Engineering topics

Bassett, B. A.

Publications and source records attributed to Bassett, B. A..

5 records

DOE OSTI2024

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 7000 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 5. 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 ${\sigma }_{{{\rm{\Omega }}}_{M},\mathrm{stat}+\mathrm{sys}}^{{\rm{\Lambda }}\mathrm{CDM}}=$ 0.017 in a flat ΛCDM model, and $({\sigma }_{{{\rm{\Omega }}}_{M}},{\sigma }_{w}{)}_{\mathrm{stat}+\mathrm{sys}}^{w\mathrm{CDM}}$ = (0.082, 0.152) in a flat wCDM model. Combining the DES SN data with the highly complementary cosmic microwave background measurements by Planck Collaboration reduces by a factor of 4 uncertainties on cosmological parameters. 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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The Dark Energy Survey: Cosmology Results with ∼1500 New High-redshift Type Ia Supernovae Using the Full 5 yr Data Set

Abstract We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, in which SNe are classified based on their spectra, we classify the DES SNe using a machine learning algorithm applied to their light curves in four photometric bands. Spectroscopic redshifts are acquired from a dedicated follow-up survey of the host galaxies. After accounting for the likelihood of each SN being an SN Ia, we find 1635 DES SNe in the redshift range 0.10 < z < 1.13 that pass quality selection criteria sufficient to constrain cosmological parameters. This quintuples the number of high-quality z > 0.5 SNe compared to the previous leading compilation of Pantheon+ and results in the tightest cosmological constraints achieved by any SN data set to date. To derive cosmological constraints, we combine the DES SN data with a high-quality external low-redshift sample consisting of 194 SNe Ia spanning 0.025 < z < 0.10. Using SN data alone and including systematic uncertainties, we find Ω M = 0.352 ± 0.017 in flat ΛCDM. SN data alone now require acceleration ( q 0 < 0 in ΛCDM) with over 5 σ confidence. We find ( Ω M , w ) = ( 0.264 − 0.096 + 0.074 , − 0.80 − 0.16 + 0.14 ) in flat w CDM. For flat w 0 w a CDM, we find ( Ω M , w 0 , w a ) = ( 0.495 − 0.043 + 0.033 , − 0.36 − 0.30 + 0.36 , − 8.8 − 4.5 + 3.7 ) , consistent with a constant equation of state to within ∼2 σ . Including Planck cosmic microwave background, Sloan Digital Sky Survey baryon acoustic oscillation, and DES 3 × 2pt data gives (Ω M , w ) = (0.321 ± 0.007, −0.941 ± 0.026). In all cases, dark energy is consistent with a cosmological constant to within ∼2 σ . Systematic errors on cosmological parameters are subdominant compared to statistical errors; these results thus pave the way for future photometrically classified SN analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

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

ABSTRACT 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.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

First Cosmology Results using Supernovae Ia from the Dark Energy Survey: Survey Overview, Performance, and Supernova Spectroscopy

We present details on the observing strategy, data-processing techniques, and spectroscopic targeting algorithms for the first three years of operation for the Dark Energy Survey Supernova Program (DES-SN). This five-year program using the Dark Energy Camera mounted on the 4 m Blanco telescope in Chile was designed to discover and follow supernovae (SNe) Ia over a wide redshift range (0.05 < z < 1.2) to measure the equation-of-state parameter of dark energy. We describe the SN program in full: strategy, observations, data reduction, spectroscopic follow-up observations, and classification. From three seasons of data, we have discovered 12,015 likely SNe, 308 of which have been spectroscopically confirmed, including 251 SNe Ia over a redshift range of 0.017 < z < 0.85. We determine the effective spectroscopic selection function for our sample and use it to investigate the redshift-dependent bias on the distance moduli of SNe Ia we have classified. The data presented here are used for the first cosmology analysis by DES-SN (“DES-SN3YR”), the results of which are given in Dark Energy Survey Collaboration et al. The 489 spectra that are used to define the DES-SN3YR sample are publicly available at https://des.ncsa.illinois.edu/releases/sn.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

The mystery of photometric twins DES17X1boj and DES16E2bjy

In this paper, we present an analysis of DES17X1boj and DES16E2bjy, two peculiar transients discovered by the Dark Energy Survey (DES). They exhibit nearly identical double-peaked light curves that reach very different maximum luminosities ($M_r$ = -15.4 and -17.9, respectively). The light-curve evolution of these events is highly atypical and has not been reported before. The transients are found in different host environments: DES17X1boj was found near the nucleus of a spiral galaxy, while DES16E2bjy is located in the outskirts of a passive red galaxy. Early photometric data are well fitted with a blackbody and the resulting moderate photospheric expansion velocities (1800 km s –1 for DES17X1boj and 4800 km s –1 for DES16E2bjy) suggest an explosive or eruptive origin. Additionally, a feature identified as high-velocity Ca II absorption ($v ≈$ 9400 km s –1 ) in the near-peak spectrum of DES17X1boj may imply that it is a supernova. While similar light-curve evolution suggests a similar physical origin for these two transients, we are not able to identify or characterize the progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗