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https://github.com/cchandre/ocdm
Optical Centrifuge for Diatomic Molecules
https://github.com/cchandre/ocdm
amo hamiltonian matplotlib molecular-mechanics numpy python3 scipy symplectic-integrators sympy
Last synced: about 17 hours ago
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Optical Centrifuge for Diatomic Molecules
- Host: GitHub
- URL: https://github.com/cchandre/ocdm
- Owner: cchandre
- License: bsd-2-clause
- Created: 2022-02-13T10:35:43.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2023-06-09T18:12:34.000Z (over 1 year ago)
- Last Synced: 2024-11-10T21:11:46.418Z (about 2 months ago)
- Topics: amo, hamiltonian, matplotlib, molecular-mechanics, numpy, python3, scipy, symplectic-integrators, sympy
- Language: Python
- Homepage:
- Size: 905 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# OCDM
Optical Centrifuge for Diatomic Molecules (OCDM) - codes for the chlorine molecule Cl2
- [`ocdm_dict.py`](https://github.com/cchandre/OCDM/blob/main/ocdm_dict.py): to be edited to change the parameters of the OCDM computation (see below for a dictionary of parameters)
- [`ocdm.py`](https://github.com/cchandre/OCDM/blob/main/ocdm.py): contains the DiaMol class and main functions defining the OCDM dynamics (for Cl2)
- [`ocdm_modules.py`](https://github.com/cchandre/OCDM/blob/main/ocdm_modules.py): contains the methods to integrate the OCDM dynamics
- [`read_DiaMol_dissocation.m`](https://github.com/cchandre/OCDM/blob/main/read_DiaMol_dissociation.m): MATLAB script to produce the dissociation probability figure from the output files `DiaMol_dissociation.txt`
- [`read_DiaMol_trajectories.m`](https://github.com/cchandre/OCDM/blob/main/read_DiaMol_trajectories.m): MATLAB script to plot the trajectories from the output files `DiaMol.mat`
- [`read_DiaMol_pphi.m`](https://github.com/cchandre/OCDM/blob/main/read_DiaMol_pphi.m): MATLAB script to plot the distributions of *p**φ* values from the output files `DiaMol.mat`
Once [`ocdm_dict.py`](https://github.com/cchandre/OCDM/blob/main/ocdm_dict.py) has been edited with the relevant parameters, run the file as
```sh
python3 ocdm.py
```
or
```sh
nohup python3 -u ocdm.py &>ocdm.out < /dev/null &
```
The list of Python packages and their version are specified in [`requirements.txt`](https://github.com/cchandre/OCDM/blob/main/requirements.txt). The code is using NumPy, SciPy, SymPy and Matplotlib.
___
## Parameter dictionary
- *Method*: string
- 'plot_potentials': plot the potential ε(*r*) and polarizabilities α(*r*)
- 'plot_ZVS': plot zero velocity functions
- 'dissociation': computes the dissociation probability as a function of the amplitude *F*0 of the electric field
- 'trajectories': computes and displays the trajectories according to *type_traj*
- 'poincaré'; Poincaré section is *φ*=0 (mod 2 π) with *φ'*<0 in the plane (*r*,*p**r*) if *EventPS*='phi', and *p*r* =0 with *p*r*'<0 in the plane (*φ*,*p**φ*) if *EventPS*='phi'
- *dimension*: 2 or 3; dimension of the computation
- *F0*: float or array of floats; amplitude(s) *F*0 of the electric field, *E*(*t*) = *F*0 *f*(*t*) [e*x* cosΦ(*t*) + e*y* sinΦ(*t*)] cosω*t*, considered in the computation (atomic units)
- *Omega*: lambda function; values of the frequency of rotation of the polarisation axis, Ω=Φ'(*t*), as a function of time (atomic units)
- *envelope*: string ('const', 'sinus', 'trapez'); envelope function *f*(*t*) of the laser field
- *te*: array of 3 or 4 floats; duration of ramp-up, plateau, ramp-down and (optional) after pulse (in picoseconds)
- *Ntraj*: integer; number of trajectories to be integrated
- *r*: array of two floats; minimum and maximum values of *r* for the display of potentials, and range of *r* (atomic units) for the selection of initial conditions
- *initial_conditions*: string or array of floats;
- ['microcanonical', *E*0] for a microcanonical distribution with energy *E*0
- ['microcanonical_J', *n*, *J*] for a microcanonical distribution with initial energy *E*0 = ωe (*n*+1/2) + *B*e *J*(*J*+1)-*D*e
- array of shape (*Ntraj*, 2*dimension*) containing the initial conditions to be integrated
- *spread3D*: float; between 0 and 1; spread in angle theta for the initial conditions (only in the 3D case)
- *TimePS*: float; time (in picoseconds) at which the Poincaré section is computed (adiabatic approximation)
- *EnergyPS*: float; initial value of the energy (in atomic units) used in *Method*='poincaré'
- *EventPS*: string; 'phi' or 'pr'; choice of Poincaré section; Poincaré section is *φ*=0 (mod 2 π) with *φ'*<0 in the plane (*r*,*p**r*) if *EventPS*='phi', and *p*r* =0 with *p*r*'<0 in the plane (*φ*,*p**φ*) if *EventPS*='phi'
- *ode_solver*: string; 'RK45', 'RK23', 'DOP853', 'Radau', 'BDF', 'LSODA', 'Verlet', 'BM4'; method for the integration of trajectories
- 'RK45', 'RK23', 'DOP853', 'Radau', 'BDF', 'LSODA': (non-symplectic, variable time step); see [ivp_solve](https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.solve_ivp.html) for more details
- 'Verlet': Strang splitting or symplectic leap-frog integrator (symplectic, fixed time step, order 2); see [Wikipedia](https://en.wikipedia.org/wiki/Strang_splitting) for more details
- 'BM4' or 'BM6': BM64 or BM106 (symplectic, fixed time step, order 4 or 6) from [Blanes, Moan, J. Comput. Appl. Math. 142, 313 (2002)](https://doi.org/10.1016/S0377-0427(01)00492-7)
- NB: For Poincaré sections, ode_solver = 'RK45' by default
- *ode_tol*: array of two floats; absolute and relative tolerances [atol, rtol] for variable time-step integrators; see [ivp_solve](https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.solve_ivp.html) for more details
- *ode_step*: float; time step (in picoseconds) for the symplectic integrators 'Verlet' and 'BM4'
- *r_thresh*: float; threshold for the integration of trajectories; the integration is stopped whenever the distance *r* is larger than *r_thresh*
- *frame*: string; 'fixed' or 'rotating'; specifies in which frame the numerical integration is performed
- *type_traj*: array of 3 strings; ['all' or 'dissociated' or 'bounded', 'cartesian' or 'spherical', 'fixed' or 'rotating'] for the type of trajectories to be plotted and/or saved
- *dpi*: integer; dpi value for the figures
####
- *SaveData*: boolean; if True, the results are saved in a `.mat` file (with the type specified in 'type_traj'); if Method='dissociation', the trajectories are saved at *t*=0, *t*=*t*u, *t*=*t*u+*t*p and *t*=*t*u+*t*p+*t*d; if Method='trajectories', the trajectories are saved with 'dpi' equispaced times from *t*=0 to *t*=*t*u+*t*p+*t*d; NB: the dissociation probabilities are saved in a `.txt` file regardless of the value of SaveData
- *PlotResults*: boolean; if True, the results (for 'plot_potentials', 'plot_ZVS' and 'trajectories') are plotted right after the computation (with the type specified in 'type_traj' for 'trajectories')
- *Parallelization*: int or string; int is the number of cores to be used, 'all' for all of the cores
- *darkmode*: boolean; if True, plots are done in dark mode
---
Reference:
- C. Chandre, J. Pablo Salas, *Nonlinear dynamics of molecular super-rotors*, [Physical Review A](https://journals.aps.org/pra/abstract/10.1103/PhysRevA.107.063105) 107, 063105 (2023); [arXiv:2303.05090](https://arxiv.org/abs/2303.05090)
```bibtex
@article{PhysRevA.107.063105,
title = {Nonlinear dynamics of molecular superrotors},
author = {Chandre, C. and Salas, J. Pablo},
journal = {Phys. Rev. A},
volume = {107},
issue = {6},
pages = {063105},
numpages = {12},
year = {2023},
month = {Jun},
publisher = {American Physical Society},
doi = {10.1103/PhysRevA.107.063105},
url = {https://link.aps.org/doi/10.1103/PhysRevA.107.063105}
}
```
For more information:
