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Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems.

ABSTRACT: Combinatorial optimization problems are ubiquitous but difficult to solve. Hardware devices for these problems have recently been developed by various approaches, including quantum computers. Inspired by recently proposed quantum adiabatic optimization using a nonlinear oscillator network, we propose a new optimization algorithm simulating adiabatic evolutions of classical nonlinear Hamiltonian systems exhibiting bifurcation phenomena, which we call simulated bifurcation (SB). SB is based on adiabatic and chaotic (ergodic) evolutions of nonlinear Hamiltonian systems. SB is also suitable for parallel computing because of its simultaneous updating. Implementing SB with a field-programmable gate array, we demonstrate that the SB machine can obtain good approximate solutions of an all-to-all connected 2000-node MAX-CUT problem in 0.5 ms, which is about 10 times faster than a state-of-the-art laser-based machine called a coherent Ising machine. SB will accelerate large-scale combinatorial optimization harnessing digital computer technologies and also offer a new application of computational and mathematical physics.

SUBMITTER: Goto H

PROVIDER: S-EPMC6474767 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems.

Goto Hayato H Tatsumura Kosuke K Dixon Alexander R AR

Science advances 20190419 4

Combinatorial optimization problems are ubiquitous but difficult to solve. Hardware devices for these problems have recently been developed by various approaches, including quantum computers. Inspired by recently proposed quantum adiabatic optimization using a nonlinear oscillator network, we propose a new optimization algorithm simulating adiabatic evolutions of classical nonlinear Hamiltonian systems exhibiting bifurcation phenomena, which we call simulated bifurcation (SB). SB is based on adi ...[more]

PMID: 31016238

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Dataset Information

Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems.

Publications

Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems.

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