Complexity-Aware Theory Testing from Bell Witnesses
Jianshuo Gao

TL;DR
This paper connects Bell witness analysis with complexity-based model selection, providing bounds and criteria to evaluate nonlocality in quantum experiments using information-theoretic measures.
Contribution
It introduces a method to relate Bell witnesses to KL divergence bounds, enabling complexity-aware assessment of nonlocal models with finite-sample guarantees.
Findings
Derived a closed-form KL divergence bound for Bell witnesses in CHSH scenario.
Applied the bound to experimental data, certifying nonlocality with complexity considerations.
Compared local and nonlocal models using information-theoretic criteria, favoring low-dimensional nonlocal descriptions.
Abstract
Bell statistical-strength analyses and complexity-based model selection are usually treated separately. Here we relate them by showing that a witness obtained from a coarse-graining of full Bell trials yields, through data processing, a lower bound on the Kullback-Leibler (KL) distance to a competitor class in terms of the induced witness distribution. For binary Bell-game witnesses this reduces to a Bernoulli bound, and in the CHSH scenario the local image collapses to a single threshold, giving the closed-form expression D_KL(Bern(omega) || Bern(3/4)) under uniform inputs, with a corresponding extension to known nonuniform designs. A finite-sample Hoeffding argument gives a lower confidence bound under independent trials. We also include a non-CHSH example based on the three-party Mermin-GHZ game. Because the bound is measured in bits per trial, it can be compared directly with an…
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