The dark energy survey 5-yr photometrically identified type Ia supernovae

Möller, A.; Smith, M.; Šako, M.; Sullivan, M.; Vincenzi, M.; Wiseman, P.; Armstrong, P.; Asorey, J.; Brout, D.; Carollo, D.; Davis, Tamara M.; Frohmaier, C.; Galbany, L.; Glazebrook, Karl; Kelsey, L.; Keßler, R.; Lewis, Geraint F.; Lidman, C.; Malik, U.; Scolnic, D.; Tucker, B.; Abbott, T. M. C.; Aguena, M.; Allam, S.; Annis, J.; Bertin, E.; Bocquet, S.; Burke, D. L.; Rosell, A. Carnero; Kind, M. Carrasco; Carretero, J.; Castander, F. J.; Conselice, C. J.; Costanzi, M.; Crocce, M.; Costa, L. N. da; Vicente, J. De; Desai, S.; Diehl, H. T.; Doel, P.; Everett, S.; Ferrero, I.; Finley, D. A.; Flaugher, B.; Friedel, D. N.; Frieman, J.; García-Bellido, J.; Gerdes, D. W.; Gruendl, R. A.; Gschwend, J.; Gutiérrez, G.; Herner, K.; Hinton, S. R.; Hollowood, D. L.; Honscheid, K.; James, D. J.; Kuêhn, K.; Kuropatkin, N.; Lahav, O.; March, M.; Marshall, J. L.; Menanteau, F.; Miquel, R.; Morgan, R.; Palmese, A.; Paz-Chinchón, F.; Pieres, A.; Malagón, A. A. Plazas; Romer, A. K.; Sánchez, E.; Scarpine, V.; Schubnell, M.; Serrano, S.; Sevilla-Noarbe, I.; Suchyta, E.; Tarlè, G.; Thomas, Daniel B.; To, C.; Varga, T. N.

doi:10.1093/mnras/stac1691

Cited by 20 publications

(13 citation statements)

References 103 publications

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“…Of the four events in the redMaGiC subsample that are classified as non-Ia by SNN, one is a spectroscopically confirmed Type Ia, and two are classified as Ia when SNN is instead trained on J17 templates (Jones et al 2017). The baseline SNN model for DES in Möller et al (2022) also classifies one of the events as Ia. In particular, we note that using DIFFIMG, the misclassified spectroscopically confirmed SN Ia has inaccurately subtracted template images in the g band.…”

Section: Potential Core-collapse Contaminationmentioning

confidence: 93%

“…To consider potential contaminants, we define an unlikely-Ia SN as having a probability of being a Type Ia of <0.5. With the conventional SALT2 cosmology cuts (Betoule et al 2014), the color uncertainty cut as included in this analysis, and no classifier, the simulated DES-5YR photometric SN sample includes 8% contamination (V21; Möller et al 2022). Of the 125 SNe in redMaGiC galaxies that pass the post-SALT2 fit cuts, four are classified by SNN as unlikely-Ia (∼3%).…”

Section: Potential Core-collapse Contaminationmentioning

confidence: 99%

“…The Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC; the PLAsTiCC Team et al 2018) included a mix of 18 transient models (Kessler et al 2019), and the top-performing light-curve classifiers achieved 95% levels of purity, by training on a subset of the data (Hložek et al 2020). SuperNNova (SNN; Moller & de Boissière 2020), a neural net classifier trained on simulations that use PLAsTiCC models (SNIa, SNIax, SNIa-91bg, SNII, and SNIb/c), has a predicted efficiency from DES simulations of 97.7%-99.5% (Vincenzi et al 2022;Möller et al 2022). An alternate approach to photometric classification is to use host galaxy information to avoid problems with low signal-to-noise ratio (S/N) data and sparse sampling.…”

Section: Introductionmentioning

confidence: 99%

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Measuring Cosmological Parameters with Type Ia Supernovae in redMaGiC Galaxies

Chen

Scolnic

Rozo

et al. 2022

ApJ

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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-z estimates are expected to be accurate to σ 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 state w is up to Δw ∼ 0.01–0.02. With real data, we measure a difference in w when 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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Section: Potential Core-collapse Contaminationmentioning

confidence: 93%

Section: Potential Core-collapse Contaminationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Measuring Cosmological Parameters with Type Ia Supernovae in redMaGiC Galaxies

Chen

Scolnic

Rozo

et al. 2022

ApJ

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“…We utilise the DES5YR-SN photometric sample described in Möller et al (2022). The SNe Ia were classified with the SuperNNova (SNN) classifier (Möller & de Boissière 2020).…”

Section: Type Ia Supernovae Samplementioning

confidence: 99%

Using host galaxy spectroscopy to explore systematics in the standardization of Type Ia supernovae

Dixon

Lidman

Mould

et al. 2022

Monthly Notices of the Royal Astronomical Society

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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 (3σ) between Hubble residual and the Balmer decrement (a measure of reddening by dust) using Hβ and Hγ. 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.

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“…The photometry is obtained using diffimg (Kessler et al 2015). DES photometric classification is outlined in Vincenzi et al (2021) and Möller et al (2022), with host association details in Wiseman et al (2020).…”

Section: The Des-sn Photometric Sn Ia Samplementioning

confidence: 99%

Concerning colour: The effect of environment on type Ia supernova colour in the dark energy survey

Kelsey

Sullivan

Wiseman

et al. 2022

Monthly Notices of the Royal Astronomical Society

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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 (Mstellar) 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 (∼0.14 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 Mstellar, approximating existing dust models, we remove the mass-step from the data and find tentative ∼2σ residual steps in rest-frame galaxy U − R colour. This indicates that dust modelling based on Mstellar 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 ≤1σ residual steps in Mstellar and local U − R, suggesting that U − R provides different information about the environment of SNe Ia compared to Mstellar, and motivating the inclusion of galaxy U − R colour in SN Ia distance bias correction.

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The dark energy survey 5-yr photometrically identified type Ia supernovae

Cited by 20 publications

References 103 publications

Measuring Cosmological Parameters with Type Ia Supernovae in redMaGiC Galaxies

Measuring Cosmological Parameters with Type Ia Supernovae in redMaGiC Galaxies

Using host galaxy spectroscopy to explore systematics in the standardization of Type Ia supernovae

Concerning colour: The effect of environment on type Ia supernova colour in the dark energy survey

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