Dataset for "Applying R-Matrix Theory to Atom–Molecule Inelastic Collisions: the Case Study of H₂O + H"

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).