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Dennis Crake

Publications and source records attributed to Dennis Crake.

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Optical monitoring of the Didymos-Dimorphos asteroid system with the Danish telescope around the DART mission impact

The NASA's Double-Asteroid Redirection Test (DART) was a unique planetary defence and technology test mission, the first of its kind. The main spacecraft of the DART mission impacted the target asteroid Dimorphos, a small moon orbiting asteroid (65803) Didymos, on 2022 September 26. The impact brought up a mass of ejecta which, together with the direct momentum transfer from the collision, caused an orbital period change of 33 +/- 1 minutes, as measured by ground-based observations. We report here the outcome of the optical monitoring campaign of the Didymos system from the Danish 1.54 m telescope at La Silla around the time of impact. The observations contributed to the determination of the changes in the orbital parameters of the Didymos-Dimorphos system, as reported by arXiv:2303.02077, but in this paper we focus on the ejecta produced by the DART impact. We present photometric measurements from which we remove the contribution from the Didymos-Dimorphos system using a H-G photometric model. Using two photometric apertures we determine the fading rate of the ejecta to be 0.115 +/- 0.003 mag/d (in a 2" aperture) and 0.086 +/- 0.003 mag/d (5") over the first week post-impact. After about 8 days post-impact we note the fading slows down to 0.057 +/- 0.003 mag/d (2" aperture) and 0.068 +/- 0.002 mag/d (5"). We include deep-stacked images of the system to illustrate the ejecta evolution during the first 18 days, noting the emergence of dust tails formed from ejecta pushed in the anti-solar direction, and measuring the extent of the particles ejected sunward to be at least 4000 km.

astro-ph.EP

A method for finding anomalous astronomical light curves and their analogs

Our understanding of the Universe has profited from deliberate, targeted studies of known phenomena, as well as from serendipitous, unexpected discoveries, such as the discovery of a complex variability pattern in the direction of KIC 8462852 (Boyajian's star). Upcoming surveys, such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), will explore the parameter space of astrophysical transients at all time scales, and offer the opportunity to discover even more extreme examples of unexpected phenomena. We investigate strategies to identify novel objects and to contextualize them within large time-series data sets in order to facilitate the discovery of new classes of objects, as well as the physical interpretation of their anomalous nature. We develop a method that combines tree-based and manifold-learning algorithms for anomaly detection in order to perform two tasks: 1) identify and rank anomalous objects in a time-domain dataset; and 2) group those anomalies according to their similarity in order to identify analogs. We achieve the latter by combining an anomaly score from a tree-based method with a dimensionality manifold-learning reduction strategy. Clustering in the reduced space allows for the successful identification of anomalies and analogs. We also assess the impact of pre-processing and feature engineering schemes and investigate the astrophysical nature of the objects that our models identify as anomalous by augmenting the Kepler data with Gaia color and luminosity information. We find that multiple models, used in combination, are a promising strategy to identify novel light curves and light curve families.

astro-ph.SR