ultrafastultrafast 0.2.2

Package for simulating nonlinear optical spectra

ultrafastultrafast (UF2)

Code for simulating nonlinear optical spectroscopies of closed systems

Taking UF2 for a test drive

To try this package without installing or downloading the repository, follow this link to see an example jupyter notebook using Google's Colaboratory:
https://colab.research.google.com/github/peterarose/ultrafastultrafast/blob/master/UF2_Colab.ipynb (Note: Google's Coloaboratory gives a warning message about running Jupyter notebooks not authored by Google. When prompted by the warning, select "RUN ANYWAY", and then click "YES" when it asks you if you would like to reset all runtimes)

You should be able to run the whole notebook in about 20 seconds. The final plot produced at the bottom is Figure 6a from our paper (JCP: https://doi.org/10.1063/1.5094062). To run the whole notebook, find the dropdown menu "Runtime", click on it, and then select "Run All". Alternatively you can run each cell one at a time by typing Shift+Enter inside each cell.

How to install

You can install UF2 without downloading the source code by running
pip install ultrafastultrafast

(Note that UF2 is only written for python 3, so you may need to run pip3 install ultrafastultrafast if pip points to python 2 on your machine)

If you would like to install from the source code, you can clone this repository, navigate the repository directory, and run either
python setup.py install
or pip install .

Once installed, you should be able to use
import ultrafastultrafast as uf2
Note: you should not need to install this code in order to run any of the Jupyter notebooks included with this repository. This notebook can be used to get an idea of what this code does.

Dependencies

numpy
matplotlib
pyfftw
scipy
pyyaml

How to Use

To take UF2 for a test run without cloning this repository or installing it on your system, you can follow the above link to Google Colaboraty, or click on UF2_Colab.ipynb on the github page, and then click on the link "Open in Colab" at the top of the document. You should be able to run the entire Jupyter notebook in about 20 seconds. It produces the isotropically averaged TA spectra shown in Fig 6a of our paper, without the Gaussian linewidth

See the Jupyter notebook UF2_examples.ipynb for examples of how to use this code to generate perturbative wavepackets, and from there the desired nonlinear spectroscopic signal.

See the Jupyter notebook RKE_examples.ipynb for exmples of how to use the RK45-Euler method included with this code to generate perturbative wavepackets, and from there the desired nonlinear spectroscopic signal. The API for both the UF2 algorithm and the RKE algorithm is the same.

The folder example_folder includes the necessary files to simulate a two-level system coupled to a single harmonic mode of Huang-Rhys factor 0.4^2/2 = 0.08. (UF2 only - see Examples.ipynb)

The folder dimer_example includes the necessary parameters file, called simple_params.yaml, to run both the UF2 and RKE algorithms. Documentation describing how to edit and create simple_params.yaml files to simulate other vibronic systems will be added soon.

Simulating with your own system

To use UF2 to calculate spectra for other systems, you must create a folder for the system. You can use the Jupyter notebook Examples.ipynb to calcualte the transient absorption signal for your system by simply changing the file_path variable to specify the folder you created,and running the notebook. You can also use the class core.UF2 to write your own code to calculate any n-wave mixing process. See TA_example.py for a 4-wave mixing example, and TA_5th_order_example.py for a 6-wave mixing example.

The folder describing the system parameters must have the following two files:

eigenvalues.npz - a numpy archive with the following keys:

• 'GSM': containing all eigenvalues in the ground state manifold
• 'SEM': containing all eigenvalues in the singly excited manifold
• 'DEM' (optional): containing all eigenvalues in the doubly excited manifold

mu.npz - a numpy archive with the following keys:

• 'GSM_to_SEM': containing a 3d numpy array with indicies [i,j,k] of the dipole elements connecting the GSM eigenstates (index j) to the SEM eigenstates (index i). The thid index k = 0,1,2 corresonds to cartesian coordinates k = x,y,z
• 'SEM_to_DEM' (optional): containing a 3d numpy array with indicies [i,j,k] of the dipole elements connecting the SEM eigenstates (index j) to the DEM eigenstates (index i). The thid index k = 0,1,2 corresonds to cartesian coordinates k = x,y,z

Note: RKE is currently not compatible with systems other than those that can be described by the vibronic_eigenstates package included in this repository. That is not a fundamental limitation, but simply a limitation of the current implementation. Eventually the code will be updated to make it compatible with your own Hamiltonians, just as UF2 is already.