A self-consistent framework with generalized local order parameters is derived for the Kuramoto model with dyadic and triadic interactions on hypergraphs, showing bistability onset depends on eigenvector correlations between dyadic and triadic structures.
Self-entrainment of a population of coupled non-linear oscillators
4 Pith papers cite this work. Polarity classification is still indexing.
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2026 4representative citing papers
Ising machines outperform every tested Potts machine on Max-k-Cut problems, with the performance gap widening from k=3 to k=4.
Deep-Koopman-KANDy recovers symbolic Koopman dictionaries post-training by replacing the encoder and decoder with KANs and applying a level-set construction with chain-rule gradients, achieving high recall on Lorenz and expected behavior on other maps.
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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Self-consistent analysis of the Kuramoto model with higher-order interactions
A self-consistent framework with generalized local order parameters is derived for the Kuramoto model with dyadic and triadic interactions on hypergraphs, showing bistability onset depends on eigenvector correlations between dyadic and triadic structures.
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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.