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| Format: | Preprint |
| Veröffentlicht: |
2026
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| Online-Zugang: | https://arxiv.org/abs/2601.13229 |
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| _version_ | 1866918296522063872 |
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| author | Nallan, Shreyes Zhu, Jian-Gang |
| author_facet | Nallan, Shreyes Zhu, Jian-Gang |
| contents | Probabilistic computers replace logic gates with networks of interacting random variables, creating bidirectional systems that can back-derive inputs from outputs. Such architectures enable efficient generation of random samples, implementations of novel algorithms, and natural solutions to classically hard problems such as prime factorization. We present a new physical implementation for these networks: ferromagnetic disks whose magnetization switching process is triggered by current pulses, skewed by external magnetic fields, and randomized by ambient thermal noise. We show that geometry-dependent magnetostatic interactions between these magnetic cells lead to system behavior that emulates deterministic logic gates. Furthermore, by chaining multiple "gates," we achieve a highly accurate bidirectional one-bit full-adder, a proof of concept for complex multi-gate logic functions with reversible information flow. This analog magnetic probabilistic computer methodology improves on other implementations in speed, tunability, and energy efficiency, thereby enabling a powerful new pathway towards practical solution of classically hard problems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_13229 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A functionally reversible probabilistic computing architecture enabled by interactions of current-controlled magnetic devices Nallan, Shreyes Zhu, Jian-Gang Mesoscale and Nanoscale Physics Emerging Technologies Probabilistic computers replace logic gates with networks of interacting random variables, creating bidirectional systems that can back-derive inputs from outputs. Such architectures enable efficient generation of random samples, implementations of novel algorithms, and natural solutions to classically hard problems such as prime factorization. We present a new physical implementation for these networks: ferromagnetic disks whose magnetization switching process is triggered by current pulses, skewed by external magnetic fields, and randomized by ambient thermal noise. We show that geometry-dependent magnetostatic interactions between these magnetic cells lead to system behavior that emulates deterministic logic gates. Furthermore, by chaining multiple "gates," we achieve a highly accurate bidirectional one-bit full-adder, a proof of concept for complex multi-gate logic functions with reversible information flow. This analog magnetic probabilistic computer methodology improves on other implementations in speed, tunability, and energy efficiency, thereby enabling a powerful new pathway towards practical solution of classically hard problems. |
| title | A functionally reversible probabilistic computing architecture enabled by interactions of current-controlled magnetic devices |
| topic | Mesoscale and Nanoscale Physics Emerging Technologies |
| url | https://arxiv.org/abs/2601.13229 |