RU-PREP Byrne Seminar Project Descriptions

Roughly half of the weeks of the seminar will be spent working on a research project in a very small group with mentors (graduate students, postdocs, or faculty) from the Physics & Astronomy Department. Students: please select your top three choices, and we will sort you into groups based on your choices. Read about the projects below, and follow the link to learn more about your potential mentors.

 


Project Title: Unwrapping the Milky Way’s Destructive Past
Mentor: Elaad Applebaum (graduate student, astronomy)
Skills: Basic Unix commands, Python: jupyter notebooks (preferred; not required), reading in table data, basic numpy, matplotlib, pandas for data manipulation

The Milky Way (the galaxy in which we live) is in a crowded neighborhood. Nearby are dozens of galaxies that we know of, with more being discovered each year. These galaxies are satellites of the Milky Way, much like the Moon is a satellite of Earth. Unlike our own Milky Way galaxy, these galaxies are very small---thousands to millions of times smaller. One of the biggest unknowns regarding our galactic neighborhood is how many of these galaxies we expect to discover with future telescopes and surveys. Contributing to the uncertainty is the fact that galaxies interacting with a large spiral galaxy like the Milky Way can be completely destroyed, and it is difficult to estimate how many small galaxies used to exist that are now incorporated into the Milky Way.

To address these and other questions, theoretical astrophysicists use large-scale simulations run on massively parallel supercomputers. A slice of the Universe is simulated from shortly after the Big Bang to the present day. With the outputs of these simulations, we can make predictions and better understand the galaxies that we observe around us. This project will use data from some of the highest resolution cosmological galaxy simulations ever run. You will use python analytical tools to compare these simulations to similar ones run with only dark matter -- the stuff that makes up over 80% of all matter in the Universe. Your goal is to study the impact that the Milky Way has on its satellite galaxies.

 


Project Title: The Age-Velocity Relation of Stars in Multiple Milky Way-mass Galaxies
Mentor: Alyson Brooks (prof, astronomy)
Skills: Basic Unix commands, Python: jupyter notebooks (preferred), numpy, matplotlib, pynbody

It has been known for many decades that the older stars in the disk of the Milky Way are moving at higher velocities than young stars (a higher velocity dispersion). It has been suggested that stars may be born with low velocities and then "scatter" off large clouds of gas in the Milky Way to achiever higher velocities. But it has also been suggested that the Milky Way's disk was born "hotter" and has "cooled" with time. Can we disentangle these effects?

In this project, students will use state-of-the-art simulations of Milky Way-mass galaxies to plot the velocity dispersion of stars (binned by age) as a function of time. The main goal is to find out how commonly we can reproduce a simulated galaxy that resembles the Milky Way.

 


Project Title: Identifying Star Forming Galaxies from Their Colors
Mentor: Adam Broussard (graduate student, astronomy)
Skills: python, plotting, reading/writing data

This project aims to classify galaxies as star forming or quenched (non-star forming) based on their de-redshifted colors. We will start by examining some example galaxy spectra and identifying the broad features that indicate star formation and dust content. We will then identify regions of the spectrum that are able to describe the primary features we have identified previously, and choose relevant wavelength bands we will use for our galaxy colors. Finally, we will plot these colors on a scatter plot and compare against more sophisticated methods of star formation measurement to show that our identified galaxy colors are able to accurately separate the star forming and non-star forming galaxies without the need for time-expensive spectroscopic measurements.

 


Project Title: Probing defect unbinding in two-dimensional crystals
Mentor: Victor Drouin-Touchette (graduate student, condensed matter theory)
Skills: Python numpy/scipy/matplotlib

The transition of matter from the solid to the liquid phase is one we understand well in three dimensions – the space we live in. Through the 20th century, more and more attention was devoted to two-dimensional materials for their unusual behavior due to the increased role of energy fluctuations in matter. A lot of attention over the last 40 years has been devoted to the understanding of melting of two-dimensional crystals, which happens through a radically different mechanism than in higher dimensions. This led to the proposal of a completely new category of phase transitions, called the Kosterlitz-Thouless theory of melting. It states that melting is dominated by the presence of free point defects. These are called topological charges because their value is either 1 or -1, i.e., it is quantized, and cannot be changed continuously. The movement of independent defects brings upon the liquid phase. On the other hand, in the rigid solid, these are not independent anymore; there are few of them, and, more importantly, they are bound in neutral pairs with a positive and a negative defect stuck together.

Through this project, students will analyze the output of numerical simulations of a related model in order to test the pair-binding scenario. They will have to write a method to identify the topological defects, and then study their distribution, attempting to measure whether vortices are free or bound. Finally, they will have to repeat their observation on many independent numerical outputs, in order to produce error bars on the statements they advance.

 


Project Title: Flight Path of Relativistic Particles
Mentor: Ron Gilman (prof, nuclear physics)
Skills: simple python coding

In this project, students will interpret data from a real particle experiment. Using the flight time of three different types of relativistic particles, students will determine the flight path and momentum of the particles as they arrived at the detector.

 


Project Title: Mapping the Speed of a Vast Cosmic Collision
Mentor: Jack Hughes (prof), Peter Doze (graduate student, astronomy)
Skills: use SDSS database, read/comprehend scientific papers, simple python coding

Gravitationally bound structures form across a wide range of sizes in the Universe. Locally we have the asteroids, moons and planets of the solar system with sizes measured in seconds of light travel time. On the other size scale are vast clusters of galaxies that can span up to 10 million light years. Galaxy clusters grow with cosmic time through the accretion of surrounding matter. In rare cases this accretion process can involve the merger of two nearly equal mass systems that collide violently, producing distortions in the gas, galaxy, and dark matter distributions that make up clusters. Studying clusters in such merger states can reveal differences between these constituents that can help inform our understanding of dark matter.

Our Chandra X-ray observations of a galaxy cluster (named J0034) shows significant distortions in its gas distribution suggesting that it is undergoing a major merger. We have recently acquired optical spectral measurements of a number of cluster members from the Southern African Large Telescope. The project involves using the spectral measurements to obtain a more accurate estimate for the cluster's distance and to search for additional evidence that J0034 is undergoing a major merger.

 


Project Title: Electronic transport properties of a metal
Mentor: Gaurab Rimal (postdoc, condensed matter experiment)
Skills: Python: reading in table data, basic numpy/scipy/matplotlib

A fundamental question in condensed matter physics is how electrons behave at low temperatures. A common method for finding this in metals to measure their transport properties at various temperatures. For this project, the students will use hall effect measurements to find electronic properties of a metal film. They will use python to analyze the experimental data and find models that can describe the observed electronic behavior.

 


Project Title: Active Black Hole Identification using Tracers of Ionization
Mentor: Ray Sharma (graduate student, astronomy)
Skills: Unix, Python numpy/astropy/matplotlib

Supermassive black holes have been found within many galaxies throughout the universe, though black holes can be tricky to identify. Black holes can have drastic effects on their surrounding regions by heating up, ionizing, and ejecting gas. In nearby galaxies, these effects can be observed as substantial changes in the structure of the galaxy, or as the formation of powerful jets. In distant galaxies, however, structure is hard to discern. Using a variety of tools, astronomers have been able to find and characterize black holes in distant galaxies without having to see changes in galaxy structure.

One such tool, the BPT-diagram, tests how much gas in a galaxy is ionized as a means of identifying the effects of black holes. Using data from the Sloan Digital Sky Survey, students will be able create BPT diagrams and identify galaxies with or without black holes. Students will be expected to use basic Unix to gather data, and basic python (including NumPy, AstroPy, and Matplotlib) to perform the analysis.

 


Project Title: Exploring Physical Properties of U-Shaped DNA with Computational Modeling
Mentor: Robert Young (graduate student, biophysics)
Skills: Python 3 (with Jupyter Notebook), Unix, Data Visualization

DNA has been used in multitudes of biological and chemical experiments, resulting in advancements in medicines and gene therapies; yet much of what is known about this double-helical polymer stems from studies of its physical properties and the way it interacts with molecules, particularly proteins. Surveys are done to understand how protein-DNA binding interactions may alter the arrangement of tens to hundreds of neighboring DNA base pairs, hydrogen-bonded complexes formed by adenine (A) and thymine (T) and by cytosine (C) with guanine (G). These configurations may also be influenced by factors such as the immediate environment or base-pair sequence. One such study revolves around a 35-base-pair sequence of DNA that when bound to certain architectural proteins adopts a U-shape with two sharp bends. While the main protein-DNA interactions occur at the ends of the sequence, the bends result from parts of two protein molecules nestling into the DNA helix. Recent experimental data have shown that changing the sequence of the six bases at a bending site alters the strength of the protein-DNA interaction. We would like to explore how different base-pair sequence in this six-base-pair region will alter various structural properties by constructing models of DNA using data from the Protein Data Bank.

Figure: A model of the Hbb protein interacting with a 35-base-pair sequence of DNA (PDB ID: '1ihf'). The magenta regions are consensus sequences while the 'ATGCAG' sequence (red) is adopted from phage DNA. Our survey focuses on structural changes by altering the NNNNNN (cyan) region sequence.