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This paper explores a novel intersection where quantum resources enable causal data fusion across heterogeneous datasets, generating non-classical signatures even in scenarios where standard Bell inequalities do not apply. By integrating interventions—a core concept from classical causal inference—the authors demonstrate how quantum correlations can be detected through the synthesis of multiple data tables rather than isolated experiments. The work advances the theoretical framework for using quantum networks to validate causality beyond classical limits, offering new tools for analyzing complex multi-source data in quantum physics.
Causal Data Fusion with Quantum Confounders
arXiv:2405.19278v2 Announce Type: replace Abstract: From the modern perspective of causal inference, Bell's theorem -- a fundamental signature of quantum theory -- is a particular case where quantum correlations are incompatible with the classical theory of causality, and the generalization of Bell's theorem to quantum networks has led to several breakthrough results and novel applications. Here, we consider the problem of causal data fusion, where we piece together multiple datasets collected under heterogeneous conditions. In particular, we show quantum experiments can generate observational and interventional data with a non-classical signature when pieced together that cannot be reproduced classically. We prove this quantum non-classicality emerges from the fusion of the datasets and is present in a plethora of scenarios, even where standard Bell non-classicality is impossible. Furthermore, we show that non-classicality genuine to the fusion of multiple data tables is achievable with quantum resources. Our work shows incorporating interventions -- a central tool in causal inference -- can be a powerful tool to detect non-classicality beyond the violation of a standard Bell inequality. In a companion article "Quantum Non-classicality from Causal Data Fusion", we extend our investigation considering all latent exogenous causal structures with 3 observable variables.
Abstract:From the modern perspective of causal inference, Bell's theorem -- a fundamental signature of quantum theory -- is a particular case where quantum correlations are incompatible with the classical theory of causality, and the generalization of Bell's theorem to quantum networks has led to several breakthrough results and novel applications. Here, we consider the problem of causal data fusion, where we piece together multiple datasets collected under heterogeneous conditions. In particular, we show quantum experiments can generate observational and interventional data with a non-classical signature when pieced together that cannot be reproduced classically. We prove this quantum non-classicality emerges from the fusion of the datasets and is present in a plethora of scenarios, even where standard Bell non-classicality is impossible. Furthermore, we show that non-classicality genuine to the fusion of multiple data tables is achievable with quantum resources. Our work shows incorporating interventions -- a central tool in causal inference -- can be a powerful tool to detect non-classicality beyond the violation of a standard Bell inequality. In a companion article "Quantum Non-classicality from Causal Data Fusion", we extend our investigation considering all latent exogenous causal structures with 3 observable variables.
Withdrawn by the authors. Its results are incorporated into arXiv:2405.19252 (v2), "Quantum nonclassicality from causal data fusion"
arXiv:2405.19278 [quant-ph]
(or arXiv:2405.19278v2 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2405.19278 Focus to learn more arXiv-issued DOI via DataCite
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