Isochrones and stellar tracks are two types of theoretical models of stars. They are widely used in astrophysics to help determine fundamental stellar properties, such as age, distance, and---if we're lucky---some aspects of the stellar interior.
The one-dimensional stellar structure and evolution codes (SSECs) that generate these models are complicated patchworks of the best data and computational methods that many subfields of astronomy and nuclear physics have to offer. Since our theoretical knowledge is incomplete, these codes rely on calibrating our physical assumptions against ultra high-precision observations of the Sun.
While solar-based formalisms are helpful when designing a stellar code, theoretical models of stars with highly non-solar properties (such as stars with drastically different sizes or chemical compositions) can quickly become unreliable.
In fact, current research suggests that the ad hoc assumption of solar formalisms can lead to dangerous estimation errors in the derivation of critical properties.
With the increased availability of high-precision observational data, however, we have recently become able to calibrate SSECs using direct, empirical measurements of stars other than the Sun.
Recent research using such methods has demonstrated the importance of checking our work in this way, finding, in particular, that the solar prescription for convective mixing is very ineffective in other stellar models.
This calls into question all publicly available stellar evolution databases, all of which make a solar-based assumption about convection in computing their isochrones.
The student will use observational constraints to test the validity of solar prescriptions, especially mixing length theory (MLT), in one or more stellar evolution codes.
The student will intercompare different stellar evolution codes, write software, and generate grids of SSEC calculations.
The student may also have the opportunity to contribute to an existing, open source SSEC or related project, earning appropriate coauthorship on software papers and any science which may follow from the code they develop.
The student should have some exposure to computing and software management, or be enthusiastic about learning these skills on her/his/their own.
For more details of this project, please contact the supervisor.