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Inverse optimal control can be used to characterize behavior in sequential decision-making tasks. Most existing work, however, is limited to fully observable or linear systems, or requires the action signals to be known. Here, we introduce…

Machine Learning · Computer Science 2023-10-31 Dominik Straub , Matthias Schultheis , Heinz Koeppl , Constantin A. Rothkopf

A reasonable description of the degradation process is essential for credible reliability assessment in accelerated degradation testing. Existing methods usually use Markovian stochastic processes to describe the degradation process.…

Applications · Statistics 2025-06-12 Shi-Shun Chen , Xiao-Yang Li , Wenrui Xie

In this paper we derive novel change of variable formulas for stochastic integrals w.r.t. a time-changed Brownian motion where we assume that the time-change is a general increasing stochastic process with finitely many jumps in a bounded…

Probability · Mathematics 2024-07-04 Giulia Di Nunno , Hannes Haferkorn , Asma Khedher , Michèle Vanmaele

We consider a class of stochastic gradient optimization schemes. Assuming that the objective function is strongly convex, we prove weak error estimates which are uniform in time for the error between the solution of the numerical scheme,…

Numerical Analysis · Mathematics 2026-01-27 Charles-Edouard Bréhier , Marc Dambrine , Nassim En-Nebbazi

Exact generalized stochastic representation of deterministic interaction between two dynamical (quantum or classical) systems is derived which helps when considering one of them to replace another by equivalent commutative ($c$-number…

Statistical Mechanics · Physics 2007-05-23 Yuriy E. Kuzovlev

Adiabatic Quantum Computing relies on the quantum adiabatic theorem, which states that a quantum system evolves along its ground state with time if the governing Hamiltonian varies infinitely slowly. However, practical limitations force…

We analyse the efficiency of several simulation methods which we have recently proposed for calculating rate constants for rare events in stochastic dynamical systems, in or out of equilibrium. We derive analytical expressions for the…

Other Condensed Matter · Physics 2009-11-11 Rosalind J. Allen , Daan Frenkel , Pieter Rein ten Wolde

One of the major resource requirements of computers - ranging from biological cells to human brains to high-performance (engineered) computers - is the energy used to run them. Those costs of performing a computation have long been a focus…

Statistical Mechanics · Physics 2025-08-06 David H. Wolpert

Extensive time-series encoding the position of particles such as viruses, vesicles, or individual proteins are routinely garnered in single-particle tracking experiments or supercomputing studies. They contain vital clues on how viruses…

In this paper we investigate the normal and the large fluctuations of additive functionals associated with a stochastic process under a general non-Poissonian resetting mechanism. Cumulative functionals of regenerative processes are very…

Probability · Mathematics 2023-04-24 Marco Zamparo

The context of the present paper is stochastic thermodynamics - an approach to nonequilibrium thermodynamics rooted within the broader framework of stochastic control. In contrast to the classical paradigm of Carnot engines, we herein…

Systems and Control · Electrical Eng. & Systems 2021-01-08 Rui Fu , Olga Movilla Miangolarra , Amirhossein Taghvaei , Yongxin Chen , Tryphon T. Georgiou

The stochastic trajectories of molecules in living cells, as well as the dynamics in many other complex systems, often exhibit memory in their path over long periods of time. In addition, these systems can show dynamic heterogeneities due…

Statistical Mechanics · Physics 2024-07-10 Michał Balcerek , Agnieszka Wyłomańska , Krzysztof Burnecki , Ralf Metzler , Diego Krapf

Herein we develop a dynamical foundation for fractional Brownian Motion. A clear relation is established between the asymptotic behaviour of the correlation function and diffusion in a dynamical system. Then, assuming that scaling is…

chao-dyn · Physics 2008-02-03 R Mannella , P Grigolini , BJ West

We devise a distributed asynchronous stochastic epsilon-gradient-based algorithm to enable a network of computing and communicating nodes to solve a constrained discrete-time time-varying stochastic convex optimization problem. Each node…

Optimization and Control · Mathematics 2014-10-02 Andrea Simonetto , Leon Kester , Geert Leus

We study a stochastic control system involving both a standard and a fractional Brownian motion with Hurst parameter less than 1/2. We apply an anticipative Girsanov transformation to transform the system into another one, driven only by…

Optimization and Control · Mathematics 2016-05-06 Rainer Buckdahn , Shuai Jing

One century after Einstein's work, Brownian Motion still remains both a fundamental open issue and a continous source of inspiration for many areas of natural sciences. We first present a discussion about stochastic and deterministic…

Chaotic Dynamics · Physics 2009-11-10 Fabio Cecconi , Massimo Cencini , Massimo Falcioni , Angelo Vulpiani

We consider a stochastic control model driven by a fractional Brownian motion. This model is a formal approximation to a queueing network with an on-off input process. We study stochastic control problems associated with the long-run…

Probability · Mathematics 2008-08-12 Arka P. Ghosh , Alexander Roitershtein , Ananda Weerasinghe

We present a new stochastic approach to describe and remodel the conversion process of a wind farm at a sampling frequency of 1Hz. When conditioning on various wind direction sectors, the dynamics of the conversion process appear as a…

Data Analysis, Statistics and Probability · Physics 2015-09-11 Patrick Milan , Matthias Wächter , Joachim Peinke

We generalize stochastic thermodynamics to include information reservoirs. Such information reservoirs, which can be modeled as a sequence of bits, modify the second law. For example, work extraction from a system in contact with a single…

Statistical Mechanics · Physics 2014-11-17 Andre C. Barato , Udo Seifert

Stochastic integration \textit{wrt} Gaussian processes has raised strong interest in recent years, motivated in particular by its applications in Internet traffic modeling, biomedicine and finance. The aim of this work is to define and…

Probability · Mathematics 2018-02-15 Joachim Lebovits