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Related papers: Collapsing Catalytic Classes

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In a variety of studies of dynamical systems, the edge of order and chaos has been singled out as a region of complexity. It was suggested by Wolfram, on the basis of qualitative behaviour of cellular automata, that the computational basis…

chao-dyn · Physics 2009-10-28 Porus Lakdawala

This article presents a new characterization of controllability and regional controllability of Deterministic Cellular Automata (CA for short). It focuses on analyzing these problems within the framework of control theory, which have been…

Dynamical Systems · Mathematics 2025-01-07 Sara Dridi

Quantum mechanics contains some strange unphysical concepts. Among these are complex numbers, Hilbert spaces with their unitary and self-adjoint operators, states represented by complex vectors, superpositions of states, collapse of wave…

Quantum Physics · Physics 2026-03-31 Stan Gudder

The congested clique model of distributed computing has been receiving attention as a model for densely connected distributed systems. While there has been significant progress on the side of upper bounds, we have very little in terms of…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-04-25 Janne H. Korhonen , Jukka Suomela

Collapse models explain the absence of quantum superpositions at the macroscopic scale, while giving practically the same predictions as quantum mechanics for microscopic systems. The Continuous Spontaneous Localization (CSL) model is the…

Quantum Physics · Physics 2015-08-10 Andrea Smirne , Angelo Bassi

Cellular automata are arrays of finite state machines that can exist in a finite number of states. These machines update their states simultaneously based on specific local rules that govern their interactions. This framework provides a…

Cellular Automata and Lattice Gases · Physics 2025-08-11 Genaro J. Martinez , Andrew Adamatzky , Guanrong Chen

While closed timelike curves (CTCs) are not known to exist, studying their consequences has led to nontrivial insights in general relativity, quantum information, and other areas. In this paper we show that if CTCs existed, then quantum…

Quantum Physics · Physics 2009-11-13 Scott Aaronson , John Watrous

Tsetlin Machines (TMs) have garnered increasing interest for their ability to learn concepts via propositional formulas and their proven efficiency across various application domains. Despite this, the convergence proof for the TMs,…

Artificial Intelligence · Computer Science 2023-10-04 Mohamed-Bachir Belaid , Jivitesh Sharma , Lei Jiao , Ole-Christoffer Granmo , Per-Arne Andersen , Anis Yazidi

A stochastic adding machine is a Markov chain on the set of non-negative integers $\mathbb{Z}_{+}$ that models the process of adding one by successively updating the digits of a number's expansion in a given numeration system. At each step,…

Dynamical Systems · Mathematics 2025-06-09 Danilo Caprio , Ali Messaoudi , Ioannis Tsokanos , Glauco Valle

Restricted Boltzmann machines are undirected neural networks which have been shown to be effective in many applications, including serving as initializations for training deep multi-layer neural networks. One of the main reasons for their…

Disordered Systems and Neural Networks · Physics 2016-02-11 Marylou Gabrié , Eric W. Tramel , Florent Krzakala

The search for a logic capturing PTIME is a long standing open problem in finite model theory. One of the most promising candidate logics for this is Choiceless Polynomial Time with counting (CPT). Abstractly speaking, CPT is an…

Logic in Computer Science · Computer Science 2024-01-17 Benedikt Pago

Born in the intersection between quantum mechanics and general relativity, indefinite causal structure is the idea that in the continuum of time, some sets of events do not have an inherent causal order between them. Process matrices,…

Quantum Physics · Physics 2024-10-08 Omri Shmueli

We describe a class calculus that is expressive enough to describe and improve its own learning process. It can design and debug programs that satisfy given input/output constraints, based on its ontology of previously learned programs. It…

Artificial Intelligence · Computer Science 2018-04-11 Daniel J. Buehrer

The goal of co-clustering is to simultaneously identify a clustering of rows as well as columns of a two dimensional data matrix. A number of co-clustering techniques have been proposed including information-theoretic co-clustering and the…

Machine Learning · Computer Science 2020-04-27 Joyce Jiyoung Whang , Inderjit S. Dhillon

The accurate representation of epistemic uncertainty is a challenging yet essential task in machine learning. A widely used representation corresponds to convex sets of probabilistic predictors, also known as credal sets. One popular way of…

Machine Learning · Computer Science 2025-07-30 Mira Jürgens , Thomas Mortier , Eyke Hüllermeier , Viktor Bengs , Willem Waegeman

Quantum mechanics is an extremely successful theory that agrees with every experiment. However, the principle of linear superposition, a central tenet of the theory, apparently contradicts a commonplace observation: macroscopic objects are…

Quantum Physics · Physics 2015-03-20 Angelo Bassi , Kinjalk Lochan , Seema Satin , Tejinder P. Singh , Hendrik Ulbricht

This paper concerns identification of uncontrolled or closed loop nonlinear systems using a set of trajectories that are generated by the system in a domain of attraction. The objective is to ensure that the trajectories of the identified…

Systems and Control · Electrical Eng. & Systems 2022-10-25 Moad Abudia , Joel A. Rosenfeld , Rushikesh Kamalapurkar

A general mathematical method is presented for the systematic construction of coupled map lattices (CMLs) out of deterministic cellular automata (CAs). The entire CA rule space is addressed by means of a universal map for CAs that we have…

Cellular Automata and Lattice Gases · Physics 2016-06-09 Vladimir García-Morales

We generalize the theory of catalytic quantum randomness to delocalized and dynamical settings. First, we expand the resource theory of randomness (RTR) by calculating the amount of entropy catalytically extractable from a correlated or…

Quantum Physics · Physics 2023-05-03 Seok Hyung Lie , Hyunseok Jeong

Property prediction and inverse structural design of catalytic materials are typically modeled as two independent tasks: the former predicts target properties from given structures, whereas the latter generates candidate structures…

Artificial Intelligence · Computer Science 2026-05-22 Yanjie Li , Jian Xu , Xu-Yao Zhang , Shiming Xiang , Nian Ran , Weijun Li , Cheng-Lin Liu