quTARANG

Welcome to quTARANG, a fast GPU enabled python solver to solve Gross-Pitaeskii equation.

Capablities of `quTARANG`

It is a solver developed to study turbulence in quantum systems specially in Bose-Einstein condensates. It can run on both GPU and CPU.

The documentation of code is available at quTARANG.

Dependencies

quTARANG depends on the following packages:

numpy
cupy (If you want to use GPU)
pathlib
h5py
matplotlib

Instllation

You can install quTARANG using pip

   pip install quTARANG

How to use:

To run a simulation:

Import the required libraries

    import numpy as xp #To run on gpu, import cupy as xp
    import quTARANG as qt

Set the parameters

Create an instance of the Params class and set the parameters according to your need. The parameters have been detailed in the documentation. Example:

# Create an instance of the Params class for storing parameters.
    par = qt.Params(N = [64, 64, 64],
                 L = [16, 16, 16],
                 g = 0.1,
                 dt = 0.001,
                 tmax = 5,
                 rms = [True, 0, 100])

Initiate GPE class Create an instance of the GPE class by passing the Params instance created previously.
```
# Create an instance of the GPE class.
   G = qt.GPE(par)
```
Set initial conditon

You can give initial condition in terms of wavefunction and potential by defining their functions and passing them to the function set_init.
```
    # Set wavefunction
    wfc = lambda x, y=0, z=0: (1/xp.pi**(1/4)) * xp.exp(-(x**2/2 + y**2/2 + z**2/2))
    
    # Set potential 
    pot = lambda x, y=0, z=0: (x**2 + y**2 + z**2)/2

    G.set_init(wfc, pot)
```
wfc function will be used to set the initial wavefunction and pot variable will be used to set the initial potential.
Start the simulation:
```
    G.evolve()
```

The results are stored as hdf5 files in the cwd or the path set by the user in the Params instance.

sachinrawat2207/quTARANG_dep

quTARANG

Capablities of quTARANG

Dependencies

Instllation

How to use:

Capablities of `quTARANG`