225 citations · 3k across the 104 of their papers we have counts for
106 papers
Efficient learning of bosonic unitaries beyond the Gaussian class
Xiaobin Zhao, Quntao Zhuang
Multimode quantum processes are generally difficult to learn, due to the large dimensionality and complex entanglement structure beyond the Gaussian class. Here, we show that the f…
Theory of quantum comb enhanced interferometry
Haowei Shi, Quntao Zhuang
Optical frequency combs, named for their comb-like peaks in the spectrum, are essential for various sensing applications. As the technology develops, its performance has reached th…
Theory Framework of Multiplexed Photon-Number-Resolving Detectors
Xiaobin Zhao, Hezheng Qin, Hong X. Tang +2
Photon counting is a fundamental component in quantum optics and quantum information. However, implementing ideal photon-number-resolving (PNR) detectors remains experimentally cha…
Scaling Laws of Quantum Information Lifetime in Monitored Quantum Dynamics
Bingzhi Zhang, Fangjun Hu, Runzhe Mo +3
Quantum information is typically fragile under measurements and environmental coupling. Remarkably, we find that its lifetime can scale exponentially with system size when the envi…
Loss-robust crossband entanglement generation beyond the direct-transduction limit
Haowei Shi, Quntao Zhuang
Entanglement across distant frequency bands is a crucial resource in quantum networking. However, directly entangling crossband photons, e.g., microwave and optical, is challenging…
Quantum-enhanced radio-frequency photonic distributed imaging
Haowei Shi, Christopher M. Jones, Mengjie Yu +2
Quantum physics has brought enhanced capability in various sensing applications. Despite challenges from noise and loss in the radio-frequency (RF) domain, [Phys. Rev. Lett. 124, 1…
Out-of-distribution generalisation for learning quantum channels with low-energy coherent states
Jason L. Pereira, Quntao Zhuang, Leonardo Banchi
When experimentally learning the action of a continuous variable quantum process by probing it with inputs, there will often be some restriction on the input states used. One exper…
Entangled dual-comb spectroscopy
Abdulkarim Hariri, Shuai Liu, Haowei Shi +3
Optical frequency combs have emerged as a cornerstone for a wide range of areas, including spectroscopy, ranging, optical clocks, time and frequency transfer, waveform synthesis, a…
Mixed-State Quantum Denoising Diffusion Probabilistic Model
Gino Kwun, Bingzhi Zhang, Quntao Zhuang
Generative quantum machine learning has gained significant attention for its ability to produce quantum states with desired distributions. Among various quantum generative models,…
Holographic deep thermalization for secure and efficient quantum random state generation
Bingzhi Zhang, Peng Xu, Xiaohui Chen +1
Randomness is a cornerstone of science, underpinning fields such as statistics, information theory, dynamical systems, and thermodynamics. In quantum science, quantum randomness, e…
Complexity of quantum tomography from genuine non-Gaussian entanglement
Xiaobin Zhao, Pengcheng Liao, Francesco Anna Mele +2
Quantum state tomography, a fundamental tool for quantum physics, usually requires a number of state copies that scale exponentially with the system size, owing to the intricate qu…
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…
Quantum-enhanced dark matter detection with in-cavity control: mitigating the Rayleigh curse
Haowei Shi, Anthony J. Brady, Wojciech Górecki +3
The nature of dark matter is a fundamental puzzle in modern physics. A major approach of searching for dark matter relies on detecting feeble noise in microwave cavities. However,…
Uncovering Quantum Many-body Scars with Quantum Machine Learning
Jiajin Feng, Bingzhi Zhang, Zhi-Cheng Yang +1
Quantum many-body scars are rare eigenstates hidden within the chaotic spectra of many-body systems, representing a weak violation of the eigenstate thermalization hypothesis (ETH)…
Quantum Illumination Advantage for Classification Among an Arbitrary Library of Targets
Ali Cox, Quntao Zhuang, Jeffrey H. Shapiro +1
Quantum illumination (QI) is the task of querying a scene using a transmitter probe whose quantum state is entangled with a reference beam retained in ideal storage, followed by op…
Quantum illumination networks
Xiaobin Zhao, Zheshen Zhang, Quntao Zhuang
Quantum illumination is an entanglement-based target detection protocol that provides quantum advantages despite the presence of entanglement-breaking noise. However, the advantage…
Quantum-enhanced learning with a controllable bosonic variational sensor network
Pengcheng Liao, Bingzhi Zhang, Quntao Zhuang
The emergence of quantum sensor networks has presented opportunities for enhancing complex sensing tasks, while simultaneously introducing significant challenges in designing and a…
Overcoming the fundamental limit of quantum transduction via intraband entanglement
Haowei Shi, Quntao Zhuang
A quantum transducer converts an input signal to an output probe at a distant frequency band while maintaining the quantum information with high fidelity, which is crucial for quan…
Safeguarding Oscillators and Qudits with Distributed Two-Mode Squeezing
Anthony J. Brady, Jing Wu, Quntao Zhuang
Recent advancements in multi-mode Gottesman-Kitaev-Preskill (GKP) codes have shown great promise in enhancing the protection of both discrete and analog quantum information. This b…
Optimal noisy entanglement testing for ranging and communication
Pengcheng Liao, Quntao Zhuang
Given a quantum system entangled with another system , the entanglement testing problem arises, prompting the identification of the system within a set of iden…
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…
Heisenberg-Limited Quantum Lidar for Joint Range and Velocity Estimation
Maximilian Reichert, Quntao Zhuang, Mikel Sanz
We propose a quantum lidar protocol to jointly estimate the range and velocity of a target by illuminating it with a single beam of pulsed displaced squeezed light. In the lossless…
Generative quantum machine learning via denoising diffusion probabilistic models
Bingzhi Zhang, Peng Xu, Xiaohui Chen +1
Deep generative models are key-enabling technology to computer vision, text generation, and large language models. Denoising diffusion probabilistic models (DDPMs) have recently ga…
Optimal entanglement-assisted electromagnetic sensing and communication in the presence of noise
Haowei Shi, Bingzhi Zhang, Jeffrey H. Shapiro +2
High time-bandwidth product signal and idler pulses comprised of independent identically distributed two-mode squeezed vacuum (TMSV) states are readily produced by spontaneous para…