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In part III is realized the consistent development of Heisenberg--Dyson's two-layer matrix approximation to the graph formalism for postulating discrete physical objects (DPO) introduced in parts I-II in the form of discrete sets of…

General Physics · Physics 2007-05-23 V. E. Asribekov

A discrete Boltzmann model (DBM) for plasma kinetics is proposed. The constructing of DBM mainly considers two aspects. The first is to build a physical model with sufficient physical functions before simulation. The second is to present…

Plasma Physics · Physics 2024-04-16 Jiahui Song , Aiguo Xu , Long Miao , Feng Chen , Zhipeng Liu , Lifeng Wang , Ningfei Wang , Xiao Hou

Dynamic Complexity is a phenomenon exhibited by a nonlinearly interacting system within which multitudes of different sizes of large scale coherent structures emerge, resulting in a globally nonlinear stochastic behavior vastly different…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-18 Tom Chang , Cheng-chin Wu , Marius Echim , Herve Lamy , Mark Vogelsberger , Lars Hernquist , Debora Sijacki

We describe a new type of polycyclic presentations, that we will call refined solvable presentations, for polycyclic groups. These presentations are obtained by refining a series of normal subgroups with abelian sections. These…

Group Theory · Mathematics 2011-02-10 René Hartung , Gunnar Traustason

In this article, we define amorphic complexity for actions of locally compact $\sigma$-compact amenable groups on compact metric spaces. Amorphic complexity, originally introduced for $\mathbb Z$-actions, is a topological invariant which…

Dynamical Systems · Mathematics 2023-03-15 Gabriel Fuhrmann , Maik Gröger , Tobias Jäger , Dominik Kwietniak

Guided by critical systems found in nature we develop a novel mechanism consisting of inhomogeneous polynomial regularisation via which we can induce scale invariance in deep learning systems. Technically, we map our deep learning (DL)…

Statistical Mechanics · Physics 2017-06-01 Dan Oprisa , Peter Toth

Logics with team semantics provide alternative means for logical characterization of complexity classes. Both dependence and independence logic are known to capture non-deterministic polynomial time, and the frontiers of tractability in…

Logic in Computer Science · Computer Science 2019-03-27 Miika Hannula , Lauri Hella

We reduce the problem of proving deterministic and nondeterministic Boolean circuit size lower bounds to the analysis of certain two-dimensional combinatorial cover problems. This is obtained by combining results of Razborov (1989),…

Computational Complexity · Computer Science 2025-03-19 Bruno P. Cavalar , Igor C. Oliveira

Dynamical decoupling (DD) is a well-known open-loop protocol for suppressing unwanted interactions in a quantum system, thereby drastically extending the coherence time of useful quantum states. In the original framework of evolution…

Quantum Physics · Physics 2025-10-03 Colin Read , Eduardo Serrano-Ensástiga , John Martin

We consider semigroup algorithmic problems in finitely generated metabelian groups. Our paper focuses on three decision problems introduced by Choffrut and Karhum\"{a}ki (2005): the Identity Problem (does a semigroup contain a neutral…

Group Theory · Mathematics 2023-04-26 Ruiwen Dong

Learning complex network dynamics is fundamental to understanding, modelling and controlling real-world complex systems. There are two main problems in the task of predicting the dynamic evolution of complex networks: on the one hand,…

Artificial Intelligence · Computer Science 2025-10-14 Bicheng Wang , Junping Wang , Yibo Xue

In this paper we investigate the problem of learning evolving concepts over a combinatorial structure. Previous work by Emamjomeh-Zadeh et al. [2020] introduced dynamics into interactive learning as a way to model non-static user…

Machine Learning · Computer Science 2022-04-15 Xing Gao , Thomas Maranzatto , Lev Reyzin

Class groups of real quadratic fields represent fundamental structures in algebraic number theory with significant computational implications. While Stark's conjecture establishes theoretical connections between special units and class…

Number Theory · Mathematics 2025-06-27 Ruopengyu Xu , Chenglian Liu

Robin Hirsch posed in 1996 the 'Really Big Complexity Problem': classify the computational complexity of the network satisfaction problem for all finite relation algebras A. We provide a complete classification for the case that A is…

Logic · Mathematics 2023-01-06 Manuel Bodirsky , Simon Knäuer

Dynamic Flows were introduced by Ford and Fulkerson in 1958 to model flows over time. They define edge capacities to be the total amount of flow that can enter an edge {\em in one time unit}. Each edge also has a length, representing the…

Data Structures and Algorithms · Computer Science 2017-10-02 Mordecai J. Golin , Hadi Khodabande , Bo Qin

Integrable $\lambda$-deformed $\sigma$-models are characterized by an underlying current algebra/coset model CFT deformed, at the infinitesimal level, by current/parafermion bilinears. We promote the deformation parameters to dynamical…

High Energy Physics - Theory · Physics 2023-03-22 Rigers Aliaj , Konstantinos Sfetsos , Konstantinos Siampos

Some aspects of the predictability problem in dynamical systems are reviewed. The deep relation among Lyapunov exponents, Kolmogorov-Sinai entropy, Shannon entropy and algorithmic complexity is discussed. In particular, we emphasize how a…

Chaotic Dynamics · Physics 2007-05-23 Fabio Cecconi , Massimo Falcioni , Angelo Vulpiani

A description of the algebra of outer derivations of a group algebra of a finitely presented discrete group is given in terms of the Cayley complex of the groupoid of the adjoint action of the group. This task is a smooth version of…

Algebraic Topology · Mathematics 2021-04-20 A. A. Arutyunov , A. S. Mishchenko

Most neural models of causality assume static causal graphs, failing to capture the dynamic and sparse nature of physical interactions where causal relationships emerge and dissolve over time. We introduce the Causal Process Framework and…

Machine Learning · Computer Science 2026-04-07 Turan Orujlu , Christian Gumbsch , Martin V. Butz , Charley M Wu

We introduce a new Collaborative Causal Discovery problem, through which we model a common scenario in which we have multiple independent entities each with their own causal graph, and the goal is to simultaneously learn all these causal…

Machine Learning · Computer Science 2021-06-08 Raghavendra Addanki , Shiva Prasad Kasiviswanathan