Commit f4249f87 authored by Marko Melander's avatar Marko Melander

Add missing files

parent 99424582
Pipeline #107557002 failed with stage
in 3 minutes and 24 seconds
from ase import Atoms
import numpy as np
from gpaw import GPAW, FermiDirac, Davidson, Mixer
from gpaw.cdft.cdft import CDFT
from gpaw.cdft.cdft_coupling import CouplingParameters
from gpaw.mpi import size
# Set the system
distance = 2.5
sys = Atoms('He2', positions = ([0.,0.,0.],[0.,0.,distance]))
# Calculator for the initial state
calc_a = GPAW(h = 0.2,
xc='PBE', symmetry='off',
occupations = FermiDirac(0., fixmagmom = True),
eigensolver = Davidson(3),
spinpol = True, #only spin-polarized calculations are supported
nbands = 4,
mixer = Mixer(beta=0.25, nmaxold=3, weight=100.0),
txt='He2+_initial_%3.2f.txt' % distance,
# Set initial state cdft
cdft_a = CDFT(calc = calc_a,
charge_regions = [[0]], # choose atom 0 as the constrained region
charges = [1], # constrain +1 charge
charge_coefs = [2.7], # initial guess for Vc
method = 'L-BFGS-B', # Vc optimization method
txt = 'He2+_initial_%3.2f.cdft' % distance, # cDFT output file
minimizer_options={'gtol':0.01}) # tolerance for cdft
#get cdft energy
# the same for the final state
calc_b = GPAW(h = 0.2,
occupations = FermiDirac(0., fixmagmom = True),
eigensolver = Davidson(3),
spinpol = True,
nbands = 4,
mixer = Mixer(beta=0.25, nmaxold=3, weight=100.0),
txt='He2+_final_%3.2f.txt' % distance,
cdft_b = CDFT(calc = calc_b,
charge_regions = [[1]], # choose atom 1
charges = [1], # constrained charge +1
charge_coefs = [2.7],
method = 'L-BFGS-B',
txt = 'He2+_final_%3.2f.cdft' % distance,
# Now for the coupling parameter
coupling = CouplingParameters(cdft_a, cdft_b, AE = False) # use pseudo orbitals
H12 = coupling.get_coupling_term() # use original cDFT method
.. module:: gpaw.cdft
.. _constrained_DFT:
Constrained DFT (cDFT)
cDFT is a method for build charge/spin localized or diabatic states with a
user-defined charge and/or spin state. As such cDFT, is a useful tool for
widening the scope of ground-state DFT to excitation processes, correcting for
self- interaction energy in current DFT functionals, excitation energy,
and electron transfer as well as parametrizing model Hamiltonians, for example.
Theoretical Background
The general cDFT methodology is reviewed in [#cdft1]_ and the publication
of the GPAW implementation is available in [#cdft2]_. In short, the cDFT works
by specifying an additional constraining term to the KS functional. The role of
this constraint is to enforce a user specified charge/spin state (`N_c`) on the
chosen regions of atoms. The constrained regions are specified by a weight
function `w(\mathbf{r})` and the strength of the constraining potential acting
on the specified region is `V_c`. With these definitions the new energy
functional with the constraint is
.. math:: F[n(\mathbf{r}), V_c] = E^{KS}[n] + \sum_c V_c \sum_{\sigma}\left(\int d\mathbf{r}w_c^{\sigma}(\mathbf{r}) n^{\sigma}(\mathbf{r})-N_c\right)
where `E^{KS}` is the Kohn-Sham energy, `c` specifies the region, and `\sigma`
is the spin variable. It is also seen that `V_c` is also a Lagrange multiplier.
The modified energy functional leads to an additional external potential
.. math:: v_{\rm eff}^{\sigma}=\dfrac{\delta E^{KS}[n(\mathbf{r})]}{\delta n(\mathbf{r})} + \sum_c V_cw_c^{\sigma}(\mathbf{r})
This is just a sum of the usual KS potential and the constraining potential
which is also used in the self-consistent calculation.
The constraint is further enforced by introducing the convergence criteria
.. math:: C \geq \bigg\lvert \sum_{\sigma} \int {\rm d}\mathbf{r} w_c^{\sigma}(\mathbf{r})n^{\sigma}(\mathbf{r}) -N_c \bigg\rvert \, ,\forall\, c
The `V_c` is self-consistently optimized so that the specified constraints are
satisfied. Formally, this is written as
.. math:: F\left[V_{c}\right]=\min _{n} \max _{\left\{V_{c}\right\}}\left[E^{\mathrm{KS}}[n(\mathbf{r})]+\sum_{c} V_{c}\left(\int \mathrm{d} \mathbf{r} w_{c}(\mathbf{r}) n(\mathbf{r})-N_{c}\right)\right]
`V_c` is obtained from
.. math:: \frac{\mathrm{d} F}{\mathrm{d} V_{c}}=\int \mathrm{d} \mathbf{r} w_{c}(\mathbf{r}) n(\mathbf{r})-N_{c}=0
In the end, one ends up with a modified electron/spin density localized
on the chosen atoms.
Notes on using cDFT
The weight function
In the GPAW implementation a Hirschfeld partition scheme with atom-centered
Gaussian functions is used. These Gaussian have two tunable parameters: the cut-off
`R_c` and the width `\mu`. If the constrained region cuts a covalent bond, the results
are sensitive to width parameter. There is no universal guide for choosing the
width in such cases. A sensible choice is to compute match the Gaussian-Hirschfeld
charges with e.g. Bader charges. The function :literal:`get_number_of_electrons_on_atoms`
helps in this process.
Optimizing `V_c`
Updating and optimizing the Lagrange multipliers `V_c` is achieved using Scipy
optimization routines. As it is easy to compute the gradient of the energy wrt `V_c`,
gradient based optimizers are recommended. The best performing optimizer seems
to be the :literal:`L-BFGS-B`. The accuracy of the optimization is controlled mainly
by the :literal:`minimizer_options={'gtol':0.01})` parameter which measurest the
error between the set and computed charge/spin value. A typical :literal:`gtol` value is around 0.01-0.1.
Choosing the constraint values and regions
Both charge and spin constraints can be specified. The charge constraints are
specified to neutral atoms: specifying :literal:`charges = [1]` constrains
the first regions to have a net charge of +1. Note, that if the usual DFT calculation
yields e.g. a Fe ion with charge +2.5, specifying the charge constraint +1 will
result in +1, not an additional hole on Fe with a charge state +3.5!
A constrained regions may contain several atoms and also several constrained regions
can be specified. However, converging more than two regions is usually very difficult.
Tips for converging cDFT calculations
Unfortunaly, the cDFT sometimes exhibits poor convergence.
1. Choose a meaningful constraints and regions
2. Try to provide a good initial guess for the `V_c`. In the actual calculation this initial guess given by the parameter :literal:`charge_coefs` or :literal:`spin_coefs`.
3. Use L-BFGS-B to set bounds for `V_c` by using :literal:`minimizer_options={'bounds':[min,max]})`.
4. Converge the underlying DFT calculation well i.e. use tight convergence criteria.
Constructing diabatic Hamiltonians
One of the main uses for cDFT is constructing diabatic Hamiltonians which utilize
cDFT states as the diabats. For instance, a 2x2 Hamiltonian matrix would have
diagonal elements `H_{11}` and `H_{22}` as well as off-diagonals `H_{12}` and `H_{21}`.
`H_{11}` and `H_{22}` values are given directly by cDFT energies
(not cDFT free energies). The off-diagonal coupling elements `H_{12}` and
`H_{21}` are also needed and often utilized in e.g. Configuration Interaction-cDFT,
in parametrizing model Hamiltonians or in computing non-adiabatic charge transfer rates.
Note, that all parameters need to be computed at the same geometry.
The coupling elements are computed using the CouplingParameters class. There are
several options and optional inputs. There are two main methods for computing
coupling elements: the original cDFT approach from [#cdft1]_ and a more general
overlap or Migliore method detailed in [#cdft3]_.
cDFT coupling constant
This method is the original approach in the context of cDFT. It works well for
simple system. For complex system it becomes quite sensitive to small errors
in the Lagrange multipliers and constraints, and the overlap method is recommended
instead. The inputs for the calculation are two cDFT objects with different constraints.
The coupling constant is computed using :literal:`get_coupling_term`.
Overlap coupling constant
This approach has been found to perform very well for a range of systems. However,
it has one major limitation: it can only be used if the two diabatic states have
different energies. In addition to the two cDFT states/objects also a normal DFT
calculator without any constraints is needed. The coupling constant is computed
using :literal:`get_migliore_coupling`.
Additional comments
In [#cdft2]_ the coupling constants were computed by computing all-electron wave
functions on a grid. However, this is quite slow and much faster implementation utilizing
only pseudo wave functions and atomic corrections has been added. For the tested cases
both give equally good values for the coupling constant. Hence, it is recommended
to use the pseudo wave functions which is set by :literal:`AE=False`.
The quantities needed for computing the coupling constants can be parallellized
only over the grid.
Example of hole transfer in `He_2^+`
Both the cDFT calculation and extraction of the coupling element calculation are
demonstrated for the simple `He_2^+` system.
.. literalinclude::
The most important cDFT results are found in the .cdft files. For instance, the
errors, iterations, and cDFT parameters are shown. Also, the energy can be found in this file.
The most relevant energy is the Final cDFT Energy (not the free energy).
.. [#cdft1] B. Kaduk, T. Kowalczyk, T. Van Voorhis,
`Constrained Density Functional Theory <>`_,
*Chem. Rev.*, **112** 321–370 (2012)
.. [#cdft2] M. Melander, E. Jońsson, J.J. Mortensen, T. Vegge,J.M. Garcia-Lastra,
`Implementation of Constrained DFT for Computing Charge Transfer Rates within the Projector Augmented Wave Method <>`_,
*J. Chem. Theory Comput.*, **12**, 5367−5378 (2016)
.. [#cdft3] A. Migliore,
`Nonorthogonality Problem and Effective Electronic Coupling Calculation: Application to Charge Transfer in π-Stacks Relevant to Biochemistry and Molecular Electronics <>`_,
*J. Chem. Theory Comput.*, **7**, 1712-1725 (2011)
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment