Nonlocality without counterfactual reasoning

Nonlocal correlations are usually understood through the outcomes of alternative measurements (on two or more parts of a system) that cannot altogether actually be carried out in an experiment. Indeed, a joint input-output — e.g., measurement-setting–outcome — behavior is nonlocal if and only if the outputs for all possible inputs cannot coexist consistently. It has been argued that this counterfactual view is how Bell's inequalities and their violations are to be seen. I propose an alternative perspective which refrains from setting into relation the results of mutually exclusive measurements, but that is based solely on data actually available. My approach uses algorithmic complexity instead of probability and randomness, and implies that nonlocality has consequences similar to those in the probabilistic view. Our view is conceptually simpler than the traditional reasoning.

Figure 1

The traditional (a) vs the new (b) view: Nonlocality à la Popescu-Rohrlich (PR) plus no-signaling leads to the output inheriting randomness (a) or complexity (b), respectively, from the input.