Nonlocality under Computational Assumptions
Paper in proceeding, 2024

Nonlocality and its connections to entanglement are fundamental features of quantum mechanics that have found numerous applications in quantum information science. A set of correlations is said to be nonlocal if it cannot be reproduced by spacelike-separated parties sharing randomness and performing local operations. An important practical consideration is that the runtime of the parties has to be shorter than the time it takes light to travel between them. One way to model this restriction is to assume that the parties are computationally bounded. We therefore initiate the study of nonlocality under computational assumptions and derive the following results: (a) We define the set NEL (not-efficiently-local) as consisting of all bipartite states whose correlations arising from local measurements cannot be reproduced with shared randomness and polynomial-time local operations. (b) Under the assumption that the Learning With Errors problem cannot be solved in quantum polynomial-time, we show that NEL=ENT, where ENT is the set of all bipartite entangled states (pure and mixed). This is in contrast to the standard notion of nonlocality where it is known that some entangled states, e.g. Werner states, are local. In essence, we show that there exist (efficient) local measurements producing correlations that cannot be reproduced through shared randomness and quantum polynomial-time computation. (c) We prove that if NEL=ENT unconditionally, then BQP not equal PP. In other words, the ability to certify all bipartite entangled states against computationally bounded adversaries gives a non-trivial separation of complexity classes. (d) Using (c), we show that a certain natural class of 1-round delegated quantum computation protocols that are sound against PP provers cannot exist.

Complexity Theory

Delegated Quantum Computation

Learning With Errors

Nonlocality

Author

Grzegorz Gluch

Swiss Federal Institute of Technology in Lausanne (EPFL)

Khashayar Barooti

Aztec Labs

Alexandru Gheorghiu

Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI

Marc-Olivier Renou

University Paris-Saclay

PROCEEDINGS OF THE 56TH ANNUAL ACM SYMPOSIUM ON THEORY OF COMPUTING, STOC 2024

0737-8017 (ISSN)

1018-1026
979-8-4007-0383-6 (ISBN)

56th Annual ACM Symposium on Theory of Computing (STOC)
Vancouver, Canada,

Subject Categories

Computer Science

DOI

10.1145/3618260.3649750

More information

Latest update

8/28/2024