Quantum oracles give an advantage for identifying classical counterfactuals
Ciar\'an M. Gilligan-Lee, Y\`il\`e Y\=ing, Jonathan Richens, David Schmid

TL;DR
This paper demonstrates that quantum oracles can identify all classical counterfactuals in causal models, surpassing classical methods, and explores the underlying quantum features responsible for this advantage.
Contribution
It introduces a quantum oracle approach that enables complete identification of counterfactuals, outperforming classical oracles in causal inference.
Findings
Quantum oracles identify all two-way joint counterfactuals.
Quantum probing provides tighter bounds on multi-way counterfactuals.
Quantum advantage may not solely rely on non-classical features like contextuality.
Abstract
We show that quantum oracles provide an advantage over classical oracles for answering classical counterfactual questions in causal models, or equivalently, for identifying unknown causal parameters such as distributions over functional dependences. In structural causal models with discrete classical variables, observational data and even ideal interventions generally fail to answer all counterfactual questions, since different causal parameters can reproduce the same observational and interventional data while disagreeing on counterfactuals. Using a simple binary example, we demonstrate that if the classical variables of interest are encoded in quantum systems and the causal dependence among them is encoded in a quantum oracle, coherently querying the oracle enables the identification of all causal parameters -- hence all classical counterfactuals. We generalize this to arbitrary…
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Taxonomy
TopicsQuantum Mechanics and Applications · Quantum Information and Cryptography · Quantum Computing Algorithms and Architecture
