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| Funder | Science and Technology Facilities Council |
|---|---|
| Recipient Organization | University of Leeds |
| Country | United Kingdom |
| Start Date | Sep 30, 2024 |
| End Date | Mar 30, 2028 |
| Duration | 1,277 days |
| Number of Grantees | 2 |
| Roles | Student; Supervisor |
| Data Source | UKRI Gateway to Research |
| Grant ID | 2929155 |
Debris disks are dusty disks of material around main sequence stars, revealed by their far-infrared excess emission.
Collisions between asteroids or Kuiper Belt Objects generate small dust particles which absorb starlight from their host stars and reradiate this in the far-IR.
Usually the amounts of dust in typical solar systems are very low, on the order of a few Lunar masses or less, however this may be an observational limitation of current debris disk surveys which are tightly focused on solar system analogues.
Because far-IR galaxy surveys cover large areas of sky they are able to rapidly survey 100,000's of stars for bright excess emission, which is uniquely suited to covering disks that are too rare to be found in smaller debris disk surveys.
These bright and massive disks suggest unusual planetary architectures with extensive Kuiper belts, or perhaps stochastic events like massive collisions or interactions with nearby stars.
This PhD project is to study the sample of ~400 candidate disks that we have identified in the Herschel-ATLAS survey, using multi-wavelength data to refine the sample and identify the most promising and unusual debris disks for further study.
We have dedicated high resolution 70 micron images of a number of disk candidates and GAIA data will also play a key part in determining the distance to the host stars.
You will also extend the search technique to the much wider area of the Herschel legacy catalogue which covers around 10% of the entire sky.
The ultimate aim is to select a sample of promising objects for high resolution observations with the ALMA interferometer to try and understand the physical nature and origin of these unique disks.
As part of the project you will gain familiarity with multi-wavelength data analysis, sophisticated data science techniques for analysing large astronomical catalogues, and experience of interferometry observations and analysis.
University of Leeds
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