# Inferring causal structure: a quantum advantage

arXiv: https://arxiv.org/abs/1406.5036 · HTML: https://mlsanity.com/paper/1406.5036/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jun 2014.

## Built on by (most cited first, 2 of 2)

- [Restricted Hidden Cardinality Constraints in Causal Models](https://mlsanity.com/paper/2109.05656/) (2021)
- [Quantum causal inference in the presence of hidden common causes: An entropic approach](https://mlsanity.com/paper/2104.13227/) (2021)

## Abstract (arXiv)

The problem of using observed correlations to infer causal relations is relevant to a wide variety of scientific disciplines. Yet given correlations between just two classical variables, it is impossible to determine whether they arose from a causal influence of one on the other or a common cause influencing both, unless one can implement a randomized intervention. We here consider the problem of causal inference for quantum variables. We introduce causal tomography, which unifies and generalizes conventional quantum tomography schemes to provide a complete solution to the causal inference problem using a quantum analogue of a randomized trial. We furthermore show that, in contrast to the classical case, observed quantum correlations alone can sometimes provide a solution. We implement a quantum-optical experiment that allows us to control the causal relation between two optical modes, and two measurement schemes -- one with and one without randomization -- that extract this relation from the observed correlations. Our results show that entanglement and coherence, known to be central to quantum information processing, also provide a quantum advantage for causal inference.