Dynamic distortion from discretized coupling feedback in soft-spin Ising machines
Abstract
Although Ising machines (IMs) have grown in popularity due to their potential as physics-based accelerators for combinatorial optimization problems (COPs), most literature focuses on empirically-obtained benchmarks with low universality. In this work, we propose dynamic feedback distortion as a universal metric to quantify the effect of coupling field discretization in time-multiplexed IMs. Starting from the transfer functions of realistic hardware, we analytically show how this distortion can be mitigated using a global bias (or choosing the correct discrete coupling element) and injecting coloured noise. Our numerical results show that our mitigation protocols are very effective, especially in complicated energy landscapes (namely tunable Möbius ladders and 2D tiling problems); where an analogue reduction of the distortion leads to a two--three order of magnitude increase in the success rate of complex COPs.
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BibTeX
@misc{gonzalez2026dynamic,
title = {{Dynamic distortion from discretized coupling feedback in soft-spin Ising machines}},
author = {Victor H. González and Natalia G. Berloff},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.07347},
eprint = {2609.07347},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.07347},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Dynamic distortion from discretized coupling feedback in soft-spin Ising machines
AU - Victor H. González
AU - Natalia G. Berloff
PY - 2026
DA - 2026/09/07
PB - arXiv
DO - 10.48550/arxiv.2609.07347
UR - https://arxiv.org/abs/2609.07347
AB - Although Ising machines (IMs) have grown in popularity due to their potential as physics-based accelerators for combinatorial optimization problems (COPs), most literature focuses on empirically-obtained benchmarks with low universality. In this work, we propose dynamic feedback distortion as a universal metric to quantify the effect of coupling field discretization in time-multiplexed IMs. Starting from the transfer functions of realistic hardware, we analytically show how this distortion can be mitigated using a global bias (or choosing the correct discrete coupling element) and injecting coloured noise. Our numerical results show that our mitigation protocols are very effective, especially in complicated energy landscapes (namely tunable Möbius ladders and 2D tiling problems); where an analogue reduction of the distortion leads to a two--three order of magnitude increase in the success rate of complex COPs.
ER -