Tight analytic bound on the trade-off between device-independent randomness and nonlocality

TL;DR

This paper derives tight analytic bounds on the maximum certifiable randomness based on the CHSH nonlocality measure, providing key insights for device-independent quantum randomness generation and practical applications.

Contribution

It introduces a precise analytic relationship between CHSH violation and certifiable randomness, including bounds and new Bell inequalities for higher CHSH values.

Findings

Maximal two bits of randomness for CHSH values between 2 and approximately 2.598.

Existence of Bell inequalities certifying maximum randomness for CHSH values above 2.598.

Bounds are robust under Werner state noise model.

Abstract

Two parties sharing entangled quantum systems can generate correlations that cannot be produced using only shared classical resources. These nonlocal correlations are a fundamental feature of quantum theory but also have practical applications. For instance, they can be used for device-independent (DI) random number generation, whose security is certified independently of the operations performed inside the devices. The amount of certifiable randomness that can be generated from some given non-local correlations is a key quantity of interest. Here we derive tight analytic bounds on the maximum certifiable randomness as a function of the nonlocality as expressed using the Clauser-Horne-Shimony-Holt (CHSH) value. We show that for every CHSH value greater than the local value ($2$) and up to $3\sqrt{3}/2\approx2.598$ there exist quantum correlations with that CHSH value that certify a maximal two bits of global randomness. Beyond this CHSH value the maximum certifiable randomness drops. We give a second family of Bell inequalities for CHSH values above $3\sqrt{3}/2$, and show that they certify the maximum possible randomness for the given CHSH value. Our work hence provides an achievable upper bound on the amount of randomness that can be certified for any CHSH value. We illustrate the robustness of our results, and how they could be used to improve randomness generation rates in practice, using a Werner state noise model.