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At least 37 records · Page 2

Deep learning unresolved lensed light curves

ABSTRACT Gravitationally lensed sources may have unresolved or blended multiple images, and for time varying sources, the light curves from individual images can overlap. We use convolutional neural nets to both classify the light curves as due to unlensed, double, or quad lensed sources and fit for the time delays. Focusing on lensed supernova systems with time delays Δt ≳ 6 d, we achieve 100 per cent precision and recall in identifying the number of images and then estimating the time delays to σΔt ≈ 1 d, with a 1000× speedup relative to our previous Monte Carlo technique. This also succeeds for flux noise levels $\sim 10{{\ \rm per\ cent}}$. For Δt ∈ [2, 6] d, we obtain 94–98 per cent accuracy, depending on image configuration. We also explore using partial light curves where observations only start near maximum light, without the rise time data, and quantify the success.

79 ASTRONOMY AND ASTROPHYSICS↗

The Early Light Curve of the Type Ia Supernova 2021hpr in NGC 3147: Progenitor Constraints with the Companion Interaction Model

The progenitor system of Type Ia supernovae (SNe Ia) is expected to be a close binary system consisting of a carbon/oxygen white dwarf (WD) and a nondegenerate star or another WD. Here, we present results from high-cadence monitoring observations of SN 2021hpr in a spiral galaxy, NGC 3147, and constraints on the progenitor system based on its early multicolor light-curve data. First, we classify SN 2021hpr as a normal SN Ia from its long-term photometric and spectroscopic data. More interestingly, we found a significant "early excess" in the light curve over a simple power-law ~t 2 evolution. The early light curve evolves from blue to red to blue during the first week. To explain this, we fitted the early part of the BVRI-band light curves with a two-component model consisting of ejecta–companion interaction and a simple power-law model. The early excess and its color can be explained by shock-cooling emission due to a companion star having a radius of 8.84 ± 0.58 R ⊙ . We also examined Hubble Space Telescope preexplosion images, finding no detection of a progenitor candidate, consistent with the above result. However, we could not detect signs of a significant amount of stripped mass from a nondegenerate companion star (≲0.003 M ⊙ for Hα emission). The early excess light in the multiband light curve supports a nondegenerate companion in the progenitor system of SN 2021hpr. At the same time, the nondetection of emission lines opens the door for other methods to explain this event.

79 ASTRONOMY AND ASTROPHYSICS↗

Deep drilling in the time domain with DECam – II: characterizing the light curves of candidates in the extragalactic fields

ABSTRACT In this second paper on the DECam deep-drilling field (DDF) program, we release 2020 optical $gri$-band light curves for transients and variables in the extragalactic COSMOS and ELAIS fields based on time series observations with a 3-d cadence from semester 2021A through 2023A. In order to demonstrate the wide variety of time domain events detected by the program and encourage others to use the data set, we characterize the sample by presenting a brief analysis of the light-curve parameters such as time span, amplitude, and peak brightness. We also present preliminary light-curve categorizations, and identify potential stellar variables, active galactic nuclei, tidal disruption events, supernovae (SNe) (such as Type Ia, Type IIP, superluminous, and gravitationally lensed SNe), and fast transients. Where relevant, the number of identified transients is compared to the predictions of the original proposal. We also discuss the challenges of analyzing DDF data in the context of the upcoming Vera C. Rubin Observatory and its Legacy Survey of Space and Time, which will include DDFs. Images from the Dark Energy Camera DDF program are available without proprietary period and the light curves presented in this work are publicly available for analysis.

Graham, Melissa L. (ORCID:0000000291543136)↗

Training custom light curve models of SN Ia subpopulations selected according to host galaxy properties

ABSTRACT Type Ia supernova (SN Ia) cosmology analyses include a luminosity step function in their distance standardization process to account for an observed yet unexplained difference in the post-standardization luminosities of SNe Ia originating from different host galaxy populations [e.g. high-mass ($M \gtrsim 10^{10} \, {\rm M}_{\odot }$) versus low-mass galaxies]. We present a novel method for including host-mass correlations in the SALT3 (Spectral Adaptive Light curve Template 3) light curve model used for standardizing SN Ia distances. We split the SALT3 training sample according to host-mass, training independent models for the low- and high-host-mass samples. Our models indicate that there are different average Si ii spectral feature strengths between the two populations, and that the average spectral energy distribution of SNe from low-mass galaxies is bluer than the high-mass counterpart. We then use our trained models to perform an SN cosmology analysis on the 3-yr spectroscopically confirmed Dark Energy Survey SN sample, treating SNe from low- and high-mass host galaxies as separate populations throughout. We find that our mass-split models reduce the Hubble residual scatter in the sample, albeit at a low statistical significance. We do find a reduction in the mass-correlated luminosity step but conclude that this arises from the model-dependent re-definition of the fiducial SN absolute magnitude rather than the models themselves. Our results stress the importance of adopting a standard definition of the SN parameters (x0, x1, c) in order to extract the most value out of the light curve modelling tools that are currently available and to correctly interpret results that are fit with different models.

Taylor, G. (ORCID:0000000157563259)↗

Alert Classification for the ALeRCE Broker System: The Light Curve Classifier

We present the first version of the Automatic Learning for the Rapid Classification of Events (ALeRCE) broker light curve classifier. ALeRCE is currently processing the Zwicky Transient Facility (ZTF) alert stream, in preparation for the Vera C. Rubin Observatory. The ALeRCE light curve classifier uses variability features computed from the ZTF alert stream and colors obtained from AllWISE and ZTF photometry. We apply a balanced random forest algorithm with a two-level scheme where the top level classifies each source as periodic, stochastic, or transient, and the bottom level further resolves each of these hierarchical classes among 15 total classes. This classifier corresponds to the first attempt to classify multiple classes of stochastic variables (including core- and host-dominated active galactic nuclei, blazars, young stellar objects, and cataclysmic variables) in addition to different classes of periodic and transient sources, using real data. We created a labeled set using various public catalogs (such as the Catalina Surveys and Gaia DR2 variable stars catalogs, and the Million Quasars catalog), and we classify all objects with ≥6 g-band or ≥6 r-band detections in ZTF (868,371 sources as of 2020 June 9), providing updated classifications for sources with new alerts every day. For the top level we obtain macro-averaged precision and recall scores of 0.96 and 0.99, respectively, and for the bottom level we obtain macro-averaged precision and recall scores of 0.57 and 0.76, respectively. Updated classifications from the light curve classifier can be found at the ALeRCE Explorer website (http://alerce.online).

47 OTHER INSTRUMENTATION↗

Bolide Light-curve Analysis and Discrimination Explorer (BLADE)

SAND2025-09601O Bolide Light-curve Analysis and Discrimination Explorer (BLADE) is a robust, high-fidelity framework designed to analyze the light curves of bolides—objects detected from space. It automates the identification of fragmentation events and energy release modes, using advanced techniques like Savitzky-Golay filtering, prominence-based peak detection, and gradient analysis. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Silber, Elizabeth [Sandia National Lab. (SNL-CA), ↗

Astraea: Predicting Long Rotation Periods with 27 Day Light Curves

The rotation periods of planet-hosting stars can be used for modeling and mitigating the impact of magnetic activity in radial velocity measurements and can help constrain the high-energy flux environment and space weather of planetary systems. Millions of stars and thousands of planet hosts are observed with the Transiting Exoplanet Survey Satellite (TESS). However, most will only be observed for 27 contiguous days in a year, making it difficult to measure rotation periods with traditional methods. This is especially problematic for field M dwarfs, which are ideal candidates for exoplanet searches, but which tend to have periods in excess of the 27 day observing baseline. We present a new tool, Astraea, for predicting long rotation periods from short-duration light curves combined with stellar parameters from Gaia DR2. Using Astraea, we can predict the rotation periods from Kepler 4 yr light curves with 13% uncertainty overall (and a 9% uncertainty for periods >30 days). By training on 27 day Kepler light-curve segments, Astraea can predict rotation periods up to 150 days with 9% uncertainty (5% for periods >30 days). After training this tool on these 27 day Kepler light-curve segments, we applied Astraea to real TESS data. For the 195 stars that were observed by both Kepler and TESS, we were able to predict the rotation periods with 55% uncertainty despite the wild differences in systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

The South Pole Telescope AGN Monitoring Campaign: First Release of SPTpol Bright AGN Light Curves

The South Pole Telescope (SPT) collaboration has recently embarked upon a campaign to monitor the brightness of a sample of active galactic nuclei (AGN), both in real time and in archival SPT data. The original design of the SPT was optimized for observations of the cosmic microwave background (CMB) at arc-minute and larger angular scales, and it has been used for this purpose for nearly twenty years, using three generations of CMB cameras. Recently it has been recognized that data from CMB experiments have the potential to be used for AGN monitoring. In this paper, we present the first public release of data from a full sample of SPT-monitored AGN, comprising 158 AGN light curves and associated data from the SPTpol camera, which was operational from 2012-2016. These light curves were created using observations from the SPTpol 500 deg$^{2}$ survey, in which the instrument was used to scan a 500 deg$^2$ patch of the sky several times per day with detectors sensitive to radiation in bands centered at 90 and 150 GHz. We provide a comprehensive description of the observations, the data processing methods, and the resulting light curve catalog. As an example of analyses that these data enable, we searched for a correlation between variability and spectral index, and we looked for ``bluer-when-brighter'' trends in the sample. Our analysis finds $> 10 σ$ correlation between fractional intrinsic variance and mean spectral index in the sample, but no significant evidence for bluer-when-brighter trends. The datasets from this study can be accessed through the SPT Treasury Record of AGN With Historical Activity and Time-Series or STRAWHAT catalog. This initial data release includes SPTpol light curves at 90 and 150 GHz, focusing on total intensity. In later updates, SPTpol polarization data and new observations from the SPT-3G instrument at 90, 150, and 220 GHz will be included.

Hood, J.C., II [Chicago U., KICP; Chicago U., Astr↗

The effect of jet–ejecta interaction on the viewing angle dependence of kilonova light curves

ABSTRACT The merger of two neutron stars produces an outflow of radioactive heavy nuclei. Within a second of merger, the central remnant is expected to also launch a relativistic jet, which shock-heats and disrupts a portion of the radioactive ejecta. Within a few hours, emission from the radioactive material gives rise to an ultraviolet, optical, and infrared transient (a kilonova). We use the endstates of a suite of 2D relativistic hydrodynamic simulations of jet–ejecta interaction as initial conditions for multidimensional Monte Carlo radiation transport simulations of the resulting viewing angle-dependent light curves and spectra starting at $1.5\, \mathrm{h}$ after merger. We find that on this time-scale, jet shock heating does not affect the kilonova emission for the jet parameters we survey. However, the jet disruption to the density structure of the ejecta does change the light curves. The jet carves a channel into the otherwise spheroidal ejecta, revealing the hot, inner regions. As seen from near (≲30°) the jet axis, the kilonova is brighter by a factor of a few and bluer. The strength of this effect depends on the jet parameters, since the light curves of more heavily disrupted ejecta are more strongly affected. The light curves and spectra are also more heavily modified in the ultraviolet than in the optical.

Klion, Hannah↗

Mapping Stellar Surfaces. II. An Interpretable Gaussian Process Model for Light Curves

The use of Gaussian processes (GPs) as models for astronomical time series data sets has recently become almost ubiquitous, given their ease of use and flexibility. In particular, GPs excel at marginalization over the stellar signal when the variability due to starspots is treated as a nuisance, as in exoplanet transit modeling. However, these effective models are less useful in cases where the starspot signal is of primary interest, since it is not obvious how the parameters of the GP relate to physical parameters like the spot size, contrast, and latitudinal distribution. Instead, it is common practice to explicitly model the effect of individual starspots on the light curve and attempt to infer their properties via optimization or posterior inference. Unfortunately, this process is ill-posed and often computationally intractable when applied to stars with more than a few spots and/or to ensembles of many stars. Here we derive a closed-form expression for a GP that describes the light curve of a rotating, evolving stellar surface conditioned on a given distribution of starspot sizes, contrasts, and latitudes. We demonstrate that this model is correctly calibrated, allowing one to robustly infer physical parameters of interest from one or more light curves, including the typical spot radii and latitudes. Our GP has far-ranging implications for understanding the variability and magnetic activity of stars from light curves and radial velocity measurements, as well as for modeling correlated noise in exoplanet searches. Our implementation is efficient, user-friendly, and open-source, available in the package starry-process.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The EBLM project – VIII. First results for M-dwarf mass, radius, and effective temperature measurements using CHEOPS light curves

ABSTRACT The accuracy of theoretical mass, radius, and effective temperature values for M-dwarf stars is an active topic of debate. Differences between observed and theoretical values have raised the possibility that current theoretical stellar structure and evolution models are inaccurate towards the low-mass end of the main sequence. To explore this issue, we use the CHEOPS satellite to obtain high-precision light curves of eclipsing binaries with low-mass stellar companions. We use these light curves combined with the spectroscopic orbit for the solar-type companion to measure the mass, radius, and effective temperature of the M-dwarf star. Here, we present the analysis of three eclipsing binaries. We use the pycheops data analysis software to fit the observed transit and eclipse events of each system. Two of our systems were also observed by the TESS satellite – we similarly analyse these light curves for comparison. We find consistent results between CHEOPS and TESS, presenting three stellar radii and two stellar effective temperature values of low-mass stellar objects. These initial results from our on-going observing programme with CHEOPS show that we can expect to have ∼24 new mass, radius, and effective temperature measurements for very low-mass stars within the next few years.

Swayne, M. I.↗

Optical variability of quasars with 20-yr photometric light curves

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 and 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.

79 ASTRONOMY AND ASTROPHYSICS↗

Millimeter Light Curves of Sagittarius A* Observed during the 2017 Event Horizon Telescope Campaign

The Event Horizon Telescope (EHT) observed the compact radio source, Sagittarius A* (Sgr A*), in the Galactic Center on 2017 April 5–11 in the 1.3 mm wavelength band. At the same time, interferometric array data from the Atacama Large Millimeter/submillimeter Array and the Submillimeter Array were collected, providing Sgr A* light curves simultaneous with the EHT observations. These data sets, complementing the EHT very long baseline interferometry, are characterized by a cadence and signal-to-noise ratio previously unattainable for Sgr A* at millimeter wavelengths, and they allow for the investigation of source variability on timescales as short as a minute. While most of the light curves correspond to a low variability state of Sgr A*, the April 11 observations follow an X-ray flare and exhibit strongly enhanced variability. All of the light curves are consistent with a red-noise process, with a power spectral density (PSD) slope measured to be between −2 and −3 on timescales between 1 minute and several hours. Our results indicate a steepening of the PSD slope for timescales shorter than 0.3 hr. The spectral energy distribution is flat at 220 GHz, and there are no time lags between the 213 and 229 GHz frequency bands, suggesting low optical depth for the event horizon scale source. We characterize Sgr A*’s variability, highlighting the different behavior observed just after the X-ray flare, and use Gaussian process modeling to extract a decorrelation timescale and a PSD slope. We also investigate the systematic calibration uncertainties by analyzing data from independent data reduction pipelines.

79 ASTRONOMY AND ASTROPHYSICS↗

SN 2020bvc: A Broad-line Type Ic Supernova with a Double-peaked Optical Light Curve and a Luminous X-Ray and Radio Counterpart

Here, we present optical, radio, and X-ray observations of SN 2020bvc (=ASASSN20bs; ZTF20aalxlis), a nearby (z = 0.0252; d = 114 Mpc) broad-lined (BL) Type Ic supernova (SN) and the first double-peaked Ic-BL discovered without a gamma-ray burst (GRB) trigger. Our observations show that SN 2020bvc shares several properties in common with the Ic-BL SN 2006aj, which was associated with the low-luminosity gamma-ray burst (LLGRB) 060218. First, the 10 GHz radio luminosity (L radio ≈ 10 37 erg s -1 ) is brighter than ordinary core-collapse SNe but fainter than LLGRB-SNe such as SN 1998bw (associated with LLGRB 980425). We model our VLA observations (spanning 13–43 d) as synchrotron emission from a mildly relativistic (v ≳ 0.3c) forward shock. Second, with Swift and Chandra we detect X-ray emission (L X ≈ 10 41 erg s -1 ) that is not naturally explained as inverse Compton emission or as part of the same synchrotron spectrum as the radio emission. Third, high-cadence (6×/night -1 ) data from the Zwicky Transient Facility (ZTF) shows a double-peaked optical light curve, the first peak from shock-cooling of extended low-mass material (mass M e < 10 -2 M ⊙ at radius R e > 10 12 cm) and the second peak from the radioactive decay of 56 Ni. SN 2020bvc is the first double-peaked Ic-BL SN discovered without a GRB trigger, so it is noteworthy that it shows X-ray and radio emission similar to LLGRB-SNe. For four of the five other nearby (z . 0.05) Ic-BL SNe with ZTF high-cadence data, we rule out a first peak like that seen in SN 2006aj and SN 2020bvc, i.e. that lasts ≈ 1 d and reaches a peak luminosity M ≈ -18. X-ray and radio follow-up observations of Ic-BL SNe with well-sampled early optical light curves will establish whether double-peaked optical light curves are indeed predictive of LLGRB-like X-ray and radio emission.

79 ASTRONOMY AND ASTROPHYSICS↗

Primordial Black Hole Triggered Type Ia Supernovae. I. Impact on Explosion Dynamics and Light Curves

Primordial black holes (PBHs) in the asteroid-mass window are compelling dark matter candidates, made plausible by the existence of black holes and by the variety of mechanisms of their production in the early Universe. If a PBH falls into a white dwarf (WD), the strong tidal forces can generate enough heat to trigger a thermonuclear runaway explosion, depending on the WD’s mass and the PBH’s orbital parameters. In this work, we investigate the WD explosion triggered by the passage of a PBH. We perform 2D simulations of the WD undergoing thermonuclear explosion in this scenario, with the predicted ignition site as a parameter assuming the deflagration–detonation transition model. We study the explosion dynamics, and predict the associated light curves and nucleosynthesis. We find that the model sequence predicts light curves which align with the Phillips relation (B max versus ΔM 15 ). Our models hint at a unifying approach in triggering Type Ia supernovae without involving two distinctive evolutionary tracks.

Dark matter↗

Actinide opacities for modelling the spectra and light curves of kilonovae

ABSTRACT We extend previous ab initio calculations of lanthanide opacities to include a complete set of actinide opacities for use in the modelling of kilonova (KN) light curves and spectra. Detailed, fine-structure line features are generated using the configuration-interaction approach. These actinide opacities display similar trends to those observed for lanthanide opacities, such as the lighter actinides producing higher opacity than the heavier ones for relevant conditions in the dynamical ejecta. A line-binned treatment is employed to pre-compute opacity tables for 14 actinide elements (89 ≤ Z ≤ 102) over a grid of relevant temperatures and densities. These tabular opacities will be made publicly available for general usage in KN modelling. We demonstrate the usefulness of these opacities in KN simulations by exploring the sensitivity of light curves and spectra to different actinide abundance distributions that are predicted by different nuclear theories, as well as to different choices of ejecta mass and velocity. We find very little sensitivity to the two considered distributions, indicating that opacities for actinides with Z ≥ 99 do not contribute strongly. On the other hand, a single actinide element, protactinium, is found to produce faint spectral features in the far-infrared at late times (5–7 d post merger). More generally, we find that the choice of ejecta mass and velocity have the most significant effect on KN emission for this study.

79 ASTRONOMY AND ASTROPHYSICS↗

Hubble Space Telescope Observations of GW170817: Complete Light Curves and the Properties of the Galaxy Merger of NGC 4993

We present the complete set of Hubble Space Telescope imaging of the binary neutron star merger GW170817 and its optical counterpart AT 2017gfo. Including deep template imaging in F814W, F110W, F140W, and F160W at 3.4 yr post-merger, we reanalyze the full light curve of AT 2017gfo across 12 bands from 5 to 1273 rest-frame days after merger. We obtain four new detections of the short γ-ray burst 170817A afterglow from 109 to 170 rest-frame days post-merger. These detections are consistent with the previously observed β = -0.6 spectral index in the afterglow light curve with no evidence for spectral evolution. We also analyze our limits in the context of kilonova afterglow or IR dust echo emission but find that our limits are not constraining for these models. We use the new data to construct deep optical and IR stacks, reaching limits of M = -6.3 to -4.6 mag, to analyze the local environment around AT 2017gfo and low surface brightness features in its host galaxy NGC 4993. We rule out the presence of any globular cluster at the position of AT 2017gfo to 2.3 × 10$^{4}$L$_{⊙}$, including those with the reddest V - H colors. Finally, we analyze the substructure of NGC 4993 in deep residual imaging and find shell features that extend up to 71."8 (14.2 kpc) from NGC 4993. The shells have a cumulative stellar mass of 6.3 × 10$^{8}$M$_{⊙}$, roughly 2% of NGC 4993, and mass-weighted ages of >3 Gyr. We conclude that it was unlikely that the GW170817 progenitor system formed in the galaxy merger.

79 ASTRONOMY AND ASTROPHYSICS↗

Kilonova light-curve interpolation with neural networks

Kilonovae are the electromagnetic transients created by the radioactive decay of freshly synthesized elements in the environment surrounding a neutron star merger. To study the fundamental physics in these complex environments, kilonova modeling requires, in part, the use of radiative transfer simulations. The microphysics involved in these simulations results in high computational cost, prompting the use of emulators for parameter inference applications. Utilizing a training set of 22 248 high-fidelity simulations (composed of 412 unique ejecta parameter combinations evaluated at 54 viewing angles), we use a neural network to efficiently train on existing radiative transfer simulations and predict light curves for new parameters in a fast and computationally efficient manner. Our neural network can generate millions of new light curves in under a minute. We discuss our emulator's degree of off-sample reliability and parameter inference of the AT2017gfo observational data. Finally, we discuss tension introduced by multiband inference in the parameter inference results, particularly with regard to the neural network's recovery of viewing angle. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗