Simulated Bifurcation algorithm

The Simulated Bifurcation (SB) algorithm[1][2][3] is a fast and highly parallelizable state-of-the-art algorithm for combinatorial optimization inspired by quantum physics and spins dynamics. It was first introduced by Toshiba experts and relies on Hamiltonian quantum mechanics to find local minima of Ising problems, known to be NP-hard.

🚧 This page is a work in progress. We invite you to consult the publications listed at the end of this page to learn more about the Simulated Bifurcation algorithm. A simplified presentation of the algorithm will be available soon.

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[1]

Hayato Goto et al., “Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems”. Sci. Adv.5, eaav2372(2019). DOI:10.1126/sciadv.aav2372

[2]

Hayato Goto et al., “High-performance combinatorial optimization based on classical mechanics”. Sci. Adv.7, eabe7953(2021). DOI:10.1126/sciadv.abe7953

[3]

Kanao, T., Goto, H. “Simulated bifurcation assisted by thermal fluctuation”. Commun Phys 5, 153 (2022). https://doi.org/10.1038/s42005-022-00929-9