arXiv subjects

Young-Lo Kim

Publications and source records attributed to Young-Lo Kim.

At least 19 recordsLinked to original sources

arXiv2026

ZTF SN Ia DR2 follow-up: early excess in Type Ia supernova light curves

There is broad consensus that Type Ia supernovae (SNe Ia) are the thermonuclear explosions of C/O white dwarfs (WDs) in binary systems, but their progenitors and explosion mechanisms remain uncertain. Their earliest light curves probe the outermost ejecta and provide important constraints on the explosion. We analyse the ZTF DR2 sample of SNe Ia to search for objects exhibiting early flux excess (EEx SNe Ia). We employ two complementary approaches: (i) identifying deviations from models without early excess using power-law and SALT2 fits, and (ii) comparing observations with double-detonation (DD) and companion-interaction (CI) models. The latter identify 145 and 199 candidates, respectively, although the methods disagree substantially on both the objects selected and the total number of candidates. Combining all methods, we identify 17 robust EEx SN Ia candidates, including six over-luminous events (five 91T-like and one 03fg-like). The strongest excesses reach ${\sim}10$--17\% of the peak flux. The best candidates have, on average, higher stretch and preferentially occur in lower-mass, bluer host galaxies, suggesting younger stellar populations. We estimate that EEx SNe Ia comprise $\lesssim25\%$ of all SNe Ia, consistent with previous work, with over-luminous subtypes showing a higher relative incidence than normal SNe Ia. Among the DD models, the preferred solutions favour intermediate WD core masses ($1 M_{\odot}$), low shell-burning fractions ($20\%$), and heavier He-burning products ($^{56}$Ni), whereas the CI models show no clear parameter trends. Overall, we find no compelling evidence that either scenario is preferred as the origin of the observed early flux excesses.

astro-ph.CO↗

arXiv2026

Decoding the Early-Time Light Curves of Type Ia Supernovae. II. Population Parameters of One Thousand ZTF Supernovae

Early-time light curves of Type Ia Supernovae (SNe Ia) encode critical information about their progenitor systems. We characterize the rise of normal SNe Ia using a volume-complete sample of 972 events from the Zwicky Transient Facility Data Release 2, an order of magnitude larger than any previous dataset for similar analyses. Fitting light curves up to $30\%$ of peak flux with a power-law model under a hierarchical Bayesian framework, we provide robust population-level constraints on the rise time ($t_\mathrm{rise}$; $\mu=18.55\pm0.08$ days, $\sigma=1.42\pm0.07$ days), rise index ($\alpha$; $\mu=2.10\pm0.04$, $\sigma=0.48\pm0.03$ in ZTF $r$), and $g-r$ color evolution ($\alpha_g - \alpha_r$; $\mu=0.20\pm0.02$, $\sigma=0.17\pm0.02$). These power-law fits are sensitive to the chosen truncation epoch if data beyond $\sim$$40\%$ of peak flux are included, but generally converge when restricted to earlier epochs. The relation between rise morphology and light-curve width ($\texttt{SALT2}$ $x_1$ stretch) bifurcates into two distinct regimes: high-stretch SNe Ia show clear trends where a higher $x_1$ correlates with shallower rises and more persistent blue colors, whereas low-stretch SNe Ia lack such trends. While rise times correlate positively with $x_1$ overall, this relation flattens significantly within the high-stretch population. Searching for anomalies, we identify several normal SNe Ia with unusually long rise times, which potentially exhibit short-duration ($\lesssim$2 days) flux excesses over a smooth rise. Long-duration ($\sim$5 days) flux excesses appear common within the high-stretch population and are tied to the shallow rises and early blue colors, pointing to widespread outward $^{56}$Ni mixing. Multi-dimensional explosion models with more realistic progenitor setups are needed to fully reproduce the observed dichotomy in rise morphology and stretch.

astro-ph.HE↗

arXiv2026

An analysis of the Type Ia SN 2024gy and a comparison of different host extinction estimation techniques

Type Ia supernovae (SNe Ia) are well-known standardisable candles, and are one of the main ways to measure the distance to their host galaxies. However, extinction due to interstellar dust causes objects to appear fainter and redder. Correcting for this requires estimating the amount of intervening material and how the extinction changes as a function of wavelength. We present and analyse optical and near-infrared data of the well-observed SN 2024gy and use these to compare different extinction estimation techniques, making use of photometric, spectroscopic, and polarimetric data. SN 2024gy is a normal SN Ia with high velocity (HV) components in Si II $\lambda6355$ (phase $<-10$ days) and a particularly strong HV feature in the Ca II near-infrared triplet (up to peak). Modelling SN 2024gy with TARDIS shows better matches with a double-detonation scenario compared to a delayed-detonation scenario due to a better match to the Ca II HV component. A measurement of the stable Ni/Fe ratio however favours a delayed-detonation scenario. Host extinction estimates range from $E(B-V)_{host}=0.12\pm0.02$ mag (narrow interstellar absorption lines) to $E(B-V)_{host}=0.24\pm0.06$ mag (Lira law) with a mean of $E(B-V)_{host}=0.22\pm0.04$ mag, assuming $R_V=3.1$. The spread between different methods highlights the challenge of accurately estimating the amount of extinction light suffers before being observed.

astro-ph.GA↗

arXiv2026

Strong Progenitor Age Bias in Supernova Cosmology. III. Progenitor Age as the Physical Origin of the Type Ia Supernova Magnitude Steps with Host Properties

The standardized magnitude of a type Ia supernova (SN Ia) correlates with host-galaxy properties, and a host mass-step correction is now routinely included in SN Ia luminosity standardization. Given that host mass cannot directly influence SN Ia luminosity, the root cause of the step must be another latent parameter associated with host mass. Identifying this driver is essential because different host properties evolve differently with redshift, so corrections based on them can lead to divergent cosmological inferences. In recent years, direct and extensive age measurements have revealed a significant relation between host age and Hubble residual (HR). Here, using a new dataset, we confirm that this relation arises from the age dependence of the SN Ia luminosity standardization process and the resulting overcorrection. Specifically, we show that while the mass-step correction reduces the age bias by about half, the host age-bias correction fully eliminates the mass step, supporting a progenitor-age origin of the host-age--HR relation. We further demonstrate that the SN Ia magnitude steps with host mass (and specific star formation rate; sSFR) emerge from a nonlinear, step-like relation between mass (and sSFR) and progenitor age, combined with a linear progenitor-age--HR relation: the SN Ia magnitude steps are therefore projected manifestations of an underlying dependence on progenitor age. Taken together, our results show that progenitor age is the primary driver of both the strong host-age--HR relation and the apparent host-mass and host-sSFR steps.

astro-ph.GA↗

arXiv2026

Illuminating the Local Universe: Large-Scale Structure from ZTF Type Ia Supernovae

Within the volume-limited subsample at $z<0.06$ of the Zwicky Transient Facility (ZTF) DR2 sample, we confirm a statistically significant excess of Type Ia supernovae (SNe Ia) at $z \simeq 0.02$-$0.04$, previously reported but not explained by survey selection effects. Forward simulations assuming a uniform volumetric SN Ia rate and realistic ZTF detection efficiencies fail to reproduce the feature at the $5$-$7\sigma$ level. We also detect an excess in the rates compared to our survey simulations at $z \simeq 0.08$ and $0.14$, albeit at smaller significance. To investigate the origin of these inhomogeneities, we compare the observed SN distribution to constrained reconstructions of the local matter density field from the Manticore project, based on Bayesian forward modelling of the 2M++ galaxy catalogue. While SN overdensities are spatially associated with prominent nearby structures such as the Perseus, Coma, and Hercules superclusters, the amplitude of the SN excesses significantly exceeds that expected from matter overdensities alone. By reconstructing a redshift-dependent volumetric SN Ia rate, we find that local enhancements can reach factors of two to five within specific clusters, while the sample-averaged rate remains consistent with previous low-redshift measurements. These results indicate that the SN Ia rate is not a linear tracer of the underlying matter density and suggest a strong environmental dependence in dense structures. We discuss possible physical origins and highlight the implications for low-redshift SN cosmology, including correlated peculiar velocities and additional covariance beyond standard linear corrections.

astro-ph.CO↗

arXiv2026

How Robust is the Cosmic Distance with Tip of Red Giant Branch against Stellar Population Variations?

The tip of the red giant branch (TRGB) provides a key standard candle for extragalactic distance measurements and for refining the Hubble constant. We test its robustness by quantifying how metallicity, $\alpha$-element enhancement, age, and initial helium abundance modulate the TRGB luminosity, using synthetic composite color--magnitude diagrams in the $I$ and $F814W$ bands. We find that metallicity and $\alpha$-element enhancement are the primary drivers of TRGB variation, while age introduces only a modest effect and helium abundance is negligible. At fixed age and helium content, increasing the mean metallicity by 0.5 dex or the $\alpha$-element enhancement by 0.3 dex produces the well-known systematic dimming of 0.046 and 0.050 mag, respectively, in $M_I^{\rm TRGB}$, and of 0.093 and 0.044 mag, respectively, in $M_{F814W}^{\rm TRGB}$. By comparison, changes in age of 3~Gyr and in initial helium abundance of 0.10 yield minor luminosity shifts, with average changes of 0.031 and 0.009~mag, respectively, in $M_I^{\rm TRGB}$, and of 0.035 and 0.027 mag, respectively, in $M_{F814W}^{\rm TRGB}$, substantially smaller than those caused by variations in metallicity or $\alpha$-element enhancement. For mixed stellar populations under typical stellar-halo metallicity conditions, the net variation in $M_I^{\rm TRGB}$ arising from each combination of the $\alpha$-element enhancement, age, and initial helium abundance remains below 0.028~mag, well within reported systematic uncertainties. Together, these results reaffirm the TRGB as a highly robust distance indicator and support its continued use as an independent anchor for precision cosmology in the era of the Hubble-tension debate.

astro-ph.GA↗

arXiv2025

ZTF SN Ia DR2 follow-up: Characterization of subluminous Type Ia supernovae in the ZTF DR2 full sample

The Zwicky Transient Facility Data Release 2 (ZTF DR2) includes a total of 3,628 Type Ia supernovae (SNe~Ia), providing the largest and most complete sample of spectroscopically confirmed SNe~Ia at low redshift to date. In this paper, we present a photometric and spectroscopic analysis of 124 subluminous SNe~Ia, the largest sample of spectroscopically classified subluminous SNe~Ia observed with a single instrument, comprising 87 91bg-like, 12 86G-like, 18 04gs-like, and 7 02es-like events. We complement the published DR2 SALT2 light-curve parameters with new parameters obtained using template-based fits from SNooPy. Expansion velocities and pseudo-equivalent widths pEW of key spectral features are measured using Spextractor, and spectral averages are constructed for each subluminous subtype, binned by phase. We also analyze the host galaxy environments, both global and local, in terms of $g - z$ color, stellar mass, and directional light radius $d_{DLR}$. We find that all subluminous SNe~Ia (except the 02es-like subtype) are intrinsically red. This is evident by separating extrinsic from intrinsic color components. Since SALT2 is not trained on subluminous SNe~Ia, it compensates for their redder colors by inflating the $c$ parameter, thus extending the luminosity-width relation to negative values of x1. As expected, all subluminous SNe~Ia fall within the Cool region of the Branch et al. (2006) diagram, with the exception of 02es-like events, which show lower Si II 5972 pEW values. All subluminous subtypes tend to occur in more massive, redder host galaxies, and in the reddest local environments. Notably, 91bg- and 86G-like SNe~Ia explode at significantly larger normalized galactocentric distances. Finally, we identify the $pEW$ of the blended Ti II+Si II+Mg II absorption feature at 4300~A, along with s_BV, as robust and sufficient indicators for subclassifying subluminous SNe~Ia.

astro-ph.HE↗

arXiv2025

Testing the effect of progenitor's metallicity on $^{56}$Ni mass and constraining the progenitor scenarios in Type Ia supernovae

The analytical model found that the intrinsic variation in the initial metallicity of the Type Ia supernova (SN Ia) progenitor stars ($Z_{progenitor}$) translates into a 25% variation in the $^{56}$Ni mass synthesized and, therefore, 0.2 mag difference in the observed peak luminosity of SNe Ia. Previous observational studies used the currently-observed global gas-phase metallicity of host galaxies, instead of $Z_{progenitor}$ used in the model, and showed a higher scatter in the $^{56}$Ni mass measurements compared to the model prediction. Here, we use $Z_{progenitor}$ of 34 normal SNe Ia and employ recent SN Ia explosion models with various configurations to cover the observed $^{56}$Ni mass range. Unlike previous studies, our sample covers the $Z_{progenitor}$ range, where most of the $Z_{progenitor}$ effect occurs. Linear regression returns a slope of 0.02+-0.03, which is the opposite trend to the analytical model, but at at low statistical significance level. We find that comparing our sample with SN Ia explosion models on the $Z_{progenitor}$--$^{56}$Ni mass diagram allows us to constrain the progenitor scenarios. We also explore other chemical composition indicators. For $(Fe/H)_{progenitor}$, our sample follows the trend predicted by the analytical models, but at a low significance level. Noticeably, $(\alpha/Fe)_{progenitor}$ shows the opposite trend and a clear gap. When we split the sample at $(\alpha/Fe)_{progenitor}$ = 0.35 $(\alpha/Fe)_{\odot}$, we find a 3$\sigma$ difference in the weighted-means of the $^{56}$Ni mass. Lastly, SNe Ia in different $Z_{progenitor}$ groups show a difference of 0.14+-0.09 mag in the standardized luminosity. The present work highlights a holistic approach (from the progenitor star to the explosion with SN Ia and host galaxy observational data) to understand the underlying physics of SNe Ia for more accurate and precise cosmology.

astro-ph.HE↗

arXiv2025

A real-time search for Type Ia Supernovae with late-time CSM interaction in ZTF

The nature of Type Ia supernova (SN Ia) progenitor systems and the mechanisms that lead up to their explosions are still widely debated. In rare cases the SN ejecta interact with circumstellar material (CSM) that was ejected from the progenitor system prior to the SN. The unknown distance between the CSM and SN explosion site makes it impossible to predict when the interaction will start. If the time between the SN and start of CSM interaction is of the order of months to years the SN has generally faded and is not actively followed up anymore, making it even more difficult to detect the interaction while it happens. Here we report on a real-time monitoring program which ran between 13-11-2023 and 09-07-2024, monitoring 6914 SNe Ia for signs of late-time rebrightening using the Zwicky Transient Facility (ZTF). Flagged candidates were rapidly followed up with photometry and spectroscopy to confirm the late-time excess and its position. We report the discovery of a $\sim50$ day rebrightening event in SN 2020qxz around 1200 days after the peak of its light curve. SN 2020qxz had signs of early CSM interaction but faded from view over 2 years before its reappearance. Follow-up spectroscopy revealed 4 emission lines that faded shortly after the end of the ZTF detected rebrightening. Our best match for these emission lines are H$\beta$ (blue shifted by $\sim5900$ km s$^{-1}$) and CaII$_{\lambda8542}$, NI$_{\lambda8567}$, and KI$_{\lambda\lambda 8763, 8767}$, all blue shifted by 5100 km s$^{-1}$ (although we note that these identifications are uncertain). This shows that catching and following up on late-time interactions as they occur can give new clues about the nature of the progenitor systems that produce these SNe by putting constraints on the possible type of donor star, and the only way to do this systematically is to use large sky surveys such as ZTF to monitor a large sample of objects.

astro-ph.HE↗

arXiv2025

Testing and Combining Transient Spectral Classification Tools on 4MOST-like Blended Spectra

With the 4-meter Multi-Object Spectroscopic Telescope (4MOST) expected to provide an influx of transient spectra when it begins observations in early 2026 we consider the potential for real-time classification of these spectra. We investigate three extant spectroscopic transient classifiers: the Deep Automated Supernova and Host classifier (DASH), Next Generation SuperFit (NGSF) and SuperNova IDentification (SNID), with a focus on comparing the completeness and purity of the transient samples they produce. We manually simulate fibre losses critical for accurately determining host-contamination and use the 4MOST Exposure Time Calculator to produce realistic, 4MOST-like, host-galaxy contaminated spectra. We investigate the three classifiers individually and in all possible combinations. We find that a combination of DASH and NGSF can produce a SN Ia sample with a purity of 99.9% while successfully classifying 70% of SNe Ia. However, it struggles to classify non-SN Ia transients. We investigate photometric cuts to transient magnitude and the transient's fraction of total fibre flux, finding that both can be used to improve non-SN Ia transient classification completeness by 8--44% with SNe Ibc benefitting the most and superluminous (SL) SNe the least. Finally, we present an example classification plan for live classification and the predicted purities and completeness across five transient classes: Ia, Ibc, II, SL and non-SN transients. We find that it is possible to classify 75% of input spectra with >70% purity in all classes except non-SN transients. Precise values can be varied using different classifiers and photometric cuts to suit the needs of a given study.

astro-ph.SR↗

arXiv2024

CCSNscore: A multi-input deep learning tool for classification of core-collapse supernovae using SED-Machine spectra

Supernovae (SNe) come in various flavors and are classified into different types based on emission and absorption lines in their spectra. SN candidates are now abundant with the advent of large systematic sky surveys like the Zwicky Transient Facility (ZTF), however, the identification bottleneck lies in their spectroscopic confirmation and classification. Fully robotic telescopes with dedicated spectrographs optimized for SN follow-up have eased the burden of data acquisition. However, the task of classifying the spectra still largely rests with the astronomers. Automating this classification step reduces human effort and can make the SN type available sooner to the public. For this purpose, we have developed a deep-learning based program for classifying core-collapse supernovae (CCSNe) with ultra-low resolution spectra from the SED-Machine spectrograph on the Palomar 60-inch telescope. The program consists of hierarchical classification task layers, with each layer composed of multiple binary classifiers running in parallel to produce a reliable classification. The binary classifiers utilize RNN and CNN architecture and are designed to take multiple inputs to supplement spectra with $g$- and $r$-band photometry from ZTF. On non-host-contaminated and good quality SEDM spectra ("gold" test set) of CCSNe, CCSNscore is ~94% accurate in distinguishing between hydrogen-rich (Type II) and hydrogen-poor (Type Ibc) CCSNe. With light curve input, CCSNscore classifies ~83% of the gold set with high confidence (score $\geq 0.8$ and score-error $<0.05$), with ~98% accuracy. Based on SNIascore's and CCSNscore's real-time performance on bright transients ($m_{pk}\leq18.5$) and our reporting criteria, we expect ~0.5% (~4) true SNe Ia to be misclassified as SNe Ibc and ~6% (~17) of true CCSNe to be misclassified between Type II and Type Ibc annually on the Transient Name Server.

astro-ph.IM↗

arXiv2024

How accurate are transient spectral classification tools? -- A study using 4,646 SEDMachine spectra

Accurate classification of transients obtained from spectroscopic data are important to understand their nature and discover new classes of astronomical objects. For supernovae (SNe), SNID, NGSF (a Python version of SuperFit), and DASH are widely used in the community. Each tool provides its own metric to help determine classification, such as rlap of SNID, chi2/dof of NGSF, and Probability of DASH. However, we do not know how accurate these tools are, and they have not been tested with a large homogeneous dataset. Thus, in this work, we study the accuracy of these spectral classification tools using 4,646 SEDMachine spectra, which have accurate classifications obtained from the Zwicky Transient Facility Bright Transient Survey (BTS). Comparing our classifications with those from BTS, we have tested the classification accuracy in various ways. We find that NGSF has the best performance (overall Accuracy 87.6% when samples are split into SNe Ia and Non-Ia types), while SNID and DASH have similar performance with overall Accuracy of 79.3% and 76.2%, respectively. Specifically for SNe Ia, SNID can accurately classify them when rlap > 15 without contamination from other types, such as Ibc, II, SLSN, and other objects that are not SNe (Purity > 98%). For other types, determining their classification is often uncertain. We conclude that it is difficult to obtain an accurate classification from these tools alone. This results in additional human visual inspection effort being required in order to confirm the classification. To reduce this human visual inspection and to support the classification process for future large-scale surveys, this work provides supporting information, such as the accuracy of each tool as a function of its metric.

astro-ph.IM↗

arXiv2024

ZTF SN Ia DR2: Overview

We present the first homogeneous release of several thousand Type Ia supernovae (SNe Ia), all having spectroscopic classification, and spectroscopic redshifts for half the sample. This release, named the "DR2", contains 3628 nearby (z < 0.3) SNe Ia discovered, followed and classified by the Zwicky Transient Facility survey between March 2018 and December 2020. Of these, 3000 have good-to-excellent sampling and 2667 pass standard cosmology light-curve quality cuts. This release is thus the largest SN Ia release to date, increasing by an order of magnitude the number of well characterized low-redshift objects. With the "DR2", we also provide a volume-limited (z < 0.06) sample of nearly a thousand SNe Ia. With such a large, homogeneous and well controlled dataset, we are studying key current questions on SN cosmology, such as the linearity SNe Ia standardization, the SN and host dependencies, the diversity of the SN Ia population, and the accuracy of the current light-curve modeling. These, and more, are studied in detail in a series of articles associated with this release. Alongside the SN Ia parameters, we publish our force-photometry gri-band light curves, 5138 spectra, local and global host properties, observing logs, and a python tool to ease use and access of these data. The photometric accuracy of the "DR2" is not yet suited for cosmological parameter inference, which will follow as "DR2.5" release. We nonetheless demonstrate that the multi-thousand SN Ia Hubble Diagram has a typical 0.15 mag scatter.

astro-ph.CO↗

arXiv2024

Tracing back the birth environments of Type Ia supernova progenitor stars: A pilot study based on 44 early-type host galaxies

The environmental dependence of Type Ia supernova (SN Ia) luminosities is well-established, and efforts are being made to find its origin. Previous studies typically use the currently-observed status of the host galaxy. However, given the delay time between the birth of the progenitor star and the SN Ia explosion, the currently-observed status may differ from the birth environments of the SN Ia progenitor star. In this paper, employing the chemical evolution and accurately determined stellar population properties of 44 early-type host galaxies, we, for the first time, estimate the SN Ia progenitor star birth environment, specifically $[Fe/H]_{Birth}$ and $[α/Fe]_{Birth}$. We show that $[α/Fe]_{Birth}$ has a $30.4^{+10.6}_{-10.1}\%$ wider range than $[α/Fe]_{Current}$, while the range of $[Fe/H]_{Birth}$ is not statistically different ($17.9^{+26.0}_{-27.1}\%$) to that of $[Fe/H]_{Current}$. The birth and current environments of [Fe/H] and [$α$/Fe] are sample from different populations (p-values of the KS test < 0.01). We find that light-curve fit parameters are insensitive to $[Fe/H]_{Birth}$ ($<0.9σ$ for the non-zero slope), while a linear trend is observed with HRs at the 2.4$σ$ significance level. With $[α/Fe]_{Birth}$, no linear trends ($<1.1σ$) are observed. Interestingly, we find that $[α/Fe]_{Birth}$ clearly splits the SN Ia sample into two groups: SN Ia exploded in $[α/Fe]_{Birth}$-rich or $[α/Fe]_{Birth}$-poor environments. SNe Ia exploded in different $[α/Fe]_{Birth}$ groups have different weighted-means of light-curve shape parameters: $0.81\pm0.33$ ($2.5σ$). They are thought to be drawn from different populations (p-value = 0.01). Regarding SN Ia colour and HRs, there is no difference in the weighted-means ($<1.0σ$) and distributions (p-value > 0.27) of each $[α/Fe]_{Birth}$ group.

astro-ph.HE↗

arXiv2024

Searching for late-time interaction signatures in Type Ia supernovae from the Zwicky Transient Facility

The nature of the progenitor systems and explosion mechanisms that give rise to Type Ia supernovae (SNe Ia) are still debated. The interaction signature of circumstellar material (CSM) being swept up by expanding ejecta can constrain the type of system from which it was ejected. Most previous studies have focused on finding CSM ejected shortly before the SN Ia explosion still residing close to the explosion site, resulting in short delay times until the interaction starts. We use a sample of 3627 SNe Ia from the Zwicky Transient Facility discovered between 2018 and 2020 and search for interaction signatures over 100 days after peak brightness. By binning the late-time light curve data to push the detection limit as deep as possible, we identify potential late-time rebrightening in 3 SNe Ia (SN 2018grt, SN 2019dlf, SN 2020tfc). The late-time detections occur between 550 and 1450 d after peak brightness, have mean absolute $r$-band magnitudes of -16.4 to -16.8 mag and last up to a few hundred days, significantly brighter than the late-time CSM interaction discovered in the prototype SN 2015cp. The late-time detections all occur within 0.8 kpc of the host nucleus and are not easily explained by nuclear activity, another transient at a similar sky position, or data quality issues. This suggests environment or specific progenitor characteristics playing a role in producing potential CSM signatures in these SNe Ia. By simulating the ZTF survey we estimate that <0.5 per cent of normal SNe Ia display late-time strong H $\alpha$-dominated CSM interaction. This is equivalent to an absolute rate of $8_{-4}^{+20}$ to $54_{-26}^{+91}$ Gpc$^{-3}$ yr$^{-1}$ assuming a constant SN Ia rate of $2.4\times10^{-5}$ Mpc$^{-3}$ yr$^{-1}$ for $z \leq 0.1$. Weaker interaction signatures, more similar to the strength seen in SN 2015cp, could be more common but are difficult to constrain with our survey depth.

astro-ph.HE↗

arXiv2023

Reconsidering photometric estimation of local star formation environment and its correlation with Type Ia Supernova luminosity

Recent studies on the environmental dependence of Type Ia supernova (SN Ia) luminosity focus on the local environment where the SN exploded, considering that this is more directly linked to the SN progenitors. However, there is a debate about the local environmental, specifically local star formation rate (SFR), dependence of the SN Ia luminosity. A recent study claims that the dependence is insignificant ($0.051 \pm 0.020$ mag; $2.6σ$), based on the local SFR measurement by fitting local $ugrizy$ photometry data. However, we find that this photometric local SFR measurement is inaccurate. We argue this based on the theoretical background of SFR measurement and the methodology used to make that claim with their local $ugrizy$ photometry data, especially due to a limited range of extinction parameters used when fitting the data. Therefore, we re-analyse the same host galaxies with the same fitting code, but with more physically motivated extinction treatments and global $ugriz$ photometry of host galaxies. We estimate global stellar mass and SFR. Then, local star formation environments are inferred by using the method which showed that SNe Ia in globally passive galaxies have locally passive environments, while those in globally star-forming low-mass galaxies have locally star-forming environments. We find that there is significant local environmental dependence of SN Ia luminosities: SNe Ia in locally star-forming environments are $0.072\pm0.021$ mag ($3.4σ$) fainter than those in locally passive environments, even though SN Ia luminosities have been further corrected by the BBC method that reduces the size of the dependence.

astro-ph.GA↗

arXiv2023

Galaxy Spectra neural Network (GaSNet). II. Using Deep Learning for Spectral Classification and Redshift Predictions

Large sky spectroscopic surveys have reached the scale of photometric surveys in terms of sample sizes and data complexity. These huge datasets require efficient, accurate, and flexible automated tools for data analysis and science exploitation. We present the Galaxy Spectra Network/GaSNet-II, a supervised multi-network deep learning tool for spectra classification and redshift prediction. GaSNet-II can be trained to identify a customized number of classes and optimize the redshift predictions for classified objects in each of them. It also provides redshift errors, using a network-of-networks that reproduces a Monte Carlo test on each spectrum, by randomizing their weight initialization. As a demonstration of the capability of the deep learning pipeline, we use 260k Sloan Digital Sky Survey spectra from Data Release 16, separated into 13 classes including 140k galactic, and 120k extragalactic objects. GaSNet-II achieves 92.4% average classification accuracy over the 13 classes (larger than 90% for the majority of them), and an average redshift error of approximately 0.23% for galaxies and 2.1% for quasars. We further train/test the same pipeline to classify spectra and predict redshifts for a sample of 200k 4MOST mock spectra and 21k publicly released DESI spectra. On 4MOST mock data, we reach 93.4% accuracy in 10-class classification and an average redshift error of 0.55% for galaxies and 0.3% for active galactic nuclei. On DESI data, we reach 96% accuracy in (star/galaxy/quasar only) classification and an average redshift error of 2.8% for galaxies and 4.8% for quasars, despite the small sample size available. GaSNet-II can process ~40k spectra in less than one minute, on a normal Desktop GPU. This makes the pipeline particularly suitable for real-time analyses of Stage-IV survey observations and an ideal tool for feedback loops aimed at night-by-night survey strategy optimization.

astro-ph.IM↗

arXiv2022

The prevalence and influence of circumstellar material around hydrogen-rich supernova progenitors

Narrow transient emission lines (flash-ionization features) in early supernova (SN) spectra trace the presence of circumstellar material (CSM) around the massive progenitor stars of core-collapse SNe. The lines disappear within days after the SN explosion, suggesting that this material is spatially confined, and originates from enhanced mass loss shortly (months to a few years) prior to explosion. We performed a systematic survey of H-rich (Type II) SNe discovered within less than two days from explosion during the first phase of the Zwicky Transient Facility (ZTF) survey (2018-2020), finding thirty events for which a first spectrum was obtained within $< 2$ days from explosion. The measured fraction of events showing flash ionisation features ($>36\%$ at $95\%$ confidence level) confirms that elevated mass loss in massive stars prior to SN explosion is common. We find that SNe II showing flash ionisation features are not significantly brighter, nor bluer, nor more slowly rising than those without. This implies that CSM interaction does not contribute significantly to their early continuum emission, and that the CSM is likely optically thin. We measured the persistence duration of flash ionisation emission and find that most SNe show flash features for $\approx 5 $ days. Rarer events, with persistence timescales $>10$ days, are brighter and rise longer, suggesting these may be intermediate between regular SNe II and strongly-interacting SNe IIn.

astro-ph.HE↗