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This research demonstrates how treating latent variables as quantum rather than classical allows for the operational distinction between causal scenarios previously considered indistinguishable. By leveraging monogamy of nonlocality and semidefinite relaxations, the study provides a framework to identify unique signatures in intermediate latents that defy classical graphical model limits. The work highlights critical open problems regarding observational equivalence, offering foundational insights into how quantum mechanics reshapes our understanding of causal inference beyond standard statistical tools.
Distinguishing quantum causal scenarios with indistinguishable classical analogs: The significance of intermediate latents
arXiv:2412.10238v3 Announce Type: replace Abstract: The use of graphical models to represent causal hypotheses has enabled revolutionary progress in the study of the foundations of quantum theory. Here we consider directed acyclic graphs each of which contains both nodes representing observed variables as well as nodes representing latent or hidden variables. When comparing distinct causal structures, a natural question to ask is if they can explain distinct sets of observable distributions or not. Statisticians have developed a great variety of tools for resolving such questions under the assumption that latent nodes are interpreted classically. Here we highlight how the change to a quantum interpretation of the latent nodes induces distinctions between causal scenarios that would be classically indistinguishable. We especially concentrate on quantum scenarios containing latent nodes with at least one latent parent, a.k.a. possessing intermediate latents. This initial survey demonstrates that many such quantum processes can be operationally distinguished by considerations related to monogamy of nonlocality, especially when computationally aided by a hierarchy of semidefinite relaxations which we tailor for the study of such scenarios. We conclude by clarifying the challenges that prevent the generalization of this work, calling attention to open problems regarding observational (in)equivalence of quantum causal structures with intermediate latents.
Abstract:The use of graphical models to represent causal hypotheses has enabled revolutionary progress in the study of the foundations of quantum theory. Here we consider directed acyclic graphs each of which contains both nodes representing observed variables as well as nodes representing latent or hidden variables. When comparing distinct causal structures, a natural question to ask is if they can explain distinct sets of observable distributions or not. Statisticians have developed a great variety of tools for resolving such questions under the assumption that latent nodes are interpreted classically. Here we highlight how the change to a quantum interpretation of the latent nodes induces distinctions between causal scenarios that would be classically indistinguishable. We especially concentrate on quantum scenarios containing latent nodes with at least one latent parent, a.k.a. possessing intermediate latents. This initial survey demonstrates that many such quantum processes can be operationally distinguished by considerations related to monogamy of nonlocality, especially when computationally aided by a hierarchy of semidefinite relaxations which we tailor for the study of such scenarios. We conclude by clarifying the challenges that prevent the generalization of this work, calling attention to open problems regarding observational (in)equivalence of quantum causal structures with intermediate latents.
arXiv:2412.10238 [quant-ph]
(or arXiv:2412.10238v3 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2412.10238 Focus to learn more arXiv-issued DOI via DataCite
Phys.Rev.A 112 (2025) 4, 042206
https://doi.org/10.1103/f7dh-5xht Focus to learn more DOI(s) linking to related resources
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