DOI: 10.17863/cam.109314
title: Research Data Supporting "Targeting spectroscopic accuracy for dispersion bound systems from ab initio techniques: translational eigenstates of Ne@C70"

description: The data required to generate the tables and figures for the paper, alongside bash and python scripts to generate the PES are found in this directory. Python version used is 3.10.6, sklearn version is 1.0.2. When learning the PES, the L-BFGS may raise a ConvergenceWarning, this is to be expected as the noise hyperparameter optimises to its lower bound. All python scripts must be run from this directory due to python adding the current directory to its path when scripts are run. This directory is structured as follows: - coords.txt Text file containing the input training coordinates for the Gaussian Process. -C70.xyz XYZ file of C70 coordinates. This has been checked as D5h. - ne_c70__ccpvz.txt es is mp2 or rpa. Basis is t/q. If basis is 5, es is hf or ks. Outfile generated by FermiONS++ with energies index as given by coords.txt in order to interpolate PES. - _ccpvz.dat es is mp2 or rpa. Basis is t/q. If basis is 5, es is hf. Data file generated by bash script in order to CBS extrapolate. - b96bpbe_x_xdm.out exchange is 25 or 50. FHI-aims energies with indices given by coords.txt in order to interpolate PES. - ne_c70_interaction_energy__ccpv,txt es is mp2 or rpa. basis is t/q. If basis is 5, es is hf or hf_pbe. Outfile generated by FermiONS++ in order to calculate the binding energy of Ne@C70 for the method. - NeC70_binding_.dat Tag is ccpvtz/ccpvqz/ccpv5z/b86bpbe/CBS. The first 3 are generated from the bash script from MP2/RPA data. b86bpbe is data from FHI-aims. CBS is generated from the python script. - extract_FermiONS_energies.bash Bash script to parse FermiONS++ results files, and extract only the energies. This does the PES energies, and the binding energies. - generate_cbs_energies.py Python script to CBS extrapolate the SCF and correlation energies from mp2/rpa data. Writes them alongside b86bpbe values to an outfile. Generates both PES interpolation energies and binding energies. - NeC70_CBS_energies.dat Data file containing the coords and corresponding CBS energies for multiple ES methods. - NeC70_bindings.dat Data file containing the binding energy for Ne@C70 for multiple ES methods. - gaussian_process_pes.py Python script to run the Gaussian Process for each ES method. `predict_nec70_pes` is the main function needed. - analyse_pes_symmetry.py Python script which uses QSym2 (https://qsym2.dev/) to analyse the symmetry on each PES. - _pes_symmetry.out method is mp2/scs/sos/rpa/crpa/b86bpbe_25x/b86bpbe_50x/lj. Outfile generated by QSym2 analysing the D5h symmetry of each ES PES. PES is not averaged over symmetrically equivalent coordinates. - NeC70_eigenstate_data.npz Keys include es_energies, es_errors, efflj_energies, ground_state_stats, ground_state_wavefunc, lj. Numpy compressed file containing the translational eigenstate data including energies, error bars, effective LJ energies, ground state wavefunction plotting data, ground state wavefunction statistics and the traditional LJ energies. - hellinger_ground_state_distances.txt Hellinger distances between ground states of multiple ES methods. - _quantum_numbers.txt method is mp2/scs/sos/rpa/crpa/b86bpbe_25x/b86bpbe_50x. All can contain LJ suffix. File containing the energy and quantum numbers indexed as (n,l,nz) for each ES method. - plot_figures_for_paper.py Python script to generate the figures. There is 1 main function which takes the figure number and a boolean as to whether it is in the SI. The rest of the script is helper functions. Refer also to the README file uploaded.