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

   Qu, H. ; Sako, M. ; Vincenzi, M. ; Sanchez, C. ; Brout, D. ; Kessler, R. ; Chen, R. ; Galbany, L. ; Kelsey, L. ; Lee, J. ; et al ( July 2023 , The Astrophysical journal)

   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. 

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2. Measuring Cosmological Parameters with Type Ia Supernovae in redMaGiC Galaxies

   https://doi.org/10.3847/1538-4357/ac8b82  

   Chen, R. ; Scolnic, D. ; Rozo, E. ; Rykoff, E. S. ; Popovic, B. ; Kessler, R. ; Vincenzi, M. ; Davis, T. M. ; Armstrong, P. ; Brout, D. ; et al ( October 2022 , The Astrophysical Journal)

   Current and future cosmological analyses with Type Ia supernovae (SNe Ia) face three critical challenges: (i) measuring the redshifts from the SNe or their host galaxies; (ii) classifying the 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 of these challenges. In the context of the Dark Energy Survey (DES), we analyze an SN Ia sample with host galaxies in the redMaGiC galaxy catalog, a selection of luminous red galaxies. redMaGiC photo-zestimates are expected to be accurate toσ_Δz/(1+z)∼ 0.02. The DES-5YR photometrically classified SN Ia 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 relating to classification uncertainties. With this subsample, we find similar Hubble scatter (to within ∼0.01 mag) using photometric redshifts in place of spectroscopic redshifts. With detailed simulations, we show that the bias due to using redMaGiC photo-zs on the measurement of the dark energy equation of statewis up to Δw∼ 0.01–0.02. With real data, we measure a difference inwwhen using the redMaGiC photo-zs versus the spec-zs of Δw= 0.005. Finally, we discuss how SNe in redMaGiC galaxies appear to comprise a more standardizable population, due to a weaker relation between color and luminosity (β) compared to the DES-3YR population by ∼5σ. These results establish the feasibility of performing redMaGiC SN cosmology with photometric survey data in the absence of spectroscopic data.

    

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3. First cosmology results using type Ia supernovae from the Dark Energy Survey: the effect of host galaxy properties on supernova luminosity

   https://doi.org/10.1093/mnras/staa946  

   Smith, M ; Sullivan, M ; Wiseman, P ; Kessler, R ; Scolnic, D ; Brout, D ; D’Andrea, C B ; Davis, T M ; Foley, R J ; Frohmaier, C ; et al ( May 2020 , Monthly Notices of the Royal Astronomical Society)

   ABSTRACT We present improved photometric measurements for the host galaxies of 206 spectroscopically confirmed type Ia supernovae discovered by the Dark Energy Survey Supernova Program (DES-SN) and used in the first DES-SN cosmological analysis. For the DES-SN sample, when considering a 5D (z, x1, c, α, β) bias correction, we find evidence of a Hubble residual ‘mass step’, where SNe Ia in high-mass galaxies (>1010M⊙) are intrinsically more luminous (after correction) than their low-mass counterparts by $\gamma =0.040\pm 0.019$ mag. This value is larger by 0.031 mag than the value found in the first DES-SN cosmological analysis. This difference is due to a combination of updated photometric measurements and improved star formation histories and is not from host-galaxy misidentification. When using a 1D (redshift-only) bias correction the inferred mass step is larger, with $\gamma =0.066\pm 0.020$ mag. The 1D−5D γ difference for DES-SN is $0.026\pm 0.009$ mag. We show that this difference is due to a strong correlation between host galaxy stellar mass and the x1 component of the 5D distance-bias correction. Including an intrinsic correlation between the observed properties of SNe Ia, stretch and colour, and stellar mass in simulated SN Ia samples, we show that a 5D fit recovers γ with −9 mmag bias compared to a +2 mmag bias for a 1D fit. This difference can explain part of the discrepancy seen in the data. Improvements in modelling correlations between galaxy properties and SN is necessary to ensure unbiased precision estimates of the dark energy equation of state as we enter the era of LSST. 

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4. Supernova host galaxies in the dark energy survey: I. Deep coadds, photometry, and stellar masses

   https://doi.org/10.1093/mnras/staa1302  

   Wiseman, P ; Smith, M ; Childress, M ; Kelsey, L ; Möller, A ; Gupta, R R ; Swann, E ; Angus, C R ; Brout, D ; Davis, T M ; et al ( July 2020 , Monthly Notices of the Royal Astronomical Society)

   ABSTRACT The 5-yr Dark Energy Survey Supernova Programme (DES-SN) is one of the largest and deepest transient surveys to date in terms of volume and number of supernovae. Identifying and characterizing the host galaxies of transients plays a key role in their classification, the study of their formation mechanisms, and the cosmological analyses. To derive accurate host galaxy properties, we create depth-optimized coadds using single-epoch DES-SN images that are selected based on sky and atmospheric conditions. For each of the five DES-SN seasons, a separate coadd is made from the other four seasons such that each SN has a corresponding deep coadd with no contaminating SN emission. The coadds reach limiting magnitudes of order ∼27 in g band, and have a much smaller magnitude uncertainty than the previous DES-SN host templates, particularly for faint objects. We present the resulting multiband photometry of host galaxies for samples of spectroscopically confirmed type Ia (SNe Ia), core-collapse (CCSNe), and superluminous (SLSNe) as well as rapidly evolving transients (RETs) discovered by DES-SN. We derive host galaxy stellar masses and probabilistically compare stellar-mass distributions to samples from other surveys. We find that the DES spectroscopically confirmed sample of SNe Ia selects preferentially fewer high-mass hosts at high-redshift compared to other surveys, while at low redshift the distributions are consistent. DES CCSNe and SLSNe hosts are similar to other samples, while RET hosts are unlike the hosts of any other transients, although these differences have not been disentangled from selection effects. 

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5. The Dark Energy Survey supernova program: cosmological biases from supernova photometric classification

   https://doi.org/10.1093/mnras/stac1404  

   Vincenzi, M. ; Sullivan, M. ; Möller, A. ; Armstrong, P. ; Bassett, B. A. ; Brout, D. ; Carollo, D. ; Carr, A. ; Davis, T. M. ; Frohmaier, C. ; et al ( June 2022 , Monthly Notices of the Royal Astronomical Society)

   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 using the photometric classifier SuperNNova on state-of-the-art simulations of SN samples to determine cosmological biases due to such ‘non-Ia’ contamination in the Dark Energy Survey (DES) 5-yr SN sample. Depending on the non-Ia SN models used in the SuperNNova training and testing samples, contamination ranges from 0.8 to 3.5 per cent, with a classification efficiency of 97.7–99.5 per cent. Using the Bayesian Estimation Applied to Multiple Species (BEAMS) framework and its extension BBC (‘BEAMS with Bias Correction’), we produce a redshift-binned Hubble diagram marginalized over contamination and corrected for selection effects, and use it to constrain the dark energy equation-of-state, w. Assuming a flat universe with Gaussian ΩM prior of 0.311 ± 0.010, we show that biases on w are <0.008 when using SuperNNova, with systematic uncertainties associated with contamination around 10 per cent of the statistical uncertainty on w for the DES-SN sample. An alternative approach of discarding contaminants using outlier rejection techniques (e.g. Chauvenet’s criterion) in place of SuperNNova leads to biases on w that are larger but still modest (0.015–0.03). Finally, we measure biases due to contamination on w0 and wa (assuming a flat universe), and find these to be <0.009 in w0 and <0.108 in wa, 5 to 10 times smaller than the statistical uncertainties for the DES-SN sample.

    

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