Easy Ab initio calculation with ASE-Siesta-Pyscf

No installation necessary, just download a ready to go container for any system, or run it into the cloud

Are we really on the Amazon cloud??



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cat /proc/cpuinfo

I do not have on my laptop an: Intel(R) Xeon(R) CPU E5-2676 v3 @ 2.40GHz

We first import the necessary libraries and define the system using ASE



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# import libraries and set up the molecule geometry
from ase.units import Ry, eV, Ha
from ase.calculators.siesta import Siesta
from ase import Atoms
import numpy as np
import matplotlib.pyplot as plt

H2O = Atoms('H2O', positions = [[-0.757,  0.586,  0.000],
                                [0.757,  0.586,  0.000],
                                [0.0, 0.0, 0.0]],
            cell=[20, 20, 20])

# visualization of the particle
from ase.visualize import view
view(H2O, viewer='x3d')

We can then run the DFT calculation using Siesta



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# enter siesta input and run siesta
siesta = Siesta(
    mesh_cutoff=150 * Ry,
    basis_set='DZP',
    pseudo_qualifier='lda',
    energy_shift=(10 * 10**-3) * eV,
    fdf_arguments={
        'SCFMustConverge': False,
        'COOP.Write': True,
        'WriteDenchar': True,
        'PAO.BasisType': 'split',
        'DM.Tolerance': 1e-4,
        'DM.MixingWeight': 0.1,
        'MaxSCFIterations': 300,
        'DM.NumberPulay': 4,
        'XML.Write': True})

H2O.set_calculator(siesta)
e = H2O.get_potential_energy()

The TDDFT calculations with PySCF-NAO



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# compute polarizability using pyscf-nao

siesta.pyscf_tddft(label="siesta", jcutoff=7, iter_broadening=0.15/Ha,
        xc_code='LDA,PZ', tol_loc=1e-6, tol_biloc=1e-7, freq = np.arange(0.0, 15.0, 0.05))



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# plot polarizability with matplotlib
%matplotlib inline

fig = plt.figure(1)
ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
ax1.plot(siesta.results["freq range"], siesta.results["polarizability nonin"][:, 0, 0].imag)
ax2.plot(siesta.results["freq range"], siesta.results["polarizability inter"][:, 0, 0].imag)

ax1.set_xlabel(r"$\omega$ (eV)")
ax2.set_xlabel(r"$\omega$ (eV)")

ax1.set_ylabel(r"Im($P_{xx}$) (au)")
ax2.set_ylabel(r"Im($P_{xx}$) (au)")

ax1.set_title(r"Non interacting")
ax2.set_title(r"Interacting")

fig.tight_layout()



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