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Related papers: Metastability-Containing Turing Machines

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Efficiently handling time-triggered and possibly nondeterministic switches for hybrid systems reachability is a challenging task. In this paper we present an approach based on conservative set-based enclosure of the dynamics that can handle…

Systems and Control · Electrical Eng. & Systems 2022-07-07 Marcelo Forets , Daniel Freire , Christian Schilling

A catalytic Turing machine is a variant of a Turing machine in which there exists an auxiliary tape in addition to the input tape and the work tape. This auxiliary tape is initially filled with arbitrary content. The machine can read and…

Computational Complexity · Computer Science 2024-08-28 Chetan Gupta , Rahul Jain , Vimal Raj Sharma , Raghunath Tewari

Developing a thermodynamic theory of computation is a challenging task at the interface of non-equilibrium thermodynamics and computer science. In particular, this task requires dealing with difficulties such as stochastic halting times,…

Statistical Mechanics · Physics 2024-05-14 Gonzalo Manzano , Gülce Kardeş , Édgar Roldán , David Wolpert

In this article, we perform quantitative analyses of metastable behavior of an interacting particle system known as the inclusion process. For inclusion processes, it is widely believed that the system nucleates the condensation of…

Probability · Mathematics 2021-02-24 Seonwoo Kim , Insuk Seo

We explore the possible connections between the dynamic behaviour of a system and Turing universality in terms of the system's ability to (effectively) transmit and manipulate information. Some arguments will be provided using a defined…

Computational Complexity · Computer Science 2012-01-05 Hector Zenil

A Turing machine with faults, failures and recovery (TMF) is described. TMF is (weakly) non-deterministic Turing machine consisting of five semi-infinite tapes (Master Tape, Synchro Tape, Backup Tape, Backup Synchro Tape, User Tape) and…

Logic in Computer Science · Computer Science 2007-05-23 Alex Vinokur

The measurability by means of continuous measurements, of an observable $\A(t_0)$, at an instant, and of a time averaged observable, $\bar \A=1/T\int \A(t')dt'$, is examined for linear and in particular for non-linear quantum mechanical…

Quantum Physics · Physics 2007-05-23 Y. Aharonov , B. Reznik

Memcomputing is a novel non-Turing paradigm of computation that uses interacting memory cells (memprocessors for short) to store and process information on the same physical platform. It was recently proved mathematically that memcomputing…

Emerging Technologies · Computer Science 2015-07-09 Fabio L. Traversa , Chiara Ramella , Fabrizio Bonani , Massimiliano Di Ventra

Framing computation as the transformation of metastable memories, we explore its fundamental thermodynamic limits. The true power of information follows from a novel decomposition of nonequilibrium free energy derived here, which provides a…

Statistical Mechanics · Physics 2018-08-13 Paul M. Riechers

We study the complexity of central controller synthesis problems for finite-state Markov decision processes, where the objective is to optimize both the expected mean-payoff performance of the system and its stability. We argue that the…

Systems and Control · Computer Science 2013-05-20 Tomáš Brázdil , Krishnendu Chatterjee , Vojtěch Forejt , Antonín Kučera

The periodic modulation of an oscillator's frequency can lead to so-called parametric oscillations at half the driving frequency, which display bistability between two states whose phases differ by \pi. Such phase-locking bistability is at…

Pattern Formation and Solitons · Physics 2018-04-25 Rubén Martínez-Lorente , Fernando Silva , Germán J. de Valcárcel

Finite Turing computation has a fundamental symmetry between inputs, outputs, programs, time, and storage space. Standard models of transfinite computational break this symmetry; we consider ways to recover it and study the resulting model…

Logic · Mathematics 2023-02-14 Lorenzo Galeotti , Ethan S. Lewis , Benedikt Löwe

Sensitivity to noise makes most of the current quantum computing schemes prone to error and nonscalable, allowing only for small proof-of-principle devices. Topologically-protected quantum computing aims at solving this problem by encoding…

Disordered Systems and Neural Networks · Physics 2013-12-17 Helmut G. Katzgraber , Ruben S. Andrist

Model predictive control solves a constrained optimization problem online in order to compute an implicit closed-loop control policy. Recursive feasibility -- guaranteeing that the optimal control problem will have a solution at every time…

Optimization and Control · Mathematics 2024-10-16 Jacob W. Knaup , Panagiotis Tsiotras

Universal memcomputing machines (UMMs) [IEEE Trans. Neural Netw. Learn. Syst. 26, 2702 (2015)] represent a novel computational model in which memory (time non-locality) accomplishes both tasks of storing and processing of information. UMMs…

Neural and Evolutionary Computing · Computer Science 2019-05-29 Yan Ru Pei , Fabio L. Traversa , Massimiliano Di Ventra

Stable quantum computation requires noisy results to remain bounded even in the presence of noise fluctuations. Yet non-stationary noise processes lead to drift in the varying characteristics of a quantum device that can greatly influence…

Quantum Physics · Physics 2023-07-12 Samudra Dasgupta , Travis S. Humble

The notion of quantum Turing machines is a basis of quantum complexity theory. We discuss a general model of multi-tape, multi-head Quantum Turing machines with multi final states that also allow tape heads to stay still.

Quantum Physics · Physics 2007-05-23 Tomoyuki Yamakami

The Quantum Computer Condition (QCC) provides a rigorous and completely general framework for carrying out analyses of questions pertaining to fault-tolerance in quantum computers. In this paper we apply the QCC to the problem of…

Quantum Physics · Physics 2007-05-23 Gerald Gilbert , Michael Hamrick , F. Javier Thayer , Yaakov S. Weinstein

Contrary to the classical case, the relation between quantum programming languages and quantum Turing Machines (QTM) has not being fully investigated. In particular, there are features of QTMs that have not been exploited, a notable example…

Logic in Computer Science · Computer Science 2020-08-13 Stefano Guerrini , Simone Martini , Andrea Masini

Reservoir Computing is a class of Recurrent Neural Networks with internal weights fixed at random. Stability relates to the sensitivity of the network state to perturbations. It is an important property in Reservoir Computing as it directly…

Neural and Evolutionary Computing · Computer Science 2022-06-09 Jonathan Dong , Erik Börve , Mushegh Rafayelyan , Michael Unser
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