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We introduce a set of techniques that allow for efficiently generating many independent random walks in the Massive Parallel Computation (MPC) model with space per machine strongly sublinear in the number of vertices. In this…

Data Structures and Algorithms · Computer Science 2019-11-07 Jakub Łącki , Slobodan Mitrović , Krzysztof Onak , Piotr Sankowski

We introduce a statistical mechanics formalism for the study of constrained graph evolution as a Markovian stochastic process, in analogy with that available for spin systems, deriving its basic properties and highlighting the role of the…

Disordered Systems and Neural Networks · Physics 2015-05-13 A. C. C. Coolen , A. De Martino , A. Annibale

This paper deals with control of partially observable discrete-time stochastic systems. It introduces and studies Markov Decision Processes with Incomplete Information and with semi-uniform Feller transition probabilities. The important…

Optimization and Control · Mathematics 2022-08-30 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

We introduce a computational framework for generating realistic transition paths between distinct conformations of large bio-molecular systems. The method is built on a stochastic integro-differential formulation derived from the Langevin…

Biomolecules · Quantitative Biology 2025-12-02 Patrice Koehl , Marc Delarue , Henri Orland

The large deviation theory has recently been applied to open quantum systems to uncover dynamical crossovers in the space of quantum trajectories associated to Markovian evolutions. Such dynamical crossovers are characterized by qualitative…

Optimal sampled-data control of a nonlinear system is considered with the stable-manifold approach and extensive use of numerical techniques. The idea is to notice the Hamiltonian system associated with the considered optimal control…

Systems and Control · Electrical Eng. & Systems 2021-12-30 Yasuaki Oishi , Noboru Sakamoto

The parameters of a discrete stationary Markov model are transition probabilities between states. Traditionally, data consist in sequences of observed states for a given number of individuals over the whole observation period. In such a…

Computation · Statistics 2012-04-30 Alberto Pasanisi , Shuai Fu , Nicolas Bousquet

The Langevin dynamics of a random heteropolymer and its dynamic glass transition are studied using elementary mode coupling theory. Contrary to recent reports using a similar framework, a discontinuous ergodic-nonergodic phase transition is…

Statistical Mechanics · Physics 2009-10-30 Shoji Takada , John J. Portman , Peter G. Wolynes

This paper establishes a Transition Path Theory (TPT) for L\'{e}vy-type processes, addressing a critical gap in the study of the transition mechanism between meta-stabile states in non-Gaussian stochastic systems. A key contribution is the…

Probability · Mathematics 2026-05-04 Yuanfei Huang , Xiang Zhou

Path reweighting is a principally exact method to estimate dynamic properties from biased simulations - provided that the path probability ratio matches the stochastic integrator used in the simulation. Previously reported path probability…

Chemical Physics · Physics 2021-03-02 Stefanie Kieninger , Bettina G. Keller

As written by statistician George Box "All models are wrong, but some are useful", standard diffusion derivation or Feynman path ensembles use nonphysical infinite velocity/kinetic energy nowhere differentiable trajectories - what seems…

Statistical Mechanics · Physics 2024-04-23 Jarek Duda

We present a closed-form, computable expression for the expected number of times any transition event occurs during the transient phase of a reducible Markov chain. Examples of events include time to absorption, number of visits to a state,…

Probability · Mathematics 2017-06-09 Brian D. Ewald , Jeffrey Humpherys , Jeremy West

This paper proposes a fully data-driven approach for optimal control of nonlinear control-affine systems represented by a stochastic diffusion. The focus is on the scenario where both the nonlinear dynamics and stage cost functions are…

Optimization and Control · Mathematics 2025-11-03 Nicolas Hoischen , Petar Bevanda , Stefan Sosnowski , Sandra Hirche , Boris Houska

The probability distributions, as well as the mean values of stochastic currents and fluxes, associated with a driven Langevin process, provide a good and topologically protected measure of how far a stochastic system is driven out of…

Chemical Physics · Physics 2017-01-04 Michael J. Catanzaro , Vladimir Y. Chernyak , John R. Klein

The probability of trajectories of weakly diffusive processes to remain in the tubular neighbourhood of a smooth path is given by the Freidlin-Wentzell-Graham theory of large deviations. The most probable path between two states (the…

Statistical Mechanics · Physics 2020-08-12 Lukas Kikuchi , Rajesh Singh , Mike E. Cates , Ronojoy Adhikari

Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or engineering applications. Since many areas, such as biology or discrete-event systems, are…

Machine Learning · Computer Science 2021-09-30 Lukas Köhs , Bastian Alt , Heinz Koeppl

We consider a class of optimal control problems, with finite or infinite horizon, for a continuous-time Markov chain with finite state space. In this case, the control process affects the transition rates. We suppose that the controlled…

Optimization and Control · Mathematics 2026-02-19 Fulvia Confortola , Marco Fuhrman

We study the role of quantum fluctuations of atomic nuclei in the real-time dynamics of non-equilibrium macro-molecular transitions. To this goal we introduce an extension of the Dominant Reaction Pathways (DRP) formalism, in which the…

Biological Physics · Physics 2015-05-20 S. a Beccara , G. Garberoglio , P. Faccioli

We study the problem of estimating the value function of discrete-time switched systems under arbitrary switching. Unlike the switched LQR problem, where both inputs and mode sequences are optimized, we consider the case where switching is…

Optimization and Control · Mathematics 2026-02-05 Léa Ninite , Adrien Banse , Guillaume O. Berger , Raphaël M. Jungers

Pedestrian crowds encompass a complex interplay of intentional movements aimed at reaching specific destinations, fluctuations due to personal and interpersonal variability, and interactions with each other and the environment. Previous…

Physics and Society · Physics 2025-03-10 Caspar A. S. Pouw , Geert G. M. van der Vleuten , Alessandro Corbetta , Federico Toschi