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We present a graph-theoretic model for dynamical systems $(X,\sigma)$ given by a surjective local homeomorphism $\sigma$ on a totally disconnected compact metrizable space $X$. In order to make the dynamics appear explicitly in the graph,…

Operator Algebras · Mathematics 2024-02-13 Pere Ara , Joan Claramunt

Let L:= Z^D be the D-dimensional lattice and let A^L be the Cantor space of L-indexed configurations in some finite alphabet A, with the natural L-action by shifts. A `cellular automaton' is a continuous, shift-commuting self-map F of A^L,…

Dynamical Systems · Mathematics 2009-09-29 Marcus Pivato

We study sources of isomorphisms of additive cellular automata on finite groups (called index-group). It is shown that many isomorphisms (called regular) of automata are reducible to the isomorphisms of underlying algebraic structures (such…

Cellular Automata and Lattice Gases · Physics 2008-12-02 Valeriy Bulitko

We present a generalized linear structural causal model, coupled with a novel data-adaptive linear regularization, to recover causal directed acyclic graphs (DAGs) from time series. By leveraging a recently developed stochastic monotone…

Machine Learning · Computer Science 2023-01-31 Song Wei , Yao Xie , Christopher S. Josef , Rishikesan Kamaleswaran

We present a generalized linear structural causal model, coupled with a novel data-adaptive linear regularization, to recover causal directed acyclic graphs (DAGs) from time series. By leveraging a recently developed stochastic monotone…

Machine Learning · Computer Science 2023-09-27 Song Wei , Yao Xie , Christopher S. Josef , Rishikesan Kamaleswaran

This paper explores the algebraic conditions under which a cellular automaton with a non-linear local rule exhibits surjectivity and reversibility. We also analyze the role of permutivity as a key factor influencing these properties and…

Discrete Mathematics · Computer Science 2025-06-30 Firas Ben Ramdhane , Alberto Dennunzio , Luciano Margara , Giuliamaria Menara

Causal theory is now widely developed with many applications to medicine and public health. However within the discipline of reliability, although causation is a key concept in this field, there has been much less theoretical attention. In…

Artificial Intelligence · Computer Science 2020-02-17 Xuewen Yu , Jim Q. Smith , Linda Nichols

We conjecture that for a wide class of interacting particle systems evolving in discrete time, namely conservative cellular automata with piecewise linear flow diagram, relaxation to the limit set follows the same power law at critical…

Cellular Automata and Lattice Gases · Physics 2009-11-07 Henryk Fuks , Nino Boccara

We discuss cellular automata over arbitrary finitely generated groups. We call a cellular automaton post-surjective if for any pair of asymptotic configurations, every pre-image of one is asymptotic to a pre-image of the other. The well…

Dynamical Systems · Mathematics 2023-06-22 Silvio Capobianco , Jarkko Kari , Siamak Taati

Causal discovery is a fundamental problem with applications spanning various areas in science and engineering. It is well understood that solely using observational data, one can only orient the causal graph up to its Markov equivalence…

Machine Learning · Computer Science 2024-10-29 Zihan Zhou , Muhammad Qasim Elahi , Murat Kocaoglu

Covariate adjustment is a widely used approach to estimate total causal effects from observational data. Several graphical criteria have been developed in recent years to identify valid covariates for adjustment from graphical causal…

Statistics Theory · Mathematics 2015-07-07 Emilija Perković , Johannes Textor , Markus Kalisch , Marloes H. Maathuis

This paper proposes a dynamical notion of discrete geodesics, understood as straightest trajectories in discretized curved spacetime. The notion is generic, as it is formulated in terms of a general deviation function, but readily…

Discrete Mathematics · Computer Science 2016-01-01 Pablo Arrighi , Gilles Dowek

We introduce priors and algorithms to perform Bayesian inference in Gaussian models defined by acyclic directed mixed graphs. Such a class of graphs, composed of directed and bi-directed edges, is a representation of conditional…

Methodology · Statistics 2012-07-02 Ricardo Silva , Zoubin Ghahramani

Causality analysis is an important problem lying at the heart of science, and is of particular importance in data science and machine learning. An endeavor during the past 16 years viewing causality as real physical notion so as to…

Artificial Intelligence · Computer Science 2021-04-26 X. San Liang

We report here on the structure of reversible quantum cellular automata with the additional restriction that these are also Clifford operations. This means that tensor products of Weyl operators (projective representation of a finite…

Mathematical Physics · Physics 2008-12-04 Dirk-Michael Schlingemann

We introduce a cellular automaton model coupled with a transport equation for flows on graphs. The direction of the flow is described by a switching process where the switching probability dynamically changes according to the value of the…

Cellular Automata and Lattice Gases · Physics 2013-07-02 Pierre Degond , Michael Herty , Jian-Guo Liu

A map on finitely many fermionic modes represents a unitary evolution if and only if it preserves canonical anti-commutation relations. We use this condition for the classification of fermionic cellu- lar automata (FCA) on Cayley graphs of…

Quantum Physics · Physics 2018-12-05 Paolo Perinotti , Leopoldo Poggiali

One-dimensional quantum cellular automata (QCA) consist in a line of identical, finite dimensional quantum systems. These evolve in discrete time steps according to a local, shift-invariant unitary evolution. By local we mean that no…

Quantum Physics · Physics 2008-04-15 Pablo Arrighi , Vincent Nesme , Reinhard Werner

Perfect adaptation in a dynamical system is the phenomenon that one or more variables have an initial transient response to a persistent change in an external stimulus but revert to their original value as the system converges to…

Artificial Intelligence · Computer Science 2023-02-27 Tineke Blom , Joris M. Mooij

Causal graphs (CGs) are compact representations of the knowledge of the data generating processes behind the data distributions. When a CG is available, e.g., from the domain knowledge, we can infer the conditional independence (CI)…

Machine Learning · Computer Science 2021-08-18 Takeshi Teshima , Masashi Sugiyama