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For molecular dynamics simulations of hard particles, we define dynamic neighbors as the distinct particles that collide with a given reference one during a specific time interval. This definition allows us to determine the distribution of…

Previous work of Ayyer, Martin, and Williams gave a probabilistic interpretation of the Macdonald polynomials $P_{\lambda}(x_1,\dots,x_n;1,t)$ at $q=1$ in terms of a Markov chain called the multispecies $t$-Push TASEP, a Markov chain…

Combinatorics · Mathematics 2026-02-17 Houcine Ben Dali , Lauren Williams

It is common, when dealing with quantum processes involving a subsystem of a much larger composite closed system, to treat them as effectively memory-less (Markovian). While open systems theory tells us that non-Markovian processes should…

Quantum Physics · Physics 2019-05-02 Pedro Figueroa-Romero , Kavan Modi , Felix A. Pollock

Virtually all questions that one can ask about the behavioral and structural complexity of a stochastic process reduce to a linear algebraic framing of a time evolution governed by an appropriate hidden-Markov process generator. Each type…

Chaotic Dynamics · Physics 2018-04-18 Paul M. Riechers , James P. Crutchfield

The notion of a successful coupling of Markov processes, based on the idea that both components of the coupled system ``intersect'' in finite time with probability one, is extended to cover situations when the coupling is unnecessarily…

Probability · Mathematics 2007-05-23 Michael Blank , Sergey Pirogov

Traditional thermodynamic trade-off relations usually apply to quantities that depend linearly on probability distributions. In contrast, many important information-theoretic measures, such as entropies, are nonlinear and therefore…

Statistical Mechanics · Physics 2026-02-17 Yoshihiko Hasegawa

An infinite system of point particles placed in $\mathds{R}^d$ is studied. The particles are of two types; they perform random walks in the course of which those of distinct types repel each other. The interaction of this kind induces an…

Probability · Mathematics 2022-07-18 Yuri Kozitsky , Michael Röckner

About two dozens of exactly solvable Markov chains on one-dimensional finite and semi-infinite integer lattices are constructed in terms of convolutions of orthogonality measures of the Krawtchouk, Hahn, Meixner, Charlier, $q$-Hahn,…

Probability · Mathematics 2022-06-17 Satoru Odake , Ryu Sasaki

Consider that the coordinates of $N$ points are randomly generated along the edges of a $d$-dimensional hypercube (random point problem). The probability that an arbitrary point is the $m$th nearest neighbor to its own $n$th nearest…

Disordered Systems and Neural Networks · Physics 2007-05-23 Cesar Augusto Sangaletti Tercariol , Felipe de Mouta Kiipper , Alexandre Souto Martinez

We present two new connections between the inhomogeneous stochastic higher spin six vertex model in a quadrant and integrable stochastic systems from the Macdonald processes hierarchy. First, we show how Macdonald $q$-difference operators…

Probability · Mathematics 2016-11-01 Daniel Orr , Leonid Petrov

This paper compiles several aspects of the dynamics of stochastic approximation algorithms with Markov iterate-dependent noise when the iterates are not known to be stable beforehand. We achieve the same by extending the lock-in probability…

Dynamical Systems · Mathematics 2019-02-22 Prasenjit Karmakar , Shalabh Bhatnagar

Macdonald processes are measures on sequences of integer partitions built using the Cauchy summation identity for Macdonald symmetric functions. These measures are a useful tool to uncover the integrability of many probabilistic systems,…

Probability · Mathematics 2020-05-27 Guillaume Barraquand , Alexei Borodin , Ivan Corwin

Using Okounkov's $q$-integral representation of Macdonald polynomials we construct an infinite sequence $\Omega_1,\Omega_2,\Omega_3,\dots$ of countable sets linked by transition probabilities from $\Omega_N$ to $\Omega_{N-1}$ for each…

Probability · Mathematics 2021-06-29 Grigori Olshanski

The probabilistic description of the time evolution of a physical system can take two conceptually distinct forms: a trajectory of probabilities, which specifies how probabilities evolve over time, and a probability on trajectories, which…

Quantum Physics · Physics 2026-03-02 Győző Egri , Marton Gomori , Balazs Gyenis , Gábor Hofer-Szabó

We prove duality relations for two interacting particle systems: the $q$-deformed totally asymmetric simple exclusion process ($q$-TASEP) and the asymmetric simple exclusion process (ASEP). Expectations of the duality functionals correspond…

Probability · Mathematics 2014-10-28 Alexei Borodin , Ivan Corwin , Tomohiro Sasamoto

The Markov dynamics of interlaced particle arrays, introduced by A. Borodin and P. Ferrari in arXiv:0811.0682, is a classical example of (2+1)-dimensional random growth model belonging to the so-called Anisotropic KPZ universality class. In…

Probability · Mathematics 2022-03-01 Vincent Lerouvillois , Fabio Lucio Toninelli

We introduce a new interacting (stochastic) particle system q-PushASEP which interpolates between the q-TASEP introduced by Borodin and Corwin (see arXiv:1111.4408, and also arXiv:1207.5035; arXiv:1305.2972; arXiv:1212.6716) and the…

Probability · Mathematics 2015-03-20 Ivan Corwin , Leonid Petrov

We obtain a new relation between the distributions $\mu_t$ at different times $t\ge 0$ of the continuous-time TASEP (Totally Asymmetric Simple Exclusion Process) started from the step initial configuration. Namely, we present a…

Probability · Mathematics 2021-02-18 Leonid Petrov , Axel Saenz

The nonlinear Markov processes are the measure-valued dynamical systems which preserve positivity. They can be represented as the law of large numbers limits of general Markov models of interacting particles. In physics, the kinetic…

Chemical Physics · Physics 2015-09-28 A. N. Gorban , V. N. Kolokoltsov

When two Markov operators commute, it suggests that we can couple two copies of one of the corresponding processes. We explicitly construct a number of couplings of this type for a commuting family of Markov processes on the set of…

Probability · Mathematics 2008-11-20 Anthony P. Metcalfe , Neil O'Connell , Jon Warren