Ab-initio experimental violation of Bell inequalities

08/02/2021
by   Davide Poderini, et al.
0

The violation of a Bell inequality is the paradigmatic example of device-independent quantum information: the nonclassicality of the data is certified without the knowledge of the functioning of devices. In practice, however, all Bell experiments rely on the precise understanding of the underlying physical mechanisms. Given that, it is natural to ask: Can one witness nonclassical behaviour in a truly black-box scenario? Here we propose and implement, computationally and experimentally, a solution to this ab-initio task. It exploits a robust automated optimization approach based on the Stochastic Nelder-Mead algorithm. Treating preparation and measurement devices as black-boxes, and relying on the observed statistics only, our adaptive protocol approaches the optimal Bell inequality violation after a limited number of iterations for a variety photonic states, measurement responses and Bell scenarios. In particular, we exploit it for randomness certification from unknown states and measurements. Our results demonstrate the power of automated algorithms, opening a new venue for the experimental implementation of device-independent quantum technologies.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
03/13/2019

An Analytic Semi-device-independent Entanglement Quantification for Bipartite Quantum States

We define a property called nondegeneracy for Bell inequalities, which d...
research
03/13/2019

Analytic Semi-device-independent Entanglement Quantification for Bipartite Quantum States

We define a property called nondegeneracy for Bell inequalities, which d...
research
05/04/2020

Setting up experimental Bell test with reinforcement learning

Finding optical setups producing measurement results with a targeted pro...
research
08/03/2020

Certified Randomness From Steering Using Sequential Measurements

The generation of certifiable randomness is one of the most promising ap...
research
04/11/2019

Experimental neural network enhanced quantum tomography

Quantum tomography is currently ubiquitous for testing any implementatio...
research
09/01/2022

Deep reinforcement learning for quantum multiparameter estimation

Estimation of physical quantities is at the core of most scientific rese...
research
02/23/2021

Ray-based framework for state identification in quantum dot devices

Quantum dots (QDs) defined with electrostatic gates are a leading platfo...

Please sign up or login with your details

Forgot password? Click here to reset