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A photon dominated region code comparison study

期刊

ASTRONOMY & ASTROPHYSICS
卷 467, 期 1, 页码 187-+

出版社

EDP SCIENCES S A
DOI: 10.1051/0004-6361:20065918

关键词

ISM : abundances; astrochemistry; ISM : clouds; ISM : general; radiative transfer; methods : numerical

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Aims. We present a comparison between independent computer codes, modeling the physics and chemistry of interstellar photon dominated regions (PDRs). Our goal was to understand the mutual differences in the PDR codes and their effects on the physical and chemical structure of the model clouds, and to converge the output of different codes to a common solution. Methods. A number of benchmark models have been created, covering low and high gas densities n = 10(3), 10(5.5) cm(-3) and far ultraviolet intensities chi = 10, 10(5) in units of the Draine field (FUV: 6 < h nu < 13.6 eV). The benchmark models were computed in two ways: one set assuming constant temperatures, thus testing the consistency of the chemical network and photo-processes, and a second set determining the temperature self consistently by solving the thermal balance, thus testing the modeling of the heating and cooling mechanisms accounting for the detailed energy balance throughout the clouds. Results. We investigated the impact of PDR geometry and agreed on the comparison of results from spherical and plane-parallel PDR models. We identified a number of key processes governing the chemical network which have been treated differently in the various codes such as the effect of PAHs on the electron density or the temperature dependence of the dissociation of CO by cosmic ray induced secondary photons, and defined a proper common treatment. We established a comprehensive set of reference models for ongoing and future PDR model bench-marking and were able to increase the agreement in model predictions for all benchmark models significantly. Nevertheless, the remaining spread in the computed observables such as the atomic fine-structure line intensities serves as a warning that there is still a considerable uncertainty when interpreting astronomical data with our models.

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