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The general framework of entropic dynamics is used to formulate a relational quantum dynamics. The main new idea is to use tools of information geometry to develop an entropic measure of the mismatch between successive configurations of a…

Quantum Physics · Physics 2016-01-11 Selman Ipek , Ariel Caticha

A rational theory is proposed to describe the large-scale motion in turbulence. The fluid element with inner orientational structures is proposed to be the building block of fluid dynamics. The variance of the orientational structures then…

Fluid Dynamics · Physics 2011-05-31 Wennan Zou

A probabilistic framework is proposed for the optimization of efficient switched control strategies for physical systems dominated by stochastic excitation. In this framework, the equation for the state trajectory is replaced with an…

Systems and Control · Computer Science 2017-01-10 Gianluca Meneghello , Paolo Luchini , Thomas Bewley

The classical fluctuation-dissipation theorem predicts the average response of a dynamical system to an external deterministic perturbation via time-lagged statistical correlation functions of the corresponding unperturbed system. In this…

Chaotic Dynamics · Physics 2017-02-28 Rafail V. Abramov

Lagrangian multiform theory is a variational framework for integrable systems. In this article we introduce a new formulation which is based on symplectic geometry and which treats position, momentum and time coordinates of a…

Mathematical Physics · Physics 2025-04-01 Vincent Caudrelier , Derek Harland

Using equilibrium fluctuations to understand the response of a physical system to an externally imposed perturbation is the basis for linear response theory, which is widely used to interpret experiments and shed light on microscopic…

Statistical Mechanics · Physics 2024-06-24 Jérémie Klinger , Grant M. Rotskoff

We introduce a novel framework for causal explanations of stochastic, sequential decision-making systems built on the well-studied structural causal model paradigm for causal reasoning. This single framework can identify multiple,…

Artificial Intelligence · Computer Science 2023-01-12 Samer B. Nashed , Saaduddin Mahmud , Claudia V. Goldman , Shlomo Zilberstein

The constituents of a complex system exchange information to function properly. Their signalling dynamics often leads to the appearance of emergent phenomena, such as phase transitions and collective behaviors. While information exchange…

Physics and Society · Physics 2020-11-18 Arsham Ghavasieh , Carlo Nicolini , Manlio De Domenico

We study the counter terms in the Eulerian version of the EFT of Large Scale Structure. We reformulate the equations to solve for the displacement of fluid elements as a bookkeeping variable and study the structure of the counter terms in…

Cosmology and Nongalactic Astrophysics · Physics 2015-11-06 Matias Zaldarriaga , Mehrdad Mirbabayi

In recently introduced schematic lattice gas models for vibrated dry granular media, we study the dynamical response of the system to small perturbations of shaking amplitudes and its relations with the characteristic fluctuations. Strong…

Condensed Matter · Physics 2009-10-31 Mario Nicodemi

We study the impact of stochastic perturbations to deterministic dynamical systems using the formalism of the Ruelle response theory and explore how stochastic noise can be used to explore the properties of the underlying deterministic…

Statistical Mechanics · Physics 2015-05-27 Valerio Lucarini

The Lie product and the order relation are viewed as defining structures for Hamiltonian dynamical systems. Their admissible combinations are singled out by the requirement that the group of the Lie automorphisms be contained in the group…

Quantum Physics · Physics 2007-05-23 A. Petrov

I discuss the design of the method of entropic inference as a general framework for reasoning under conditions of uncertainty. The main contribution of this discussion is to emphasize the pragmatic elements in the derivation. More…

History and Philosophy of Physics · Physics 2014-12-19 Ariel Caticha

We define the class of multivariate group entropies as a novel set of information - theoretical measures, which extends significantly the family of group entropies. We propose new examples related to the "super-exponential" universality…

Mathematical Physics · Physics 2020-12-03 Piergiulio Tempesta

We present a general setting in which the formula describing the linear response of the physical measure of a perturbed system can be obtained. In this general setting we obtain an algorithm to rigorously compute the linear response. We…

Dynamical Systems · Mathematics 2017-08-30 Wael Bahsoun , Stefano Galatolo , Isaia Nisoli , Xiaolong Niu

Recurrence rate, determinism, average line length, and entropy of line lengths are measures of complexity in recurrence quantification analysis, that help to understand the structure, predictability and complexity of dynamical systems. In…

Dynamical Systems · Mathematics 2023-10-19 Miroslava Poláková , Vladimír Špitalský

It is a mystery which input features contribute to a neural network's output. Various explanation (feature attribution) methods are proposed in the literature to shed light on the problem. One peculiar observation is that these explanations…

Machine Learning · Computer Science 2022-03-07 Ashkan Khakzar , Pedram Khorsandi , Rozhin Nobahari , Nassir Navab

This note provides a comprehensive examination of the various approaches to formulating relativistic hydrodynamics, with a particular emphasis on the canonical approach. Relativistic hydrodynamics plays a crucial role in understanding the…

High Energy Physics - Theory · Physics 2025-02-11 Luca Martinoia , Rajeev Singh

The maximum entropy approach operating with quite general entropy measure and constraint is considered. It is demonstrated that for a conditional or parametrized probability distribution $f(x|\mu)$ there is a "universal" relation among the…

Statistical Mechanics · Physics 2015-05-19 E. V. Vakarin , J. P. Badiali

Chemical reactions are the fundamental building blocks of drug design and organic chemistry research. In recent years, there has been a growing need for a large-scale deep-learning framework that can efficiently capture the basic rules of…

Machine Learning · Computer Science 2024-03-08 Bo Qiang , Yiran Zhou , Yuheng Ding , Ningfeng Liu , Song Song , Liangren Zhang , Bo Huang , Zhenming Liu