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Research PaperResearchia:202610.01071

Gibbs Sampling in the Shattered Phase by Decoded Quantum Interferometry

Leo Zhou

Abstract

We apply Decoded Quantum Interferometry (DQI) to sample from the Gibbs measures of classical Ising spin Hamiltonians. We show that this Gibbs sampling problem reduces to a quantum decoding problem, and the temperature achievable by DQI is determined by the performance of decoding algorithms. We then focus on the task of Gibbs sampling for classical Ising $k$-spin glasses (or Max-$k$-XORSAT) on random Erdős-Rényi hypergraphs with average degree $D\ge k$. In a temperature range beginning asymptoti...

Submitted: October 1, 2026Subjects: Quantum Physics; Quantum Computing

Description / Details

We apply Decoded Quantum Interferometry (DQI) to sample from the Gibbs measures of classical Ising spin Hamiltonians. We show that this Gibbs sampling problem reduces to a quantum decoding problem, and the temperature achievable by DQI is determined by the performance of decoding algorithms. We then focus on the task of Gibbs sampling for classical Ising kk-spin glasses (or Max-kk-XORSAT) on random Erdős-Rényi hypergraphs with average degree D≥kD\ge k. In a temperature range beginning asymptotically at the predicted dynamical phase transition, βdyn(k,D)=(2ln⁡k)/D×[1+ok→∞(1)]β_{\rm dyn}(k,D) = \sqrt{(2\ln k)/D}\times [1+o_{k\to\infty}(1)], we show that shattering and disorder chaos form a topological barrier that obstructs many algorithms, including Glauber dynamics and any algorithm whose output distribution is "stable" under perturbations of the input. In contrast, we prove that this barrier can be broken both by a classical algorithm based on Prange's method, and by DQI equipped with a quantum decoder. For example, when D=αkD=αk with fixed α>1α>1, both Prange's algorithm and DQI can sample at any inverse temperature β<tanh⁡−1(1/α)β< \tanh^{-1}(1/α) for sufficiently large kk, well beyond the dynamical threshold βdyn∼2ln⁡k/(αk)β_{\rm dyn} \sim \sqrt{2\ln k / (αk)}. Therefore, our results show that DQI can overcome topological barriers that obstruct stable algorithms.


Source: arXiv:2609.40345v1 - http://arxiv.org/abs/2609.40345v1 PDF: https://arxiv.org/pdf/2609.40345v1 Original Link: http://arxiv.org/abs/2609.40345v1

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Date:
Oct 1, 2026
Topic:
Quantum Computing
Area:
Quantum Physics
Comments:
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