mlsanityData to 7 Oct 2026

Stability of mixed-state phases under weak decoherence

arXiv 2511.01976 ↗First posted 3 Nov 2025quant-ph cond-mat.stat-mech cs.LGcited by 1

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Abstract (arXiv)

We prove that the Gibbs states of classical, and commuting-Pauli, Hamiltonians are stable under weak local decoherence: i.e., we show that the effect of the decoherence can be locally reversed. In particular, our conclusions apply to finite-temperature equilibrium critical points and ordered low-temperature phases. In these systems the unconditional spatio-temporal correlations are long-range, and local (e.g., Metropolis) dynamics exhibits critical slowing down. Nevertheless, our results imply the existence of local "decoders" that undo the decoherence, when the decoherence strength is below a critical value. An implication of these results is that thermally stable quantum memories have a threshold against decoherence that remains nonzero as one approaches the critical temperature. Analogously, in diffusion models, stability of data distributions implies the existence of computationally-efficent local denoisers in the late-time generation dynamics.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 57 references that are in the map. First posted on arXiv 3 Nov 2025.

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8 of 57 references.

References · 8

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  3. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  4. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  5. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,036
  6. 2025Local Diffusion Models and Phases of Data Distributionscited by 8
  7. 2025Quantum Gibbs states are locally Markoviancited by 2
  8. 2025A Dobrushin condition for quantum Markov chains: Rapid mixing and conditional mutual information at high temperaturecited by 1

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  4. 2026The Score Hamiltonian: Mapping Diffusion Models to Adiabatic Transport
  5. 2024Quantum State Generation with Structure-Preserving Diffusion Model
  6. 2026Learning Quantum Data Distribution via Chaotic Quantum Diffusion Model
  7. 2026Learning and Generating Mixed States Prepared by Shallow Channel Circuits
  8. 2023The statistical thermodynamics of generative diffusion models: Phase transitions, symmetry breaking and critical instability