X-ray absorption computation analysis

The x-ray_scripting_out pipeline processes X-ray Absorption Spectroscopy (XAS) output data generated by the ORCA quantum chemistry software. Its primary purpose is to leverage the force oscillator strength and transition density matrices to derive the core-virtual coupling molecular orbitals (MOs) represented as matrices. The updated output format integrates transition intensity from the matrix densities with their force oscillator strengths to build the matrices that describe MOs in the core and virtual spaces. These matrices encapsulate the core-virtual coupling MOs, as exemplified below:

 1. Number of transition intensities
 2. Transition intensity probability
 3. Force oscillator strenght 

This program has been used, e.g. for the analysis of quantum spectroscopy calculations for charge transfer in aromatic amino acids.

                                                         

Electron transition decomposition atomic contribution analysis (equation 5 of the reference) uses some matrix expressions.
Those matrix representations are encoded information from quantum spectroscopy calculations, the data parsing and encoding process prior to the calculation of the analysis (equation 5) is exactly what this repo does :)

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Getting Started

The pipeline is implemented in Shell script and is best suited for a Linux operating system. To execute the pipeline, you can use either manager.sh or overall.sh.

Prerequisites

The input required to run this pipeline is an XAS output file from ORCA, generated using either ROCIS/DFT or PNO-ROCIS/DFT. This input file must include the molecular orbital (MO) Löwdin population and the standard format of the transition intensities and probabilities for each excited state, along with a list of coupling MOs. You can specify a localized group of atoms involved in the coupling MO transitions, allowing for focused analysis of transitions between two sets of atoms, such as two amino acids in a protein.

Quick start

Choose any of the two versions:

• run in python+shell: docs/quickstart.md
• run in shell: docs/quickstart_old.md

Contributing

Contributions are what make the open-source community such a remarkable space for learning, inspiration, and innovation. Your contributions are highly valued and greatly appreciated!
If you have a suggestion to improve this project, feel free to fork the repository and submit a pull request. Alternatively, you can open an issue with the tag "enhancement." And do not forget to give the project a star if you find it helpful—thank you for your support!

Steps to Contribute

1. Fork the Project
2. Create Your Feature Branch:

   git checkout -b feature/branch  

3. Commit your Changes:

   git commit -m 'Add some Feature'  

4. Push to the Branch:

   git push origin feature/branch 

5. Open a Pull Request

Top contributors:

External information from ORCA

License

Distributed under the GNU General Public License v3.0

Contact

Lead project:

Carlos A. Ortiz-Mahecha