arXiv subjects

Pei Wang

Publications and source records attributed to Pei Wang.

At least 19 recordsLinked to original sources

arXiv2026

A Missing Tool for Calculating Auto/Cross-correlation Function under Nonuniform Sampling Observations

Nonuniform sampling presents a long-standing challenge in astrophysical time-domain analysis, invalidating the standard autocorrelation and cross-correlation functions and forcing researchers to adopt ad-hoc methods like interpolation or binning, which introduce unquantified biases and lack rigorous error estimation. Here we introduce a new method for calculating the nonuniform autocorrelation function (NUACF) and nonuniform cross-correlation function (NUCCF) for irregularly sampled time series. Instead of relying on interpolation, it naturally evaluates the correlation function by incorporating time-interval weights and misalignment penalties. Monte Carlo simulations provide confidence bands for significance assessment and a complete error budget for the time delays that accounts for both flux uncertainties and sampling irregularity (essential but generally absent from existing methods). Through extensive simulations, we demonstrate our method outperforms traditional methods across various conditions, from strictly periodic to complex repeating variability patterns (e.g., intermittent but aperiodic). Its effectiveness is demonstrated via various real astrophysical data sets, revealing repetitive variability in stellar light curves, measuring time delays for multi-band disc reverberation in the AGN Fairall 9, and providing model-independent validation of time delays for the gravitationally lensed quasar HE 0435-1223. The method provides a rigorous and general solution to the ubiquitous problem of nonuniform sampling, positioning it as a useful tool for large-scale time-domain survey data analysis. The framework is also directly applicable to emerging time-domain phenomena such as fast radio bursts (FRBs), enabling, e.g., the study of correlations between persistent radio source luminosity and repeating FRB activity, or among the multi-parameter variability curves of FRB emission itself.

astro-ph.IM↗

arXiv2026

Constraints on the Low-frequency Radio Emission of the Galactic FRB Source SGR 1935+2154

We present a search for radio pulses from the Galactic magnetar SGR 1935+2154, a well-known source of fast radio bursts (FRBs), at $\sim$110 MHz using the Large Phased Array (LPA) of the Pushchino Radio Astronomy Observatory. Data from two active periods in 2020 (March -- May and September -- November, with $\sim 3.5$ minutes of daily coverage) were analyzed with new methods tailored to both FRB-like single pulses and pulsar-like periodic signals. No significant FRB-like pulses were found. Using Monte Carlo simulations, $3\sigma$ upper limits were derived for the burst rate: for a log-normal energy distribution the limit is $\sim$${10}^{1.5}~{\rm{d}}^{-1}$ for a mean of average monochromatic isotropic luminosity $L_{\nu{\rm ,mean}}\sim1.3\times{10}^{29}~{\rm{erg~s^{-1}~ {Hz}^{-1}}}$ and a natural log-space scatter of $\sigma\sim0.85$; while for a power-law distribution it is $\sim$${10}^{1.8}~{\rm{d}}^{-1}$ for an index $\beta\lesssim3.0$ and a minimum average monochromatic isotropic luminosity $L_{\nu{\rm{,min}}}\lesssim0.7\times{10}^{25}~{\rm{erg~s^{-1}~{Hz}^{-1}}}$. When folded at the known 3.24781628 s period of SGR 1935+2154, a weak pulse was noted (S/N $<$ 3.16), but the significance is insufficient for a secure detection of the pulsar-like emission signal. A conservative upper limit on the average monochromatic isotropic luminosity of any possible periodic emission is $2.08\times{10}^{19}~{\rm{erg~s^{-1}~{Hz}^{-1}}}$. Our results offer meaningful low-frequency upper limits on the burst rate of SGR 1935+2154, and hint for very faint pulsar-like radiation at meter wavelengths.

astro-ph.HE↗

arXiv2026

Statistical Symmetry Breaking and Emergent Colored Noise in a Stochastic Scalar-Doublet Field Theory

We investigate a relativistic stochastic field theory in which a complex scalar doublet is coupled to a complex white-noise source. The action preserves Lorentz and $\mathrm{U(1)}\times\mathrm{SU(2)}$ symmetries at the statistical level, whereas the corresponding Euler-Lagrange equations exhibit symmetry breaking along individual stochastic realizations. Within a gauge-field-free sector introduced to obtain analytical solutions, we show that the scalar doublet undergoes a noise-driven random walk in field space, leading to a finite, time-dependent ensemble average of its magnitude. As an illustrative application, we further investigate the coupling of the stochastic scalar field to fermions through a Yukawa interaction. The scalar-field solution naturally separates into a tail component, which contributes as an effective mass-like term, and a light-cone component, which acts as a colored-noise source that induces a spatially correlated stochastic phase in the fermion wave function. The statistical properties and correlation length of this emergent colored noise are derived analytically within the adopted approximations. The present work provides an exploratory study of statistical symmetry breaking and emergent colored-noise dynamics in a relativistic stochastic scalar-doublet field theory.

hep-ph↗

arXiv2026

Timing, Polarization, and Single-Pulse Properties of Long-Period FAST Pulsars

We present phase-connected timing and polarization measurements for two long-period FAST-CRAFTS pulsars, PSRs J0000+6252 and J2131+3642, and extend single-pulse emission-state analysis to a five-source sample including PSRs J1903+1407, J1502+4653, and J2112+4058. FAST L-band timing baselines span 414 to 511 days; the two pulsars have spin periods of 1.11 to 1.55 s, period derivatives of $(3.99$ to $4.06)\times10^{-15}~{\rm s~s^{-1}}$, characteristic ages of 4.34 to 6.16 Myr, surface magnetic fields of $(2.15$ to $2.52)\times10^{12}$ G, and spin-down luminosities of $(4.21\times10^{31}$ to $1.16\times10^{32})~{\rm erg~s^{-1}}$. Their rotation measures are $70.2\pm26.7$ and $-44.6\pm7.6~{\rm rad~m^{-2}}$, with linear polarization fractions of 17.6\% to 27.2\%. PSR J2131+3642 shows a short monotonic PA segment permitting a formal rotating-vector-model fit, though limited longitude coverage leaves the geometric parameters poorly constrained; PSR J0000+6252 has too few PA points for such a fit. Gaussian mixture modeling (GMM) of single-pulse energy distributions identifies null, weak, and burst components in PSRs J0000+6252, J1903+1407, J1502+4653, and J2112+4058, while J2131+3642 shows only weak and burst states. We also identify bright single pulses (peak intensity $\geq10\times$ the integrated average profile): 42 in J0000+6252, four each in J1903+1407 and J2112+4058, and none in J2131+3642 or J1502+4653. These bright pulses occur within the main emission window with no evidence of periodic recurrence, consistent with sporadic enhancements of the normal radio-emission beam. For J2112+4058, we measure a scattering timescale $\tau_{\rm sc}=5.84\pm0.18$ ms at $\nu_{\rm ref}=1.25$ GHz. Together, these results highlight the diversity of magnetospheric variability among slowly rotating neutron stars.

astro-ph.HE↗

arXiv2026

Rethinking the Evaluation and Optimization of LLM-Based Social Simulation

LLM-based social simulation is a promising complement to traditional methods such as surveys and behavioral experiments. A core question is how to evaluate the fidelity of LLM-simulated human behavior and optimize LLMs toward it. Prevailing practice evaluates by accuracy, checking whether the model selects the single response observed from a human, and trains the LLM to reproduce this hard label. However, human behavior is inherently subjective: the same person in the same situation may reasonably act differently, so an observed response is only one draw from an underlying response distribution, rendering accuracy-based evaluation unreliable and hard-label training misleading. To address these problems, we first introduce the subjectivity coefficient, an entropy-based quantity distinguishing objective tasks such as coding from subjective ones such as social simulation, and use it to systematically analyze how accuracy-based evaluation and hard-label training fail as subjectivity grows. Based on the subjectivity coefficient, we propose Subjectivity-Adaptive soft-Label Training (SALT): it pools observed outputs from semantically nearby inputs into soft distributional labels, with an aggregation radius adapted to the estimated subjectivity of each input; in the near-objective limit the neighborhood shrinks, so SALT naturally falls back to standard single-label training. Moreover, since existing datasets record only single observed responses and cannot support distributional evaluation, we construct SUBJSIM, a benchmark of 19,300 contexts covering 193 annotators and 100 subjective questions. Since real-world data typically provide only a single observation per input, our experiments train models from single observed outputs while evaluating them against the full response distributions, verifying feasibility in realistic settings. Results on SUBJSIM demonstrate the advantages of our method.

cs.AI↗

arXiv2026

A Helium-shell Burning Blue Horizontal Branch Star Produced from Common Envelope Evolution

Observationally, blue horizontal branch (BHB) stars are defined as hot stars occupying a characteristic region between the extreme blue horizontal branch and RR Lyrae variables in the Hertzsprung-Russell diagram. Most of them are interpreted as stripped core-helium-burning stars, but the role of binary interaction in their formation remains unclear. Here, we report the discovery of a metal-rich BHB star in a 0.82628-day binary system (Feige 64) comprising a $0.35\pm0.03\,M_{\odot}$ BHB star and a likely $1.26\pm0.17\,M_{\odot}$ white dwarf (WD). The BHB star has an effective temperature of $15{,}524\pm310$ K and a luminosity of $39.7\pm4.1\,L_{\odot}$. Stellar evolution modelling indicates that it is a helium-shell-burning star produced through the common-envelope channel, retaining a hydrogen-rich envelope that is more massive than previously thought for low-mass stars. This finding provides direct evidence for binary interaction in the formation of BHB stars, offering a fresh perspective on interpreting this emerging population.

astro-ph.SR↗

arXiv2026

Optical Images of the Braneworld Black Hole Surrounded by an Optically Thin Accretion Disk

This work examines the observational signatures of rotating black holes with tidal charge in the Randall--Sundrum braneworld scenario. Combining an elliptic-integral-based analytical treatment with numerical ray tracing, we characterize photon motion around braneworld black holes in detail. For small observer inclinations, secondary images remain embedded inside the primary emission rings. As the inclination becomes larger, the primary and secondary images gradually separate and produce a strongly asymmetric image morphology. We show that the image asymmetry and the deformation of the inner shadow are jointly controlled by the black hole spin, the tidal charge, and the observer inclination. To analyze the frequency shifts across the accretion disk, we extend the emitting region from the ISCO down to the event horizon by including the plunging flow. The results indicate that the observer inclination is the dominant factor governing the frequency-shift distribution. In addition, we reconstruct braneworld black hole images using a fisheye-lens ray-tracing model. The optical morphology and brightness distribution show a clear dependence on the observing frequency, especially when comparing 230~GHz with 86~GHz. We also contrast the brightness distributions of prograde and retrograde disks, finding that both the total intensity and the peak intensity at 86~GHz are higher than those at 230~GHz. For negative values of the tidal charge, we further investigate the corresponding frequency-shift behavior and 230~GHz intensity profiles, which may provide useful theoretical guidance for future studies of extra-dimensional gravity models.

astro-ph.HE↗

arXiv2026

Analyzing and Correcting Benevolence Bias in Large Language Models

Large language models (LLMs) are increasingly used as stand-ins for human respondents, from opinion polls and simulated survey participants to agent-based social simulations. These uses rest on one assumption: that conditioning a model on who a person is yields answers resembling those of real people from that group. Here we identify and measure benevolence bias, a small but consistent tendency for aligned LLMs to lean toward the kinder, safer, more socially approved answer on value-laden survey questions. Across 18 widely used models, four social-science datasets (ANES, GSS, WVS, and a cross-cultural prospect-theory replication) and six psychological categories, we find that the bias is a stable model property, not a quirk of any one system: it points the same way across models, grows with model size, and traces to the post-training stage. Prompt language and framing change its size but never its direction, and a "malicious persona" stress test shows a one-sided limit: aligned models struggle to play people who are less kind, less prosocial or more harm-tolerant than average. The issue is thus not only a shifted average, but a narrowed range of people the model can imitate. The bias sits in the middle of the answer distribution rather than its tails, and survives changes in sampling temperature and simple prompted reflection. The encouraging news is that it is easy to diagnose and straightforward to fix: a light-touch contrastive calibration, which needs no retraining and works on black-box APIs, brings all six categories back to the human baseline. Our results give researchers a clear map of where aligned LLMs can already be trusted as human stand-ins, where they need care, and a ready-to-use method for closing the gap.

cs.HC↗

arXiv2026

Cross-validation of six dispersion measure estimation methods for FRB 20240114A

Fast Radio Bursts (FRBs) are important cosmological probes, but their applications depend critically on accurate dispersion measure (DM) determinations. We present a systematic comparison of six DM estimation methods using 2,874 bursts from FRB20240114A, the most active repeating FRB currently known, observed by FAST during a single 4.4-hr session on 2024 March 12. This large, homogeneous sample over a short timescale, during which the propagation environment is expected to be nearly static, provides an ideal benchmark for isolating algorithmic effects on DM determination. We investigate the dependence of inter-method consistency on signal-to-noise ratio (S/N), burst morphology, and radio frequency interference (RFI). Low-S/N bursts exhibit significantly larger inter-method deviations, while single-component bursts produce highly consistent DM values across methods. In contrast, complex double- and multiple-component bursts with drifting substructures lead to substantial inter-method scattering, indicating that DM discrepancies are primarily driven by algorithmic responses to burst morphology. RFI does not significantly alter the global statistical behavior of DM deviations, but it affects density-filtering methods through morphology distortion caused by frequency-channel masking. Even after imposing strict inter-method consistency constraints, FRB20240114A still exhibits notable apparent DM fluctuations spanning $\sim$528-534~pc~cm$^{-3}$ over 15,780s. For morphologically simple bursts these variations far exceed the measurement uncertainty and, on second-to-minute timescales, cannot arise from any plausible change in the line-of-sight electron column, pointing instead to a frequency-dependent emission-time structure intrinsic to the bursts that mimics dispersion.

astro-ph.HE↗

arXiv2026

A pulsar escaping an ancient open cluster via tidal stripping

Open clusters are the primary birthplaces of stars in the Milky Way disk, yet their neutron star progeny are rarely found within them, presumably due to supernova-induced kicks that eject them at birth. Here we report the arcsec-level localization of the pulsar PSR J1921+3745 to the tidal tail of NGC 6791, one of the oldest and most massive open clusters. Our N-body simulation shows that more than 95% of neutron stars formed in such clusters have been ejected. This pulsar's location in the tidal tail indicates it was retained for billions of years before being stripped by Galactic tides. This long-term retention requires low natal kicks, consistent with formation via electron-capture supernova. Our findings capture a rare snapshot of a neutron star transitioning into the Galactic field, identifying tidal stripping of ancient clusters as a verified source of the Galactic neutron star population.

astro-ph.HE↗

arXiv2026

Indication for Decreasing Dispersion Measure in the Population of Repeating Fast Radio Bursts and Connection to Young Supernova Remnant Expansion

Fast Radio Bursts (FRBs) are millisecond-duration, highly energetic radio transients of uncertain origin. Repeating FRBs provide an excellent population for investigating their nature, particularly through studies of parameter evolution. Out of the 63 repeaters monitored by CHIME, we select the 19 sources with more than 10 detected bursts, and examine their long-term dispersion measure (DM) evolution. Seven sources show statistically significant DM evolution and are classified as the golden sample. Of these, five exhibit a decreasing DM trend and two show an increasing trend. We then perform a binomial test under the null hypothesis that decreasing and increasing DM variation trends have equal probabilities. The current combined sample, including our golden sample and additional repeaters with reported DM change rate from the literature, gives a p-value of 0.033, supporting that decreasing DM trends are more common in the repeating FRB population. This statistical result is consistent with scenarios in that the local electron density around repeaters generally decreases with time, for example, due to expansion of a young supernova remnant (SNR). Finally, within the SNR expansion model, we provide an illustrative estimate of the SNR contributions to the DM for different ejecta masses.

astro-ph.HE↗

arXiv2026

Fast radio bursts, magnetars and earthquakes: their "family feud"?

Fast radio bursts (FRBs) are millisecond-duration cosmic transients whose origin remains elusive. Competing models invoke either earthquake-like processes or flare-like mechanisms. To discriminate between these scenarios, we develop a novel diagnostic, the Pincus-Lyapunov diagram (PLD), to characterize the energetic transients in the stochasticity-chaos phase space. We compile burst sequences from five representative FRBs (FRB 20121102A, FRB 20190520B, FRB 20201124A, FRB 20220912A, and FRB 20240114A), together with those from magnetar flares (SGR J1550$-$5418, SGR J0501+4516, SGR 1806$-$20, SGR 1900+14, and SGR J1935+2154), pulsar glitches, solar flares, and earthquakes, and map them onto the PLD for comparative analysis. The resulting diagram shows that FRBs occupy a distinct region of the phase space. Specifically, a permutation test reveals a statistically significant difference in the distributions of magnetar flares and pulsar glitches compared to those of repeating FRBs ($p$-value $\simeq 0.05$). To examine whether temporal variations in source activity can shift a repeater's position in this phase space, we analyze the time evolution of the most prolific repeater, FRB~20240114A. For this repeating FRB, both Pincus Index and Lyapunov Exponent demonstrate statistically stable behaviour over the eight-month observation session, with Augmented Dickey--Fuller tests yielding $p \simeq 1.78\times10^{-3}$ and $9.91\times10^{-3}$, respectively. By assembling the most comprehensive dataset to date, our work indicates that the trigger mechanisms of repeating FRBs are likely to be distinct from those driving magnetar flares, pulsar glitches, solar flares, and earthquakes.

astro-ph.HE↗

arXiv2026

The superite phase and phase transition inducing multiscale solidification microstructures and segregations in steels

Based on classical concept, solidification of alloys is a direct transition from liquid phase to solid phase, by which dendrites and dendritic segregation are produced. Through in-situ and real time morphology observation and XRD test during solidification of three steels, a new superite phase featured as statistically oriented tiny structures was identified, and a general liquid-superite-solid phase transformation process is revealed. In the early solidification stage, the liquid alloys transit to dendrites composed of superite phase. Initiated from the boundaries of dendritic arms or dendrite grains, the superite phase transits to austenite grains within an initial dendritic arm, and expels solute elements to the residual superite phase. Mixed multi-phase microstructures are subsequently produced from the residual enriched superite phase. Here, although three steels exhibit different phase proportion and phase constitution in the superite-solid transition, they all follow above general transition mode. Multiscale microstructures and segregations are produced in the transition from superite to solid. These new findings change the basic understanding about the solidification of alloys, rediscover the formation mechanism on segregations and multiscale solidification microstructures, including dendrite pattern, solid dendritic arm, dendritic segregation, the mixed multi-phase microstructures, eutectic, inclusions and precipitate. These new findings are also crucial to the control of solidification microstructures and segregation in metals.

cond-mat.mtrl-sci↗

arXiv2026

Diffusive transport from spatially correlated random phase kicks

We study the dynamics of a single-particle wave packet on a one-dimensional lattice subject to periodic random phase kicks with finite spatial correlation length. This stroboscopic setting provides a controllable model of dephasing in driven quantum systems. Using a momentum-space formulation, we show that the evolution is governed by an accumulated phase whose structure determines the spreading of the wave packet. We find that the phase kicks strongly suppress ballistic transport and induce diffusion at long times. We derive an explicit analytical expression for the diffusion coefficient as a function of the correlation length, in excellent agreement with numerical simulations. Our results uncover a simple mechanism by which spatially correlated phase noise controls quantum transport, and provide a quantitatively testable prediction for diffusion in periodically driven lattice systems. Possible experimental realizations in cold-atom platforms are discussed.

cond-mat.mes-hall↗

arXiv2026

Random Polarization Position Angle Behaviors across Bursts of Repeating Fast Radio Bursts

Fast radio bursts (FRBs), highly polarized, mostly have a nearly constant polarization position angle (PA) during each burst. Their PAs are observed to vary from burst to burst, with the statistical properties remaining stable across different observation sessions. We found that the intrinsic PAs of repeating FRBs are approximately Gaussian distributed, suggesting that the emission likely originates from a localized region within the neutron star's magnetosphere. A periodicity search of the PA time series using the Lomb-Scargle periodogram reveals no credible periodic signal in the period range from 10 ms to $10^7$ ms, and similar analyses of several active observations also yield null detections. We interpret these properties by extending the rotating vector model to include a dynamically evolving magnetosphere, in which the effective magnetic axis varies from burst to burst due to stochastic perturbations. In this framework, the observed PA distributions can naturally arise from geometric projection effects, and the absence of periodicity reflects the random wandering of the magnetic axis within a confined region. This scenario provides a natural explanation for both repeating and apparently non-repeating FRBs.

astro-ph.HE↗

arXiv2026

A Python/CuPy Software Correlator for QUEST: Real-Time Performance and Initial Imaging

We present a Python/CuPy FX software correlator for small radio interferometer arrays and evaluate it on QUEST (Qilu University Explorer Survey Telescope). The system combines multi-threaded data ingest, pinned-memory host-device transfers, GPU-accelerated correlation, Polyphase Filter Bank channelization, MAD-based RFI flagging, and delay/phase calibration in a single workflow aimed at array commissioning. On a single NVIDIA RTX 4090D GPU, the implementation reaches a peak throughput of 1.51 GB/s, which is sufficient for real-time operation in the four-antenna mode tested here. After calibration, the visibility phase across a clean 1.32-1.38 GHz band is flattened to a residual scatter of a few degrees. Using the calibrated visibilities, we form a four-antenna synthesis image of Cassiopeia A; the CLEANed image recovers a compact source at the phase center and reduces image-domain background fluctuations from order 0.1 to a few 0.01 Jy/beam. These results indicate that the software is suitable for small-array commissioning and initial synthesis imaging on QUEST. A GNSS-based beam measurement is included as a supporting commissioning check.

astro-ph.IM↗

arXiv2026

Visual Reasoning through Tool-supervised Reinforcement Learning

In this paper, we investigate the problem of how to effectively master tool-use to solve complex visual reasoning tasks for Multimodal Large Language Models. To achieve that, we propose a novel Tool-supervised Reinforcement Learning (ToolsRL) framework, with direct tool supervision for more effective tool-use learning. We focus on a series of simple, native, and interpretable visual tools, including zoom-in, rotate, flip, and draw point/line, whose tool supervision is easy to collect. A reinforcement learning curriculum is developed, where the first stage is solely optimized by a set of well motivated tool-specific rewards, and the second stage is trained with the accuracy targeted rewards while allowing calling tools. In this way, tool calling capability is mastered before using tools to complete visual reasoning tasks, avoiding the potential optimization conflict among those heterogeneous tasks. Our experiments have shown that the tool-supervised curriculum training is efficient and ToolsRL can achieve strong tool-use capabilities for complex visual reasoning tasks.

cs.CV↗

arXiv2026

From Natural Language to Executable Narsese: A Neuro-Symbolic Benchmark and Pipeline for Reasoning with NARS

Large language models (LLMs) are highly capable at language generation, but they remain unreliable when reasoning requires explicit symbolic structure, multi-step inference, and interpretable uncertainty. This paper presents a neuro-symbolic framework for translating natural-language reasoning problems into executable formal representations using first-order logic (FOL) and Narsese, the language of the Non-Axiomatic Reasoning System (NARS). To support this direction, we introduce NARS-Reasoning-v0.1, a benchmark of natural-language reasoning problems paired with FOL forms, executable Narsese programs, and three gold labels: True, False, and Uncertain. We develop a deterministic compilation pipeline from FOL to executable Narsese and validate retained examples through runtime execution in OpenNARS for Applications (ONA), ensuring that the symbolic targets are not only syntactically well formed but also behaviorally aligned with the intended answer. We further present Language-Structured Perception (LSP), a formulation in which an LLM is trained to produce reasoning-relevant symbolic structure rather than only a final verbal response. As an initial proof of concept, we also train and release a Phi-2 LoRA adapter on NARS-Reasoning-v0.1 for three-label reasoning classification, showing that the benchmark can support supervised adaptation in addition to executable evaluation. Overall, the paper positions executable symbolic generation and execution-based validation as a practical path toward more reliable neuro-symbolic reasoning systems.

cs.AI↗