Optical spectra from Sternheimer
We have just seen how to calculate optical spectra in the time domain with a finite perturbation, and in a frequency-domain, linear-response matrix formulation with the Casida equation. Now we will try a third approach, which is in the frequency domain and linear response but rather than using a pseudo-eigenvalue equation as in Casida, uses a self-consistent linear equation, the Sternheimer equation. This approach is also known as density-functional perturbation theory. It has superior scaling, is more efficient for dense spectra, and is more applicable to nonlinear response. One disadvantage is that one needs to proceed one frequency point at a time, rather than getting the whole spectrum at once. We will find we can obtain equivalent results with this approach for the optical spectra as for time propagation and Casida, by calculating the polarizability and taking the imaginary part.
Ground state
Before doing linear response, we need to obtain the ground state of the system, for which we can use the same input file as for Optical spectra from Casida, but we will use a tighter numerical tolerance, which helps the Sternheimer equation to be solved more rapidly. Unlike for Casida, no unoccupied states are required. If they are present, they won’t be used anyway.
CalculationMode = gs
UnitsOutput = eV_angstrom
Radius = 6.5*angstrom
Spacing = 0.24*angstrom
CH = 1.097*angstrom
%Coordinates
"C" | 0 | 0 | 0
"H" | CH/sqrt(3) | CH/sqrt(3) | CH/sqrt(3)
"H" | -CH/sqrt(3) |-CH/sqrt(3) | CH/sqrt(3)
"H" | CH/sqrt(3) |-CH/sqrt(3) | -CH/sqrt(3)
"H" | -CH/sqrt(3) | CH/sqrt(3) | -CH/sqrt(3)
%
ConvRelDens = 1e-7
Linear response
Change the CalculationMode to em_resp
and add
the lines below to the input file.
%EMFreqs
5 | 0*eV | 8*eV
9 | 10*eV | 12*eV
%
EMEta = 0.1*eV
Preconditioner = no
LinearSolver = qmr_dotp
ExperimentalFeatures = yes
The frequencies of interest must be specified, and we choose them based on the what we have seen from the Casida spectrum. The block above specifies 5 frequencies spanning the range 0 to 8 eV (below the resonances) and 9 frequencies spanning the range 10 to 12 eV (where there are peaks). If we didn’t know where to look, then looking at a coarse frequency grid and then sampling more points in the region that seems to have a peak (including looking for signs of resonances in the real part of the polarizability) would be a reasonable approach. We must add a small imaginary part ($\eta$) to the frequency in order to be able to obtain the imaginary part of the response, and to avoid divergence at resonances. The resonances are broadened into Lorentzians with this width. The larger the $\eta$, the easier the SCF convergence is, but the lower the resolution of the spectrum.
To help in the numerical solution, we turn off the preconditioner (which sometimes causes trouble here), and use a linear solver that is experimental but will give convergence much faster than the default one.
Spectrum
This Perl script can extract the needed info out of the files in the em_resp directory:
#!/bin/perl
use Math::Trig;
$c = 137.035999679;
$ls = `ls -d em_resp/freq*`;
@list = ($ls =~/em\_resp\/freq_([0-9.]*)/g);
@freqs = sort {$a <=> $b} @list;
print "# Energy (eV) Re alpha Im alpha Cross-section (A^2)\n";
format =
@###.### @####.####### @####.######## @####.########
$energy, $Re_alpha , $Im_alpha, $cross_section
.
foreach(@freqs)
{
if ($_ eq "0.0000")
{
$Im_alpha = 0;
}
else
{
$crossfile = `cat em_resp/freq_$_/cross_section`;
@crossbits = split(' ', $crossfile);
$energy = $crossbits[26];
$cross_section = $crossbits[27]; # isotropic average
$Im_alpha = $c * $cross_section / (4 * pi * $energy);
}
$alphafile = `cat em_resp/freq_$_/alpha`;
@alphabits = split(' ', $alphafile);
$Re_alpha = $alphabits[15];
write;
}
Our result is
# Energy (eV) Re alpha Im alpha Cross-section (A^2)
0.000 2.6399420 0.00000000 0.00000000
2.000 2.6982850 0.00041753 0.00007658
4.000 2.8971400 0.00101794 0.00037339
6.000 3.3481960 0.00234264 0.00128894
8.000 4.6913730 0.00996672 0.00731168
10.000 3.5491510 0.04353013 0.03991767
10.250 4.2029660 0.11944279 0.11226878
10.500 4.8277720 0.05017816 0.04831469
10.750 6.7248380 0.07195993 0.07093725
11.000 10.3714610 0.25085658 0.25304244
11.250 4.0375190 1.05741417 1.09086960
11.500 -0.6101760 0.21304879 0.22467363
11.750 4.2159620 0.26923934 0.29010257
12.000 -1.1343180 0.22131726 0.24354080