arXiv subjects

Wenlin Li

Publications and source records attributed to Wenlin Li.

At least 19 recordsLinked to original sources

arXiv2026

Theoretical analysis towards accurate optomechanical detection of quantum gravity effects

Optomechanical systems offer a promising platform for observing dynamical signatures of quantum gravity through precision measurements of quantum harmonic oscillator dynamics. However, most existing analyses consider only the linear radiation-pressure interaction while neglecting higher-order optomechanical couplings and laser phase noise. These neglected contributions can be comparable in magnitude to the predicted quantum-gravity corrections and may therefore introduce spurious signals or mask the genuine physical effect. Here we reanalyze two experimentally realized platforms, a Fabry-Perot optomechanical system and a membrane-in-the-middle optomechanical system, by incorporating the complete nonlinear dynamics and realistic laser phase noise. Using measured device parameters, we derive revised protocols for generalized uncertainty principle tests and establish practical sensitivity bounds. Our results demonstrate that previous idealized estimates significantly overestimate the achievable resolution, underscoring the necessity of including higher-order interactions and implementing effective laser phase noise suppression in realistic assessments of optomechanical quantum gravity tests.

quant-ph↗

arXiv2026

Quantum master equation approach for the multiphonon up-pumping model

A fully quantum multiphonon up-pumping model is proposed to characterize coherent energy transfer in energetic materials (EMs) subjected to external shock. After eliminating the degrees of freedom of the phonon bath within a mean-field approximation, we derive a quantum master equation governing the energy transfer among vibrational modes. Our analysis reveals that doorway modes of different frequencies undergo distinct levels of effective coherent driving and dissipation, induced by the shocked phonon environment. This not only clarifies the microscopic origin of coherent phonon generation, but also reveals the possibility of modulating such coherent driving and dissipation. Based on numerical simulations of a simplified model using the master equation, we demonstrate how doorway modes extract energy from the phonon environment and subsequently excite higher-frequency molecular vibrational modes. This work offers a renewed perspective for understanding the mechanisms of energy transfer in energetic materials.

quant-ph↗

arXiv2026

A general interpretation of nonlinear connected time crystals: quantum self-sustaining combined with quantum synchronization

Although classical nonlinear dynamics suggests that sufficiently strong nonlinearity can sustain oscillations, quantization of such model typically yields a time-independent steady state that respects time-translation symmetry and thus precludes time-crystal behavior. We identify dephasing as the primary mechanism enforcing this symmetry, which can be suppressed by intercomponent phase correlations. Consequently, a sufficient condition for realizing a continuous time crystal is a nonlinear quantum self-sustaining system exhibiting quantum synchronization among its constituents. As a concrete example, we demonstrate spontaneous oscillations in a synchronized array of van der Pol oscillators, corroborated by both semiclassical dynamics and the quantum Liouville spectrum. These results reduce the identification of time crystals in many-body systems to the evaluation of only two-body correlations and provide a framework for classifying uncorrelated time crystals as trivial.

quant-ph↗

arXiv2026

Fluctuation-induced quenching of chaos in quantum optics

Recent studies have extensively explored chaotic dynamics in quantum optical systems through the mean-field approximation, which corresponds to an ideal, fluctuation-free scenario. However, the inherent sensitivity of chaos to initial conditions implies that even minute fluctuations can be amplified, thereby questioning the applicability of this approximation. Here, we analyze these chaotic effects using stochastic Langevin equations or the Lindblad master equation. For systems operating at frequencies of $10^5$ to $10^7$ Hz, we demonstrate that room-temperature thermal fluctuations are sufficient to suppress chaos at the level of expectation values, even under weak nonlinearity. Furthermore, nonlinearity induces deviations from Gaussian phase-space distributions of the quantum state, revealing attractor-like features in the Wigner function. With increasing nonlinearity, the noise threshold for chaos suppression decreases, approaching the scale of vacuum fluctuations. These results provide a bidirectional validation of the quantum mechanical suppression of chaos.

quant-ph↗

arXiv2025

The detection of Planck-scale physics facilitated by nonlinear quantum optics

A tenet of contemporary physics is that novel physics beyond the Standard Model lurks at a scale related to the Planck length. The development and validation of a unified framework that merges general relativity and quantum physics is contingent upon the observation of Planck-scale physics. Here, we present a fully quantum model for measuring the nonstationary dynamics of a ng-mass mechanical resonator, which will slightly deviate from the predictions of standard quantum mechanics induced by modified commutation relations associated with quantum gravity effects at low-energy scalar. The deformed commutator is quantified by the oscillation frequency deviation, which is amplified by the nonlinear mechanism of the detection field. The measurement resolution is optimized to a precision level that is $15$ orders of magnitude below the electroweak scale.

quant-ph↗

arXiv2025

Probing minimal observable length with dark modes in an optomechanical detector

Several theories that attempt to unify quantum theory and gravitational theory assume that space has an observable limiting resolution related to the Planck length, denoted by $\sqrt{\beta_0}L_p$. Quantum mechanically, this concept derives a generalized uncertainty principle (GUP) and the corresponding modified commutator. The prediction and observation of GUP-induced new physics, as well as the quantitative measurement of the value of $\beta_0$, may provide substantial support for the establishment of quantum gravity theory. In this paper, we propose a comprehensive quantum framework for measuring GUP at low energy scales by utilizing the interference-induced bright-dark mode effect of oscillators in an optomechanical system. The nonlinearity induced by GUP will be amplified by the bright mode dynamics, and then be quantitatively read out by the noise spectrum of the dark mode. The measurement limit resolution of the scheme is not constrained by the quality factor of the oscillator. Under experimentally achievable parameters, the measurement resolution has been shown to reach $\beta_{\text{NL,lim}}=10^{-16.75}$, which is $10$ orders of magnitude lower than the electroweak level.

quant-ph↗

arXiv2025

Building Safer Sites: A Large-Scale Multi-Level Dataset for Construction Safety Research

Construction safety research is a critical field in civil engineering, aiming to mitigate risks and prevent injuries through the analysis of site conditions and human factors. However, the limited volume and lack of diversity in existing construction safety datasets pose significant challenges to conducting in-depth analyses. To address this research gap, this paper introduces the Construction Safety Dataset (CSDataset), a well-organized comprehensive multi-level dataset that encompasses incidents, inspections, and violations recorded sourced from the Occupational Safety and Health Administration (OSHA). This dataset uniquely integrates structured attributes with unstructured narratives, facilitating a wide range of approaches driven by machine learning and large language models. We also conduct a preliminary approach benchmarking and various cross-level analyses using our dataset, offering insights to inform and enhance future efforts in construction safety. For example, we found that complaint-driven inspections were associated with a 17.3% reduction in the likelihood of subsequent incidents. Our dataset and code are released at https://github.com/zhenhuiou/Construction-Safety-Dataset-CSDataset.

cs.LG↗

arXiv2025

High-precision laser spectrum analyzer via digital decoherence

With the continuous advancement of laser technology, accurately evaluating the noise spectrum of high-performance lasers has become increasingly challenging. In this work, we demonstrate a high-precision laser spectrum analyzer based on the proposed digital decoherence method, which can precisely measure the frequency noise spectrum of sub-Hz linewidth lasers. In addition, it has broad wavelength compatibility, which enables convenient switching between lasers with different center wavelengths. Its performance is validated through measurements of ultra-stable lasers. Based on the measured frequency noise power spectral density, a beta-line linewidth is determined to be 570 mHz at 10-second observation time, and the minimum observable linewidth is calculated to be 133 mHz. The system's noise floor is evaluated to be 210 mHz beta-line linewidth at 25-second observation time, and a minimum observable linewidth of 39 mHz.

physics.optics↗

arXiv2025

Full dynamics of two-membrane cavity optomechanics

In a two-membrane cavity optomechanical setup, two semi-transparent membranes placed within an optical Fabry-P\'erot cavity yield a nontrivial dependence of the frequency of a mode of the optical cavity on the membranes' positions, which is due to interference. However, the system dynamics is typically described by a radiation pressure force treatment in which the frequency shift is expanded stopping at first order in the membrane displacements. In this paper, we study the full dynamics of the system obtained by considering the exact nonlinear dependence of the optomechanical interaction between two membranes' vibrational modes and the driven cavity mode. We then compare this dynamics with the standard treatment based on the Hamiltonian linear interaction, and we find the conditions under which the two dynamics may significantly depart from each other. In particular, we see that a parameter regime exists in which the customary first-order treatment provides distinct and incorrect predictions for the synchronization of two self-sustained mechanical limit-cycles, and for Gaussian entanglement of the two membranes in the case of two-tone driving.

quant-ph↗

arXiv2025

Large amplitude mechanical coherent states and detection of weak nonlinearities in cavity optomechanics

The generation of large-amplitude coherent states of a massive mechanical resonator, and their quantum-limited detection represent useful tools for quantum sensing and for testing fundamental physics theories. In fact, any weak perturbation may affect the coherent quantum evolution of the prepared state, providing a sensitive probe for such a perturbation. Here we consider a cavity optomechanical setup and the case of the detection of a weak mechanical nonlinearity. We consider different strategies, first focusing on the stationary dynamics in the presence of multiple tones driving the system, and then focusing on non-equilibrium dynamical strategies. These methods can be successfully applied for measuring Duffing-like material nonlinearities, or effective nonlinear corrections associated with quantum gravity theories.

quant-ph↗

arXiv2025

Hybrid Fiber-Based Radio Frequency Distribution and Vibration Detection System Tailored for Large Radio Arrays

Radio telescope arrays, such as Square Kilometre Array (SKA) and next-generation Very Large Array (ngVLA), require highly precise synchronization of time-frequency references to ensure high-quality observational data. Fiber-based frequency distribution systems are highly effective. However, their proper functioning can be threatened by risk events. In this paper, we propose a hybrid fiber-based frequency-distribution and vibration detection system tailored for large radio arrays. The system ensures the performance of distributed frequency signals while allowing for the monitoring of potential threats to the optical fiber network. We design and implement a single-to-multiple hybrid system, conducting tests via a 55-km fiber link. Experimental results demonstrate its effectiveness, achieving the relative frequency stability of 3E-14/1 s and 2.7E-17/1E5 s, along with vibration detection and localization capabilities.

astro-ph.IM↗

arXiv2024

MEATRD: Multimodal Anomalous Tissue Region Detection Enhanced with Spatial Transcriptomics

The detection of anomalous tissue regions (ATRs) within affected tissues is crucial in clinical diagnosis and pathological studies. Conventional automated ATR detection methods, primarily based on histology images alone, falter in cases where ATRs and normal tissues have subtle visual differences. The recent spatial transcriptomics (ST) technology profiles gene expressions across tissue regions, offering a molecular perspective for detecting ATRs. However, there is a dearth of ATR detection methods that effectively harness complementary information from both histology images and ST. To address this gap, we propose MEATRD, a novel ATR detection method that integrates histology image and ST data. MEATRD is trained to reconstruct image patches and gene expression profiles of normal tissue spots (inliers) from their multimodal embeddings, followed by learning a one-class classification AD model based on latent multimodal reconstruction errors. This strategy harmonizes the strengths of reconstruction-based and one-class classification approaches. At the heart of MEATRD is an innovative masked graph dual-attention transformer (MGDAT) network, which not only facilitates cross-modality and cross-node information sharing but also addresses the model over-generalization issue commonly seen in reconstruction-based AD methods. Additionally, we demonstrate that modality-specific, task-relevant information is collated and condensed in multimodal bottleneck encoding generated in MGDAT, marking the first theoretical analysis of the informational properties of multimodal bottleneck encoding. Extensive evaluations across eight real ST datasets reveal MEATRD's superior performance in ATR detection, surpassing various state-of-the-art AD methods. Remarkably, MEATRD also proves adept at discerning ATRs that only show slight visual deviations from normal tissues.

cs.CV↗

arXiv2024

Quantum synchronization in an all-optical stroboscopic quantum simulator

In this work, we propose an all-optical stroboscopic scheme to simulate an open quantum system. By incorporating the tritter, consisting of a group of beam splitters, we find the emergence of spontaneous anti-phase synchronization in the steady state. To better understand the synchronization and entanglement properties within the system, we utilize the relative error measure and find the distribution of logarithmic negativity in parameter space shows similar structures with the results of synchronization measure. Finally, we derive the adjoint master equation corresponding to the system when the synchronization condition is satisfied and explain the existence of oscillations. In addition, we explore the effect of non-Markovianity on synchronization, and we find that it only slows down the time for the system to reach the steady state but does not change the synchronization properties of the steady state. Our work provides a promising scheme for experimental studies focused on synchronization and other nonequilibrium steady states.

quant-ph↗

arXiv2024

Cycle Pixel Difference Network for Crisp Edge Detection

Edge detection, as a fundamental task in computer vision, has garnered increasing attention. The advent of deep learning has significantly advanced this field. However, recent deep learning-based methods generally face two significant issues: 1) reliance on large-scale pre-trained weights, and 2) generation of thick edges. We construct a U-shape encoder-decoder model named CPD-Net that successfully addresses these two issues simultaneously. In response to issue 1), we propose a novel cycle pixel difference convolution (CPDC), which effectively integrates edge prior knowledge with modern convolution operations, consequently successfully eliminating the dependence on large-scale pre-trained weights. As for issue 2), we construct a multi-scale information enhancement module (MSEM) and a dual residual connection-based (DRC) decoder to enhance the edge location ability of the model, thereby generating crisp and clean contour maps. Comprehensive experiments conducted on four standard benchmarks demonstrate that our method achieves competitive performance on the BSDS500 dataset (ODS=0.813 and AC=0.352), NYUD-V2 (ODS=0.760 and AC=0.223), BIPED dataset (ODS=0.898 and AC=0.426), and CID (ODS=0.59). Our approach provides a novel perspective for addressing these challenges in edge detection.

cs.CV↗

arXiv2024

Dual Advancement of Representation Learning and Clustering for Sparse and Noisy Images

Sparse and noisy images (SNIs), like those in spatial gene expression data, pose significant challenges for effective representation learning and clustering, which are essential for thorough data analysis and interpretation. In response to these challenges, we propose Dual Advancement of Representation Learning and Clustering (DARLC), an innovative framework that leverages contrastive learning to enhance the representations derived from masked image modeling. Simultaneously, DARLC integrates cluster assignments in a cohesive, end-to-end approach. This integrated clustering strategy addresses the "class collision problem" inherent in contrastive learning, thus improving the quality of the resulting representations. To generate more plausible positive views for contrastive learning, we employ a graph attention network-based technique that produces denoised images as augmented data. As such, our framework offers a comprehensive approach that improves the learning of representations by enhancing their local perceptibility, distinctiveness, and the understanding of relational semantics. Furthermore, we utilize a Student's t mixture model to achieve more robust and adaptable clustering of SNIs. Extensive experiments, conducted across 12 different types of datasets consisting of SNIs, demonstrate that DARLC surpasses the state-of-the-art methods in both image clustering and generating image representations that accurately capture gene interactions. Code is available at https://github.com/zipging/DARLC.

cs.CV↗

arXiv2024

Learning to utilize image second-order derivative information for crisp edge detection

Edge detection is a fundamental task in computer vision. It has made great progress under the development of deep convolutional neural networks (DCNNs), some of which have achieved a beyond human-level performance. However, recent top-performing edge detection methods tend to generate thick and noisy edge lines. In this work, we solve this problem from two aspects: (1) the lack of prior knowledge regarding image edges, and (2) the issue of imbalanced pixel distribution. We propose a second-order derivative-based multi-scale contextual enhancement module (SDMCM) to help the model locate true edge pixels accurately by introducing the edge prior knowledge. We also construct a hybrid focal loss function (HFL) to alleviate the imbalanced distribution issue. In addition, we employ the conditionally parameterized convolution (CondConv) to develop a novel boundary refinement module (BRM), which can further refine the final output edge maps. In the end, we propose a U-shape network named LUS-Net which is based on the SDMCM and BRM for crisp edge detection. We perform extensive experiments on three standard benchmarks, and the experiment results illustrate that our method can predict crisp and clean edge maps and achieves state-of-the-art performance on the BSDS500 dataset (ODS=0.829), NYUD-V2 dataset (ODS=0.768), and BIPED dataset (ODS=0.903).

cs.CV↗

arXiv2024

A Tampering Risk of Fiber-Based Frequency Synchronization Networks and Its Countermeasures

Fiber optic networks are used worldwide and have been regarded as excellent media for transmitting time-frequency (TF) signals. In the past decades, fiber-based TF synchronization techniques have been extensively studied. Instruments based on these techniques have been successfully applied. With the increasing application of TF synchronization instruments, their security has become an important issue. Unfortunately, the security risks of fiber-based frequency synchronization (FbFS) instruments have been overlooked. This paper proposes a frequency tampering method called "frequency lens". On a 200 km fiber link, we demonstrate a frequency tampering scenario using a frequency lens-enabled frequency tampering module (FTM). On the user side, the frequency value of the recovered 100 MHz signal can be stealthily altered within a range of 100 MHz-100 Hz to 100 MHz+100 Hz, while the frequency dissemination stability of the system remains normal. Related to this tampering risk, potential hazards in three different application scenarios, which rely on precise frequency references, are analyzed. Two countermeasures are also proposed to solve this tampering risk.

physics.ins-det↗

arXiv2023

Optimized sideband cooling with initial system correlations in non-Markovian regime

An optimized sideband cooling in the presence of initial system correlations is investigated for a standard optomechanical system coupled to a general mechanical non-Markovian reservoir. We study the evolution of phonon number by incorporating the effects of initial correlations into the time-dependent coefficients in the Heisenberg equation. We introduce the concept of cooling rate and define an average phonon reduction function to describe the sideband cooling effect in non-Markovian regime. Our results show that the instantaneous phonon number can be significantly reduced by introducing either the parametric-amplification type or the beam-splitter type initial correlations. In addition, the ground state cooling rate can be accelerated by enhancing the initial correlation of beam-splitter type. By optimizing the initial state of the system and utilizing Q-modulation technology, a stable mechanical ground state can be obtained in a very short time. Our optimized cooling protocol provides an appealing platform for phonon manipulation and quantum information processing in solid-state systems.

quant-ph↗