PDFchem: A new fast method to determine ISM properties and infer environmental parameters using probability distributions
Thomas G. Bisbas, Ewine F. van Dishoeck, Chia-Yu Hu, and Andreas, Schruba

TL;DR
PDFchem is a rapid, probabilistic algorithm that models the cold interstellar medium's chemical composition and emission lines across various environmental conditions, enabling large-scale studies without intensive computations.
Contribution
It introduces PDFchem, a novel fast method using probability density functions to model ISM properties and emissions efficiently across different environments.
Findings
Reproduces results of complex hydrodynamical models
Works across a wide range of environmental parameters
Provides quick estimates of ISM chemical abundances and emissions
Abstract
Determining the atomic and molecular content of the interstellar medium (ISM) as a function of environmental parameters is of fundamental importance to understand the star-formation process across the epochs. Although there exist various three-dimensional hydro-chemical codes modelling the ISM at different scales and redshifts, they are computationally expensive and inefficient for studies over a large parameter space. Building on our earlier approach, we present PDFchem, a novel algorithm that models the cold ISM at moderate and large scales using functions connecting the quantities of the local () and the observed () visual extinctions, and the local number density, , with probability density functions (PDF) of on cloud scales typically tens-to-hundreds of pc as an input. For any given -PDF, sampled with thousands…
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Taxonomy
TopicsAir Quality Monitoring and Forecasting
