Search for: All records

Context.Type Ia supernovae (SNe Ia) are a key probe in modern cosmology, as they can be used to measure luminosity distances at gigaparsec scales. Models of their light curves are used to project heterogeneous observed data onto a common basis for analysis. Aims.The SALT model currently used for SN Ia cosmology describes SNe as having two sources of variability, accounted for by a color parameterc, and a “stretch” parameterx₁. We extend the model to include an additional parameter we labelx₂, to investigate the cosmological impact of currently unaddressed light-curve variability. Methods.We constructed a new SALT model, that we dub “SALT3+”. This model was trained by an improved version of theSALTshakercode, using training data combining a selection of the second data release of cosmological SNe Ia from the Zwicky Transient Facility and the existing SALT3 training compilation. Results.We find additional, coherent variability in supernova light curves beyond SALT3. Most of this variation can be described as phase-dependent variation ing − randr − icolor curves, correlated with a boost in the height of the secondary maximum ini-band. These behaviors correlate with spectral differences, particularly in line velocity. We find that fits with the existing SALT3 model tend to address this excess variation with the color parameter, leading to less informative measurements of supernova color. We find that neglecting the new parameter in light-curve fits leads to a trend in Hubble residuals withx₂of 0.039 ± 0.005 mag, representing a potential systematic uncertainty. However, we find no evidence of a bias in current cosmological measurements. Conclusions.We conclude that extended SN Ia light-curve models promise mild improvement in the accuracy of color measurements, and corresponding cosmological precision. However, models with more parameters are unlikely to substantially affect current cosmological results. 

Abstract We present UV–optical–near-infrared observations and modeling of supernova (SN) 2024ggi, a type II supernova (SN II) located in NGC 3621 at 7.2 Mpc. Early-time (“flash”) spectroscopy of SN 2024ggi within +0.8 days of discovery shows emission lines of Hi, Hei, Ciii, and Niiiwith a narrow core and broad, symmetric wings (i.e., “IIn-like”) arising from the photoionized, optically thick, unshocked circumstellar material (CSM) that surrounded the progenitor star at shock breakout (SBO). By the next spectral epoch at +1.5 days, SN 2024ggi showed a rise in ionization as emission lines of Heii, Civ, Niv/v, and Ovbecame visible. This phenomenon is temporally consistent with a blueward shift in the UV–optical colors, both likely the result of SBO in an extended, dense CSM. The IIn-like features in SN 2024ggi persist on a timescale oft_IIn= 3.8 ± 1.6 days, at which time a reduction in CSM density allows the detection of Doppler-broadened features from the fastest SN material. SN 2024ggi has peak UV–optical absolute magnitudes ofM_w2= −18.7 mag andM_g= −18.1 mag, respectively, that are consistent with the known population of CSM-interacting SNe II. Comparison of SN 2024ggi with a grid of radiation hydrodynamics and non–local thermodynamic equilibrium radiative-transfer simulations suggests a progenitor mass-loss rate of $\dot{M}={10}^{-2}{M}_{\odot }$yr⁻¹(v_w= 50 km s⁻¹), confined to a distance ofr< 5 × 10¹⁴cm. Assuming a wind velocity ofv_w= 50 km s⁻¹, the progenitor star underwent an enhanced mass-loss episode in the last ∼3 yr before explosion. 

Abstract We present ultraviolet/optical/near-infrared observations and modeling of Type II supernovae (SNe II) whose early time (δt< 2 days) spectra show transient, narrow emission lines from shock ionization of confined (r< 10¹⁵cm) circumstellar material (CSM). The observed electron-scattering broadened line profiles (i.e., IIn-like) of Hi, Hei/ii, Civ, and Niii/iv/vfrom the CSM persist on a characteristic timescale (t_IIn) that marks a transition to a lower-density CSM and the emergence of Doppler-broadened features from the fast-moving SN ejecta. Our sample, the largest to date, consists of 39 SNe with early time IIn-like features in addition to 35 “comparison” SNe with no evidence of early time IIn-like features, all with ultraviolet observations. The total sample includes 50 unpublished objects with a total of 474 previously unpublished spectra and 50 multiband light curves, collected primarily through the Young Supernova Experiment and Global Supernova Project collaborations. For all sample objects, we find a significant correlation between peak ultraviolet brightness and botht_IInand the rise time, as well as evidence for enhanced peak luminosities in SNe II with IIn-like features. We quantify mass-loss rates and CSM density for the sample through the matching of peak multiband absolute magnitudes, rise times,t_IIn, and optical SN spectra with a grid of radiation hydrodynamics and non-local thermodynamic equilibrium radiative-transfer simulations. For our grid of models, all with the same underlying explosion, there is a trend between the duration of the electron-scattering broadened line profiles and inferred mass-loss rate: $t_{\mathrm{IIn}}\approx 3.8[\dot{M}/$(0.01M_⊙yr⁻¹)] days. 

Abstract The modern study of astrophysical transients has been transformed by an exponentially growing volume of data. Within the last decade, the transient discovery rate has increased by a factor of ∼20, with associated survey data, archival data, and metadata also increasing with the number of discoveries. To manage the data at this increased rate, we require new tools. Here we presentYSE-PZ, a transient survey management platform that ingests multiple live streams of transient discovery alerts, identifies the host galaxies of those transients, downloads coincident archival data, and retrieves photometry and spectra from ongoing surveys.YSE-PZalso presents a user with a range of tools to make and support timely and informed transient follow-up decisions. Those subsequent observations enhance transient science and can reveal physics only accessible with rapid follow-up observations. Rather than automating out human interaction,YSE-PZfocuses on accelerating and enhancing human decision making, a role we describe as empowering the human-in-the-loop. Finally,YSE-PZis built to be flexibly used and deployed;YSE-PZcan support multiple, simultaneous, and independent transient collaborations through group-level data permissions, allowing a user to view the data associated with the union of all groups in which they are a member.YSE-PZcan be used as a local instance installed via Docker or deployed as a service hosted in the cloud. We provideYSE-PZas an open-source tool for the community. 

Abstract We present photometric and spectroscopic data for SN 2022joj, a nearby peculiar Type Ia supernova (SN Ia) with a fast decline rate (Δm_15,B= 1.4 mag). SN 2022joj shows exceedingly red colors, with a value of approximatelyB−V≈ 1.1 mag during its initial stages, beginning from 11 days before maximum brightness. As it evolves, the flux shifts toward the blue end of the spectrum, approachingB−V≈ 0 mag around maximum light. Furthermore, at maximum light and beyond, the photometry is consistent with that of typical SNe Ia. This unusual behavior extends to its spectral characteristics, which initially displayed a red spectrum and later evolved to exhibit greater consistency with typical SNe Ia. Spectroscopically, we find strong agreement between SN 2022joj and double detonation models with white dwarf masses of around 1M_⊙and a thin He shell between 0.01 and 0.05M_⊙. Moreover, the early red colors are explained by line-blanketing absorption from iron peak elements created by the double detonation scenario in similar mass ranges. The nebular spectra in SN 2022joj deviate from expectations for double detonation, as we observe strong [Feiii] emission instead of [Caii] lines as anticipated, though this is not as robust a prediction as early red colors and spectra. The fact that as He shells get thinner these SNe start to look more like normal SNe Ia raises the possibility that this is the triggering mechanism for the majority of SNe Ia, though evidence would be missed if the SNe are not observed early enough. 

Abstract Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory (Rubin) will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze the development of robust classifiers under LSST-like conditions of a nonrepresentative training set for a large photometric test set of imbalanced classes. Over 1000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between 2018 September 28 and 2018 December 17, ultimately identifying three winners in 2019 February. Participants produced classifiers employing a diverse set of machine-learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multilayer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state of the art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next-generation PLAsTiCC data set. 

ABSTRACT After correcting for their light-curve shape and colour, Type Ia supernovae (SNe Ia) are precise cosmological distance indicators. However, there remains a non-zero intrinsic scatter in the differences between measured distance and that inferred from a cosmological model (i.e. Hubble residuals or HRs), indicating that SN Ia distances can potentially be further improved. We use the open-source relational data base kaepora to generate composite spectra with desired average properties of phase, light-curve shape, and HR. At many phases, the composite spectra from two subsamples with positive and negative average HRs are significantly different. In particular, in all spectra from 9 d before to 15 d after peak brightness, we find that SNe with negative HRs have, on average, higher ejecta velocities (as seen in nearly every optical spectral feature) than SNe with positive HRs. At +4 d relative to B-band maximum, using a sample of 62 SNe Ia, we measure a 0.091 ± 0.035 mag (2.7σ) HR step between SNe with Si ii λ6355 line velocities ($$v_{Si\, rm{\small II}}$$) higher/lower than −11 000 km s−1 (the median velocity). After light-curve shape and colour correction, SNe with higher velocities tend to have underestimated distance moduli relative to a cosmological model. The intrinsic scatter in our sample reduces from 0.094 to 0.082 mag after making this correction. Using the Si ii λ6355 velocity evolution of 115 SNe Ia, we estimate that a velocity difference >500 km s−1 exists at each epoch between the positive-HR and negative-HR samples with 99.4 per cent confidence. Finally at epochs later than +37 d, we observe that negative-HR composite spectra tend to have weaker spectral features in comparison to positive-HR composite spectra. 

Abstract We present the Keck Infrared Transient Survey, a NASA Key Strategic Mission Support program to obtain near-infrared (NIR) spectra of astrophysical transients of all types, and its first data release, consisting of 105 NIR spectra of 50 transients. Such a data set is essential as we enter a new era of IR astronomy with the James Webb Space Telescope (JWST) and the upcoming Nancy Grace Roman Space Telescope (Roman). NIR spectral templates will be essential to search JWST images for stellar explosions of the first stars and to plan an effective Roman SN Ia cosmology survey, both key science objectives for mission success. Between 2022 February and 2023 July, we systematically obtained 274 NIR spectra of 146 astronomical transients, representing a significant increase in the number of available NIR spectra in the literature. Here, we describe the first release of data from the 2022A semester. We systematically observed three samples: a flux-limited sample that includes all transients <17 mag in a red optical band (usually ZTFror ATLASobands); a volume-limited sample including all transients within redshiftz< 0.01 (D≈ 50 Mpc); and an SN Ia sample targeting objects at phases and light-curve parameters that had scant existing NIR data in the literature. The flux-limited sample is 39% complete (60% excluding SNe Ia), while the volume-limited sample is 54% complete and is 79% complete toz= 0.005. Transient classes observed include common Type Ia and core-collapse supernovae, tidal disruption events, luminous red novae, and the newly categorized hydrogen-free/helium-poor interacting Type Icn supernovae. We describe our observing procedures and data reduction usingPypeIt, which requires minimal human interaction to ensure reproducibility. 

Abstract We present multiwavelength observations of the Type II SN 2020pni. Classified at ∼1.3 days after explosion, the object showed narrow (FWHM intensity <250 km s −1 ) recombination lines of ionized helium, nitrogen, and carbon, as typically seen in flash-spectroscopy events. Using the non-LTE radiative transfer code CMFGEN to model our first high-resolution spectrum, we infer a progenitor mass-loss rate of M ̇ = ( 3.5 – 5.3 ) × 10 − 3 M ⊙ yr −1 (assuming a wind velocity of v w = 200 km s −1 ), estimated at a radius of R in = 2.5 × 10 14 cm. In addition, we find that the progenitor of SN 2020pni was enriched in helium and nitrogen (relative abundances in mass fractions of 0.30–0.40 and 8.2 × 10 −3 , respectively). Radio upper limits are also consistent with dense circumstellar material (CSM) and a mass-loss rate of M ̇ > 5 × 10 − 4 M ☉ yr − 1 . During the initial 4 days after first light, we also observe an increase in velocity of the hydrogen lines (from ∼250 to ∼1000 km s −1 ), suggesting complex CSM. The presence of dense and confined CSM, as well as its inhomogeneous structure, indicates a phase of enhanced mass loss of the progenitor of SN 2020pni during the last year before explosion. Finally, we compare SN 2020pni to a sample of other shock-photoionization events. We find no evidence of correlations among the physical parameters of the explosions and the characteristics of the CSM surrounding the progenitors of these events. This favors the idea that the mass loss experienced by massive stars during their final years could be governed by stochastic phenomena and that, at the same time, the physical mechanisms responsible for this mass loss must be common to a variety of different progenitors.