Nobel Laureates of the University of California

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.

The Nancy Grace Roman Space Telescope (Roman) is an observatory for both wide-field observations and coronagraphy that is scheduled for launch in the mid-2020s. Part of the planned survey is a deep, cadenced field or fields that enable cosmological measurements with type Ia supernovae (SNe Ia). With a pixel scale of 0 11, the Wide Field Instrument will be undersampled, presenting a difficulty for precisely subtracting the galaxy light underneath the SNe. We use simulated data to validate the ability of a forward-model code (such codes are frequently also called “scene-modeling” codes) to perform precision supernova photometry for the Roman SN survey. Our simulation includes over 760,000 image cutouts around SNe Ia or host galaxies (∼10% of a full-scale survey). To have a realistic 2D distribution of underlying galaxy light, we use the VELA simulated high-resolution images of galaxies. We run each set of cutouts through our forward-modeling code which automatically measures time-dependent SN fluxes. Given our assumed inputs of a perfect model of the instrument point-spread functions and calibration, we find biases at the millimagnitude level from this method in four red filters (Y106, J129, H158, and F184), easily meeting the 0.5% Roman inter-filter calibration requirement for a cutting-edge measurement of cosmological parameters using SNe Ia. Simulated data in the bluer Z087 filter shows larger ∼ 2–3 mmg biases, also meeting this requirement, but with more room for improvement. Our forward-model code has been released on Zenodo.

We study the spectral diversity of Type Ia supernovae (SNe Ia) at maximum light using high signal-to-noise spectrophotometry of 173 SNe Ia from the Nearby Supernova Factory. We decompose the diversity of these spectra into different extrinsic and intrinsic components, and we construct a nonlinear parameterization of the intrinsic diversity of SNe Ia that preserves pairings of "twin"SNe Ia. We call this parameterization the "Twins Embedding."Our methodology naturally handles highly nonlinear variability in spectra, such as changes in the photosphere expansion velocity, and uses the full spectrum rather than being limited to specific spectral line strengths, ratios, or velocities. We find that the time evolution of SNe Ia near maximum light is remarkably similar, with 84.6% of the variance in common to all SNe Ia. After correcting for brightness and color, the intrinsic variability of SNe Ia is mostly restricted to specific spectral lines, and we find intrinsic dispersions as low as ∼0.02 mag between 6600 and 7200 Å. With a nonlinear three-dimensional model plus one dimension for color, we can explain 89.2% of the intrinsic diversity in our sample of SNe Ia, which includes several different kinds of "peculiar"SNe Ia. A linear model requires seven dimensions to explain a comparable fraction of the intrinsic diversity. We show how a wide range of previously established indicators of diversity in SNe Ia can be recovered from the Twins Embedding. In a companion article, we discuss how these results can be applied to the standardization of SNe Ia for cosmology.

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.

We show how spectra of Type Ia supernovae (SNe Ia) at maximum light can be used to improve cosmological distance estimates. In a companion article, we used manifold learning to build a three-dimensional parameterization of the intrinsic diversity of SNe Ia at maximum light that we call the "Twins Embedding."In this article, we discuss how the Twins Embedding can be used to improve the standardization of SNe Ia. With a single spectrophotometrically calibrated spectrum near maximum light, we can standardize our sample of SNe Ia with an rms of 0.101 0.007 mag, which corresponds to 0.084 0.009 mag if peculiar velocity contributions are removed and to 0.073 0.008 mag if a larger reference sample were obtained. Our techniques can standardize the full range of SNe Ia, including those typically labeled as peculiar and often rejected from other analyses. We find that traditional light-curve width + color standardization such as SALT2 is not sufficient. The Twins Embedding identifies a subset of SNe Ia, including, but not limited to, 91T-like SNe Ia whose SALT2 distance estimates are biased by 0.229 0.045 mag. Standardization using the Twins Embedding also significantly decreases host-galaxy correlations. We recover a host mass step of 0.040 0.020 mag compared to 0.092 0.026 mag for SALT2 standardization on the same sample of SNe Ia. These biases in traditional standardization methods could significantly impact future cosmology analyses if not properly taken into account.

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 ΔY = 0.163 ± 0.029 mag (5.7σ) 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 ΔM = 0.119 ± 0.032 mag (4.5σ), for the same set of SNe Ia. When fit simultaneously, the environment-age offset remains very significant, with ΔY = 0.129 ± 0.032 mag (4.0σ), while the global stellar mass step is reduced to ΔM = 0.064 ± 0.029 mag (2.2σ). 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. 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.

The Type Ia supernova (SN Ia) LSQ14fmg exhibits exaggerated properties that may help to reveal the origin of the "super-Chandrasekhar"(or 03fg-like) group. The optical spectrum is typical of a 03fg-like SN Ia, but the light curves are unlike those of any SNe Ia observed. The light curves of LSQ14fmg rise extremely slowly. At -23 rest-frame days relative to B-band maximum, LSQ14fmg is already brighter than MV = -19 mag before host extinction correction. The observed color curves show a flat evolution from the earliest observation to approximately 1 week after maximum. The near-infrared light curves peak brighter than -20.5 mag in the J and H bands, far more luminous than any 03fg-like SNe Ia with near-infrared observations. At 1 month past maximum, the optical light curves decline rapidly. The early, slow rise and flat color evolution are interpreted to result from an additional excess flux from a power source other than the radioactive decay of the synthesized 56Ni. The excess flux matches the interaction with a typical superwind of an asymptotic giant branch (AGB) star in density structure, mass-loss rate, and duration. The rapid decline starting at around 1 month past B-band maximum may be an indication of rapid cooling by active carbon monoxide (CO) formation, which requires a low-temperature and high-density environment. These peculiarities point to an AGB progenitor near the end of its evolution and the core degenerate scenario as the likely explosion mechanism for LSQ14fmg.

© P.-F. Léget et al. 2020. Context. Type Ia supernovae (SNe Ia) are widely used to measure the expansion of the Universe. Improving distance measurements of SNe Ia is one technique to better constrain the acceleration of expansion and determine its physical nature. Aims. This document develops a new SNe Ia spectral energy distribution (SED) model, called the SUpernova Generator And Reconstructor (SUGAR), which improves the spectral description of SNe Ia, and consequently could improve the distance measurements. Methods. This model was constructed from SNe Ia spectral properties and spectrophotometric data from the Nearby Supernova Factory collaboration. In a first step, a principal component analysis-like method was used on spectral features measured at maximum light, which allowed us to extract the intrinsic properties of SNe Ia. Next, the intrinsic properties were used to extract the average extinction curve. Third, an interpolation using Gaussian processes facilitated using data taken at different epochs during the lifetime of an SN Ia and then projecting the data on a fixed time grid. Finally, the three steps were combined to build the SED model as a function of time and wavelength. This is the SUGAR model. Results. The main advancement in SUGAR is the addition of two additional parameters to characterize SNe Ia variability. The first is tied to the properties of SNe Ia ejecta velocity and the second correlates with their calcium lines. The addition of these parameters, as well as the high quality of the Nearby Supernova Factory data, makes SUGAR an accurate and efficient model for describing the spectra of normal SNe Ia as they brighten and fade. Conclusions. The performance of this model makes it an excellent SED model for experiments like the Zwicky Transient Facility, the Large Synoptic Survey Telescope, or the Wide Field Infrared Survey Telescope.

© 2019. The American Astronomical Society. All rights reserved.. We present a detailed high-resolution weak-lensing study of SPT-CL J2106-5844 at z = 1.132, claimed to be the most massive system discovered at z > 1 in the South Pole Telescope Sunyaev-Zel'dovich survey. Based on the deep imaging data from the Advanced Camera for Surveys and Wide Field Camera 3 on board the Hubble Space Telescope, we find that the cluster mass distribution is asymmetric, composed of a main clump and a subclump ∼640 kpc west thereof. The central clump is further resolved into two smaller northwestern and southeastern substructures separated by ∼150 kpc. We show that this rather complex mass distribution is more consistent with the cluster galaxy distribution than a unimodal distribution as previously presented. The northwestern substructure coincides with the brightest cluster galaxy and the X-ray peak while the southeastern one agrees with the location of the peak in number density. These morphological features and the comparison with the X-ray emission suggest that the cluster might be a merging system. We estimate the virial mass of the cluster to be M200c =(10.4-3.0+3.3 ± 1.0) × 1014 M⊙, where the second error bar is the systematic uncertainty. Our result confirms that the cluster SPT-CL J2106-5844 is indeed the most massive cluster at z > 1 known to date. We demonstrate the robustness of this mass estimate by performing a number of tests with different assumptions on the centroids, mass-concentration relations, and sample variance.

© 2019. The American Astronomical Society. All rights reserved. We present the Massive and Distant Clusters of WISE Survey (MaDCoWS), a search for galaxy clusters at 0.7 ≲ z ≲ 1.5 based upon data from the Wide-field Infrared Survey Explorer (WISE) mission. MaDCoWS is the first cluster survey capable of discovering massive clusters at these redshifts over the full extragalactic sky. The search is divided into two regions - the region of the extragalactic sky covered by Pan-STARRS (δ > -30°) and the remainder of the southern extragalactic sky at δ < -30° for which shallower optical data from the SuperCOSMOS Sky Survey is available. In this paper, we describe the search algorithm, characterize the sample, and present the first MaDCoWS data release - catalogs of the 2433 highest amplitude detections in the WISE-Pan-STARRS region and the 250 highest amplitude detections in the WISE-SuperCOSMOS region. A total of 1723 of the detections from the WISE-Pan-STARRS sample have also been observed with the Spitzer Space Telescope, providing photometric redshifts and richnesses, and an additional 64 detections within the WISE-SuperCOSMOS region also have photometric redshifts and richnesses. Spectroscopic redshifts for 38 MaDCoWS clusters with IRAC photometry demonstrate that the photometric redshifts have an uncertainty of σ z /(1 + z) ≃ 0.036. Combining the richness measurements with Sunyaev-Zel'dovich observations of MaDCoWS clusters, we also present a preliminary mass-richness relation that can be used to infer the approximate mass distribution of the full sample. The estimated median mass for the WISE-Pan-STARRS catalog is , with the Sunyaev-Zel'dovich data confirming that we detect clusters with masses up to M 500 ∼ 5 ×10 14 M (M 200 ∼ 10 15 M ).