation of suitable quantum (Euclidean) systems whose Hamiltonians involve L\'{e}vy-type…

Probability · Mathematics 2013-08-13 Nicolas Privault , Xiangfeng Yang , Jean-Claude Zambrini

The representation of quark distribution and fragmentation functions in terms of non-local operators is combined with a simple spectator model. This allows us to estimate these functions for the nucleon and the pion ensuring correct…

High Energy Physics - Phenomenology · Physics 2009-10-30 R. Jakob , P. J. Mulders , J. Rodrigues

In these expository notes, we describe some features of the multiplicative coalescent and its connection with random graphs and minimum spanning trees. We use Pitman's proof of Cayley's formula, which proceeds via a calculation of the…

Probability · Mathematics 2014-08-01 Louigi Addario-Berry

Matrix-product states and their continuous analogues are variational classes of states that capture quantum many-body systems or quantum fields with low entanglement; they are at the basis of the density-matrix renormalization group method…

Quantum Physics · Physics 2015-06-05 R. Hübener , A. Mari , J. Eisert

The existing formulations of the Schr\"{o}dinger interpolating dynamics, which is constrained by the prescribed input-output statistics data, utilize strictly positive Feynman-Kac kernels. This implies that the related Markov diffusion…

Quantum Physics · Physics 2009-10-28 Ph. Blanchard , P. Garbaczewski , R. Olkiewicz

We study the diffusion of classical hard-core particles in disordered lattices within the formalism of a quantum spin representation. This analogy enables an exact treatment of non-instantaneous correlation functions at finite particle…

Statistical Mechanics · Physics 2009-10-31 M. D. Grynberg , R. B. Stinchcombe

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

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

In this paper, we study how the probability of presence of a particle is distributed between the two parts of a composite fermionic system. We uncover that the difference of probability depends on the energy in a striking way and show the…

Statistical Mechanics · Physics 2020-10-20 Filiberto Ares , José G. Esteve , Fernando Falceto , Alberto Usón

We prove the existence of weak solutions of a class of multi-species cross-diffusion systems as well as the propagation of chaos result by means of nonlocal approximation of the nonlinear diffusion terms, coupling methods and compactness…

Analysis of PDEs · Mathematics 2024-10-18 Jose Antonio Carrillo , Shuchen Guo

Hidden tree Markov models allow learning distributions for tree structured data while being interpretable as nondeterministic automata. We provide a concise summary of the main approaches in literature, focusing in particular on the…

Machine Learning · Statistics 2018-06-01 Davide Bacciu , Daniele Castellana