Classical signal model reproducing quantum probabilities for single and coincidence detections

TL;DR

This paper introduces a classical signal model that reproduces quantum probabilities by incorporating detector thresholds, challenging the traditional view that such phenomena are exclusively quantum in nature.

Contribution

The paper proposes the threshold signal detection model (TSD), a classical framework that accounts for quantum probabilities through detector thresholds and calibration, offering an alternative to quantum explanations.

Findings

TSD predicts the coefficient g^{(2)}(0) decreases with increasing detection threshold.

The model suggests classical explanations can mimic quantum correlations.

Experimental tests can verify the dependence of g^{(2)}(0) on detection thresholds.

Abstract

We present a simple classical (random) signal model reproducing Born's rule. The crucial point of our approach is that the presence of detector's threshold and calibration procedure have to be treated not as simply experimental technicalities, but as the basic counterparts of the theoretical model. We call this approach threshold signal detection model (TSD). The experiment on coincidence detection which was done by Grangier in 1986 \cite{Grangier} played a crucial role in rejection of (semi-)classical field models in favor of quantum mechanics (QM): impossibility to resolve the wave-particle duality in favor of a purely wave model. QM predicts that the relative probability of coincidence detection, the coefficient $g^{(2)}(0),$ is zero (for one photon states), but in (semi-)classical models $g^{(2)}(0)\geq 1.$ In TSD the coefficient $g^{(2)}(0)$ decreases as $1/{\cal E}_d^2,$ where ${\cal E}_d>0$ is the detection threshold. Hence, by increasing this threshold an experimenter can make the coefficient $g^{(2)}(0)$ essentially less than 1. The TSD-prediction can be tested experimentally in new Grangier type experiments presenting a detailed monitoring of dependence of the coefficient $g^{(2)}(0)$ on the detection threshold.