Dey, Biprateep
(2024)
Cosmic Cartography: Photometric Redshifts for Next-Generation Sky Surveys.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Knowing the distances to galaxies as measured by their cosmological redshift is crucial for studies of cosmology, galaxy evolution, and astronomical transients. The next generation of astronomical imaging surveys will all be critically dependent on estimates of galaxy redshifts from imaging data alone; the resulting measurements are called photometric redshifts or photo-z's. Traditional photo-z estimation methods only use measures of total light received from a galaxy (colors and magnitudes) as input, thereby removing the rich pixel-level information often present in images. In addition, the uncertainty estimates produced by these methods are not statistically well defined, and the availability of data to train these methods is scarce. In this thesis, I will present my work on developing new deep learning-based photo-$z$ estimation methods that take images directly as input and provide state-of-the-art photo-$z$ prediction accuracy while being interpretable and requiring fewer training data. I will also discuss a statistical formalism that I developed to produce well-calibrated photo-z uncertainty estimates that are method-agnostic and employ minimal assumptions. Finally, I will provide an overview of our recent efforts to obtain spectroscopic samples to train for photo-z algorithms using the Dark Energy Spectroscopic Instrument (DESI).
Share
| Citation/Export: |
|
| Social Networking: |
|
Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
|
| Date: |
27 August 2024 |
| Date Type: |
Publication |
| Defense Date: |
24 June 2024 |
| Approval Date: |
27 August 2024 |
| Submission Date: |
4 August 2024 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
202 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Dietrich School of Arts and Sciences > Physics |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
photometric redshift, uncertainty quantification |
| Date Deposited: |
27 Aug 2024 13:11 |
| Last Modified: |
27 Aug 2024 13:11 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/46829 |
Metrics
Monthly Views for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |
![[feed]](/images/feed-icon-32x32.png){kind=icon}