9 research outputs found
Observing the earliest moments of supernovae using strong gravitational lenses
We determine the viability of exploiting lensing time delays to observe
strongly gravitationally lensed supernovae (gLSNe) from first light. Assuming a
plausible discovery strategy, the Legacy Survey of Space and Time (LSST) and
the Zwicky Transient Facility (ZTF) will discover 110 and 1
systems per year before the supernova (SN) explosion in the final image
respectively. Systems will be identified days before the
final explosion. We then explore the possibility of performing early-time
observations for Type IIP and Type Ia SNe in LSST-discovered systems. Using a
simulated Type IIP explosion, we predict that the shock breakout in one
trailing image per year will peak at 24.1 mag ( 23.3) in
the -band (), however evolving over a timescale of 30 minutes.
Using an analytic model of Type Ia companion interaction, we find that in the
-band we should observe at least one shock cooling emission event per year
that peaks at 26.3 mag ( 29.6) assuming all Type Ia gLSNe
have a 1 M red giant (main sequence) companion. We perform Bayesian
analysis to investigate how well deep observations with 1 hour exposures on the
European Extremely Large Telescope would discriminate between Type Ia
progenitor populations. We find that if all Type Ia SNe evolved from the
double-degenerate channel, then observations of the lack of early blue flux in
10 (50) trailing images would rule out more than 27% (19%) of the population
having 1 M main sequence companions at 95% confidence.Comment: 17 pages, 15 figures (including appendices). Accepted by MNRAS 3rd
May 202
Observing the earliest moments of supernovae using strong gravitational lenses
We determine the viability of exploiting lensing time delays to observe strongly gravitationally lensed supernovae (gLSNe) from first light. Assuming a plausible discovery strategy, the Legacy Survey of Space and Time (LSST) and the Zwicky Transient Facility (ZTF) will discover ∼110 and ∼1 systems per year before the supernova (SN) explosion in the final image, respectively. Systems will be identified 11.7^(+29.8)_(−9.3) d before the final explosion. We then explore the possibility of performing early-time observations for Type IIP and Type Ia SNe in LSST-discovered systems. Using a simulated Type IIP explosion, we predict that the shock breakout in one trailing image per year will peak at ≲24.1 mag (≲23.3) in the B-band (F218W), however evolving over a time-scale of ∼30 min. Using an analytic model of Type Ia companion interaction, we find that in the B-band we should observe at least one shock cooling emission event per year that peaks at ≲26.3 mag (≲29.6) assuming all Type Ia gLSNe have a 1 M_⊙ red giant (main sequence) companion. We perform Bayesian analysis to investigate how well deep observations with 1 h exposures on the European Extremely Large Telescope would discriminate between Type Ia progenitor populations. We find that if all Type Ia SNe evolved from the double-degenerate channel, then observations of the lack of early blue flux in 10 (50) trailing images would rule out more than 27 per cent (19 per cent) of the population having 1 M_⊙ main sequence companions at 95 per cent confidence
The mystery of photometric twins DES17X1boj and DES16E2bjy
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 (Mr = −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
First cosmology results using type Ia supernovae from the Dark Energy Survey: the effect of host galaxy properties on supernova luminosity
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 γ=0.040 +- 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 γ=0.066 +- 0.020 mag. The 1D−5D γ difference for DES-SN is 0.026 +- 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.We acknowledge support from EU/FP7-ERC grant no. 615929. LG
was funded by the European Union’s Horizon 2020 research and
innovation programme under the Marie Skłodowska-Curie grant
agreement no. 839090.
The UCSC team is supported in part by NASA grant no.
NNG17PX03C, NSF grant nos AST-1518052 and AST-1815935,
the Gordon & Betty Moore Foundation, the Heising-Simons Foundation, and by fellowships from the Alfred P. Sloan Foundation and
the David and Lucile Packard Foundation to RJF.
This work was completed in part with resources provided by the
University of Chicago Research Computing Center. This research
used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science
User Facility operated under Contract No. DE-AC02-05CH11231.
Funding for the DES Projects has been provided by the U.S.
Department of Energy, the U.S. National Science Foundation,
the Ministry of Science and Education of Spain, the Science
and Technology Facilities Council of the United Kingdom, the
Higher Education Funding Council for England, the National Center
for Supercomputing Applications at the University of Illinois at Urbana-Champaign, the Kavli Institute of Cosmological Physics
at the University of Chicago, the Center for Cosmology and
Astro-Particle Physics at the Ohio State University, the Mitchell
Institute for Fundamental Physics and Astronomy at Texas A&M
University, Financiadora de Estudos e Projetos, Fundac¸ao Carlos ˜
Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro, `
Conselho Nacional de Desenvolvimento Cient´ıfico e Tecnologico ´
and the Ministerio da Ci ´ encia, Tecnologia e Inovac ˆ ¸ao, the Deutsche ˜
Forschungsgemeinschaft and the Collaborating Institutions in the
Dark Energy Survey
PISCOLA: a data-driven transient light-curve fitter
International audienceForthcoming time-domain surveys, such as the Rubin Observatory Legacy Survey of Space and Time, will vastly increase samples of supernovae (SNe) and other optical transients, requiring new data-driven techniques to analyse their photometric light curves. Here, we present the ‘Python for Intelligent Supernova-COsmology Light-curve Analysis’ (PISCOLA ), an open source data-driven light-curve fitter using Gaussian Processes that can estimate rest-frame light curves of transients without the need for an underlying light-curve template. We test PISCOLA on large-scale simulations of type Ia SNe (SNe Ia) to validate its performance, and show it successfully retrieves rest-frame peak magnitudes for average survey cadences of up to 7 d. We also compare to the existing SN Ia light-curve fitter SALT2 on real data, and find only small (but significant) disagreements for different light-curve parameters. As a proof-of-concept of an application of PISCOLA , we decomposed and analysed the PISCOLA rest-frame light curves of SNe Ia from the Pantheon SN Ia sample with Non-Negative Matrix Factorization. Our new parametrization provides a similar performance to existing light-curve fitters such as SALT2. We further derived a SN Ia colour law from PISCOLA fits over ∼3500–7000 Å, and find agreement with the SALT2 colour law and with reddening laws with total-to-selective extinction ratio ≲ 3.1
Understanding the extreme luminosity of DES14X2fna
ABSTRACT
We present DES14X2fna, a high-luminosity, fast-declining Type IIb supernova (SN IIb) at redshift z = 0.0453, detected by the Dark Energy Survey (DES). DES14X2fna is an unusual member of its class, with a light curve showing a broad, luminous peak reaching Mr ≃ −19.3 mag 20 d after explosion. This object does not show a linear decline tail in the light curve until ≃60 d after explosion, after which it declines very rapidly (4.30 ± 0.10 mag 100 d−1 in the r band). By fitting semi-analytic models to the photometry of DES14X2fna, we find that its light curve cannot be explained by a standard 56Ni decay model as this is unable to fit the peak and fast tail decline observed. Inclusion of either interaction with surrounding circumstellar material or a rapidly-rotating neutron star (magnetar) significantly increases the quality of the model fit. We also investigate the possibility for an object similar to DES14X2fna to act as a contaminant in photometric samples of SNe Ia for cosmology, finding that a similar simulated object is misclassified by a recurrent neural network (RNN)-based photometric classifier as an SN Ia in ∼1.1–2.4 per cent of cases in DES, depending on the probability threshold used for a positive classification
The Dark Energy Survey supernova programme: modelling selection efficiency and observed core-collapse supernova contamination
ABSTRACT
The analysis of current and future cosmological surveys of Type Ia supernovae (SNe Ia) at high redshift depends on the accurate photometric classification of the SN events detected. Generating realistic simulations of photometric SN surveys constitutes an essential step for training and testing photometric classification algorithms, and for correcting biases introduced by selection effects and contamination arising from core-collapse SNe in the photometric SN Ia samples. We use published SN time-series spectrophotometric templates, rates, luminosity functions, and empirical relationships between SNe and their host galaxies to construct a framework for simulating photometric SN surveys. We present this framework in the context of the Dark Energy Survey (DES) 5-yr photometric SN sample, comparing our simulations of DES with the observed DES transient populations. We demonstrate excellent agreement in many distributions, including Hubble residuals, between our simulations and data. We estimate the core collapse fraction expected in the DES SN sample after selection requirements are applied and before photometric classification. After testing different modelling choices and astrophysical assumptions underlying our simulation, we find that the predicted contamination varies from 7.2 to 11.7 per cent, with an average of 8.8 per cent and an r.m.s. of 1.1 per cent. Our simulations are the first to reproduce the observed photometric SN and host galaxy properties in high-redshift surveys without fine-tuning the input parameters. The simulation methods presented here will be a critical component of the cosmology analysis of the DES photometric SN Ia sample: correcting for biases arising from contamination, and evaluating the associated systematic uncertainty
Rates and delay times of Type Ia supernovae in the Dark Energy Survey
We use a sample of 809 photometrically classified Type Ia supernovae (SNe Ia) discovered by the Dark Energy Survey (DES) along with 40 415 field galaxies to calculate the rate of SNe Ia per galaxy in the redshift range 0.2 < z < 0.6. We recover the known correlation between SN Ia rate and galaxy stellar mass across a broad range of scales 8.5 ≤ log (M*/M⊙) ≤ 11.25. We find that the SN Ia rate increases with stellar mass as a power law with index 0.63 ± 0.02, which is consistent with the previous work. We use an empirical model of stellar mass assembly to estimate the average star formation histories (SFHs) of galaxies across the stellar mass range of our measurement. Combining the modelled SFHs with the SN Ia rates to estimate constraints on the SN Ia delay time distribution (DTD), we find that the data are fit well by a power-law DTD with slope index β = −1.13 ± 0.05 and normalization A = 2.11 ± 0.05 × 10−13 SNe M⊙−1 yr−1, which corresponds to an overall SN Ia production efficiency NIa/M∗=0.9 +4.0−0.7×10−3 SNe M−1⊙. Upon splitting the SN sample by properties of the light curves, we find a strong dependence on DTD slope with the SN decline rate, with slower-declining SNe exhibiting a steeper DTD slope. We interpret this as a result of a relationship between intrinsic luminosity and progenitor age, and explore the implications of the result in the context of SN Ia progenitors