Related Experiment Video
Updated: Sep 4, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
Published on: September 8, 2023
Quantum Liang Information Flow as Causation Quantifier
1Department of Physics and Astronomy, University College London, Gower Street, WC1E 6BT London, United Kingdom.
Abstract:
Liang information flow is widely used in classical systems and network theory for causality quantification and has been applied widely, for example, to finance, neuroscience, and climate studies. The key part of the theory is to freeze a node of a network to ascertain its causal influence on other nodes. Such a theory is yet to be applied to quantum network dynamics. Here, we generalize the Liang information flow to the quantum domain with respect to von Neumann entropy and exemplify its usage by applying it to a variety of small quantum networks.
More Related Videos
Related Concept Videos
Criteria for Causality: Bradford Hill Criteria - II
Quantum Numbers
Criteria for Causality: Bradford Hill Criteria - I
Relating Angular And Linear Quantities - I
When comparing the linear and rotational variables individually, the linear variable of position has physical units of meters, whereas the angular position variable has dimensionless units of radians, as it is the ratio of two lengths. The linear velocity...
Relating Angular And Linear Quantities - II
Correlation and Causation
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...

