Engineering topics

Nordin, J.

Publications and source records attributed to Nordin, J..

7 records

DOE OSTI2025

ZTF SN Ia DR2: Improved SN Ia colors through expanded dimensionality with SALT3+

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 parameter c , and a “stretch” parameter x 1 . We extend the model to include an additional parameter we label x 2 , 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 the SALTshaker code, 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 in g − r and r − i color curves, correlated with a boost in the height of the secondary maximum in i -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 with x 2 of 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.

Kenworthy, W. D. (ORCID:0000000251535983)↗

DOE OSTI2022

A Probabilistic Autoencoder for Type Ia Supernova Spectral Time Series

We construct a physically parameterized probabilistic autoencoder (PAE) to learn the intrinsic diversity of Type Ia supernovae (SNe Ia) from a sparse set of spectral time series. The PAE is a two-stage generative model, composed of an autoencoder that is interpreted probabilistically after training using a normalizing flow. We demonstrate that the PAE learns a low-dimensional latent space that captures the nonlinear range of features that exists within the population and can accurately model the spectral evolution of SNe Ia across the full range of wavelength and observation times directly from the data. By introducing a correlation penalty term and multistage training setup alongside our physically parameterized network, we show that intrinsic and extrinsic modes of variability can be separated during training, removing the need for the additional models to perform magnitude standardization. We then use our PAE in a number of downstream tasks on SNe Ia for increasingly precise cosmological analyses, including the automatic detection of SN outliers, the generation of samples consistent with the data distribution, and solving the inverse problem in the presence of noisy and incomplete data to constrain cosmological distance measurements. We find that the optimal number of intrinsic model parameters appears to be three, in line with previous studies, and show that we can standardize our test sample of SNe Ia with an rms of 0.091 ± 0.010 mag, which corresponds to 0.074 ± 0.010 mag if peculiar velocity contributions are removed.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Constraining Type Ia supernova explosions and early flux excesses with the Zwicky Transient Factory

In the new era of time-domain surveys, Type Ia supernovae are being caught sooner after explosion, which has exposed significant variation in their early light curves. Two driving factors for early-time evolution are the distribution of 56 Ni in the ejecta and the presence of flux excesses of various causes. We perform an analysis of the largest young SN Ia sample to date. We compare 115 SN Ia light curves from the Zwicky Transient Facility to the turtls model grid containing light curves of Chandrasekhar mass explosions with a range of 56 Ni masses, 56 Ni distributions, and explosion energies. We find that the majority of our observed light curves are well reproduced by Chandrasekhar mass explosion models with a preference for highly extended 56 Ni distributions. We identify six SNe Ia with an early-time flux excess in our gr-band data (four ‘blue’ and two ‘red’ flux excesses). We find an intrinsic rate of 18 ± 11 percent of early flux excesses in SNe Ia at z < 0.07, based on three detected flux excesses out of 30 (10 percent) observed SNe Ia with a simulated efficiency of 57 percent. This is comparable to rates of flux excesses in the literature but also accounts for detection efficiencies. Two of these events are mostly consistent with circumstellar material interaction, while the other four have longer lifetimes in agreement with companion interaction and 56 Ni-clump models. We find a higher frequency of flux excesses in 91T/99aa-like events (44 ± 13 percent).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Accuracy of environmental tracers and consequences for determining the Type Ia supernova magnitude step

Type Ia Supernovae (SNe Ia) are standardizable candles that allow us to measure the recent expansion rate of the Universe. Due to uncertainties in progenitor physics, potential astrophysical dependencies may bias cosmological measurements if not properly accounted for. The dependency of the intrinsic luminosity of SNe Ia with their host-galaxy environment is often used to standardize SNe Ia luminosity and is commonly parameterized as a step function. This functional form implicitly assumes two-populations of SNe Ia. In the literature, multiple environmental indicators have been considered, finding different, sometimes incompatible, step function amplitudes. We compare these indicators in the context of a two-populations model, based on their ability to distinguish the two populations. We show that local Hα-based specific star formation rate (lsSFR) and global stellar mass are better tracers than, for instance, host galaxy morphology. We show that tracer accuracy can explain the discrepancy between the observed SNe Ia step amplitudes found in the literature. Using lsSFR or global mass to identify the two populations can explain all other observations, though lsSFR is favoured. As lsSFR is strongly connected to age, our results favour a prompt and delayed population model. In any case, there exists two populations that differ in standardized magnitude by at least 0.121 ± 0.010 mag.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

SN 2020bqj: A Type Ibn supernova with a long-lasting peak plateau

We report type Ibn supernovae (SNe Ibn) are a rare class of stripped envelope supernovae interacting with a helium-rich circumstellar medium (CSM). The majority of the SNe Ibn reported in the literature display a surprising homogeneity in their fast-evolving lightcurves and are typically found in actively starforming spiral galaxies. We present the discovery and the study of SN 2020bqj (ZTF20aalrqbu), a SN Ibn with a long-duration peak plateau lasting 40 days and hosted by a faint low-mass galaxy. We aim to explain its peculiar properties using an extensive photometric and spectroscopic data set. We compare the photometric and spectral evolution of SN 2020bqj with regular SNe Ibn from the literature, as well as with other outliers in the SN Ibn subclass. We fit the bolometric and multi-band lightcurves with powering mechanism models such as radioactive decay and CSM interaction. We also model the host galaxy of SN 2020bqj. The risetime, peak magnitude and spectral features of SN 2020bqj are consistent with those of most SNe Ibn, but the SN is a clear outlier in the subclass based on its bright, long-lasting peak plateau and the low mass of its faint host galaxy. We show through modeling that the lightcurve of SN 2020bqj can be powered predominantly by shock heating from the interaction of the SN ejecta and a dense CSM, combined with radioactive decay. The peculiar Type Ibn SN 2011hw is a close analog to SN 2020bqj in terms of lightcurve and spectral evolution, suggesting a similar progenitor and CSM scenario. In this scenario a very massive progenitor star in the transitional phase between a luminous blue variable and a compact Wolf-Rayet star undergoes core-collapse, embedded in a dense helium-rich CSM with an elevated opacity compared to normal SNe Ibn, due to the presence of residual hydrogen. This scenario is consistent with the observed properties of SN 2020bqj and the modeling results. SN 2020bqj is a compelling example of a transitional SN Ibn/IIn based on not only its spectral features, but also its lightcurve, host galaxy properties and the inferred progenitor properties. The strong similarity with SN 2011hw suggests this subclass may be the result of a progenitor in a stellar evolution phase that is distinct from those of progenitors of regular SNe Ibn.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Redshift evolution of the underlying type Ia supernova stretch distribution

The detailed nature of type Ia supernovae (SNe Ia) remains uncertain, and as survey statistics increase, the question of astrophysical systematic uncertainties arises, notably that of the evolution of SN Ia populations. We study the dependence on redshift of the SN Ia SALT2.4 light-curve stretch, which is a purely intrinsic SN property, to probe its potential redshift drift. The SN stretch has been shown to be strongly correlated with the SN environment, notably with stellar age tracers. We modeled the underlying stretch distribution as a function of redshift, using the evolution of the fraction of young and old SNe Ia as predicted using the SNfactory dataset, and assuming a constant underlying stretch distribution for each age population consisting of Gaussian mixtures. We tested our prediction against published samples that were cut to have marginal magnitude selection effects, so that any observed change is indeed astrophysical and not observational in origin. In this first study, there are indications that the underlying SN Ia stretch distribution evolves as a function of redshift, and that the age drifting model is a better description of the data than any time-constant model, including the sample-based asymmetric distributions that are often used to correct Malmquist bias at a significance higher than 5σ. The favored underlying stretch model is a bimodal one, composed of a high-stretch mode shared by both young and old environments, and a low-stretch mode that is exclusive to old environments. The precise effect of the redshift evolution of the intrinsic properties of a SN Ia population on cosmology remains to be studied. The astrophysical drift of the SN stretch distribution does affect current Malmquist bias corrections, however, and thereby the distances that are derived based on SN that are affected by observational selection effects. We highlight that this bias will increase with surveys covering increasingly larger redshift ranges, which is particularly important for the Large Synoptic Survey Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Strong dependence of Type Ia supernova standardization on the local specific star formation rate

As part of an on-going effort to identify, understand and correct for astrophysics biases in the standardization of Type Ia supernovae (SN Ia) for cosmology, we have statistically classified a large sample of nearby SNe Ia into those that are located in predominantly younger or older environments. This classification is based on the specific star formation rate measured within a projected distance of 1 kpc from each SN location (LsSFR). This is an important refinement compared to using the local star formation rate directly, as it provides a normalization for relative numbers of available SN progenitors and is more robust against extinction by dust. We find that the SNe Ia in predominantly younger environments are Δ Y = 0.163 ± 0.029 mag (5.7 σ ) fainter than those in predominantly older environments after conventional light-curve standardization. This is the strongest standardized SN Ia brightness systematic connected to the host-galaxy environment measured to date. The well-established step in standardized brightnesses between SNe Ia in hosts with lower or higher total stellar masses is smaller, at Δ M = 0.119 ± 0.032 mag (4.5 σ ), for the same set of SNe Ia. When fit simultaneously, the environment-age offset remains very significant, with Δ Y = 0.129 ± 0.032 mag (4.0 σ ), while the global stellar mass step is reduced to Δ M = 0.064 ± 0.029 mag (2.2 σ ). Thus, approximately 70% of the variance from the stellar mass step is due to an underlying dependence on environment-based progenitor age. Also, we verify that using the local star formation rate alone is not as powerful as LsSFR at sorting SNe Ia into brighter and fainter subsets. Standardization that only uses the SNe Ia in younger environments reduces the total dispersion from 0.142 ± 0.008 mag to 0.120 ± 0.010 mag. Overall, we show that as environment-ages evolve with redshift, a strong bias, especially on the measurement of the derivative of the dark energy equation of state, can develop. Fortunately, data that measure and correct for this effect using our local specific star formation rate indicator, are likely to be available for many next-generation SN Ia cosmology experiments.

79 ASTRONOMY AND ASTROPHYSICS↗