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Spin Vector Control for Heisenberg-Inspired Probabilistic Computing — arXiv:2608.12568

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.12568
License (as archived): CC0-1.0
Archived: 2026-10-19T04:59:33.749Z
SHA-256 of the archived text: 655a47c902f03d605108ff5c8004eacd427246d53a9c3b4a47d265f6aa8bc560
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Spin Vector Control for Heisenberg-Inspired Probabilistic Computing — arXiv:2608.12568 — arXiv (en), https://arxiv.org/abs/2608.12568 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_83f41ea6bcce (Metraipolis archive dc_83f41ea6bcce, sha256 655a47c902f03d605108ff5c8004eacd427246d53a9c3b4a47d265f6aa8bc560)

BibTeX

@misc{dc83f41ea6bcce,
  title = {Spin Vector Control for Heisenberg-Inspired Probabilistic Computing — arXiv:2608.12568},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.12568},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_83f41ea6bcce; sha256 655a47c902f03d605108ff5c8004eacd427246d53a9c3b4a47d265f6aa8bc560},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.12568. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Probabilistic bits (p-bits) have emerged as a cornerstone of probabilistic computing, enabling energy-efficient hardware implementation for probabilistic inference and combinatorial optimization. A critical challenge in advancing this field beyond binary p-bits lies in realizing and manipulating vector spin information, essential for mapping complex energy-based models such as the Heisenberg this http URL , we demonstrate a spintronic platform capable of real-space vector summation by using dual ferromagnetic spin injections into a monolayer graphene channel. By electrically tuning the spin polarization through independently controlled injection currents, we achieve continuous control over the magnitude and direction of the resulting spin accumulation vector. Experimental observations, supported by theoretical vector summation models and spin-circuit simulations, reveal coherent vector interactions and angular tunability of the spin state. This approach enables direct implementation of vector-based spin logic and lays the groundwork for mapping classical Heisenberg models using stochastic low-barrier magnets. Our results establish a scalable pathway for realizing probabilistic spin circuits based on two-dimensional materials, offering new opportunities for low-power, non-Boolean computing architectures.

Tema degli esploratori: calcolo e infrastrutture (retro-catalogo arXiv: annunci del 2026-08-14 in cs.ET).
Categorie arXiv: Mesoscale and Nanoscale Physics (cond-mat.mes-hall) ; Emerging Technologies (cs.ET).
Pagina del lavoro: https://arxiv.org/abs/2608.12568 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-19T04:54:04.467Z dalla pagina https://arxiv.org/catchup/cs.ET/2026-08-14?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).