Published 2014 | Version public
Book Section - Chapter

Unbounded Entanglement Can Be Needed to Achieve the Optimal Success Probability

  • 1. ROR icon Centre for Quantum Technologies
  • 2. ROR icon University of California, Berkeley

Abstract

Quantum entanglement is known to provide a strong advantage in many two-party distributed tasks. We investigate the question of how much entanglement is needed to reach optimal performance. For the first time we show that there exists a purely classical scenario for which no finite amount of entanglement suffices. To this end we introduce a simple two-party nonlocal game H, inspired by a paradox of Lucien Hardy. In our game each player has only two possible questions and can provide answers in a countable set. We exhibit a sequence of strategies which use entangled states in increasing dimension d and succeed with probability 1 − O(d^(−c)) for some c ≥ 0.13. On the other hand, we show that any strategy using an entangled state of local dimension d has success probability at most 1 − Ω(d⁻²). In addition, we show that any strategy restricted to producing answers in a set of cardinality at most d has success probability at most 1 − Ω(d⁻²).

Additional Information

© 2014 Springer-Verlag Berlin Heidelberg. The first author thanks the anonymous referees of QIP 2014 for pointing out a mistake in an earlier proof of the non-quantitative part of Theorem 1, Aleksandrs Belovs, Richard Cleve, David Roberson, Stephanie Wehner, Harry Buhrman and his group at CWI for helpful discussions. Both authors are supported by the Ministry of Education, Singapore under the Tier 3 grant MOE2012-T3-1-009. Thomas Vidick is also supported by the Newton Institute, Cambridge. Parts of this work was completed during a workshop at the Institute for Mathematical Sciences, Singapore.

Additional details

Identifiers

Eprint ID
104767
Resolver ID
CaltechAUTHORS:20200805-153500961

Funding

Ministry of Education (Singapore)
MOE2012-T3-1-009
Newton Institute

Dates

Created
2020-08-05
Created from EPrint's datestamp field
Updated
2021-11-16
Created from EPrint's last_modified field

Caltech Custom Metadata

Series Name
Lecture Notes in Computer Science
Series Volume or Issue Number
8572