arXiv subjects

Jingzheng Huang

Publications and source records attributed to Jingzheng Huang.

At least 19 recordsLinked to original sources

arXiv2026

High-Resolution Sensing via Quantum States Discrimination

High-resolution sensing plays a significant role in scientific research and industrial production, but the practical implementation is constrained by the physical mechanisms of the sensors. To address the critical limitation, we propose a high-resolution sensing approach based on quantum state discrimination. Distinct from conventional strategies, the proposed approach constructs measurement operators in the orthogonal complement space rather than eigenspace of the eigenstate, thereby notably improving the discriminability among quantum states. Moreover, the experimental results via an optical microcavity demonstrate a potential sensing resolution of 4 $\times$ 10\textsuperscript{-6} \degree C and 18 p$ε$ respectively for temperature and strain, and further verify the feasibility of simultaneous sensing of the two parameters. This work establishs a universal approach for high-resolution sensing, and may be extended to different sensing platforms across various application scenarios.

physics.optics↗

arXiv2026

Simultaneous Heisenberg-Limited Multiparameter Metrology via Indefinite Evolution

Quantum metrology achieves Heisenberg-limited precision in single-parameter estimation, but its multiparameter extension is fundamentally constrained by both parameter-encoding and measurement incompatibility. Noncommuting signal generators may cause incompatible parameter-encoding, preventing the quantum Fisher information matrix from simultaneously achieving the Heisenberg scale for all parameters. Due to incompatible optimal measurements, the classical Fisher information matrix represents the practical attainable precision. Here, we introduce a multiparameter metrology framework based on indefinite evolution (IE), in which different control operations and signal reversal are placed in a coherent superposition. For a single-qubit probe with mutually orthogonal signal generators, IE enables compatible parameter encoding and optimal measurement without the signal reversal. For parallel generators, where only signal reversal realized by its generator is available, IE can achieve the same performance. We further extend this mechanism to noisy, many-body, and high-dimensional probes, and establish general conditions for achieving the simultaneous Heisenberg-limit. In contrast, definite evolution cannot achieve the same performance under compatible optimal measurements, even when signal reversal is available. Our results identify IE as an operational resource for overcoming multiparameter incompatibility and open a route toward attainable Heisenberg-limited sensing in interferometric platforms.

quant-ph↗

arXiv2026

Preserving Heisenberg-Limited Metrological Information during Storage via Correlated-Noise Correction

Quantum error correction has become an indispensable tool for restoring Heisenberg-limited precision in noisy quantum metrology. Existing protocols, however, almost exclusively focus on correcting noise during the signal-encoding stage and implicitly assume that the probe is measured immediately after sensing. In many quantum information processing tasks, the encoded probe must instead be stored before subsequent quantum operations, during which environmental noise can significantly degrade the accumulated metrological information. Here, we propose a correlated-noise correction (CNC) protocol for protecting quantum probes during the storage stage. By correlating probe errors with auxiliary qubits through fixed two-body entangling gates, memory errors are converted into measurable syndromes that are extracted only once after storage. We show that the protocol naturally extends from single-qubit to multi-qubit probes and protects the stored quantum Fisher information against dephasing, bit-flip, and amplitude-damping noise. Furthermore, we demonstrate that preserving the quantum Fisher information does not necessarily require restoring the entire quantum state when the probe is measured immediately after storage, whereas full state recovery becomes essential for subsequent rounds of quantum signal processing. Our results establish correlated-noise correction as a practical framework for protecting metrological information during quantum memory and provide a useful building block for sensing-enabled quantum information processing.

quant-ph↗

arXiv2026

Converting Quantum Sensing Noise into Erasures

Erasures are more favorable for quantum sensing than unflagged errors such as Pauli errors. However, realistic sensing noise does not usually appear as erasures; it often acts within the same sensing Hilbert space as the signal, making it difficult to identify and mitigate. For such noise, we establish a noise-model-agnostic necessary and sufficient condition for erasure conversion, identifying the noise components that can be converted into erasures and removed without damaging the signal. For components satisfying the condition, conversion can be realized by a passive dimension-lifted scheme requiring neither detailed noise knowledge nor active control. Theoretically, the protocol remains effective over a broad range of noise strengths and approaches the corresponding precision limit. Experimentally, in single-photon phase sensing, we recover standard-quantum-limit precision in a Pauli-noise channel with erasure-convertible weight 0.5, using orbital angular momentum as the ancilla. These results provide a practical route to robust quantum sensing under realistic noise.

quant-ph↗

arXiv2026

Scaling Enhancement in Quantum Metrology via Indefinite-Time-Direction Encoding

The precision limit in quantum metrology, quantified by the root-mean-square error of parameter estimation, is conventionally expected to improve at most linearly with the total interrogation time T and with the number N of queried quantum gates. Although several metrological schemes have been shown to achieve precision scaling faster than linear in T and N, they typically rely on unbounded probe-side information resources, usually qualified by an increasingly large variance of the parameter generator. This requirement complicates the interpretation of the resulting scaling advantage and poses substantial technical challenges. In this work, we employ an indefinite-time-direction encoding process to achieve a nonlinear-scaling enhancement of the precision limit. Rather than relying on increasingly informative probe states, our method converts controllable noncommuting encoding operations into metrological gain. Experimentally, we implement this protocol for angular-rotation measurement in a quantum optical system and demonstrate a nonlinear-scaling improvement in practical precision without using probe-side information resources. These results establish a practical framework for surpassing conventional linear-scaling precision limits in quantum metrology and provide new insights into precision enhancement in realistic quantum metrological and sensing applications.

quant-ph↗

arXiv2026

Scaling Enhancement in Distributed Quantum Sensing via Bidirectional Causal Routing

Sensing networks underpin applications ranging from fundamental physics to real-world engineering. Distributed quantum sensing (DQS) can improve measurement performance, but existing protocols typically require multipartite entanglement, which poses substantial challenges for scalable implementation. Here, we introduce a DQS protocol based on bidirectional causal routing in a cyclic network, where a single probe sequentially interrogates M independent sensors along two opposite causal routes. By exploiting the noncommutativity between inter-sensor propagation and local sensing operations, the protocol turns propagation from a passive transport process into a source of sensing information, yielding an asymptotic 1/M^2 scaling of the estimation precision without multipartite entanglement. We experimentally demonstrate the protocol for distributed beam-tilt sensing in a free-space quantum optical network comprising up to 9 sensors, achieving picoradian-level precision in estimating the average tilt angle. These results identify propagation dynamics and routing geometry as active metrological resources for scalable distributed quantum sensing.

quant-ph↗

arXiv2026

Incorporating rank-free coupling and external field via an incoherent modulated spatial photonic Ising machine

Spatial photonic Ising machines offer a novel optical platform for optimization and spin-model simulation, but existing diffraction-based schemes rely on auxiliary spins or multiplexing to encode high-rank couplings and external fields, reducing either speed or spin count. We demonstrate an amplitude-only, rank-free spatial photonic Ising machine in which arbitrary Ising Hamiltonians are encoded as Hadamard products on aligned amplitude and binary spatial modulators and read out by a single-pixel intensity measurement. The machine directly programs fully connected 797-spin Ising models with external fields at nearly 9-bit precision and operates at a constant iteration rate of ~200 Hz. By removing zero-valued product terms, the same architecture scales to sparse problems and experimentally solves a Max-Cut instance on a 424,108-vertex Mobius ladder graph. We also observe the phase transition of the Sherrington-Kirkpatrick model, demonstrating programmable optical simulation beyond low-rank couplings. These results establish amplitude modulation as a scalable route to programmable photonic Ising machines.

physics.optics↗

arXiv2026

Noise-resilient nanophotonic gyroscope with sub-prad phase resolution

Optical gyroscopes based on the Sagnac effect are the cornerstone of precision orientation and navigation. However, their bulky form factors prevent deployment in emerging mobile and autonomous systems. On nanophotonic platforms, the Sagnac signal plummets under aggressive miniaturization. Consequently, the signal is easily swamped by refractive-index fluctuations, rendering navigation-grade sensitivity within just a few square millimeters a notoriously elusive goal. Here, we demonstrate a noise-resilient nanophotonic optical gyroscope by exploiting a two-chain decoupling architecture to effectively isolate the rotation signal from channel noise. Implemented on a 3 mm^2 passive silicon nitride chip, the proof-of-concept device achieves a bias instability of 1.42 deg/h and an angle random walk of 0.001 deg/\sqrt{h}, representing improvements of 4 and 6 orders of magnitude, respectively, over the representative nanophotonic gyroscope of similar footprint (ref. 27). In the broader context of integrated optical gyroscopes, our approach bridges the long-standing size-performance gap by two to three orders of magnitude, moving chip-scale devices into a previously inaccessible regime and pointing toward navigation-relevant precision for monolithic microsystems. This architecture further enables sub-prad phase resolution with general applicability, establishing a foundational framework for the next generation of robust, monolithically integrated photonic sensing systems.

physics.optics↗

arXiv2026

Fault-Tolerant Information Processing with Quantum Weak Measurement

Noise is an important factor that influences the reliability of information acquisition, transmission, processing, and storage. In order to suppress the inevitable noise effects, a fault-tolerant information processing approach via quantum weak measurement is proposed, where pairwise orthogonal postselected measurement bases with various tiny angles and optimal compositions of measured results are chosen as a decoding rule. The signal to be protected can be retrieved with a minimal distortion after having been transmitted through a noisy channel. Demonstrated by typical examples of encoding signal on two-level superposition state or Einstein-Podolsky-Rossen state transmitted through random telegraph noise and decoherence noises channel, the mean squared error distortion may be close to $0$ and the fault-tolerant capability could reach $1$ with finite quantum resources. To verify the availability of the proposed approach, classic coherent light and quantum coherent state are used for encoding information in the experiment. Potentially, the proposed approach may provide a solution for suppressing noise effects in long-distance quantum communication, high-sensitivity quantum sensing, and accurate quantum computation.

quant-ph↗

arXiv2026

Sensing Low-Frequency Field with Rydberg Atoms via Quantum Weak Measurement

Recently, Rydberg atom has emerged as an attractive choice to realize quantum sensing of low-frequency electric field. The progress so far has mostly utilized the intensity and phase changes in probe laser and the corresponding detection mechanism still remains classical. Nevertheless, external field acting on the Rydberg state can induce the polarization variation of probe laser in the Rydberg electromagnetically induced transparency (EIT) system embedded in realistic multi-state atoms. We experimentally observe this phenomenon and realize signal extraction by appropriately utilizing the polarization degrees of freedom. Based on such a mechanism, we further design and implement a quantum weak measurement scheme, which clearly suppresses the technical noise and leads to considerable improvement of performance. Evaluation of the sensitivities across different post-selection angles demonstrates that the weak measurement results agree well with the theoretical model predictions. The advantages of our method are analyzed from multiple aspects, including characterizing the responses over different frequencies and comparing the responses of the weak measurement scheme and the traditional transmission-based method. After accounting for the screening effect of a measured ratio 17\% where the $^\text{87}$Rb atoms experience a substantially reduced field inside the glass cell, the performance reaches 33 $μ\text{V}~\text{cm}^\text{-1}~\text{Hz}^\text{-1/2}$ in sensitivity and 1.0 $μ\text{V/cm}$ in minimal detectable field for an integration time of 1000 s, as perceived by the atoms.

physics.atom-ph↗

arXiv2025

Learning to Restore Heisenberg Limit in Noisy Quantum Sensing via Quantum Digital Twin

Quantum sensors leverage nonclassical resources to achieve sensing precision at the Heisenberg limit, surpassing the standard quantum limit attainable through classical strategies. However, a critical issue is that the environmental noise induces rapid decoherence, fundamentally limiting the realizability of the Heisenberg limit. In this Letter, we propose a quantum digital twin protocol to overcome this issue. The protocol first establishes observable-constrained state reconstruction to infer random errors in the decoherence process, and then utilizes reinforcement learning to derive adaptive compensatory control strategies. Demonstrated across discrete, continuous variable and multi-qubit circuit systems, our approach bypasses quantum state tomography's exponential overhead and discovers optimal control schemes to restore the Heisenberg limit. Unlike quantum error correction or mitigation schemes requiring precise noise characterization and ancillary qubits, our autonomous protocol achieves noise-resilient sensing through environment-adaptive control sequencing. This work establishes quantum digital twin as a generic methodology for quantum control, proposing a noise-immune paradigm for next-generation quantum sensors compatible with NISQ-era experimental constraints.

quant-ph↗

arXiv2025

Real-time imaging through dynamic scattering media enabled by fixed optical modulations

Dynamic scattering remains a significant challenge to the practical deployment of anti-scattering imaging. Existing methods, such as transmission matrix measurements, iterative wavefront shaping, and optical phase conjugation, depend on a quasi-static assumption, requiring the object and scattering medium to remain stable during a single imaging process to enable one-to-one compensation. However, image reconstruction becomes unattainable when this assumption is violated. Here, we propose a novel imaging strategy that counteracts time-dependent scattering perturbations through a fixed modulation module. This one-to-many compensation mechanism is realized via optical diffraction neural networks (ODNNs) trained on simulated datasets. For the first time, we reveal that its feasibility stems from the optical shower-curtain effect, and its effectiveness typically within 1-2 transport mean free paths. Our approach is not only immune to speckle decorrelation but also leverages it to enhance image quality. ODNNs generalize effectively to real-world scattering medium scenarios via multi-simulated scattering media learning and reconstruct images in real time with light-speed processing. We achieve 80 Hz imaging of moving objects in dynamic scattering media with decorrelation times < 1 ms, demonstrating applicability in large-field-of-view imaging and incoherent illumination scenarios. This work lays the foundation for high-speed, intelligent optical imaging, advancing practical anti-dynamic scattering techniques.

physics.optics↗

arXiv2025

High-sensitivity Optical Microcavity Acoustic Sensor Covering Free Spectral Range

Optical whispering gallery mode microcavity acoustic sensors have emerged significant potential in high-sensitivity acoustic signal detection, but the narrow dynamic range limits the application prospect. To address the challenge, we propose and experimentally demonstrate a high-sensitivity acoustic sensor in optical whispering gallery mode microcavity. The proposed sensor integrates an extended Mach-Zehnder polarization interferometer with postselection, extending the dynamic range to the free spectral range. The sensing regions can be categorized into phase-drastic and phase-enhanced regions, both of which yield an optimal acoustic response that surpasses traditional transmission method. Experiment results demonstrate improvements of 57.87 dB in detection sensitivity and 26 times in minimal detectable acoustic pressure over the transmission method. Moreover, the application of coherent state and heterodyne detection can enhance response amplitude, further improving the detection sensitivity. Given the wide application range for acoustic dispersion and dissipation response, as well as the performance advantages of high sensitivity and wide dynamic range, the proposed WGM sensor offers a promising solution for acoustic sensing. Potentially, the structural design may be adaptable to other application scenarios involving time-varying signals through optical microcavity sensing.

physics.optics↗

arXiv2025

Towards Heisenberg limit without critical slowing down via quantum reinforcement learning

Critical ground states of quantum many-body systems have emerged as vital resources for quantum-enhanced sensing. Traditional methods to prepare these states often rely on adiabatic evolution, which may diminish the quantum sensing advantage. In this work, we propose a quantum reinforcement learning (QRL)-enhanced critical sensing protocol for quantum many-body systems with exotic phase diagrams. Starting from product states and utilizing QRL-discovered gate sequences, we explore sensing accuracy in the presence of unknown external magnetic fields, covering both local and global regimes. Our results demonstrate that QRL-learned sequences reach the finite quantum speed limit and generalize effectively across systems of arbitrary size, ensuring accuracy regardless of preparation time. This method can robustly achieve Heisenberg and super-Heisenberg limits, even in noisy environments with practical Pauli measurements. Our study highlights the efficacy of QRL in enabling precise quantum state preparation, thereby advancing scalable, high-accuracy quantum critical sensing.

quant-ph↗

arXiv2025

Quantum neural compressive sensing for ghost imaging

Demonstrating the utility of quantum algorithms is a long-standing challenge, where quantum machine learning becomes one of the most promising candidate that can be resorted to. In this study, we investigate a quantum neural compressive sensing algorithm for ghost imaging to showcase its utility. The algorithm utilizes the variational quantum circuits to reparameterize the inverse problem of ghost imaging and uses the inductive bias of the physical forward model to perform optimization. To validate the algorithm's effectiveness, we conduct optical ghost imaging experiments, capturing signals from objects at different physical sampling rates and detection signal-to-noise ratios. The experimental results show that our proposed algorithm surpasses conventional methods in both visual appearance and quantitative metrics, achieving state-of-the-art performance. Importantly, we observe that the quantum neural network, guided by prior knowledge of physics, effectively overcomes the challenge of barren plateau in the optimization process. The proposed algorithm demonstrates robustness against various quantum noise levels, making it suitable for near-term quantum devices. Our study leverages physical inductive bias guided variational quantum algorithm, underscoring the potential of quantum computation in tackling a broad range of optimization and inverse problems.

quant-ph↗

arXiv2024

Nanoradian-Scale Precision in Light Rotation Measurement via Indefinite Quantum Dynamics

The manipulation and metrology of light beams are pivotal for optical science and applications. In particular, achieving ultra-high precision in the measurement of light beam rotations has been a long-standing challenge. Instead of utilizing quantum probes like entangled photons, we address this challenge by incorporating a quantum strategy called "indefinite time direction" into the parameterizing process of quantum parameter estimation. Leveraging this quantum property of the parameterizing dynamics allows us to maximize the utilization of OAM resources for measuring ultra-small angular rotations of beam profile. Notably, a nanoradian-scale precision of light rotation measurement is finally achieved in the experiment, which is the highest precision by far to our best knowledge. Furthermore, this scheme holds promise in various optical applications due to the diverse range of manipulable resources offered by photons.

quant-ph↗

arXiv2023

Toward Incompatible Quantum Limits on Multiparameter Estimation

Achieving the ultimate precisions for multiple parameters simultaneously is an outstanding challenge in quantum physics, because the optimal measurements for incompatible parameters cannot be performed jointly due to the Heisenberg uncertainty principle. In this work, a criterion proposed for multiparameter estimation provides a possible way to beat this curse. According to this criterion, it is possible to mitigate the influence of incompatibility meanwhile improve the ultimate precisions by increasing the variances of the parameter generators simultaneously. For demonstration, a scheme involving high-order Hermite-Gaussian states as probes is proposed for estimating the spatial displacement and angular tilt of light at the same time, and precisions up to 1.45 nm and 4.08 nrad are achieved in experiment simultaneously. Consequently, our findings provide a deeper insight into the role of Heisenberg uncertainty principle in multiparameter estimation, and contribute in several ways to the applications of quantum metrology.

quant-ph↗

arXiv2023

High Precision Multi-parameter Weak Measurement with Hermite-Gaussian Pointer

The weak value amplification technique has been proved useful for precision metrology in both theory and experiment. To explore the ultimate performance of weak value amplification for multi-parameter estimation, we investigate a general weak measurement formalism with assistance of high-order Hermite-Gaussian pointer and quantum Fisher information matrix. Theoretical analysis shows that the ultimate precision of our scheme is improved by a factor of square root of 2n+1, where n is the order of Hermite-Gaussian mode. Moreover, the parameters' estimation precision can approach the precision limit with maximum likelihood estimation method and homodyne method. We have also given a proof-of-principle experimental setup to validate the H-G pointer theory and explore its potential applications in precision metrology.

quant-ph↗