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Researcher profile

Qing Lin

Qing Lin contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
hep-exphysics.ins-detComputer Visioneess.IVhep-phastro-ph.HEastro-ph.SRmath.DSnlin.PSphysics.opticsquant-ph

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Published work

17 published item(s)

preprint2026arXiv

GPS-Synchronized Monitoring of Core-collapse Supernova Bursts with PandaX-4T via Coherent Elastic Neutrino Nuclear Scattering

The landmark detection of neutrinos from SN1987A marked the dawn of neutrino astrophysics. The neutrino burst provided essential insights into fundamental properties of neutrinos, and served as key probes of stellar evolution and supernova dynamics. The recent advancement in coherent elastic neutrino-nucleus scattering enables the detection of core-collapse supernova burst neutrinos using tonne-scale liquid xenon detectors originally designed for dark matter direct detection. Leveraging this capability, we developed and deployed an online supernova monitoring system for the PandaX-4T experiment. This system features a GPS module with millisecond-level timing precision, a low false-alarm rate, and high sensitivity to galactic core-collapse supernova explosion events. The methodology is robust, directly scalable, and planned for implementation in the next-generation PandaX-20T experiment.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Learning to Perceive "Where": Spatial Pretext Tasks for Robust Self-Supervised Learning

Existing self-supervised learning (SSL) methods primarily learn object-invariant representations but often neglect the spatial structure and relationships among object parts. To address this limitation, we introduce Spatial Prediction (SP), a spatially aware pretext regression task that predicts the relative position and scale between a pair of disentangled local views from the same image. By modeling part-to-part relationships in a continuous geometric space, SP encourages representations to capture fine-grained spatial dependencies beyond invariant categorical semantics, thereby learning the compositional structure of visual scenes. SP is implemented as a decoupled plug-in and can be seamlessly integrated into diverse SSL frameworks. Extensive experiments show consistent improvements across image recognition, fine-grained classification, semantic segmentation, and depth estimation, as well as substantial gains in out-of-distribution robustness for object recognition. To evaluate spatial reasoning, we introduce (1) a position and scale prediction task on image patch pairs and (2) a jigsaw understanding task requiring patch reordering and recognition after reconstruction. Strong performance on these tasks indicates improved spatial structure and geometric awareness. Overall, explicitly modeling spatial information provides an effective inductive bias for SSL, leading to more structured representations and better generalization. Code and models will be released.

0 citations0 reviewsNo code linkedOpen access
preprint2025arXiv

Highly Undersampled MRI Reconstruction via a Single Posterior Sampling of Diffusion Models

Incoherent k-space undersampling and deep learning-based reconstruction methods have shown great success in accelerating MRI. However, the performance of most previous methods will degrade dramatically under high acceleration factors, e.g., 8$\times$ or higher. Recently, denoising diffusion models (DM) have demonstrated promising results in solving this issue; however, one major drawback of the DM methods is the long inference time due to a dramatic number of iterative reverse posterior sampling steps. In this work, a Single Step Diffusion Model-based reconstruction framework, namely SSDM-MRI, is proposed for restoring MRI images from highly undersampled k-space. The proposed method achieves one-step reconstruction by first training a conditional DM and then iteratively distilling this model four times using an iterative selective distillation algorithm, which works synergistically with a shortcut reverse sampling strategy for model inference. Comprehensive experiments were carried out on both publicly available fastMRI brain and knee images, as well as an in-house multi-echo GRE (QSM) subject. Overall, the results showed that SSDM-MRI outperformed other methods in terms of numerical metrics (e.g., PSNR and SSIM), error maps, image fine details, and latent susceptibility information hidden in MRI phase images. In addition, the reconstruction time for a 320$\times$320 brain slice of SSDM-MRI is only 0.45 second, which is only comparable to that of a simple U-net, making it a highly effective solution for MRI reconstruction tasks.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

A First Search for Solar $^8$B Neutrino in the PandaX-4T Experiment using Neutrino-Nucleus Coherent Scattering

A search for interactions from solar $^8$B neutrinos elastically scattering off xenon nuclei using PandaX-4T commissioning data is reported. The energy threshold of this search is further lowered compared with the previous search for dark matter, with various techniques utilized to suppress the background that emerges from data with the lowered threshold. A blind analysis is performed on the data with an effective exposure of 0.48 tonne$\cdot$year, and no significant excess of events is observed. Among results obtained using the neutrino-nucleus coherent scattering, our results give the best constraint on the solar $^8$B neutrino flux. We further provide a more stringent limit on the cross section between dark matter and nucleon in the mass range from 3 to 9 GeV/c$^2$.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

A Search for the Cosmic Ray Boosted Sub-GeV Dark Matter at the PandaX-II Experiment

We report a novel search for the cosmic ray boosted dark matter using the 100~tonne$\cdot$day full data set of the PandaX-II detector located at the China Jinping Underground Laboratory. With the extra energy gained from the cosmic rays, sub-GeV dark matter particles can produce visible recoil signals in the detector. The diurnal modulations in rate and energy spectrum are utilized to further enhance the signal sensitivity. Our result excludes the dark matter-nucleon elastic scattering cross section between 10$^{-31}$cm$^{2}$ and 10$^{-28}$cm$^{2}$ for a dark matter masses from 0.1 MeV/$c^2$ to 0.1 GeV/$c^2$, with a large parameter space previously unexplored by experimental collaborations.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

A search for two-component Majorana dark matter in a simplified model using the full exposure data of PandaX-II experiment

In the two-component Majorana dark matter model, one dark matter particle can scatter off the target nuclei, and turn into a slightly heavier component. In the framework of a simplified model with a vector boson mediator, both the tree-level and loop-level processes contribute to the signal in direct detection experiment. In this paper, we report the search results for such dark matter from PandaX-II experiment, using total data of the full 100.7 tonne$\cdot$day exposure. No significant excess is observed, so strong constraints on the combined parameter space of mediator mass and dark matter mass are derived. With the complementary search results from collider experiments, a large range of parameter space can be excluded.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Design and Operation of the PandaX-4T High Speed Ultra-high Purity Xenon Recuperation System

In order to recuperate the ultra-high purity xenon from PandaX-4T dark matter detector to high-pressure gas cylinders in emergency or at the end-of-run situation, a high speed ultra-high purity xenon recuperation system is designed and developed. This system includes a diaphragm pump, the heat management system, the main recuperation pipeline, the reflux pipeline, the auxiliary recuperation pipeline and the automatic control system. The liquid xenon in the detector is vaporized by the heat management system, and the gaseous xenon is compressed to 6 MPa at the flow rate of 200 standard litres per minute (SLPM) using the diaphragm compressor. The high-pressure xenon is filled into 128 gas cylinders via the main recuperation pipeline. During the recuperation, the low pressure and temperature conditions of 2 ~ 3 atmospheres and 178 ~ 186.5 K in PandaX-4T dark matter detector are kept by the cooperation of the main recuperation pipeline, reflux pipeline and the auxiliary recuperation pipeline to guarantee the safety, and the purity of the recuperated xenon gas is measured to ensure no contamination happened. The development of the high speed ultra-high purity xenon recuperation system is important for the operation of large-scale dark matter detectors with the requirements of strict temperature and pressure environment and low background.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Low Radioactive Material Screening and Background Control for the PandaX-4T Experiment

PandaX-4T is a ton-scale dark matter direct detection experiment using a dual-phase TPC technique at the China Jinping Underground Laboratory. Various ultra-low background technologies have been developed and applied to material screening for PandaX-4T, including HPGe gamma spectroscopy, ICP-MS, NAA, radon emanation measurement system, krypton assay station, and alpha detection system. Low background materials were selected to assemble the detector. Surface treatment procedures were investigated to further suppress radioactive background. Combining measured results and Monte Carlo simulation, the total material background rates of PandaX-4T in the energy region of 1-25 keV$\rm{}_{ee}$ are estimated to be (9.9 $\pm$ 1.9) $\times \ 10^{-3}$ mDRU for electron recoil and (2.8 $\pm$ 0.6) $\times \ 10^{-4}$ mDRU for nuclear recoil. In addition, $^{nat}$Kr in the detector is estimated to be <8 ppt.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Neutron-induced nuclear recoil background in the PandaX-4T experiment

Neutron-induced nuclear recoil background is critical to the dark matter searches in the PandaX-4T liquid xenon experiment. This paper studies the feature of neutron background in liquid xenon and evaluates their contribution in the single scattering nuclear recoil events through three methods. The first method is fully Monte Carlo simulation based. The last two are data-driven methods that also use the multiple scattering signals and high energy signals in the data, respectively. In the PandaX-4T commissioning data with an exposure of 0.63 tonne-year, all these methods give a consistent result that there are $1.15\pm0.57$ neutron-induced background in dark matter signal region within an approximated nuclear recoil energy window between 5 and 100 keV.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Rethinking Super-Resolution as Text-Guided Details Generation

Deep neural networks have greatly promoted the performance of single image super-resolution (SISR). Conventional methods still resort to restoring the single high-resolution (HR) solution only based on the input of image modality. However, the image-level information is insufficient to predict adequate details and photo-realistic visual quality facing large upscaling factors (x8, x16). In this paper, we propose a new perspective that regards the SISR as a semantic image detail enhancement problem to generate semantically reasonable HR image that are faithful to the ground truth. To enhance the semantic accuracy and the visual quality of the reconstructed image, we explore the multi-modal fusion learning in SISR by proposing a Text-Guided Super-Resolution (TGSR) framework, which can effectively utilize the information from the text and image modalities. Different from existing methods, the proposed TGSR could generate HR image details that match the text descriptions through a coarse-to-fine process. Extensive experiments and ablation studies demonstrate the effect of the TGSR, which exploits the text reference to recover realistic images.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Snowmass2021 Cosmic Frontier White Paper: Puzzling Excesses in Dark Matter Searches and How to Resolve Them

Intriguing signals with excesses over expected backgrounds have been observed in many astrophysical and terrestrial settings, which could potentially have a dark matter origin. Astrophysical excesses include the Galactic Center GeV gamma-ray excess detected by the Fermi Gamma-Ray Space Telescope, the AMS antiproton and positron excesses, and the 511 and 3.5 keV X-ray lines. Direct detection excesses include the DAMA/LIBRA annual modulation signal, the XENON1T excess, and low-threshold excesses in solid state detectors. We discuss avenues to resolve these excesses, with actions the field can take over the next several years.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

The deformation of an erupting magnetic flux rope in a confined solar flare

Magnetic flux ropes (MFRs), sets of coherently twisted magnetic field lines, are believed as core structures of various solar eruptions. Their evolution plays an important role to understand the physical mechanisms of solar eruptions, and can shed light on adverse space weather near the Earth. However, the erupting MFRs are occasionally prevented by strong overlying magnetic fields, and the MFR evolution during the descending phase in the confined cases is lack of attention. Here, we present the deformation of an erupting MFR accompanied by a confined double-peaked solar flare. The first peak corresponded to the MFR eruption in a standard flare model, and the second peak was closely associated with the flashings of an underlying sheared arcade (SA), the reversal slipping motion of the L-shaped flare ribbon, the falling of the MFR, and the shifting of top of filament threads. All results suggest that the confined MFR eruption involved in two-step magnetic reconnection presenting two distinct episodes of energy release in the flare impulsive phase, and the latter magnetic reconnection between the confined MFR and the underlying SA caused the deformation of MFR.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Dark Matter Search Results from the PandaX-4T Commissioning Run

We report the first dark matter search results using the commissioning data from PandaX-4T. Using a time projection chamber with 3.7-tonne of liquid xenon target and an exposure of 0.63 tonne$\cdot$year, 1058 candidate events are identified within an approximate nuclear recoil energy window between 5 and 100 keV. No significant excess over background is observed. Our data set a stringent limit to the dark matter-nucleon spin-independent interactions, with a lowest excluded cross section (90% C.L.) of $3.8\times10^{-47} $cm$^2$ at a dark matter mass of 30 GeV/$c^2$.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Light yield and field dependence measurement in PandaX-II dual-phase xenon detector

The dual-phase xenon time projection chamber (TPC) is one of the most sensitive detector technology for dark matter direct search, where the energy deposition of incoming particle can be converted into photons and electrons through xenon excitation and ionization. The detector response to signal energy deposition varies significantly with the electric field in liquid xenon. We study the detector&#39;s light yield and its dependence on the electric field in the PandaX-II dual-phase detector containing 580~kg liquid xenon in the sensitive volume. From our measurements, the light yield at electric fields from 0~V/cm to 317~V/cm is obtained for energy depositions up to 236~keV.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Scalable, Proposal-free Instance Segmentation Network for 3D Pixel Clustering and Particle Trajectory Reconstruction in Liquid Argon Time Projection Chambers

Liquid Argon Time Projection Chambers (LArTPCs) are high resolution particle imaging detectors, employed by accelerator-based neutrino oscillation experiments for high precision physics measurements. While images of particle trajectories are intuitive to analyze for physicists, the development of a high quality, automated data reconstruction chain remains challenging. One of the most critical reconstruction steps is particle clustering: the task of grouping 3D image pixels into different particle instances that share the same particle type. In this paper, we propose the first scalable deep learning algorithm for particle clustering in LArTPC data using sparse convolutional neural networks (SCNN). Building on previous works on SCNNs and proposal free instance segmentation, we build an end-to-end trainable instance segmentation network that learns an embedding of the image pixels to perform point cloud clustering in a transformed space. We benchmark the performance of our algorithm on PILArNet, a public 3D particle imaging dataset, with respect to common clustering evaluation metrics. 3D pixels were successfully clustered into individual particle trajectories with 90% of them having an adjusted Rand index score greater than 92% with a mean pixel clustering efficiency and purity above 96%. This work contributes to the development of an end-to-end optimizable full data reconstruction chain for LArTPCs, in particular pixel-based 3D imaging detectors including the near detector of the Deep Underground Neutrino Experiment. Our algorithm is made available in the open access repository, and we share our Singularity software container, which can be used to reproduce our work on the dataset.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Synchronous oscillations locked on classical energy levels by two cooperating drives

It is intuitively imagined that the energy of a classical object always takes continues values and can hardly be confined to discrete ones like the energy levels of microscopic systems. Here, we demonstrate that such classical energy levels against intuition can be created through a previously unknown synchronization process for nonlinearly coupled macroscopic oscillators driven by two equally strong fields. Given the properly matched frequencies of the two drive fields, the amplitude and phase of an oscillator will be frozen on one of a series of determined trajectories like energy levels, and the phenomenon exists for whatever drive intensity beyond a threshold. Interestingly, the oscillator&#39;s motion can be highly sensitive to its initial condition but, unlike the aperiodicity in chaotic motion, it will nonetheless end up on such fixed energy levels. Upon reaching the stability, however, the oscillations on the energy levels are robust against noisy perturbation.

0 citations0 reviewsNo code linkedOpen access
preprint2017arXiv

Entangling light field with mechanical resonator at high temperature

We present a study on how to realize the widely interested optomechanical entanglement at high temperature. Unlike the majority of the previous experimental and theoretical researches that consider the entanglement of a mechanical resonator with a cavity field created by red-detuned continuous-wave or blue-detuned pulsed driving field, we find that applying blue-detuned continuous-wave pump field to cavity optomechanical systems can achieve considerable degrees of quantum entanglement, which is generally challenging to obtain at high temperature for the known physical systems. The competition between the induced squeezing-type interaction and the existing decoherence leads to stable entanglement in dynamically unstable regime. There is a much more relaxed condition for the existence of entanglement, as compared with the well-known criterion for neglecting the thermal decoherence on optomechanically coupled systems. A simple relation about a boundary in the parameter space, across which the entanglement can exist or not, is found with an analytical expression for the degree of the achieved entanglement at any temperature, which is derived for the systems of highly resolved sideband. The studied scenario with blue-detuned continuous-wave driving field can greatly simplify the generation of the widely interested optomechanical entanglement of macroscopic quantum states. Our study also provides the answers to two fundamentally meaningful open problems: (1) what is the condition for a system to avoid its loss of quantum entanglement under thermal decoherence? (2) is it possible to preserve the entanglement in a thermal environment by increasing the interaction that entangles the subsystems?

0 citations0 reviewsNo code linkedOpen access