Journal
NPJ QUANTUM INFORMATION
Volume 4, Issue -, Pages -Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/s41534-018-0062-6
Keywords
-
Categories
Funding
- Australian Research Council (ARC) Centre for Engineered Quantum Systems grant [CE 110001013]
- ARC Centre for Quantum Computation and Communication Technology [CE110001027]
- Templeton World Charity Foundation [TWCF 0064/AB38]
- John Templeton Foundation
Ask authors/readers for more resources
Finding a causal model for a set of classical variables is now a well-established task-but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available