A new Stein-method-based Gaussian approximation controls the full correlation structure of Ising models with a single negative eigenvalue outlier, delivering near-optimal mixing times where prior spectral methods break down.
Rapid mixing on random regular graphs beyond uniqueness.arXiv preprint arXiv:2504.03406
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Glauber dynamics for RFIM on bounded-degree graphs mixes in polynomial time w.h.p. under anti-concentrated random fields, with MLSI and weak Poincaré inequalities also established.
The hard-core partition function is zero-free in a complex neighborhood of [0, λ] for all λ below the connective constant threshold λ_c(μ).
Efficient sampling algorithm for the hardcore model on random regular bipartite graphs for λ ≲ 1/√Δ, implying an FPRAS for the partition function at all fugacities via combination with prior work.
citing papers explorer
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Fast mixing in Ising models with a negative spectral outlier via Gaussian approximation
A new Stein-method-based Gaussian approximation controls the full correlation structure of Ising models with a single negative eigenvalue outlier, delivering near-optimal mixing times where prior spectral methods break down.
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Glauber dynamics for random field Ising models on bounded degree graphs and MLSI
Glauber dynamics for RFIM on bounded-degree graphs mixes in polynomial time w.h.p. under anti-concentrated random fields, with MLSI and weak Poincaré inequalities also established.
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Zero-Freeness of the Hard-Core Model with Bounded Connective Constant
The hard-core partition function is zero-free in a complex neighborhood of [0, λ] for all λ below the connective constant threshold λ_c(μ).
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Sampling from the Hardcore Model on Random Regular Bipartite Graphs above the Uniqueness Threshold
Efficient sampling algorithm for the hardcore model on random regular bipartite graphs for λ ≲ 1/√Δ, implying an FPRAS for the partition function at all fugacities via combination with prior work.