DOI: 10.5281/zenodo.17909784
title: Dataset for "Applying R-Matrix Theory to Atom–Molecule Inelastic Collisions: the Case Study of H₂O + H"

description: Description

This dataset contains the numerical data and Jupyter notebooks used to generate Figures 1 and 2 of the article:

“Applying R-Matrix Theory to Atom–Molecule Inelastic Collisions: the case study of H₂O + H”  Ricardo Manuel García-Vázquez, Lisan David Cabrera-González, Otoniel Denis-Alpizar,  Philippe Halvick, and Thierry Stoecklin, Physical Chemistry Chemical Physics, (2026),https://doi.org/10.1039/D5CP04501K

The dataset includes Close-Coupling (CC) calculations, R-Matrix results, elastic cross sections,  and the Python notebooks used to produce the published figures.

Contents

1. Close-Coupling (cc) and R-Matrix (rmat) Data — Figure 1



Collision-energy range (cc): 0.001–3981 cm⁻¹.

Collision-energy range (rmat): 0.1–1000 cm⁻¹.

Each file contains multiple columns:


1. Column 1 — Collision energy  2. Column 2 — Number of energetically open channels (n),       following the ordering of the rotational states of H₂O  3. Columns 3 to (2 + n) — Integral cross sections from the initial       level (given in the file name) to final states 1…n       of the same nuclear-spin symmetry (para/ortho)



Only rotational relaxation transitions are converged.    Cross sections for rotational excitation have not been validated    and must not be used for comparison or publication.


2. R-Matrix Data — Figure 2

Includes both inelastic and elastic scattering cross sections obtained from  inner-region R-Matrix calculations, with or without long-range propagation.

Figure 2: Na⁺ + He Elastic Scattering

Files provided:



crosssec_30+prop50.dat — R-Matrix on [0.2, 30] a₀ with propagation to 50 a₀

crosssec_rasy=50.dat — Full R-Matrix calculation on [0.2, 50] a₀

crosssec_rasy=30.dat — R-Matrix restricted to [0.2, 30] a₀ without propagation


Each file contains:



Collision energy (equal to the total energy for elastic scattering)

Elastic cross section


3. Jupyter Notebooks



Notebook for Figure 1: Reads CC and R-Matrix datasets and generates the published plot

Notebook for Figure 2: Reads elastic cross section data and reproduces the Na⁺ + He comparison plot


Both notebooks are self-contained and documented.

File Formats



All data files are plain-text files for long-term reproducibility

Jupyter notebooks are provided as .ipynb

Plots are generated in standard Python/Matplotlib


How to Cite

If you use this dataset, please cite the article above.  For CC data specifically, please also cite:

L. D. Cabrera-González, O. Denis-Alpizar, D. Páez-Hernández, and T. Stoecklin,  Monthly Notices of the Royal Astronomical Society, 514, 4426–4432 (2022).

Keywords

R-Matrix theory, molecular collisions, close coupling, H₂O + H, Na⁺ + He,  elastic scattering, inelastic scattering, cross sections, quantum dynamics,  astrochemistry, computational chemistry, scattering theory

Python Dependencies

The Jupyter notebooks use the following Python libraries:

Figure 1



numpy

matplotlib

pandas

mmap (standard library)

adjustText

matplotlib.ticker (LogLocator)

matplotlib.lines (Line2D)


Figure 2



numpy

matplotlib

seaborn

adjustText

matplotlib.ticker (LogLocator)

matplotlib.lines (Line2D)


These libraries are widely available in common scientific Python distributions  (e.g., Anaconda, Miniconda).