Enhancing the Data Production of Astronomical Surveys

Lead Research Organisation: University of Southampton


Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.




10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509747/1 30/09/2016 29/09/2021
1807985 Studentship EP/N509747/1 30/09/2016 29/09/2019
Description I have quantified the performance of several potential observing strategies for the Large Synoptic Survey Telescope (LSST) with respect to Low Mass X-ray Binaries.
I demonstrated the use of provenance as a means of improving the processing efficiency of scientific workflows - contrary to the norm as recording provenance usually adds an initial overhead to the processing. I have identified ~2 million transient events within a set of calibration data for the Kepler Space telescope which include both newly discovered objects and previously known astronomical objects whose observations within this dataset predate their original discovery. I have investigated and quantitatively assessed the use of techniques such as brute force, simulated annealing and the hill climbing algorithm for improving the quality of astronomical data processing. I have developed an approach to be applied to workflows which analyse astronomical data in order to improve the quality of the data that they produce.
Exploitation Route Thee results from period studies and LSST can be extended to other periodic objects and can be used to inform decisions on the final LSST observing strategy when it is operational in ~2022. A tool is under development to facilitate the former. The research into using provenance as a means to improve processing efficiency will help reduce the computational overhead of recording it, making provenance recording more desirable for astronomical workflows. The approach and methods for improving data quality may be implemented by others within the astronomical community.
Sectors Digital/Communication/Information Technologies (including Software),Other

Description UK Involvement in LSST: Phase A
Amount £1,308,664 (GBP)
Funding ID ST/N002512/1 
Organisation Science and Technologies Facilities Council (STFC) 
Sector Public
Country United Kingdom
Start 06/2015 
End 03/2019