A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem
Edward Farhi(Massachusetts Institute of Technology), Jeffrey Goldstone(Massachusetts Institute of Technology), Sam Gutmann(Northeastern University), Joshua M. Lapan(Massachusetts Institute of Technology), A. P. Lundgren(Massachusetts Institute of Technology), Daniel Preda(Massachusetts Institute of Technology)
Cited by 2,081Open Access
Abstract
A quantum system will stay near its instantaneous ground state if the Hamiltonian that governs its evolution varies slowly enough. This quantum adiabatic behavior is the basis of a new class of algorithms for quantum computing. We tested one such algorithm by applying it to randomly generated hard instances of an NP-complete problem. For the small examples that we could simulate, the quantum adiabatic algorithm worked well, providing evidence that quantum computers (if large ones can be built) may be able to outperform ordinary computers on hard sets of instances of NP-complete problems.
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