Enhancing the Data Production of Astronomical Surveys
Lead Research Organisation:
University of Southampton
Abstract
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Organisations
People |
ORCID iD |
Publications
Gandhi P
(2019)
Gaia Data Release 2 distances and peculiar velocities for Galactic black hole transients
in Monthly Notices of the Royal Astronomical Society
Johnson M
(2019)
Prospecting for periods with LSST - low-mass X-ray binaries as a test case
in Monthly Notices of the Royal Astronomical Society
Johnson M. A. C.
(2018)
Using the Provenance from Astronomical Workflows to Increase Processing Efficiency
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 |