MPH, or Many-Particle Holstein is essentially just a Python translation of the exciton1D code written by Dr. Nicholas Hestand (https://github.com/nicholashestand/exciton1d). The code constructs and diagonalizes the Frenkel-Holstein Hamiltonian for a molecular aggregate in the basis of 1- and 2-particle excitonic and charge-transfer states, and uses the resulting eigenvalues and eigenvectors to compute the absorption spectrum. In the future, I plan on adding a few things, including a PDF showing derivations for all matrix elements, multimode vibrations and anharmonicity, 3-particle and higher terms, and higher-order spectroscopy simulations, such as pump-prope and 2D electronic spectroscopy.
Create a conda environment with Numpy, Matplotlib, and Numba installed. Clone this repository and run
make. The given makefile will install the package locally and it can be used as shown in the examples.
For convenience, a yml file is added so that all you need to do is conda env create -f environment.yml.
The environment name by default is mph_env. Activate with conda activate mph_env and run make.