8 papers · 1 filter
Scaling Quantum Networks via Phase-Stable Vacuum Beam Guide: Architectural Blueprint and Benchmark
Yuexun Huang, Delaney Smith, Pei Zeng +4
Scaling quantum networks to continental distances requires physical infrastructure capable of overcoming both exponential attenuation and severe phase decoherence. While the concep…
Advancing quantum imaging through learning theory
Yunkai Wang, Changhun Oh, Junyu Liu +2
We study quantum imaging by applying the resolvable expressive capacity (REC) formalism developed for physical neural networks (PNNs). In this paradigm of quantum learning, the ima…
SU(d)-Symmetric Random Unitaries: Quantum Scrambling, Error Correction, and Machine Learning
Zimu Li, Han Zheng, Yunfei Wang +3
Quantum information processing in the presence of continuous symmetry is of wide importance and exhibits many novel physical and mathematical phenomena. SU(d) is a continuous group…
Quantum-data-driven dynamical transition in quantum learning
Bingzhi Zhang, Junyu Liu, Liang Jiang +1
Quantum neural networks, parameterized quantum circuits optimized under a specific cost function, provide a paradigm for achieving near-term quantum advantage in quantum informatio…
Designs from Local Random Quantum Circuits with SU(d) Symmetry
Zimu Li, Han Zheng, Junyu Liu +2
The generation of -designs (pseudorandom distributions that emulate the Haar measure up to moments) with local quantum circuit ensembles is a problem of fundamental importan…
Practical hybrid PQC-QKD protocols with enhanced security and performance
Pei Zeng, Debayan Bandyopadhyay, José A. Méndez Méndez +10
Quantum resistance is vital for emerging cryptographic systems as quantum technologies continue to advance towards large-scale, fault-tolerant quantum computers. Resistance may be…