A review and reformulation of macroscopic realism: resolving its deficiencies using the framework of generalized probabilistic theories
David Schmid

TL;DR
This paper critically reviews macrorealism, identifies its deficiencies, and proposes a reformulation within generalized probabilistic theories, offering clearer conceptual understanding and new, more informative tests of macrorealism.
Contribution
It introduces a reformulation of macrorealism using generalized probabilistic theories, resolving previous issues and enabling more robust, theory-independent tests.
Findings
Reformulation of macrorealism within generalized probabilistic theories.
A new, maximally informative test of macrorealism proposed.
Proof that generalized contextuality implies macrorealism failure.
Abstract
The notion of macrorealism was introduced by Leggett and Garg in an attempt to capture our intuitive conception of the macroscopic world, which seems difficult to reconcile with our knowledge of quantum physics. By now, numerous experimental witnesses have been proposed as methods of falsifying macrorealism. In this work, I critically review and analyze both the definition of macrorealism and the various proposed tests thereof, identifying a number of problems with these (and revisiting key criticisms raised by other authors). I then show that all these problems can be resolved by reformulating macrorealism within the framework of generalized probabilistic theories. In particular, I argue that a theory should be considered to be macrorealist if and only if it describes every macroscopic system by a strictly classical (i.e., simplicial) generalized probabilistic theory. This approach…
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Taxonomy
TopicsQuantum Mechanics and Applications · Statistical Mechanics and Entropy · Philosophy and History of Science
