PyEMILI: A New Generation Computer-aided Spectral-line Identifier. II. Emission-line Identification and Plasma Diagnostics of a Sample of Gaseous Nebulae

Abstract In order to test the robustness and reliability of the new generation spectral-line identifier PyEMILI, as initially introduced in Paper I, in line identification and establish a reference/benchmark dataset for future spectroscopic studies, we run the code on the line lists of a selected sample of emission-line nebulae, including planetary nebulae (PNe), H ii regions, and Herbig–Haro objects with deep high-dispersion spectroscopic observations published over the past two decades. The automated line identifications by PyEMILI demonstrate significant improvements in both completeness and accuracy compared to the previous manual identifications in the literature. Since our last report of PyEMILI, the atomic transition database used by the code has been further expanded by crossmatching the Kurucz line lists. Moreover, to aid the PyEMILI identification of numerous faint optical recombination lines (ORLs) of C ii , N ii , O ii , and Ne ii , we compiled a new dataset of effective recombination coefficients for these nebular lines, and created a new subroutine in the code to generate theoretical spectra of heavy-element ORLs at various electron temperature and density cases; these theoretical spectra can be used to fit the observed recombination spectrum of a PN to obtain the electron temperature, density, and ionic abundances using the Markov Chain Monte Carlo (MCMC) method. We present MCMC-derived parameters for a sample of PNe. This work establishes PyEMILI as a robust and versatile tool for both line identification and plasma diagnostics in deep spectroscopy of gaseous nebulae.