aiqbench analysis
This research details how Spontaneous Symmetry Breaking Machines (SSBM) can emulate continuous-variable Ising machines through specific driving conditions and pseudo-annealing techniques to optimize combinatorial problems like K_{2000}. By achieving cut values reaching 99.7% of known bests, the study bridges physical simulation methods with established quantum-inspired optimization architectures without relying on full-scale qubit hardware. The work advances our understanding of hybrid classical-physical approaches for solving hard computational tasks relevant to both AI training and logistics planning.
Ising-machine-like Driving Condition Restrictions in SSBM and Additional Pseudo-annealing- Driving Method for SSBM that Achieves Best Cut Value Search -
arXiv:2608.12545v2 Announce Type: replace-cross Abstract: In our previous paper, we described the proposal and validation of a new physical implementation-type simulator (spontaneous symmetry breaking machine (SSBM)) for a combinatorial optimization problem that utilizes a phenomenon dual to the model in which a pseudo-spin many-body system is created by spontaneous symmetry breaking. Furthermore, we performed numerical simulations with different initial fluctuations on a large-scale benchmark problem (K_{2000}) and reported that we identified a condition under which pseudo-spin patterns gradually converge during the solution search process to ultimately form a single pattern and that the cut value of this converged solution reached 99.7% of the known best. In this paper, we discuss the conditions under which the SSBM can exhibit behavior analogous to that of a continuous-variable-type Ising machine, and report that by adding an effect similar to physical annealing to these conditions, the SSBM can be made to search for the best known cuts in K_{2000}.
Abstract:In our previous paper, we described the proposal and validation of a new physical implementation-type simulator (spontaneous symmetry breaking machine (SSBM)) for a combinatorial optimization problem that utilizes a phenomenon dual to the model in which a pseudo-spin many-body system is created by spontaneous symmetry breaking. Furthermore, we performed numerical simulations with different initial fluctuations on a large-scale benchmark problem (K_{2000}) and reported that we identified a condition under which pseudo-spin patterns gradually converge during the solution search process to ultimately form a single pattern and that the cut value of this converged solution reached 99.7% of the known best. In this paper, we discuss the conditions under which the SSBM can exhibit behavior analogous to that of a continuous-variable-type Ising machine, and report that by adding an effect similar to physical annealing to these conditions, the SSBM can be made to search for the best known cuts in K_{2000}.
Optics (physics.optics); Mathematical Physics (math-ph); Adaptation and Self-Organizing Systems (nlin.AO); Quantum Physics (quant-ph)
arXiv:2608.12545 [physics.optics]
(or arXiv:2608.12545v2 [physics.optics] for this version)
https://doi.org/10.48550/arXiv.2608.12545 Focus to learn more arXiv-issued DOI via DataCite
mySup20260818.pdf
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