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Atomic and Laser Physics
Credit: Jack Hobhouse

Dr Aonan Zhang

Marie Curie Fellow

Research theme

  • Quantum optics & ultra-cold matter

Sub department

  • Atomic and Laser Physics

Research groups

  • Quantum and optical technology
aonan.zhang@physics.ox.ac.uk
Clarendon Laboratory, room 163
  • About
  • Publications

Enhancing quantum memories with light–matter interference

Optica Optica Publishing Group 12:9 (2025) 1514

Authors:

Paul M Burdekin, Ilse Maillette de Buy Wenniger, Steven Sagona-Stophel, Jerzy Szuniewicz, Aonan Zhang, Sarah E Thomas, Ian A Walmsley

Abstract:

Future optical quantum technologies, such as quantum networks, distributed quantum computing and sensing, demand efficient, broadband quantum memories. However, achieving high efficiency without introducing noise, reducing bandwidth, or limiting scalability remains a challenge. Here, we present an approach to enhance quantum memory protocols by leveraging constructive light–matter interference, leading to an increase in memory efficiency without increasing atomic density or laser intensity. We implement this method in a Raman quantum memory in warm cesium vapor and achieve more than a threefold improvement in total efficiency, reaching (34.3±8.4)%, while retaining GHz-bandwidth operation and low noise levels. Numerical simulations predict that this approach can boost efficiencies in systems limited by atomic density, such as cold atomic ensembles, from 65% to beyond 96%, while in warm atomic vapors, it could reduce the laser intensity needed to reach a given efficiency by over an order-of-magnitude, exceeding 95% total efficiency. Furthermore, our method preserves the single-mode nature of the memory at high efficiencies. This protocol is applicable to various memory architectures, paving the way toward scalable, efficient, low-noise, and high-bandwidth quantum memories.
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Boosting photon-number-resolved detection rates of transition-edge sensors by machine learning

Optica Quantum Optica Publishing Group 3:3 (2025) 246-246

Authors:

Zhenghao Li, Matthew JH Kendall, Gerard J Machado, Ruidi Zhu, Ewan Mer, Hao Zhan, Aonan Zhang, Shang Yu, Ian A Walmsley, Raj B Patel

Abstract:

Transition-edge sensors (TESs) are very effective photon-number-resolving (PNR) detectors that have enabled many photonic quantum technologies. However, their relatively slow thermal recovery time severely limits their operation rate in experimental scenarios compared with leading non-PNR detectors. In this work, we develop an algorithmic approach that enables TESs to detect and accurately classify photon pulses without waiting for a full recovery time between detection events. We propose two machine-learning-based signal processing methods: one supervised learning method and one unsupervised clustering method. By benchmarking against data obtained using coherent states and squeezed states, we show that the methods extend the TES operation rate to 800 kHz, achieving at least a four-fold improvement, whilst maintaining accurate photon-number assignment up to at least five photons. Our algorithms will find utility in applications where high rates of PNR detection are required and in technologies that demand fast active feed-forward of PNR detection outcomes.
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Experimental benchmarking of quantum state overlap estimation strategies with photonic systems.

Light, science & applications 14:1 (2025) 83

Authors:

Hao Zhan, Ben Wang, Minghao Mi, Jie Xie, Liang Xu, Aonan Zhang, Lijian Zhang

Abstract:

Accurately estimating the overlap between quantum states is a fundamental task in quantum information processing. While various strategies using distinct quantum measurements have been proposed for overlap estimation, the lack of experimental benchmarks on estimation precision limits strategy selection in different situations. Here we compare the performance of four practical strategies for overlap estimation, including tomography-tomography, tomography-projection, Schur collective measurement and optical swap test using photonic quantum systems. We encode the quantum states on the polarization and path degrees of freedom of single photons. The corresponding measurements are performed by photon detection on certain modes following single-photon mode transformation or two-photon interference. We further propose an adaptive strategy with optimized precision in full-range overlap estimation. Our results shed new light on extracting the parameter of interest from quantum systems, prompting the design of efficient quantum protocols.
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Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning

ArXiv 2411.1536 (2024)

Authors:

Zhenghao Li, Matthew JH Kendall, Gerard J Machado, Ruidi Zhu, Ewan Mer, Hao Zhan, Aonan Zhang, Shang Yu, Ian A Walmsley, Raj B Patel
Details from ArXiV

Achieving the multiparameter quantum Cramér-Rao bound with antiunitary symmetry

Physical Review Letters American Physical Society 133:21 (2024) 210801

Authors:

Ben Wang, Kaimin Zheng, Qian Xie, Aonan Zhang, Liang Xu, Lijian Zhang

Abstract:

The estimation of multiple parameters is a ubiquitous requirement in many quantum metrology applications. However, achieving the ultimate precision limit, i.e., the quantum Cramér-Rao bound, becomes challenging in these scenarios compared to single parameter estimation. To address this issue, optimizing the parameters encoding strategies with the aid of antiunitary symmetry is a novel and comprehensive approach. For demonstration, we propose two types of quantum statistical models exhibiting antiunitary symmetry in experiments. The results showcase the simultaneous achievement of ultimate precision for multiple parameters without any trade-off and the precision is improved at least twice compared to conventional encoding strategies. Our work emphasizes the significant potential of antiunitary symmetry in addressing multiparameter estimation problems.
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