We propose an approach based on the Fixed-Point Grover search in combinatorial spaces to efficiently identify acyclic causal structures compatible with the PC and FCI causal discovery algorithm’s output, paving the way for scalable statistical studies of causal structures in large astrophysical datasets.
Gianini, G., Banfi, M., Mio, C., Leporati, A., Pasquato, M. (2025). Quantum-Enhanced Causal Inference for High-Dimensional Astronomical Data - Extended Abstract. In Proceedings of the 4th Italian Conference on Big Data and Data Science - Workshops (ITADATA-WS 2025) (pp.1-2). CEUR-WS.
Quantum-Enhanced Causal Inference for High-Dimensional Astronomical Data - Extended Abstract
Gianini G.;Leporati A.;
2025
Abstract
We propose an approach based on the Fixed-Point Grover search in combinatorial spaces to efficiently identify acyclic causal structures compatible with the PC and FCI causal discovery algorithm’s output, paving the way for scalable statistical studies of causal structures in large astrophysical datasets.
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