ArticleScientific reports2018
Boltzmann sampling from the Ising model using quantum heating of coupled nonlinear oscillators.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Quantum benchmarking of high-fidelity noise-biased operations on a detuned Kerr-cat qubit.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Point convolutional neural network algorithm for Ising model ground state research based on spring vibration.Scientific reports · 2024Article
- Efficient low temperature Monte Carlo sampling using quantum annealing.Scientific reports · 2023Article
- Measurement-based preparation of stable coherent states of a Kerr parametric oscillator.Scientific reports · 2023Article
- High-performance combinatorial optimization based on classical mechanics.Science advances · 2021Article
- Combinatorial optimization by simulating adiabatic bifurcations in nonlinear Hamiltonian systems.Science advances · 2019Article
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Authors and funding
3 authors.
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Abstract
A network of Kerr-nonlinear parametric oscillators without dissipation has recently been proposed for solving combinatorial optimization problems via quantum adiabatic evolution through its bifurcation point. Here we investigate the behavior of the quantum bifurcation machine (QbM) in the presence of dissipation. Our numerical study suggests that the output probability distribution of the dissipative QbM is Boltzmann-like, where the energy in the Boltzmann distribution corresponds to the cost function of the optimization problem. We explain the Boltzmann distribution by generalizing the concept of quantum heating in a single nonlinear oscillator to the case of multiple coupled nonlinear oscillators. The present result also suggests that such driven dissipative nonlinear oscillator networks can be applied to Boltzmann sampling, which is used, e.g., for Boltzmann machine learning in the field of artificial intelligence.
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