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The large deviations properties of trajectory observables for chaotic non-invertible deterministic maps as studied recently by N. R. Smith, Phys. Rev. E 106, L042202 (2022) and by R. Gutierrez, A. Canella-Ortiz, C. Perez-Espigares,…

Statistical Mechanics · Physics 2024-01-30 Cecile Monthus

Motivated by techniques developed in recent progress on lower bounds for sublinear time algorithms (Behnezhad, Roghani and Rubinstein, STOC 2023, FOCS 2023, and STOC 2024) we introduce and study a new class of randomized algorithmic…

Data Structures and Algorithms · Computer Science 2026-03-19 Amir Azarmehr , Soheil Behnezhad , Alma Ghafari , Madhu Sudan

Parametric Markov chains (pMC) are used to model probabilistic systems with unknown or partially known probabilities. Although (universal) pMC verification for reachability properties is known to be coETR-complete, there have been efforts…

Logic in Computer Science · Computer Science 2025-04-29 Kasper Engelen , Guillermo A. Pérez , Shrisha Rao

We propose a "decomposition method" to prove non-asymptotic bound for the convergence of empirical measures in various dual norms. The main point is to show that if one measures convergence in duality with sufficiently regular observables,…

Probability · Mathematics 2018-02-13 Benoît Kloeckner

Conserved dynamical systems are generally considered to be critical. We study a class of critical routing models, equivalent to random maps, which can be solved rigorously in the thermodynamic limit. The information flow is conserved for…

Adaptation and Self-Organizing Systems · Physics 2013-01-10 Dimitrije Markovic , Andre Schuelein , Claudius Gros

It is common practice in Markov chain Monte Carlo to update the simulation one variable (or sub-block of variables) at a time, rather than conduct a single full-dimensional update. When it is possible to draw from each full-conditional…

Computation · Statistics 2013-10-03 Alicia A. Johnson , Galin L. Jones , Ronald C. Neath

This simple note lays out a few observations which are well known in many ways but may not have been said in quite this way before. The basic idea is that when comparing two different Markov chains it is useful to couple them is such a way…

Probability · Mathematics 2017-11-16 James E. Johndrow , Jonathan C. Mattingly

By considering general Markov stochastic dynamics and its coarse-graining, we study the framework of stochastic thermodynamics for the original and reduced descriptions corresponding to different scales. We are especially concerned with the…

Statistical Mechanics · Physics 2015-01-29 Yohei Nakayama , Kyogo Kawaguchi

The collective properties of small material systems considered as semidynamical systems revealing the Markov-type irreversible evolution, are investigated. It is shown that these material systems admit their treatment as thermodynamic…

Mathematical Physics · Physics 2015-09-08 Andrzej Trzesowski

We propose an efficient Markov Chain Monte Carlo method for sampling equilibrium distributions for stochastic lattice models, capable of handling correctly long and short-range particle interactions. The proposed method is a Metropolis-type…

Numerical Analysis · Mathematics 2010-06-21 Evangelia Kalligiannaki , Markos A. Katsoulakis , Petr Plechac

This paper considers the optimal scaling problem for high-dimensional random walk Metropolis algorithms for densities which are differentiable in Lp mean but which may be irregular at some points (like the Laplace density for example)…

Probability · Mathematics 2016-04-25 Alain Durmus , Sylvain Le Corff , Eric Moulines , Gareth O. Roberts

We consider the problem of metastability for a stochastic dynamics with a parallel updating rule with single spin rates equal to those of the heat bath for the Ising nearest neighbors interaction. We study the exit from the metastable…

Statistical Mechanics · Physics 2009-07-14 Emilio N. M. Cirillo , Francesca R. Nardi

We consider an ordinary differential equation with a unique hyperbolic attractor at the origin, to which we add a small random perturbation. It is known that under general conditions, the solution of this stochastic differential equation…

Probability · Mathematics 2023-05-05 Gerardo Barrera , Milton Jara

We introduce a new approach to an enumerative problem closely linked with the geometry of branched coverings; that is, we study the number of ways a permutation can be decomposed into a product of a given number of 2-cycles, 3-cycles, etc.…

Combinatorics · Mathematics 2007-05-23 John Irving

We study the Markovianity of a composite system and its subsystems. We show how the dissipative nature of a subsystem's dynamics can be modified without having to change properties of the composite system environment. By preparing different…

Quantum Physics · Physics 2015-08-13 Frederico Brito , Thiago Werlang

We consider irreducible reversible discrete time Markov chains on a finite state space. Mixing times and hitting times are fundamental parameters of the chain. We relate them by showing that the mixing time of the lazy chain is equivalent…

Probability · Mathematics 2013-04-30 Yuval Peres , Perla Sousi

A divide-and-conquer approach to analyzing Markov chains (MCs) is not utilized as widely as it could be, despite its potential benefits. One primary reason for this is the fact that most MC decomposition approaches involve a complex and…

Probability · Mathematics 2021-02-25 Katsunobu Sasanuma , Robert Hampshire , Alan Scheller-Wolf

We study the existence of periodic solutions in a class of planar Filippov systems obtained from non-autonomous periodic perturbations of reversible piecewise smooth differential systems. It is assumed that the unperturbed system presents a…

Dynamical Systems · Mathematics 2020-06-15 Douglas D. Novaes , Tere M. Seara , Marco A. Teixeira , Iris O. Zeli

In this reply, we resolve the apparent discrepancy raised in the "Comment on Inferring broken detailed balance in the absence of observable currents" [arXiv:2112.08978v1]. We stress that the non-instantaneous transition paths originate from…

Statistical Mechanics · Physics 2022-02-07 Gili Bisker , Ignacio A. Martinez , Jordan M. Horowitz , Juan MR Parrondo

We exhibit an efficient procedure for testing, based on a single long state sequence, whether an unknown Markov chain is identical to or $\varepsilon$-far from a given reference chain. We obtain nearly matching (up to logarithmic factors)…

Machine Learning · Statistics 2019-09-26 Geoffrey Wolfer , Aryeh Kontorovich