arXiv subjects

Robert Okuła

Publications and source records attributed to Robert Okuła.

6 recordsLinked to original sources

arXiv2026

Extensive search of Shannon entropy-based randomness certification protocols

Quantum technologies offer significant advancements in information processing and communication, notably in the domain of random number generation (RNG). The use of Bell inequalities enables users to certify the randomness of outputs produced by untrusted quantum RNG devices. We present a method for quantitatively analyzing Bell expressions used to certify randomness in quantum systems. Using this method, we conducted a comprehensive analysis on more than half a million Bell expressions involving configurations with four measurement settings for one party and three for the other. We identified five notable examples based on entropy scores under varying levels of white noise. As an extension of these results, we further incorporate the concept of self-testing for boxes (Banacki et al 2022, New J. Phys. 24 083003), enabling a more comprehensive characterization of quantum correlations through the evaluation of $Boxes(α, B)$ and the corresponding measure $Flex(α, B)$.

quant-ph↗

arXiv2026

Mapping correlations between quantum discord and Bell non-locality

We present a numerical framework for the certification and systematic analysis of the relationship between Bell nonlocality and quantum discord. By determining the minimum discord required for a bipartite state to manifest a specific Bell violation, we establish lower bounds for these correlations. We evaluate this methodology across six distinct Bell expressions, comparing their performance through the minimal discord values observed under varying intensities of white noise. Analysis of the resulting optimization landscape suggests the existence of two characteristic classes of optimized states, categorized by their minimized quantum discord.

quant-ph↗

arXiv2026

Autonomous Optical Alignment of Satellite-Based Entanglement Sources using Reinforcement Learning

Quantum entanglement distributed via satellites enable global-scale quantum communication. However, onboard sources are susceptible to misalignment due to dynamical orbital conditions. Here, we present two recalibration techniques for efficient generation of high quality entanglement using a periodically poled lithium niobate (PPLN)-based spontaneous parametric down-conversion (SPDC) source with minimum intervention. The first is a heuristic algorithm (HA) which mimics the manual alignment process in a laboratory. The second is based on reinforcement learning (RL). Our simulation demonstrates superior performance of RL with AUC=0.9119 compared to HA's 0.7042 in the modified ROC analysis (60 min threshold). RL achieves perfect alignment in 10 min as opposed to HA's 30 min. Both the methods operate within feasible satellite constraints, offering scalable automation for complex quantum communication scenarios.

quant-ph↗

arXiv2025

Device-independent Shannon entropy certification

Quantum technologies promise information processing and communication technology advancements, including random number generation (RNG). Using Bell inequalities, a user of a quantum RNG hardware can certify that the values provided by an untrusted device are truly random. This problem has been extensively studied for von Neumann and min-entropy as a measure of randomness. However, in this paper, we analyze the feasibility of such verification for Shannon entropy. We investigate how the usability of various Bell inequalities differs depending on the presence of noise. Moreover, we present the benefit of certification for Shannon compared to min-entropy, as well as the tight analytical lower bound for Shannon entropy in randomness certification.

quant-ph↗

arXiv2025

Modern applications of machine learning in quantum sciences

In this book, we provide a comprehensive introduction to the most recent advances in the application of machine learning methods in quantum sciences. We cover the use of deep learning and kernel methods in supervised, unsupervised, and reinforcement learning algorithms for phase classification, representation of many-body quantum states, quantum feedback control, and quantum circuits optimization. Moreover, we introduce and discuss more specialized topics such as differentiable programming, generative models, statistical approach to machine learning, and quantum machine learning.

quant-ph↗

arXiv2024

How decoherence affects the security of BB84 quantum key distribution protocol

We present how the mechanisms of quantum Darwinism allow for the leakage of information in the standard BB84 quantum key distribution protocol, a paradigmatic prepare and measure quantum cryptography scenario. We work within the decoherence theory framework and employ the model of measurements provided by quantum Darwinism. We investigate how much of the information about the results crucial for the cryptographic key to be kept secret is leaked during the quantum measurement process and subsequently how much of that information might be later obtained by an eavesdropper using a type of a so-called Van Eck side-channel wiretapping. We also show how the security can be affected by different ways of organizing the surrounding environment into layers, e.g. rooms or other divisions affecting the spread of quantum information in the environment and its interaction, paving a venue to potential enhancements, and insight into proper engineering of shieldings for cryptographical devices.

quant-ph↗