Bell test 2026-10-18
A Bell test compares experimental probabilities or expectation values with a Bell inequality. In a two-setting photon polarization test, each station chooses a polarizer orientation and records an outcome. A coincidence circuit identifies candidate pairs using an agreed timing rule. The choice of which trials enter the statistic is part of the experiment: correlations calculated only from detected pairs can differ from correlations of all emitted pairs. The Polarization CHSH count model separates ideal expectation values from this experimental selection problem.
Two-setting polarization measurements and coincidence readout
. Conceptual apparatus for the ideal two-output model. The displayed angles belong to the worked CHSH example; they are not a reconstruction of a historical apparatus. Each station chooses one basis, then records either output. The coincidence record also needs a rule for missed detections. Details. CHSH inequality Created 2026-09-24 Updated 2026-10-18
For local outcomes , the Clauser–Horne–Shimony–Holt inequality isAn arbitrary no-signalling correlation can reach the algebraic maximum , while quantum correlations are bounded by .
For a short proof of the local bound, fix a deterministic local hidden-variable model assignment. The combination is . Exactly one bracket vanishes and the other is , so every assignment contributes . Averaging with a single setting-independent probability distribution preserves the interval . Mixtures also cover stochastic local hidden-variable theories. Rejecting a different sample at each setting would invalidate precisely that common-average step.
The quantum bound follows just as economically. For Hermitian operators with , the CHSH inequality operator obeys . Each commutator has operator norm at most two, giving . The Polarization CHSH count model attains this bound without allowing either station to control the distant marginal probability distribution.
Fair sampling 2026-10-18
For a specified Bell test statistic, fair sampling assumes that conditioning on successful detections preserves the correlations needed to represent the intended ensemble. Constant detector efficiency in an independently specified loss model can ensure this; constant observed count rates alone do not establish independence from the hidden state. The Polarization CHSH count model explicitly assumes independent losses.
