8 papers
Quantum Reservoir Computing: Recent Advances and Future Directions
Shehbaz Tariq, Muhammad Talha, Arshid Ali +2
Quantum reservoir computing (QRC) uses the dynamics of a fixed or weakly tuned quantum system to transform temporal and sequential inputs into measured features, while training is…
Quantum Key Distribution Without Shared Reference Frame Under Unital Noise
Junaid ur Rehman, Shehbaz Tariq, Symeon Chatzinotas
We consider a general and practical scenario of quantum key distribution (QKD) over an unknown, stationary, unital qubit channel. Furthermore, due to practical limitations, e.g., r…
Optimal GHZ-State Distribution in LOSR Quantum Networks via Local Decoding from Information Sets
Leonardo Oleynik, Shehbaz Tariq, Symeon Chatzinotas
Distributing multipartite entanglement is a prerequisite for scalable quantum networks. Networks restricted to local operations and shared randomness (LOSR) avoid the quantum-memor…
Design and Optimization of Adaptive Diversity Schemes in Quantum MIMO Channels
Shehbaz Tariq, Symeon Chatzinotas
As quantum networks evolve toward a full quantum Internet, reliable transmission in quantum multiple-input multiple-output (QuMIMO) settings becomes essential, yet remains difficul…
Towards Quantum Enhanced Adversarial Robustness with Rydberg Reservoir Learning
Shehbaz Tariq, Muhammad Talha, Symeon Chatzinotas +1
Quantum reservoir computing (QRC) leverages the high-dimensional, nonlinear dynamics inherent in quantum many-body systems for extracting spatiotemporal patterns in sequential and…
Quantum Reinforcement Learning: Recent Advances and Future Directions
Jawaher Kaldari, Shehbaz Tariq, Saif Al-Kuwari +3
As quantum machine learning continues to evolve, reinforcement learning stands out as a particularly promising yet underexplored frontier. In this survey, we investigate the recent…