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  1. ABSTRACT We study the optical gri photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during ∼1998−2020 with SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up monitoring with Blanco 4m/DECam. With on average ∼200 nightly epochs per quasar per filter band, we improve the parameter constraints from a Damped Random Walk (DRW) model fit to the light curves over previous studies with 10–15 yr baselines and ≲ 100 epochs. We find that the average damping time-scale τDRW continues to rise with increased baseline, reaching a median value of ∼750 d (g band) in the rest frame of these quasars using the 20-yr light curves. Some quasars may have gradual, long-term trends in their light curves, suggesting that either the DRW fit requires very long baselines to converge, or that the underlying variability is more complex than a single DRW process for these quasars. Using a subset of quasars with better-constrained τDRW (less than 20 per cent of the baseline), we confirm a weak wavelength dependence of τDRW∝λ0.51 ± 0.20. We further quantify optical variability of these quasars over days to decades time-scales using structure function (SF) and power spectrum density (PSD) analyses. The SF andmore »PSD measurements qualitatively confirm the measured (hundreds of days) damping time-scales from the DRW fits. However, the ensemble PSD is steeper than that of a DRW on time-scales less than ∼ a month for these luminous quasars, and this second break point correlates with the longer DRW damping time-scale.« less
    Free, publicly-accessible full text available June 2, 2023
  2. ABSTRACT As part of the cosmology analysis using Type Ia Supernovae (SN Ia) in the Dark Energy Survey (DES), we present photometrically identified SN Ia samples using multiband light curves and host galaxy redshifts. For this analysis, we use the photometric classification framework SuperNNovatrained on realistic DES-like simulations. For reliable classification, we process the DES SN programme (DES-SN) data and introduce improvements to the classifier architecture, obtaining classification accuracies of more than 98 per cent on simulations. This is the first SN classification to make use of ensemble methods, resulting in more robust samples. Using photometry, host galaxy redshifts, and a classification probability requirement, we identify 1863 SNe Ia from which we select 1484 cosmology-grade SNe Ia spanning the redshift range of 0.07 < z < 1.14. We find good agreement between the light-curve properties of the photometrically selected sample and simulations. Additionally, we create similar SN Ia samples using two types of Bayesian Neural Network classifiers that provide uncertainties on the classification probabilities. We test the feasibility of using these uncertainties as indicators for out-of-distribution candidates and model confidence. Finally, we discuss the implications of photometric samples and classification methods for future surveys such as Vera C. Rubin Observatory Legacy Surveymore »of Space and Time.« less
    Free, publicly-accessible full text available July 7, 2023
  3. 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-year SN sample. Depending on the non-Ia SN models used in the SuperNNova training and testing samples, contamination ranges from 0.8–3.5 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 marginalised 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 stillmore »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.« less
    Free, publicly-accessible full text available June 3, 2023
  4. ABSTRACT We present multiwavelength spectral and temporal variability analysis of PKS 0027-426 using optical griz observations from Dark Energy Survey between 2013 and 2018 and VEILS Optical Light curves of Extragalactic TransienT Events (VOILETTE) between 2018 and 2019 and near-infrared (NIR) JKs observations from Visible and Infrared Survey Telescope for Astronomy Extragalactic Infrared Legacy Survey (VEILS) between 2017 and 2019. Multiple methods of cross-correlation of each combination of light curve provides measurements of possible lags between optical–optical, optical–NIR, and NIR–NIR emission, for each observation season and for the entire observational period. Inter-band time lag measurements consistently suggest either simultaneous emission or delays between emission regions on time-scales smaller than the cadences of observations. The colour–magnitude relation between each combination of filters was also studied to determine the spectral behaviour of PKS 0027-426. Our results demonstrate complex colour behaviour that changes between bluer when brighter, stable when brighter, and redder when brighter trends over different time-scales and using different combinations of optical filters. Additional analysis of the optical spectra is performed to provide further understanding of this complex spectral behaviour.
    Free, publicly-accessible full text available January 8, 2023
  5. Abstract We present the second public data release (DR2) from the DECam Local Volume Exploration survey (DELVE). DELVE DR2 combines new DECam observations with archival DECam data from the Dark Energy Survey, the DECam Legacy Survey, and other DECam community programs. DELVE DR2 consists of ∼160,000 exposures that cover >21,000 deg 2 of the high-Galactic-latitude (∣ b ∣ > 10°) sky in four broadband optical/near-infrared filters ( g , r , i , z ). DELVE DR2 provides point-source and automatic aperture photometry for ∼2.5 billion astronomical sources with a median 5 σ point-source depth of g = 24.3, r = 23.9, i = 23.5, and z = 22.8 mag. A region of ∼17,000 deg 2 has been imaged in all four filters, providing four-band photometric measurements for ∼618 million astronomical sources. DELVE DR2 covers more than 4 times the area of the previous DELVE data release and contains roughly 5 times as many astronomical objects. DELVE DR2 is publicly available via the NOIRLab Astro Data Lab science platform.
    Free, publicly-accessible full text available August 1, 2023
  6. Free, publicly-accessible full text available June 1, 2023
  7. ABSTRACT Reverberation mapping is a robust method to measure the masses of supermassive black holes outside of the local Universe. Measurements of the radius–luminosity (R−L) relation using the Mg ii emission line are critical for determining these masses near the peak of quasar activity at z ≈ 1−2, and for calibrating secondary mass estimators based on Mg ii that can be applied to large samples with only single-epoch spectroscopy. We present the first nine Mg ii lags from our 5-yr Australian Dark Energy Survey reverberation mapping programme, which substantially improves the number and quality of Mg ii lag measurements. As the Mg ii feature is somewhat blended with iron emission, we model and subtract both the continuum and iron contamination from the multiepoch spectra before analysing the Mg ii line. We also develop a new method of quantifying correlated spectroscopic calibration errors based on our numerous, contemporaneous observations of F-stars. The lag measurements for seven of our nine sources are consistent with both the H β and Mg ii R−L relations reported by previous studies. Our simulations verify the lag reliability of our nine measurements, and we estimate that the median false positive rate of the lag measurements is $4{{\ \rm per\ cent}}$.
  8. Abstract SN 2017jgh is a type IIb supernova discovered by Pan-STARRS during the C16/C17 campaigns of the Kepler/K2 mission. Here we present the Kepler/K2 and ground based observations of SN 2017jgh, which captured the shock cooling of the progenitor shock breakout with an unprecedented cadence. This event presents a unique opportunity to investigate the progenitors of stripped envelope supernovae. By fitting analytical models to the SN 2017jgh lightcurve, we find that the progenitor of SN 2017jgh was likely a yellow supergiant with an envelope radius of ∼50 − 290 R⊙, and an envelope mass of ∼0 − 1.7 M⊙. SN 2017jgh likely had a shock velocity of ∼7500 − 10300 km s−1. Additionally, we use the lightcurve of SN 2017jgh to investigate how early observations of the rise contribute to constraints on progenitor models. Fitting just the ground based observations, we find an envelope radius of ∼50 − 330 R⊙, an envelope mass of ∼0.3 − 1.7 M⊙ and a shock velocity of ∼9, 000 − 15, 000 km s−1. Without the rise, the explosion time can not be well constrained which leads to a systematic offset in the velocity parameter and larger uncertainties in the mass and radius. Therefore, it is likely that progenitor property estimates throughmore »these models may have larger systematic uncertainties than previously calculated.« less
  9. ABSTRACT We constrain the matter density Ωm and the amplitude of density fluctuations σ8 within the ΛCDM cosmological model with shear peak statistics and angular convergence power spectra using mass maps constructed from the first three years of data of the Dark Energy Survey (DES Y3). We use tomographic shear peak statistics, including cross-peaks: peak counts calculated on maps created by taking a harmonic space product of the convergence of two tomographic redshift bins. Our analysis follows a forward-modelling scheme to create a likelihood of these statistics using N-body simulations, using a Gaussian process emulator. We take into account the uncertainty from the remaining, largely unconstrained ΛCDM parameters (Ωb, ns, and h). We include the following lensing systematics: multiplicative shear bias, photometric redshift uncertainty, and galaxy intrinsic alignment. Stringent scale cuts are applied to avoid biases from unmodelled baryonic physics. We find that the additional non-Gaussian information leads to a tightening of the constraints on the structure growth parameter yielding $S_8~\equiv ~\sigma _8\sqrt{\Omega _{\mathrm{m}}/0.3}~=~0.797_{-0.013}^{+0.015}$ (68 per cent confidence limits), with a precision of 1.8 per cent, an improvement of 38 per cent compared to the angular power spectra only case. The results obtained with the angular power spectra and peak counts are found to be inmore »agreement with each other and no significant difference in S8 is recorded. We find a mild tension of $1.5 \, \sigma$ between our study and the results from Planck 2018, with our analysis yielding a lower S8. Furthermore, we observe that the combination of angular power spectra and tomographic peak counts breaks the degeneracy between galaxy intrinsic alignment AIA and S8, improving cosmological constraints. We run a suite of tests concluding that our results are robust and consistent with the results from other studies using DES Y3 data.« less
    Free, publicly-accessible full text available February 11, 2023
  10. Free, publicly-accessible full text available February 1, 2023