Qubits reveal cause and effect with just measurements

Researchers have demonstrated causal inference using only measurements, extending the analysis beyond single points in time to encompass two systems and two times. The work, detailed in a publication dated August 10, 2026, in npj Quantum Information, utilized coarse-grained projective measurements implemented through scattering circuits in a nuclear magnetic resonance platform. Data analysis relied on the pseudo-density matrix formalism to assess compatibility with established causal structures; the authors successfully demonstrate causal inference from measurements alone in a multi-qubit scenario. Hongfeng Liu, Xiangjing Liu, Qian Chen, Oscar Dahlsten, and Dawei Lu achieved this advance.

This advancement moves beyond previous work focused on instantaneous events, allowing for the investigation of how quantum systems influence each other over time. The team achieved this by analyzing correlations between the systems, establishing a framework for understanding cause and effect without direct intervention, which differs from traditional methods of causal inference. Data acquisition involved coarse-grained projective measurements, meaning the researchers deliberately reduced the precision of their observations, yet still successfully inferred causal connections.

This resilience to measurement imprecision is a key finding, indicating the robustness of the approach. The PDM formalism allowed the researchers to determine whether the observed measurements aligned with a specific hypothesized causal relationship between the two quantum systems.

The authors state that the manuscript includes the statement, “We thereby successfully demonstrate causal inference from coarse-grained measurements alone, in a scenario with several qubits and two times,” highlighting the scope of their achievement. This method differs from standard quantum analysis techniques, indicating a tailored approach for tackling the complexities of quantum causal inference. The team’s work involved multiple qubits, increasing the complexity of the experiment beyond simple two-state systems; this scaling up is crucial, as real-world causal inference problems often involve numerous interacting variables.

The researchers demonstrated the ability to discern causal links even when the measurements were not perfectly precise, a significant step toward practical applications. The study’s findings have implications for understanding the foundations of quantum mechanics and the nature of causality itself.

By demonstrating causal inference solely from measurements, the work challenges conventional assumptions about the need for interventions to establish cause-and-effect relationships. Oscar Dahlsten of Southern University of Science and Technology and Dawei Lu of both Southern University of Science and Technology and City University of Hong Kong are corresponding authors on the study, indicating their central roles in the research and analysis.

The team’s success in a scenario involving multiple qubits and two time points suggests the potential for extending this approach to even more complex quantum systems. The research was supported by funding from the Foundational Questions Institute and the Fetzer Franklin Fund, a donor-advised fund of the Silicon Valley Community Foundation, which enabled the team to pursue this fundamental investigation into the nature of quantum causality.

The results published in npj Quantum Information represent a significant step forward in the field, offering a new pathway for exploring causal relationships in the quantum realm. The ability to infer causality from measurements alone opens up possibilities for developing new quantum technologies and deepening our understanding of the universe.