A binary vector encoding with truth-table spin interactions gives probabilistic Ising machines competitive graph-coloring accuracy and a 1024-neuron FPGA implementation with large speedups.
In2022 International Joint Conference on Neural Networks (IJCNN), 1–8 (2022)
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Efficient Optimization Accelerator Framework for Multistate Ising Problems
A binary vector encoding with truth-table spin interactions gives probabilistic Ising machines competitive graph-coloring accuracy and a 1024-neuron FPGA implementation with large speedups.