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We address the nonadiabatic quantum dynamics of macrosystems with several coupled electronic states, taking into account the possibility of multi-state conical intersections. The general situation of an arbitrary number of states and…

Chemical Physics · Physics 2009-11-13 Etienne Gindensperger , Lorenz S. Cederbaum

This article provides an introductory tutorial on structural results in partially observed Markov decision processes (POMDPs). Typically, computing the optimal policy of a POMDP is computationally intractable. We use lattice program- ming…

Optimization and Control · Mathematics 2015-12-15 Vikram Krishnamurthy

Deterministic many-body systems governed by simple interactions can self-organize into macroscopic patterns, and the determinants of long-time behavior are assumed to be encoded in the initial configuration. Here we show that predictability…

Biological Physics · Physics 2026-04-02 Lars Koopmans , Elinor M. Kay , Hyun Youk

Markov processes serve as foundational models in many scientific disciplines, such as molecular dynamics, and their simulation forms a common basis for analysis. While simulations produce useful trajectories, obtaining macroscopic…

Chemical Physics · Physics 2024-06-11 Alexander Sikorski , Robert Julian Rabben , Surahit Chewle , Marcus Weber

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

Much of our mechanistic understanding of the functions of biological macromolecules is based on static structural experiments, which can be modelled either as single structures or conformational ensembles. While these provide us with…

Biomolecules · Quantitative Biology 2025-10-02 Daria Gusew , Carl G. Henning Hansen , Kresten Lindorff-Larsen

We study data-driven learning of robust stochastic control for infinite-horizon systems with potentially continuous state and action spaces. In many managerial settings--supply chains, finance, manufacturing, services, and dynamic…

Machine Learning · Statistics 2025-11-18 Shengbo Wang , Jason Meng , Nian Si , Jose Blanchet , Zhengyuan Zhou

This work introduces a non-intrusive model reduction approach for learning reduced models from partially observed state trajectories of high-dimensional dynamical systems. The proposed approach compensates for the loss of information due to…

Machine Learning · Computer Science 2021-03-29 Wayne Isaac Tan Uy , Benjamin Peherstorfer

The dynamics of an infinite system of point particles in $\mathbb{R}^d$, which hop and interact with each other, is described at both micro- and mesoscopic levels. The states of the system are probability measures on the space of…

Probability · Mathematics 2012-08-21 Christoph Berns , Yuri kondratiev , Yuri Kozitsky , Oleksandr Kutoviy

In this review we define and discuss metastates, mathematical tools with general applicability to thermodynamic systems which are particularly useful when working with disordered or inhomogeneous short-range systems. In an infinite such…

Disordered Systems and Neural Networks · Physics 2022-05-03 C. M. Newman , N. Read , D. L. Stein

One of the central aims of neuroscience is to reliably predict the behavioral response of an organism using its neural activity. If possible, this implies we can causally manipulate the neural response and design brain-computer-interface…

Neurons and Cognition · Quantitative Biology 2025-04-01 Jayanth R Taranath

Stochastic resetting describes dynamics which are reinitialized to a reference state at random times. These protocols are attracting significant interest: they can stabilize nonequilibrium stationary states, generate correlations in…

Quantum Physics · Physics 2026-01-21 Federico Carollo , Sascha Wald

The deterministic and time-reversal symmetric dynamics of isolated quantum systems is at odds with irreversible equilibration observed in generic thermodynamic systems. Standard approaches at a reconciliation employ subjective restrictions…

Quantum Physics · Physics 2025-11-07 Aritro Mukherjee

We study a system whose dynamics are governed by predictions of its future states. A general formalism and concrete examples are presented. We find that the dynamical characteristics depend on how to shape the predictions as well as on how…

Other Condensed Matter · Physics 2015-06-25 Toru Ohira

Machine learning techniques not only offer efficient tools for modelling dynamical systems from data, but can also be employed as frontline investigative instruments for the underlying physics. Nontrivial information about the original…

Data Analysis, Statistics and Probability · Physics 2021-02-24 Francesco Borra , Marco Baldovin

I give a highly selective overview of the way statistical mechanics explains the microscopic origins of the time asymmetric evolution of macroscopic systems towards equilibrium and of first order phase transitions in equilibrium. These…

Mathematical Physics · Physics 2009-10-31 Joel L. Lebowitz

Maximum entropy principle identifies forces conjugated to observables and the thermodynamic relations between them, independent upon their underlying mechanistic details. For data about state distributions or transition statistics, the…

Statistical Mechanics · Physics 2023-12-08 Ying-Jen Yang , Hong Qian

The second law of thermodynamics states that entropy production in macroscopic systems is non-negative, reaching zero only at thermodynamic equilibrium. As a corollary, this implies that the state trajectory of macroscopic systems is…

Statistical Mechanics · Physics 2025-01-30 O. Politano , Alejandro L. Garcia , F. Baras , M. Malek Mansour

Thermodynamics is usually formulated on the presumption that the observer has complete information about the system he/she deals with: no parasitic current, exact evaluation of the forces that drive the system. For example, the acclaimed…

Statistical Mechanics · Physics 2017-12-15 Matteo Polettini , Massimiliano Esposito

Dynamical models underpin our ability to understand and predict the behavior of natural systems. Whether dynamical models are developed from first-principles derivations or from observational data, they are predicated on our choice of state…

Machine Learning · Computer Science 2023-01-11 Daniel Floryan , Michael D. Graham
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