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Many appplications in computational science are sufficiently compute-intensive that they depend on the power of parallel computing for viability. For all but the "embarrassingly parallel" problems, the performance depends upon the level of…

High Energy Physics - Lattice · Physics 2009-09-29 Z. Sroczynski , N. Eicker , Th. Lippert , B. Orth , K. Schilling

One might think that, once we know something is computable, how efficiently it can be computed is a practical question with little further philosophical importance. In this essay, I offer a detailed case that one would be wrong. In…

Computational Complexity · Computer Science 2024-05-11 Scott Aaronson

To identify potential universal cellular automata, a method is developed to measure information processing capacity of elementary cellular automata. We consider two features of cellular automata: Ability to store information, and ability to…

Cellular Automata and Lattice Gases · Physics 2018-03-20 Yanbo Zhang

In the effort to develop useful quantum computers simulating quantum machines with conventional computing resources is a key capability. Such simulations will always face limits preventing the emulation of quantum computers of substantial…

Quantum Physics · Physics 2023-02-20 Xiaosi Xu , Simon Benjamin , Jinzhao Sun , Xiao Yuan , Pan Zhang

Computational thinking is a new problem soling method named for its extensive use of computer science techniques. It synthesizes critical thinking and existing knowledge and applies them in solving complex technological problems. The term…

Artificial Intelligence · Computer Science 2012-12-05 Michael Gr. Voskoglou , Sheryl Buckley

Herein we survey the main results concerning quantum automata and machines with classical control. These machines were originally proposed by Sernadas et al in [37], during the FCT QuantLog project. First, we focus on the expressivity of…

Quantum Physics · Physics 2017-09-06 Paulo Mateus , Daowen Qiu , Andre Souto

Perturbation theory is an important technique for reducing computational cost and providing physical insights in simulating quantum systems with classical computers. Here, we provide a quantum algorithm to obtain perturbative energies on…

Quantum Physics · Physics 2023-05-17 Kosuke Mitarai , Kiichiro Toyoizumi , Wataru Mizukami

The Turing Machine is the paradigmatic case of computing machines, but there are others such as analogical, connectionist, quantum and diverse forms of unconventional computing, each based on a particular intuition of the phenomenon of…

Artificial Intelligence · Computer Science 2023-10-10 Luis A. Pineda

A novel computing model, called \emph{Probe Machine}, is proposed in this paper. Different from Turing Machine, Probe Machine is a fully-parallel computing model in the sense that it can simultaneously process multiple pairs of data, rather…

Computational Complexity · Computer Science 2016-03-01 Jin Xu

The driving force in the pursuit for quantum computation is the exciting possibility that quantum algorithms can be more efficient than their classical analogues. Research on the subject has unraveled several aspects of how that can happen.…

Quantum Physics · Physics 2011-09-15 Apoorva Patel

The theory of quantum computation is presented in a self contained way from a computer science perspective. The basics of classical computation and quantum mechanics is reviewed. The circuit model of quantum computation is presented in…

Quantum Physics · Physics 2007-05-23 Anders K. H. Bengtsson

We study the computational complexity theory of smooth, finite-dimensional dynamical systems. Building off of previous work, we give definitions for what it means for a smooth dynamical system to simulate a Turing machine. We then show that…

Computational Complexity · Computer Science 2024-09-19 Jordan Cotler , Semon Rezchikov

In the same sense as classical logic is a formal theory of truth, the recently initiated approach called computability logic is a formal theory of computability. It understands (interactive) computational problems as games played by a…

Logic in Computer Science · Computer Science 2011-04-15 Giorgi Japaridze

Turing machines and register machines have been used for decades in theoretical computer science as abstract models of computation. Also the $\lambda$-calculus has played a central role in this domain as it allows to focus on the notion of…

Logic in Computer Science · Computer Science 2023-06-22 Giuseppe Della Penna , Benedetto Intrigila , Giulio Manzonetto

Many forms of programmable matter have been proposed for various tasks. We use an abstract model of self-organizing particle systems for programmable matter which could be used for a variety of applications, including smart paint and…

Emerging Technologies · Computer Science 2017-10-24 Alexandra Porter , Andréa W. Richa

We examine different generalizations of checking stack automata by allowing multiple input heads and multiple stacks, and characterize their computing power in terms of two-way multi-head finite automata and space-bounded Turing machines.…

Formal Languages and Automata Theory · Computer Science 2022-12-05 Oscar H. Ibarra , Ian McQuillan

This paper proposes a thought experiment to search for efficient bounded algorithms of NPC problems by machine enumeration. The key contributions are: -- On Universal Turing Machines, a program's time complexity should be characterized as:…

Computational Complexity · Computer Science 2012-10-09 YuQian Zhou

Most continuous mathematical formulations arising in science and engineering can only be solved numerically and therefore approximately. We shall always assume that we're dealing with a numerical approximation to the solution. There are two…

Quantum Physics · Physics 2007-12-10 A. Papageorgiou , J. F. Traub

Turing's (1936) paper on computable numbers has played its role in underpinning different perspectives on the world of information. On the one hand, it encourages a digital ontology, with a perceived flatness of computational structure…

Logic · Mathematics 2015-06-23 S. Barry Cooper

Computational mechanics is a method for discovering, describing and quantifying patterns, using tools from statistical physics. It constructs optimal, minimal models of stochastic processes and their underlying causal structures. These…

Machine Learning · Computer Science 2007-05-23 Cosma Rohilla Shalizi , James P. Crutchfield
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