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Brodie Popovic

Publications and source records attributed to Brodie Popovic.

At least 19 recordsLinked to original sources

Supernovae Unite: Combining Pantheon+ and DES-SN5YR

We present the Hubble diagram and cosmological constraints resulting from the combination of the Pantheon+ and DES-SN5YR supernova (SN) samples, which we refer to as Unite. Unite updates Pantheon+, including methodology improvements that the DES sample enabled, and adds the new SN from the DES survey. This represents the most comprehensive and internally consistent SN Ia dataset available, consisting of 2884 likely type Ia supernovae. This work features consistent SN Ia modelling, sample selection, and bias corrections. We also redetermine host-galaxy stellar masses for over 98% of the sample using a consistent framework. Using Unite alone, for a flat universe with a cosmological constant (Flat-$\Lambda$CDM), we find $\Omega_{\rm m} = 0.310^{+0.012}_{-0.011}$. We further present constraints using the Unite sample combined with Cosmic Microwave Background and both DES and DESI Baryon Acoustic Oscillation data. We find strong evidence of tension between CMB measurements and the combined BAO and supernova datasets when fitting a model with constant dark energy equation of state ($w$), which is alleviated when allowing $w$ to vary with time. For a flat universe with dark energy that has a time-evolving equation of state parametrized by $w_0$ and $w_a$ we find $(\Omega_{\rm m},w_0,w_a) = (0.305\pm0.004,-0.861^{+0.044}_{-0.042},-0.60^{+0.17}_{-0.19})$ with a dark energy Figure of Merit of 315. This corresponds to a $\sim30\%$ reduction in the area of the $w_0-w_a$ confidence region relative to previous constraints from the combination of DES Y6, DESI-DR2, and CMB data (arXiv:2605.27221). The Bayesian evidence indicates only weak preference for time evolving dark energy, whereas frequentist analyses yield a preference over Flat-$\Lambda$CDM at a significance of $3.3\sigma$ ($3.1\sigma$) when using the maximum $\textit{a posteriori}$ probability (maximum likelihood).

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Still Accelerating: Type Ia supernova cosmology is robust to host galaxy age evolution

Type Ia supernovae are a cornerstone of modern cosmology, providing first evidence for cosmic acceleration and new tests of dark energy. Son et al. 2025 (S25) claim a strong redshift evolution in standardized supernova luminosities driven by supernova progenitor age, with dramatic cosmological implications: rapidly evolving dark energy, decelerating expansion, and a $9σ$ tension with $Λ$CDM. We show that the underpinning evidence required for this conclusion -- the supernova progenitor-age dependence, the redshift-dependent age difference, and their combined impact -- is either negligible or relies on effects already corrected for in modern supernova analyses. First, the S25 analysis omits the standard host-galaxy stellar mass correction that captures known environmental dependencies that also correlate with stellar age. Applying this correction to the S25 sample, we find no dependence of standardized supernova brightness on host age. Independent data also show no significant difference at low-redshift in standardized brightness between star-forming galaxies and several Gyr older quiescent galaxies of the same stellar mass. Second, the S25 scenario predicts strong redshift evolution of the host-mass effect. Data from the Dark Energy Survey supernova survey measure evolution of $-0.028 \pm 0.034~\mathrm{mag}\,z^{-1}$, consistent with zero and altering the dark-energy equation-of-state measurement ($w$) by $<$0.01 if included. Third, we demonstrate that the claimed $\sim5$~Gyr progenitor age difference between nearby and distant supernovae is overstated by factors of three to five largely due to a conflation of host galaxy age with supernova progenitor age. We conclude that type~Ia supernova cosmology remains robust for current measurements of dark energy.

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Old Universe, Young SNe Ia: A Statistical Analysis of Type Ia Supernova Progenitor Age from 6,983 TITAN Host Galaxies, and Implications for Cosmology

Correlations between standardized Type Ia supernova (SN Ia) luminosities and host-galaxy properties are routinely modeled to avoid bias in cosmological parameter inference. A recent hypothesis attributes these correlations to progenitor-age variations and, combined with a strong ($\sim$5-6 Gyr) age evolution between low- and high-redshift samples, could alter cosmological conclusions. We test this scenario using the SN Ia host galaxies of TITAN DR1, the largest low-redshift sample of its kind to date (6,983 hosts; 0 $\lesssim$ z $\lesssim$ 0.15). Progenitor ages are estimated by combining host-galaxy star-formation histories (SFHs) with empirical delay-time distributions. The SFHs are constrained via spectral energy distribution (SED) fitting of photometry spanning ultraviolet (UV) to mid-infrared (MIR) wavelengths, enabling robust separation of dusty star-forming and quiescent systems. The resulting progenitor-age distribution has a mean of 3.5 Gyr, substantially younger than predicted by strong-evolution models. It is strongly peaked near 2.2 Gyr, predominantly from star-forming hosts (60% of the sample), with a smaller, broader component centered near 6.0 Gyr from quiescent systems. Restricting to high-mass galaxies (in order to isolate progenitor effects from the mass-step), the age difference between host types reduces to 3.3 Gyr which, under the age-dependence hypothesis, would imply a 0.10 mag luminosity offset, inconsistent with observed standardized magnitudes. We infer a modest 1.5 Gyr evolution in mean progenitor age over cosmic time which, combined with observed age-Hubble-residual (HR) relations, yields a maximum redshift-dependent bias of $Δ$HR = $-0.007^{+0.012}_{-0.014}$ mag, consistent with zero. We find no evidence for a large, unmodeled progenitor-age systematic beyond what is already captured, to good approximation, by standard host-mass corrections.

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TITAN DR1: An Improved, Validated, and Systematically-Controlled Recalibration of ATLAS Photometry toward Type Ia Supernova Cosmology

ATLAS (Asteroid Terrestrial Last Alert System) is a time-domain survey using four telescopes, covering the entire sky. It has observed over 10,000 spectroscopically confirmed Type Ia supernovae (SNe~Ia), with thousands of cosmology-grade light curves (to be released as TITAN DR1). To prepare this massive, low-redshift dataset for cosmology, we evaluate and cross-calibrate ATLAS forced photometry using tertiary stars from the DES (Dark Energy Survey) Y6 release. The 5000 deg$^2$ DES footprint overlaps regions both in and out of the PS1 (Pan-STARRS DR1) footprint, allowing tests of the primary calibrator for the ATLAS Refcat2 catalog. Initial offsets are at the $\sim$40 mmag scale. To improve this we determine $Δ$ zeropoint offsets for two cases: (1) pixel-to-pixel offsets within individual CCDs (reduced from $\sim$8 to $\sim$4 mmag RMS) and (2) chip-to-chip offsets across the 9 CCDs and filters (reduced from $\sim$17 to $\sim$3 mmag RMS). We also identify the largest systematic uncertainty as a transmission-function color dependence, requiring shifts in the assumed ATLAS filters at the $\sim$30 mmag level if uncorrected. We validate our calibration using (a) CALSPEC standards, (b) an independent tertiary catalog, and (c) distance moduli of cross-matched SNe~Ia, all showing improved consistency. Overall, we estimate combined calibration-related systematics at the $\sim$5--10 mmag level, supporting competitive cosmological constraints with the TITAN SN~Ia dataset.

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The Dark Energy Bedrock All-Sky Supernova Program: Cross Calibration, Simulations, and Cosmology Forecasts

Type Ia supernovae (SNe Ia) have been essential for probing the nature of dark energy; however, most SN analyses rely on the same low-redshift sample, which may lead to shared systematics. In a companion paper (arXiv:2508.10878), we introduce the Dark Energy Bedrock All-Sky Supernova (DEBASS) program, which has already collected more than 500 low-redshift SNe Ia on the Dark Energy Camera (DECam), and present an initial release of 77 SNe Ia within the Dark Energy Survey (DES) footprint observed between 2021 and 2024. Here, we examine the systematics, including photometric calibration and selection effects. We find agreement at the 10 millimagnitude level among the tertiary standard stars of DEBASS, DES, and Pan-STARRS1. Our simulations reproduce the observed distributions of DEBASS SN light-curve properties, and we measure a bias-corrected Hubble residual scatter of $0.08$ mag, which, while small, is found in 10% of our simulations. We compare the DEBASS SN distances to the Foundation sample and find consistency with a median residual offset of $0.016 \pm 0.019$ mag. Selection effects have negligible impacts on distances, but a different photometric calibration solution shifts the median residual $-0.015 \pm 0.019$ mag, highlighting calibration sensitivity. Using conservative simulations, we forecast that replacing historical low-redshift samples with the full DEBASS sample (>400 SNe Ia) will improve the statistical uncertainties on dark energy parameters $w_0$ and $w_a$ by 30% and 24% respectively, enhance the dark energy Figure of Merit by up to 60%, and enable a measurement of $fσ_8$ at the 25% level.

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BayeSN and SALT: A Comparison of Dust Inference Across SN Ia Light-curve Models with DES5YR

In recent years there has been significant debate around the impact of dust on SNe Ia, a major source of uncertainty in cosmological analyses. We perform the first validation of the probabilistic hierarchical SN Ia SED model BayeSN on the conventional SALT model, an important test given the history of conflicting conclusions regarding the distributions of host galaxy dust properties between the two. Applying BayeSN to SALT-based simulations, we find that BayeSN is able to accurately recover our simulated inputs and successfully disentangle differences in dust extinction from an intrinsic mass step. This validates BayeSN as a method to identify the relative contributions of dust and intrinsic differences in explaining the mass step. When inferring dust parameters with simulated samples including non-Ia contamination, we find that our choice of photometric classifier causes a bias in the inferred dust distribution; this arises because SNe Ia heavily impacted by dust are misclassified as contaminants and excluded. We then apply BayeSN to the sample of SNe from DES5YR to jointly infer host galaxy dust distributions and intrinsic differences on either side of the `mass step' at $10^{10}$ M$\odot$. We find evidence in favour of an intrinsic contribution to the mass step and differing $R_V$ distributions. We also build on recent results supporting an environmental-dependence on the secondary maximum of SNe Ia in $i$-band. Twenty days post-peak, we find an offset in intrinsic $i$-band light curve between each mass bin at a significance in excess of $3σ$.

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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.

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The axis of systematic bias in SN~Ia cosmology and implications for DESI 2024 results

Relative distances between a high-redshift sample of Type Ia supernovae (SNe~Ia), anchored to a low-redshift sample, have been instrumental in drawing insights on the nature of the dark energy driving the accelerated expansion of the universe. A combination (hereafter called SBC) of the SNe~Ia with baryon acoustic oscillations (BAO) from the Dark Energy Spectroscopic Instrument (DESI) and the cosmic microwave background (CMB) recently indicated deviations from the standard interpretation of dark energy as a cosmological constant. In this paper, we analyse various systematic uncertainties in the distance measurement of SNe~Ia and their impact on the inferred dark energy properties in the canonical Chevallier-Polarski-Linder (CPL) model. We model systematic effects like photometric calibration, progenitor and dust evolution, and uncertainty in the galactic extinction law. We find that all the dominant systematic errors shift the dark energy inference towards the DESI 2024 results from an underlying $Λ$CDM cosmology. A small change in the calibration, and change in the Milky Way dust, can give rise to systematic-driven shifts on $w_0$-$w_a$ constraints, comparable to the deviation reported from the DESI 2024 results. We forecast that the systematic uncertainties can shift the inference of $w_0-w_a$ by a few times the error ellipse for future low- and high-$z$ SN~Ia compilations and hence, it is critical to circumvent them to robustly test for deviations from $Λ$. A slider and visualisation tool for quantifying the impact of systematic effects on the fitted cosmological parameters is publicly available at: https://github.com/sdhawan21/DEslider.git

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The DEHVILS in the Details: Type Ia Supernova Hubble Residual Comparisons and Mass Step Analysis in the Near-Infrared

Measurements of Type Ia Supernovae (SNe Ia) in the near-infrared (NIR) have been used both as an alternate path to cosmology compared to optical measurements and as a method of constraining key systematics for the larger optical studies. With the DEHVILS sample, the largest published NIR sample with consistent NIR coverage of maximum light across three NIR bands ($Y$, $J$, and $H$), we check three key systematics: (i) the reduction in Hubble residual scatter as compared to the optical, (ii) the measurement of a "mass step" or lack thereof and its implications, and (iii) the ability to distinguish between various dust models by analyzing slopes and correlations between Hubble residuals in the NIR and optical. We produce SN Ia simulations of the DEHVILS sample and find that it is $\textit{harder}$ to differentiate between various dust models than previously understood. Additionally, we find that fitting with the current SALT3-NIR model does not yield accurate wavelength-dependent stretch-luminosity correlations, and we propose a limited solution for this problem. From the data, we see that (i) the standard deviation of Hubble residual values from NIR bands treated as standard candles are 0.007-0.042 mag smaller than those in the optical, (ii) the NIR mass step is not constrainable with the current sample size of 47 SNe Ia from DEHVILS, and (iii) Hubble residuals in the NIR and optical are correlated in the data. We test a few variations on the number and combinations of filters and data samples, and we observe that none of our findings or conclusions are significantly impacted by these modifications.

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Amalgame: Cosmological Constraints from the First Combined Photometric Supernova Sample

Future constraints of cosmological parameters from Type Ia supernovae (SNe Ia) will depend on the use of photometric samples, those samples without spectroscopic measurements of the SNe Ia. There is a growing number of analyses that show that photometric samples can be utilised for precision cosmological studies with minimal systematic uncertainties. To investigate this claim, we perform the first analysis that combines two separate photometric samples, SDSS and Pan-STARRS, without including a low-redshift anchor. We evaluate the consistency of the cosmological parameters from these two samples and find they are consistent with each other to under $1σ$. From the combined sample, named Amalgame, we measure $Ω_M = 0.328 \pm 0.024$ with SN alone in a flat $Λ$CDM model, and $Ω_M = 0.330 \pm 0.018$ and $w = -1.016^{+0.055}_{-0.058}$ when combining with a Planck data prior and a flat $w$CDM model. These results are consistent with constraints from the Pantheon+ analysis of only spectroscopically confirmed SNe Ia, and show that there are no significant impediments to analyses of purely photometric samples of SNe Ia.

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A Synthetic Roman Space Telescope High-Latitude Time-Domain Survey: Supernovae in the Deep Field

NASA will launch the Nancy Grace Roman Space Telescope (Roman) in the second half of this decade, which will allow for a generation-defining measurement of dark energy through multiple probes, including Type Ia supernovae (SNe Ia). To improve decisions on survey strategy, we have created the first simulations of realistic Roman images that include artificial SNe Ia injected as point sources in the images. Our analysis combines work done on Roman simulations for weak gravitational lensing studies as well as catalog-level simulations of SN samples. We have created a time series of images over two years containing $\sim$ 1,050 SNe Ia, covering a 1 square degree subarea of a planned 5 square degree deep survey. We have released these images publicly for community use along with input catalogs of all injected sources. We create secondary products from these images by generating coadded images and demonstrating recovery of transient sources using image subtraction. We perform first-use analyses on these images in order to measure galaxy-detection efficiency, point source-detection efficiency, and host-galaxy association biases. The simulated images can be found here: https://roman.ipac.caltech.edu/sims/SN_Survey_Image_sim.html.

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The DEHVILS Survey Overview and Initial Data Release: High-Quality Near-Infrared Type Ia Supernova Light Curves at Low Redshift

While the sample of optical Type Ia Supernova (SN Ia) light curves (LCs) usable for cosmological parameter measurements surpasses 2000, the sample of published, cosmologically viable near-infrared (NIR) SN Ia LCs, which have been shown to be good "standard candles," is still $\lesssim$ 200. Here, we present high-quality NIR LCs for 83 SNe Ia ranging from $0.002 < z < 0.09$ as a part of the Dark Energy, H$_0$, and peculiar Velocities using Infrared Light from Supernovae (DEHVILS) survey. Observations are taken using UKIRT's WFCAM, where the median depth of the images is 20.7, 20.1, and 19.3 mag (Vega) for $Y$, $J$, and $H$-bands, respectively. The median number of epochs per SN Ia is 18 for all three bands ($YJH$) combined and 6 for each band individually. We fit 47 SN Ia LCs that pass strict quality cuts using three LC models, SALT3, SNooPy, and BayeSN and find scatter on the Hubble diagram to be comparable to or better than scatter from optical-only fits in the literature. Fitting NIR-only LCs, we obtain standard deviations ranging from 0.128-0.135 mag. Additionally, we present a refined calibration method for transforming 2MASS magnitudes to WFCAM magnitudes using HST CALSPEC stars that results in a 0.03 mag shift in the WFCAM $Y$-band magnitudes.

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The Pantheon+ Analysis: Forward-Modeling the Dust and Intrinsic Colour Distributions of Type Ia Supernovae, and Quantifying their Impact on Cosmological Inferences

Recent studies have shown that the observed colour distributions of Type Ia SNe (SNIa) are well-described by a combination of distributions from dust and intrinsic colour. Here we present a new forward-modeling fitting method (Dust2Dust) to measure the parent dust and colour distributions, including their dependence on host-galaxy mass. At each fit step, the SNIa selection efficiency is determined from a large simulated sample that is re-weighted to reflect the proposed distributions. We use five separate metrics to constrain the Dust2Dust parameters: distribution of fitted light-curve colour $c$, cosmological residual trends with $c$, cosmological residual scatter with $c$, fitted colour-luminosity relationship $β_{\rm SALT2}$, and intrinsic scatter $σ_{\rm int}$. Using the Pantheon+ data sample, we present results for a Dust2Dust fit that includes 4 parameters describing intrinsic colour variations and 8 parameters describing dust. Furthermore, we propagate the Dust2Dust parameter uncertainties and covariance to the dark energy equation-of-state $w$ and Hubble constant H$_0$: we find $σ_w = 0.005$ and $σ_{\textrm{H}_0} = 0.145~$km/s/Mpc. The Dust2Dust code is publically available.

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The Pantheon+ Analysis: Cosmological Constraints

We present constraints on cosmological parameters from the Pantheon+ analysis of 1701 light curves of 1550 distinct Type Ia supernovae (SNe Ia) ranging in redshift from $z=0.001$ to 2.26. This work features an increased sample size, increased redshift span, and improved treatment of systematic uncertainties in comparison to the original Pantheon analysis and results in a factor of two improvement in cosmological constraining power. For a Flat$Λ$CDM model, we find $Ω_M=0.334\pm0.018$ from SNe Ia alone. For a Flat$w_0$CDM model, we measure $w_0=-0.90\pm0.14$ from SNe Ia alone, H$_0=73.5\pm1.1$ km s$^{-1}$ Mpc$^{-1}$ when including the Cepheid host distances and covariance (SH0ES), and $w_0=-0.978^{+0.024}_{-0.031}$ when combining the SN likelihood with constraints from the cosmic microwave background (CMB) and baryon acoustic oscillations (BAO); both $w_0$ values are consistent with a cosmological constant. We also present the most precise measurements to date on the evolution of dark energy in a Flat$w_0w_a$CDM universe, and measure $w_a=-0.1^{+0.9}_{-2.0}$ from Pantheon+ alone, H$_0=73.3\pm1.1$ km s$^{-1}$ Mpc$^{-1}$ when including SH0ES, and $w_a=-0.65^{+0.28}_{-0.32}$ when combining Pantheon+ with CMB and BAO data. Finally, we find that systematic uncertainties in the use of SNe Ia along the distance ladder comprise less than one third of the total uncertainty in the measurement of H$_0$ and cannot explain the present "Hubble tension" between local measurements and early-Universe predictions from the cosmological model.

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Constraining R$_V$ Variation Using Highly Reddened Type Ia Supernovae from the Pantheon+ Sample

Type Ia supernovae (SNe Ia) are powerful tools for measuring the expansion history of the universe, but the impact of dust around SNe Ia remains unknown and is a critical systematic uncertainty. One way to improve our empirical description of dust is to analyse highly reddened SNe Ia ($E(B-V)>0.4$, roughly equivalent to the fitted SALT2 light-curve parameter $c>0.3$). With the recently released Pantheon+ sample, there are 57 SNe Ia that were removed because of their high colour alone (with colours up to $c=1.61$), which can provide enormous leverage on understanding line-of-sight $R_V$. Previous studies have claimed that $R_V$ decreases with redder colour, though it is unclear if this is due to limited statistics, selection effects, or an alternative explanation. To test this claim, we fit two separate colour-luminosity relationships, one for the main cosmological sample ($c<0.3$) and one for highly reddened ($c>0.3$) SNe Ia. We find the change in the colour-luminosity coefficient to be consistent with zero. Additionally, we compare the data to simulations with different colour models, and find that the data prefers a model with a flat dependence of $R_V$ on colour over a declining dependence. Finally, our results strongly support that line-of-sight $R_V$ to SNe Ia is not a single value, but forms a distribution.

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The Pantheon+ Analysis: The Full Dataset and Light-Curve Release

Here we present 1701 light curves of 1550 spectroscopically confirmed Type Ia supernovae (SNe Ia) that will be used to infer cosmological parameters as part of the Pantheon+ SN analysis and the SH0ES (Supernovae and H0 for the Equation of State of dark energy) distance-ladder analysis. This effort is one part of a series of works that perform an extensive review of redshifts, peculiar velocities, photometric calibration, and intrinsic-scatter models of SNe Ia. The total number of light curves, which are compiled across 18 different surveys, is a significant increase from the first Pantheon analysis (1048 SNe), particularly at low redshift ($z$). Furthermore, unlike in the Pantheon analysis, we include light curves for SNe with $z<0.01$ such that SN systematic covariance can be included in a joint measurement of the Hubble constant (H$_0$) and the dark energy equation-of-state parameter ($w$). We use the large sample to compare properties of 151 SNe Ia observed by multiple surveys and 12 pairs/triplets of "SN siblings" - SNe found in the same host galaxy. Distance measurements, application of bias corrections, and inference of cosmological parameters are discussed in the companion paper by Brout et al. (2022b), and the determination of H$_0$ is discussed by Riess et al. (2022). These analyses will measure w with $\sim3\%$ precision and H$_0$ with 1 km/s/Mpc precision.

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The Pantheon+ Analysis: Evaluating Peculiar Velocity Corrections in Cosmological Analyses with Nearby Type Ia Supernovae

Separating the components of redshift due to expansion and peculiar motion in the nearby universe ($z<0.1$) is critical for using Type Ia Supernovae (SNe Ia) to measure the Hubble constant ($H_0$) and the equation-of-state parameter of dark energy ($w$). Here, we study the two dominant 'motions' contributing to nearby peculiar velocities: large-scale, coherent-flow (CF) motions and small-scale motions due to gravitationally associated galaxies deemed to be in a galaxy group. We use a set of 584 low-$z$ SNe from the Pantheon+ sample, and evaluate the efficacy of corrections to these motions by measuring the improvement of SN distance residuals. We study multiple methods for modeling the large and small-scale motions and show that, while group assignments and CF corrections individually contribute to small improvements in Hubble residual scatter, the greatest improvement comes from the combination of the two (relative standard deviation of the Hubble residuals, Rel. SD, improves from 0.167 to 0.157 mag). We find the optimal flow corrections derived from various local density maps significantly reduce Hubble residuals while raising $H_0$ by $\sim0.4$ km s$^{-1}$ Mpc$^{-1}$ as compared to using CMB redshifts, disfavoring the hypothesis that unrecognized local structure could resolve the Hubble tension. We estimate that the systematic uncertainties in cosmological parameters after optimally correcting redshifts are 0.06-0.11 km s$^{-1}$ Mpc$^{-1}$ in $H_0$ and 0.02-0.03 in $w$ which are smaller than the statistical uncertainties for these measurements: 1.5 km s$^{-1}$ Mpc$^{-1}$ for $H_0$ and 0.04 for $w$.

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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.

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