The Statistical Thermodynamics of Generative Diffusion Models: Phase Transitions, Symmetry Breaking, and Critical Instability

Generative diffusion models have achieved spectacular performance in many areas of machine learning and generative modeling. While the fundamental ideas behind these models come from non-equilibrium physics, variational inference, and stochastic calculus, in this paper we show that many aspects of t...

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Main Author: Luca Ambrogioni
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Entropy
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Online Access:https://www.mdpi.com/1099-4300/27/3/291
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author Luca Ambrogioni
author_facet Luca Ambrogioni
author_sort Luca Ambrogioni
collection DOAJ
description Generative diffusion models have achieved spectacular performance in many areas of machine learning and generative modeling. While the fundamental ideas behind these models come from non-equilibrium physics, variational inference, and stochastic calculus, in this paper we show that many aspects of these models can be understood using the tools of equilibrium statistical mechanics. Using this reformulation, we show that generative diffusion models undergo second-order phase transitions corresponding to symmetry breaking phenomena. We show that these phase transitions are always in a mean-field universality class, as they are the result of a self-consistency condition in the generative dynamics. We argue that the critical instability arising from these phase transitions lies at the heart of their generative capabilities, which are characterized by a set of mean-field critical exponents. Finally, we show that the dynamic equation of the generative process can be interpreted as a stochastic adiabatic transformation that minimizes the free energy while keeping the system in thermal equilibrium.
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spelling doaj-art-34c04e75aa8d47b2b6ddde485921c83a2025-08-20T03:43:36ZengMDPI AGEntropy1099-43002025-03-0127329110.3390/e27030291The Statistical Thermodynamics of Generative Diffusion Models: Phase Transitions, Symmetry Breaking, and Critical InstabilityLuca Ambrogioni0Donders Institute for Brain, Cognition and Behaviour, Radboud University, 6525 XZ Nijmegen, The NetherlandsGenerative diffusion models have achieved spectacular performance in many areas of machine learning and generative modeling. While the fundamental ideas behind these models come from non-equilibrium physics, variational inference, and stochastic calculus, in this paper we show that many aspects of these models can be understood using the tools of equilibrium statistical mechanics. Using this reformulation, we show that generative diffusion models undergo second-order phase transitions corresponding to symmetry breaking phenomena. We show that these phase transitions are always in a mean-field universality class, as they are the result of a self-consistency condition in the generative dynamics. We argue that the critical instability arising from these phase transitions lies at the heart of their generative capabilities, which are characterized by a set of mean-field critical exponents. Finally, we show that the dynamic equation of the generative process can be interpreted as a stochastic adiabatic transformation that minimizes the free energy while keeping the system in thermal equilibrium.https://www.mdpi.com/1099-4300/27/3/291generative diffusionstatistical physicsphase transitionsspontaneous symmetry breaking
spellingShingle Luca Ambrogioni
The Statistical Thermodynamics of Generative Diffusion Models: Phase Transitions, Symmetry Breaking, and Critical Instability
Entropy
generative diffusion
statistical physics
phase transitions
spontaneous symmetry breaking
title The Statistical Thermodynamics of Generative Diffusion Models: Phase Transitions, Symmetry Breaking, and Critical Instability
title_full The Statistical Thermodynamics of Generative Diffusion Models: Phase Transitions, Symmetry Breaking, and Critical Instability
title_fullStr The Statistical Thermodynamics of Generative Diffusion Models: Phase Transitions, Symmetry Breaking, and Critical Instability
title_full_unstemmed The Statistical Thermodynamics of Generative Diffusion Models: Phase Transitions, Symmetry Breaking, and Critical Instability
title_short The Statistical Thermodynamics of Generative Diffusion Models: Phase Transitions, Symmetry Breaking, and Critical Instability
title_sort statistical thermodynamics of generative diffusion models phase transitions symmetry breaking and critical instability
topic generative diffusion
statistical physics
phase transitions
spontaneous symmetry breaking
url https://www.mdpi.com/1099-4300/27/3/291
work_keys_str_mv AT lucaambrogioni thestatisticalthermodynamicsofgenerativediffusionmodelsphasetransitionssymmetrybreakingandcriticalinstability
AT lucaambrogioni statisticalthermodynamicsofgenerativediffusionmodelsphasetransitionssymmetrybreakingandcriticalinstability