Gaia-CU9 2019-2024 (Bristol element)
Lead Research Organisation:
University of Bristol
Department Name: Physics
Abstract
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.
Planned Impact
While the primary motivation for Gaia is to revolutionise our understanding of the Universe, Gaia is also a software and technology mission. Gaia UK technology development has two aspects. Industrial developments, for example of new classes of CCDs, ESA-funded at e2v, are already proving of wider importance, have earned the UK the Euclid contract, and are generating other new international markets. Precision control systems, and on-board real-time image processing systems (Astrium Stevenage) are intended to be applied much more widely. There are many ESA-UK industry-UK academic partnerships built on Gaia. The first Gaia data releases have underpinned significant outreach activities. The Gaia data are the basis for a range of deep learning investigations, and are being used in PhD training programmes, for instance the STFC-funded CDT network in Cambridge.
The majority of development, however, involves fast and complex processing of large data volumes, and the development of tools to allow fast public access to huge and heavily-structured data sets. This naturally builds on and expands the Big Data and Virtual Observatory developments of late. The Cambridge developments in very large database systems (Spark/Hadoop) have been adopted mission-wide, illustrating one more area of technical leadership. Gaia is the next "big beast" in data volumes, with Gaia learning experience showing applications to astronomy (Euclid/PLATO) and wider implications for science and aspects of the digital economy. Big Data problems generically involve gathering subsets of the data for further exploration and visualising those data in some fashion. The techniques already in use in TOPCAT provide some important software approaches, and the developments to be driven by this work will be applicable in other fields, for example visualising remote sensing data monitoring crop rotation, relevant to areas such as the STFC Food network.
The majority of development, however, involves fast and complex processing of large data volumes, and the development of tools to allow fast public access to huge and heavily-structured data sets. This naturally builds on and expands the Big Data and Virtual Observatory developments of late. The Cambridge developments in very large database systems (Spark/Hadoop) have been adopted mission-wide, illustrating one more area of technical leadership. Gaia is the next "big beast" in data volumes, with Gaia learning experience showing applications to astronomy (Euclid/PLATO) and wider implications for science and aspects of the digital economy. Big Data problems generically involve gathering subsets of the data for further exploration and visualising those data in some fashion. The techniques already in use in TOPCAT provide some important software approaches, and the developments to be driven by this work will be applicable in other fields, for example visualising remote sensing data monitoring crop rotation, relevant to areas such as the STFC Food network.
Publications
A. V. Smith Castelli
(2024)
The S-PLUS Fornax Project (S+FP): A first 12-band glimpse of the Fornax galaxy cluster
A. V. Smith Castelli
(2024)
The S-PLUS Fornax Project (S+FP): A first 12-band glimpse of the Fornax galaxy cluster
Blomme R
(2023)
Gaia Data Release 3 Hot-star radial velocities
in Astronomy & Astrophysics
Blomme R
(2022)
Gaia Data Release 3: Hot-star radial velocities
Carnerero M
(2022)
Gaia Data Release 3: The first Gaia catalogue of variable AGN
Carnerero M
(2023)
Gaia Data Release 3 The first Gaia catalogue of variable AGN
in Astronomy & Astrophysics
Cecconi B
(2022)
JSON Implementation of Time-Frequency Radio Catalogues: TFCat
Collaboration G
(2019)
VizieR Online Data Catalog: Gaia DR2. Variable stars in CMD (Gaia Collaboration+, 2019)
in VizieR Online Data Catalog
Collaboration G
(2020)
Gaia Early Data Release 3: Acceleration of the solar system from Gaia astrometry
in arXiv e-prints
Collaboration G
(2020)
Gaia Early Data Release 3: Structure and properties of the Magellanic Clouds
in arXiv e-prints
Collaboration G
(2020)
Gaia Early Data Release 3: The Gaia Catalogue of Nearby Stars
in arXiv e-prints
De Angeli F
(2023)
Gaia Data Release 3 Processing and validation of BP/RP low-resolution spectral data
in Astronomy & Astrophysics
Delchambre L
(2023)
Gaia Data Release 3 Apsis. III. Non-stellar content and source classification
in Astronomy & Astrophysics
Eyer L
(2023)
Gaia Data Release 3 Summary of the variability processing and analysis
in Astronomy & Astrophysics
Frémat Y
(2023)
Gaia Data Release 3 Properties of the line-broadening parameter derived with the Radial Velocity Spectrometer (RVS)
in Astronomy & Astrophysics
Gaia Collaboration
(2022)
Gaia Data Release 3: Pulsations in main sequence OBAF-type stars
Gaia Collaboration
(2023)
Gaia Focused Product Release: Asteroid orbital solution. Properties and assessment
Gaia Collaboration
(2022)
Gaia Data Release 3: Summary of the content and survey properties
Gaia Collaboration
(2023)
Gaia Focused Product Release: Radial velocity time series of long-period variables
Gaia Collaboration
(2022)
Gaia Data Release 3: Exploring and mapping the diffuse interstellar band at 862 nm
| Title | TOPCAT |
| Description | TOPCAT is the most-used astronomical catalogue handling tool. It is extensively used to handle Gaia data and to create exploration plots of stellar populations, as well as in many other astronomical applications. It is also used for education in astronomical methods in the UK, Africa, and elsewhere. The underlying libraries are also used extensively for software developments. |
| Type Of Material | Improvements to research infrastructure |
| Provided To Others? | Yes |
| Impact | Extensively used world-wide. |
| URL | http://www.star.bris.ac.uk/~mbt/topcat/ |
| Description | GAIA team |
| Organisation | ESA - ESTEC |
| Country | Netherlands |
| Sector | Public |
| PI Contribution | Taylor has written much of the database access code for end-users, including major graphical display improvements. |
| Collaborator Contribution | ESA satellite project to map star positions in the Galaxy: highly successful at generating vast database, requiring our database access methodology |
| Impact | Extensive database for studies of structure of Galaxy. |
| Start Year | 2009 |