Quantum

Bounding Freedom of Choice via Causal Network Embeddings

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Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 13/11/2026, 07:43:25 UTC.

Briefings

A new method embeds Bell scenarios into causal networks to bypass measurement independence assumptions, allowing direct certification of nonclassicality from data. The study introduces a linear-programming framework for measuring measurement dependence consistency (MDC) Bell inequalities, which outperforms existing techniques in noise robustness and computational simplicity. The authors reveal that genuine quantum nonlocality can be certified even when correlations exceed the Tsirelson bound, with broad applicability to multi-outcome and multipartite Bell tests.

Key points

• The study demonstrates that embedding Bell scenarios into larger causal networks naturally overcomes the limitation of standard Bell inequalities regarding measurement independence.
• A general linear-programming framework was formulated to derive measurement-dependence consistency (MDC) Bell inequalities, significantly improving upon existing techniques in noise robustness and computational simplicity.

Context

Standard Bell inequalities rely on measurement independence, the assumption that measurement settings are perfectly decoupled from the source of correlations. This new approach bypasses that assumption by embedding Bell scenarios into causal networks, enabling direct certification of nonclassicality from data without prior assumptions about free choice.

Limitations

The evidence is a preprint (arXiv:2611.14791v1) from November 2026, so the findings remain unverified. The study focuses on two-dimensional Bell scenarios and does not provide data on higher-dimensional cases or experimental validation results.

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