arXiv subjects

Richard Kessler

Publications and source records attributed to Richard Kessler.

At least 37 records · Page 2Linked to original sources

arXiv2021

Improved Treatment of Host-Galaxy Correlations in Cosmological Analyses With Type Ia Supernovae

Improving the use of Type Ia supernovae (SNIa) as standard candles requires a better approach to incorporate the relationship between SNIa and the properties of their host galaxies. Using a spectroscopically-confirmed sample of $\sim$1600 SNIa, we develop the first empirical model of underlying populations for SNIa light-curve properties that includes their dependence on host-galaxy stellar mass. These populations are important inputs to simulations that are used to model selection effects and correct distance biases within the BEAMS with Bias Correction (BBC) framework. Here we improve BBC to also account for SNIa-host correlations, and we validate this technique on simulated data samples. We recover the input relationship between SNIa luminosity and host-galaxy stellar mass (the mass step, $γ$) to within 0.004 mags, which is a factor of 5 improvement over the previous method that results in a $γ$-bias of ${\sim}0.02$. We adapt BBC for a novel dust-based model of intrinsic brightness variations, which results in a greatly reduced mass step for data ($γ= 0.017 \pm 0.008$), and for simulations ($γ=0.006 \pm 0.007$). Analysing simulated SNIa, the biases on the dark energy equation-of-state, $w$, vary from $Δw = 0.006(5)$ to $0.010(5)$ with our new BBC method; these biases are significantly smaller than the $0.02(5)$ $w$-bias using previous BBC methods that ignore SNIa-host correlations.

astro-ph.CO↗

arXiv2020

Discovery of a Candidate Binary Supermassive Black Hole in a Periodic Quasar from Circumbinary Accretion Variability

Binary supermassive black holes (BSBHs) are expected to be a generic byproduct from hierarchical galaxy formation. The final coalescence of BSBHs is thought to be the loudest gravitational wave (GW) siren, yet no confirmed BSBH is known in the GW-dominated regime. While periodic quasars have been proposed as BSBH candidates, the physical origin of the periodicity has been largely uncertain. Here we report discovery of a periodicity (P=1607$\pm$7 days) at 99.95% significance (with a global p-value of ~$10^{-3}$ accounting for the look elsewhere effect) in the optical light curves of a redshift 1.53 quasar, SDSS J025214.67-002813.7. Combining archival Sloan Digital Sky Survey data with new, sensitive imaging from the Dark Energy Survey, the total ~20-yr time baseline spans ~4.6 cycles of the observed 4.4-yr (restframe 1.7-yr) periodicity. The light curves are best fit by a bursty model predicted by hydrodynamic simulations of circumbinary accretion disks. The periodicity is likely caused by accretion rate modulation by a milli-parsec BSBH emitting GWs, dynamically coupled to the circumbinary accretion disk. A bursty hydrodynamic variability model is statistically preferred over a smooth, sinusoidal model expected from relativistic Doppler boost, a kinematic effect proposed for PG1302-102. Furthermore, the frequency dependence of the variability amplitudes disfavors Doppler boost, lending independent support to the circumbinary accretion variability hypothesis. Given our detection rate of one BSBH candidate from circumbinary accretion variability out of 625 quasars, it suggests that future large, sensitive synoptic surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time may be able to detect hundreds to thousands of candidate BSBHs from circumbinary accretion with direct implications for Laser Interferometer Space Antenna.

astro-ph.GA↗

arXiv2020

Assessment of the Systematic Uncertainties in the Cosmological Analysis of the SDSS Supernovae Photometric Sample

Improvement in the precision of measurements of cosmological parameters with Type Ia Supernovae (SNIa) is expected to come from large photometrically identified (photometric) SN samples. Here we re-analyse the SDSS photometric SN sample, with roughly 700 high-quality, likely but unconfirmed SNIa light-curves, to develop new analysis tools aimed at evaluating systematic uncertainties on the dark energy equation-of-state parameter $w$. Since we require a spectroscopically measured host galaxy redshift for each SN, we determine the associated selection efficiency of host galaxies in order to simulate bias corrections. We determine that the mis-association rate of host galaxies is $0.6\%$; ignoring this effect in simulated bias corrections leads to a $w$-bias of $Δw = +0.0007$, where $w$ is evaluated from SNIa and priors from measurements of baryon acoustic oscillations and the cosmic microwave background. We assess the uncertainty in our modeling of the host galaxy selection efficiency and find the associated $w$ uncertainty to be $-0.0072$. Finally, we explore new core collapse (CC) models in simulated training samples and find that adjusting the CC luminosity distribution to be in agreement with previous Pan-STARRS analyses yields a better match to the SDSS data. The impact of ignoring this adjustment is $Δw = -0.0109$; the impact of replacing the new CC models with those used by Pan-STARRS is $Δw = -0.0028$. These systematic uncertainties are subdominant to the statistical constraints from the SDSS sample, but must be considered in future photometric analyses of large SN samples such as those from DES, LSST and WFIRST.

astro-ph.CO↗

arXiv2018

The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC): Data set

The Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC) is an open data challenge to classify simulated astronomical time-series data in preparation for observations from the Large Synoptic Survey Telescope (LSST), which will achieve first light in 2019 and commence its 10-year main survey in 2022. LSST will revolutionize our understanding of the changing sky, discovering and measuring millions of time-varying objects. In this challenge, we pose the question: how well can we classify objects in the sky that vary in brightness from simulated LSST time-series data, with all its challenges of non-representativity? In this note we explain the need for a data challenge to help classify such astronomical sources and describe the PLAsTiCC data set and Kaggle data challenge, noting that while the references are provided for context, they are not needed to participate in the challenge.

astro-ph.IM↗

arXiv2017

Science-Driven Optimization of the LSST Observing Strategy

The Large Synoptic Survey Telescope is designed to provide an unprecedented optical imaging dataset that will support investigations of our Solar System, Galaxy and Universe, across half the sky and over ten years of repeated observation. However, exactly how the LSST observations will be taken (the observing strategy or "cadence") is not yet finalized. In this dynamically-evolving community white paper, we explore how the detailed performance of the anticipated science investigations is expected to depend on small changes to the LSST observing strategy. Using realistic simulations of the LSST schedule and observation properties, we design and compute diagnostic metrics and Figures of Merit that provide quantitative evaluations of different observing strategies, analyzing their impact on a wide range of proposed science projects. This is work in progress: we are using this white paper to communicate to each other the relative merits of the observing strategy choices that could be made, in an effort to maximize the scientific value of the survey. The investigation of some science cases leads to suggestions for new strategies that could be simulated and potentially adopted. Notably, we find motivation for exploring departures from a spatially uniform annual tiling of the sky: focusing instead on different parts of the survey area in different years in a "rolling cadence" is likely to have significant benefits for a number of time domain and moving object astronomy projects. The communal assembly of a suite of quantified and homogeneously coded metrics is the vital first step towards an automated, systematic, science-based assessment of any given cadence simulation, that will enable the scheduling of the LSST to be as well-informed as possible.

astro-ph.IM↗

arXiv2017

Correcting Type Ia Supernova Distances for Selection Biases and Contamination in Photometrically Identified Samples

We present a new technique to create a bin-averaged Hubble Diagram (HD) from photometrically identified SN~Ia data. The resulting HD is corrected for selection biases and contamination from core collapse (CC) SNe, and can be used to infer cosmological parameters. This method, called "BBC" (BEAMS with Bias Corrections), includes two fitting stages. The first BBC fitting stage uses a posterior distribution that includes multiple SN likelihoods, a Monte Carlo simulation to bias-correct the fitted SALT-II parameters, and CC probabilities determined from a machine learning technique. The BBC fit determines 1) a bin-averaged HD (average distance vs. redshift), and 2) the nuisance parameters alpha and beta, which multiply the stretch and color (respectively) to standardize the SN brightness. In the second stage, the bin-averaged HD is fit to a cosmological model where priors can be imposed. We perform high precision tests of the BBC method by simulating large (150,000 event) data samples corresponding to the Dark Energy Survey Supernova Program. Our tests include three models of intrinsic scatter, each with two different CC rates. In the BBC fit, the SALT-II nuisance parameters alpha and beta are recovered to within 1% of their true values. In the cosmology fit, we determine the dark energy equation of state parameter w using a fixed value of Omega_matter as a prior: averaging over all six tests based on 6 x 150,000 = 900,000 SNe, there is a small w-bias of 0.006 +- 0.002. Finally, the BBC fitting code is publicly available in the SNANA package.

astro-ph.CO↗

arXiv2016

Search For Type Ia Supernova NUV-Optical Subclasses

In response to a recently reported observation of evidence for two classes of Type Ia Supernovae (SNe Ia) distinguished by their brightness in the rest-frame near ultraviolet (NUV), we search for the phenomenon in publicly available light-curve data. We use the SNANA supernova analysis package to simulate SN Ia-light curves in the Sloan Digital Sky Survey Supernova Search (SDSS) and the Supernova Legacy Survey (SNLS) with a model of two distinct ultraviolet classes of SNe Ia and a conventional model with a single broad distribution of SN-Ia ultraviolet brightnesses. We compare simulated distributions of rest-frame colors with these two models to those observed in 158 SNe Ia in the SDSS and SNLS data. The SNLS sample of 99 SNe Ia is in clearly better agreement with a model with one class of SN Ia light curves and shows no evidence for distinct NUV sub-classes. The SDSS sample of 59 SNe Ia with poorer color resolution does not distinguish between the two models.

astro-ph.CO↗

arXiv2016

Host Galaxy Identification for Supernova Surveys

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST), which will discover SNe by the thousands. Spectroscopic resources are limited, so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey.

astro-ph.CO↗

arXiv2016

Measuring Type Ia Supernova Populations of Stretch and Color and Predicting Distance Biases

Simulations of Type Ia Supernovae (SNIa) surveys are a critical tool for correcting biases in the analysis of SNIa to infer cosmological parameters. Large scale Monte Carlo simulations include a thorough treatment of observation history, measurement noise, intrinsic scatter models and selection effects. In this paper, we improve simulations with a robust technique to evaluate the underlying populations of SNIa color and stretch that correlate with luminosity. In typical analyses, the standardized SNIa brightness is determined from linear `Tripp' relations between the light curve color and luminosity and between stretch and luminosity. However, this solution produces Hubble residual biases because intrinsic scatter and measurement noise result in measured color and stretch values that do not follow the Tripp relation. We find a $10σ$ bias (up to 0.3 mag) in Hubble residuals versus color and $5σ$ bias (up to 0.2 mag) in Hubble residuals versus stretch in a joint sample of 920 spectroscopically confirmed SNIa from PS1, SNLS, SDSS and several low-z surveys. After we determine the underlying color and stretch distributions, we use simulations to predict and correct the biases in the data. We show that removing these biases has a small impact on the low-z sample, but reduces the intrinsic scatter $σ_{\textrm{int}}$ from $0.101$ to $0.083$ in the combined PS1, SNLS and SDSS sample. Past estimates of the underlying populations were too broad, leading to a small bias in the equation-of-state of dark energy $w$ of $Δw=0.005$.

astro-ph.CO↗

arXiv2014

Three-dimensional Simulations of Pure Deflagration Models for Thermonuclear Supernovae

We present a systematic study of the pure deflagration model of Type Ia supernovae using three-dimensional, high-resolution, full-star hydrodynamical simulations, nucleosynthetic yields calculated using Lagrangian tracer particles, and light curves calculated using radiation transport. We evaluate the simulations by comparing their predicted light curves with many observed SNe Ia using the SALT2 data-driven model and find that the simulations may correspond to under-luminous SNe Iax. We explore the effects of the initial conditions on our results by varying the number of randomly selected ignition points from 63 to 3500, and the radius of the centered sphere they are confined in from 128 to 384 km. We find that the rate of nuclear burning depends on the number of ignition points at early times, the density of ignition points at intermediate times, and the radius of the confining sphere at late times. The results depend primarily on the number of ignition points, but we do not expect this to be the case in general. The simulations with few ignition points release more nuclear energy $E_{\mathrm{nuc}}$, have larger kinetic energies $E_{\mathrm{K}}$, and produce more $^{56}$Ni than those with many ignition points, and differ in the distribution of $^{56}$Ni, Si, and C/O in the ejecta. For these reasons, the simulations with few ignition points exhibit higher peak B-band absolute magnitudes $M_\mathrm{B}$ and light curves that rise and decline more quickly; their $M_\mathrm{B}$ and light curves resemble those of under-luminous SNe Iax, while those for simulations with many ignition points are not.

astro-ph.HE↗

arXiv2014

The Data Release of the Sloan Digital Sky Survey-II Supernova Survey

This paper describes the data release of the Sloan Digital Sky Survey-II (SDSS-II) Supernova Survey conducted between 2005 and 2007. Light curves, spectra, classifications, and ancillary data are presented for 10,258 variable and transient sources discovered through repeat ugriz imaging of SDSS Stripe 82, a 300 deg2 area along the celestial equator. This data release is comprised of all transient sources brighter than r~22.5 mag with no history of variability prior to 2004. Dedicated spectroscopic observations were performed on a subset of 889 transients, as well as spectra for thousands of transient host galaxies using the SDSS-III BOSS spectrographs. Photometric classifications are provided for the candidates with good multi-color light curves that were not observed spectroscopically. From these observations, 4607 transients are either spectroscopically confirmed, or likely to be, supernovae, making this the largest sample of supernova candidates ever compiled. We present a new method for SN host-galaxy identification and derive host-galaxy properties including stellar masses, star-formation rates, and the average stellar population ages from our SDSS multi-band photometry. We derive SALT2 distance moduli for a total of 1443 SN Ia with spectroscopic redshifts as well as photometric redshifts for a further 677 purely-photometric SN Ia candidates. Using the spectroscopically confirmed subset of the three-year SDSS-II SN Ia sample and assuming a flat Lambda-CDM cosmology, we determine Omega_M = 0.315 +/- 0.093 (statistical error only) and detect a non-zero cosmological constant at 5.7 sigmas.

astro-ph.CO↗

arXiv2013

Comparing the light curves of simulated Type Ia Supernovae with observations using data-driven models

We propose a robust, quantitative method to compare the synthetic light curves of a Type Ia Supernova (SNIa) explosion model with a large set of observed SNeIa, and derive a figure of merit for the explosion model's agreement with observations. The synthetic light curves are fit with the data-driven model SALT2 which returns values for stretch, color, and magnitude at peak brightness, as well as a goodness-of-fit parameter. Each fit is performed multiple times with different choices of filter bands and epoch range in order to quantify the systematic uncertainty on the fitted parameters. We use a parametric population model for the distribution of observed SNIa parameters from large surveys, and extend it to represent red, dim, and bright outliers found in a low-redshift SNIa data set. We discuss the potential uncertainties of this population model and find it to be reliable given the current uncertainties on cosmological parameters. Using our population model, we assign each set of fitted parameters a likelihood of being observed in nature, and a figure of merit based on this likelihood. We define a second figure of merit based on the quality of the light curve fit, and combine the two measures into an overall figure of merit for each explosion model. We compute figures of merit for a variety of 1D, 2D and 3D explosion models and show that our evaluation method allows meaningful inferences across a wide range of light curve quality and fitted parameters.

astro-ph.CO↗

arXiv2012

Testing Models of Intrinsic Brightness Variations in Type Ia Supernovae, and their Impact on Measuring Cosmological Parameters

For spectroscopically confirmed Type Ia supernovae we evaluate models of intrinsic brightness variations with detailed data/Monte Carlo comparisons of the dispersion in the following quantities: Hubble-diagram scatter, color difference (B-V-c) between the true B-V color and the fitted color (c) from the SALT-II light curve model, and photometric redshift residual. The data sample includes 251 ugriz light curves from the 3-season Sloan Digital Sky Survey-II, and 191 griz light curves from the Supernova Legacy Survey 3-year data release. We find that the simplest model of a wavelength-independent (coherent) scatter is not adequate, and that to describe the data the intrinsic scatter model must have wavelength-dependent variations. We use Monte Carlo simulations to examine the standard approach of adding a coherent scatter term in quadrature to the distance-modulus uncertainty in order to bring the reduced chi2 to unity when fitting a Hubble diagram. If the light curve fits include model uncertainties with the correct wavelength dependence of the scatter, we find that the bias on the dark energy equation of state parameter $w$ is negligible. However, incorrect model uncertainties can lead to a significant bias on the distance moduli, with up to ~0.05 mag redshift-dependent variation. For the recent SNLS3 cosmology results we estimate that this effect introduces an additional systematic uncertainty on $w$ of ~0.02, well below the total uncertainty. However, this uncertainty depends on the samples used, and thus this small $w$-uncertainty is not guaranteed in future cosmology results.

astro-ph.CO↗

arXiv2012

A Mismatch in the Ultraviolet Spectra between Low-Redshift and Intermediate-Redshift Type Ia Supernovae as a Possible Systematic Uncertainty for Supernova Cosmology

We present Keck high-quality rest-frame ultraviolet (UV) through optical spectra of 21 Type Ia supernovae (SNe Ia) in the redshift range 0.11 < z < 0.37 and a mean redshift of 0.22 that were discovered during the Sloan Digital Sky Survey-II (SDSS-II) SN Survey. Using the broad-band photometry of the SDSS survey, we are able to reconstruct the SN host-galaxy spectral energy distributions (SEDs), allowing for a correction for the host-galaxy contamination in the SN Ia spectra. Comparison of composite spectra constructed from a subsample of 17 high-quality spectra to those created from a low-redshift sample with otherwise similar properties shows that the Keck/SDSS SNe Ia have, on average, extremely similar rest-frame optical spectra but show a UV flux excess. This observation is confirmed by comparing synthesized broad-band colors of the individual spectra, showing a difference in mean colors at the 2.4 - 4.4 sigma level for various UV colors. We further see a slight difference in the UV spectral shape between SNe with low-mass and high-mass host galaxies. Additionally, we detect a relationship between the flux ratio at 2770 and 2900 A and peak luminosity that differs from that observed at low redshift. We find that changing the UV SED of an SN Ia within the observed dispersion can change the inferred distance moduli by ~0.1 mag. This effect only occurs when the data probe the rest-frame UV. We suggest that this discrepancy could be due to differences in the host-galaxy population of the two SN samples or to small-sample statistics.

astro-ph.CO↗

arXiv2011

Spectroscopic Properties of Star-Forming Host Galaxies and Type Ia Supernova Hubble Residuals in a Nearly Unbiased Sample

We examine the correlation between supernova host galaxy properties and their residuals on the Hubble diagram. We use supernovae discovered during the Sloan Digital Sky Survey II - Supernova Survey, and focus on objects at a redshift of z < 0.15, where the selection effects of the survey are known to yield a complete Type Ia supernova sample. To minimize the bias in our analysis with respect to measured host-galaxy properties, spectra were obtained for nearly all hosts, spanning a range in magnitude of -23 < M_r < -17. In contrast to previous works that use photometric estimates of host mass as a proxy for global metallicity, we analyze host-galaxy spectra to obtain gas-phase metallicities and star-formation rates from host galaxies with active star formation. From a final sample of ~ 40 emission-line galaxies, we find that light-curve corrected Type Ia supernovae are ~ 0.1 magnitudes brighter in high-metallicity hosts than in low-metallicity hosts. We also find a significant (> 3σ) correlation between the Hubble residuals of Type Ia supernovae and the specific star-formation rate of the host galaxy. We comment on the importance of supernova/host-galaxy correlations as a source of systematic bias in future deep supernova surveys.

astro-ph.CO↗

arXiv2011

The SDSS-II Supernova Survey: Parameterizing the Type Ia Supernova Rate as a Function of Host Galaxy Properties

Using data from the Sloan Digital Sky Supernova Survey-II, we measure the rate of Type Ia Supernovae (SNe Ia) as a function of galaxy properties at intermediate redshift. A sample of 342 SNe Ia with 0.05<z<0.25 is constructed. Using broad-band photometry we use the PEGASE spectral energy distributions (SEDs) to estimate host galaxy stellar masses and recent star-formation rates. We find that the rate of SNe Ia per unit stellar mass is significantly higher (by a factor of ~30) in highly star-forming galaxies compared to passive galaxies. When parameterizing the SN Ia rate (SNR_Ia) based on host galaxy properties, we find that the rate of SNe Ia in passive galaxies is not linearly proportional to the stellar mass, instead a SNR_Ia proportional to M^0.68 is favored. However, such a parameterization does not describe the observed SN Ia rate in star-forming galaxies. The SN Ia rate in star-forming galaxies is well fit by SNR_Ia = 1.05\pm0.16x10^{-10} M ^{0.68\pm0.01} + 1.01\pm0.09x10^{-3} SFR^{1.00\pm0.05} (statistical errors only), where M is the host galaxy mass and SFR is the star-formation rate. These results are insensitive to the selection criteria used, redshift limit considered and the inclusion of non-spectroscopically confirmed SNe Ia. We also show there is a dependence between the distribution of the MLCS light-curve decline rate parameter, Δ, and host galaxy type. Passive galaxies host less luminous SNe Ia than seen in moderately and highly star-forming galaxies, although a population of luminous SNe is observed in passive galaxies, contradicting previous assertions that these SNe Ia are only observed in younger stellar systems. The MLCS extinction parameter, A_V, is similar in passive and moderately star-forming galaxies, but we find indications that it is smaller, on average, in highly star-forming galaxies. We confirm these results using the SALT2 light-curve fitter.

astro-ph.CO↗

arXiv2011

The effect of peculiar velocities on supernova cosmology

We present an analysis of peculiar velocities and their effect on supernova cosmology. In particular, we study (a) the corrections due to our own motion, (b) the effects of correlations in peculiar velocities induced by large-scale structure, and (c) uncertainties arising from a possible local under- or over-density. For all of these effects we present a case study of their impact on the cosmology derived by the Sloan Digital Sky Survey-II Supernova Survey (SDSS-II SN Survey). Correcting supernova redshifts for the CMB dipole slightly over-corrects nearby supernovae that share some of our local motion. We show that while neglecting the CMB dipole would cause a shift in the derived equation of state of Delta w ~ 0.04 (at fixed matter density) the additional local-motion correction is currently negligible (Delta w<0.01). We use a covariance-matrix approach to statistically account for correlated peculiar velocities. This down-weights nearby supernovae and effectively acts as a graduated version of the usual sharp low-redshift cut. Neglecting coherent velocities in the current sample causes a systematic shift of ~2% in the preferred value of w and will therefore have to be considered carefully when future surveys aim for percent-level accuracy. Finally, we perform n-body simulations to estimate the likely magnitude of any local density fluctuation (monopole) and estimate the impact as a function of the low-redshift cutoff. We see that for this aspect the low-z cutoff of z=0.02 is well-justified theoretically, but that living in a putative local density fluctuation leaves an indelible imprint on the magnitude-redshift relation.

astro-ph.CO↗

arXiv2011

Improved Constraints on Type Ia Supernova Host Galaxy Properties using Multi-Wavelength Photometry and their Correlations with Supernova Properties

We improve estimates of stellar mass and mass-weighted average age of Type Ia supernova (SN Ia) host galaxies by combining UV and near-IR photometry with optical photometry in our analysis. Using 206 SNe Ia drawn from the full three-year SDSS-II Supernova Survey (median redshift of z {\approx} 0.2) and multi-wavelength host-galaxy photometry from SDSS, GALEX, and UKIDSS, we present evidence of a correlation (1.9σ confidence level) between the residuals of SNe Ia about the best-fit Hubble relation and the mass-weighted average age of their host galaxies. The trend is such that older galaxies host SNe Ia that are brighter than average after standard light-curve corrections are made. We also confirm, at the 3.0σ level, the trend seen by previous studies that more massive galaxies often host brighter SNe Ia after light-curve correction.

astro-ph.CO↗