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April 20, 2001Science2,111 citationsOpen Access

A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem

EFEdward FarhiGoogle (United States)JGJeffrey GoldstoneMassachusetts Institute of TechnologySGSam GutmannBoston University

Key Points

  • To evaluate whether a quantum adiabatic evolution algorithm can successfully solve computationally difficult, randomly generated instances of an NP-complete problem.
  • Simulated a quantum adiabatic algorithm based on slow Hamiltonian variation to maintain the system near its ground state.
  • Tested the algorithm across small, randomly generated hard instances of an NP-complete problem.
  • The adiabatic algorithm successfully solved the simulated small-scale instances of the NP-complete problem.
  • Results provide evidence that sufficiently scaled quantum computers could potentially outperform classical computing architectures on hard problem instances.

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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Cite This Study

Farhi et al. (2001) studied this question.

synapsesocial.com/papers/69d890a5c025a7c015bee27dhttps://doi.org/10.1126/science.1057726
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