|
Award Abstract #0540369
Collaborative Research: DDDAS-TMRP: Real-Time Astronomy with a Rapid-Response Telescope Grid
| NSF Org: |
CNS
Division of Computer and Network Systems
|
|
|
| Initial Amendment Date: |
September 20, 2005 |
|
| Latest Amendment Date: |
September 30, 2008 |
|
| Award Number: |
0540369 |
|
| Award Instrument: |
Continuing grant |
|
| Program Manager: |
Krishna Kant
CNS Division of Computer and Network Systems
CSE Directorate for Computer & Information Science & Engineering
|
|
| Start Date: |
October 1, 2005 |
|
| Expires: |
September 30, 2009 (Estimated) |
|
| Awarded Amount to Date: |
$464613 |
|
| Investigator(s): |
Roy Williams roy@cacr.caltech.edu (Principal Investigator)
Stanislav Djorgovski (Co-Principal Investigator)
Shrinivas Kulkarni (Co-Principal Investigator)
|
|
| Sponsor: |
California Institute of Technology
1200 E California Blvd
PASADENA, CA 91125 626/395-6219
|
|
| NSF Program(s): |
ITR-DYNAMIC DATA DRIV APP SYS,
OFFICE OF MULTIDISCIPLINARY AC
|
|
| Field Application(s): |
0000912 Computer Science
|
|
| Program Reference Code(s): |
HPCC, 9218, 7569
|
|
| Program Element Code(s): |
7581, 1798, 1253
|
ABSTRACT
Exploration of transient sources represents one of the last frontiers in modern astrophysics. The development of a comprehensive understanding of a new event requires real-time observation with multiple instruments. Yet while telescope facilities continue to ramp up to unprecedented data rates, there has been no concerted effort to ensure real-time communications of astronomical events. A federated response must be enabled to push transient astrophysics ahead in the 21st century.
The activity undertaken in this project is a synergy of distributed computing with distributed sensors. Though set up by humans with pre-defined criteria, VOEventNet operates automatically and autonomously. The project will build an event factory to detect sky transients in near real time, and utilize novel machine-learning technology to distinguish scientifically relevant transients from false positives through synthesizing multiple observations. In this way, VOEventNet will enable an already active area of astrophysical research to flourish. The system that will be enable constitutes the unification of existing powerful resources to form a new, robust, competent production system that will generate a great deal of new science.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
Babu, G.J., Mahabal, A., Djorgovski, S.G., & Williams, R.. "Object Detection in Multi-Epoch Data," Statistical Methods, v.5, 2008, p. 299.
Bloom, J. S.; Starr, D. L.; Butler, N. R.; Nugent, P.; Rischard, M.; Eads, D.; Poznanski, D.. "Towards a real-time transient classification engine," Astronomische Nachrichten, v.329, 2008, p. 284.
Please report errors in award information by writing to: awardsearch@nsf.gov.
|
