Among various algorithms designed to exploit the specific properties of quantum computers with respect to classical ones, the quantum adiabatic algorithm is a versatile proposition to find the minimal value of an arbitrary cost function (ground state energy). Random optimization problems provide a natural testbed to compare its efficiency with that of classical algorithms. These problems correspond to mean field spin glasses that have been extensively studied in the classical case. This paper reviews recent analytical works that extended these studies to incorporate the effect of quantum fluctuations, and presents also some original results in this direction. (c) 2012 Elsevier B.V. All rights reserved.
The quantum adiabatic algorithm applied to random optimization problems: The quantum spin glass perspective / Bapst, V; Foini, L; Krzakala, F; Semerjian, G; Zamponi, F. - In: PHYSICS REPORTS. - ISSN 0370-1573. - 523:3(2013), pp. 127-205. [10.1016/j.physrep.2012.10.002]
The quantum adiabatic algorithm applied to random optimization problems: The quantum spin glass perspective
Zamponi F
2013
Abstract
Among various algorithms designed to exploit the specific properties of quantum computers with respect to classical ones, the quantum adiabatic algorithm is a versatile proposition to find the minimal value of an arbitrary cost function (ground state energy). Random optimization problems provide a natural testbed to compare its efficiency with that of classical algorithms. These problems correspond to mean field spin glasses that have been extensively studied in the classical case. This paper reviews recent analytical works that extended these studies to incorporate the effect of quantum fluctuations, and presents also some original results in this direction. (c) 2012 Elsevier B.V. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
