Larry Denneau
ATLAS Co-PI and senior software engineer Larry Denneau was the chief software architect of the Pan-STARRS moving object processing system (MOPS) and adapted it to the ATLAS survey. MOPS is a software package that automatically identifies solar system objects (in particular hazardous asteroids) in the ATLAS and Pan-STARRS data streams.
Larry has been poking at computer keyboards since the early 80s and received his B.S.E.E. from the University of Arizona, whereupon he quickly escaped academia. His software career has spanned projects ranging from surface metrology for the semiconductor industry, medical scheduling, geophysical instrumentation, and a dot-com Internet startup that actually turned a profit. Now back in academia, Larry received a Ph.D. in astrophysics from Queen's University Belfast and has enthusiastically joined the effort to protect the earth from dangerous asteroids.
Sessions
From MPEC N12: "A new NEOCP candidate A11pl3Z was discovered by ATLAS Chile (W68) in four 30-second survey images taken on July 1 UT. Immediate follow-up and precovery observations by Q.-Z. Ye (I41) and S. Deen (W68, M22), including data from June, revealed a highly eccentric, hyperbolic orbit (e ~ 6). There are tentative reports of cometary activity from X09 (S. Deen), G37 (Q.-Z. Ye) and T14 (R. Weryk) with a marginal coma and a short 3" tail at a position angle 280 deg. Additional observations are strongly encouraged to better constrain the object's orbit and nature."
The era of Vera C. Rubin and NEO Surveyor and V=24 near-Earth object discoveries is nearly upon us. Observatories and archives are scrambling to find ways to squeeze even more performance out of their systems to meet the challenges of Rubin and Surveyor. Yet there is still a great deal of action brighter than V=24, as Rubin may not detect many small near-Earth asteroids when they are very close to the Earth. This regime is where the ATLAS survey lives.
Now with five observatories surveying 24/7 distributed globally, ATLAS has accelerated efforts to improve multi-observatory survey efficiencies and object detection, in some cases via real-time collaborations with other projects. In this talk, we present three such efforts with in ATLAS: a) real-time telescope scheduler optimized for NEO discovery; b) cross-telescope and cross-organizational detection linking of discovery tracklets, and c) participation in public archives for object recovery. We close with some guidance regarding the difficult problem of object precovery and the importance of deep knowledge regarding survey data in this process.