PyExoCross 2.0: A Python Framework for LTE and non-LTE Spectra, Cross Sections, and Spectroscopic Post-processing of Atomic and Molecular Line Lists

@misc{zhang2026pyexocross,
  title = {{PyExoCross 2.0: A Python Framework for LTE and non-LTE Spectra, Cross Sections, and Spectroscopic Post-processing of Atomic and Molecular Line Lists}},
  author = {Jingxin Zhang and Sergei N. Yurchenko and Jonathan Tennyson},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.17273},
  eprint = {2609.17273},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.17273},
  note = {CC BY 4.0},
}

TY  - UNPB
TI  - PyExoCross 2.0: A Python Framework for LTE and non-LTE Spectra, Cross Sections, and Spectroscopic Post-processing of Atomic and Molecular Line Lists
AU  - Jingxin Zhang
AU  - Sergei N. Yurchenko
AU  - Jonathan Tennyson
PY  - 2026
DA  - 2026/09/15
PB  - arXiv
DO  - 10.48550/arxiv.2609.17273
UR  - https://arxiv.org/abs/2609.17273
AB  - PyExoCross is a Python-based spectroscopic post-processing framework for converting large atomic and molecular line lists into scientifically useful quantities, including partition function, specific heats, cooling functions, lifetimes, oscillator strengths, line intensities, stick spectra, and absorption and emission cross sections. It is intended for applications in astrophysics, planetary atmospheres, laboratory spectroscopy, and other high-temperature environments where large modern databases require efficient and reproducible computational treatment. The new release provides both a configuration-file-driven command-line interface (CLI) and a Python application programming interface (API) within a unified computational framework. The original input file workflow is retained, while the Python API enables direct use in scripts, notebooks, and automated pipelines. The version PyExoCross 2.0 also adds explicit support for non-local thermodynamic equilibrium (non-LTE) calculations, including two-temperature models and user-defined density and population treatments for both absorption and emission spectra. In addition, database compatibility has been expanded beyond ExoMol, HITRAN, and HITEMP line lists to include high-resolution molecular database ExoMolHR and atomic database ExoAtom. GPU acceleration is also introduced for computationally intensive intensity and cross-section calculations and is available for all currently supported database formats. These developments improve workflow flexibility, reproducibility, and integration with modern data-analysis environments, while extending the physical modelling capabilities of the code. PyExoCross therefore provides a more general and extensible platform for large-scale spectroscopic simulations based on modern atomic and molecular databases.
ER  -