Presentation #124.06 in the session Laboratory Astrophysics Division (LAD): iPosters.
For many modern astrophysical observatories with high resolution spectrometers or calorimeters the factor limiting the accuracy of astrophysical models is often no longer the instrument resolution or calibration, but is instead the uncertainties inherent in the physical models and diagnostics used to interpret them. Assigning uncertainties on atomic rate coefficients is essential to effectively understand these spectra. We present a method that can assign uncertainties on radiative and dielectronic recombination rate coefficients. A Bayesian method is used, along with a Markov chain Monte-Carlo approach, in the generation of the uncertainties. Recombination rate coefficients can be generated along iso-electronic sequences, and we compare our results with experimental measurements for the Be-like and Li-like sequences. The data can be used in modeling codes via the extraction of samples from the full dataset, and interpolation of the distribution functions onto the modeling temperature grid. The uncertainties are then propagated through a collisional ionization balance calculation, to illustrate how the uncertainties can be used in modeling codes.