Solving Large-Scale Optimization Problems Related to Bell's Theorem
Jacek Gondzio, Jacek A. Gruca, J. A. Julian Hall, Wies{\l}aw, Laskowski, Marek \.Zukowski

TL;DR
This paper introduces an improved optimization method using a matrix-free interior point approach to efficiently test the existence of local realistic models for quantum correlations, enabling analysis of larger problems in quantum physics.
Contribution
The paper develops and demonstrates a new implementation of the optimization method using a matrix-free interior point technique, significantly enhancing performance over traditional simplex-based methods.
Findings
Matrix-free interior point method outperforms simplex method in large-scale problems
Enables computation of noise resistance for quantum correlations previously infeasible
Provides extensive data and analysis for quantum non-classicality tests
Abstract
Impossibility of finding local realistic models for quantum correlations due to entanglement is an important fact in foundations of quantum physics, gaining now new applications in quantum information theory. We present an in-depth description of a method of testing the existence of such models, which involves two levels of optimization: a higher-level non-linear task and a lower-level linear programming (LP) task. The article compares the performances of the existing implementation of the method, where the LPs are solved with the simplex method, and our new implementation, where the LPs are solved with a matrix-free interior point method. We describe in detail how the latter can be applied to our problem, discuss the basic scenario and possible improvements and how they impact on overall performance. Significant performance advantage of the matrix-free interior point method over the…
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