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Register a new userA New Blind Asteroid Detection Scheme
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As astronomical photometric surveys continue to tile the sky repeatedly, the potential to pushdetection thresholds to fainter limits increases; however, traditional digital-tracking methods cannotachieve this efficiently beyond time scales where motion is approximately linear. In this paper weprototype an optimal detection scheme that samples under a user defined prior on a parameterizationof the motion space, maps these sampled trajectories to the data space, and computes an optimalsignal-matched filter for computing the signal to noise ratio of trial trajectories. We demonstrate thecapability of this method on a small test data set from the Dark Energy Camera. We recover themajority of asteroids expected to appear and also discover hundreds of new asteroids with only a fewhours of observations. We conclude by exploring the potential for extending this scheme to larger datasets that cover larger areas of the sky over longer time baselines.
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We present the Signal Detection using Random-Forest Algorithm (SIDRA). SIDRA is a detection and classification algorithm based on the Machine Learning technique (Random Forest). The goal of this paper is to show the power of SIDRA for quick and accurate signal detection and classification. We first diagnose the power of the method with simulated light curves and try it on a subset of the Kepler space mission catalogue. We use five classes of simulated light curves (CONSTANT, TRANSIT, VARIABLE, MLENS and EB for constant light curves, transiting exoplanet, variable, microlensing events and eclipsing binaries, respectively) to analyse the power of the method. The algorithm uses four features in order to classify the light curves. The training sample contains 5000 light curves (1000 from each class) and 50000 random light curves for testing. The total SIDRA success ratio is $geq 90%$. Furthermore, the success ratio reaches 95 - 100$%$ for the CONSTANT, VARIABLE, EB, and MLENS classes and 92$%$ for the TRANSIT class with a decision probability of 60$%$. Because the TRANSIT class is the one which fails the most, we run a simultaneous fit using SIDRA and a Box Least Square (BLS) based algorithm for searching for transiting exoplanets. As a result, our algorithm detects 7.5$%$ more planets than a classic BLS algorithm, with better results for lower signal-to-noise light curves. SIDRA succeeds to catch 98$%$ of the planet candidates in the Kepler sample and fails for 7$%$ of the false alarms subset. SIDRA promises to be useful for developing a detection algorithm and/or classifier for large photometric surveys such as TESS and PLATO exoplanet future space missions.
Several chemical networks have been developed to study warm (exo)planetary atmospheres. The kinetics of the reactions related to the methanol chemistry included in these schemes have been questioned. The goal of this paper is to update the methanol chemistry for such chemical networks thanks to recent publications in the combustion literature. We aim also at studying the consequences of this update on the atmospheric compositions of (exo)planetary atmospheres and brown dwarfs. We have performed an extensive review of combustion experimental studies and revisited the sub-mechanism describing methanol combustion in the scheme of Venot et al. (2012, A&A 624, A58). The updated scheme involves 108 species linked by a total of 1906 reactions. We have then applied our 1D kinetic model with this new scheme to several case studies (HD 209458b, HD 189733b, GJ 436b, GJ 1214b, ULAS J1335+11, Uranus, Neptune), and compared the results obtained with those obtained with the former scheme. The update of the scheme has a negligible impact on hot Jupiters atmospheres. However, the atmospheric composition of warm Neptunes and brown dwarfs is modified sufficiently to impact observational spectra in the wavelength range JWST will operate. Concerning Uranus and Neptune, the update of the chemical scheme modifies the abundance of CO and thus impacts the deep oxygen abundance required to reproduce the observational data. For future 3D kinetics models, we also derived a reduced scheme containing 44 species and 582 reactions. Chemical schemes should be regularly updated in order to maintain a high level of reliability on the results of kinetic models and be able to improve our knowledge on planetary formation.
We have carried out simulations to predict the performance of a new space-based telescopic survey operating at thermal infrared wavelengths that seeks to discover and characterize a large fraction of the potentially hazardous near-Earth asteroid (NEA) population. Two potential architectures for the survey were considered: one located at the Earth-Sun L1 Lagrange point, and one in a Venus-trailing orbit. A sample cadence was formulated and tested, allowing for the self-follow-up necessary for objects discovered in the daytime sky on Earth. Synthetic populations of NEAs with sizes >=140 m in effective spherical diameter were simulated using recent determinations of their physical and orbital properties. Estimates of the instrumental sensitivity, integration times, and slew speeds were included for both architectures assuming the properties of new large-format 10 um detector arrays capable of operating at ~35 K. Our simulation included the creation of a preliminary version of a moving object processing pipeline suitable for operating on the trial cadence. We tested this pipeline on a simulated sky populated with astrophysical sources such as stars and galaxies extrapolated from Spitzer and WISE data, the catalog of known minor planets (including Main Belt asteroids, comets, Jovian Trojans, etc.), and the synthetic NEA model. Trial orbits were computed for simulated position-time pairs extracted from the synthetic surveys to verify that the tested cadence would result in orbits suitable for recovering objects at a later time. Our results indicate that the Earth-Sun L1 and Venus-trailing surveys achieve similar levels of integral completeness for potentially hazardous asteroids larger than 140 m; placing the telescope in an interior orbit does not yield an improvement in discovery rates. This work serves as a necessary first step for the detailed planning of a next-generation NEA survey.
Small near-Earth asteroids (>20 meters) are interesting because they are progenitors for meteorites in our terrestrial collection. Crucial to our understanding of the effectiveness of our atmosphere in filtering low-strength impactors is the physical characteristics of these small near-Earth asteroids (NEAs). In the past, characterization of small NEAs has been a challenge because of the difficulty in detecting them prior to close Earth flyby. In this study we physically characterized the 2-meter diameter near-Earth asteroid 2015 TC25 using ground-based optical, near-infrared and radar assets during a close flyby of the Earth (distance 69,000 miles) in Oct. 2015. Our observations suggest that its surface composition is similar to aubrites, a rare class of high albedo differentiated meteorites. Aubrites make up only 0.14 % of all know meteorites in our terrestrial meteorite collection. 2015 TC25 is also a very fast rotator with a rotation period of 133 seconds. We compared spectral and dynamical properties of 2015 TC25 and found the best candidate source body in the inner main belt to be the 70-km diameter E-type asteroid (44) Nysa. We attribute difference in spectral slope between the two objects to the lack of regolith on the surface of 2015 TC25. Using the albedo of E-type asteroids (50-60%) we refine the diameter of 2015 TC25 to 2-meters making it one of the smallest NEA ever to be characterized.
Orbit-determination programs find the orbit solution that best fits a set of observations by minimizing the RMS of the residuals of the fit. For near-Earth asteroids, the uncertainty of the orbit solution may be compatible with trajectories that impact Earth. This paper shows how incorporating the impact condition as an observation in the orbit-determination process results in a robust technique for finding the regions in parameter space leading to impacts. The impact pseudo-observation residuals are the b-plane coordinates at the time of close approach and the uncertainty is set to a fraction of the Earth radius. The extended orbit-determination filter converges naturally to an impacting solution if allowed by the observations. The uncertainty of the resulting orbit provides an excellent geometric representation of the virtual impactor. As a result, the impact probability can be efficiently estimated by exploring this region in parameter space using importance sampling. The proposed technique can systematically handle a large number of estimated parameters, account for nongravitational forces, deal with nonlinearities, and correct for non-Gaussian initial uncertainty distributions. The algorithm has been implemented into a new impact monitoring system at JPL called Sentry-II, which is undergoing extensive testing. The main advantages of Sentry-II over JPLs currently operating impact monitoring system Sentry are that Sentry-II can systematically process orbits perturbed by nongravitational forces and that it is generally more robust when dealing with pathological cases. The runtimes and completeness of both systems are comparable, with the impact probability of Sentry-II for 99% completeness being $3times10^{-7}$.
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