arXiv subjects

Pei Wang

Publications and source records attributed to Pei Wang.

At least 73 records · Page 4Linked to original sources

arXiv2025

High-order staggered Lagrangian hydrodynamics (II) : the artificial viscosity and hourglass control algorithm

In this article, we investigate the artificial viscosity and hourglass control algorithms for high-order staggered Lagrangian hydrodynamics(SGH), as proposed in~\cite[Sun et al., 2025]{Sun2025High}. Inspired by the subzonal pressure method in classical staggered Lagrangian hydrodynamics, we extend the stiffness-based hourglass control algorithm to the high-order setting, enriching the pressure field from the $Q^{m-1}$ to the $Q^{m}$ polynomial space. A unified framework for this hourglass control approach is established, from which the classical subzonal pressure method naturally emerges as the special case of the $Q^1-P^0$ space. The artificial viscosity follows the formulation in~\cite[Dobrev et al., 2012]{Dobrev2012High}. We show that the viscosity admits a concise form, with intermediate variables explicitly computable, leading to improved computational efficiency and easier implementation. Moreover, the tensor viscosity in classical staggered Lagrangian hydrodynamics can be derived in a similarly compact and explicit form. Numerical experiments on two-dimensional problems are presented to demonstrate the accuracy and efficiency of the proposed algorithms.

math.NA↗

arXiv2025

The magnetar model's energy crisis for a prolific repeating fast radio burst source

Fast radio bursts (FRBs) are widely considered to originate from magnetars that power the explosion through releasing magnetic energy. Active repeating FRBs have been seen to produce hundreds of bursts per hour and can stay active for months, thus may provide stringent constraints on the energy budget of FRBs' central engine. Within a time span of 214 days, we detected 11,553 bursts from the hyper-active FRB 20240114A that reached a peak burst rate of 729 hr$^{-1}$. This is the largest burst sample from any single FRB source, exceeding the cumulative total of all published bursts from all known FRBs to date. Assuming typical values of radio efficiency and beaming factor, the estimated total isotropic burst energy of this source exceeds 86% of the dipolar magnetic energy of a typical magnetar. The total released energy from this source exceeds that of other known repeaters by about one and a half orders of magnitude, yielding the most stringent lower limit of $4.7\times10^{32}$ G cm$^3$ for the magnetar's magnetic moment. The source remained active at the end of this observation campaign. Our findings thus require either the FRB's central magnetar engine's possessing exceptionally high emission efficiency or a more powerful compact object than a typical magnetar.

astro-ph.HE↗

arXiv2025

Sensitive Constraints on Coherent Radio Emission from Five Isolated White Dwarfs

Coherent, periodic radio emission from pulsars has been widely interpreted as evidence of neutron stars as strongly magnetized compact objects. In recent years, radio pulses have also been detected from white dwarfs (WDs) in tight binary systems, raising the question of whether isolated WDs could similarly host pulsar-like emission. We conducted the most sensitive search to date for coherent radio signals from five isolated, rapidly rotating, and magnetized WDs, using the Five-hundred-meter Aperture Spherical radio Telescope (FAST), the Green Bank Telescope (GBT), and the Australia Telescope Compact Array (ATCA). No pulsed or continuum radio emission was detected down to $μ$Jy levels. These non-detections place the most stringent observational constraints yet on the existence of isolated WD pulsars. Our results suggest that either such emission is intrinsically weak, narrowly beamed, or requires binary-induced magnetospheric interactions absent in solitary systems. Comparison with the known radio-emitting WDs highlights the critical role of companion interaction in enabling detectable emission. This work expands on prior surveys by targeting sources with the most favorable physical conditions for WD pulsar-like activity and employing highly sensitive, targeted observations. Future observations with next-generation facilities such as the SKA will be essential to explore fainter or sporadic emission from massive, magnetic WDs and to investigate their potential as compact radio transients further.

astro-ph.HE↗

arXiv2025

ForgetMe: Evaluating Selective Forgetting in Generative Models

The widespread adoption of diffusion models in image generation has increased the demand for privacy-compliant unlearning. However, due to the high-dimensional nature and complex feature representations of diffusion models, achieving selective unlearning remains challenging, as existing methods struggle to remove sensitive information while preserving the consistency of non-sensitive regions. To address this, we propose an Automatic Dataset Creation Framework based on prompt-based layered editing and training-free local feature removal, constructing the ForgetMe dataset and introducing the Entangled evaluation metric. The Entangled metric quantifies unlearning effectiveness by assessing the similarity and consistency between the target and background regions and supports both paired (Entangled-D) and unpaired (Entangled-S) image data, enabling unsupervised evaluation. The ForgetMe dataset encompasses a diverse set of real and synthetic scenarios, including CUB-200-2011 (Birds), Stanford-Dogs, ImageNet, and a synthetic cat dataset. We apply LoRA fine-tuning on Stable Diffusion to achieve selective unlearning on this dataset and validate the effectiveness of both the ForgetMe dataset and the Entangled metric, establishing them as benchmarks for selective unlearning. Our work provides a scalable and adaptable solution for advancing privacy-preserving generative AI.

cs.CV↗

arXiv2025

A Target Search for Fast Radio Bursts Associated with Two Fast Blue Optical Transients: AT2018cow and CSS161010

Fast blue optical transients (FBOTs) are luminous, rapidly evolving events with blue spectra, possibly powered by newborn magnetars and linked to fast radio bursts (FRBs). Given this potential connection, we conducted deep radio observations of two nearby FBOTs (AT2018cow and CSS161010) using the Five-hundred-meter Aperture Spherical radio Telescope (FAST), but detected no FRB-like signals. Our observations establish the most stringent upper limits on millisecond radio transients from FBOTs, reaching $\sim$10 mJy flux density. Assuming a log-normal luminosity function analogous to the repeating FRB 121102, we constrain the burst rate from potential magnetars in FBOTs to $<0.01$ hr$^{-1}$. The short ejecta escape timescale ($\sim$2.6 yr) compared to our observation epochs (4$-$6 years post-explosion) suggests that nondetection may not be attributed to FBOT's ejecta absorption. These findings impose useful constraints on the FRB activity emanating from newborn magnetars within FBOTs. They indicate that if there is a burst phase, it is either characterized by weaker bursts, occurs less frequently compared to those in known repeating FRB sources, or takes place beyond the time frame of our current observations. To gain deeper insights into the birth-related activity of magnetars, it is of importance to conduct timely and sustained FRB searches in FBOTs that emerge in the future.

astro-ph.HE↗

arXiv2025

CRAFTS for HI cosmology: I. data processing pipeline and validation tests

We present the calibration procedures and validation of source measurement with the data of the Commensal Radio Astronomy FAST Survey (CRAFTS) for \HI intensity mapping by the Five-hundred-meter Aperture Spherical Radio Telescope (FAST). Using 70-hour drift-scan observation with the L-band (1.05-1.45GHz) 19-beam receiver, we obtain the data covering $270\,\rm deg^2$ sky area. We employ both the pulsar backend and the spectrum backend to calibrate the spectral time-ordered-data (TOD) before projecting them onto HEALPix maps. We produce calibrated TOD with frequency resolution of 30kHz and time resolution of 1s and the map data-cube with frequency resolution of 30kHz and spatial resolution of $2.95\,\rm arcmin^2$. We examine the pointing errors, noise overflow, RFI contamination and their effect on the data quality. The resulting noise level is $\sim$ 5.7mJy for the calibrated TOD and 1.6mJy for the map, consistent with the theoretical predictions within 5\% at RFI-free channels. We also validate the data by Principal Components Analysis (PCA) and find the residual map looks thermal noise dominated after removing 30 modes. We identify 447 isolated bright continuum sources in our data matching the NRAO-VLA Sky Survey (NVSS) catalog, with relative flux error of 8.3\% for TOD and 6.6\% for the map-level. We also measure the \HI emission of 90 galaxies with redshift $z<0.07$ and compare with \HI-MaNGA spectra, yielding an overall relative \HI integral flux error of 16.7\%. These results provide an important first step in assessing the feasibility of conducting cosmological \HI detection with CRAFTS.

astro-ph.CO↗

arXiv2025

Accelerating FRB Search: Dataset and Methods

Fast Radio Burst (FRB) is an extremely energetic cosmic phenomenon of short duration. Discovered only recently and with its origin still unknown, FRBs have already started to play a significant role in studying the distribution and evolution of matter in the universe. FRBs can only be observed through radio telescopes, which produce petabytes of data, rendering the search for FRB a challenging task. Traditional techniques are computationally expensive, time-consuming, and generally biased against weak signals. Various machine learning algorithms have been developed and employed, all of which require substantial datasets. We here introduce the FAST dataset for Fast Radio bursts EXploration (FAST-FREX), built upon the observations obtained by the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Our dataset comprises 600 positive samples of observed FRB signals from three sources and 1000 negative samples of noise and Radio Frequency Interference (RFI). Furthermore, we provide a machine learning algorithm, Radio Single-Pulse Detection Algorithm Based on Visual Morphological Features (RaSPDAM), with significant improvements in efficiency and accuracy for FRB search. We also employed the benchmark comparison between conventional single-pulse search softwares, namely PRESTO and Heimdall, and RaSPDAM. RaSPDAMv2 achieves an average precision of 97% and an average recall of 83%, with notable enhancements in computational performance. Future machine learning algorithms can use this as a reference point to measure their performance and help the potential improvements. By enabling more accurate and efficient detection of transient radio events, our work facilitates the FRB and pulsars search pipeline, enhances the potential for discovering new astrophysical phenomena.

astro-ph.IM↗

arXiv2025

Random non-Hermitian Hamiltonian framework for symmetry breaking dynamics

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.

quant-ph↗

arXiv2025

A narrowband burst from FRB 20190520B simultaneously observed by FAST and Parkes

Fast Radio Bursts (FRBs) are short-duration radio transients with mysterious origins. Since its uncertainty, there are very few FRBs that are observed by different instruments, simultaneously. This study presents a detailed analysis of a burst from FRB 20190520B observed by FAST and Parkes at the same time. The spectrum of this individual burst ended at the upper limit of the FAST frequency band and was simultaneously detected by the Parkes telescope in the 1.5-1.8 GHz range. By employing spectral energy distribution (SED) and spectral sharpness methods, we confirmed the presence of narrowband radiation in FRB 20190520B, which is crucial for understanding its radiation mechanisms. Our findings support the narrowband characteristics that most repeaters exhibit. This work also highlights the necessity of continued multiband observations to explore its periodicity and frequency-dependent properties, contributing to an in-depth understanding of FRB phenomena.

astro-ph.HE↗

arXiv2025

Optical images of the Kerr-Sen black hole and thin accretion disk

This paper investigates the observable properties of a Kerr-Sen black hole surrounded by a thin accretion disk, focusing on the impact of the black hole's spin and charge on the image. Using ray-tracing techniques, we conduct a detailed analysis of the black hole's image, redshift distribution, and intensity distributions at different observation frequencies. The results demonstrate that spin has a more significant effect on the distortion of the inner shadow than charge, and the observer's inclination angle plays a critical role in shaping the redshift distribution, especially near the innermost stable circular orbit. Additionally, the intensity is found to be higher at 86 GHz than at 230 GHz. This study highlights the crucial role of the accretion disk's geometry in determining the black hole's image and redshift effects, thereby providing a refined theoretical framework to guide future observational efforts targeting the Kerr-Sen black hole and its electromagnetic signals.

gr-qc↗

arXiv2025

Do Multi-Structural One-Off FRBs Trace Similar Cosmology History with Repeaters?

Fast Radio Bursts (FRBs) are millisecond-duration transient events that are typically observed at radio wavelengths and cosmological distances but their origin remains unclear. Furthermore, most FRB origin models are related to the processes at stellar scales, involving neutron stars, blackholes, supernovae, etc. In this paper, our purpose is to determine whether multi-structural one-off FRBs and repeaters share similarities. To achieve this, we focus on analyzing the relationship between the FRB event rate and the star formation rate, complemented by statistical testing methods. Based on the CHIME/FRB Catalog 1, we calculate the energy functions for four subsamples, including apparent non-repeating FRBs (one-offs), repeaters, multi-structural one-offs, and the joint repeaters and multi-structural events, respectively. We then derive the FRB event rates at different redshifts for all four subsamples, all of which were found to share a similar cosmological evolution trend. However, we find that the multi-structural one-offs and repeaters are distinguishable from the KS and MWW tests.

astro-ph.HE↗

arXiv2025

From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion

Quantitative remote sensing inversion aims to estimate continuous surface variables-such as biomass, vegetation indices, and evapotranspiration-from satellite observations, supporting applications in ecosystem monitoring, carbon accounting, and land management. With the evolution of remote sensing systems and artificial intelligence, traditional physics-based paradigms are giving way to data-driven and foundation model (FM)-based approaches. This paper systematically reviews the methodological evolution of inversion techniques, from physical models (e.g., PROSPECT, SCOPE, DART) to machine learning methods (e.g., deep learning, multimodal fusion), and further to foundation models (e.g., SatMAE, GFM, mmEarth). We compare the modeling assumptions, application scenarios, and limitations of each paradigm, with emphasis on recent FM advances in self-supervised pretraining, multi-modal integration, and cross-task adaptation. We also highlight persistent challenges in physical interpretability, domain generalization, limited supervision, and uncertainty quantification. Finally, we envision the development of next-generation foundation models for remote sensing inversion, emphasizing unified modeling capacity, cross-domain generalization, and physical interpretability.

cs.CV↗

arXiv2025

Multi-year Polarimetric Monitoring of Four CHIME-Discovered Repeating Fast Radio Bursts with FAST

In this study, we report multi-year polarization measurements of four repeating FRBs initially discovered by CHIME: FRBs~20190117A, 20190208A, 20190303A, and 20190417A. We observed the four repeating FRBs with FAST, detecting a total of 66 bursts. Two bursts from FRB~20190417A exhibit a circular polarization signal-to-noise ratio greater than 7, with the highest circular polarization fraction recorded at 35.7%. While the bursts from FRBs 20190208A and 20190303A are highly linearly polarized, those from FRBs~20190117A and 20190417A show depolarization due to multi-path propagation, with σ_{\mathrm{RM}} = 2.78 \pm 0.05 rad m$^{-2}$ and 5.19 \pm 0.09 rad m$^{-2}$, respectively. The linear polarization distributions among five repeating FRB--FRBs~20190208A, 20190303A, 20201124A, 20220912A, and 20240114A--are nearly identical but show distinct differences from those of non-repeating FRBs. FRBs~20190117A, 20190303A, and 20190417A exhibit substantial rotation measure (RM) variations between bursts, joining other repeating FRBs in this behavior. Combining these findings with published results, 64% of repeating FRBs show RM variations greater than 50 rad m$^{-2}$, and 21\% exhibit RM reversals. A significant proportion of repeating FRBs reside in a dynamic magneto-ionic environment. The structure function of RM variations shows a power-law index of $γ\sim (0-0.8)$, corresponding to a shallow power spectrum $α= -(γ+ 2) \sim -(2.0-2.8)$ of turbulence, if the RM variations are attributed to turbulence. This suggests that the variations are dominated by small-scale RM density fluctuations. We perform K-S tests comparing the RMs of repeating and non-repeating FRBs, which reveal a marginal dichotomy in the distribution of their RMs.We caution that the observed dichotomy may be due to the small sample size and selection biases.

astro-ph.HE↗

arXiv2025

Polarization Position Angle Swing and the Rotating Vector Model of Repeating Fast Radio Bursts

Fast radio bursts (FRBs), typically highly polarized, usually have a nearly constant polarization position angle (PA) during each burst. Some bursts show significant PA variations, and one of them was claimed to have a PA variation pattern consistent with the prediction of the rotating vector model (RVM) commonly adopted to fit the PA variations in radio pulsars. We systematically study the PA evolution pattern of 1727 bursts from three active repeating FRB sources monitored by the Five-hundred-meter Aperture Spherical Telescope (FAST). We identify 46 bursts whose PA variations are fully consistent with the RVM. However, the inferred geometrical parameters and rotation periods derived from these RVM fitting are inconsistent from each other. This suggests that the magnetosphere of the FRB central engine is constantly distorted by the FRB emitter, and the magnetic configuration is dynamically evolving.

astro-ph.HE↗

arXiv2025

Hyper-active repeating fast radio bursts from rotation modulated starquakes on magnetars

The non-detection of periodicity related to rotation challenges magnetar models for fast radio bursts (FRBs) with FRB emission from close to the magnetar surface. Moreover, a bimodal distribution of the burst waiting times is widely observed in hyper-active FRBs, a significant deviation from the exponential distribution expected from stationary Poisson processes. By combining the epidemic-type aftershock sequence (ETAS) earthquake model and the rotating vector model (RVM) involving the rotation of the magnetar and orientations of the spin and magnetic axes, we find that starquake events modulated by the rotation of FRB-emitting magnetar can explain the bimodal distribution of FRB waiting times, as well as the non-detection of periodicity in hyper-active repeating FRBs. We analyze data from multiple FRB sources, demonstrating that differences in waiting time distributions and, to some extent, observed energies can be explained by varying parameters related to geometric properties of the magnetar FRB emission and starquake dynamics. Our results show that the assumption that all FRBs are repeaters is compatible with our model. Notably, we find that hyper-active repeaters tend to have small magnetic inclination angles in order to hide their periodicity. We also show that our model can reproduce the waiting time distribution of a pulsar phase of the galactic magnetar SGR J1935+2154 with a larger inclination angle than the hyper-active repeaters, which could explain the detection of spin period and the relatively low observed energy for FRBs from the magnetar. The spin periods of hyper-active repeaters are not well constrained, but most likely fall in the valley region between the two peaks of the waiting time distributions.

astro-ph.HE↗

arXiv2025

Reinforcement Learning Optimization for Large-Scale Learning: An Efficient and User-Friendly Scaling Library

We introduce ROLL, an efficient, scalable, and user-friendly library designed for Reinforcement Learning Optimization for Large-scale Learning. ROLL caters to three primary user groups: tech pioneers aiming for cost-effective, fault-tolerant large-scale training, developers requiring flexible control over training workflows, and researchers seeking agile experimentation. ROLL is built upon several key modules to serve these user groups effectively. First, a single-controller architecture combined with an abstraction of the parallel worker simplifies the development of the training pipeline. Second, the parallel strategy and data transfer modules enable efficient and scalable training. Third, the rollout scheduler offers fine-grained management of each sample's lifecycle during the rollout stage. Fourth, the environment worker and reward worker support rapid and flexible experimentation with agentic RL algorithms and reward designs. Finally, AutoDeviceMapping allows users to assign resources to different models flexibly across various stages.

cs.LG↗

arXiv2025

SatelliteFormula: Multi-Modal Symbolic Regression from Remote Sensing Imagery for Physics Discovery

We propose SatelliteFormula, a novel symbolic regression framework that derives physically interpretable expressions directly from multi-spectral remote sensing imagery. Unlike traditional empirical indices or black-box learning models, SatelliteFormula combines a Vision Transformer-based encoder for spatial-spectral feature extraction with physics-guided constraints to ensure consistency and interpretability. Existing symbolic regression methods struggle with the high-dimensional complexity of multi-spectral data; our method addresses this by integrating transformer representations into a symbolic optimizer that balances accuracy and physical plausibility. Extensive experiments on benchmark datasets and remote sensing tasks demonstrate superior performance, stability, and generalization compared to state-of-the-art baselines. SatelliteFormula enables interpretable modeling of complex environmental variables, bridging the gap between data-driven learning and physical understanding.

cs.CV↗

arXiv2025

Do they repeat? Monitoring 36 non-repeating FRBs with FAST

The origin of fast radio bursts (FRBs), highly energetic, millisecond-duration radio pulses originating from beyond our galaxy, remains unknown. Observationally, FRBs are classified as non-repeating or repeating, however, this classification is complicated by limited observing time and sensitivity constraints, which may result in some repeating FRBs being misidentified as non-repeating. To address this issue, we adopt both empirical and machine-learning techniques from previous studies to identify candidates that may have been misclassified. We conducted follow-up observations of 36 such candidates, each observed for 10 minutes using the Five-hundred-meter Aperture Spherical Telescope (FAST). No radio bursts exceeding a signal-to-noise ratio of 7 were detected, with a typical 7 sigma fluence limit of ~0.013 Jy ms. We constrain the repetition rates of these sources using two statistical models of FRB occurrence. Combining our FAST non-detections with prior observations, we derive upper limits on the repetition rates of ~$10^{-2.6}$-$10^{-0.22}$ hr$^{-1}$ under a Poisson process, and ~$10^{-2.3}$-$10^{-0.25}$ hr$^{-1}$ under a Weibull process. This work presents one of the most stringent upper limits on FRB repetition rates to date, based on a sample size five times larger than those used in previous studies.

astro-ph.HE↗