We have conducted a detailed simulation of the Large Synoptic Survey Telescope (LSST) in order to understand the system's ability to link detections of asteroids within and across nights in order to populate a catalog of asteroid orbits. We show that LSST, using its baseline survey cadence, should be able to successfully link and catalog asteroids. In our simulation of a single monthly observing cycle, LSST produced 66 million candidate detections of main belt asteroids (MBAs) and near-Earth objects (NEOs), of which 77% were spurious detections related to detector noise or image processing. Using the Moving Object Processing System (MOPS, Denneau et al. 2013, PASP 125, p. 357), we were able to assemble single-night “tracklets” with negligible losses, but a purity of only 43%. The next stage of linking led to three-night orbits with data sets no more than 12 days in length, and it is at this stage that the false detections are readily removed from the data stream. Main-belt linkages were essentially complete and 99.8% pure. Similarly, only 0.02% of linked detections involving NEOs were spurious. On the other hand, NEO linking was 93.6% complete, indicating that 6.4% of potentially findable NEOs were not successfully linked. We believe that this rate can be improved with careful tuning of the MOPS linking algorithms. The NEO catalog was affected by main-belt confusion so that mis-linked MBAs appeared as NEOs, and many correctly linked MBAs were consistent with NEO orbits. We show that these cases arise primarily from MBAs detected at lower solar elongations and we postulate that this is an artifact of a one month simulation that will be readily resolved by surveying over many months.


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    Titel :

    Linking asteroid detections from the large synoptic survey telescope


    Beteiligte:
    Chesley, Steven R. (Autor:in) / Veres, Peter (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    01.03.2018


    Format / Umfang :

    2814824 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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