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A simplified version of a classical problem in thermodynamics -- the adiabatic piston -- is discussed in the framework of kinetic theory. We consider the limit of gases whose relaxation time is extremely fast so that the gases contained on…

Chaotic Dynamics · Physics 2009-11-11 Massimo Cencini , Luigi Palatella , Simone Pigolotti , Angelo Vulpiani

In modeling multivariate time series for either forecast or policy analysis, it would be beneficial to have figured out the cause-effect relations within the data. Regression analysis, however, is generally for correlation relation, and…

Machine Learning · Statistics 2021-11-23 Xingwei Hu

We compute statistical properties of the lowest-order multipole coefficients of the magnetic field generated by a dynamo of arbitrary shape. To this end we expand the field in a complete biorthogonal set of base functions, viz. B = sum_k…

Earth and Planetary Astrophysics · Physics 2015-05-13 P. Hoyng

Cells and organisms follow aligned structures in their environment, a process that can generate persistent migration paths. Kinetic transport equations are a popular modelling tool for describing biological movements at the mesoscopic…

Cell Behavior · Quantitative Biology 2021-01-13 Nadia Loy , Thomas Hillen , Kevin John Painter

In this work, the causality and stability of a first-order relativistic dissipative hydrodynamic theory, that redefines the hydrodynamic fields from a first principle microscopic estimation, have been analyzed. A generic approach of…

Nuclear Theory · Physics 2022-06-08 Sukanya Mitra

We propose an approach for learning the causal structure in stochastic dynamical systems with a $1$-step functional dependency in the presence of latent variables. We propose an information-theoretic approach that allows us to recover the…

Information Theory · Computer Science 2017-01-25 Saber Salehkaleybar , Jalal Etesami , Negar Kiyavash

When observational data is available from practical studies and a directed cyclic graph for how various variables affect each other is known based on substantive understanding of the process, we consider a problem in which a control plan of…

Methodology · Statistics 2012-06-26 Manabu Kuroki , Zhihong Cai

Recent developments in structural equation modeling have produced several methods that can usually distinguish cause from effect in the two-variable case. For that purpose, however, one has to impose substantial structural constraints or…

Artificial Intelligence · Computer Science 2015-04-23 Kun Zhang , Jiji Zhang , Bernhard Schölkopf

We introduce and analyze a model for the transport of particles or energy in extended lattice systems. The dynamics of the model acts on a discrete phase space at discrete times but has nonetheless some of the characteristic properties of…

Mathematical Physics · Physics 2015-06-12 Raphael Lefevere

We derive the set of inequalities that is necessary and sufficient for nonlinear causality and linear stability of first-order relativistic hydrodynamics with either a $U(1)_V$ conserved current or a $U(1)_A$ current with a chiral anomaly…

High Energy Physics - Theory · Physics 2024-09-11 Nick Abboud , Enrico Speranza , Jorge Noronha

We consider the time-harmonic Maxwell equations at a nonzero wavenumber $k\in\mathbb{C}$ on a bounded and simply connected Lipschitz domain $\Omega$ with an analytic boundary $\Gamma$, on which we impose impedance boundary conditions. We…

Analysis of PDEs · Mathematics 2026-03-18 Jens Markus Melenk , David Wörgötter

It is shown how to explicitly coarse-grain the microscopic dynamics of the Vicsek model for self-propelled agents. The macroscopic transport equations are derived by means of an Enskog-type kinetic theory. Expressions for all transport…

Biological Physics · Physics 2015-02-24 Thomas Ihle

In the present paper the macroscopic limits of the kinetic model for inter-acting entities (individuals, organisms, cells) are studied. The kinetic model is one-dimensional and entities are characterized by their position and orientation…

Analysis of PDEs · Mathematics 2012-07-12 Jacek Banasiak , Miroslaw Lachowicz

Prior work has shown that causal structure can be uniquely identified from observational data when these follow a structural equation model whose error terms have equal variances. We show that this fact is implied by an ordering among…

Methodology · Statistics 2021-05-25 Wenyu Chen , Mathias Drton , Y. Samuel Wang

Starting from certain causality conditions and a discrete form of general covariance, we derive a very general family of classically stochastic, sequential growth dynamics for causal sets. The resulting theories provide a relatively…

General Relativity and Quantum Cosmology · Physics 2011-05-05 D. P. Rideout , R. D. Sorkin

Temporally evolving systems are typically modeled by dynamic equations. A key challenge in accurate modeling is understanding the causal relationships between subsystems, as well as identifying the presence and influence of unobserved…

Methodology · Statistics 2024-10-28 András Telcs , Marcell T. Kurbucz , Antal Jakovác

Predicting the effect of unseen interventions is a fundamental research question across the data sciences. It is well established that in general such questions cannot be answered definitively from observational data. This realization has…

Machine Learning · Statistics 2024-05-27 Alexis Bellot

We introduce a class of Kac-like kinetic equations on the real line, with general random collisional rules, which include as particular cases models for wealth redistribution in an agent-based market or models for granular gases with a…

Mathematical Physics · Physics 2015-05-20 Federico Bassetti , Lucia Ladelli , Giuseppe Toscani

Many physical phenomena occur on domains that grow in time. When the timescales of the phenomena and domain growth are comparable, models must include the dynamics of the domain. A widespread intrinsically slow transport process is…

Statistical Mechanics · Physics 2017-11-01 C. N. Angstmann , B. I. Henry , A. V. McGann

This paper introduces a new framework for recovering causal graphs from observational data, leveraging the observation that the distribution of an effect, conditioned on its causes, remains invariant to changes in the prior distribution of…

Machine Learning · Computer Science 2026-02-04 Nang Hung Nguyen , Phi Le Nguyen , Thao Nguyen Truong , Trong Nghia Hoang , Masashi Sugiyama
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