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Intelligent Automation & Soft Computing

Modeling and Processing Using Reversible Conservative Noisy Elementary Cellular Automata Circuits and their M-Ary Quantum Computing

Anas N. Al‐Rabadi

Published Jan 1, 2008• 0 citations
Publisher

Abstract

Abstract Modeling noisy discrete systems utilizing conservative reversible elementary cellular automata (CRECA) is introduced. Reversibility in the ECA evolution rule and reversibility in the ECA circuit implementation are both achieved using a new Swap-based algorithm called Swap-based CRECA (SCRECA). The new method results in adding variable redundancy to counteract the effect of noise. The problem of obtaining a reversible map from an irreversible map is important because quantum circuits are inherently reversible and thus does not consume power, while irreversible circuits (due to either an irreversible mapping or to noise within a reversible mapping) cannot exist in the quantum domain and its circuits consume power. Since noise is an integral part of any real process and since the reduction of power consumption is a main requirement for the circuit design of future technologies such as in quantum computing (QC), the main features of several future technologies will include reversibility, and thus the...

DOI
10.1080/10798587.2008.10642990

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Quantum cellular automata are important tools in understanding quantum dynamics, thanks to their simple and effective list of rules. Here we consider a class of noisy, one-dimensional quantum cellular automata that allow one to shift from unitary dynamics to completely positive maps, investigating the evolution of coherence as well as the notion of reversibility in such a setting. To this aim, we associate an approximate reverse automaton to each noisy automaton, and assess its effect, and we define an irreversibility time based on the distance from the maximally mixed state, which is shown to be the only attractor of the automaton map in the presence of dephasing. Our analysis illustrates the interplay between unitary and noisy dynamics.
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