Relative Entropy-Based Training of Quantum Neural Networks

Abstract: Quantum neural networks (QNNs) are gaining attention as versatile models for quantum machine learning, but training them effectively remains a challenge. Most existing approaches, such as quantum multilayer perceptrons, use fidelity-based cost functions. While well-suited for pure states, these measures are less reliable when inputs and outputs are mixed states—a situation common in learning […]

High-Dimensional Semiquantum Cryptography

A semiquantum key distribution (SQKD) protocol allows two users, one of whom is restricted in their quantum capabilities to being nearly classical, to establish a shared secret key, secure against an all-powerful adversary. The study of such protocols helps to answer the fundamental question of “how quantum” must a protocol be to gain an advantage […]