arXiv subjects

Zhen Guo

Publications and source records attributed to Zhen Guo.

At least 55 records · Page 3Linked to original sources

arXiv2025

On the mean square of the error term for the asymmetric two-dimensional divisor problem with congruence conditions

Suppose that $a$ and $b$ are positive integers subject to $(a,b)=1$. For $n\in\mathbb{Z}^+$, denote by $τ_{a,b}(n;\ell_1,M_1,l_2,M_2)$ the asymmetric two--dimensional divisor function with congruence conditions, i.e., \begin{equation*} τ_{a,b}(n;\ell_1,M_1,l_2,M_2)=\sum_{\substack{n=n_1^an_2^b\\ n_1\equiv\ell_1\!\!\!\!\!\pmod{M_1}\\ n_2\equiv\ell_2\!\!\!\!\!\pmod{M_2}}}1. \end{equation*} In this paper, we shall establish an asymptotic formula of the mean square of the error term of the sum $\sum_{n\leqslant M_1^aM_2^bx}τ_{a,b}(n;\ell_1,M_1,l_2,M_2)$. This result constitutes an enhancement upon the previous result of Zhai and Cao [16].

math.NT↗

arXiv2025

VVV-WIT-13: an eruptive young star with cool molecular features

Here we investigate an infrared eruptive source, identified from the decade-long VISTA Variables in the Via Lactea survey (VVV). We named this target after a group of variable sources discovered by VVV, as VVV-WIT-13, with WIT standing for "What Is This?", due to its unique photometric variation behaviour and the mysterious origin of the outburst. This target exhibited an outburst with a 5.7 mag amplitude in the Ks-band, remained on its brightness plateau for 3.5 years, and then rapidly faded to its pre-eruptive brightness afterwards. We aim to reveal the variable nature and outburst origin of VVV-WIT-13 by presenting our follow-up photometric and spectroscopic observations along with theoretical models. We gathered photometric time series in both near- and mid-infrared wavelengths. We obtained near-infrared spectra during the outburst and decaying stages on XSHOOTER/VLT and FIRE/Magellan, and then fitted the detected molecular absorption features using models from ExoMol. We applied 2D numerical simulations to re-create the observables of the eruptive phenomenon. We observe deep AlO absorption bands in the infrared spectra of VVV-WIT-13, during the outburst stage, along with other more common absorption bands (e.g. CO). Our best-fit model suggests a 600 K temperature of the AlO absorption band. In the decaying stage, the AlO bands disappeared, whilst broad blue-shifted H2 lines arose, a common indicator of stellar wind and outflow. The observational evidence suggests that the CO and TiO features originate from an outflow or a wind environment. We find that VVV-WIT-13 is an eruptive young star with instability occurring in the accretion disk. One favoured theoretical explanation of this event is a disrupted gas clump at a distance of 3 au from the source. If confirmed, this would be the first such event observed in real time.

astro-ph.SR↗

arXiv2025

Integrating Attention-Enhanced LSTM and Particle Swarm Optimization for Dynamic Pricing and Replenishment Strategies in Fresh Food Supermarkets

This paper presents a novel approach to optimizing pricing and replenishment strategies in fresh food supermarkets by combining Long Short-Term Memory (LSTM) networks with Particle Swarm Optimization (PSO). The LSTM model, enhanced with an attention mechanism, is used to predict sales volumes, pricing trends, and spoilage rates over a seven-day period. The predictions generated by the LSTM model serve as inputs for the PSO algorithm, which iteratively optimizes pricing and replenishment strategies to maximize profitability while adhering to inventory constraints. The integration of cost-plus pricing allows for dynamic adjustments based on fixed and variable costs, ensuring real-time adaptability to market fluctuations. The framework not only maximizes profits but also reduces food waste, contributing to more sustainable supermarket operations. The attention mechanism enhances the interpretability of the LSTM model by identifying key time points and factors influencing sales, improving decision-making accuracy. This methodology bridges the gap between predictive modeling and optimization, offering a scalable solution for dynamic pricing and inventory management in fresh food retail and other industries dealing with perishable goods.

cs.LG↗

arXiv2025

A magnetic white dwarf formed through a binary merger within 35 million years

White dwarfs (WDs) represent the final evolutionary stage of most stars, typically originating from progenitor stars with masses below approximately 8 $M_{\odot}$ to 10 $M_{\odot}$. Formation through single-star evolution generally requires at least 25 Myr, with the youngest WDs often near the Chandrasekhar limit of 1.4 $M_{\odot}$. In contrast, WDs formed via binary channels, such as mergers or mass transfer, can develop smaller masses in a shorter timescale and may exhibit unique characteristics, including strong surface magnetic fields and rapid rotation. Accurately determining the ages of these WDs is essential for understanding their formation. A valuable method involves studying WDs in star clusters, where member stars share the same age and chemical composition, allowing for precise constraints on the formation times and metallicities of the WDs' progenitors. Here we report a WD found in the open cluster RSG 5, which is only 35 Myr old. The WD's mass is lower than 1.05 $M_{\odot}$, indicating it may not have formed through single-star evolution. The WD possesses an exceptionally strong surface magnetic field ($\ge 200$ MG), a short rotational period ($\sim 6.5$ min), and, most notably, a co-rotating half-ring of ionized circumstellar debris. This distinctive feature provides evidence for a binary merger origin, a scenario further substantiated by our stellar evolution models.

astro-ph.SR↗

arXiv2025

Persistent Backdoor Attacks in Continual Learning

Backdoor attacks pose a significant threat to neural networks, enabling adversaries to manipulate model outputs on specific inputs, often with devastating consequences, especially in critical applications. While backdoor attacks have been studied in various contexts, little attention has been given to their practicality and persistence in continual learning, particularly in understanding how the continual updates to model parameters, as new data distributions are learned and integrated, impact the effectiveness of these attacks over time. To address this gap, we introduce two persistent backdoor attacks-Blind Task Backdoor and Latent Task Backdoor-each leveraging minimal adversarial influence. Our blind task backdoor subtly alters the loss computation without direct control over the training process, while the latent task backdoor influences only a single task's training, with all other tasks trained benignly. We evaluate these attacks under various configurations, demonstrating their efficacy with static, dynamic, physical, and semantic triggers. Our results show that both attacks consistently achieve high success rates across different continual learning algorithms, while effectively evading state-of-the-art defenses, such as SentiNet and I-BAU.

cs.LG↗

arXiv2025

Episodic accretion in high-mass star formation: An analysis of thermal instability for axially symmetric disks

High-mass young stellar objects exhibit episodic accretion bursts similar to their low-mass counterparts. Understanding these outbursts is crucial for elucidating massive star formation and disk evolution around high-mass protostars. We investigate thermal instability's role in triggering accretion outbursts using a two-dimensional hydrodynamical model that fully resolves the vertical structure of the inner disk. This approach provides a more realistic depiction of axially symmetric disk dynamics and assesses observable burst signatures. We simulate the inner 10 astronomical units of a circumstellar disk around a high-mass protostar, incorporating viscous heating and radiative transport in radial and vertical directions. Unlike previous one-dimensional studies, our two-dimensional model resolves time-dependent vertical disk structure, capturing complex radial-vertical dynamics. Our simulations show thermal instability causes significant structural changes. Steep temperature gradients and vigorous convection develop at outburst onset, with gas flows differing between midplane and upper layers. Energy release produces 15-30 year outbursts with peak accretion rates of $2-3\times10^{-4}~\rm M_{\odot}~\rm{yr}^{-1}$. While observable, these bursts are insufficiently bright with rise times differing from rapid observed events. Our models lack the "reflares" seen in one-dimensional calculations. Resolving full vertical disk structure is essential for accurate thermal instability modeling. While thermal instability significantly influences episodic accretion, it appears insufficient alone to explain observed HMYSO outburst diversity. Additional mechanisms are required for comprehensive understanding.

astro-ph.SR↗

arXiv2025

Young Stellar Objects in the Carina nebula: Near-Infrared variability and spectroscopy

We present a catalog of 652 young stellar objects (YSOs) in the Carina star-forming region. The catalog was constructed by combining near-infrared Ks-band variability from the VISTA Variables in the Via Lactea eXtended survey and medium-resolution H-band spectroscopy from APOGEE-2, Sloan Digital Sky Survey IV (SDSS-IV). Variability analysis of 6.35 million sources identified 606 variable stars. The classification of the spectral lines by semisupervised K-means clustering of 704 stars, refined through comparison with known catalogs in literature and visual inspection of the spectra, was performed. Combined with Ks variability, the final catalog contains three groups: Emission-line YSOs, Absorption-line YSOs, and Literature/Variable-identified YSOs. Cross validation with the Gaia DR3 proper motion and distance estimates supports Carina membership for 415 sources. The statistical characterization of YSO variability demonstrated that most Carina members (78%) exhibit variability patterns. Of these, 134 stars show emissions in their spectra, which is consistent with some accretion processes. Analysis of fundamental stellar parameters from StarHorse and Gaia DR3 reveals typical distributions of YSOs, dominated by low-mass 1-4 Msun, solar-metallicity stars with temperatures between 4000 and 6000K. Only a small fraction (4%) of the sources are more massive than 4 Msun, suggesting limited ongoing massive star formation in Carina. This well-characterized catalog also offers a robust training dataset for machine learning applications aimed at predicting YSO behavior.

astro-ph.SR↗

arXiv2025

Discovery of a variable yellow supergiant progenitor for the Type IIb SN 2024abfo

We report the discovery of a progenitor candidate for the Type~IIb SN2024abfo using multi-epoch pre-explosion images from the Hubble Space Telescope and the Dark Energy Camera Legacy Survey. The progenitor exhibited a ~0.7 mag decline in F814W from 2001 to 2013, followed by significant brightening and color fluctuations in the g, r and z bands. This is the first time that substantial photometric variability has been found for the progenitor of a SN IIb. We suggest that the variability is caused by intrinsic changes in the progenitor star instead of varying obscuration by circumstellar dust. Our results show that the progenitor of SN2024abfo was likely a yellow supergiant star with an initial mass of 12--18 Msun for circumstellar reddening of E(B-V)_CSM < 0.2 mag. Our study underscores the critical role of multi-epoch imaging surveys in revealing the final stages of core-collapse supernovae progenitors.

astro-ph.HE↗

arXiv2025

Synthetic Data RL: Task Definition Is All You Need

Reinforcement learning (RL) is a powerful way to adapt foundation models to specialized tasks, but its reliance on large-scale human-labeled data limits broad adoption. We introduce Synthetic Data RL, a simple and general framework that reinforcement fine-tunes models using only synthetic data generated from a task definition. Our method first generates question and answer pairs from the task definition and retrieved documents, then adapts the difficulty of the question based on model solvability, and selects questions using the average pass rate of the model across samples for RL training. On Qwen-2.5-7B, our method achieves a 29.2% absolute improvement over the base model on GSM8K (+2.9 pp vs. instruction-tuned, +6.6 pp vs. Self-Instruct), 8.7% on MATH, 13.1% on GPQA (+7.0 pp vs. SynthLLM), 8.9% on MedQA, 17.7% on CQA (law) and 13.7% on CFA (finance). It surpasses supervised fine-tuning under the same data budget and nearly matches RL with full human data across datasets (e.g., +17.2 pp on GSM8K). Adding 100 human demonstrations improves the performance of GSM8K only by 0.4 pp, showing a limited added value. By reducing human data annotation, Synthetic Data RL enables scalable and efficient RL-based model adaptation. Code and demos are available at https://github.com/gydpku/Data_Synthesis_RL/.

cs.CL↗

arXiv2025

"Oh FUors where art thou": A search for long-lasting YSO outbursts hiding in infrared surveys

Long-lasting episodes of high accretion can strongly impact stellar and planetary formation. However, the universality of these events during the formation of young stellar objects (YSOs) is still under debate. Accurate statistics of strong outbursts (FUors), are necessary to understand the role of episodic accretion bursts. In this work, we search for a population of FUors that may have gone undetected in the past because they either a) went into outburst before the start of modern monitoring surveys and are now slowly fading back into quiescence or b) are slow-rising outbursts that would not commonly be classified as candidate FUors. We hypothesise that the light curves of these outbursts should be well fitted by linear models with negative (declining) or positive (rising) slopes. The analysis of the infrared light curves and photometry of $\sim$99000 YSO candidates from SPICY yields 717 candidate FUors. Infrared spectroscopy of 20 candidates, from both the literature and obtained by our group, confirms that 18 YSOs are going through long-term outbursts and identifies two evolved sources as contaminants. The number of candidate FUors combined with previously measured values of the frequency of FUor outbursts, yield average outburst decay times that are 2.5 times longer than the rise times. In addition, a population of outbursts with rise timescales between 2000 and 5000 days must exist to obtain our observed number of YSOs with positive slopes. Finally, we estimate a mean burst lifetime of between 45 and 100 years.

astro-ph.SR↗

arXiv2025

Confirmation of a ring structure in the disk around MP Mus (PDS 66) with ALMA Band 7 observations

Young stellar objects (YSOs) are surrounded by protoplanetary disks, which are the birthplace of young planets. Ring and gap structures are observed among evolved protoplanetary disks, often interpreted as a consequence of planet formation. The pre-Main Sequence (pre-MS) star MP Mus hosts one of the few known examples of protoplanetary disks within ~100 pc. Previously, a disk ring structure, with a radius of 80-85 au, was detected in scattered light via near-infrared coronographic/polarimetric imaging. This ring structure may be indicative of the disk clearing process. Although such ring structures were not seen in the ALMA Band 6 images, some features were detected at $\sim$50 au. In this paper, we analyzed new ALMA Band 7 observations of MP Mus in order to investigate the details of its disk substructures. By subtracting the continuum profile generated from Band 7 data, we discovered a ring structure in the Band 7 dust continuum image at $\sim$50 au. We calculated the overall dust mass as $28.4\pm2.8 M_{\oplus}$ at 0.89 mm and $26.3\pm2.6 M_{\oplus}$ at 1.3 mm and the millimeter spectral index $α_{0.89-1.3mm} \sim 2.2 \pm 0.3$ between 0.89 mm and 1.3 mm. Moreover, we display the spatial distribution of the spectral index ($α_{mm}$), estimating values ranging from 1.3 at the inner disk to 4.0 at a large radius. Additionally, we observed an extended gas disk up to $\sim$120 au, in contrast with a compact continuum millimeter extent of $\sim$60 au. We conclude that there are strong indicators for an active radial drift process within the disk. However, we cannot discard the possibility of a dust evolution process and a grain growth process as responsible for the outer disk structures observed in the ALMA continuum imaging.

astro-ph.SR↗

arXiv2025

Subaru Hyper-Supreme Cam observations of IC 1396: Source catalogue, member population, and sub-clusters of the complex

To identify member populations of IC 1396, we employ the random forest (RF) classifier of machine learning technique. Random forest classifier is an ensemble of individual decision trees suitable for large, high-dimensional datasets. The training set used in this work is derived from previous Gaia-based studies, where the member stars are younger than $\sim$ 10~Myr. However, its sensitivity is limited to $\sim$ 20~mag in the $\rm r_2$ band, making it challenging to identify candidates at the fainter end. In this analysis, in addition to magnitudes and colours, we incorporate several derived parameters from the magnitude and colour of the sources to identify candidate members of the star-forming complex. By employing this method, we are able to identify promising candidate member populations of the star-forming complex. We discuss the associated limitations and caveats in the method and for improvment in future studies. In this analysis, we identify 2425 high-probability low-mass stars distributed within the entire star-forming complex, of which 1331 are new detections. Comparison of these identified member populations shows a high retrieval rate with Gaia-based literature sources, as well as sources detected through methods based on optical spectroscopy, Spitzer, $\rm H_α/X-ray$ emissions, optical, and 2MASS photometry. The mean age of the member populations is $\rm \sim 2-4~Myr$, consistent with findings from previous studies. Considering the identified member populations, we present preliminary results by exploring the presence of sub-clusters within IC 1396, assessing the possible mass limit of the member populations, and providing a brief discussion on the star formation history of the complex.

astro-ph.GA↗

arXiv2025

ByteQC: GPU-Accelerated Quantum Chemistry Package for Large-Scale Systems

Applying quantum chemistry algorithms to large-scale systems requires substantial computational resources scaled with the system size and the desired accuracy. To address this, ByteQC, a fully-functional and efficient package for large-scale quantum chemistry simulations, has been open-sourced at https://github.com/bytedance/byteqc, leveraging recent advances in computational power and many-body algorithms. Regarding computational power, several standard algorithms are efficiently implemented on modern GPUs, ranging from mean-field calculations (Hartree-Fock and density functional theory) to post-Hartree-Fock methods such as Møller-Plesset perturbation theory, random phase approximation, coupled cluster methods, and quantum Monte Carlo methods. For the algorithmic approach, we also employ a quantum embedding method, which significantly expands the tractable system size while preserving high accuracy at the gold-standard level. All these features have been systematically benchmarked. For standalone algorithms, the benchmark results demonstrate up to a 60$\times$ speedup when compared to 100-core CPUs. Additionally, the tractable system sizes have been significantly expanded: 1,610 orbitals for coupled cluster with single and double excitations (1,380 orbitals with perturbative triple excitations), 11,040 orbitals for Møller-Plesset perturbation theory of second order, 37,120 orbitals for mean-field calculations under open boundary conditions, and over 100,000 orbitals for periodic boundary conditions. For the advanced quantum embedding feature, two representative examples are demonstrated: the water cluster problem (2,752 orbitals) and a water monomer adsorbed on a boron nitride surface (3,929 orbitals), achieving the gold-standard accuracy.

physics.chem-ph↗

arXiv2025

Evidence of a Disk-wind Origin for Fluorescent H$_2$ in Classical T Tauri Stars

We use FUV spectra of 36 T Tauri stars, predominately from $\textit{Hubble Space Telescope}$'s ULLYSES program, to examine the kinematic properties of fluorescent H$_2$ emission lines for evidence of disk outflows. Leveraging improvements to the $\textit{HST}$-COS wavelength solution, we co-add isolated lines within four fluorescent progressions ([$\textit{v'}$,$\textit{J'}$] = [1,4], [1,7], [0,2], and [3,16]) to improve signal-to-noise, and we fit each co-added line profile with one or two Gaussian components. Of the high S/N line profiles (S/N $\geq$ 12 at the peak of the profile), over half are best fit with a combination of a broad and narrow Gaussian component. For profiles of the [1,4] and [1,7] progressions, we find a systematic blue-shift of a few km s$^{-1}$ between the broad and narrow centroid velocities and stellar radial velocities. For the [0,2] progression, we find centroid velocities consistently blueshifted with respect to stellar radial velocities on the order of -5 km s$^{-1}$ for the single and narrow components, and -10 km s$^{-1}$ for the broad components. Overall, the blueshifts observed in our sample suggest that the molecular gas traces an outflow from a disk wind in some sources, and not solely disk gas in Keplerian rotation. The low-velocity systematic blue-shifts, and emitting radii as inferred from line FWHMs, observed in our sample are similar to those observed with optical [O I] surveys of T Tauri stars. We estimate H$_2$ mass-loss rates of 10$^{-9}$ to 10$^{-11}$ $M_{\odot}$ yr$^{-1}$, but incomplete knowledge of wind parameters limits comparisons to global models.

astro-ph.SR↗

arXiv2025

API Pack: A Massive Multi-Programming Language Dataset for API Call Generation

We introduce API Pack, a massive multi-programming language dataset containing over one million instruction-API calls for improving the API call generation capabilities of large language models. Our evaluation highlights three key findings: First, fine-tuning on API Pack enables open-source models to outperform GPT-3.5 and GPT-4 in generating code for entirely new API calls. We show this by fine-tuning CodeLlama-13B on 20,000 Python instances from API Pack. Second, fine-tuning on a large dataset in one language, combined with smaller datasets from others, improves API generation accuracy across multiple languages. Third, we confirm the benefits of larger datasets for API generalization, as increasing fine-tuning data to one million instances enhances generalization to new APIs. To support further research, we open-source the API Pack dataset, trained model, and code at https://github.com/zguo0525/API-Pack.

cs.CL↗

arXiv2025

Variable stars in the VVV globular clusters III. RR Lyrae stars in the inner Galactic globular clusters

High reddening near the Galactic plane hampers observations and proper characterization of the globular clusters (GCs) located toward the inner regions of the Milky Way. The VISTA Variables in the Via Lactea (VVV) survey observed the Galactic bulge and adjacent disk for several years, providing multi-epoch, near-infrared images for 41 Galactic GCs. Detecting RRLyrae variables belonging to these GCs will aid in their accurate parameterization. By fully leveraging the astrometric, photometric, and variability VVV catalogs, we searched for RRLyrae stars associated with GCs. Our selection criteria, based on proper motions, proximity to the cluster centers, and distances inferred from their period-luminosity-metallicity relations, enable us to accurately identify the RRLyrae population in these GCs and determine color excesses and distances in a homogeneous manner. Since the VVV catalogs cover from the innermost regions of the GCs to their outskirts, we can provide a comprehensive picture of the entire RRLyrae population in these GCs. We have discovered significant RRLyrae populations in two highly reddened Galactic GCs: UKS1 and VVV-CL160, previously unknown to host RRLyrae stars. Additionally, we have detected one RRLyrae candidate in each of Terzan4 and Terzan9, also new to RRLyrae detection. We further confirm and increase the number of RRLyrae stars detected in 22 other low-latitude Galactic GCs. The RRLyrae distances place most of these GCs within the Galactic bulge, aligning well with the few GCs in our sample with reliable Gaia or Hubble Space Telescope measurements. However, most of the VVV GCs lack accurate Gaia distances, and literature distances are generally significantly smaller than those derived in this work. As a byproduct of our analysis, we have obtained the proper motions for all the VVV GCs, independently confirming Gaia results, except for UKS1 and 2MASS-GC02.

astro-ph.GA↗

arXiv2025

Advancing Surface Chemistry with Large-Scale Ab-Initio Quantum Many-Body Simulations

Predictive simulation of surface chemistry is of paramount importance for progress in fields from catalysis to electrochemistry and clean energy generation. Ab-initio quantum many-body methods should be offering deep insights into these systems at the electronic level, but are limited in their efficacy by their steep computational cost. In this work, we build upon state-of-the-art correlated wavefunctions to reliably converge to the `gold standard' accuracy in quantum chemistry for application to extended surface chemistry. Efficiently harnessing graphics processing unit acceleration along with systematically improvable multiscale resolution techniques, we achieve linear computational scaling up to 392 atoms in size. These large-scale simulations demonstrate the importance of converging to these extended system sizes, achieving a validating handshake between simulations with different boundary conditions for the interaction of water on a graphene surface. We provide a new benchmark for this water-graphene interaction that clarifies the preference for water orientations at the graphene interface. This is extended to the adsorption of carbonaceous molecules on chemically complex surfaces, including metal oxides and metal-organic frameworks, where we consistently achieve chemical accuracy compared to experimental references, and well inside the scatter of traditional density functional material modeling approaches. This pushes the state of the art for simulation of molecular adsorption on surfaces, and marks progress into a post-density functional era for more reliable and improvable approaches to first-principles modeling of surface problems at an unprecedented scale and accuracy using ab-initio quantum many-body methods.

cond-mat.mtrl-sci↗

arXiv2024

Detection of an Orphan X-ray Flare from a Blazar Candidate EP240709a with Einstein Probe

Blazars are often observed to flare across multiple wavelengths. Orphan flares from blazars have been only detected a few times, providing an opportunity to understand the structure of the jet in the accreting system. We report a remarkable orphan X-ray flare from a blazar candidate EP240709a, detected by Einstein Probe (EP) in July 2024. The multi-band spectral properties and variability support EP240709a as a high-energy peaked BL Lacertae-type object. The flux in 0.5-10 keV increases by at least 28 times to the value of low state in 2020, with non-detection of remarkable flaring in other bands during the same period. EP240709a exhibits the harder-when-brighter tendency in the X-ray band during the orphan flare, while its infrared-optical spectra are featureless. We employ one-zone and two-zone leptonic synchrotron self-Compton models to perform the spectral energy distribution fitting. Detecting this rare orphan flare shows the potential of EP in discovering peculiar activities from AGN in high-cadence X-ray sky surveys.

astro-ph.HE↗