Quantum Analog Computing

✍ Scribed by Michail Zak

• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 485 KB
• Volume: 10
• Category: Article
• ISSN: 0960-0779
• DOI: 10.1016/s0960-0779(98)00215-x

✦ Synopsis

Quantum analog computing is based upon similarity between mathematical formalism of quantum mechanics and phenomena to be computed[ It exploits a dynamical convergence of several competing phenomena to an attractor which can represent an extremum of a function\ an image\ a solution to a system of ODE\ or a stochastic process[ In this paper\ a quantum version of recurrent neural nets "QRN# as an analog computing device is discussed[ This concept is introduced by incorporating classical feedback loops into conventional quantum networks[ It is shown that the dynamical evolution of such networks\ which interleave quantum evolution with measurement and reset operations\ exhibit novel dynamical properties[ Moreover\ decoherence in quantum recurrent networks is less problematic than in conventional quantum network architectures due to the modest phase coherence times needed for network operation[ Application of QRN to simulation of chaos\ turbulence\ NP!problems\ as well as data com! pression demonstrate computational speedup and exponential increase of information capacity[