84 citations · 131 across the 12 of their papers we have counts for
12 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…
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…
Towards efficient and secure quantum-classical communication networks
Pei Zeng, Debayan Bandyopadhyay, José A. Méndez Méndez +7
The rapid advancement of quantum technologies calls for the design and deployment of quantum-safe cryptographic protocols and communication networks. There are two primary approach…
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…
The curse of random quantum data
Kaining Zhang, Junyu Liu, Liu Liu +3
Quantum machine learning, which involves running machine learning algorithms on quantum devices, may be one of the most significant flagship applications for these devices. Unlike…
Dynamical transition in controllable quantum neural networks with large depth
Bingzhi Zhang, Junyu Liu, Xiao-Chuan Wu +2
Understanding the training dynamics of quantum neural networks is a fundamental task in quantum information science with wide impact in physics, chemistry and machine learning. In…
Quantum Data Center: Perspectives
Junyu Liu, Liang Jiang
A quantum version of data centers might be significant in the quantum era. In this paper, we introduce Quantum Data Center (QDC), a quantum version of existing classical data cente…
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…
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…
Quantum Computing Applications for Flight Trajectory Optimization
Henry Makhanov, Kanav Setia, Junyu Liu +2
Major players in the global aerospace industry are shifting their focus toward achieving net carbon-neutral operations by 2050. A considerable portion of the overall carbon emissio…
Towards provably efficient quantum algorithms for large-scale machine-learning models
Junyu Liu, Minzhao Liu, Jin-Peng Liu +5
Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power, and time used both in the pre-…