| 1. |
- Abolfathi, Bela, et al.
(author)
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The LSST DESC DC2 Simulated Sky Survey
- 2021
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In: Astrophysical Journal Supplement Series. - : American Astronomical Society. - 0067-0049 .- 1538-4365. ; 253:31
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Journal article (peer-reviewed)abstract
- We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin's LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep area of approximately 300 deg2, as well as a deep drilling field of approximately 1 deg2. We simulate 5 yr of the planned 10 yr survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the data set to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic test bed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time domain cosmology.
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| 2. |
- Lochner, Michelle, et al.
(author)
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Optimizing the LSST Observing Strategy for Dark Energy Science : DESC Recommendations for the Wide-Fast-Deep Survey
- 2018
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Other publication (other academic/artistic)abstract
- Cosmology is one of the four science pillars of LSST, which promises to be transformative for our understanding of dark energy and dark matter. The LSST Dark Energy Science Collaboration (DESC) has been tasked with deriving constraints on cosmological parameters from LSST data. Each of the cosmological probes for LSST is heavily impacted by the choice of observing strategy. This white paper is written by the LSST DESC Observing Strategy Task Force (OSTF), which represents the entire collaboration, and aims to make recommendations on observing strategy that will benefit all cosmological analyses with LSST. It is accompanied by the DESC DDF (Deep Drilling Fields) white paper (Scolnic et al.). We use a variety of metrics to understand the effects of the observing strategy on measurements of weak lensing, large-scale structure, clusters, photometric redshifts, supernovae, strong lensing and kilonovae. In order to reduce systematic uncertainties, we conclude that the current baseline observing strategy needs to be significantly modified to result in the best possible cosmological constraints. We provide some key recommendations: moving the WFD (Wide-Fast-Deep) footprint to avoid regions of high extinction, taking visit pairs in different filters, changing the 2x15s snaps to a single exposure to improve efficiency, focusing on strategies that reduce long gaps (>15 days) between observations, and prioritizing spatial uniformity at several intervals during the 10-year survey.
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| 3. |
- Dwomoh, Arianna M., et al.
(author)
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Evaluating the Consistency of Cosmological Distances Using Supernova Siblings in the Near-infrared
- 2024
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In: Astrophysical Journal. - 0004-637X .- 1538-4357. ; 965:1
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Journal article (peer-reviewed)abstract
- The study of supernova (SN) siblings, supernovae with the same host galaxy, is an important avenue for understanding and measuring the properties of Type Ia SN Ia light curves (LCs). Thus far, sibling analyses have mainly focused on optical LC data. Considering that LCs in the near-infrared (NIR) are expected to be better standard candles than those in the optical, we carry out the first analysis compiling SN siblings with only NIR data. We perform an extensive literature search of all SN siblings and find six sets of siblings with published NIR photometry. We calibrate each set of siblings ensuring they are on homogeneous photometric systems, fit the LCs with the SALT3-NIR and SNooPy models, and find median absolute differences in μ values between siblings of 0.248 and 0.186 mag, respectively. To evaluate the significance of these differences beyond measurement noise, we run simulations that mimic these LCs and provide an estimate for uncertainty on these median absolute differences of ∼0.052 mag, and we find that, statistically, our analysis rules out the nonexistence of intrinsic scatter in the NIR at the 99% level. When comparing the same sets of SN siblings, we observe a median absolute difference in μ values between siblings of 0.177 mag when using optical data alone as compared to 0.186 mag when using NIR data alone. It is unclear if these results may be due to limited statistics or poor quality NIR data, all of which will be improved with the Nancy Grace Roman Space Telescope.
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| 4. |
- Feeney, Stephen M., et al.
(author)
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Prospects for Resolving the Hubble Constant Tension with Standard Sirens
- 2019
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In: Physical Review Letters. - 0031-9007 .- 1079-7114. ; 122:6
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Journal article (peer-reviewed)abstract
- The Hubble constant (H-0) estimated from the local Cepheid-supernova distance ladder is in 3-sigma tension with the value extrapolated from cosmic microwave background (CMB) data assuming the standard cosmological model. Whether this tension represents newphysics or systematic effects is the subject of intense debate. Here, we investigate how new, independent H-0 estimates can arbitrate this tension, assessing whether the measurements are consistent with being derived from the same model using the posterior predictive distribution (PPD). We show that, with existing data, the inverse distance ladder formed from BOSS baryon acoustic oscillation measurements and the Pantheon supernova sample yields an H-0 posterior near identical to the Planck CMB measurement. The observed local distance ladder value is a very unlikely draw from the resulting PPD. Turning to the future, we find that a sample of similar to 50 binary neutron star standard sirens (detectable within the next decade) will be able to adjudicate between the local and CMB estimates.
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| 5. |
- Goobar, Ariel, et al.
(author)
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The cosmic transparency measured with Type Ia supernovae : implications for intergalactic dust
- 2018
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In: Monthly notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966 .- 1745-3925 .- 1745-3933. ; 477:1, s. l75-L79
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Journal article (peer-reviewed)abstract
- Observations of high-redshift Type Ia supernovae (SNe Ia) are used to study the cosmic transparency at optical wavelengths. Assuming a flat Lambda cold dark matter (Lambda CDM) cosmological model based on baryon acoustic oscillations and cosmic microwave background measurements, redshift dependent deviations of SN Ia distances are used to constrain mechanisms that would dim light. The analysis is based on the most recent Pantheon SN compilation, for which there is a 0.03 +/- 0.01 (stat) mag discrepancy in the distant supernova distance moduli relative to the Lambda CDM model anchored by supernovae at z < 0.05. While there are known systematic uncertainties that combined could explain the observed offset, here we entertain the possibility that the discrepancy may instead be explained by scattering of supernova light in the intergalactic medium (IGM). We focus on two effects: Compton scattering by free electrons and extinction by dust in the IGM. We find that if the discrepancy is entirely due to dimming by dust, the measurements can be modelled with a cosmic dust density Omega(dust)(IGM) = 8 x 10(-5)(1 + z)(-1), corresponding to an average attenuation of 2 x 10(-5) mag Mpc(-1) in V band. Forthcoming SN Ia studies may provide a definitive measurement of the IGM dust properties, while still providing an unbiased estimate of cosmological parameters by introducing additional parameters in the global fits to the observations.
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| 6. |
- Hosseinzadeh, Griffin, et al.
(author)
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Photometric Classification of 2315 Pan-STARRS1 Supernovae with Superphot
- 2020
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In: Astrophysical Journal. - : American Astronomical Society. - 0004-637X .- 1538-4357. ; 905:2
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Journal article (peer-reviewed)abstract
- The classification of supernovae (SNe) and its impact on our understanding of explosion physics and progenitors have traditionally been based on the presence or absence of certain spectral features. However, current and upcoming wide-field time-domain surveys have increased the transient discovery rate far beyond our capacity to obtain even a single spectrum of each new event. We must therefore rely heavily on photometric classification-connecting SN light curves back to their spectroscopically defined classes. Here, we present Superphot, an open-source Python implementation of the machine-learning classification algorithm of Villar et al., and apply it to 2315 previously unclassified transients from the Pan-STARRS1 Medium Deep Survey for which we obtained spectroscopic host-galaxy redshifts. Our classifier achieves an overall accuracy of 82%, with completenesses and purities of >80% for the best classes (SNe Ia and superluminous SNe). For the worst performing SN class (SNe Ibc), the completeness and purity fall to 37% and 21%, respectively. Our classifier provides 1257 newly classified SNe Ia, 521 SNe II, 298 SNe Ibc, 181 SNe IIn, and 58 SLSNe. These are among the largest uniformly observed samples of SNe available in the literature and will enable a wide range of statistical studies of each class.
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| 7. |
- Katebi, Reza, et al.
(author)
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PS1-13cbe : the rapid transition of a Seyfert 2 to a Seyfert 1
- 2019
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In: Monthly notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 487:3, s. 4057-4070
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Journal article (peer-reviewed)abstract
- We present a nuclear transient event, PS1-13cbe, that was first discovered in the Pan-STARRS1 survey in 2013. The outburst occurred in the nucleus of the galaxy SDSS J222153.87+003054.2 at z = 0.123 55, which was classified as a Seyfert 2 in a pre-outburst archival Sloan Digital Sky Survey (SDSS) spectrum. PS1-13cbe showed the appearance of strong broad H alpha and H beta emission lines and a non-stellar continuum in a Magellan spectrum taken 57 d after the peak of the outburst that resembled the characteristics of a Seyfert 1. These broad lines were not present in the SDSS spectrum taken a decade earlier and faded away within 2 yr, as observed in several late-time MDM spectra. We argue that the dramatic appearance and disappearance of the broad lines and a factor of similar to 8 increase in the optical continuum are most likely caused by variability in the pre-existing accretion disc than a tidal disruption event, supernova, or variable obscuration. The time-scale for the turn-on of the optical emission of similar to 70 d observed in this transient is among the shortest observed in a 'changing-look' active galactic nucleus,
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| 8. |
- Lochner, Michelle, et al.
(author)
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The Impact of Observing Strategy on Cosmological Constraints with LSST
- 2022
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In: Astrophysical Journal Supplement Series. - : American Astronomical Society. - 0067-0049 .- 1538-4365. ; 259:2
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Journal article (peer-reviewed)abstract
- The generation-defining Vera C. Rubin Observatory will make state-of-the-art measurements of both the static and transient universe through its Legacy Survey for Space and Time (LSST). With such capabilities, it is immensely challenging to optimize the LSST observing strategy across the survey's wide range of science drivers. Many aspects of the LSST observing strategy relevant to the LSST Dark Energy Science Collaboration, such as survey footprint definition, single-visit exposure time, and the cadence of repeat visits in different filters, are yet to be finalized. Here, we present metrics used to assess the impact of observing strategy on the cosmological probes considered most sensitive to survey design; these are large-scale structure, weak lensing, type Ia supernovae, kilonovae, and strong lens systems (as well as photometric redshifts, which enable many of these probes). We evaluate these metrics for over 100 different simulated potential survey designs. Our results show that multiple observing strategy decisions can profoundly impact cosmological constraints with LSST; these include adjusting the survey footprint, ensuring repeat nightly visits are taken in different filters, and enforcing regular cadence. We provide public code for our metrics, which makes them readily available for evaluating further modifications to the survey design. We conclude with a set of recommendations and highlight observing strategy factors that require further research.
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| 9. |
- Villar, V. Ashley, et al.
(author)
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SuperRAENN : A Semisupervised Supernova Photometric Classification Pipeline Trained on Pan-STARRS1 Medium-Deep Survey Supernovae
- 2020
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In: Astrophysical Journal. - : American Astronomical Society. - 0004-637X .- 1538-4357. ; 905:2
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Journal article (peer-reviewed)abstract
- Automated classification of supernovae (SNe) based on optical photometric light-curve information is essential in the upcoming era of wide-field time domain surveys, such as the Legacy Survey of Space and Time (LSST) conducted by the Rubin Observatory. Photometric classification can enable real-time identification of interesting events for extended multiwavelength follow-up, as well as archival population studies. Here we present the complete sample of 5243 SN-like light curves (in g(P1)r(P1)i(P1)z(P1)) from the Pan-STARRS1 Medium-Deep Survey (PS1-MDS). The PS1-MDS is similar to the planned LSST Wide-Fast-Deep survey in terms of cadence, filters, and depth, making this a useful training set for the community. Using this data set, we train a novel semisupervised machine learning algorithm to photometrically classify 2315 new SN-like light curves with host galaxy spectroscopic redshifts. Our algorithm consists of an RF supervised classification step and a novel unsupervised step in which we introduce a recurrent autoencoder neural network (RAENN). Our final pipeline, dubbed SuperRAENN, has an accuracy of 87% across five SN classes (Type Ia, Ibc, II, IIn, SLSN-I) and macro-averaged purity and completeness of 66% and 69%, respectively. We find the highest accuracy rates for SNe Ia and SLSNe and the lowest for SNe Ibc. Our complete spectroscopically and photometrically classified samples break down into 62.0% Type Ia (1839 objects), 19.8% Type II (553 objects), 4.8% Type IIn (136 objects), 11.7% Type Ibc (291 objects), and 1.6% Type I SLSNe (54 objects).
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