Any centered 1-subgaussian random vector equals the sum of a universal number of standard Gaussians, solving Talagrand's convexity conjecture.
arXiv preprint arXiv:2507.00346 , year=
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A polynomial-time algorithm samples the SK model Gibbs measure with o(1) TVD error for β < 1/2 by combining potential Hessian ascent, stochastic localization, Jarzynski equality, and Glauber dynamics.
Asymptotic expansions in 1/N² are established for traces and transport maps in multimatrix models with convex potentials, implying strong convergence.
citing papers explorer
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On Talagrand's Convexity Conjecture
Any centered 1-subgaussian random vector equals the sum of a universal number of standard Gaussians, solving Talagrand's convexity conjecture.
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Potential Hessian Ascent III: Sampling the Sherrington--Kirkpatrick Model at Beta < 1/2
A polynomial-time algorithm samples the SK model Gibbs measure with o(1) TVD error for β < 1/2 by combining potential Hessian ascent, stochastic localization, Jarzynski equality, and Glauber dynamics.
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Asymptotic expansion for transport maps between laws of multimatrix models
Asymptotic expansions in 1/N² are established for traces and transport maps in multimatrix models with convex potentials, implying strong convergence.