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In this work, we investigate the relation between the concept of ``information rate'', an information geometric method for measuring the speed of the time evolution of the statistical states of a stochastic process, and stochastic…

Statistical Mechanics · Physics 2023-03-29 Adrian-Josue Guel-Cortez , Eun-jin Kim

We study finite memory belief approximation for partially observable (PO) stochastic optimal control (SOC) problems. While belief states are sufficient for SOC in partially observable Markov decision processes (POMDPs), they are generally…

Systems and Control · Electrical Eng. & Systems 2026-01-07 Mintae Kim

We theoretically derive and experimentally compare several different ways to access entropy production in a quantum process under feedback control. We focus on a bipartite quantum system realizing an autonomous Maxwell's demon scheme…

External piecewise-constant feedback control can modify energetic and entropic balances, allowing in extreme scenarios for Maxwell demon operational modes. Without specifying the actual implementation of external feedback loops, one can…

Statistical Mechanics · Physics 2024-07-30 Gernot Schaller

The second law of thermodynamics states that entropy production cannot be negative. Recent developments concerning uncertainty relations in stochastic thermodynamics, such as thermodynamic uncertainty relations and speed limits, have…

Statistical Mechanics · Physics 2023-10-09 Tomohiro Nishiyama , Yoshihiko Hasegawa

How biological networks achieve robust control despite relying on imperfect, local information remains an important open question. Here, we identify thermodynamic constraints that can curtail non-equilibrium steady-state responses so…

Statistical Mechanics · Physics 2026-05-27 Carlos Floyd , Aaron R. Dinner , Suriyanarayanan Vaikuntanathan

We propose a novel, tractable latent state inference scheme for Markov jump processes, for which exact inference is often intractable. Our approach is based on an entropic matching framework that can be embedded into the well-known…

Machine Learning · Computer Science 2026-02-27 Yannick Eich , Bastian Alt , Heinz Koeppl

We investigate the problem of synthesizing optimal control policies for Markov decision processes (MDPs) with both qualitative and quantitative objectives. Specifically, our goal is to achieve a given linear temporal logic (LTL) task with…

Systems and Control · Electrical Eng. & Systems 2025-04-08 Yu Chen , Shaoyuan Li , Xiang Yin

The finite state semi-Markov process is a generalization over the Markov chain in which the sojourn time distribution is any general distribution. In this article we provide a sufficient stochastic maximum principle for the optimal control…

Optimization and Control · Mathematics 2014-07-14 Amogh Deshpande

Landauer's limit on heat dissipation during information erasure is critical as devices shrink, requiring optimal pure-state preparation to minimise errors. However, Nernst's third law states this demands infinite resources in energy, time,…

We investigate the finite time thermodynamics of a single-level fermion system interacting with a thermal reservoir through a tunneling junction. The optimal protocol to extract the maximum work from the system when moving the single energy…

Statistical Mechanics · Physics 2015-05-14 Massimiliano Esposito , Ryoichi Kawai , Katja Lindenberg , Christian Van den Broeck

Thermodynamic principles governing energy and information are important tools for a deeper understanding and better control of quantum systems. In this work, we experimentally investigate the interplay of the thermodynamic costs and…

Entropy production and the detailed fluctuation theorem are of fundamental importance for thermodynamic processes. In this paper, we study the multiple entropy production for multitime quantum processes in a unified framework. For closed…

Quantum Physics · Physics 2023-09-27 Zhiqiang Huang

We investigate thermodynamics of feedback processes driven by measurement. Regarding system and memory device as a composite system, mutual information as a measure of correlation between the two constituents contributes to the entropy of…

Statistical Mechanics · Physics 2017-04-12 Chulan Kwon

The emergence of irreversibility in physical processes, despite the fundamentally reversible nature of quantum mechanics, remains an open question in physics. This thesis explores the intricate relationship between quantum mechanics and…

Quantum Physics · Physics 2024-10-25 Alberto Rolandi

Differential geometry offers a powerful framework for optimising and characterising finite-time thermodynamic processes, both classical and quantum. Here, we start by a pedagogical introduction to the notion of thermodynamic length. We…

Quantum Physics · Physics 2021-08-31 Paolo Abiuso , Harry J. D. Miller , Martí Perarnau-Llobet , Matteo Scandi

Hidden information emerges under impulse interactions with Markov diffusion process modeling interactive random environment. Impulse yes no action cuts Markov correlations revealing Bit of hidden information connected correlated states.…

Adaptation and Self-Organizing Systems · Physics 2019-05-16 Vladimir S. Lerner

We consider optimization of the average entropy production in inhomogeneous temperature environments within the framework of stochastic thermodynamics. For systems modeled by Langevin equations (e.g. a colloidal particle in a heat bath) it…

Statistical Mechanics · Physics 2013-03-14 Stefano Bo , Erik Aurell , Ralf Eichhorn , Antonio Celani

The thermodynamics of stochastic non-Markovian systems is still widely unexplored. We present an analytical approach for the net steady-state heat flux in nonlinear overdamped systems subject to a continuous feedback force with a discrete…

Statistical Mechanics · Physics 2019-02-22 Sarah A. M. Loos , Sabine H. L. Klapp

The selection of an equilibrium state by maximising the entropy of a system, subject to certain constraints, is often powerfully motivated as an exercise in logical inference, a procedure where conclusions are reached on the basis of…

Statistical Mechanics · Physics 2015-12-03 Ian J. Ford