arXiv subjects

D. Scolnic

Publications and source records attributed to D. Scolnic.

At least 37 records · Page 2Linked to original sources

arXiv2024

The Dark Energy Survey Supernova Program: Cosmological Biases from Host Galaxy Mismatch of Type Ia Supernovae

Redshift measurements, primarily obtained from host galaxies, are essential for inferring cosmological parameters from type Ia supernovae (SNe Ia). Matching SNe to host galaxies using images is non-trivial, resulting in a subset of SNe with mismatched hosts and thus incorrect redshifts. We evaluate the host galaxy mismatch rate and resulting biases on cosmological parameters from simulations modeled after the Dark Energy Survey 5-Year (DES-SN5YR) photometric sample. For both DES-SN5YR data and simulations, we employ the directional light radius method for host galaxy matching. In our SN Ia simulations, we find that 1.7% of SNe are matched to the wrong host galaxy, with redshift difference between the true and matched host of up to 0.6. Using our analysis pipeline, we determine the shift in the dark energy equation of state parameter (Dw) due to including SNe with incorrect host galaxy matches. For SN Ia-only simulations, we find Dw = 0.0013 +/- 0.0026 with constraints from the cosmic microwave background (CMB). Including core-collapse SNe and peculiar SNe Ia in the simulation, we find that Dw ranges from 0.0009 to 0.0032 depending on the photometric classifier used. This bias is an order of magnitude smaller than the expected total uncertainty on w from the DES-SN5YR sample of around 0.03. We conclude that the bias on w from host galaxy mismatch is much smaller than the uncertainties expected from the DES-SN5YR sample, but we encourage further studies to reduce this bias through better host-matching algorithms or selection cuts.

astro-ph.CO↗

arXiv2024

The Dark Energy Survey Supernova Program: Cosmological Analysis and Systematic Uncertainties

We present the full Hubble diagram of photometrically-classified Type Ia supernovae (SNe Ia) from the Dark Energy Survey supernova program (DES-SN). DES-SN discovered more than 20,000 SN candidates and obtained spectroscopic redshifts of 7,000 host galaxies. Based on the light-curve quality, we select 1635 photometrically-identified SNe Ia with spectroscopic redshift 0.10$< z <$1.13, which is the largest sample of supernovae from any single survey and increases the number of known $z>0.5$ supernovae by a factor of five. In a companion paper, we present cosmological results of the DES-SN sample combined with 194 spectroscopically-classified SNe Ia at low redshift as an anchor for cosmological fits. Here we present extensive modeling of this combined sample and validate the entire analysis pipeline used to derive distances. We show that the statistical and systematic uncertainties on cosmological parameters are $σ_{Ω_M,{\rm stat+sys}}^{Λ{\rm CDM}}=$0.017 in a flat $Λ$CDM model, and $(σ_{Ω_M},σ_w)_{\rm stat+sys}^{w{\rm CDM}}=$(0.082, 0.152) in a flat $w$CDM model. Combining the DES SN data with the highly complementary CMB measurements by Planck Collaboration (2020) reduces uncertainties on cosmological parameters by a factor of 4. In all cases, statistical uncertainties dominate over systematics. We show that uncertainties due to photometric classification make up less than 10% of the total systematic uncertainty budget. This result sets the stage for the next generation of SN cosmology surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time.

astro-ph.CO↗

arXiv2023

A Sample of Dust Attenuation Laws for DES Supernova Host Galaxies

Type Ia supernovae (SNe Ia) are useful distance indicators in cosmology, provided their luminosity is standardized by applying empirical corrections based on light-curve properties. One factor behind these corrections is dust extinction, accounted for in the color-luminosity relation of the standardization. This relation is usually assumed to be universal, which could potentially introduce systematics into the standardization. The ``mass-step'' observed for SNe Ia Hubble residuals has been suggested as one such systematic. We seek to obtain a completer view of dust attenuation properties for a sample of 162 SN Ia host galaxies and to probe their link to the ``mass-step''. We infer attenuation laws towards hosts from both global and local (4 kpc) Dark Energy Survey photometry and Composite Stellar Population model fits. We recover a optical depth/attenuation slope relation, best explained by differing star/dust geometry for different galaxy orientations, which is significantly different from the optical depth/extinction slope relation observed directly for SNe. We obtain a large variation of attenuation slopes and confirm these change with host properties, like stellar mass and age, meaning a universal SN Ia correction should ideally not be assumed. Analyzing the cosmological standardization, we find evidence for a ``mass-step'' and a two dimensional ``dust-step'', both more pronounced for red SNe. Although comparable, the two steps are found no to be completely analogous. We conclude that host galaxy dust data cannot fully account for the ``mass-step'', using either an alternative SN standardization with extinction proxied by host attenuation or a ``dust-step'' approach.

astro-ph.GA↗

arXiv2023

Rates and properties of type Ia supernovae in galaxy clusters within the Dark Energy Survey

We identify 66 photometrically classified type Ia supernovae (SNe Ia) from the Dark Energy Survey (DES) that have occurred within red-sequence selected galaxy clusters. We compare light-curve and host galaxy properties of the cluster SNe to 1024 DES SNe Ia located in field galaxies, the largest comparison of two such samples at high redshift (z > 0.1). We find that cluster SN light curves decline faster than those in the field (97.7 per cent confidence). However, when limiting these samples to host galaxies of similar colour and mass, there is no significant difference in the SN light curve properties. Motivated by previous detections of a higher-normalised SN Ia delay time distribution in galaxy clusters, we measure the intrinsic rate of SNe Ia in cluster and field environments. We find the average ratio of the SN Ia rate per galaxy between high mass ($10\leq\log\mathrm{(M_{*}/M_{\odot})} \leq 11.25$) cluster and field galaxies to be $0.594 \pm0.068$. This difference is mass-dependent, with the ratio declining with increasing mass, which suggests that the stellar populations in cluster hosts are older than those in field hosts. We show that the mass-normalised rate (or SNe per unit mass) in massive-passive galaxies is consistent between cluster and field environments. Additionally, both of these rates are consistent with rates previously measured in clusters at similar redshifts. We conclude that in massive-passive galaxies, which are the dominant hosts of cluster SNe, the cluster DTD is comparable to the field.

astro-ph.HE↗

arXiv2023

CATS: The Hubble Constant from Standardized TRGB and Type Ia Supernova Measurements

The Tip of the Red Giant Branch (TRGB) provides a luminous standard candle for constructing distance ladders to measure the Hubble constant. In practice its measurements via edge-detection response (EDR) are complicated by the apparent fuzziness of the tip and the multi-peak landscape of the EDR. As a result, it can be difficult to replicate due to a case-by-case measurement process. Previously we optimized an unsupervised algorithm, Comparative Analysis of TRGBs (CATs), to minimize the variance among multiple halo fields per host without reliance on individualized choices, achieving state-of-the-art $\sim$ $<$ 0.05 mag distance measures for optimal data. Further, we found an empirical correlation at 5$σ$ confidence in the GHOSTS halo survey between our measurements of the tip and their contrast ratios (ratio of stars 0.5 mag just below and above the tip), useful for standardizing the apparent tips at different host locations. Here, we apply this algorithm to an expanded sample of SN Ia hosts to standardize these to multiple fields in the geometric anchor, NGC 4258. In concert with the Pantheon$+$ SN Ia sample, this analysis produces a (baseline) result of $H_0= 73.22 \pm 2.06$ km/s/Mpc. The largest difference in $H_0$ between this and similar studies employing the TRGB derives from corrections for SN survey differences and local flows used in most recent SN Ia compilations but which were absent in earlier studies. SN-related differences total $\sim$ 2.0 km/s/Mpc. A smaller share, $\sim$ 1.4 km/s/Mpc, results from the inhomogeneity of the TRGB calibration across the distance ladder. We employ a grid of 108 variants around the optimal TRGB algorithm and find the median of variants is $72.94\pm1.98$ km/s/Mpc with an additional uncertainty due to algorithm choices of 0.83 km/s/Mpc. None of these TRGB variants result in $H_0$ less than 71.6 km/s/Mpc.

astro-ph.CO↗

arXiv2023

The Dark Energy Survey Supernova Program: Corrections on photometry due to wavelength-dependent atmospheric effects

Wavelength-dependent atmospheric effects impact photometric supernova flux measurements for ground-based observations. We present corrections on supernova flux measurements from the Dark Energy Survey Supernova Program's 5YR sample (DES-SN5YR) for differential chromatic refraction (DCR) and wavelength-dependent seeing, and we show their impact on the cosmological parameters $w$ and $Ω_m$. We use $g-i$ colors of Type Ia supernovae (SNe Ia) to quantify astrometric offsets caused by DCR and simulate point spread functions (PSFs) using the GalSIM package to predict the shapes of the PSFs with DCR and wavelength-dependent seeing. We calculate the magnitude corrections and apply them to the magnitudes computed by the DES-SN5YR photometric pipeline. We find that for the DES-SN5YR analysis, not accounting for the astrometric offsets and changes in the PSF shape cause an average bias of $+0.2$ mmag and $-0.3$ mmag respectively, with standard deviations of $0.7$ mmag and $2.7$ mmag across all DES observing bands (\textit{griz}) throughout all redshifts. When the DCR and seeing effects are not accounted for, we find that $w$ and $Ω_m$ are lower by less than $0.004\pm0.02$ and $0.001\pm0.01$ respectively, with $0.02$ and $0.01$ being the $1σ$ statistical uncertainties. Although we find that these biases do not limit the constraints of the DES-SN5YR sample, future surveys with much higher statistics, lower systematics, and especially those that observe in the $u$ band will require these corrections as wavelength-dependent atmospheric effects are larger at shorter wavelengths. We also discuss limitations of our method and how they can be better accounted for in future surveys.

astro-ph.CO↗

arXiv2023

Concerning Colour: The Effect of Environment on Type Ia Supernova Colour in the Dark Energy Survey

Recent analyses have found intriguing correlations between the colour ($c$) of type Ia supernovae (SNe Ia) and the size of their 'mass-step', the relationship between SN Ia host galaxy stellar mass ($M_\mathrm{stellar}$) and SN Ia Hubble residual, and suggest that the cause of this relationship is dust. Using 675 photometrically-classified SNe Ia from the Dark Energy Survey 5-year sample, we study the differences in Hubble residual for a variety of global host galaxy and local environmental properties for SN Ia subsamples split by their colour. We find a $3σ$ difference in the mass-step when comparing blue ($c<0$) and red ($c>0$) SNe. We observe the lowest r.m.s. scatter ($\sim0.14$ mag) in the Hubble residual for blue SNe in low mass/blue environments, suggesting that this is the most homogeneous sample for cosmological analyses. By fitting for $c$-dependent relationships between Hubble residuals and $M_\mathrm{stellar}$, approximating existing dust models, we remove the mass-step from the data and find tentative $\sim 2σ$ residual steps in rest-frame galaxy $U-R$ colour. This indicates that dust modelling based on $M_\mathrm{stellar}$ may not fully explain the remaining dispersion in SN Ia luminosity. Instead, accounting for a $c$-dependent relationship between Hubble residuals and global $U-R$, results in $\leq1σ$ residual steps in $M_\mathrm{stellar}$ and local $U-R$, suggesting that $U-R$ provides different information about the environment of SNe Ia compared to $M_\mathrm{stellar}$, and motivating the inclusion of galaxy $U-R$ colour in SN Ia distance bias correction.

astro-ph.CO↗

arXiv2023

SALT2 Versus SALT3: Updated Model Surfaces and Their Impacts on Type Ia Supernova Cosmology

For the past decade, SALT2 has been the most common model used to fit Type Ia supernova (SN Ia) light curves for dark energy analyses. Recently, the SALT3 model was released, which upgraded a number of model features but has not yet been used for measurements of dark energy. Here, we evaluate the impact of switching from SALT2 to SALT3 for a SN cosmology analysis. We train SALT2 and SALT3 on an identical training sample of 1083 well-calibrated Type Ia supernovae, ensuring that any differences found come from the underlying model framework. We publicly release the results of this training (the SALT "surfaces"). We then run a cosmology analysis on the public Dark Energy Survey 3-Year Supernova data sample (DES-SN3YR), and on realistic simulations of those data. We provide the first estimate of the SN+CMB systematic uncertainty arising from the choice of SALT model framework (i.e. SALT2 versus SALT3), $Δw = +0.001 \pm 0.005$ -- a negligible effect at the current level of dark energy analyses. We also find that the updated surfaces are less sensitive to photometric calibration uncertainties than previous SALT2 surfaces, with the average spectral energy density dispersion reduced by a factor of two over optical wavelengths. This offers an opportunity to reduce the contribution of calibration errors to SN cosmology uncertainty budgets.

astro-ph.CO↗

arXiv2022

Dark Energy Survey Year 3 results: Cosmological constraints from galaxy clustering and galaxy-galaxy lensing using the MagLim lens sample

Two of the most sensitive probes of the large scale structure of the universe are the clustering of galaxies and the tangential shear of background galaxy shapes produced by those foreground galaxies, so-called galaxy-galaxy lensing. Combining the measurements of these two two-point functions leads to cosmological constraints that are independent of the galaxy bias factor. The optimal choice of foreground, or lens, galaxies is governed by the joint, but conflicting requirements to obtain accurate redshift information and large statistics. We present cosmological results from the full 5000 sq. deg. of the Dark Energy Survey first three years of observations (Y3) combining those two-point functions, using for the first time a magnitude-limited lens sample (MagLim) of 11 million galaxies especially selected to optimize such combination, and 100 million background shapes. We consider two cosmological models, flat $Λ$CDM and $w$CDM. In $Λ$CDM we obtain for the matter density $Ω_m = 0.320^{+0.041}_{-0.034}$ and for the clustering amplitude $S_8 = 0.778^{+0.037}_{-0.031}$, at 68% C.L. The latter is only 1$σ$ smaller than the prediction in this model informed by measurements of the cosmic microwave background by the Planck satellite. In $w$CDM we find $Ω_m = 0.32^{+0.044}_{-0.046}$, $S_8=0.777^{+0.049}_{-0.051}$, and dark energy equation of state $w=-1.031^{+0.218}_{-0.379}$. We find that including smaller scales while marginalizing over non-linear galaxy bias improves the constraining power in the $Ω_m-S_8$ plane by $31$% and in the $Ω_m-w$ plane by $41$% while yielding consistent cosmological parameters from those in the linear bias case. These results are combined with those from cosmic shear in a companion paper to present full DES-Y3 constraints from the three two-point functions (3x2pt).

astro-ph.CO↗

arXiv2022

Comparative Analysis of TRGBs (CATs) from Unsupervised, Multi-Halo-Field Measurements: Contrast is Key

The Tip of the Red Giant Branch (TRGB) is an apparent discontinuity in the color-magnitude diagram (CMD) along the giant branch due to the end of the red giant evolutionary phase and is used to measure distances in the local universe. In practice, the tip is often fuzzy and its localization via edge detection response (EDR) relies on several methods applied on a case-by-case basis. It is hard to evaluate how individual choices affect a distance estimation using only a single host field while also avoiding confirmation bias. To devise a standardized approach, we compare unsupervised, algorithmic analyses of the TRGB in multiple halo fields per galaxy, up to 11 fields for a single host and 50 fields across 10 galaxies, using high signal-to-noise stellar photometry obtained by the GHOSTS survey with the Hubble Space Telescope. We first optimize methods for the lowest field-to-field dispersion including spatial filtering to remove star forming regions, smoothing and weighting of the luminosity function, selection of the RGB by color, and tip selection based on the number of likely RGB stars and the ratio of stars above versus below the tip ($R$). We find $R$, which we call the tip `contrast', to be the most important indicator of the quality of EDR measurements; we find that field-to-field EDR repeatability varies from 0.3 mag to $\leq$ 0.05 mag for $R=4$ to 7, respectively, though less than half the fields reach the higher quality. Further, we find that $R$, which varies with the age/metallicity of the stellar population based on models, correlates with the magnitude of the tip (and after accounting for low internal extinction), i.e., a tip-contrast relation with slope of $-0.023\pm0.0046$ mag/ratio, a $\sim 5σ$ result that improves standardization of the TRGB. We discuss the value of consistent TRGB standardization across rungs for robust distance ladder measurements.

astro-ph.CO↗

arXiv2022

Type Ia Supernova cosmology combining data from the $Euclid$ mission and the Vera C. Rubin Observatory

The $Euclid$ mission will provide first-of-its-kind coverage in the near-infrared over deep (three fields, $\sim$10-20 square degrees each) and wide ($\sim$10000 square degrees) fields. While the survey is not designed to discover transients, the deep fields will have repeated observations over a two-week span, followed by a gap of roughly six months. In this analysis, we explore how useful the deep field observations will be for measuring properties of Type Ia supernovae (SNe Ia). Using simulations that include $Euclid$'s planned depth, area and cadence in the deep fields, we calculate that more than 3700 SNe between $0.0 0.8$. Furthermore, we predict how well additional $Euclid$ mock data can be used to constrain a key systematic in SN Ia studies - the size of the luminosity 'step' found between SNe hosted in high mass ($>10^{10} M_{\odot}$) and low mass ($>10^{10} M_{\odot}$) galaxies. This measurement has unique information in the rest-frame NIR. We predict that if the step is caused by dust, we will be able to measure its reduction in the NIR compared to optical at the 4$σ$ level. We highlight that the LSST and $Euclid$ observing strategies used in this work are still provisional and some level of joint processing is required. Still, these first results are promising, and assuming $Euclid$ begins observations well before the Nancy Roman Space Telescope (Roman), we expect this dataset to be extremely helpful for preparation for Roman itself.

astro-ph.CO↗

arXiv2022

Using Host Galaxy Spectroscopy to Explore Systematics in the Standardisation of Type Ia Supernovae

We use stacked spectra of the host galaxies of photometrically identified type Ia supernovae (SNe Ia) from the Dark Energy Survey (DES) to search for correlations between Hubble diagram residuals and the spectral properties of the host galaxies. Utilising full spectrum fitting techniques on stacked spectra binned by Hubble residual, we find no evidence for trends between Hubble residuals and properties of the host galaxies that rely on spectral absorption features ($< 1.3σ$), such as stellar population age, metallicity, and mass-to-light ratio. However, we find significant trends between the Hubble residuals and the strengths of [OII] ($4.4σ$) and the Balmer emission lines ($3σ$). These trends are weaker than the well known trend between Hubble residuals and host galaxy stellar mass ($7.2σ$) that is derived from broad band photometry. After light curve corrections, we see fainter SNe Ia residing in galaxies with larger line strengths. We also find a trend (3$σ$) between Hubble residual and the Balmer decrement (a measure of reddening by dust) using H$β$ and H$γ$. The trend, quantified by correlation coefficients, is slightly more significant in the redder SNe Ia, suggesting that bluer SNe Ia are relatively unaffected by dust in the interstellar medium of the host and that dust contributes to current Hubble diagram scatter impacting the measurement of cosmological parameters.

astro-ph.CO↗

arXiv2022

The Dark Energy Survey 5-year photometrically identified Type Ia Supernovae

As part of the cosmology analysis using Type Ia Supernovae (SN Ia) in the Dark Energy Survey (DES), we present photometrically identified SN Ia samples using multi-band light-curves and host galaxy redshifts. For this analysis, we use the photometric classification framework SuperNNova (SNN; Möller et al. 2019) trained on realistic DES-like simulations. For reliable classification, we process the DES SN programme (DES-SN) data and introduce improvements to the classifier architecture, obtaining classification accuracies of more than 98 per cent on simulations. This is the first SN classification to make use of ensemble methods, resulting in more robust samples. Using photometry, host galaxy redshifts, and a classification probability requirement, we identify 1,863 SNe Ia from which we select 1,484 cosmology-grade SNe Ia spanning the redshift range of 0.07 < z < 1.14. We find good agreement between the light-curve properties of the photometrically-selected sample and simulations. Additionally, we create similar SN Ia samples using two types of Bayesian Neural Network classifiers that provide uncertainties on the classification probabilities. We test the feasibility of using these uncertainties as indicators for out-of-distribution candidates and model confidence. Finally, we discuss the implications of photometric samples and classification methods for future surveys such as Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST).

astro-ph.CO↗

arXiv2022

A galaxy-driven model of type Ia supernova luminosity variations

Type Ia supernovae (SNe Ia) are used as standardisable candles to measure cosmological distances, but differences remain in their corrected luminosities which display a magnitude step as a function of host galaxy properties such as stellar mass and rest-frame $U-R$ colour. Identifying the cause of these steps is key to cosmological analyses and provides insight into SN physics. Here we investigate the effects of SN progenitor ages on their light curve properties using a galaxy-based forward model that we compare to the Dark Energy Survey 5-year SN Ia sample. We trace SN Ia progenitors through time and draw their light-curve width parameters from a bimodal distribution according to their age. We find that an intrinsic luminosity difference between SNe of different ages cannot explain the observed trend between step size and SN colour. The data split by stellar mass are better reproduced by following recent work implementing a step in total-to-selective dust extinction ratio $(R_V)$ between low- and high-mass hosts, although an additional intrinsic luminosity step is still required to explain the data split by host galaxy $U-R$. Modelling the $R_V$ step as a function of galaxy age provides a better match overall. Additional age vs. luminosity steps marginally improve the match to the data, although most of the step is absorbed by the width vs. luminosity coefficient $α$. Furthermore, we find no evidence that $α$ varies with SN age.

astro-ph.GA↗

arXiv2022

A DECam Search for Explosive Optical Transients Associated with IceCube Neutrinos

In this work, we investigate the likelihood of association between realtime, TeV-PeV energy neutrino alerts from IceCube and optical counterparts in the form of core-collapse supernovae (CC SNe). The optical follow-up of IceCube alerts requires two main instrumental capabilities: (1) deep imaging, since 73\% of neutrinos would come from CC SNe at redshifts $z > 0.3$, and (2) a large field of view (FoV), since typical IceCube muon neutrino pointing accuracy is on the order of $\sim1$~deg. With Blanco/DECam ($gri$ to 24th magnitude and $2.2$~deg diameter FoV), we performed a triggered optical follow-up observation of two IceCube alerts, IC170922A and IC171106A on $\sim6$~nights during the $\sim3$~weeks following each alert. For the IC170922A (IC171106A) follow-up observations, we expect that 12.1\% (9.5\%) of coincident CC SNe at $z \lesssim 0.3$ are detectable, and that on average, 0.23 (0.07) unassociated SNe in the neutrino 90\% containment regions also pass our selection criteria. We find two candidate CC SNe that are temporally coincident with the neutrino alerts in the FoV, but none in the 90\% containment regions, which is statistically consistent with expected rates of background CC SNe for these observations. If CC SNe are the dominant source of TeV-PeV neutrinos, we would expect an excess of coincident CC SNe to be detectable at the $3σ$ confidence level using DECam observations similar to those of this work for $\sim60$ ($\sim200$) neutrino alerts with (without) redshift information for all candidates.

astro-ph.HE↗

arXiv2022

Constraints on the Physical Properties of GW190814 through Simulations based on DECam Follow-up Observations by the Dark Energy Survey

On 14 August 2019, the LIGO and Virgo Collaborations detected gravitational waves from a black hole and a 2.6 solar mass compact object, possibly the first neutron star -- black hole (NSBH) merger. In search of an optical counterpart, the Dark Energy Survey (DES) obtained deep imaging of the entire 90 percent confidence level localization area with Blanco/DECam 0, 1, 2, 3, 6, and 16 nights after the merger. Objects with varying brightness were detected by the DES Pipeline and we systematically reduced the candidate counterparts through catalog matching, light curve properties, host-galaxy photometric redshifts, SOAR spectroscopic follow-up observations, and machine-learning-based photometric classification. All candidates were rejected as counterparts to the merger. To quantify the sensitivity of our search, we applied our selection criteria to full light curve simulations of supernovae and kilonovae as they would appear in the DECam observations. Since the source class of the merger was uncertain, we utilized an agnostic, three-component kilonova model based on tidally-disrupted NS ejecta properties to quantify our detection efficiency of a counterpart if the merger included a NS. We find that if a kilonova occurred during this merger, configurations where the ejected matter is greater than 0.07 solar masses, has lanthanide abundance less than $10^{-8.56}$, and has a velocity between $0.18c$ and $0.21c$ are disfavored at the $2σ$ level. Furthermore, we estimate that our background reduction methods are capable of associating gravitational wave signals with a detected electromagnetic counterpart at the $4σ$ level in $95\%$ of future follow-up observations.

astro-ph.HE↗

arXiv2022

Measuring Cosmological Parameters with Type Ia Supernovae in redMaGiC galaxies

Current and future cosmological analyses with Type Ia Supernovae (SNe Ia) face three critical challenges: i) measuring redshifts from the supernova or its host galaxy; ii) classifying SNe without spectra; and iii) accounting for correlations between the properties of SNe Ia and their host galaxies. We present here a novel approach that addresses each challenge. In the context of the Dark Energy Survey (DES), we analyze a SNIa sample with host galaxies in the redMaGiC galaxy catalog, a selection of Luminous Red Galaxies. Photo-$z$ estimates for these galaxies are expected to be accurate to $σ_{Δz/(1+z)}\sim0.02$. The DES-5YR photometrically classified SNIa sample contains approximately 1600 SNe and 125 of these SNe are in redMaGiC galaxies. We demonstrate that redMaGiC galaxies almost exclusively host SNe Ia, reducing concerns with classification uncertainties. With this subsample, we find similar Hubble scatter (to within $\sim0.01$ mag) using photometric redshifts in place of spectroscopic redshifts. With detailed simulations, we show the bias due to using photo-$z$s from redMaGiC host galaxies on the measurement of the dark energy equation-of-state $w$ is up to $Δw \sim 0.01-0.02$. With real data, we measure a difference in $w$ when using redMaGiC photometric redshifts versus spectroscopic redshifts of $Δw = 0.005$. Finally, we discuss how SNe in redMaGiC galaxies appear to be a more standardizable population due to a weaker relation between color and luminosity ($β$) compared to the DES-3YR population by $\sim5σ$; this finding is consistent with predictions that redMaGiC galaxies exhibit lower reddening ratios ($\textrm{R}_\textrm{V}$) than the general population of SN host galaxies. These results establish the feasibility of performing redMaGiC SN cosmology with photometric survey data in the absence of spectroscopic data.

astro-ph.CO↗

arXiv2021

The Dark Energy Survey Supernova Program: Cosmological biases from supernova photometric classification

Cosmological analyses of samples of photometrically-identified Type Ia supernovae (SNe Ia) depend on understanding the effects of 'contamination' from core-collapse and peculiar SN Ia events. We employ a rigorous analysis on state-of-the-art simulations of photometrically identified SN Ia samples and determine cosmological biases due to such 'non-Ia' contamination in the Dark Energy Survey (DES) 5-year SN sample. As part of the analysis, we test on our DES simulations the performance of SuperNNova, a photometric SN classifier based on recurrent neural networks. Depending on the choice of non-Ia SN models in both the simulated data sample and training sample, contamination ranges from 0.8-3.5 %, with the efficiency of the classification from 97.7-99.5 %. Using the Bayesian Estimation Applied to Multiple Species (BEAMS) framework and its extension 'BEAMS with Bias Correction' (BBC), we produce a redshift-binned Hubble diagram marginalised over contamination and corrected for selection effects and we use it to constrain the dark energy equation-of-state, $w$. Assuming a flat universe with Gaussian $Ω_M$ prior of $0.311\pm0.010$, we show that biases on $w$ are $<0.008$ when using SuperNNova and accounting for a wide range of non-Ia SN models in the simulations. Systematic uncertainties associated with contamination are estimated to be at most $σ_{w, \mathrm{syst}}=0.004$. This compares to an expected statistical uncertainty of $σ_{w,\mathrm{stat}}=0.039$ for the DES-SN sample, thus showing that contamination is not a limiting uncertainty in our analysis. We also measure biases due to contamination on $w_0$ and $w_a$ (assuming a flat universe), and find these to be $<$0.009 in $w_0$ and $<$0.108 in $w_a$, hence 5 to 10 times smaller than the statistical uncertainties expected from the DES-SN sample.

astro-ph.CO↗