New Advances in Photoionisation Codes: How and what for?

The study of photoionised gas in planetary nebulae (PNe) has played a major role in the achievement, over the years, of a better understanding of a number of physical processes, pertinent to a broader range of fields than that of PNe studies, spanning from atomic physics to stellar evolution theories. Whilst empirical techniques are routinely employed for the analysis of the emission line spectra of these objects, the accurate interpretation of the observational data often requires the solution of a set of coupled equations, via the application of a photoionisation/plasma code. A number of large-scale codes have been developed since the late sixties, using various analytical or statistical techniques for the transfer of continuum radiation, mainly under the assumption of spherical symmetry and a few in 3D. These codes have been proved to be powerful and in many cases essential tools, but a clear idea of the underlying physical processes and assumptions is necessary in order to avoid reaching misleading conclusions.The development of the codes over the years has been driven by the observational constraints available, but also compromised by the available computer power. Modern codes are faster and more flexible, with the ultimate goal being the achievement of a description of the observations relying on the smallest number of parameters possible. In this light recent developments have been focused on the inclusion of new available atomic data, the inclusion of a realistic treatment for dust grains mixed in the ionised and photon dominated regions (PDRs) and the expansion of some codes to PDRs with the inclusion of chemical reaction networks. Furthermore the last few years have seen the development of fully 3D photoionisation codes based on the Monte Carlo method.A brief review of the field of photoionisation today is given here, with emphasis on the recent developments, including the expansion of the models to the 3D domain. Attention is given to the identification of new available observational constraints and how these can be used to extract useful information from realistic models