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Preprint

Deterministic Approximation of the Total Variation Distance Between Spin Systems

Oct 2026 · 0 citations · 29 references
Computer Science

Abstract

We study deterministic relative approximation of the total variation distance between two Gibbs distributions induced by spin systems on the same bounded-degree graph. For the hard-core model, we give a deterministic polynomial-time $\varepsilon$-relative-error approximation when both external-field vectors lie in $[b,(1-\eta)\lambda_{\mathrm c}(\Delta)]^V$, where $b>0$ and $\eta\in(0,1)$ are fixed and $\lambda_{\mathrm c}(\Delta)$ is the hard-core uniqueness threshold. For the Ising model, we obtain deterministic polynomial-time algorithms in two settings: the ferromagnetic Lee--Yang regime and the antiferromagnetic correlation-decay regime. We develop a new deterministic framework that reduces this task to estimating suitably chosen partition functions.

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