The Role of Quantum Measurements when Testing the Quantum Nature of Gravity
arXiv:2503.11882 · doi:10.1103/PhysRevD.111.104084
Abstract
In order to test the quantum nature of gravity, it is essential to explore the construction of classical gravity theories that are as consistent with experiments as possible. In particular, the classical gravity field must receive input regarding matter distribution. Previously, such input has been constructed by taking expectation values of the matter density operator or by using the outcomes of all measurements being performed on the quantum system. We propose a framework that unifies these models, and argue that the Causal Conditional Formulation of Schroedinger-Newton (CCSN) theory, which takes classical inputs only from experimental and environmental channels, is a minimum model within this framework. Since CCSN can be viewed as a quantum feedback control scheme, it can be made causal and free from pathologies that previously plagued SN theories. Since classical information from measurement results are used to generate classical gravity, CCSN can mimic quantum gravity better than one would naively expect for a classical theory. We predict experimental signatures of CCSN in two concrete scenarios: (i) a single test mass and (ii) two objects interacting via mutual gravity. In case (i), we show that the mass-concentration effect of self classical gravity still makes CCSN much easier to test than testing the mutual entanglement, yet the signatures are more subtle than previously thought for classical gravity theories. Using time-delayed and non-stationary measurements, which delay or suspend the flow of classical information into classical gravity, one can make CCSN more detectable. In case (ii), we show that mutual gravity generated by CCSN can lead to correlations that largely mimic signatures of quantum entanglement. Rigorous protocols that rule out LOCC channels, which are experimentally more challenging than simply testing entanglement, must be applied to completely rule out CCSN.
arXiv comment29 pages, 15 figures
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