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Enforcing exact conservation laws instead of average ones in statistical thermal models for relativistic heavy ion reactions gives raise to so called canonical effect, which can be used to explain some enhancement effects when going from…

Nuclear Theory · Physics 2008-11-26 A. Keranen , F. Becattini

The potential applications of boundary functionals of random processes, such as the extreme values of these processes, the moment of first reaching a fixed level, the value of the process at the moment of reaching the level, the moment of…

Statistical Mechanics · Physics 2025-01-15 V. V. Ryazanov

We present a novel approach to Bayesian inference and general Bayesian computation that is defined through a sequential decision loop. Our method defines a recursive partitioning of the sample space. It neither relies on gradients nor…

Machine Learning · Statistics 2021-06-10 Erik Bodin , Zhenwen Dai , Neill D. F. Campbell , Carl Henrik Ek

Traditional Bayesian random partition models assume that the size of each cluster grows linearly with the number of data points. While this is appealing for some applications, this assumption is not appropriate for other tasks such as…

Methodology · Statistics 2020-04-07 Brenda Betancourt , Giacomo Zanella , Rebecca C. Steorts

We consider the problem of leakage or effusion of an ensemble of independent stochastic processes from a region where they are initially randomly distributed. The case of Brownian motion, initially confined to the left half line with…

Statistical Mechanics · Physics 2023-06-29 David S. Dean , Satya N. Majumdar , Gregory Schehr

We study the transition probabilities for the totally asymmetric simple exclusion process (TASEP) on the infinite integer lattice with a finite, but arbitrary number of first and second class particles. Using the Bethe ansatz we present an…

Statistical Mechanics · Physics 2010-08-17 Sakuntala Chatterjee , Gunter M. Schütz

The certification of intrinsic randomness is foundational to quantum information theory and central in many practical applications thereof, such as in the generation of unquestionably random numbers and in cryptographic protocols.…

Quantum Physics · Physics 2025-10-27 Maria Ciudad Alañón , Daniel Centeno , Andrew Watford , Elie Wolfe

Regularized coherent-state functional integrals are derived for ensembles of identical bosons on a lattice, the regularization being a discretization of Euclidian time. Convergence of the time-continuum limit is shown for various…

Mathematical Physics · Physics 2021-03-31 Manfred Salmhofer

As a guideline for experimental tests of the ideal glass transition (Random Pinning Glass Transition, RPGT) that shall be induced in a system by randomly pinning particles, we performed first-principle computations within the Hypernetted…

Disordered Systems and Neural Networks · Physics 2017-03-07 Chiara Cammarota , Beatriz Seoane

We derive the continuous canonical distribution only by requiring the extensivity of the mean energy and the multiplicative probabilistic composition rule. The derivation is independent of the thermodynamic limit and moreover it does not…

Statistical Mechanics · Physics 2016-08-31 Thomas Oikonomou , G. Baris Bagci

We consider the problem of positive-semidefinite continuation: extending a partially specified covariance kernel from a subdomain $\Omega$ of a rectangular domain $I\times I$ to a covariance kernel on the entire domain $I\times I$. For a…

Statistics Theory · Mathematics 2022-05-13 Kartik G. Waghmare , Victor M. Panaretos

In this paper, we formulate statistical mechanics of the polymerized systems in the semiclassical regime. On the corresponding polymeric symplectic manifold, we set up a noncanonical coordinate system in which all of the polymeric effects…

General Relativity and Quantum Cosmology · Physics 2015-06-22 M. A. Gorji , K. Nozari , B. Vakili

We analytically investigate a 1d branching-coalescing model with reflecting boundaries in a canonical ensemble where the total number of particles on the chain is conserved. Exact analytical calculations show that the model has two…

Statistical Mechanics · Physics 2009-11-10 F. H. Jafarpour , S. R. Masharian

Suppose some random resource (energy, mass or space) $\chi \geq 0$ is to be shared at random between (possibly infinitely many) species (atoms or fragments). Assume ${\Bbb E}\chi =\theta <\infty $ and suppose the amount of the individual…

Disordered Systems and Neural Networks · Physics 2007-05-23 Thierry Huillet

We introduce and analyse a class of fragmentation-coalescence processes defined on finite systems of particles organised into clusters. Coalescent events merge multiple clusters simultaneously to form a single larger cluster, while…

Probability · Mathematics 2017-01-31 Andreas E. Kyprianou , Steven W. Pagett , Tim Rogers

In this paper we study a parametric class of stochastic processes to model both fast and slow anomalous diffusion. This class, called generalized grey Brownian motion (ggBm), is made up off self-similar with stationary increments processes…

Mathematical Physics · Physics 2009-11-13 Antonio Mura , Gianni Pagnini

We show, in two different ways, that the Tsallis' partition function and its derivatives are related to thermodynamic quantities such as entropy, internal energy, etc., in the same way as in Boltzmann-Gibbs' formalism, with the Lagrange…

Statistical Mechanics · Physics 2007-05-23 F. Q. Potiguar , U. M. S. Costa

Consider a branching system with particles moving according to an Ornstein-Uhlenbeck process with drift $\mu>0$ and branching according to a law in the domain of attraction of the $(1+\beta)$-stable distribution. The mean of the branching…

Probability · Mathematics 2018-03-23 Rafał Marks , Piotr Miłoś

In the classical stochastic resetting problem, a particle, moving according to some stochastic dynamics, undergoes random interruptions that bring it to a selected domain, and then, the process recommences. Hitherto, the resetting mechanism…

Statistical Mechanics · Physics 2020-12-08 Carlos A. Plata , Deepak Gupta , Sandro Azaele

Rare transitions in stochastic processes can often be rigorously described via an underlying large deviation principle. Recent breakthroughs in the classification of reversible stochastic processes as gradient flows have led to a connection…

Statistical Mechanics · Physics 2019-05-22 Tobias Grafke