UROP Project

astrophysics, physics, applied mathematics, statistics, computational science, sensitivity analysis, uncertainty quantification

Research Mentor: Dr. Tomasz Plewa,
Department, College, Affiliation: Scientific Computing, Arts and Sciences
Contact Email: tplewa@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 1
Relevant Majors: mathematics, physics, statistics, computer science, engineering
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: Partially Remote
Approximate Weekly Hours: 10,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

Motivated by observations of supernova remnants such as SN 1987A or Tycho, we are investigating links between the supernova progenitor structure, instabilities developing during the explosion process, and characteristics of emerging young supernova remnants. The starting point for such investigations are stellar evolution studies of supernova progenitors.

From practical point of view, stellar evolution calculations require solving a set of coupled, nonlinear ordinary or partial differential equations. In this project, we will be using the MESA code,

http://mesa.sourceforge.net/

to solve the required evolutionary equations. In recent years, MESA had become a tool of choice for studying variety of astrophysical systems such as stars, binary stars, planets, and basic physics problems in dedicated settings. In this project, we study the evolution of thermonuclear flames powering Type Ia supernovae explosions, and assess sensitivity of their properties, such as speed and width, on the fuel parameters. The results of this study will subsequently be used as input to supernova explosion codes such as Agile-IDSA,

http://www.physik.unibas.ch/~liebend/download/index.html

or FLASH,

https://flash.rochester.edu/site/flashcode/

More advanced students may participate in and contribute to the analysis of multiphysics simulation results, such as computing nucleosynthetic yields and obtaining specific characteristics of explosion models.

This project is strongly computationally-oriented and requires practical user knowledge of Linux or MacOS operating systems. In addition, a broader range of topics is available to students fluent with programming languages such as C, C++, Fortran, or Python. Familiarity with simulation data analysis and visualization tools (e.g. Excel, gnuplot, matplotlib) is a plus.

Applications of students who do not have programming skills or do not plan taking a programming class during the first semester of this project are strongly discouraged.

Additional information related to the project can be obtained at

http://people.sc.fsu.edu/~tplewa/Research/index.html#resources

Research Tasks: All the required work will be done on desktop computers provided by the Department of Scientific Computing or with student's laptop computers serving as front ends to departmental computers (connecting via Remote Desktop/Anydesk software), and Zoom for weekly communications. The project tasks involve,
(1) Review text book information about mathematics and physics relevant to problems in stellar evolution.
(2) Familiarize with the Linux operating system. Download, install, and familiarize with the MESA stellar evolution code.
(3) Construct a series of stellar evolution tracks for various stellar masses (Hertzsprung-Russel Diagram).
(4) Present evolution of stellar structure using Kippenhahn's diagrams (see, e.g., https://github.com/orlox/mkipp ).
(5) Study sensitivity of stellar progenitors characteristics or stellar physics phenomena to problem parameters.
(6) Obtain a series of stellar evolution or relevant multiphysics simulations.
(7) Analyze obtained results.
(8) Prepare a poster presenting the project findings.

Skills that research assistant(s) may need: Recommended: familiarity with the Linux-type operating system; practical knowledge of MATLAB, Python, or Fortran/C/C++.
Required: interest in and solid basic preparation in the areas of mathematics, physics, or statistics.