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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Seeking Echoes of Circumstellar Disks in Kepler Light Curves

Light echoes of flares on active stars offer the opportunity for direct detection of circumstellar dust. We revisit the problem of identifying faint echoes in postflare light curves, focusing on debris disks from ongoing planet formation. Starting with simulations, we develop an algorithm for estimating the radial extent and total mass from disk echo profiles. We apply this algorithm to light curves from over 2100 stars observed by NASA’s Kepler mission, selected for multiple short-lived flares in either the long-cadence or short-cadence data sets. While flux uncertainties in light curves from individual stars preclude useful mass limits on circumstellar disks, catalog-averaged light curves yield constraints on disk mass that are comparable to estimates from known debris disks. The average mass in micron- to millimeter-sized dust around the Kepler stars cannot exceed 10% of an Earth mass in exo-Kuiper belts or 10% of a lunar mass in the terrestrial zone. We group stars according to IR excess, based on WISE W1–W3 color, as an indicator for the presence of circumstellar dust. The mass limits are greater for stars with strong IR excess, a hint that echoes are lurking not far beneath the noise in postflare light curves. With increased sensitivity, echo detection will let time-domain astronomy complement spectroscopic and direct-imaging studies in mapping how, when, and where planets form.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Neural ODEs for Light Curves: Classifying and Approximating Light Curves

Neural differential equations are a increasingly popular neural network framework. Neural ODEs remove discretizations that traditional layer based neural networks necessarily have. Neural ODEs are a continuous depth model that can trade precision and speed. I show that neural ODEs can estimate light curve time series using LSST Kaggle data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

A Six-year Image-subtraction Light Curve of SN 2010jl

SN 2010jl was a luminous Type IIn supernova (SN), detected in radio, optical, X-ray and hard X-rays. Here we report on its six-year R - and g -band light curves obtained using the Palomar Transient Factory. The light curve was generated using a pipeline based on the proper image-subtraction method and we discuss the algorithm performances. As noted before, the R -band light curve, up to about 300 days after maximum light is well described by a power-law decline with a power-law index of α ≈ -0.5. Between day 300 and day 2300 after maximum light, it is consistent with a power-law decline, with a power-law index of about α ≈ -3.4. Here, the longevity of the light curve suggests that the massive circumstellar material around the progenitor was ejected on timescales of at least tens of years prior to the progenitor explosion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The Swan: Data-driven Inference of Stellar Surface Gravities for Cool Stars from Photometric Light Curves

Stellar light curves are well known to encode physical stellar properties. Precise, automated, and computationally inexpensive methods to derive physical parameters from light curves are needed to cope with the large influx of these data from space-based missions such as Kepler and TESS. Here we present a new methodology that we call “The Swan,” a fast, generalizable, and effective approach for deriving stellar surface gravity (logg) for main-sequence, subgiant, and red giant stars from Kepler light curves using local linear regression on the full frequency content of Kepler long-cadence power spectra. With this inexpensive data-driven approach, we recover logg to a precision of ~0.02 dex for 13,822 stars with seismic logg values between 0.2 and 4.4 dex and ~0.11 dex for 4646 stars with Gaia-derived logg values between 2.3 and 4.6 dex. We further develop a signal-to-noise metric and find that granulation is difficult to detect in many cool main-sequence stars (T {sub eff} ≲ 5500 K), in particular K dwarfs. By combining our logg measurements with Gaia radii, we derive empirical masses for 4646 subgiant and main-sequence stars with a median precision of ~7%. Finally, we demonstrate that our method can be used to recover logg to a similar mean absolute deviation precision for a TESS baseline of 27 days. Our methodology can be readily applied to photometric time series observations to infer stellar surface gravities to high precision across evolutionary states.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Physics-driven Explosions of Stripped High-mass Stars: Synthetic Light Curves and Spectra of Stripped-envelope Supernovae with Broad Light Curves

Stripped-envelope supernovae (SESNe) represent a significant fraction of core-collapse supernovae, arising from massive stars that have shed their hydrogen and, in some cases, helium envelopes. The origins and explosion mechanisms of SESNe remain a topic of active investigation. In this work, we employ radiative-transfer simulations to model the light curves and spectra of a set of explosions of single, solar-metallicity, massive Wolf–Rayet stars with ejecta masses ranging from 4 to 11 M ⊙ , which were computed from a turbulence-aided and neutrino-driven explosion mechanism. We analyze these synthetic observables to explore the impact of varying ejecta mass and helium content on observable features. We find that the light curve shape of these progenitors with high ejecta masses is consistent with observed SESNe with broad light curves but not the peak luminosities. The commonly used analytic formula based on rising bolometric light curves overestimates the ejecta mass of these high-initial-mass progenitor explosions by a factor of up to 2.6. In contrast, the calibrated method by Haynie et al., which relies on late-time decay tails, reduces uncertainties to an average of 20% within the calibrated ejecta mass range. Spectroscopically, the He I 1.083 μm line remains prominent even in models with as little as 0.02 M ⊙ of helium. However, the strength of the optical He I lines is not directly proportional to the helium mass but instead depends on a complex interplay of factors such as the 56 Ni distribution, composition, and radiation field. Thus, producing realistic helium features requires detailed radiative transfer simulations for each new hydrodynamic model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

On the relation between active-region lifetimes and the autocorrelation function of light curves

ABSTRACT Rotational modulation of stellar light curves due to dark spots encloses information on spot properties and, thus, on magnetic activity. In particular, the decay of the autocorrelation function (ACF) of light curves is presumed to be linked to spot/active-region lifetimes, given that some coherence of the signal is expected throughout their lifetime. In the literature, an exponential decay has been adopted to describe the ACF. Here, we investigate the relation between the ACF and the active-region lifetimes. For this purpose, we produce artificial light curves of rotating spotted stars with different observation, stellar, and spot properties. We find that a linear decay and respective time-scale better represent the ACF than the exponential decay. We therefore adopt a linear decay. The spot/active-region time-scale inferred from the ACF is strongly restricted by the observation length of the light curves. For 1-yr light curves our results are consistent with no correlation between the inferred and the input time-scales. The ACF decay is also significantly affected by differential rotation and spot evolution: strong differential rotation and fast spot evolution contribute to a more severe underestimation of the active-region lifetimes. Nevertheless, in both circumstances the observed time-scale is still correlated with the input lifetimes. Therefore, our analysis suggests that the ACF decay can be used to obtain a lower limit of the active-region lifetimes for relatively long-term observations. However, strategies to avoid or flag targets with fast active-region evolution or displaying stable beating patterns associated with differential rotation should be employed.

Santos, A. R. G. (ORCID:0000000171956542)↗
DOE OSTI2021

Earth as a Proxy Exoplanet: Deconstructing and Reconstructing Spectrophotometric Light Curves

Point-source spectrophotometric (single-point) light curves of Earth-like planets contain a surprising amount of information about the spatial features of those worlds. Spatially resolving these light curves is important for assessing time-varying surface features and the existence of an atmosphere, which in turn is critical to life on Earth and significant for determining habitability on exoplanets. Given that Earth is the only celestial body confirmed to harbor life, treating it as a proxy exoplanet by analyzing time-resolved spectral images provides a benchmark in the search for habitable exoplanets. The Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) provides such an opportunity, with observations of ∼5000 full-disk sunlit Earth images each year at 10 wavelengths with high temporal frequency. We disk-integrate these spectral images to create single-point light curves and decompose them into principal components (PCs). Using machine-learning techniques to relate the PCs to six preselected spatial features, we find that the first and fourth PCs of the single-point light curves, contributing ∼83.23% of the light-curve variability, contain information about low and high clouds, respectively. Surface information relevant to the contrast between land and ocean reflectance is contained in the second PC, while individual land subtypes are not easily distinguishable (<0.1% total light-curve variation). We build an Earth model by systematically altering the spatial features to derive causal relationships to the PCs. This model can serve as a baseline for analyzing Earth-like exoplanets and guide wavelength selection and sampling strategies for future observations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Core-Collapse Supernovae: From Neutrino-Driven 1D Explosions to Light Curves and Spectra.

We present broadband light curves and spectra for a suite of core-collapse supernova models computed self-consistently in spherical symmetry within the PUSH framework. We use the open source LANL code SuperNU to compute light curves and spectra. This data release covers only the electromagnetic counterparts of the models, not the models themselves, which were produced at North Carolina State University and used with permission. We follow spectra from the photospheric to the nebular phase. The data is released as machine-readable ASCII tables, with luminous flux tabulated by wavelength (or band for the broadband light curves) vs. time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models

Abstract We present 307 type Ia supernova (SN) light curves from the first 4 yr of the Transiting Exoplanet Survey Satellite mission. We use this sample to characterize the shapes of the early-time light curves, measure the rise times from first light to peak, and search for companion star interactions. Using simulations, we show that light curves must have noise <10% of the peak flux to avoid biases in the early-time light-curve shape, restricting our quantitative analysis to 74 light curves. We find that the mean power-law index t β 1 of the early-time light curves isβ 1 = 1.93 ± 0.57, and the mean rise time to peak is 15.7 ± 3.5 days. The underlying population distribution forβ 1 may instead consist of a Gaussian component with mean 2.29, width 0.34, and a long tail extending to values less than 1.0. We find that the data can rarely distinguish between models with and without companion interaction models. Nevertheless, we find three high-quality light curves that tentatively prefer the addition of a companion interaction model, but the statistical evidence for the companion interactions is not robust. We also find two SNe that disfavor the addition of a companion interaction model to a curved power-law model. Taking the 74 SNe together, we calculate 3σupper limits on the presence of companion signatures to control for orientation effects that can hide companions in individual light curves. Our results rule out common progenitor systems with companions having Roche lobe radii >31R ⊙ (separations >5.7 × 10 12 cm, 99.9% confidence level) and disfavor companions having Roche lobe radii >10R ⊙ (separations >1.9 × 10 12 cm, 95% confidence level). Lastly, we discuss the implications of our results for the intrinsic fraction of single degenerate progenitor systems.

Astronomy & Astrophysics↗
DOE OSTI2022

The Pantheon+ Analysis: The Full Data Set and Light-curve Release

Abstract Here we present 1701 light curves of 1550 unique, spectroscopically confirmed Type Ia supernovae (SNe Ia) that will be used to infer cosmological parameters as part of the Pantheon+ SN analysis and the Supernovae and H 0 for the Equation of State of dark energy distance-ladder analysis. This effort is one part of a series of works that perform an extensive review of redshifts, peculiar velocities, photometric calibration, and intrinsic-scatter models of SNe Ia. The total number of light curves, which are compiled across 18 different surveys, is a significant increase from the first Pantheon analysis (1048 SNe), particularly at low redshift ( z ). Furthermore, unlike in the Pantheon analysis, we include light curves for SNe with z < 0.01 such that SN systematic covariance can be included in a joint measurement of the Hubble constant ( H 0 ) and the dark energy equation-of-state parameter ( w ). We use the large sample to compare properties of 151 SNe Ia observed by multiple surveys and 12 pairs/triplets of “SN siblings”—SNe found in the same host galaxy. Distance measurements, application of bias corrections, and inference of cosmological parameters are discussed in the companion paper by Brout et al., and the determination of H 0 is discussed by Riess et al. These analyses will measure w with ∼3% precision and H 0 with ∼1 km s −1 Mpc −1 precision.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

RRab variables with identical light-curve shapes at different pulsation periods

In this paper, we report on the detection of RRab stars with quasi-identical-shape light curves but period differences as large as 0.05–0.21 d using the Galactic bulge data of the OGLE-IV survey. We have examined stars with shorter periods than the Oosterhoff I ridge of the bulge. These stars generally have smaller amplitudes and larger Fourier phase-differences than the typical bulge RRab stars have at the same period. Many of these ‘anomalous’ stars have good-quality light curves without any sign of the Blazhko modulation. Examining their Fourier parameters revealed that several of these stars show very similar light curve to the typical bulge RR Lyrae. We found hundreds of quasi-identical-shape light-curve pairs with different periods between the ‘anomalous’- and the ‘normal’-position RRab stars based on the OGLE I-band data. The OGLE V-band, and the archive VVV and MACHO surveys K s -, b- and r -band data of these stars were also checked for light-curve-shape similarity. Finally, 149 pairs with identical-shape light curves in each available photometric band were identified. Calculating the physical properties of the variables using empirical formulae, on average, −0.5 dex, −0.13 mag, 0.67, and 165 K differences between the [Fe/H], M V , R/R ⊙ , and T eff values of the members of the pairs are derived, being the short-period stars less metal-poor, fainter, smaller, and hotter than the long-period variables. To explain the existence of variables with different physical properties and pulsation periods but with identical-shape light curves is a challenging task for modelling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Photometric Classification of Early-time Supernova Light Curves with SCONE

Abstract In this work, we present classification results on early supernova light curves from SCONE, a photometric classifier that uses convolutional neural networks to categorize supernovae (SNe) by type using light-curve data. SCONE is able to identify SN types from light curves at any stage, from the night of initial alert to the end of their lifetimes. Simulated LSST SNe light curves were truncated at 0, 5, 15, 25, and 50 days after the trigger date and used to train Gaussian processes in wavelength and time space to produce wavelength–time heatmaps. SCONE uses these heatmaps to perform six-way classification between SN types Ia, II, Ibc, Ia-91bg, Iax, and SLSN-I. SCONE is able to perform classification with or without redshift, but we show that incorporating redshift information improves performance at each epoch. SCONE achieved 75% overall accuracy at the date of trigger (60% without redshift), and 89% accuracy 50 days after trigger (82% without redshift). SCONE was also tested on bright subsets of SNe ( r < 20 mag) and produced 91% accuracy at the date of trigger (83% without redshift) and 95% five days after trigger (94.7% without redshift). SCONE is the first application of convolutional neural networks to the early-time photometric transient classification problem. All of the data processing and model code developed for this paper can be found in the SCONE software package 1 1 github.com/helenqu/scone located at github.com/helenqu/scone (Qu 2021).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

First Cosmology Results Using Type Ia Supernovae from the Dark Energy Survey: Photometric Pipeline and Light-curve Data Release

We present griz light curves of 251 SNe Ia from the first 3 years of the Dark Energy Survey Supernova Program’s (DES-SN) spectroscopically classified sample. The photometric pipeline described in this paper produces the calibrated fluxes and associated uncertainties used in the cosmological parameter analysis by employing a scene modeling approach that simultaneously models a variable transient flux and temporally constant host galaxy. We inject artificial point sources onto DECam images to test the accuracy of our photometric method. Upon comparison of input and measured artificial supernova fluxes, we find that flux biases peak at 3 mmag. Here, we require corrections to our photometric uncertainties as a function of host galaxy surface brightness at the transient location, similar to that seen by the DES Difference Imaging Pipeline used to discover transients. The public release of the light curves can be found at https://des.ncsa.illinois.edu/releases/sn.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Evidence for a luminosity–decay correlation in GRB GeV light curves

ABSTRACT Correlations between intrinsic properties of gamma-ray burst (GRB) light curves provide clues to the nature of the central engine, the jet, and a possible means to standardize GRBs for cosmological use. Here, we report on the discovery of a correlation between the intrinsic early-time luminosity, LG,10 s, measured at rest frame 10 s, and the average decay rate measured from rest frame 10 s onward, $\alpha _{\mathrm{G,avg\gt 10\, s}}$, in a sample of 13 Fermi Large Area Telescope long GRB light curves. We note that our selection criteria, in particular the requirement for a redshift to construct luminosity light curves, naturally limits our sample to energetic GRBs. A Spearman’s rank correlation gives a coefficient of –0.74, corresponding to a confidence level of 99.6 per cent, indicating that brighter afterglows decay faster than less luminous ones. Assuming a linear relation with log(LG,10s), we find $\alpha _{\mathrm{G,avg\gt 10\, s}}$$= -0.31_{-0.09}^{+0.12}\log ($LG,10s$) + 14.43_{-5.97}^{+4.55}$. The slope of −0.31 is consistent at 1σ with previously identified correlations in the optical/ultraviolet and X-ray light curves. We speculate that differences in the rate at which energy is released by the central engine or differences in observer viewing angle may be responsible for the correlation.

Hinds, K. R. (ORCID:000000020129806X)↗
DOE OSTI2018

Robust Period Estimation Using Mutual Information for Multiband Light Curves in the Synoptic Survey Era

The Large Synoptic Survey Telescope (LSST) will produce an unprecedented amount of light curves using six optical bands. Robust and efficient methods that can aggregate data from multidimensional sparsely sampled time-series are needed. Here, we present a new method for light curve period estimation based on quadratic mutual information (QMI). The presented method does not assume a particular model for the light curve nor its underlying probability density and it is robust to non-Gaussian noise and outliers. By combining the QMI from several bands the true period can be estimated even when no single-band QMI yields the period. Period recovery performance as a function of average magnitude and sample size is measured using 30,000 synthetic multiband light curves of RR Lyrae and Cepheid variables generated by the LSST Operations and Catalog simulators. The results show that aggregating information from several bands is highly beneficial in LSST sparsely sampled time-series, obtaining an absolute increase in period recovery rate up to 50%. We also show that the QMI is more robust to noise and light curve length (sample size) than the multiband generalizations of the Lomb–Scargle and AoV periodograms, recovering the true period in 10%–30% more cases than its competitors. A python package with efficient Cython implementations of the QMI and other methods is provided.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

The Kepler Light Curves of AGN: A Detailed Analysis

Here, we present a comprehensive analysis of 21 light curves of Type 1 active galactic nuclei (AGN) from the Kepler spacecraft. First, we describe the necessity and development of a customized pipeline for treating Kepler data of stochastically variable sources like AGN. We then present the light curves, power spectral density functions (PSDs), and flux histograms. The light curves display an astonishing variety of behaviors, many of which would not be detected in ground-based studies, including switching between distinct flux levels. Six objects exhibit PSD flattening at characteristic timescales that roughly correlate with black hole mass. These timescales are consistent with orbital timescales or free-fall accretion timescales. We check for correlations of variability and high-frequency PSD slope with accretion rate, black hole mass, redshift, and luminosity. We find that bolometric luminosity is anticorrelated with both variability and steepness of the PSD slope. We do not find evidence of the linear rms–flux relationships or lognormal flux distributions found in X-ray AGN light curves, indicating that reprocessing is not a significant contributor to optical variability at the 0.1%–10% level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

BLADE: An Automated Framework for Classifying Light Curves from the Center for Near-Earth Object Studies Fireball Database

Fireballs (bolides) are high-energy luminous phenomena produced when meteoroids and small asteroids enter Earth’s atmosphere at hypersonic speeds, often resulting in fragmentation or complete disintegration accompanied by significant energy release. The resulting bolide light curves capture temporal brightness variations as these objects traverse increasingly dense atmospheric layers, providing essential information on meteoroid entry dynamics, fragmentation behavior, and atmospheric energy deposition processes. The Center for Near-Earth Object Studies’ (CNEOS) continuously expanding fireball database offers a globally comprehensive archive of bolide events, including light curves and associated metadata. Events associated with infrasound detections allow direct correlations between acoustic signatures and light curve features, therefore enabling detailed analyses of fragmentation dynamics and energy deposition. Here, we introduce Bolide Light-curve Analysis and Discrimination Explorer (BLADE), a robust and high-fidelity framework specifically designed to analyze bolide light curves for objects detected from space. BLADE incorporates a processing pipeline integrating Savitzky–Golay filtering, prominence-based peak detection, and gradient analysis, enabling systematic identification and classification of fragmentation events and their associated energy release characteristics. Preliminary results demonstrate that BLADE reliably distinguishes distinct bolide behaviors, providing an objective, scalable methodology for characterization and analysis of large bolide light curve data sets. This foundational work establishes a novel pathway for advanced bolide research, with promising applications in planetary defense and global atmospheric monitoring. Future research should adopt an integrative approach combining CNEOS optical data with complementary infrasound measurements, further clarifying relationships between bolide energy deposition and acoustic signatures, thus refining our understanding of meteoroid and asteroid atmospheric entry processes.

Asteroids↗
DOE OSTI2021

Early-time Light Curves of Type Ia Supernovae Observed with TESS

We present the early-time light curves of Type Ia supernovae (SNe Ia) observed in the first six sectors of Transiting Exoplanet Survey Satellite (TESS) data. Ten of these SNe were discovered by ASAS-SN, seven by ATLAS, six by ZTF, and one by Gaia. For nine of these objects with sufficient dynamic range (>3.0 mag from detection to peak), we fit power-law models and searched for signatures of companion stars. We found a diversity of early-time light-curve shapes, although most of our sources are consistent with fireball models where the flux increases as ∝t 2 . Three SNe displayed a flatter rise with flux ∝t. We did not find any obvious evidence for additional structures, such as multiple power-law components, in the early rising light curves. For assumptions about the SN properties and the observer viewing angle (ejecta mass of 1.4 M⊙, expansion velocity of 10 4 km s –1 , opacity of 0.2 cm 2 g –1 , and viewing angle of 45°) and a further assumption that any companion stars would be in Roche lobe overflow, it is possible to place upper limits on the radii of any companion stars. Six of the nine SNe had complete coverage of the early-time light curves, and we placed upper limits on the radii of companion stars of ≲32 R ⊙ for these SNe, ≲20 R ⊙ for five of the six, and ≲4 R ⊙ for two of the six. The small sample size did not allow us to put limits on the occurrence rate of companion stars in the progenitors of SNe Ia. However, we expect that TESS observed enough SNe in its two-year primary mission (26 sectors) to either detect the signature of a large companion (R > 20 R ⊙ ) or constrain the occurrence rate of such systems, at least for the fiducial SN properties adopted here. Here, we also show that TESS is capable of detecting emission from a 1 R ⊙ companion for an SN Ia within 50 Mpc and has a reasonable chance of doing so after about six years.

79 ASTRONOMY AND ASTROPHYSICS↗