Quantifying quantum causal influences

Lucas Hutter, Rafael Chaves, Ranieri Vieira Nery, George Moreno, and Daniel Jost Brod
Phys. Rev. A 108, 022222 – Published 28 August 2023

Abstract

Causal influences are at the core of any empirical science, the reason why its quantification is of paramount relevance for the mathematical theory of causality and applications. Quantum correlations, however, challenge our notion of cause and effect, implying that tools and concepts developed over the years having in mind a classical world have to be reevaluated in the presence of quantum effects. Here, we propose the quantum version of the most common causality quantifier, the average causal effect, measuring how much a target quantum system is changed by interventions on its presumed cause. Not only does it offer an innate manner to quantify causation in two-qubit gates but also in alternative quantum computation models such as the measurement-based version, suggesting that causality can be used as a proxy for optimizing quantum algorithms. Considering quantum teleportation, we show that any pure entangled state offers an advantage in terms of causal effects as compared to separable states. This broadness of different uses showcases that, just as in the classical case, the quantification of causal influence has foundational and applied consequences and can lead to a yet totally unexplored tool for quantum information science.

  • Figure
  • Figure
  • Figure
  • Received 17 October 2022
  • Revised 7 February 2023
  • Accepted 2 August 2023

DOI:https://doi.org/10.1103/PhysRevA.108.022222

©2023 American Physical Society

Physics Subject Headings (PhySH)

Quantum Information, Science & TechnologyGeneral Physics

Authors & Affiliations

Lucas Hutter1, Rafael Chaves2,3, Ranieri Vieira Nery2, George Moreno2,4, and Daniel Jost Brod1

  • 1Institute of Physics, Federal University Fluminense, Niterói, Brazil
  • 2International Institute of Physics, Federal University of Rio Grande do Norte, 59070-405 Natal, Brazil
  • 3School of Science and Technology, Federal University of Rio Grande do Norte, 59078-970 Natal, Brazil
  • 4Departamento de Computação, Universidade Federal Rural de Pernambuco, 52171-900 Recife, Pernambuco, Brazil

Article Text (Subscription Required)

Click to Expand

References (Subscription Required)

Click to Expand
Issue

Vol. 108, Iss. 2 — August 2023

Reuse & Permissions
Access Options
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review A

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×