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We introduce a novel characterization of phase transitions based on hypothesis testing. In our formulation, a phase transition is defined as the breakdown of statistical indistinguishability under vanishing parameter perturbations in the…

Statistical Mechanics · Physics 2026-04-20 Taiyo Narita , Hideyuki Miyahara

In self-gravitating stars, two dimensional or geophysical flows and in plasmas, long range interactions imply a lack of additivity for the energy; as a consequence, the usual thermodynamic limit is not appropriate. However, by contrast with…

Statistical Mechanics · Physics 2009-11-13 Freddy Bouchet , Julien Barré , Antoine Venaille

The deep connection between entropy and information is discussed in terms of both classical and quantum physics. The mechanism of information transfer between systems via entanglement is explored in the context of decoherence theory. The…

Quantum Physics · Physics 2021-01-05 Martin Paul Vaughan

How do decisions change with the economic environment and with time? This paper studies general nonstationary stopping problems and provides the methodological tools to answer these questions. First, we identify conditions that ensure a…

Theoretical Economics · Economics 2024-08-01 Théo Durandard , Matteo Camboni

We address the excess entropy, which is a measure of complexity for stationary time series, from the ordinal point of view. We show that the permutation excess entropy is equal to the mutual information between two adjacent semi-infinite…

Chaotic Dynamics · Physics 2011-12-13 Taichi Haruna , Kohei Nakajima

The characterization of collective behavior and nonequilibrium phase transitions in quantum systems is typically rooted in the analysis of suitable system observables, so-called order parameters. These observables might not be known a…

Quantum Physics · Physics 2026-02-20 Erik Fitzner , Francesco Carnazza , Federico Carollo , Igor Lesanovsky

Deterministic chaos permits a precise notion of a "perfect measurement" as one that, when obtained repeatedly, captures all of the information created by the system's evolution with minimal redundancy. Finding an optimal measurement is…

Machine Learning · Computer Science 2024-03-21 Kieran A. Murphy , Dani S. Bassett

A new measure of information in quantum mechanics is proposed which takes into account that for quantum systems the only feature known before an experiment is performed are the probabilities for various events to occur. The sum of the…

Quantum Physics · Physics 2009-11-06 Caslav Brukner , Anton Zeilinger

A central concern across the natural sciences is a quantitative understanding of the mechanism governing rare transitions between two metastable states. Recent research has uncovered a fundamental equality between the time-reversal…

Statistical Mechanics · Physics 2024-12-30 Miranda D. Louwerse , David A. Sivak

Two zero-range-interacting atoms in a circular, transversely harmonic waveguide are used as a test-bench for a quantitative description of the crossover between integrability and chaos in a quantum system with no selection rules. For such…

Quantum Gases · Physics 2015-05-14 Maxim Olshanii , Vladimir Yurovsky

We introduce a method for learning the dynamics of complex nonlinear systems based on deep generative models over temporal segments of states and actions. Unlike dynamics models that operate over individual discrete timesteps, we learn the…

Machine Learning · Computer Science 2017-07-14 Nikhil Mishra , Pieter Abbeel , Igor Mordatch

Often in Phase 3 clinical trials measuring a long-term time-to-event endpoint, such as overall survival or progression-free survival, investigators also collect repeated measures on biomarkers which may be predictive of the primary…

Methodology · Statistics 2022-11-30 Abigail J. Burdon , Lisa V. Hampson , Christopher Jennison

Whereas the importance of transient dynamics to the functionality and management of complex systems has been increasingly recognized, most of the studies are based on models. Yet in realistic situations the models are often unknown and what…

Adaptation and Self-Organizing Systems · Physics 2021-10-25 Huawei Fan , Liang Wang , Yao Du , Yafeng Wang , Jinghua Xiao , Xingang Wang

An approach for the description of stochastic systems is derived. Some of the variables in the system are studied forward in time, others backward in time. The approach is based on a perturbation expansion in the strength of the coupling…

Statistical Mechanics · Physics 2021-08-04 Piero Olla

This paper studies the informativity problem for reachability and null-controllability of constrained systems. To be precise, we will focus on an unknown linear systems with convex conic constraints from which we measure data consisting of…

Optimization and Control · Mathematics 2021-05-03 Jaap Eising , M. Kanat Camlibel

High-dimensional multivariate longitudinal data, which arise when many outcome variables are measured repeatedly over time, are becoming increasingly common in social, behavioral and health sciences. We propose a latent variable model for…

Methodology · Statistics 2025-12-09 Sze Ming Lee , Yunxiao Chen , Tony Sit

This Thesis explores how tools from Statistical Physics and Information Theory can help us describe and understand complex systems. In the first part, we study the interplay between internal interactions, environmental changes, and…

Statistical Mechanics · Physics 2023-03-01 Giorgio Nicoletti

The ability to predict the future in a given domain can be acquired by discovering empirically from experience certain temporal patterns that tend to repeat unerringly. Previous works in time series analysis allow one to make quantitative…

Artificial Intelligence · Computer Science 2013-04-12 Kaihu Chen

In a physical system, changing parameters such as temperature can induce a phase transition: an abrupt change from one state of matter to another. Analogous phenomena have recently been observed in large language models. Typically, the task…

Machine Learning · Computer Science 2024-05-28 Julian Arnold , Flemming Holtorf , Frank Schäfer , Niels Lörch

Low-dimensional representations of underdamped systems often provide insightful grasps and analytical tractability. Here, we build such representations via information projections, obtaining an optimal model that captures the most…

Statistical Mechanics · Physics 2022-08-10 Giorgio Nicoletti , Amos Maritan , Daniel M. Busiello