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A causal input-output system may be described by a function space for inputs, a function space for outputs, and a causal operator mapping the input space into the output space. A particular representation of the state of such a system at…

Dynamical Systems · Mathematics 2010-09-28 Demetrios Serakos

This article proposes a dynamical system modeling approach for the analysis of longitudinal data of self-regulated systems experiencing multiple excitations. The aim of such an approach is to focus on the evolution of a signal (e.g., heart…

We consider nonequilibrium systems with complex dynamics in stationary states with large fluctuations of intensive quantities (e.g. the temperature, chemical potential, or energy dissipation) on long time scales. Depending on the…

Statistical Mechanics · Physics 2009-11-07 C. Beck , E. G. D. Cohen

This thesis develops exact analytical tools to study strongly correlated stochastic systems, with a focus on extreme value statistics, gap statistics, and full counting statistics in multi-particle processes. A central contribution is the…

Statistical Mechanics · Physics 2025-08-19 Marco Biroli

The present communication addresses a set of observations, obeying both deterministic as well as statistical formal requirements, and serving to operate within the framework of the dynamical systems theory, with a certain emphasis placed on…

Physics and Society · Physics 2017-06-30 Adam Gadomski , Marcel Ausloos , Tahlia Casey

Sometimes we obtain attractive results when associating facts to simple elements. The goal of this work is to introduce a possible alternative in the study of the dynamics of rational maps.

Dynamical Systems · Mathematics 2010-02-02 H. Melo , J. Cabral

The topic of statistical inference for dynamical systems has been studied extensively across several fields. In this survey we focus on the problem of parameter estimation for non-linear dynamical systems. Our objective is to place results…

Statistics Theory · Mathematics 2012-06-19 Kevin McGoff , Sayan Mukherjee , Natesh S. Pillai

Multivariate Analysis is an increasingly common tool in experimental high energy physics; however, many of the common approaches were borrowed from other fields. We clarify what the goal of a multivariate algorithm should be for the search…

Data Analysis, Statistics and Probability · Physics 2014-11-18 Kyle S. Cranmer

This paper presents an operator-theoretic framework Linear Operator Causality Analysis (LOCA), for analysing causality in linearised dynamical systems, focusing here on fluid flows. We demonstrate that the matrix exponential of the…

Chaotic Dynamics · Physics 2025-07-15 Ankit Srivastava , Louis Cattafesta , Scott Dawson

In this thesis, we use classical, semi-classical and quantum-mechanical methods to simulate chemical reaction dynamics inside of an optical cavity. Within such a cavity, by selectively coupling vibrational modes of the reactants to the…

Chemical Physics · Physics 2024-02-08 Andrew C. Hunt

Measurements of the peculiar velocities of large samples of galaxies enable new tests of the standard cosmological model, including determination of the growth rate of cosmic structure that encodes gravitational physics. With the size of…

Cosmology and Nongalactic Astrophysics · Physics 2023-10-19 Chris Blake , Ryan J. Turner

Even though the phenomenological relations between perception and stimulus have been firmly established, a theoretical argument for Weber's and Fechner's law in terms of relevant models or from statistical physics is largely missing. We…

Statistical Mechanics · Physics 2021-03-17 Christian Maes

In social sciences and economics, causal inference traditionally focuses on assessing the impact of predefined treatments (or interventions) on predefined outcomes, such as the effect of education programs on earnings. Causal discovery, in…

Econometrics · Economics 2024-07-12 Martin Huber

The primary emphasis of this work on kinetics is to illustrate the a posteriori approach to applications, where focus on data leads to novel outcomes, rather than the a priori tendencies of applied analysis which imposes constructs on the…

General Physics · Physics 2011-01-27 Christopher G. Jesudason

It is shown that the statistical conception of quantum mechanics is dynamical but not probabilistic, i.e. the statistical description in quantum mechanics is founded on dynamics. A use of the probability theory, when it takes place, is…

Quantum Physics · Physics 2007-05-23 Yuri A. Rylov

This paper serves as a starting point for machine learning researchers, engineers and students who are interested in but not yet familiar with causal inference. We start by laying out an important set of assumptions that are collectively…

Machine Learning · Computer Science 2024-08-28 Daniel Jiwoong Im , Kyunghyun Cho

Causal structure learning from observational data remains a non-trivial task due to various factors such as finite sampling, unobserved confounding factors, and measurement errors. Constraint-based and score-based methods tend to suffer…

Machine Learning · Computer Science 2022-11-09 Rezaur Rashid , Jawad Chowdhury , Gabriel Terejanu

In studies of entanglement, finding out if a state is entangled and quantifying the amount of entanglement contained in a state are related but different questions. Similarly in studies of causality, finding out the causal structures…

Quantum Physics · Physics 2018-01-22 Ding Jia

Statistical physics provides a useful perspective for the analysis of many complex systems; it allows us to relate microscopic fluctuations to macroscopic observations. Developmental biology, but also cell biology more generally, are…

Cell Behavior · Quantitative Biology 2020-11-10 Anissa Guillemin , Michael P. H. Stumpf

Processes occurring in real open systems are far from equilibrium state and they can lead to synergetic effects, which are caused by coordinated behavior of system units. Traditional methods of analysis often just establish such behavior,…

Computational Physics · Physics 2007-05-23 E. N. Vertyagina