The lesson of causal discovery algorithms for quantum correlations: Causal explanations of Bell-inequality violations require fine-tuning

TL;DR

This paper examines the limitations of causal discovery algorithms in explaining quantum correlations, showing they cannot distinguish Bell inequality violations without fine-tuning, which challenges their causal explanatory power.

Contribution

It demonstrates that existing causal discovery algorithms cannot differentiate quantum correlations violating Bell inequalities, highlighting the necessity of fine-tuning in causal explanations of such phenomena.

Findings

Causal discovery algorithms fail to distinguish Bell-inequality-violating correlations.

Any causal explanation of Bell violations requires fine-tuning of parameters.

Most proposed mechanisms for Bell correlations involve fine-tuning, contradicting core causal assumptions.

Abstract

An active area of research in the fields of machine learning and statistics is the development of causal discovery algorithms, the purpose of which is to infer the causal relations that hold among a set of variables from the correlations that these exhibit. We apply some of these algorithms to the correlations that arise for entangled quantum systems. We show that they cannot distinguish correlations that satisfy Bell inequalities from correlations that violate Bell inequalities, and consequently that they cannot do justice to the challenges of explaining certain quantum correlations causally. Nonetheless, by adapting the conceptual tools of causal inference, we can show that any attempt to provide a causal explanation of nonsignalling correlations that violate a Bell inequality must contradict a core principle of these algorithms, namely, that an observed statistical independence between variables should not be explained by fine-tuning of the causal parameters. In particular, we demonstrate the need for such fine-tuning for most of the causal mechanisms that have been proposed to underlie Bell correlations, including superluminal causal influences, superdeterminism (that is, a denial of freedom of choice of settings), and retrocausal influences which do not introduce causal cycles.