Probing Antiferromagnetic Hysteresis on Programmable Quantum Annealers

Fuente: arXiv
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Autores principales: Pelofske, Elijah, Sathe, Pratik, Nisoli, Cristiano, Barrows, Frank
Formato: Preprint
Publicado: 2025
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author Pelofske, Elijah
Sathe, Pratik
Nisoli, Cristiano
Barrows, Frank
author_facet Pelofske, Elijah
Sathe, Pratik
Nisoli, Cristiano
Barrows, Frank
contents Using programmable analog quantum annealing processors, we implement a sampling-based magnetic hysteresis protocol to probe the counterintuitive notion of magnetic memory of antiferromagnets. A key component of this protocol responsible for the hysteresis is a transverse field, which enables state transitions, while the magnetic field sweep is done via a longitudinal control field. We present evidence of full saturation and reversal of the hysteresis curve, as well as emergent magnetic domain mediated by quantum fluctuations that give rise to the magnetic memory effect in antiferromagnets.
format Preprint
id arxiv_https___arxiv_org_abs_2511_17779
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Probing Antiferromagnetic Hysteresis on Programmable Quantum Annealers
Pelofske, Elijah
Sathe, Pratik
Nisoli, Cristiano
Barrows, Frank
Quantum Physics
Other Condensed Matter
Statistical Mechanics
Strongly Correlated Electrons
Computational Physics
Using programmable analog quantum annealing processors, we implement a sampling-based magnetic hysteresis protocol to probe the counterintuitive notion of magnetic memory of antiferromagnets. A key component of this protocol responsible for the hysteresis is a transverse field, which enables state transitions, while the magnetic field sweep is done via a longitudinal control field. We present evidence of full saturation and reversal of the hysteresis curve, as well as emergent magnetic domain mediated by quantum fluctuations that give rise to the magnetic memory effect in antiferromagnets.
title Probing Antiferromagnetic Hysteresis on Programmable Quantum Annealers
topic Quantum Physics
Other Condensed Matter
Statistical Mechanics
Strongly Correlated Electrons
Computational Physics
url https://arxiv.org/abs/2511.17779