Showing 1–50 of 172 results for author: Wang, P

Single-Step Phase-Engineered Pulse for Active Readout Cavity Reset in Superconducting Circuits

Authors: Ren-Ze Zhao, Ze-An Zhao, Tian-Le Wang, Peng Wang, Sheng Zhang, Xiao-Yan Yang, Hai-Feng Zhang, Zhi-Fei Li, Yuan Wu, Zi-Hao Fu, Sheng-Ri Liu, Peng Duan, Guo-Ping Guo

Abstract: In a circuit QED architecture, we experimentally demonstrate a simple and hardware-efficient Single-Step Phase-Engineered (SSPE) pulse scheme for actively depopulating the readout cavity. The method appends a reset segment with tailored amplitude and phase to a normal square readout pulse. Within the linear-response regime, the optimal reset amplitude scales proportionally with the readout amplitu… ▽ More In a circuit QED architecture, we experimentally demonstrate a simple and hardware-efficient Single-Step Phase-Engineered (SSPE) pulse scheme for actively depopulating the readout cavity. The method appends a reset segment with tailored amplitude and phase to a normal square readout pulse. Within the linear-response regime, the optimal reset amplitude scales proportionally with the readout amplitude, while the optimal reset phase remains nearly invariant, significantly simplifying the calibration process. By characterizing the cavity photons dynamics, we show that the SSPE pulse accelerates photon depletion by up to a factor of six compared to passive free decay. We further quantify the qubit backaction induced by the readout pulse and find that the SSPE pulse yields the lowest excitation and relaxation rates compared to a Square and CLEAR pulses. Our results establish the SSPE scheme as a practical and scalable approach for achieving fast, smooth, low-backaction cavity reset in superconducting quantum circuits. △ Less

Submitted 9 December, 2025; originally announced December 2025.

Universal learning of nonlocal entropy via local correlations in non-equilibrium quantum states

Authors: Hao Liao, Xuanqin Huang, Ping Wang

Abstract: Characterizing the nonlocal nature of quantum states is a central challenge in the practical application of large-scale quantum computation and simulation. Quantum mutual information (QMI), a fundamental nonlocal measure, plays a key role in quantifying entanglement and has become increasingly important in studying nonequilibrium quantum many-body phenomena, such as many-body localization and ther… ▽ More Characterizing the nonlocal nature of quantum states is a central challenge in the practical application of large-scale quantum computation and simulation. Quantum mutual information (QMI), a fundamental nonlocal measure, plays a key role in quantifying entanglement and has become increasingly important in studying nonequilibrium quantum many-body phenomena, such as many-body localization and thermalization. However, experimental measurement of QMI remains extremely difficult, particularly for nonequilibrium states, which are more complex than ground states. In this Letter, we employ a multilayer perceptron (MLP) to establish a universal mapping between the QMI and local correlations only up to second order for nonequilibrium states generated by quenches in a one-dimensional disordered XXZ model. Our approach provides a practical method for experimentally extracting QMI, readily applicable in platforms such as superconducting qubits. Moreover, this work will establishes a general framework for reconstructing other nonlocal observables, including Fisher information and out-of-time-ordered correlators. △ Less

Submitted 23 November, 2025; originally announced November 2025.

Inverse designed Hamiltonians for perfect state transfer and remote entanglement generation, and applications in superconducting qubits

Authors: Tian-Le Wang, Ze-An Zhao, Peng Wang, Sheng Zhang, Ren-Ze Zhao, Xiao-Yan Yang, Hai-Feng Zhang, Zhi-Fei Li, Yuan Wu, Peng Duan, Ming Gong, Guo-Ping Guo

Abstract: Hamiltonian inverse engineering enables the design of protocols for specific quantum evolutions or target state preparation. Perfect state transfer (PST) and remote entanglement generation are notable examples, as they serve as key primitives in quantum information processing. However, Hamiltonians obtained through conventional methods often lack robustness against noise. Assisted by inverse engin… ▽ More Hamiltonian inverse engineering enables the design of protocols for specific quantum evolutions or target state preparation. Perfect state transfer (PST) and remote entanglement generation are notable examples, as they serve as key primitives in quantum information processing. However, Hamiltonians obtained through conventional methods often lack robustness against noise. Assisted by inverse engineering, we begin with a noise-resilient energy spectrum and construct a class of Hamiltonians, referred to as the dome model, that significantly improves the system's robustness against noise, as confirmed by numerical simulations. This model introduces a tunable parameter $m$ that modifies the energy-level spacing and gives rise to a well-structured Hamiltonian. It reduces to the conventional PST model at $m=0$ and simplifies to a SWAP model involving only two end qubits in the large-$m$ regime. To address the challenge of scalability, we propose a cascaded strategy that divides long-distance PST into multiple consecutive PST steps. Our work is particularly suited for demonstration on superconducting qubits with tunable couplers, which enable rapid and flexible Hamiltonian engineering, thereby advancing the experimental potential of robust and scalable quantum information processing. △ Less

Submitted 15 October, 2025; originally announced October 2025.

Comments: 18 pages, 9 figures

High-Fidelity Single-Shot Readout and Selective Nuclear Spin Control for a Spin-1/2 Quantum Register in Diamond

Authors: Prithvi Gundlapalli, Philipp J. Vetter, Genko Genov, Michael Olney-Fraser, Peng Wang, Matthias M. Müller, Katharina Senkalla, Fedor Jelezko

Abstract: Quantum networks offer a way to overcome the size and complexity limitations of single quantum devices by linking multiple nodes into a scalable architecture. Group-IV color centers in diamond, paired with long-lived nuclear spins, have emerged as promising building blocks demonstrating proof-of-concept experiments such as blind quantum computing and quantum-enhanced sensing. However, realizing a… ▽ More Quantum networks offer a way to overcome the size and complexity limitations of single quantum devices by linking multiple nodes into a scalable architecture. Group-IV color centers in diamond, paired with long-lived nuclear spins, have emerged as promising building blocks demonstrating proof-of-concept experiments such as blind quantum computing and quantum-enhanced sensing. However, realizing a large-scale electro-nuclear register remains a major challenge. Here we establish the germanium-vacancy (GeV) center as a viable platform for such network nodes. Using correlation spectroscopy, we identify single nuclear spins within a convoluted spin environment, overcoming limitations imposed by the color center's spin-$1/2$ nature and thereby enabling indirect control of these nuclear spins. We further demonstrate high-fidelity single-shot readout of both the GeV center ($95.8\,\%$) and a neighboring ${}^{13}\text{C}$ nuclear spin ($93.7\,\%$), a key tool for feed-forward error correction. These critical advances position the GeV center as a compelling candidate for next-generation quantum network nodes. △ Less

Submitted 3 November, 2025; v1 submitted 10 October, 2025; originally announced October 2025.

High-resolution electric field imaging based on intermittent-contact mode scanning NV center electrometry

Authors: Zhi Cheng, Zhiwei Yu, Mengqi Wang, Lingfeng Yang, Zihao Cui, Ya Wang, Pengfei Wang

Abstract: Scanning nitrogen-vacancy (NV) center electrometry has shown potential for quantitative quantum imaging of electric fields at the nanoscale. However, achieving nanoscale spatial resolution remains a challenge since employing gradiometry to overcome electrostatic screening causes resolution-limiting trade-offs including the averaging effect and the sensor-sample proximity. Here, we demonstrate a sc… ▽ More Scanning nitrogen-vacancy (NV) center electrometry has shown potential for quantitative quantum imaging of electric fields at the nanoscale. However, achieving nanoscale spatial resolution remains a challenge since employing gradiometry to overcome electrostatic screening causes resolution-limiting trade-offs including the averaging effect and the sensor-sample proximity. Here, we demonstrate a scanning NV center protocol that achieves an enhanced spatial resolution of approximately 10 nm. We develop an axially symmetric probe with a sub-nanometer oscillating amplitude, which simultaneously provides robust intermittent-contact mode feedback and ensures close engagement between the diamond tip and the sample. As an example, we experimentally demonstrate a 10 nm spatial resolution on ferroelectric lithium niobate. Scanning NV center electrometry with this resolution can directly resolve the nanoscale polar textures and dynamics of emerging ferroelectrics, which commonly arise on the scale of tens of nanometers. △ Less

Submitted 15 September, 2025; originally announced September 2025.

Continuous-variable quantum key distribution over 50.4 km fiber using integrated silicon photonic transmitter and receiver

Authors: Shuaishuai Liu, Yanxiang Jia, Yuqi Shi, Yizhuo Hou, Pu Wang, Yu Zhang, Shiwei Yang, Zhenguo Lu, Xuyang Wang, Yongmin Li

Abstract: Quantum key distribution (QKD) is the fastest-growing and relatively mature technology in the field of quantum information, enabling information-theoretically secure key distribution between two remote users. Although QKD based on off-the-shelf telecom components has been validated in both laboratory and field tests, its high cost and large volume remain major obstacles to large-scale deployment.… ▽ More Quantum key distribution (QKD) is the fastest-growing and relatively mature technology in the field of quantum information, enabling information-theoretically secure key distribution between two remote users. Although QKD based on off-the-shelf telecom components has been validated in both laboratory and field tests, its high cost and large volume remain major obstacles to large-scale deployment. Photonic integration, featured by its compact size and low cost, offers an effective approach to addressing the above challenges faced by QKD. Here, we implement a high-performance, integrated local local oscillator continuous-variable (CV) QKD system based on an integrated silicon photonic transmitter and receiver. By employing a high-speed silicon photonic integrated in-phase and quadrature modulator, a low-noise and high bandwidth silicon photonic integrated heterodyne detector, and digital signal processing, our CV-QKD system achieves a symbol rate of up to 1.5625 GBaud. Furthermore, the system achieves asymptotic secret key rates of 31.05 and 5.05 Mbps over 25.8 and 50.4 km standard single-mode fiber, respectively, using an 8-phase-shift keying discrete modulation. Our integrated CV-QKD system with high symbol rate and long transmission distance pays the way for the quantum secure communication network at metropolitan area. △ Less

Submitted 12 August, 2025; originally announced August 2025.

Journal ref: Photon. Res. 13, 3141-3150 (2025)

Spectator Leakage Elimination in CZ Gates via Tunable Coupler Interference on a Superconducting Quantum Processor

Authors: Peng Wang, Bin-Han Lu, Tian-Le Wang, Sheng Zhang, Zhao-Yun Chen, Hai-Feng Zhang, Ren-Ze Zhao, Xiao-Yan Yang, Ze-An Zhao, Zhuo-Zhi Zhang, Xiang-Xiang Song, Yu-Chun Wu, Peng Duan, Guo-Ping Guo

Abstract: Spectator-induced leakage poses a fundamental challenge to scalable quantum computing, particularly as frequency collisions become unavoidable in multi-qubit processors. We introduce a leakage mitigation strategy based on dynamically reshaping the system Hamiltonian. Our technique utilizes a tunable coupler to enforce a block-diagonal structure on the effective Hamiltonian governing near-resonant… ▽ More Spectator-induced leakage poses a fundamental challenge to scalable quantum computing, particularly as frequency collisions become unavoidable in multi-qubit processors. We introduce a leakage mitigation strategy based on dynamically reshaping the system Hamiltonian. Our technique utilizes a tunable coupler to enforce a block-diagonal structure on the effective Hamiltonian governing near-resonant spectator interactions, confining the gate dynamics to a two-dimensional invariant subspace and thus preventing leakage by construction. On a multi-qubit superconducting processor, we experimentally demonstrate that this dynamic control scheme suppresses leakage rates to the order of $10^{-4}$ across a wide near-resonant detuning range. The method also scales effectively with the number of spectators. With three simultaneous spectators, the total leakage remains below the threshold relevant for surface code error correction. This approach eases the tension between dense frequency packing and high-fidelity gate operation, establishing dynamic Hamiltonian engineering as an essential tool for advancing fault-tolerant quantum computing. △ Less

Submitted 19 July, 2025; originally announced July 2025.

Comments: 6 pages, 4 figures in main text

Compilation, Optimization, Error Mitigation, and Machine Learning in Quantum Algorithms

Authors: Shuangbao Paul Wang, Jianzhou Mao, Eric Sakk

Abstract: This paper discusses the compilation, optimization, and error mitigation of quantum algorithms, essential steps to execute real-world quantum algorithms. Quantum algorithms running on a hybrid platform with QPU and CPU/GPU take advantage of existing high-performance computing power with quantum-enabled exponential speedups. The proposed approximate quantum Fourier transform (AQFT) for quantum algo… ▽ More This paper discusses the compilation, optimization, and error mitigation of quantum algorithms, essential steps to execute real-world quantum algorithms. Quantum algorithms running on a hybrid platform with QPU and CPU/GPU take advantage of existing high-performance computing power with quantum-enabled exponential speedups. The proposed approximate quantum Fourier transform (AQFT) for quantum algorithm optimization improves the circuit execution on top of an exponential speed-ups the quantum Fourier transform has provided. △ Less

Submitted 18 June, 2025; originally announced June 2025.

Journal ref: Computer Science & Information Technology (CS & IT) ISSN : 2231 - 5403 Volume 15, Number 05, March 2025

Adam assisted Fully informed Particle Swarm Optimization ( Adam-FIPSO ) based Parameter Prediction for the Quantum Approximate Optimization Algorithm (QAOA)

Authors: Shashank Sanjay Bhat, Peiyong Wang, Udaya Parampalli

Abstract: The Quantum Approximate Optimization Algorithm (QAOA) is a prominent variational algorithm used for solving combinatorial optimization problems such as the Max-Cut problem. A key challenge in QAOA lies in efficiently identifying suitable parameters (gamma, beta) that lead to high-quality solutions. In this paper, we propose a framework that combines Fully Informed Particle Swarm Optimization (FIPS… ▽ More The Quantum Approximate Optimization Algorithm (QAOA) is a prominent variational algorithm used for solving combinatorial optimization problems such as the Max-Cut problem. A key challenge in QAOA lies in efficiently identifying suitable parameters (gamma, beta) that lead to high-quality solutions. In this paper, we propose a framework that combines Fully Informed Particle Swarm Optimization (FIPSO) with adaptive gradient correction using the Adam Optimizer to navigate the QAOA parameter space. This approach aims to avoid issues such as barren plateaus and convergence to local minima. The proposed algorithm is evaluated against two classes of graph instances, Erdos Renyi and Watts-Strogatz. Experimental results across multiple QAOA depths consistently demonstrate superior performance compared to random initialization, underscoring the effectiveness and robustness of the proposed optimization framework. △ Less

Submitted 6 August, 2025; v1 submitted 7 June, 2025; originally announced June 2025.

Remote entanglement generation via enhanced quantum state transfer

Authors: Tian-Le Wang, Peng Wang, Ze-An Zhao, Sheng Zhang, Ren-Ze Zhao, Xiao-Yan Yang, Hai-Feng Zhang, Zhi-Fei Li, Yuan Wu, Liang-Liang Guo, Yong Chen, Hao-Ran Tao, Lei Du, Chi Zhang, Zhi-Long Jia, Wei-Cheng Kong, Peng Duan, Ming Gong, Guo-Ping Guo

Abstract: Achieving robust and scalable remote quantum entanglement is a fundamental challenge for the development of distributed quantum networks and modular quantum computing systems. Along this, perfect state transfer (PST) and fractional state transfer (FST) have emerged as promising schemes for quantum state transfer and remote entanglement generation using only nearest-neighbor couplings. However, the… ▽ More Achieving robust and scalable remote quantum entanglement is a fundamental challenge for the development of distributed quantum networks and modular quantum computing systems. Along this, perfect state transfer (PST) and fractional state transfer (FST) have emerged as promising schemes for quantum state transfer and remote entanglement generation using only nearest-neighbor couplings. However, the current implementations suffer from quantum loss and limited parameter tunability. In this work, we propose a new quantum state transfer scheme based on a zig-zag configuration, which introduces a controlling parameter for PST and FST. We show that this new parameter can suppress the population in the intermediate qubits, thereby reducing losses. We experimentally demonstrate the dynamics of different configurations on a superconducting quantum processor, achieving an $18\%$ reduction in error for remote Bell state generation in a 1D ($1\times5$) qubit chain, and exhibit robustness against certain types of noise. Then we extend our approach to a 2D network, successfully generating a W state among the four corner qubits. These results highlight the potential of our enhanced quantum state transfer scheme for scalable and noise-resilient quantum communication and computing. △ Less

Submitted 7 June, 2025; originally announced June 2025.

Comments: 9 pages, 4 figures in main text

Experimental robustness benchmark of quantum neural network on a superconducting quantum processor

Authors: Hai-Feng Zhang, Zhao-Yun Chen, Peng Wang, Liang-Liang Guo, Tian-Le Wang, Xiao-Yan Yang, Ren-Ze Zhao, Ze-An Zhao, Sheng Zhang, Lei Du, Hao-Ran Tao, Zhi-Long Jia, Wei-Cheng Kong, Huan-Yu Liu, Athanasios V. Vasilakos, Yang Yang, Yu-Chun Wu, Ji Guan, Peng Duan, Guo-Ping Guo

Abstract: Quantum machine learning (QML) models, like their classical counterparts, are vulnerable to adversarial attacks, hindering their secure deployment. Here, we report the first systematic experimental robustness benchmark for 20-qubit quantum neural network (QNN) classifiers executed on a superconducting processor. Our benchmarking framework features an efficient adversarial attack algorithm designed… ▽ More Quantum machine learning (QML) models, like their classical counterparts, are vulnerable to adversarial attacks, hindering their secure deployment. Here, we report the first systematic experimental robustness benchmark for 20-qubit quantum neural network (QNN) classifiers executed on a superconducting processor. Our benchmarking framework features an efficient adversarial attack algorithm designed for QNNs, enabling quantitative characterization of adversarial robustness and robustness bounds. From our analysis, we verify that adversarial training reduces sensitivity to targeted perturbations by regularizing input gradients, significantly enhancing QNN's robustness. Additionally, our analysis reveals that QNNs exhibit superior adversarial robustness compared to classical neural networks, an advantage attributed to inherent quantum noise. Furthermore, the empirical upper bound extracted from our attack experiments shows a minimal deviation ($3 \times 10^{-3}$) from the theoretical lower bound, providing strong experimental confirmation of the attack's effectiveness and the tightness of fidelity-based robustness bounds. This work establishes a critical experimental framework for assessing and improving quantum adversarial robustness, paving the way for secure and reliable QML applications. △ Less

Submitted 22 May, 2025; originally announced May 2025.

Comments: There are 8 pages with 5 figures in the main text and 15 pages with 14 figures in the supplementary information

Demonstrating Coherent Quantum Routers for Bucket-Brigade Quantum Random Access Memory on a Superconducting Processor

Authors: Sheng Zhang, Yun-Jie Wang, Peng Wang, Ren-Ze Zhao, Xiao-Yan Yang, Ze-An Zhao, Tian-Le Wang, Hai-Feng Zhang, Zhi-Fei Li, Yuan Wu, Hao-Ran Tao, Liang-Liang Guo, Lei Du, Chi Zhang, Zhi-Long Jia, Wei-Cheng Kong, Zhuo-Zhi Zhang, Xiang-Xiang Song, Yu-Chun Wu, Zhao-Yun Chen, Peng Duan, Guo-Ping Guo

Abstract: Quantum routers (QRouters) are essential components of bucket-brigade quantum random access memory (QRAM), enabling quantum applications such as Grover's search and quantum machine learning. Despite significant theoretical advances, achieving scalable and coherent QRouters experimentally remains challenging. Here, we demonstrate coherent quantum routers using a superconducting quantum processor, l… ▽ More Quantum routers (QRouters) are essential components of bucket-brigade quantum random access memory (QRAM), enabling quantum applications such as Grover's search and quantum machine learning. Despite significant theoretical advances, achieving scalable and coherent QRouters experimentally remains challenging. Here, we demonstrate coherent quantum routers using a superconducting quantum processor, laying a practical foundation for scalable QRAM systems. The quantum router at the core of our implementation utilizes the transition composite gate (TCG) scheme, wherein auxiliary energy levels temporarily mediate conditional interactions, substantially reducing circuit depth compared to traditional gate decompositions. Moreover, by encoding routing addresses in the non-adjacent qutrit states $|0\rangle$ and $|2\rangle$, our design inherently enables eraser-detection capability, providing efficient post-selection to mitigate routing errors. Experimentally, we achieve individual QRouter fidelities up to 95.74%, and validate scalability through a two-layer quantum routing network achieving an average fidelity of 82.40%. Our results represent a significant advancement in quantum routing technology, providing enhanced fidelity, built-in error resilience, and practical scalability crucial for the development of future QRAM and large-scale quantum computing architectures. △ Less

Submitted 20 May, 2025; originally announced May 2025.

Comments: 5 pages,4 figures

Narrow Inhomogeneous Distribution and Charge State Stabilization of Lead-Vacancy Centers in Diamond

Authors: Ryotaro Abe, Peng Wang, Takashi Taniguchi, Masashi Miyakawa, Shinobu Onoda, Mutsuko Hatano, Takayuki Iwasaki

Abstract: Lead-vacancy (PbV) centers in diamond with a large ground state splitting are expected to be a building block of quantum network nodes. Due to the heaviness of the Pb atom, it is challenging to fabricate high-quality PbV centers with a narrow inhomogeneous distribution and stable charge state. In this study, for the formation of the PbV centers, high temperature anneal up to 2300°C is performed af… ▽ More Lead-vacancy (PbV) centers in diamond with a large ground state splitting are expected to be a building block of quantum network nodes. Due to the heaviness of the Pb atom, it is challenging to fabricate high-quality PbV centers with a narrow inhomogeneous distribution and stable charge state. In this study, for the formation of the PbV centers, high temperature anneal up to 2300°C is performed after Pb ion implantation. At a lower temperature of 1800°C, the PbV centers show a large inhomogeneous distribution and spectral diffusion, while higher temperatures of 2200-2300°C leads to narrow inhomogeneous distributions with standard deviations of ~5 GHz. The charge state transition of the PbV centers formed at 2200°C occurs by capturing photo-carriers generated from surrounding defects under 532 nm laser irradiation. Finally, multiple stable PbV centers with nearly identical photon frequencies are obtained, which is essential for applications in quantum information processing. △ Less

Submitted 1 May, 2025; originally announced May 2025.

Robust and digital hyper-polarization protocol of nuclear spins via magic sequential sequence

Authors: Haiyang Li, Hao Liao, Ping Wang

Abstract: Hyper-polarization of nuclear spins is crucial for advancing nuclear magnetic resonance (NMR) and quantum information technologies, as nuclear spins typically exhibit extremely low polarization at room temperature due to their small gyro-magnetic ratios. A promising approach to achieving high nuclear spin polarization is transferring the polarization of electron to nuclear spin. The nitrogen-vacan… ▽ More Hyper-polarization of nuclear spins is crucial for advancing nuclear magnetic resonance (NMR) and quantum information technologies, as nuclear spins typically exhibit extremely low polarization at room temperature due to their small gyro-magnetic ratios. A promising approach to achieving high nuclear spin polarization is transferring the polarization of electron to nuclear spin. The nitrogen-vacancy (NV) center in diamond has emerged as a highly effective medium for this purpose, and various hyper-polarization protocols have been developed. Among these, the pulsed polarization (PulsePol) method has been extensively studied due to its robustness against static energy shifts of the electron spin. In this study, we introduce a sequential polarization protocol and identify a series of magic and digital sequences for hyper-polarizing nuclear spins. Notably, we demonstrate that some of these magic sequences exhibit significantly greater robustness compared to the PulsePol protocol in the presence of finite half $π$ pulse duration of the protocol. This enhanced robustness positions our protocol as a more suitable candidate for hyper-polarizing nuclear spins species with large gyromagnetic ratios and also ensures better compatibility with high-efficiency readout techniques at high magnetic fields. Additionally, the generality of our protocol allows for its direct application to other solid-state quantum systems beyond the NV center. △ Less

Submitted 17 May, 2025; v1 submitted 25 April, 2025; originally announced April 2025.

Fractional spatiotemporal optical vortices

Authors: Shunlin Huang, Peng Wang, Yilin Xu, Jun Liu, Ruxin Li

Abstract: Spatiotemporal optical vortices (STOVs) with spiral phase in the space-time domain, which carry intrinsic transverse orbital angular momentum (OAM), introduce a new degree of freedom to light beams and exhibit unique properties. While integer and fractional spatial vortices have been extensively studied and widely applied, and research on integer STOVs have grown prosperously, fractional STOVs (FS… ▽ More Spatiotemporal optical vortices (STOVs) with spiral phase in the space-time domain, which carry intrinsic transverse orbital angular momentum (OAM), introduce a new degree of freedom to light beams and exhibit unique properties. While integer and fractional spatial vortices have been extensively studied and widely applied, and research on integer STOVs have grown prosperously, fractional STOVs (FSTOVs), classified as STOVs with fractional spiral phases are rarely explored due to the challenges in characterizing rapidly varying spatiotemporal phases. Furthermore, approaches for the rapid recognition of FSTOVs are lacking. Herein, we experimentally and theoretically demonstrate the generation of FSTOVs in the far field. The generation, evolution, and diffraction rules of FSTOVs are revealed. Furthermore, a self-referential method for the rapid recognition of FSTOVs based on the energy ratio between the two end lobes of their diffraction patterns is proposed. This work will promote the development of the theory of light with transverse OAM, and open new opportunities for the applications of STOV, such as STOV-based optical communication and quantum information. △ Less

Submitted 15 April, 2025; originally announced April 2025.

Room-temperature hybrid 2D-3D quantum spin system for enhanced magnetic sensing and many-body dynamics

Authors: Haoyu Sun, Pei Yu, Xu Zhou, Xiangyu Ye, Mengqi Wang, Zhaoxin Liu, Yuhang Guo, Wenzhao Liu, You Huang, Pengfei Wang, Fazhan Shi, Kangwei Xia, Ya Wang

Abstract: Advances in hybrid quantum systems and their precise control are pivotal for developing advanced quantum technologies. Two-dimensional (2D) materials with optically accessible spin defects have emerged as a promising platform for building integrated quantum spin systems due to their exceptional flexibility and scalability. However, experimentally realizing such systems and demonstrating their supe… ▽ More Advances in hybrid quantum systems and their precise control are pivotal for developing advanced quantum technologies. Two-dimensional (2D) materials with optically accessible spin defects have emerged as a promising platform for building integrated quantum spin systems due to their exceptional flexibility and scalability. However, experimentally realizing such systems and demonstrating their superiority remains challenging. Here, we present a hybrid spin system operating under ambient conditions, integrating boron vacancy (V_B^-) spins in 2D hexagonal boron nitride flakes with a single nitrogen vacancy (NV) center in 3D single-crystal diamonds. This combined system achieves full controllability and exhibits enhanced performance for nanoscale magnetic sensing, including an improved dynamic range. Moreover, we investigate the rich many-body spin dynamics within the hybrid system, which enables us to estimate the concentration of V_B^- spins. This work provides a critical foundation for advancing the development of 2D-3D integrated quantum spin systems. △ Less

Submitted 8 December, 2025; v1 submitted 14 April, 2025; originally announced April 2025.

Comments: 15 pages, 4 figures, published to npj Quantum Information

Journal ref: npj Quantum Inf (2025)

Nonreciprocal Entanglement by Dynamically Encircling a Nexus

Authors: Lei Huang, Peng-Fei Wang, Jian-Qi Zhang, Xin Zhou, Shuo Zhang, Han-Xiao Zhang, Hong Yang, Dong Yan

Abstract: Nonreciprocal entanglement, characterized by inherently robust operation, is a cornerstone for quantum information processing and communications. However, it remains a great challenge to achieve nonreciprocal entanglement characterized by stability and robustness against environmental fluctuations. Here, we propose a universal nonlinear mechanism to engineer magnetic-free nonreciprocity in dissipa… ▽ More Nonreciprocal entanglement, characterized by inherently robust operation, is a cornerstone for quantum information processing and communications. However, it remains a great challenge to achieve nonreciprocal entanglement characterized by stability and robustness against environmental fluctuations. Here, we propose a universal nonlinear mechanism to engineer magnetic-free nonreciprocity in dissipative optomechanics by utilizing bistability, a phenomenon ubiquitous across nonlinear physical systems. By dynamically encircling the nexus of bistability, a cusp converged by the bistable surfaces, we obtain nonreciprocal displacement and then utilize it to achieve robust nonreciprocal entanglement. Owing to the unique landscape of bistability, our nonreciprocal displacement and entanglements exhibit stability and robustness through closed-loop operations. Our work presents a foundational framework for leveraging nonlinearity to achieve nonreciprocal quantum information processing. It paves new avenues for exploring nonreciprocal quantum information processing and designing backaction-immune quantum metrology with nonlinearity. △ Less

Submitted 30 August, 2025; v1 submitted 26 February, 2025; originally announced February 2025.

Comments: 8 pages, 4 figures

Advances in Continuous Variable Measurement-Device-Independent Quantum Key Distribution

Authors: Pu Wang, Yan Tian, Yongmin Li

Abstract: Continuous variable quantum key distribution (CV-QKD), utilizes continuous variables encoding such as the quadra-ture components of the quantized electromagnetic field and coherent detection decoding, offering good compatibility with the existing telecommunications technology and components. Continuous variable measurement-device-independent QKD (CV-MDI-QKD) can eliminate all the security threats… ▽ More Continuous variable quantum key distribution (CV-QKD), utilizes continuous variables encoding such as the quadra-ture components of the quantized electromagnetic field and coherent detection decoding, offering good compatibility with the existing telecommunications technology and components. Continuous variable measurement-device-independent QKD (CV-MDI-QKD) can eliminate all the security threats arising from the receiver effectively, the crucial security loophole of CV-QKD implementations. Recently, CV-MDI-QKD has attracted extensive attentions and witnessed rapid progress. Here, we review the achievements that have been made in the field of CV-MDI-QKD, including the basic principle, advancements in theoretical protocols and experimental demonstrations. Finally, we discuss the challenges faced in practical applications and future research directions. △ Less

Submitted 23 February, 2025; originally announced February 2025.

Comments: 13 pages, 7 figures

Journal ref: SCIENCE CHINA Information Sciences 68(8): 180501 (2025)

Low-loss polarization-maintaining router for single and entangled photons at a telecom wavelength

Authors: Pengfei Wang, Soyoung Baek, Masahiro Yabuno, Shigehito Miki, Hirotaka Terai, Fumihiro Kaneda

Abstract: Photon polarization serves as an essential quantum information carrier in quantum information and measurement applications. Routing of arbitrarily polarized single photons and polarization-entangled photons is a crucial technology for scaling up quantum information applications. Here, we demonstrate a low-loss, noiseless, polarization-maintaining routing of arbitrarily polarized single photons and… ▽ More Photon polarization serves as an essential quantum information carrier in quantum information and measurement applications. Routing of arbitrarily polarized single photons and polarization-entangled photons is a crucial technology for scaling up quantum information applications. Here, we demonstrate a low-loss, noiseless, polarization-maintaining routing of arbitrarily polarized single photons and, crucially, multi-photon entangled states where the entanglement is encoded in orthogonal polarization bases, at the telecom L-band. Our interferometer-based router is constructed by optics with a low angle of incidence and cross-aligned electro-optic crystals, achieving the polarization-maintaining operation with a minimal number of optical components. We demonstrate the routing of arbitrarily-polarized heralded single photons with a 0.057 dB (1.3%) loss, a $>$ 22 dB switching extinction ratio, and $>$ 99% polarization process fidelity to ideal identity operation. Moreover, the high-quality router achieves the routing of two-photon N00N-type entangled states with a highly maintained interference visibility of $\approx$ 97%. The demonstrated router scheme preserving multi-photon polarization state paves the way toward polarization-encoded photonic quantum networks as well as multi-photon entanglement synthesis via spatial- and time-multiplexing techniques. △ Less

Submitted 30 September, 2025; v1 submitted 18 February, 2025; originally announced February 2025.

Machine Learning for Detecting Steering in Qutrit-Pair States

Authors: Pu Wang, Zhongyan Li, Huixian Meng

Abstract: Only a few states in high-dimensional systems can be identified as (un)steerable using existing theoretical or experimental methods. We utilize semidefinite programming (SDP) to construct a dataset for steerability detection in qutrit-qutrit systems. For the full-information feature $F_1$, artificial neural networks achieve high classification accuracy and generalization, and preform better than t… ▽ More Only a few states in high-dimensional systems can be identified as (un)steerable using existing theoretical or experimental methods. We utilize semidefinite programming (SDP) to construct a dataset for steerability detection in qutrit-qutrit systems. For the full-information feature $F_1$, artificial neural networks achieve high classification accuracy and generalization, and preform better than the support vector machine. As feature engineering playing a pivotal role, we introduce a steering ellipsoid-like feature $F_2$, which significantly enhances the performance of each of our models. Given the SDP method provides only a sufficient condition for steerability detection, we establish the first rigorously constructed, accurately labeled dataset based on theoretical foundations. This dataset enables models to exhibit outstanding accuracy and generalization capabilities, independent of the choice of features. As applications, we investigate the steerability boundaries of isotropic states and partially entangled states, and find new steerable states. This work not only advances the application of machine learning for probing quantum steerability in high-dimensional systems but also deepens the theoretical understanding of quantum steerability itself. △ Less

Submitted 26 February, 2025; v1 submitted 16 February, 2025; originally announced February 2025.

Relativistic model of spontaneous wave-function localization induced by nonHermitian colored noise

Authors: Pei Wang

Abstract: We develop a quantum field theory based on random nonHermitian actions, which upon quantization lead to stochastic nonlinear Schrödinger dynamics for the state vector. In this framework, Lorentz and spacetime translation symmetries are preserved only in a statistical sense: the probability distribution of the action remains invariant under these transformations. As a result, the theory describes e… ▽ More We develop a quantum field theory based on random nonHermitian actions, which upon quantization lead to stochastic nonlinear Schrödinger dynamics for the state vector. In this framework, Lorentz and spacetime translation symmetries are preserved only in a statistical sense: the probability distribution of the action remains invariant under these transformations. As a result, the theory describes ensembles of quantum-state trajectories whose probability distributions remain invariant under changes of reference frame. As a concrete example, we augment the Dirac action with a purely imaginary term coupling the fermion density operator to a universal colored noise. This noise is constructed by solving the d'Alembert equation with white noise as its source, using a generalized stochastic calculus in 1+3 dimensions. We demonstrate that the colored noise drives stochastic localization of wave packets and derive the localization length analytically. Remarkably, the localization length decreases as the size of the observable universe increases. Our model thus provides a potential framework for relativistic spontaneous wave-function collapse. While establishing consistency with Born's law remains an open challenge, the present work constitutes a step toward embedding collapse models into a Lorentz-invariant quantum field theory. △ Less

Submitted 12 November, 2025; v1 submitted 12 January, 2025; originally announced January 2025.

Comments: 18 pages, 3 figures

Machine Learning Enhanced Quantum State Tomography on FPGA

Authors: Hsun-Chung Wu, Hsien-Yi Hsieh, Zhi-Kai Xu, Hua Li Chen, Zi-Hao Shi, Po-Han Wang, Popo Yang, Ole Steuernagel, Chien-Ming Wu, Ray-Kuang Lee

Abstract: Machine learning techniques have opened new avenues for real-time quantum state tomography (QST). In this work, we demonstrate the deployment of machine learning-based QST onto edge devices, specifically utilizing field programmable gate arrays (FPGAs). This implementation is realized using the {\it Vitis AI Integrated Development Environment} provided by AMD\textsuperscript \textregistered~Inc. C… ▽ More Machine learning techniques have opened new avenues for real-time quantum state tomography (QST). In this work, we demonstrate the deployment of machine learning-based QST onto edge devices, specifically utilizing field programmable gate arrays (FPGAs). This implementation is realized using the {\it Vitis AI Integrated Development Environment} provided by AMD\textsuperscript \textregistered~Inc. Compared to the Graphics Processing Unit (GPU)-based machine learning QST, our FPGA-based one reduces the average inference time by an order of magnitude, from 38 ms to 2.94 ms, but only sacrifices the average fidelity about $1\% $ reduction (from 0.99 to 0.98). The FPGA-based QST offers a highly efficient and precise tool for diagnosing quantum states, marking a significant advancement in the practical applications for quantum information processing and quantum sensing. △ Less

Submitted 8 January, 2025; originally announced January 2025.

Comments: 6 pages, 5 figures

Spin-wave frequency multiplication by magnetic vortex cores

Authors: Cheng-Jie Wang, Yuxin Li, Zhe Ding, Pengfei Wang, Fazhan Shi, Jiangfeng Du

Abstract: Frequency multiplication involves generating harmonics from an input frequency, a technique particularly useful for integrating spin-wave devices operating at different frequencies. While topological magnetic textures offer distinct advantages in spin-wave applications, frequency multiplication has not yet been observed in these structures. Here, we study the magnetization dynamics of magnetic vor… ▽ More Frequency multiplication involves generating harmonics from an input frequency, a technique particularly useful for integrating spin-wave devices operating at different frequencies. While topological magnetic textures offer distinct advantages in spin-wave applications, frequency multiplication has not yet been observed in these structures. Here, we study the magnetization dynamics of magnetic vortices formed in micron-sized disks and squares via wide-field magnetic imaging. We found the occurrence of coherent spin-wave harmonics arising from the gyration of vortex cores driven by microwave fields. This phenomenon reveals a universal mechanism where the periodical motion of delta function-like objects such as vortex cores gives rise to a frequency comb. Our results pave the way for creating nanoscale, tunable spin-based frequency multipliers and open new possibilities for frequency comb generation in a variety of systems. △ Less

Submitted 18 December, 2024; originally announced December 2024.

Charge state transition of spectrally stabilized tin-vacancy centers in diamond

Authors: Keita Ikeda, Yiyang Chen, Peng Wang, Yoshiyuki Miyamoto, Takashi Taniguchi, Shinobu Onoda, Mutsuko Hatano, Takayuki Iwasaki

Abstract: Solid-state quantum emitters are an important platform for quantum information processing. The fabrication of the emitters with stable photon frequency and narrow linewidth is a fundamental issue, and it is essential to understand optical conditions under which the emitter keeps a bright charge state or transitions to a dark state. For these purposes, in this study, we investigate the spectral sta… ▽ More Solid-state quantum emitters are an important platform for quantum information processing. The fabrication of the emitters with stable photon frequency and narrow linewidth is a fundamental issue, and it is essential to understand optical conditions under which the emitter keeps a bright charge state or transitions to a dark state. For these purposes, in this study, we investigate the spectral stability and charge state transition of tin-vacancy (SnV) centers in diamond. The photoluminescence excitation spectra of multiple SnV centers are basically stable over time with nearly transform-limited linewidths under resonant excitation, while simultaneous irradiation of resonant and non-resonant lasers makes spectra from the SnV centers unstable. We find that the instability occurs due to the charge state transition to a dark state. The charge state transition rates are quantitatively investigated depending on the laser powers. Lastly, with first-principle calculations, we model the charge state transition of the SnV center under the laser irradiation. △ Less

Submitted 9 December, 2024; originally announced December 2024.

Enhancing low-temperature quantum thermometry via sequential measurements

Authors: Ning Zhang, Chong Chen, Ping Wang

Abstract: We propose a sequential measurement protocol for accurate low-temperature estimation. The resulting correlated outputs significantly enhance the low temperature precision compared to that of the independent measurement scheme. This enhancement manifests a Heisenberg scaling of the signal-to-noise ratio for small measurement numbers $N$. Detailed analysis reveals that the final precision is determi… ▽ More We propose a sequential measurement protocol for accurate low-temperature estimation. The resulting correlated outputs significantly enhance the low temperature precision compared to that of the independent measurement scheme. This enhancement manifests a Heisenberg scaling of the signal-to-noise ratio for small measurement numbers $N$. Detailed analysis reveals that the final precision is determined by the pair correlation of the sequential outputs, which produces a dependence $N^2$ on the signal-to-noise ratio. Remarkably, we find that quantum thermometry within the sequential protocol functions as a high-resolution quantum spectroscopy of the thermal noise, underscoring the pivotal role of the sequential measurements in enhancing the spectral resolution and the temperature estimation precision. Our methodology incorporates sequential measurement into low-temperature quantum thermometry, representing an important advancement in low-temperature measurement. △ Less

Submitted 6 December, 2024; originally announced December 2024.

Comments: 8 pages, 2 figures

Neural Network-Based Frequency Optimization for Superconducting Quantum Chips

Authors: Bin-Han Lu, Peng Wang, Qing-Song Li, Yu-Chun Wu, Zhao-Yun Chen, Guo-Ping Guo

Abstract: Optimizing the frequency configuration of qubits and quantum gates in superconducting quantum chips presents a complex NP-complete optimization challenge. This process is critical for enabling practical control while minimizing decoherence and suppressing significant crosstalk. In this paper, we propose a neural network-based frequency configuration approach. A trained neural network model estimat… ▽ More Optimizing the frequency configuration of qubits and quantum gates in superconducting quantum chips presents a complex NP-complete optimization challenge. This process is critical for enabling practical control while minimizing decoherence and suppressing significant crosstalk. In this paper, we propose a neural network-based frequency configuration approach. A trained neural network model estimates frequency configuration errors, and an intermediate optimization strategy identifies optimal configurations within localized regions of the chip. The effectiveness of our method is validated through randomized benchmarking and cross-entropy benchmarking. Furthermore, we design a crosstalk-aware hardware-efficient ansatz for variational quantum eigensolvers, achieving improved energy computations. △ Less

Submitted 20 December, 2024; v1 submitted 2 December, 2024; originally announced December 2024.

Correlated Rydberg Electromagnetically Induced Transparencys

Authors: Lei Huang, Peng-fei Wang, Han-xiao Zhang, Yu Zhu, Hong Yang, Dong Yan

Abstract: In the regime of Rydberg electromagnetically induced transparency, we study the correlated behaviors between the transmission spectra of a pair of probe fields passing through respective parallel one-dimensional cold Rydberg ensembles. Due to the van der Waals (vdW) interactions between Rydberg atoms, each ensemble exhibits a local optical nonlinearity, where the output EIT spectra are sensitive t… ▽ More In the regime of Rydberg electromagnetically induced transparency, we study the correlated behaviors between the transmission spectra of a pair of probe fields passing through respective parallel one-dimensional cold Rydberg ensembles. Due to the van der Waals (vdW) interactions between Rydberg atoms, each ensemble exhibits a local optical nonlinearity, where the output EIT spectra are sensitive to both the input probe intensity and the photonic statistics. More interestingly, a nonlocal optical nonlinearity emerges between two spatially separated ensembles, as the probe transmissivity and probe correlation at the exit of one Rydberg ensemble can be manipulated by the probe field at the input of the other Rydberg ensemble. Realizing correlated Rydberg EITs holds great potential for applications in quantum control, quantum network, quantum walk and so on. △ Less

Submitted 12 November, 2024; originally announced November 2024.

Comments: 7 pages, 6 figures

Causality and Duality in Multipartite Generalized Probabilistic Theories

Authors: Yiying Chen, Peidong Wang, Zizhu Wang

Abstract: Causality is one of the most fundamental notions in physics. Generalized probabilistic theories (GPTs) and the process matrix framework incorporate it in different forms. However, a direct connection between these frameworks remains unexplored. By demonstrating the duality between no-signaling principle and classical processes in tripartite classical systems, and extending some results to multipar… ▽ More Causality is one of the most fundamental notions in physics. Generalized probabilistic theories (GPTs) and the process matrix framework incorporate it in different forms. However, a direct connection between these frameworks remains unexplored. By demonstrating the duality between no-signaling principle and classical processes in tripartite classical systems, and extending some results to multipartite systems, we first establish a strong link between these two frameworks, which are two sides of the same coin. This provides an axiomatic approach to describe the measurement space within both box world and local theories. Furthermore, we describe a logically consistent 4-partite classical process acting as an extension of the quantum switch. By incorporating more than two control states, it allows both parallel and serial application of operations. We also provide a device-independent certification of its quantum variant in the form of an inequality. △ Less

Submitted 6 November, 2024; originally announced November 2024.

Comments: 15 pages, 12 figures

Random non-Hermitian action theory for stochastic quantum dynamics: from canonical to path integral quantization

Authors: Pei Wang

Abstract: We develop a theory of random non-Hermitian action that, after quantization, describes the stochastic nonlinear dynamics of quantum states in Hilbert space. Focusing on fermionic fields, we propose both canonical quantization and path integral quantization, demonstrating that these two approaches are equivalent. Using this formalism, we investigate the evolution of a single-particle Gaussian wave… ▽ More We develop a theory of random non-Hermitian action that, after quantization, describes the stochastic nonlinear dynamics of quantum states in Hilbert space. Focusing on fermionic fields, we propose both canonical quantization and path integral quantization, demonstrating that these two approaches are equivalent. Using this formalism, we investigate the evolution of a single-particle Gaussian wave packet under the influence of non-Hermiticity and randomness. Our results show that specific types of non-Hermiticity lead to wave packet localization, while randomness affects the central position of the wave packet, causing the variance of its distribution to increase with the strength of the randomness. △ Less

Submitted 14 October, 2024; originally announced October 2024.

Comments: 9 pages

Journal ref: J. Phys. A: Math. Theor. 58, 135303 (2025)

Random non-Hermitian Hamiltonian framework for symmetry breaking dynamics

Authors: Pei Wang

Abstract: We propose random non-Hermitian Hamiltonians to model the generic stochastic nonlinear dynamics of a quantum state in Hilbert space. Our approach features an underlying linearity in the dynamical equations, ensuring the applicability of techniques used for solving linear systems. Additionally, it offers the advantage of easily incorporating statistical symmetry, a generalization of explicit symmet… ▽ More We propose random non-Hermitian Hamiltonians to model the generic stochastic nonlinear dynamics of a quantum state in Hilbert space. Our approach features an underlying linearity in the dynamical equations, ensuring the applicability of techniques used for solving linear systems. Additionally, it offers the advantage of easily incorporating statistical symmetry, a generalization of explicit symmetry to stochastic processes. To demonstrate the utility of our approach, we apply it to describe real-time dynamics, starting from an initial symmetry-preserving state and evolving into a randomly distributed, symmetry-breaking final state. Our model serves as a quantum framework for the transition process, from disordered states to ordered ones, where symmetry is spontaneously broken. △ Less

Submitted 29 July, 2025; v1 submitted 5 October, 2024; originally announced October 2024.

Comments: 16 pages, 11 figures. Published version

Journal ref: Phys. Rev. A 112, 012209 (2025)

Let the Quantum Creep In: Designing Quantum Neural Network Models by Gradually Swapping Out Classical Components

Authors: Peiyong Wang, Casey. R. Myers, Lloyd C. L. Hollenberg, Udaya Parampalli

Abstract: Artificial Intelligence (AI), with its multiplier effect and wide applications in multiple areas, could potentially be an important application of quantum computing. Since modern AI systems are often built on neural networks, the design of quantum neural networks becomes a key challenge in integrating quantum computing into AI. To provide a more fine-grained characterisation of the impact of quant… ▽ More Artificial Intelligence (AI), with its multiplier effect and wide applications in multiple areas, could potentially be an important application of quantum computing. Since modern AI systems are often built on neural networks, the design of quantum neural networks becomes a key challenge in integrating quantum computing into AI. To provide a more fine-grained characterisation of the impact of quantum components on the performance of neural networks, we propose a framework where classical neural network layers are gradually replaced by quantum layers that have the same type of input and output while keeping the flow of information between layers unchanged, different from most current research in quantum neural network, which favours an end-to-end quantum model. We start with a simple three-layer classical neural network without any normalisation layers or activation functions, and gradually change the classical layers to the corresponding quantum versions. We conduct numerical experiments on image classification datasets such as the MNIST, FashionMNIST and CIFAR-10 datasets to demonstrate the change of performance brought by the systematic introduction of quantum components. Through this framework, our research sheds new light on the design of future quantum neural network models where it could be more favourable to search for methods and frameworks that harness the advantages from both the classical and quantum worlds. △ Less

Submitted 26 September, 2024; originally announced September 2024.

Comments: 50 pages (including Appendix), many figures, accepted as a poster on QTML2024. Code available at https://github.com/peiyong-addwater/Let-The-Quantum-Creep-In

Electric imaging and dynamics of photo-charged graphene edge

Authors: Zhe Ding, Zhousheng Chen, Xiaodong Fan, Weihui Zhang, Jun Fu, Yumeng Sun, Zhi Cheng, Zhiwei Yu, Kai Yang, Yuxin Li, Xing Liu, Pengfei Wang, Ya Wang, Jianhua Jiang, Hualing Zeng, Changgan Zeng, Guosheng Shi, Fazhan Shi, Jiangfeng Du

Abstract: The one-dimensional side gate based on graphene edges shows a significant capability of reducing the channel length of field-effect transistors, further increasing the integration density of semiconductor devices. The nano-scale electric field distribution near the edge provides the physical limit of the effective channel length, however, its imaging under ambient conditions still lacks, which is… ▽ More The one-dimensional side gate based on graphene edges shows a significant capability of reducing the channel length of field-effect transistors, further increasing the integration density of semiconductor devices. The nano-scale electric field distribution near the edge provides the physical limit of the effective channel length, however, its imaging under ambient conditions still lacks, which is a critical aspect for the practical deployment of semiconductor devices. Here, we used scanning nitrogen-vacancy microscopy to investigate the electric field distribution near edges of a single-layer-graphene. Real-space scanning maps of photo-charged floating graphene flakes were acquired with a spatial resolution of $\sim$ 10 nm, and the electric edge effect was quantitatively studied by analyzing the NV spin energy level shifts due to the electric Stark effect. Since the graphene flakes are isolated from external electric sources, we brought out a theory based on photo-thermionic effect to explain the charge transfer from graphene to oxygen-terminated diamond probe with a disordered distribution of charge traps. Real-time tracing of electric fields detected the photo-thermionic emission process and the recombination process of the emitted electrons. This study provides a new perspective for graphene-based one-dimensional gates and opto-electronics with nanoscale real-space imaging, and moreover, offers a novel method to tune the chemical environment of diamond surfaces based on optical charge transfer. △ Less

Submitted 23 September, 2024; originally announced September 2024.

Comments: 8 pages, 4 figures

A Single-Ion Information Engine for Charging Quantum Battery

Authors: Jialiang Zhang, Pengfei Wang, Wentao Chen, Zhengyang Cai, Mu Qiao, Riling Li, Yingye Huang, Haonan Tian, Henchao Tu, Kaifeng Cui, Leilei Yan, Junhua Zhang, Jingning Zhang, Manhong Yung, Kihwan Kim

Abstract: Information engines produce mechanical work through measurement and adaptive control. For information engines, the principal challenge lies in how to store the generated work for subsequent utilization. Here, we report an experimental demonstration where quantized mechanical motion serves as a quantum battery and gets charged in repeated cycles by a single trapped-ion information engine. This is e… ▽ More Information engines produce mechanical work through measurement and adaptive control. For information engines, the principal challenge lies in how to store the generated work for subsequent utilization. Here, we report an experimental demonstration where quantized mechanical motion serves as a quantum battery and gets charged in repeated cycles by a single trapped-ion information engine. This is enabled by a key technological advancement in rapid state discrimination, allowing us to suppress measurement-induced disturbances. Consequently, we were able to obtain a charging efficiency over 50\% of the theoretical limit at the optimal temperature. The experimental results substantiate that this approach can render trapped ions a promising platform for microscopic information engines with potential applications in the future upon scaling up. △ Less

Submitted 26 August, 2024; originally announced August 2024.

Journal ref: Phys. Rev. Lett. 135, 140403 (2025)

Quantum Dynamics of Machine Learning

Authors: Peng Wang, Maimaitiniyazi Maimaitiabudula

Abstract: The quantum dynamic equation (QDE) of machine learning is obtained based on Schrödinger equation and potential energy equivalence relationship. Through Wick rotation, the relationship between quantum dynamics and thermodynamics is also established in this paper. This equation reformulates the iterative process of machine learning into a time-dependent partial differential equation with a clear mat… ▽ More The quantum dynamic equation (QDE) of machine learning is obtained based on Schrödinger equation and potential energy equivalence relationship. Through Wick rotation, the relationship between quantum dynamics and thermodynamics is also established in this paper. This equation reformulates the iterative process of machine learning into a time-dependent partial differential equation with a clear mathematical structure, offering a theoretical framework for investigating machine learning iterations through quantum and mathematical theories. Within this framework, the fundamental iterative process, the diffusion model, and the Softmax and Sigmoid functions are examined, validating the proposed quantum dynamics equations. This approach not only presents a rigorous theoretical foundation for machine learning but also holds promise for supporting the implementation of machine learning algorithms on quantum computers. △ Less

Submitted 7 July, 2024; originally announced July 2024.

Quantum Hamiltonian Embedding of Images for Data Reuploading Classifiers

Authors: Peiyong Wang, Casey R. Myers, Lloyd C. L. Hollenberg, Udaya Parampalli

Abstract: When applying quantum computing to machine learning tasks, one of the first considerations is the design of the quantum machine learning model itself. Conventionally, the design of quantum machine learning algorithms relies on the ``quantisation" of classical learning algorithms, such as using quantum linear algebra to implement important subroutines of classical algorithms, if not the entire algo… ▽ More When applying quantum computing to machine learning tasks, one of the first considerations is the design of the quantum machine learning model itself. Conventionally, the design of quantum machine learning algorithms relies on the ``quantisation" of classical learning algorithms, such as using quantum linear algebra to implement important subroutines of classical algorithms, if not the entire algorithm, seeking to achieve quantum advantage through possible run-time accelerations brought by quantum computing. However, recent research has started questioning whether quantum advantage via speedup is the right goal for quantum machine learning [1]. Research also has been undertaken to exploit properties that are unique to quantum systems, such as quantum contextuality, to better design quantum machine learning models [2]. In this paper, we take an alternative approach by incorporating the heuristics and empirical evidences from the design of classical deep learning algorithms to the design of quantum neural networks. We first construct a model based on the data reuploading circuit [3] with the quantum Hamiltonian data embedding unitary [4]. Through numerical experiments on images datasets, including the famous MNIST and FashionMNIST datasets, we demonstrate that our model outperforms the quantum convolutional neural network (QCNN)[5] by a large margin (up to over 40% on MNIST test set). Based on the model design process and numerical results, we then laid out six principles for designing quantum machine learning models, especially quantum neural networks. △ Less

Submitted 31 July, 2024; v1 submitted 19 July, 2024; originally announced July 2024.

Comments: 11 figures, 31 pages. Code available on https://github.com/peiyong-addwater/HamEmbedding. Author affiliation updated for v2. Acknowledgements and funding information added for v2

Realizing Scalable Conditional Operations through Auxiliary Energy Levels

Authors: Sheng Zhang, Peng Duan, Yun-Jie Wang, Tian-Le Wang, Peng Wang, Ren-Ze Zhao, Xiao-Yan Yang, Ze-An Zhao, Liang-Liang Guo, Yong Chen, Hai-Feng Zhang, Lei Du, Hao-Ran Tao, Zhi-Fei Li, Yuan Wu, Zhi-Long Jia, Wei-Cheng Kong, Zhao-Yun Chen, Zhuo-Zhi Zhang, Xiang-Xiang Song, Yu-Chun Wu, Guo-Ping Guo

Abstract: In the noisy intermediate-scale quantum (NISQ) era, flexible quantum operations are essential for advancing large-scale quantum computing, as they enable shorter circuits that mitigate decoherence and reduce gate errors. However, the complex control of quantum interactions poses significant experimental challenges that limit scalability. Here, we propose a transition composite gate scheme based on… ▽ More In the noisy intermediate-scale quantum (NISQ) era, flexible quantum operations are essential for advancing large-scale quantum computing, as they enable shorter circuits that mitigate decoherence and reduce gate errors. However, the complex control of quantum interactions poses significant experimental challenges that limit scalability. Here, we propose a transition composite gate scheme based on transition pathway engineering, which digitally implements conditional operations with reduced complexity by leveraging auxiliary energy levels. Experimentally, we demonstrate the controlled-unitary (CU) family and its applications. In entangled state preparation, our CU gate reduces the circuit depth for three-qubit Greenberger-Horne-Zeilinger (GHZ) and W states by approximately 40-44% compared to circuits using only CZ gates, leading to fidelity improvements of 1.5% and 4.2%, respectively. Furthermore, with a 72% reduction in circuit depth, we successfully implement a quantum comparator-a fundamental building block for quantum algorithms requiring conditional logic, which has remained experimentally challenging due to its inherent circuit complexity. These results demonstrate the scalability and practicality of our scheme, laying a solid foundation for the implementation of large-scale quantum algorithms in future quantum processors. △ Less

Submitted 15 April, 2025; v1 submitted 9 July, 2024; originally announced July 2024.

Comments: 16 pages, 13 figures

Improving the trainability of VQE on NISQ computers for solving portfolio optimization using convex interpolation

Authors: Shengbin Wang, Guihui Li, Zhimin Wang, Zhaoyun Chen, Peng Wang, Menghan Dou, Haiyong Zheng, Yongjian Gu, Yu-Chun Wu, Guo-Ping Guo

Abstract: Solving combinatorial optimization problems using variational quantum algorithms (VQAs) might be a promise application in the NISQ era. However, the limited trainability of VQAs could hinder their scalability to large problem sizes. In this paper, we improve the trainability of variational quantum eigensolver (VQE) by utilizing convex interpolation to solve portfolio optimization. Based on convex… ▽ More Solving combinatorial optimization problems using variational quantum algorithms (VQAs) might be a promise application in the NISQ era. However, the limited trainability of VQAs could hinder their scalability to large problem sizes. In this paper, we improve the trainability of variational quantum eigensolver (VQE) by utilizing convex interpolation to solve portfolio optimization. Based on convex interpolation, the location of the ground state can be evaluated by learning the property of a small subset of basis states in the Hilbert space. This enlightens naturally the proposals of the strategies of close-to-solution initialization, regular cost function landscape, and recursive ansatz equilibrium partition. The successfully implementation of a $40$-qubit experiment using only $10$ superconducting qubits demonstrates the effectiveness of our proposals. Furthermore, the quantum inspiration has also spurred the development of a prototype greedy algorithm. Extensive numerical simulations indicate that the hybridization of VQE and greedy algorithms achieves a mutual complementarity, combining the advantages of both global and local optimization methods. Our proposals can be extended to improve the trainability for solving other large-scale combinatorial optimization problems that are widely used in real applications, paving the way to unleash quantum advantages of NISQ computers in the near future. △ Less

Submitted 27 July, 2025; v1 submitted 7 July, 2024; originally announced July 2024.

Critical fluctuation and noise spectra in two-dimensional Fe$_{3}$GeTe$_{2}$ magnets

Authors: Yuxin Li, Zhe Ding, Chen Wang, Haoyu Sun, Zhousheng Chen, Pengfei Wang, Ya Wang, Ming Gong, Hualing Zeng, Fazhan Shi, Jiangfeng Du

Abstract: Critical fluctuations play a fundamental role in determining the spin orders for low-dimensional quantum materials, especially for recently discovered two-dimensional (2D) magnets. Here we employ the quantum decoherence imaging technique utilizing nitrogen-vacancy centers in diamond to explore the critical magnetic fluctuations and the associated temporal spin noise in van der Waals magnet… ▽ More Critical fluctuations play a fundamental role in determining the spin orders for low-dimensional quantum materials, especially for recently discovered two-dimensional (2D) magnets. Here we employ the quantum decoherence imaging technique utilizing nitrogen-vacancy centers in diamond to explore the critical magnetic fluctuations and the associated temporal spin noise in van der Waals magnet $\rm{Fe_{3}GeTe_{2}}$. We show that the critical fluctuation contributes to a random magnetic field characterized by the noise spectra, which can be changed dramatically near the critical temperature $T_c$. A theoretical model to describe this phenomenon is developed, showing that the spectral density is characterized by a $1/f$ noise near the $T_c$, while away from this point it behaves like a white noise. The crossover at a certain temperature between these two situations is determined by changing of the distance between the sample and the diamond. This work provides a new way to study critical fluctuation and to extract some of the critical exponents, which may greatly deepen our understanding of criticality in a wide range of physical systems. △ Less

Submitted 30 June, 2024; originally announced July 2024.

Expressibility of linear combination of ansatz circuits

Authors: Peng Wang, Ruyu Yang

Abstract: Variational Quantum Eigensolver is considered promising for medium-scale noisy quantum computers. Expressibility is an important metric for measuring the capability of a variational quantum Ansatz circuit. A commonly used method to increase expressibility is to increase the circuit depth. However, increasing the circuit depth also introduces more noise. We propose to use a linear combination of an… ▽ More Variational Quantum Eigensolver is considered promising for medium-scale noisy quantum computers. Expressibility is an important metric for measuring the capability of a variational quantum Ansatz circuit. A commonly used method to increase expressibility is to increase the circuit depth. However, increasing the circuit depth also introduces more noise. We propose to use a linear combination of ansatzes to improve the expressibility of variational circuits, thus avoiding the increase of circuit depth. Concurrently, we introduce a novel measurement strategy that circumvents the necessity for the Hadamard test, thereby significantly diminishing the reliance on two-qubit gates, which are presently the predominant contributors to quantum noise. We also provide a corresponding gradient calculation method, which makes it convenient to update the parameters. Compared with the method of increasing the circuit depth, our method of improving expressibility is more practical. Numerical simulations demonstrate the effectiveness of our method. △ Less

Submitted 16 June, 2024; originally announced June 2024.

Comments: 10pages, 9figures

Enabling Large-Scale and High-Precision Fluid Simulations on Near-Term Quantum Computers

Authors: Zhao-Yun Chen, Teng-Yang Ma, Chuang-Chao Ye, Liang Xu, Ming-Yang Tan, Xi-Ning Zhuang, Xiao-Fan Xu, Yun-Jie Wang, Tai-Ping Sun, Yong Chen, Lei Du, Liang-Liang Guo, Hai-Feng Zhang, Hao-Ran Tao, Tian-Le Wang, Xiao-Yan Yang, Ze-An Zhao, Peng Wang, Sheng Zhang, Chi Zhang, Ren-Ze Zhao, Zhi-Long Jia, Wei-Cheng Kong, Meng-Han Dou, Jun-Chao Wang , et al. (7 additional authors not shown)

Abstract: Quantum computational fluid dynamics (QCFD) offers a promising alternative to classical computational fluid dynamics (CFD) by leveraging quantum algorithms for higher efficiency. This paper introduces a comprehensive QCFD method, including an iterative method "Iterative-QLS" that suppresses error in quantum linear solver, and a subspace method to scale the solution to a larger size. We implement o… ▽ More Quantum computational fluid dynamics (QCFD) offers a promising alternative to classical computational fluid dynamics (CFD) by leveraging quantum algorithms for higher efficiency. This paper introduces a comprehensive QCFD method, including an iterative method "Iterative-QLS" that suppresses error in quantum linear solver, and a subspace method to scale the solution to a larger size. We implement our method on a superconducting quantum computer, demonstrating successful simulations of steady Poiseuille flow and unsteady acoustic wave propagation. The Poiseuille flow simulation achieved a relative error of less than $0.2\%$, and the unsteady acoustic wave simulation solved a 5043-dimensional matrix. We emphasize the utilization of the quantum-classical hybrid approach in applications of near-term quantum computers. By adapting to quantum hardware constraints and offering scalable solutions for large-scale CFD problems, our method paves the way for practical applications of near-term quantum computers in computational science. △ Less

Submitted 19 June, 2024; v1 submitted 10 June, 2024; originally announced June 2024.

Comments: 31 pages, 10 figures

Journal ref: Computer Methods in Applied Mechanics and Engineering, Volume 432, Part B, 2024, 117428

Deterministic interconversion of GHZ state and KLM state via Lie-transform-based pulse design in Rydberg atoms

Authors: J. P. Wang, Y. Q. Ji, L. P. Yang, C. Q. Wang, L. Dong, X. M. Xiu

Abstract: Conversion between different types of entangled states is an interesting problem in quantum mechanics. But research on the conversion between Greenberger-Horne-Zeilinger (GHZ) state and Knill-Laflamme-Milburn (KLM) state in atomic system is absent. In this paper, we propose a scheme to realize the interconversion (one-step) between GHZ state and KLM state with Rydberg atoms. By utilizing Rydberg-m… ▽ More Conversion between different types of entangled states is an interesting problem in quantum mechanics. But research on the conversion between Greenberger-Horne-Zeilinger (GHZ) state and Knill-Laflamme-Milburn (KLM) state in atomic system is absent. In this paper, we propose a scheme to realize the interconversion (one-step) between GHZ state and KLM state with Rydberg atoms. By utilizing Rydberg-mediated interactions, we simplify the system. By combining Lie-transform-based pulse design, the evolution path is built up to realize interconversion of GHZ state and KLM state. The numerical simulation result shows that the present scheme is robust against decoherence and operational imperfection, the analysis shows that the scheme is feasible with current experimental technology. △ Less

Submitted 24 May, 2024; originally announced May 2024.

Comments: 11 pages, 8 figures

Cavity-enhanced photon indistinguishability at room temperature and telecom wavelengths

Authors: Lukas Husel, Julian Trapp, Johannes Scherzer, Xiaojian Wu, Peng Wang, Jacob Fortner, Manuel Nutz, Thomas Hümmer, Borislav Polovnikov, Michael Förg, David Hunger, YuHuang Wang, Alexander Högele

Abstract: Indistinguishable single photons in the telecom-bandwidth of optical fibers are indispensable for long-distance quantum communication. Solid-state single photon emitters have achieved excellent performance in key benchmarks, however, the demonstration of indistinguishability at room-temperature remains a major challenge. Here, we report room-temperature photon indistinguishability at telecom wavel… ▽ More Indistinguishable single photons in the telecom-bandwidth of optical fibers are indispensable for long-distance quantum communication. Solid-state single photon emitters have achieved excellent performance in key benchmarks, however, the demonstration of indistinguishability at room-temperature remains a major challenge. Here, we report room-temperature photon indistinguishability at telecom wavelengths from individual nanotube defects in a fiber-based microcavity operated in the regime of incoherent good cavity-coupling. The efficiency of the coupled system outperforms spectral or temporal filtering, and the photon indistinguishability is increased by more than two orders of magnitude compared to the free-space limit. Our results highlight a promising strategy to attain optimized non-classical light sources. △ Less

Submitted 13 May, 2024; originally announced May 2024.

Journal ref: Nature Communications 15, 3989 (2024)

Neural Network Enhanced Single-Photon Fock State Tomography

Authors: Hsien-Yi Hsieh, Yi-Ru Chen, Jingyu Ning, Hsun-Chung Wu, Hua Li Chen, Zi-Hao Shi, Po-Han Wang, Ole Steuernagel, Chien-Ming Wu, Ray-Kuang Lee

Abstract: Even though heralded single-photon sources have been generated routinely through the spontaneous parametric down conversion, vacuum and multiple photon states are unavoidably involved. With machine-learning, we report the experimental implementation of single-photon quantum state tomography by directly estimating target parameters. Compared to the Hanbury Brown and Twiss (HBT) measurements only wi… ▽ More Even though heralded single-photon sources have been generated routinely through the spontaneous parametric down conversion, vacuum and multiple photon states are unavoidably involved. With machine-learning, we report the experimental implementation of single-photon quantum state tomography by directly estimating target parameters. Compared to the Hanbury Brown and Twiss (HBT) measurements only with clicked events recorded, our neural network enhanced quantum state tomography characterizes the photon number distribution for all possible photon number states from the balanced homodyne detectors. By using the histogram-based architecture, a direct parameter estimation on the negativity in Wigner's quasi-probability phase space is demonstrated. Such a fast, robust, and precise quantum state tomography provides us a crucial diagnostic toolbox for the applications with single-photon Fock states and other non-Gaussisan quantum states. △ Less

Submitted 5 May, 2024; originally announced May 2024.

Comments: 8 pages, 8 figures

Variational Optimization for Quantum Problems using Deep Generative Networks

Authors: Lingxia Zhang, Xiaodie Lin, Peidong Wang, Kaiyan Yang, Xiao Zeng, Zhaohui Wei, Zizhu Wang

Abstract: Optimization drives advances in quantum science and machine learning, yet most generative models aim to mimic data rather than to discover optimal answers to challenging problems. Here we present a variational generative optimization network that learns to map simple random inputs into high quality solutions across a variety of quantum tasks. We demonstrate that the network rapidly identifies enta… ▽ More Optimization drives advances in quantum science and machine learning, yet most generative models aim to mimic data rather than to discover optimal answers to challenging problems. Here we present a variational generative optimization network that learns to map simple random inputs into high quality solutions across a variety of quantum tasks. We demonstrate that the network rapidly identifies entangled states exhibiting an optimal advantage in entanglement detection when allowing classical communication, attains the ground state energy of an eighteen spin model without encountering the barren plateau phenomenon that hampers standard hybrid algorithms, and-after a single training run-outputs multiple orthogonal ground states of degenerate quantum models. Because the method is model agnostic, parallelizable and runs on current classical hardware, it can accelerate future variational optimization problems in quantum information, quantum computing and beyond. △ Less

Submitted 16 August, 2025; v1 submitted 27 April, 2024; originally announced April 2024.

Comments: 21 pages. Closer to the published version

Journal ref: Communications Physics 8, 334 (2025)

Multiparameter cascaded quantum interferometer

Authors: Baihong Li, Qi-qi Li, Zhuo-zhuo Wang, Penglong Wang, Changhua Chen, Boxin Yuan, Yiwei Zhai, Xiaofei Zhang

Abstract: We theoretically propose a multiparameter cascaded quantum interferometer in which a two-input and two-output setup is obtained by concatenating 50:50 beam splitters with $n$ independent and adjustable time delays. A general method for deriving the coincidence probability of such an interferometer is given based on the linear transformation of the matrix of beam splitters. As examples, we analyze… ▽ More We theoretically propose a multiparameter cascaded quantum interferometer in which a two-input and two-output setup is obtained by concatenating 50:50 beam splitters with $n$ independent and adjustable time delays. A general method for deriving the coincidence probability of such an interferometer is given based on the linear transformation of the matrix of beam splitters. As examples, we analyze the interference characteristics of one-, two- and three-parameter cascaded quantum interferometers with different frequency correlations and input states. Some typical interferograms of such interferometers are provided to reveal richer and more complicated two-photon interference phenomena. This work offers a general theoretical framework for designing versatile quantum interferometers and provides a convenient method for deriving the coincidence probabilities involved. In principle, arbitrary two-input and two-output experimental setups can be designed with the framework. Potential applications can be found in the complete spectral characterization of two-photon states, multiparameter estimation, and quantum metrology. △ Less

Submitted 15 November, 2024; v1 submitted 11 April, 2024; originally announced April 2024.

Comments: 16 pages, 10 figures. arXiv admin note: text overlap with arXiv:2305.13734

Journal ref: Optics & Laser Technology 181 (2025) 111558

Variational quantum eigensolver with linear depth problem-inspired ansatz for solving portfolio optimization in finance

Authors: Shengbin Wang, Peng Wang, Guihui Li, Shubin Zhao, Dongyi Zhao, Jing Wang, Yuan Fang, Menghan Dou, Yongjian Gu, Yu-Chun Wu, Guo-Ping Guo

Abstract: Great efforts have been dedicated in recent years to explore practical applications for noisy intermediate-scale quantum (NISQ) computers, which is a fundamental and challenging problem in quantum computing. As one of the most promising methods, the variational quantum eigensolver (VQE) has been extensively studied. In this paper, VQE is applied to solve portfolio optimization problems in finance… ▽ More Great efforts have been dedicated in recent years to explore practical applications for noisy intermediate-scale quantum (NISQ) computers, which is a fundamental and challenging problem in quantum computing. As one of the most promising methods, the variational quantum eigensolver (VQE) has been extensively studied. In this paper, VQE is applied to solve portfolio optimization problems in finance by designing two hardware-efficient Dicke state ansatze that reach a maximum of 2n two-qubit gate depth and n^2/4 parameters, with n being the number of qubits used. Both ansatze are partitioning-friendly, allowing for the proposal of a highly scalable quantum/classical hybrid distributed computing (HDC) scheme. Combining simultaneous sampling, problem-specific measurement error mitigation, and fragment reuse techniques, we successfully implement the HDC experiments on the superconducting quantum computer Wu Kong with up to 55 qubits. The simulation and experimental results illustrate that the restricted expressibility of the ansatze, induced by the small number of parameters and limited entanglement, is advantageous for solving classical optimization problems with the cost function of the conditional value-at-risk (CVaR) for the NISQ era and beyond. Furthermore, the HDC scheme shows great potential for achieving quantum advantage in the NISQ era. We hope that the heuristic idea presented in this paper can motivate fruitful investigations in current and future quantum computing paradigms. △ Less

Submitted 7 March, 2024; originally announced March 2024.

Comments: 21 pages, 20 figures

Journal ref: Sci. China Inf. Sci. 68, 180504 (2025)

Optically-Trapped Nanodiamond-Relaxometry Detection of Nanomolar Paramagnetic Spins in Aqueous Environments

Authors: Shiva Iyer, Changyu Yao, Olivia Lazorik, Md Shakil Bin Kashem, Pengyun Wang, Gianna Glenn, Michael Mohs, Yinyao Shi, Michael Mansour, Erik Henriksen, Kater Murch, Shankar Mukherji, Chong Zu

Abstract: Probing electrical and magnetic properties in aqueous environments remains a frontier challenge in nanoscale sensing. Our inability to do so with quantitative accuracy imposes severe limitations, for example, on our understanding of the ionic environments in a diverse array of systems, ranging from novel materials to the living cell. The Nitrogen-Vacancy (NV) center in fluorescent nanodiamonds (FN… ▽ More Probing electrical and magnetic properties in aqueous environments remains a frontier challenge in nanoscale sensing. Our inability to do so with quantitative accuracy imposes severe limitations, for example, on our understanding of the ionic environments in a diverse array of systems, ranging from novel materials to the living cell. The Nitrogen-Vacancy (NV) center in fluorescent nanodiamonds (FNDs) has emerged as a good candidate to sense temperature, pH, and the concentration of paramagnetic species at the nanoscale, but comes with several hurdles such as particle-to-particle variation which render calibrated measurements difficult, and the challenge to tightly confine and precisely position sensors in aqueous environment. To address this, we demonstrate relaxometry with NV centers within optically-trapped FNDs. In a proof of principle experiment, we show that optically-trapped FNDs enable highly reproducible nanomolar sensitivity to the paramagnetic ion, (\mathrm{Gd}^{3+}). We capture the three distinct phases of our experimental data by devising a model analogous to nanoscale Langmuir adsorption combined with spin coherence dynamics. Our work provides a basis for routes to sense free paramagnetic ions and molecules in biologically relevant conditions. △ Less

Submitted 20 November, 2024; v1 submitted 30 January, 2024; originally announced January 2024.

Comments: 7 pages, 3 figures

Journal ref: Phys. Rev. Applied 22, 064076 (2024)

Nuclear scattering via quantum computing

Authors: Peiyan Wang, Weijie Du, Wei Zuo, James P. Vary

Abstract: We propose a hybrid quantum-classical framework to solve the elastic scattering phase shift of two well-bound nuclei in an uncoupled channel. Within this framework, we develop a many-body formalism in which the continuum scattering states of the two colliding nuclei are regulated by a weak external harmonic oscillator potential with varying strength. Based on our formalism, we propose an approach… ▽ More We propose a hybrid quantum-classical framework to solve the elastic scattering phase shift of two well-bound nuclei in an uncoupled channel. Within this framework, we develop a many-body formalism in which the continuum scattering states of the two colliding nuclei are regulated by a weak external harmonic oscillator potential with varying strength. Based on our formalism, we propose an approach to compute the eigenenergies of the low-lying scattering states of the relative motion of the colliding nuclei as a function of the oscillator strength of the confining potential. Utilizing the modified effective range expansion, we extrapolate the elastic scattering phase shift of the colliding nuclei from these eigenenergies to the limit when the external potential vanishes. In our hybrid approach, we leverage the advantage of quantum computing to solve for these eigenenergies from a set of many-nucleon Hamiltonian eigenvalue problems. These eigenenergies are inputs to classical computers to obtain the phase shift. We demonstrate our framework with two simple problems, where we implement the rodeo algorithm to solve the relevant eigenenergies with the IBM Qiskit quantum simulator. The results of both the spectra and the elastic scattering phase shifts agree well with other theoretical results. △ Less

Submitted 15 June, 2024; v1 submitted 30 January, 2024; originally announced January 2024.

Comments: We welcome comments!

Journal ref: Phys.Rev.C 109 6, 064623 (2024)

Low-Loss Polarization-Maintaining Optical Router for Photonic Quantum Information Processing

Authors: Pengfei Wang, Soyoung Baek, Keiichi Edamatsu, Fumihiro Kaneda

Abstract: In photonic quantum applications, optical routers are required to handle single photons with low loss, high speed, and preservation of their quantum states. Single-photon routing with maintained polarization states is particularly important for utilizing them as qubits. Here, we demonstrate a polarization-maintaining electro-optic router compatible with single photons. Our custom electro-optic mod… ▽ More In photonic quantum applications, optical routers are required to handle single photons with low loss, high speed, and preservation of their quantum states. Single-photon routing with maintained polarization states is particularly important for utilizing them as qubits. Here, we demonstrate a polarization-maintaining electro-optic router compatible with single photons. Our custom electro-optic modulator is embedded in a configuration of a Mach-Zehnder interferometer, where each optical component achieves polarization-maintaining operation. We observe the performance of the router with 2-4% loss, 20 dB switching extinction ratio, 2.9 ns rise time, and $>$ 99% polarization process fidelity to an ideal identity operation. △ Less

Submitted 6 April, 2024; v1 submitted 11 January, 2024; originally announced January 2024.

Journal ref: Jpn. J. Appl. Phys. 63 040901 (2024)

Loophole-free test of macroscopic realism via high-order correlations of measurement

Authors: Ping Wang, Chong Chen, Hao Liao, Vadim V. Vorobyov, Joerg Wrachtrup, and Ren-Bao Liu

Abstract: Test of {macroscopic realism} (MR) is key to understanding the foundation of quantum mechanics. Due to the existence of the {non-invasive measurability} loophole and other interpretation loopholes, however, such test remains an open question. Here we propose a general inequality based on high-order correlations of measurements for a loophole-free test of MR at the weak signal limit. Importantly, t… ▽ More Test of {macroscopic realism} (MR) is key to understanding the foundation of quantum mechanics. Due to the existence of the {non-invasive measurability} loophole and other interpretation loopholes, however, such test remains an open question. Here we propose a general inequality based on high-order correlations of measurements for a loophole-free test of MR at the weak signal limit. Importantly, the inequality is established using the statistics of \textit{raw data} recorded by classical devices, without requiring a specific model for the measurement process, so its violation would falsify MR without the interpretation loophole. The non-invasive measurability loophole is also closed, since the weak signal limit can be verified solely by measurement data (using the relative scaling behaviors of different orders of correlations). We demonstrate that the inequality can be broken by a quantum spin model. The inequality proposed here provides an unambiguous test of the MR principle and is also useful to characterizing {quantum coherence}. △ Less

Submitted 15 January, 2024; v1 submitted 10 January, 2024; originally announced January 2024.