QuantumResponsePro

QuantumResponsePro is a Python package for computing and analyzing dynamic response properties of molecules in TDDFT and TDHF formalisms with arbitrary accuracy. It enables comparison of results computed using the MADNESS and Dalton quantum chemistry packages by translating generic inputs into specific MADNESS and Dalton input files, and processing Dalton output files into easily readable JSON files.

Features

• Input and output translators for MADNESS and Dalton quantum chemistry packages.
• Frequency-dependent polarizability analysis for various molecules at multiple frequencies.
• Extensive basis set analysis based on augmentation, valence size, core polarization, etc.
• Compatibility with other response properties beyond polarizability.
• Includes example scripts and Jupyter notebooks for demonstration purposes.

Installation

Install QuantumResponsePro via pip:

pip install quantumresponsepro

Alternatively, you can clone the repository and install it from the source:

git clone https://github.com/yourusername/QuantumResponsePro.git
cd QuantumResponsePro
pip install -e .

Usage

Generate a response database

1. Create a response database directory with the following subdirectories: molecules: contains the molecule definition madness.mol in xyz format json_data: stores database property json files (generated later) To run response property calculations, generate a frequency.json file with a list of frequencies for computing response properties. First, calculate the first excited-state energy for a given functional and save the results in dalton_excited.json.

Use this code:

from pathlib import Path
from quantumresponsepro import DatabaseGenerator

dir = "path/to/directory"
db_gen = DatabaseGenerator(Path(dir))
xc = "hf"
basis = 'aug-cc-pVDZ'

db_gen.DatabaseGenerator.get_dalton_excited_json(xc, [basis], True)

The code generates input files for the first excited-state calculation, runs the calculation, and saves the results for each molecule in dalton/xc/excited_state/ Output files have the prefix excited_mol_basis, with .out for output files and .json for json files. All molecule-basis pair json files are combined into a single dalton_excited.json file in the json_data directory.

Once the excited-state calculations are complete and a dalton_excited.json file has been generated you can now generate a frequency.json file with a list of frequencies for computing response properties. The frequency.json file is used by the MADNESS mad_freq executable and dalton to set the frequencies for the response property calculations.

Generate frequency.json file

from pathlib import Path
from quantumresponsepro import DatabaseGenerator

database_path = Path('path/to/directory')
dg = DatabaseGenerator(database_path)
excited_json = dg.get_dalton_excited_json('hf', ['aug-cc-pVDZ'], run=True)
try:
    freq_json = dg.get_frequency_json('hf', 'dipole', 'aug-cc-pVTZ', ), .5
except KeyError as k:
    excited_json = dg.get_dalton_excited_json('hf', ['aug-cc-pVTZ'], run=True)
    freq_json = dg.get_frequency_json('hf', 'dipole', 'aug-cc-pVTZ', ), .5
    excited_json = dg.get_dalton_excited_json('hf', ['aug-cc-pVDZ'], run=True)

In this example, we generate a frequency.json file for the HF functional, dipole response, and aug-cc-pVTZ basis set. The frequency.json file defines the frequencies for response property calculations for a specific functional and operator. The frequencies are generated from the excited-state energies of the basis set.

The get_frequency_json function first checks if the dalton_excited.json file exists and whether data for a specific functional and basis set is present. If found, it overwrites the frequency.json file. Otherwise, it raises an exception.

Before running the get_frequency_json function, make sure to run the get_dalton_excited_json function for the desired functional and basis set, as shown in the example.

Running Response Calculations

Now that a frequency.json file is generated you are ready to compute response properties with MADNESS or Dalton.

Running MADNESS Response Calculations with mad_freq

To run MADNESS response calculations, use the mad_freq executable. The

1. Create a json file for the database properties. The json file should contain the following properties:

After generating the MADNESS and Dalton files, you can use the following code to generate the output response dataframe:

from quantumresponsepro import (
    BasisMRADataCollection,
)

response_dataframes = BasisMRADataCollection(dir)

For more detailed examples, please refer to the examples directory and the provided Jupyter notebooks.

Contributing We welcome contributions to QuantumResponsePro! Please fork the repository, create a new branch with your changes, and submit a pull request. Make sure to follow the established code style and add appropriate tests and documentation for your changes.

License

QuantumResponsePro is released under the MIT License. .