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.
New for 2021: 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.
|Project:||Multiple Projects in Galaxy Evolution and Data Science|
|Disciplines:||Astronomy, Computer Science, Physics|
|Mentor URL:||https://dawn.nbi.ku.dk/events/surfdawn/ (opens in new window)|
NOTE: This project is being offered by a Caltech postdoc alum and will take place at the Niels Bohr Institute at the University of Copenhagen in Copenhagen, Denmark. Only Caltech students are eligible for this project.
NOTE: THE DESCRIPTION BELOW ASSUMES THAT TRAVEL IS RECOMMENDED THIS SUMMER.
This is one of several projects available at the Niels Bohr Institute this summer, and we expect that in total 6-10 students (some from Caltech and some from elsewhere) will come to Copenhagen during our fifth year running a summer program. Since travel within Europe is inexpensive, this will be an 11 or 12 week program, so that students can take a 1-2 week vacation to see other parts of Europe. Other projects in astronomy with different mentors will also be available. We hope to finalize who will be coming by mid-January, so that there will be plenty of time to both write a SURF proposal and take care of any necessary visa/housing.
Note that this work will take place in Copenhagen, so you will be traveling to and living in a foreign country for your research over the summer. Denmark is a very friendly country and it is possible to do everything both inside and outside of work by speaking English. However, it is still a foreign country, and successful students will need to be able to live independently in an environment without some of the support systems and accommodations available in Pasadena.
It is possible that international travel will not be advisable this summer. If travel is legal but still not recommended, the program will not run in Denmark. If so, we will either look for a different location where travel is recommended or run the program remotely, but either way we will advise research projects this summer..
Finally, the Niels Bohr Institute will be hosting several major international meetings during the summer, including a summer school in machine learning and data science. Summer researchers will be welcome to attend these meetings, as well as invited to present if their projects are far enough along at that point in the summer.
A range of projects related to early-Universe galaxy formation and evolution are available, ranging from observational to computational depending upon your background and interest. Possible projects might include:
1) We were recently awarded a large Hubble Space Telescope program, BUFFALO, which uses massive galaxy clusters as gravitational lenses to find faint, distant galaxies. As part of this effort, we have been developing novel machine learning methods for analyzing the resulting catalogs, which generates several problems suitable for students interested in either computer science or astronomical research. Several students last summer did work relating to BUFFALO and are authors on upcoming BUFFALO papers.
One particularly interesting problem might be trying to identify high-redshift galaxies which don’t have any similar low-redshift counterparts. This is a particularly sharp problem because we often identify the earliest galaxies by assuming they are simply high-redshift versions of local galaxies. If this turns out not to be true, we might have been missing a substantial population of galaxies at an early stage in their evolution. Studying this population might even be a good way to understand some of the puzzling properties that galaxies exhibit at later times (such as in the next topic).
2) Many different ways of observing galaxies at a variety of stages in their evolution reach the same surprising conclusion: evolving galaxies all look remarkably similar. This similarity recently prompted us to build a model in which galaxies share a common evolutionary history, and the various stages that we observe (star formation, quasar accretion, eventual turnoff, etc.) are all included. The success of our initial exploration had led us to try and develop this model further, which will involve both theory work modeling gas dynamics and comparison with observations.
In this case, the problem suffers from a wealth of data -- there is so much information out there about so many different states of galaxy evolution that it's difficult to make sense of it all. Thus, the initial stages of this problem will likely involve taking some time to become familiar with the enormous literature on what we've learned in the past few decades about how galaxies grow. As a result, this project would be very well suited for a student interested in astronomy or astrophysics, but a strong background in astronomy is not required as you will pick this up along the way.
3) Analysis of high-redshift galaxies can often only be done from very limited data, in many cases using only the colors of galaxies in very broad filters (called photometry). Everything we learn about these galaxies therefore comes from fitting models derived from local galaxies to photometric data. However, there are several good reasons to think that the first galaxies to form in the Universe actually aren’t exactly like local galaxies, and therefore we would need to use different models.
Over the past few years, we have been developing models for the ways in which the first galaxies might differ from local ones, particularly in terms of the temperatures in star-forming regions. We spent much of the past two years developing an up are currently working to develop updated galaxy property catalogs, which will be ready by this summer. The next step is to see whether we can use this to develop improved models for how galaxies grow. Much of this work has involved summer students over the past couple of years, including two publications and several others in preparation.
4) We recently found that novel machine learning techniques allowed us to categorize gamma-ray bursts far more efficiently than was previously possible. We are now looking at other places where these methods might be applicable, not just in astronomy but also with groups at the Niels Bohr Institute in biology. This project would be well suited for a computer science student, as the creative aspects are almost entirely computer science rather than astronomy (or biology). It also may be a good fit for a student with a strong mathematical background.
|Student Requirements:||Variable, depending upon the project, but some computational background is strongly recommended. Some projects will be suitable for freshmen, and others will require a more formal astronomy, physics, computer science, or even math background.|
This AO can be done under the following programs:
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