Announcements of Opportunity
SURF: Announcements of Opportunity
Below are Announcements of Opportunity posted by Caltech faculty and JPL technical staff for the SURF program. Each AO indicates whether or not it is open to non-Caltech students. If an AO is NOT open to non-Caltech students, please DO NOT contact the mentor. Announcements of Opportunity are posted as they are received. Please check back regularly for new AO submissions!
Remember: This is just one way that you can go about identifying a suitable project and/or mentor. Click here for more tips on finding a mentor. Announcements for external summer programs are listed here.
*Students applying for JPL projects should complete a SURF@JPL application instead of a "regular" SURF application.
*Students pursuing opportunities at JPL must be U.S. citizens or U.S. permanent residents.
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| Project: | Determining the proper motion of stars in ZTF | ||||||||
| Disciplines: | Astronomy, Data Science | ||||||||
| Mentor: |
Matthew Graham,
Research Professor, (PMA),
mjg@caltech.edu, |
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| AO Contact: | Sam Whitebook, sewhitebook@astro.caltech.edu | ||||||||
| Background: |
The Zwicky Transient Facility (ZTF) has collected measurements of the bright- ness over time of billions of stars and galaxies in the Northern sky. Analysis of these time series light curves reveals an extreme variety of exotic systems which allow us to probe fundamental physics problems. Ensuring the quality of ZTF data is imperative to studying these objects, and there are many data science problems that arise in the extraction of light curves from raw data. One of the emergent problems that ZTF faces is the detection of stars that move relative to the Sun over time. This motion, called proper motion, causes the light from a star to appear in different places on a detector over the years. This motion can cause starlight to fall out of the region where it is usually counted, and therefore sources appear to vanish. For many objects, this motion has been solved using the Gaia space telescope, however there are millions of objects which are found in ZTF that do not have measured proper motions. We therefore seek to solve for these proper motions directly from ZTF data. |
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| Description: |
The student will work with raw ZTF images to detect the motion of stars’ light on the detector over time. The goal of this project is to design statistically rigorous and fast code that can detect moderate and high proper motions quickly for billions of sources over the seven year baseline of ZTF data. The student will primarily use python with astronomy libraries. The student will learn how to write and optimize code for astrophysical data reduction, as well as relevant statistics. This project will take place in-person at Caltech. The student will be a part of the ZTF stellar working group and the ZTF variability group (ZVAR), as well as the broader ZTF collaboration, with opportunities to learn more about sky surveys and explorative astronomy, and the opportunity to publish a research note or paper at the end of the project. |
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| References: | ZTF: https://www.ztf.caltech.edu/ | ||||||||
| Student Requirements: | Applicants should be proficient in Python and know basic statistics on the level of understanding distributions and basic linear fitting. Applicants need not possess experience with stellar astrophysics, but interest in physics and astronomy is encouraged. | ||||||||
| Programs: |
This AO can be done under the following programs:
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