arXiv subjects

Qiang Xi

Publications and source records attributed to Qiang Xi.

13 recordsLinked to original sources

arXiv2026

SN 2023fyq: direct detection of a Type Ibn supernova progenitor and its multi-wavelength environmental constraints

Context. Type Ibn supernovae (SNe) are characterized by narrow helium emission lines arising from ejecta-circumstellar medium interaction, yet their progenitors remain debated, with both massive Wolf-Rayet stars and low-mass helium stars in binaries proposed. Aims. We aim to directly identify the progenitor of the Type Ibn SN 2023fyq and to characterize its environment in order to constrain the progenitor's nature and evolutionary channel. Methods. We search for the SN progenitor based on pre-explosion and late-time HST and JWST images and derive its properties by fitting the spectral energy distribution. We investigate the SN environment by probing the stars, dust, ionized gas and molecular gas with a multi-wavelength dataset including HST and JWST imaging, VLT/MUSE integral-field-unit spectroscopy and ALMA CO (2--1) radio interferometry. Results. We discover a pre-explosion source at the SN position, which is consistent with a hot ($T>$15000 K) and luminous (log($L$/$L_\odot$) $\gtrsim$ 5.5) SN progenitor and a possible host star cluster. The progenitor is confirmed to have disappeared after explosion. Analysis of the SN environment implies that the progenitor likely has an age of log($t$/yr) = 7.1--7.2. These phenomena disfavor a very massive single-star progenitor and instead support a binary scenario involving a low-mass helium star and a compact object; the observed progenitor emission likely arises from binary interaction that began at least $\sim$12 yr before the explosion. Conclusions. SN 2023fyq is the first Type Ibn SN with a directly detected progenitor and a possible host star cluster. It adds to the diversity of Type Ibn SNe in terms of their progenitor channels and mass-loss mechanisms.

astro-ph.SR↗

arXiv2026

An improved PINN framework integrating localized collocation scheme and PIKF

We propose a localized physics-informed kernel function neural network (LPIKFNN), which is an improved physics-informed neural network (PINN) based on physics-informed kernel function (PIKF). In the LPIKFNN framework, the localized collocation scheme discretizes the physical quantities within the local domain, where the physical field is represented as a linear combination of PIKFs. Based on this representation, the multilayer perceptron is trained to iteratively learn the physical quantities. To overcome the computational challenges of conventional PINN in higher-order derivative and high wavenumber problems, the LPIKFNN constructs the loss function using the PIKF and a localized collocation scheme rather than relying on automatic differentiation. As a result, the costly derivative evaluations required to enforce governing equations during iterative training are eliminated, leading to significantly improved computational efficiency and training performance. Moreover, incorporating PIKFs into the loss function enables the proposed LPIKFNN to significantly improve computational accuracy in high-wavenumber problems characterized by highly oscillatory physical fields. To overcome the computational bottleneck of the physics-informed kernel function neural network (PIKFNN) in heterogeneous problems, the LPIKFNN introduces a localized collocation scheme that removes reliance on global PIKFs, enabling accurate predictions where global PIKFs are unavailable. The feasibility and accuracy of the proposed LPIKFNN are demonstrated through a series of benchmark studies, including high wavenumber problems, higher-order derivative problems, nonlinear problems, heterogeneous problems, and potential-based inverse electromyography. The numerical predictions obtained by LPIKFNN show excellent agreement with available analytical solutions and experimental measurements.

cs.CE↗

arXiv2026

Virtual boundary integral neural network for three-dimensional exterior acoustic problems

This paper presents a virtual boundary integral neural network (VBINN) for exterior acoustic problems in three dimensions. The method introduces a virtual boundary inside the scatterer or vibrating body and represents the associated source density with a neural network. Coupled with the acoustic fundamental solution, this representation satisfies the Sommerfeld radiation condition by construction and enables direct evaluation of the acoustic pressure and its normal derivative at arbitrary field points. Because the integration surface is separated from the physical boundary, the formulation avoids the singular and near singular kernel evaluations associated with coincident source and collocation points in conventional boundary integral learning methods. To reduce sensitivity to boundary placement, the geometric parameters of the virtual boundary are optimized jointly with the source density during training. Numerical examples for acoustic scattering, multiple body interaction, and underwater acoustic propagation show close agreement with analytical solutions and COMSOL results, and the Burton Miller extension further improves stability near characteristic frequencies. These results demonstrate the potential of VBINN for exterior acoustic analysis in three dimensions.

cs.SD↗

arXiv2026

A statistical study of the environmental age of core-collapse supernovae based on VLT/MUSE integral-field-unit spectroscopy

We aim to understand the progenitor channels of CCSNe via a statistical study of the ages of their environments. We compiled a large and minimally biased sample of 128 CCSNe discovered by untargeted wide-field transient surveys and with archival VLT/MUSE integral-field-unit spectroscopy. We measured the local H{\alpha} luminosity within a 300-pc aperture centered on the SN explosion site as an empirical proxy for the environmental age. We find that the mean local H$\alpha$ luminosities are ordered as II(P) $\approx$ IIb $\lesssim$ Ib $<$ Ic. The differences among Types~II(P), IIb and Ib are very small, if any. Type~Ic SNe are located in clearly younger environments than the other types. Our result suggests that Type Ic SNe have much younger and more massive progenitors than the other CCSN types and they likely originate from a distinct progenitor channel. The distinction between Types II(P), IIb and Ib SNe is insensitive to progenitor mass and mainly due to the different binary separation; in contrast, Type Ic SNe predominantly require much higher-mass progenitors accompanied by close companions with large mass ratios and/or much stronger stellar wind that depends sensitively on progenitor mass.

astro-ph.SR↗

arXiv2026

SN 2024abfl: A Low-Luminosity Type IIP Supernova in NGC 2146 from a Low-Mass Red Supergiant Progenitor

Type IIP supernovae (SNe IIP) exhibit a significant diversity in their explosion properties, yet the physical mechanisms driving this diversity remain unknown. In this work, we present photometric and spectroscopic observations of SN 2024abfl, a SN IIP in NGC 2146 with a directly detected red supergiant (RSG) progenitor. We find it has a low plateau luminosity ($M_V \sim -15$ mag) and a relatively long plateau length ($\sim 126.5$ days). By fitting a semi-analytical model, we estimated a $^{56}$Ni mass of $\sim 0.009 M_\odot$, an initial kinetic energy of $\sim 0.42$ foe, an initial thermal energy of $\sim 0.03$ foe and an ejecta mass of $\sim 8.3 M_\odot$. The spectral evolution of SN 2024abfl is similar to those of other SNe IIP, except for much lower ejecta velocities at similar epochs. At later epochs, we find a relatively high-velocity H$\alpha$ absorption feature at $\sim -4000$ km s$^{-1}$, possibly due to a fast-moving plume of matter in the inner ejecta, and two emission features at $\pm 2000$ km s$^{-1}$, possibly caused by CSM interaction. We estimate the progenitor mass to be $\le 15 M_\odot$ based on nebular spectra. We conclude that SN 2024abfl is a low-luminosity SN IIP originating from a low-mass RSG progenitor.

astro-ph.HE↗

arXiv2026

Direct Detection of Type II-P Supernova Progenitors with the $\textit{Euclid}$ and CSST Surveys

Identifying and characterizing supernova (SN) progenitor stars remains a central yet difficult goal in SN research, limited by archival images lacking sufficient depth or spatial resolution and circumstellar dust biasing intrinsic parameter estimates. This field will be revolutionized by $\textit{Euclid}$ and the upcoming Chinese Space-station Survey Telescope (CSST), which conduct deep, wide-field, high-resolution and multi-band imaging surveys. We evaluate their detection capability by comparing model magnitudes of RSG progenitors with detection limits, finding their optical and near-infrared filters highly effective. Monte-Carlo simulations predict that completed $\textit{Euclid}$ and CSST surveys will enable $\lesssim$13 (or 24) progenitor detections per year within the mass range of 8--16 (or 8--25)\,$M_\odot$, an order of magnitude higher than the current detection rate of $\sim$1 per year (primarily based on HST). With the circumstellar dust, the emerging spectral energy distribution (SED) of the SN progenitor is mainly affected by the optical depth and is almost independent of dust temperature in their survey filters. Mock tests demonstrate that the progenitor mass and dust optical depth can be derived simultaneously by fitting the observed SED over 11 survey filters while fixing dust temperature to a typical value. $\textit{Euclid}$ and CSST will significantly enlarge the sample of direct progenitor detections with accurate mass measurements, crucial for resolving the long-standing RSG problem.

astro-ph.SR↗

arXiv2025

SN 2025coe: A Multiple-Peaked Calcium-Strong Transient from A White-Dwarf Progenitor

SN 2025coe is a calcium-strong transient located at an extremely large projected offset $\sim$39.3 kpc from the center of its host, the nearby early-type galaxy NGC 3277 at a distance of $\sim$25.5 Mpc. In this paper, we present multi-band photometric and spectroscopic observations spanning $\sim$100 days post-discovery. Its multi-band light curves display {multiple} distinct peaks: (1) an initial peak at $t \approx 1.6$ days attributed to shock cooling emission, (2) a secondary peak of $M_{R, \, peak} \approx$ $-$15.8 mag at $t \approx 10.2$ days powered by radioactive decay, and (3) a {possible} late-time bump at $t \approx 42.8$ days likely caused by ejecta-circumstellar material/clump interaction. Spectral evolution of SN 2025coe reveals a fast transition to the nebular phase within 2 months, where it exhibits an exceptionally high [Ca II]/[O I] ratio larger than 6. Modeling of the bolometric light curve suggests an ejecta mass of $M_{\rm ej} = 0.29^{+0.14}_{-0.15} \, M_{\odot}$, a $^{56}$Ni mass of $M_{\rm ^{56}Ni} = 2.4^{+0.06}_{-0.05} \times 10^{-2} M_{\odot}$, and a progenitor envelope with mass $M_e = 1.4^{+6.9}_{-1.2} \times 10^{-3} \, M_{\odot}$ and radius $R_e = 13.5^{+64.1}_{-11.1} \, R_{\odot}$. The tidal disruption of a hybrid HeCO white dwarf (WD) by a low-mass CO WD provides a natural explanation for the low ejecta mass, the small fraction of $^{56}$Ni, and the presence of an extended, low-mass envelope.

astro-ph.HE↗

arXiv2025

SN 2024aecx: a fast-evolving Type IIb supernova with a prominent shock-cooling peak

SN 2024aecx is a nearby ($\sim$11 Mpc) Type IIb SN discovered within $\sim$1 d after explosion. In this paper we report high-cadence photometric (typically 0.5$\sim$1 day) and spectroscopic follow-up observations, conducted from as early as 0.27 d post discovery out to the nebular phase at 158.4 d. We analyze the environment of SN 2024aecx and derive a new distance (11.3$\pm$1.1 Mpc), metallicity and host extinction. The light curve exhibits a hot and luminous shock-cooling peak at the first few days, followed by a main peak with very rapid post-maximum decline. The earliest spectra are blue and featureless, while from 2.3 d after discovery prominent P-Cygni profiles emerge. At nebular phase, the emission lines exhibit asymmetric and double-peaked profiles, indicating asphericity and/or early dust formation in the ejecta. Nebular spectral modelling indicates a blueshifted O-rich clump moving toward observer, and the $[\text{OI}]/[\text{CaII}]$ line ratio suggests an intermediate-mass progenitor. We simulated the progenitor and explosion using a two-component model of shock cooling and radioactive $^{56}$Ni heating; our model favors an extended, low-mass H-rich envelope with $M_{\mathrm{e}} = 0.04\pm{0.01} M_{\odot}$ and a low ejecta mass of$M_{\mathrm{ej}} = 1.55^{+0.18}_{-0.14} M_{\odot}$. And the nebular-phase spectra and light-curve modelling both suggest that it most likely originated from an intermediate-mass binary progenitor system. The comprehensive monitoring of SN 2024aecx, coupled with the detailed characterization of its local environment, establishes it as a benchmark event for probing the progenitors and explosion mechanisms of Type IIb SNe.

astro-ph.SR↗

arXiv2024

A statistical study of the metallicity of core-collapse supernovae based on VLT/MUSE integral-field-unit spectroscopy

Metallicity plays a crucial role in the evolution of massive stars and their final core-collapse supernova (CCSN) explosions. Integral-field-unit (IFU) spectroscopy can provide a spatially resolved view of SN host galaxies and serve as a powerful tool to study SN metallicities. While early transient surveys targeted on high star formation rate and metallicity galaxies, recent untargeted, wide-field surveys (e.g., ASAS-SN, ZTF) have discovered large numbers of SNe without this bias. In this work, we construct a large sample of SNe discovered by wide-field untargted searches, consisting of 166 SNe of Types II(P), IIn, IIb, Ib and Ic at $z \leq 0.02$ with VLT/MUSE observations. This is currently the largest CCSN sample with IFU observations. With the strong-line method, we reveal the spatially-resolved metallicity maps of the SN host galaxies and acquire accurate metallicity measurements for the SN sites, finding a range from $12 + \log(\text{O/H}) = 8.1$ to 8.7 dex. And the metallicity distributions for different SN types are very close to each other, with mean and median values of 8.4--8.5 dex. Our large sample size narrows the 1$\sigma$ uncertainty down to only 0.05 dex. The apparent metallicity differences among SN types are all within $\sim$1$\sigma$ uncertainties and the metallicity distributions for different SN types are all consistent with being randomly drawn from the same reference distribution. This suggests that metallicity plays a minor role in the origin of different CCSN types and some other metallicity-insensitive processes, such as binary interaction, dominate the distinction of CCSN types.

astro-ph.GA↗

arXiv2024

Exclusion of a direct progenitor detection for the Type Ic SN 2017ein based on late-time observations

To date, SN 2017ein is the only Type Ic supernova with a directly identified progenitor candidate. This candidate points to a very massive ($>$45 $M_\odot$) Wolf-Rayet progenitor, but its disappearance after the explosion of SN 2017ein remains unconfirmed. In this work, we revisit SN 2017ein in late-time images acquired by the Hubble Space Telescope (HST) at 2.4--3.8 yrs after peak brightness. We find this source has not disappeared and its brightness and color remain almost the same as in the pre-explosion images. Thus, we conclude that the pre-explosion source is not the genuine progenitor of SN 2017ein. We exclude the possibility that it is a companion star of the progenitor, since it has a much lower extinction than SN 2017ein; its color is also inconsistent with a star cluster, indicated by the newly added magnitude limit in F336W, apart from F555W and F814W. We suggest, therefore, this source is an unrelated star in chance alignment with SN 2017ein. Based on the low ejecta mass, we propose that SN 2017ein is most likely originated from a moderately massive star with $M_{\rm ini}$ $\sim$ 8--20 $M_\odot$, stripped by binary interaction, rather than a very massive Wolf-Rayet progenitor.

astro-ph.HE↗

arXiv2024

Constraining the progenitor of the nearby Type II-P SN 2024ggi with environmental analysis

The progenitors of Type II-P supernovae (SN) have been confirmed to be red supergiants. However, the upper mass limit of the directly probed progenitors is much lower than that predicted by current theories, and the accurate determination of the progenitor masses is key to understand the final fate of massive stars. Located at a distance of only 6.72 Mpc, the Type II-P SN 2024ggi is one of the closest SN in the last decade. Previous studies have analyzed its progenitor by direct detection, but the derived progenitor mass may be influenced by the very uncertain circumstellar extinction and pulsational brightness variability. In this work, we try to constrain the progenitor mass with an environmental analysis based on images from the Hubble Space Telescope. We found that stars in the progenitor environment have a uniform spatial distribution without significant clumpiness, and we derived the star formation history of the environment with a hierarchical Bayesian method. The progenitor is associated with the youngest population in the SN environment with an age of log($t$/yr) = 7.41 (i.e. 25.7 Myr), which corresponds to an initial mass of $10.2^{+0.06}_{-0.09}$ $M_\odot$. Our work provides an independent measurement of the progenitor mass, which is not affected by circumstellar extinction and pulsational brightness variability.

astro-ph.SR↗

arXiv2024

Derivative Spectroscopy and its Application at Detecting the Weak Emission/Absorption Lines

The development of spectroscopic survey telescopes like Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), Apache Point Observatory Galactic Evolution Experiment and Sloan Digital Sky Survey has opened up unprecedented opportunities for stellar classification. Specific types of stars, such as early-type emission-line stars and those with stellar winds, can be distinguished by the profiles of their spectral lines. In this paper, we introduce a method based on derivative spectroscopy (DS) designed to detect signals within complex backgrounds and provide a preliminary estimation of curve profiles. This method exhibits a unique advantage in identifying weak signals and unusual spectral line profiles when compared to other popular line detection methods. We validated our approach using synthesis spectra, demonstrating that DS can detect emission signals three times fainter than Gaussian fitting. Furthermore, we applied our method to 579,680 co-added spectra from LAMOST Medium-Resolution Spectroscopic Survey, identifying 16,629 spectra with emission peaks around the H{\alpha} line from 10,963 stars. These spectra were classified into three distinct morphological groups, resulting in nine subclasses as follows. (1) Emission peak above the pseudo-continuum line (single peak, double peaks, emission peak situated within an absorption line, P Cygni profile, Inverse P Cygni profile); (2) Emission peak below the pseudo-continuum line (sharp emission peak, double absorption peaks, emission peak shifted to one side of the absorption line); (3) Emission peak between the pseudo-continuum line.

astro-ph.SR↗

arXiv2023

FEM-PIKFNNs for underwater acoustic propagation induced by structural vibrations in different ocean environments

In this paper, a novel hybrid method based on the finite element method (FEM) and physics-informed kernel function neural networks (PIKFNNs) is proposed and applied to the prediction of underwater acoustic propagation induced by structural vibrations in the unbounded ocean, deep ocean and shallow ocean. In the hybrid method, PIKFNNs are a class of improved shallow physics-informed neural networks (PINNs) that replace the activation functions in PINNs with the physics-informed kernel functions (PIKFs), thereby integrating prior physical information into the neural network model. Moreover, this neural network circumvents the step of embedding the governing equations into the loss function in PINNs, and requires only training on boundary data. By using the Green's functions as the PIKFs and the structural-acoustic coupling response information obtained from the FEM as boundary training data, the PIKFNNs can inherently capture the Sommerfeld radiation condition at infinity, which is naturally suitable for predicting ocean acoustic propagation. Numerical experiments demonstrate the accuracy and feasibility of the FEM-PIKFNNs in comparison with the true solutions and finite element results.

math.NA↗