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31 lines (31 loc) · 1.24 KB
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cff-version: 1.2.0
message: "If you use the software, data, figures, protocols, or derived results, cite release v1.1.0 and identify any later commit used; see CITATION.md for copy-ready formats."
title: "Representation Alignment in Commuting Quantum Boltzmann Machines"
type: software
authors:
- family-names: Lin
given-names: Ruge
affiliation: "The Hong Kong University of Science and Technology (Guangzhou)"
version: 1.1.0
date-released: 2026-08-26
repository-code: "https://github.com/GoGoKo699/QBM-Representation-Alignment"
url: "https://github.com/GoGoKo699/QBM-Representation-Alignment"
license: BSD-3-Clause
abstract: >-
Reproducible theory, experiments, and exact preparation-resource analyses for
representation alignment in commuting quantum Boltzmann machines. The archive
includes a prospectively frozen weighted sparse-Ising confirmation on a
separately generated target ensemble and a separate exhaustive supporting
study that records a graph-selection boundary.
keywords:
- quantum Boltzmann machine
- commuting Gibbs model
- Gibbs-state preparation
- sparse Ising optimization
- representation alignment
- natural gradient
- graphical models
- maximum spanning tree
- treewidth
- q-sample
- reproducible research