SAFE ma-QAOA achieves 64.3% fewer active parameters and 94.5% lower estimated QPU workload via surrogate pre-training and parameter distillation on Sherrington-Kirkpatrick, 2D spin glass, and Max-Cut instances.
Ising machines as hardware solvers of combinatorial optimization problems
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Ising machines outperform every tested Potts machine on Max-k-Cut problems, with the performance gap widening from k=3 to k=4.
Ising machine probabilistic computing achieves optimal ML detection for XL-MIMO up to 2048x2048 antennas in 100 iterations and extends to 256-QAM via p-dits while matching or beating MMSE.
citing papers explorer
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SAFE ma-QAOA: Surrogate-Assisted and Fine-Tuning Enhanced Multi-Angle QAOA with Parameter Distillation
SAFE ma-QAOA achieves 64.3% fewer active parameters and 94.5% lower estimated QPU workload via surrogate pre-training and parameter distillation on Sherrington-Kirkpatrick, 2D spin glass, and Max-Cut instances.
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Comparative Study of Potts Machine Dynamics and Performance for Max-k-Cut
Ising machines outperform every tested Potts machine on Max-k-Cut problems, with the performance gap widening from k=3 to k=4.
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Physics-Inspired Probabilistic Computing for Extremely Large-Scale MIMO Detection in Future 6G Wireless Systems
Ising machine probabilistic computing achieves optimal ML detection for XL-MIMO up to 2048x2048 antennas in 100 iterations and extends to 256-QAM via p-dits while matching or beating MMSE.