Replica symmetry breaking in a quantum-optical vector spin glass
- URL: http://arxiv.org/abs/2311.04216v1
- Date: Tue, 7 Nov 2023 18:59:34 GMT
- Title: Replica symmetry breaking in a quantum-optical vector spin glass
- Authors: Ronen M. Kroeze, Brendan P. Marsh, David Atri Schuller, Henry S. Hunt,
Sarang Gopalakrishnan, Jonathan Keeling, and Benjamin L. Lev
- Abstract summary: Spin glasses are canonical examples of complex matter.
Spin glass theory forms a mathematical basis for neuromorphic computing.
Spin configurations are observed in cavity emission and reveal the emergence of replica symmetry breaking.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Spin glasses are canonical examples of complex matter. Although much about
their structure remains uncertain, they inform the description of a wide array
of complex phenomena, ranging from magnetic ordering in metals with impurities
to aspects of evolution, protein folding, climate models, combinatorial
optimization, and artificial intelligence. Indeed, spin glass theory forms a
mathematical basis for neuromorphic computing and brain modeling. Advancing
experimental insight into their structure requires repeatable control over
microscopic degrees of freedom. Here, we achieve this at the atomic level using
a quantum-optical system comprised of ultracold gases of atoms coupled via
photons resonating within a confocal cavity. This active quantum gas microscope
realizes an unusual type of transverse-field vector spin glass with all-to-all
connectivity. Spin configurations are observed in cavity emission and reveal
the emergence of replica symmetry breaking and nascent ultrametric structure as
signatures of spin-glass order. The driven-dissipative nature of the system
manifests as a nonthermal Parisi distribution, in qualitative correspondence
with Monte Carlo simulations. The controllability provided by this new
spin-glass system, potentially down to the quantum-spin-level, enables the
study of spin-glass physics in novel regimes with application to quantum neural
network computing.
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