Rare object detection with Gaia
Lead Research Organisation:
University of Cambridge
Department Name: Institute of Astronomy
Abstract
The aim of this Project is to use astrophysically motivated data mining and
machine learning to identify objects that look or behave differently from the
rest in the Gaia's DR1 and DR2 data. The aim is to build a set of automated
detection algorithms for known classes of rare objects such as
tidal disruption of a star by an intermediate mass black holes inside a dwarf
galaxy, and astrometric microlensing events. This project has started with a
search for candidate astrometric microlensing events in Gaia DR1.
machine learning to identify objects that look or behave differently from the
rest in the Gaia's DR1 and DR2 data. The aim is to build a set of automated
detection algorithms for known classes of rare objects such as
tidal disruption of a star by an intermediate mass black holes inside a dwarf
galaxy, and astrometric microlensing events. This project has started with a
search for candidate astrometric microlensing events in Gaia DR1.
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| ST/P006787/1 | 01/10/2017 | 30/09/2024 | |||
| 1950369 | Studentship | ST/P006787/1 | 01/10/2017 | 30/09/2021 | Peter McGill |