Newly developed relativistic R-matrix codes that harness the capabilities of Europe’s supercomputer network have been developed at QUB. This suite of codes can produce atomic data useful in the modelling and interpretation of astrophysical spectra.

At Queen’s, we have the capability to take *ab initio* atomic structure calculations through various collisional processes: electron-impact excitation/ionization/recombination or photoionisation through to spectral diagnostics applicable to astrophysics. The ability to carry-out such calculations within a reasonable time-frame, has enabled us to address the theoretical uncertainty in such predictions, by propagating correlated uncertainty on the fundamental atomic structure and collisional rates, through to a diagnostic within a Monte Carlo framework. It is widely accepted that the accuracy of temperature and density diagnostics is underpinned by the fundamental atomic work.

For example if we take photoionisation as a test case: As stated in Sterling et al 2015, the "abundance determinations of Se and Kr and indeed all n-capture elements in astrophysical nebulae are plagued by uncertainties. The most important of these uncertainties stems from the absence of reliable atomic data. However, atomic data needed to reliably correct for the abundances of unobserved ionization stages are unknown". Such "ionization correction factors", or ICFs, are most reliably de- rived via numerical simulations of astrophysical nebulae (Stasiska 1978; Kingsburgh Barlow 1994; Kwitter Henry 2001; Rodrguez Rubin 2005; Delgado-Inglada et al.2014 (see references with Sterling paper). However, the simulations are only as accurate as the underlying atomic physics that they include. Specifically, ionization equilibrium solutions in photo-ionized nebulae rely on accurate photoionization (PI) cross sections and rate coefficients for radiative recombination (RR), dielectronic recombination (DR), and charge transfer (CT). Until recently, these data were unknown for nearly all n-capture-element ions.

It would be beneficial if the prospective student has an entry-level quantum mechanical course. There is the intent that the student would develop, calculate and employ the resulting fundamental atomic data with numerical simulations. Therefore, an interest in solving problems from first principles and an interest in programming on large scale parallel computer architectures with the end focus of applying these results to the interpretation of astrophysical observation is important. However, more important is an interest in the topic as these skill-sets can be acquired during the project.

- There will be an opportunity to calculate the missing atomic and collisional data, for yet unidentified lines of Trans-Fe elements as well a elements above Z=54.
- There will be a strong computational aspect, therefore an interest in computational modelling, and in particular utilizing powerful parallel supercomputers is required.
- The student will have the unique opportunity to be a valuable bridge between the atomic structure and collisional calculations (CTAMOP) and the astrophysical requirements of ARC
- Beyond academia, numerical programming and experience with high performance computing are valuable marketable skills.

- N Sterling et al ArXiv:1505.01162v1 [astro-ph.SR] 5 May 2015

Drs. Connor Ballance and Cathy Ramsbottom

public/phds2019/2019_ballance.txt · Last modified: 2019/01/17 15:58 by Stuart Sim