“Creating the Data Reduction Software Machinery for the Big Data Age”
A star observed at different parallactic and zenith angles may appear slightly elongated in the zenith direction, but this is due to differential Chromatic refraction (DCR). Correcting for DCR we can not only improve the image quality but increase the spectral resolution of the image
DIRAC’s Astronomical Software Group leads the development of data processing pipelines spanning the gamut of astronomical data processing, including:
- Image reduction of gigapixel mosaic cameras
- Algorithms to detect and characterize astronomical sources on large images
- Codes to build (infer) deep reference images of the sky given hundreds of observations in varying conditions
- Creation of clean difference images to detect changes in the sky and enable time domain astronomy
- Machine learning driven algorithms to distinguish true detections from false positives
- Codes capable of linking together observations of moving objects given >10^20 possible combinations
- Real-time event processing systems capable of filtering and distributing tens of millions of time domain events to hundreds of users, each night.
Our group leads the development of the time domain (“prompt data products”) pipelines for the Large Synoptic Survey Telescope, as well as the real-time alert distribution system for the Zwicky Transient Facility. Codes developed by DIRAC members have been successfully used for research with data from a number of prior surveys including the Sloan Digital Sky Survey, Pan-STARRS PS1, and Palomar Transient Facility.
Core Team
- Faculty: Eric Bellm
- DIRAC Fellows: Krzysztof Findeisen, Chris Morrison, Russell Owen, John Parejko, Meredith Rawls, Ian Sullivan
- Graduate Students: Joachim Moeyens, Chris Suberlak