arXiv subjects

Tianmeng Zhang

Publications and source records attributed to Tianmeng Zhang.

At least 19 recordsLinked to original sources

arXiv2026

Comparative analysis of missing data imputation methods for CSST survey: Impact on photometric redshift estimation performance

Improving the accuracy of photometric redshifts (photo-$z$) is essential for reliable statistical studies of cosmology and galaxy evolution. However, missing photometric bands are a common observational challenge that can significantly degrade photo-$z$ estimation accuracy. In this work, we present a systematic evaluation of data imputation methods aimed at improving photo-$z$ performance. We benchmark a range of representative machine learning (ML) and deep learning (DL) architectures, identifying k-nearest neighbors (KNN) and the attention-based SAITS model as the leading performers. These models are then applied to China Space Station Survey Telescope (CSST) mock data to assess their performance under realistic observational conditions. Our results show that KNN yields the highest accuracy under idealized missing completely at random (MCAR) conditions with complete training sets, whereas robustness tests reveal that SAITS significantly outperforms KNN when training data is incomplete or when applied to realistic mixed-mechanism scenarios. We find that domain consistency between training and testing missingness patterns is a prerequisite for optimal performance, highlighting the risks of domain shift in supervised regression tasks. Furthermore, our analysis demonstrates that while general imputation models are highly effective for MCAR and missing at random (MAR) data, they are detrimental when applied to missing not at random (MNAR) data arising from flux limits, as statistical models fail to capture the physical information inherent in these non-detections. Consequently, we advocate for more sophisticated architectures capable of disentangling stochastic missingness from physical non-detections to address these distinct mechanisms individually.

astro-ph.GA↗

arXiv2026

A Multi-modal Fusion Network for Star-Galaxy Classification from CSST Simulated Datasets

The distinction between stars and galaxies is a fundamental problem in the field of celestial classification. This issue has become challenging for these ongoing and upcoming digital surveys, which will produce terabytes and even petabytes of astronomical data. While deep learning offers a powerful solution for star-galaxy classification in large-scale datasets, most current approaches are limited by their reliance on catalog data alone, which consists primarily of multi-band magnitudes and imprecise morphological parameters. Therefore, we utilize China Space Station Telescope (CSST) simulation data to build a dataset with both image and photometric catalog, including 32,371 stars and 93,525 galaxies. A supervised deep learning network based on ResNet-50 and BiLSTM is proposed to improve the classification of two types of astronomical objects. The features of the catalog and image are integrated by the model, achieving 99.81% recall for galaxies and 99.66% recall for stars after training on GPU for 50 epochs. We evaluated the effects of data augmentation and multi-modal data fusion, which demonstrate that our model has commendable performance. Furthermore, our model also has a high accuracy rate for faint astronomical objects and high redshift galaxies, demonstrating its applicability to the upcoming CSST scientific data.

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arXiv2026

Spectral Dataset of Stripped-Envelope Supernovae from the Tsinghua Supernova Group

The extent of envelope stripping in the progenitor stars is directly reflected in the diversity of spectral features observed in stripped-envelope supernovae (SESNe). Through extensive spectral observation and analysis, we aim to clarify the statistical differences between the subclasses of SESNe. The Tsinghua Supernova group obtained 249 optical spectra of 62 SESNe during the years from 2010 to 2020, covering phases from $-$16 to over 190 days relative to maximum light. Most spectra were obtained during the photospheric phases after the supernova explosion. For each spectrum, the pseudo-equivalent widths (pEWs) and blueshift velocities of principal lines were measured. We further investigated the common spectral features by analysing their velocity and strength correlations across all subtypes. We identify the feature near 6200~Å in SNe Ib as H$\mathrmα$ through comparison with SNe IIb and Ic, which resolves inconsistent literature interpretations. Our finding reveals prevalent residual hydrogen in SNe Ib, further supporting a continuous stripping sequence from SNe IIb to Ib. We observe a trend in increasing velocity among different subtypes of stripped-envelope SNe, with SNe IIb exhibiting the lowest line velocities, followed by Ib, Ic, and Ic-BL. Typically, the O~I lines in SNe Ic/Ic-BL are stronger than those seen in SNe IIb/Ib. In nebular phases, the [Ca II] emission dominates over [O I] in SNe IIb/Ib while [O I] is stronger in SNe Ic, including the He-rich SN 2016coi. This spectral dichotomy implies that progenitors of SNe Ic (BL) have more massive CO cores and hence higher initial masses.

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arXiv2026

A Robust Geometric Distortion Solution for Main Survey Camera of CSST

The advancement in sensitivity and field of view of next-generation wide-field survey telescopes requires astrometric measurements with high precision, even in the presence of significant geometric distortions. To address this challenge, we develop a Weighted Polynomial Distortion Correction in 2-Phase (WPDC-2P) method. This approach enhances stellar cross-matching, incorporates distance-based weighting into the traditional polynomial fitting, and employs a look-up table to absorb the remaining distortion residuals. Validated on simulated data from the Main Survey Camera of the \emph{Chinese Space Station Survey Telescope} (CSST), incorporating geometric distortions up to approximately $200$ pixels, the method achieves astrometric standard deviation ranging from 0.013 to 0.107 pixels (0.03 pixels for the $g$-1 detector) across all 18 detectors. Under extreme crowding conditions (e.g., globular cluster NGC 2298), the astrometric precision for the $g$-1 detector reaches 0.05-pixel level within the central region ($r_d < 4000$), despite a centroiding precision of $\sim$0.04 pixels. When applied to the Beijing-Arizona Sky Survey data, for which the standard pipeline delivers an astrometric uncertainty of $\sim$20 mas, our method reduces the positional scatter to $ σ_{Δα}=5.494$ mas (0.01 pixels) and $ σ_{Δδ}=9.981$ mas (0.02 pixels) using only a weighted 3rd-order polynomial correction. The method has been integrated into the CSST data processing pipeline and is prepared for further refinement using on-orbit calibration data.

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arXiv2025

Cosmic Ray Detection and Rejection for CSST

As a space telescope, the China Space Station Survey Telescope (CSST) will face significant challenges from cosmic ray (CR) contamination. These CRs will severely degrade image quality and further influence scientific analysis. Due to the CSST's sky survey strategy, traditional multi-frame stacking methods become invalid. The limited revisits prompted us to develop an effective single-image CR processing method for CSST. We retrained the DeepCR model based on CSST simulated images and achieved 97.90+-0.18% recall and 98.67+-0.05% precision on CR detection. Moreover, this paper puts forward an innovative morphology-sensitive inpainting method, which focuses more on areas with higher scientific value. We trained a UNet++ model especially on contaminated stellar/galactic areas, alongside adaptive median filtering for background regions. This method achieves effective for CRs with different intensities and different distances from centers of scientific targets. By this approach, the photometric errors of CR-corrected targets could be restricted to the level comparable to those of uncontaminated sources. Also, it increases the detection rate by 13.6% compared to CR masking. This method will provide a robust CR mitigation for next-generation space telescopes.

astro-ph.IM↗

arXiv2025

Supernovae at Distances < 40 Mpc: I.Catalogues and fractions of Supernovae in a Complete Sample

Context.This is the first paper of a series aiming to determine the fractions and birth rates of various types of supernovae (SNe) in the local Universe. Aims. In this paper, we aim to construct a complete sample of SNe in the nearby universe and provide more precise measurement of subtype fractions. Methods.We carefully selected our SN sample at a distance of < 40 Mpc mainly from wide-field surveys conducted over the years from 2016 to 2023. Results.The sample contains a total of 211 SNe, including 109 SNe II, 69 SNe Ia, and 33 SNe Ibc. With the aid of sufficient spectra, we can obtain relatively accurate subtype classifications for all SNe in this sample. After corrections for the Malmquist bias, this volume-limited sample gives fractions of SNe Ia, SNe Ibc, and SNe II as $30.4^{+3.7}_{-11.5}\%$, $16.3^{+3.7}_{-7.4}\%$, and $53.3^{+9.5}_{-18.7}\%$, respectively.In the SN Ia sample, the fraction of the 91T-like subtype becomes relatively low (~5.4\%), while that of the 02cx-like subtype shows a moderate increase (~6.8\%). In the SN Ibc sample, we find significant fractions of broadlined SNe Ic (~18.0\%) and SNe Ibn (~8.8\%). The fraction of 87A-like subtype is determined as ~2.3\% for the first time, indicating rare explosions from blue supergiant stars. We find that SNe Ia show a double peak number distribution in S0- and Sc-type host galaxies, which may serve as a straightforward evidence for the presence of "prompt" and "delayed" progenitor components giving rise to SN Ia explosions. Several subtypes of SNe such as 02cx-like SNe Ia, broadlined SNe Ic, SNe IIn (and perhaps SNe Ibn) are found to occur preferentially in less massive spiral galaxies, favoring their associations with young stellar progenitors. Moreover, the 02cx-like subtype shows a trend of exploding in the outer skirt of their hosts, suggestive of metal-poor progenitors.

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arXiv2024

CSST Strong Lensing Preparation: a Framework for Detecting Strong Lenses in the Multi-color Imaging Survey by the China Survey Space Telescope (CSST)

Strong gravitational lensing is a powerful tool for investigating dark matter and dark energy properties. With the advent of large-scale sky surveys, we can discover strong lensing systems on an unprecedented scale, which requires efficient tools to extract them from billions of astronomical objects. The existing mainstream lens-finding tools are based on machine learning algorithms and applied to cut-out-centered galaxies. However, according to the design and survey strategy of optical surveys by CSST, preparing cutouts with multiple bands requires considerable efforts. To overcome these challenges, we have developed a framework based on a hierarchical visual Transformer with a sliding window technique to search for strong lensing systems within entire images. Moreover, given that multi-color images of strong lensing systems can provide insights into their physical characteristics, our framework is specifically crafted to identify strong lensing systems in images with any number of channels. As evaluated using CSST mock data based on an Semi-Analytic Model named CosmoDC2, our framework achieves precision and recall rates of 0.98 and 0.90, respectively. To evaluate the effectiveness of our method in real observations, we have applied it to a subset of images from the DESI Legacy Imaging Surveys and media images from Euclid Early Release Observations. 61 new strong lensing system candidates are discovered by our method. However, we also identified false positives arising primarily from the simplified galaxy morphology assumptions within the simulation. This underscores the practical limitations of our approach while simultaneously highlighting potential avenues for future improvements.

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arXiv2024

Forklens: Accurate weak-lensing shear measurement with deep learning

Weak gravitational lensing is one of the most important probes of the nature of dark matter and dark energy. In order to extract cosmological information from next-generation weak lensing surveys (e.g., Euclid, Roman, LSST, and CSST) as much as possible, accurate measurements of weak lensing shear are required. There are existing algorithms to measure the weak lensing shear on imaging data, which have been successfully applied in previous surveys. In the meantime, machine learning (ML) has been widely recognized in various astrophysics applications in modeling and observations. In this work, we present a fully deep-learning-based approach to measuring weak lensing shear accurately. Our approach comprises two modules. The first one contains a convolutional neural network (CNN) with two branches for taking galaxy images and point spread function (PSF) simultaneously, and the output of this module includes the galaxy's magnitude, size, and shape. The second module includes a multiple-layer neural network (NN) to calibrate weak-lensing shear measurements. We name the program Forklens and make it publicly available online. Applying Forklens to CSST-like mock images, we achieve consistent accuracy with traditional approaches (such as moment-based measurement and forward model fitting) on the sources with high signal-to-noise ratios (S/N, > 20). For the sources with S/N < 10, Forklens exhibits an $\sim 36\%$ higher Pearson coefficient on galaxy ellipticity measurements. After adopting galaxy weighting, the shear measurements with Forklens deliver accuracy levels to $0.2\%$. The whole procedure of Forklens is automated and costs about $0.7$ milliseconds per galaxy, which is appropriate for adequately taking advantage of the sky coverage and depth of the upcoming weak lensing surveys.

astro-ph.CO↗

arXiv2024

A spectral data release for 104 Type II Supernovae from the Tsinghua Supernova Group

We present 206 unpublished optical spectra of 104 type II supernovae obtained by the Xinglong 2.16m telescope and Lijiang 2.4m telescope during the period from 2011 to 2018, spanning the phases from about 1 to 200 days after the SN explosion. The spectral line identifications, evolution of line velocities and pseudo equivalent widths, as well as correlations between some important spectral parameters are presented. Our sample displays a large range in expansion velocities. For instance, the Fe~{\sc ii} $5169$ velocities measured from spectra at $t\sim 50$ days after the explosion vary from ${\rm 2000\ km\ s^{-1}}$ to ${\rm 5500\ km\ s^{-1}}$, with an average value of ${\rm 3872 \pm 949\ km\ s^{-1}}$. Power-law functions can be used to fit the velocity evolution, with the power-law exponent quantifying the velocity decline rate. We found an anticorrelation existing between H$β$ velocity at mid-plateau phase and its velocity decay exponent, SNe II with higher velocities tending to have smaller velocity decay rate. Moreover, we noticed that the velocity decay rate inferred from the Balmer lines (i.e., H$α$ and H$β$) have moderate correlations with the ratio of absorption to emission for H$α$ (a/e). In our sample, two objects show possibly flash-ionized features at early phases. Besides, we noticed that multiple high-velocity components may exist on the blue side of hydrogen lines of SN 2013ab, possibly suggesting that these features arise from complex line forming region. All our spectra can be found in WISeREP and Zenodo.

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arXiv2023

SN 2022vqz: A Peculiar Subluminous Type Ia Supernova with Prominent Early Excess Emission

We present extensive photometric and spectroscopic observations of the peculiar Type Ia supernova (SN Ia) 2022vqz. It shares many similarities with the SN 2002es-like SNe Ia, such as low luminosity ($M_{B,\rm max}=-18.11\pm0.16$ mag) and moderate post-peak decline rate ($Δm_{15,B}=1.33\pm0.11$ mag). The nickel mass synthesised in the explosion is estimated as $0.20\pm0.04~{\rm M}_\odot$ from the bolometric light curve, which is obviously lower than that of normal SNe Ia. SN 2022vqz is also characterised by slowly expanding ejecta, with Si II velocities persisting around 7000 km s$^{-1}$ since 16 days before peak brightness, unique among all known SNe Ia. While all of these properties imply a lower-energy thermonuclear explosion that should leave a considerable amount of unburnt materials, the absent signature of unburnt carbon in spectra of SN 2022vqz is puzzling. A prominent early peak is clearly detected in the ATLAS $c$- and $o$-band light curves and in the ZTF $gr$-band data within days after the explosion. Possible mechanisms for the early peak are discussed, including the sub-Chandrasekhar-mass double-detonation model and interaction of SN ejecta with circumstellar material. We find that both models face some difficulties in replicating all aspects of the observed data. As an alternative, we propose a hybrid C-O-Ne white dwarf as the progenitor of SN 2022vqz; it can simultaneously reconcile the tension between low ejecta velocity and the absence of carbon. We further discuss the diversity of SN 2002es-like objects and their origin in the context of different scenarios.

astro-ph.HE↗

arXiv2023

Discovery of the Closest Ultrastripped Supernova: SN 2021agco in UGC 3855

We present the discovery and studies of the helium-rich, fast-evolving supernova (SN) 2021agco at a distance of $\sim$ 40 Mpc. Its early-time flux is found to rise from half peak to the peak of $-16.06\pm0.42$ mag in the $r$ band within $2.4^{+1.5}_{-1.0}$ days, and the post-peak light curves also decline at a much faster pace relative to normal stripped-envelope SNe of Type Ib/Ic. The early-time spectrum of SN~2021agco ($t \approx 1.0$ days after the peak) is characterized by a featureless blue continuum superimposed with a weak emission line of ionized C III, and the subsequent spectra show prominent He I lines. Both the photometric and spectroscopic evolution shows close resemblances to SN 2019dge, which is believed to have an extremely stripped progenitor. We reproduce the multicolor light curves of SN 2021agco with a model combining shock-cooling emission with \Ni decay. The best-fit results give an ejecta mass of $\approx 0.3$~M$_\odot$ and a synthesized nickel mass of $\approx 2.2\times10^{-2}$~M$_\odot$. The progenitor is estimated to have an envelope radius $R_{\rm env} \approx 80$~R$_\odot$ and a mass $M_{\rm env} \approx 0.10$~M$_\odot$. All these suggest that SN~2021agco can be categorized as an ultrastripped SN~Ib, representing the closest object of this rare subtype. This SN is found to explode in the disk of an Sab-type galaxy with an age of $\sim 10.0$~Gyr and low star-forming activity. Compared to normal SNe Ib/c, the host galaxies of SN 2021agco and other ultrastripped SNe tend to have relatively lower metallicity, which complicates the properties of their progenitor populations.

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arXiv2023

Astrometric Calibration of the Beijing$-$Arizona Sky Survey

We present the astrometric calibration of the Beijing-Arizona Sky Survey (BASS). The BASS astrometry was tied to the International Celestial Reference Frame via the \emph{Gaia} Data Release 2 reference catalog. For effects that were stable throughout the BASS observations, including differential chromatic refraction and the low charge transfer efficiency of the CCD, we corrected for these effects at the raw image coordinates. Fourth-order polynomial intermediate longitudinal and latitudinal corrections were used to remove optical distortions. The comparison with the \emph{Gaia} catalog shows that the systematic errors, depending on color or magnitude, are less than 2 milliarcseconds (mas). The position systematic error is estimated to be about $-0.01\pm0.7$ mas in the region between 30 and 60 degrees of declination and up to $-0.07 \pm 0.9$ mas in the region north of declination 60 degrees.

astro-ph.IM↗

arXiv2023

SN 2016ije: An SN 2002es-like Type Ia Supernova Exploded in a Metal-poor and Low-surface Brightness Galaxy

We have conducted photometric and spectroscopic observations of the peculiar Type Ia supernova (SN Ia) 2016ije that was discovered through the Tsinghua-NAOC Transient Survey. This peculiar object exploded in the outskirts of a metal-poor, low-surface brightness galaxy (i.e., $M_{g}$ = $-$14.5 mag). Our photometric analysis reveals that SN 2016ije is subluminous ($M_{B,\rm{max}}$ = $-$17.65$\pm$0.06 mag) but exhibits relatively broad light curves ($Δm_{15}(B)$ = 1.35$\pm$0.14 mag), similar to the behavior of SN 2002es. Our analysis of the bolometric light curve indicates that only 0.14$\pm$0.04 $M_{\odot}$ of $^{56}$Ni was synthesized in the explosion of SN 2016ije, which suggests a less energetic thermonuclear explosion when compared to normal SNe Ia, and this left a considerable amount of unburned materials in the ejecta. Spectroscopically, SN 2016ije resembles other SN 2002es-like SNe Ia, except that the ejecta velocity inferred from its carbon absorption line ($\sim$ 4500 km s$^{-1}$) is much lower than that from silicon lines ($\sim$ 8300 km s$^{-1}$) at around the maximum light. Additionally, most of the absorption lines are broader than other 02es-like SNe Ia. These peculiarities suggest the presence of significant unburned carbon in the inner region and a wide line-forming region along the line of sight. These characteristics suggest that SN 2016ije might originate from the violent merger of a white dwarf binary system, when viewed near an orientation along the iron-group-element cavity caused by the companion star.

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arXiv2023

SN 2018hna: Adding a Piece to the Puzzles of the Explosion of Blue Supergiants

We present extensive optical/ultraviolet observations and modelling analysis for the nearby SN 1987A-like peculiar Type II supernova (SN) 2018hna. Both photometry and spectroscopy covered phases extending to $>$500 days after the explosion, making it one of the best-observed SN II of this subtype. SN 2018hna is obviously bluer than SN 1987A during the photospheric phase, suggesting higher photospheric temperature, which may account for weaker BaII $\mathrmλ$6142 lines in its spectra. Analysis of early-time temperature evolution suggests a radius of $\sim$45 $\mathrm{R_{\odot}}$ for the progenitor of SN 2018hna, consistent with a blue supergiant (BSG). By fitting the bolometric light curve with hydrodynamical models, we find that SN 2018hna has an ejecta mass of $\sim$(13.7--17.7) $\mathrm{M_{\odot}}$, a kinetic energy of $\sim$ (1.0--1.2) $\times 10^{51}$ erg, and a $^{56}$Ni mass of about 0.05 $\mathrm{M_{\odot}}$. Moreover, based on standard stellar evolution and the oxygen mass (0.44--0.73 $\mathrm{M_{\odot}}$) deduced from nebular [OI] lines, the progenitor of SN 2018hna is expected to have an initial main-sequence mass $<$16 $\mathrm{M_{\odot}}$. In principle, such a relatively low-mass star cannot end as a BSG just before core-collapse, except some unique mechanisms are involved, such as rapid rotation, restricted semiconvection, etc. On the other hand, binary scenario may be more favourable, like in the case of SN 1987A. While the much lower oxygen mass inferred for SN~2018hna may imply that its progenitor system also had much lower initial masses than that of SN 1987A.

astro-ph.HE↗

arXiv2022

Forecast of Cosmological Constraints with Type Ia Supernovae from the Chinese Space Station Telescope

The 2-m aperture Chinese Space Station Telescope (CSST), which observes at wavelengths ranging from 255 to 1000 nm, is expected to start science operations in 2024. An ultra-deep field observation program covering approximately 10 square degrees is proposed with supernovae (SNe) and other transients as one of its primary science drivers. This paper presents the simulated detection results of type Ia supernovae (SNe Ia) and explores the impact of new datasets on the determinations of cosmological parameters. The simulated observations are conducted with an exposure time of 150 s and cadences of 10, 20, and 30 days. The survey mode covering a total of 80 observations but with a random cadence in the range of 4 to 14 days is also explored. Our simulation results indicate that the CSST can detect up to $\sim 1800$ SNe Ia at z $<$ 1.3. The simulated SNe Ia are then used to constrain the cosmological parameters. The constraint on $Ω_m$ can be improved by 37.5% using the 10-day cadence sample in comparison with the Pantheon sample. A deeper measurement simulation with a 300 s exposure time together with the Pantheon sample improves the current constraints on $Ω_m$ by 58.3% and $ω$ by 47.7%. Taking future ground-based SNe Ia surveys into consideration, the constraints on $ω$ can be improved by 59.1%. The CSST ultra-deep field observation program is expected to discover large amounts of SNe Ia over a broad redshift span and enhance our understanding of the nature of dark energy.

astro-ph.CO↗

arXiv2022

Optical Observations of the Nearby Type Ia Supernova 2021hpr

We present the optical photometric and spectroscopic observations of the nearby Type Ia supernova (SN) 2021hpr. The observations covered the phase of $-$14.37 to +63.68 days relative to its maximum luminosity in the $B$ band. The evolution of multiband light/color curves of SN 2021hpr is similar to that of normal Type Ia supernovae (SNe Ia) with the exception of some phases, especially a plateau phase that appeared in the $V-R$ color curve before peak luminosity, which resembles that of SN 2017cbv. The first spectrum we observed at t $\sim -$14.4 days shows a higher velocity for the Si II $λ$6355 feature ($\sim$ 21,000 km s$^{-1}$) than that of other normal Velocity (NV) SNe Ia at the same phase. Based on the Si II $λ$6355 velocity of $\sim$ 12,420 km s$^{-1}$ around the maximum light, we deduce that SN 2021hpr is a transitional object between high velocity (HV) and NV SNe Ia. Meanwhile, the Si II $λ$6355 feature shows a high velocity gradient (HVG) of about 800 km s$^{-1}$ day$^{-1}$ from roughly $-$14.37 to $-$4.31 days relative to the $B$-band maximum, which indicates that SN 2021hpr can also be classified as an HVG SN Ia. The evolution of SN 2021hpr is similar to that of SN 2011fe. Including SN 2021hpr, there have been six supernovae observed in the host galaxy NGC 3147, and the supernovae explosion rate in the last 50 yr is slightly higher for SNe Ia, while lower for SNe Ibc and SNe II it is lower than expected rate from the radio data. Inspecting the spectra, we find that SN 2021hpr has a metal-rich (12 + log(O/H) $\approx$ 8.648) circumstellar environment, where HV SNe tend to reside. Based on the decline rate of SN 2021hpr in the $B$ band, we determine the distance modulus of the host galaxy NGC 3147 using the Phillips relation to be 33.46 $\pm$ 0.21 mag, which is close to that found by previous works.

astro-ph.HE↗

arXiv2022

Observations of the Very Young Type Ia Supernova 2019np with Early-excess Emission

Early-time radiative signals from type Ia supernovae (SNe Ia) can provide important constraints on the explosion mechanism and the progenitor system. We present observations and analysis of SN 2019np, a nearby SN Ia discovered within 1-2 days after the explosion. Follow-up observations were conducted in optical, ultraviolet, and near-infrared bands, covering the phases from $\sim-$16.7 days to $\sim$+367.8 days relative to its $B-$band peak luminosity. The photometric and spectral evolutions of SN 2019np resembles the average behavior of normal SNe Ia. The absolute B-band peak magnitude and the post-peak decline rate are $M_{\rm max}(B)=-19.52 \pm 0.47$mag and $Δm_{\rm15}(B) =1.04 \pm 0.04$mag, respectively. No Hydrogen line has been detected in the near-infrared and nebular-phase spectra of SN 2019np. Assuming that the $^{56}$Ni powering the light curve is centrally located, we find that the bolometric light curve of SN 2019np shows a flux excess up to 5.0% in the early phase compared to the radiative diffusion model. Such an extra radiation perhaps suggests the presence of an additional energy source beyond the radioactive decay of central nickel. Comparing the observed color evolution with that predicted by different models such as interactions of SN ejecta with circumstellar matter (CSM)/companion star, a double-detonation explosion from a sub-Chandrasekhar mass white dwarf (WD), and surface $^{56}$Ni mixing, the latter one is favored.

astro-ph.HE↗

arXiv2022

Searching Extra-tidal Features around the Globular Cluster Whiting 1

Whiting 1 is a faint and young globular cluster in the halo of the Milky Way, and was suggested to have originated in the Sagittarius spherical dwarf galaxy (Sgr dSph). In this paper, we use the deep DESI Legacy Imaging Surveys to explore tentative spatial connection between Whiting 1 and the Sgr dSph. We redetermine the fundamental parameters of Whiting 1 and use the best-fitting isochrone (age $τ$=6.5 Gyr, metalicity Z=0.005 and $\rm d_{\odot}$=26.9 kpc) to construct a theoretical matched filter for the extra-tidal features searching. Without any smooth technique to the matched filter density map, we detect a round-shape feature with possible leading and trailing tails on either side of the cluster. This raw image is not totally new compared to old discoveries, but confirms that no more large-scale features can be detected under a depth of r<=22.5 mag. In our results, the whole feature stretches 0.1-0.2 degree along the orbit of Whiting 1, which gives a much larger area than the cluster core. The tails on both sides of the cluster align along the orbital direction of the Sgr dSph as well as the cluster itself, which implies that these debris are probably stripped remnants of Whiting 1 by the Milky Way.

astro-ph.GA↗