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Added Nexus examples for H2O and LiH using different pseudopotentials 

git-svn-id: https://subversion.assembla.com/svn/qmcdev/trunk@6559 e5b18d87-469d-4833-9cc0-8cdfa06e9491
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William Parker 2015-08-19 15:42:16 +00:00
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manual/examples.tex
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\chapter{Examples}
\label{chap:examples}
\textbf{WARNING: THESE EXAMPLES ARE NOT CONVERGED! YOU MUST CONVERGE PARAMETERS (SIMULATION CELL SIZE, JASTROW PARAMETER NUMBER/CUTOFF, TWIST NUMBER, DMC TIME STEP, DFT PLANE WAVE CUTOFF, DFT K-POINT MESH, ETC.) FOR REAL CALCUATIONS!}
The following examples should run in serial on a modern workstation in a few hours.
\section{Using Nexus}
\subsection{H$_2$O Molecule with Quantum ESPRESSO Orbitals}
With BFD pseudopotentials (see Section \ref{subsec:BFD}) for O and H in a subdirectory named \texttt{pseudopotentials} (both UPF and FSAtom xml formats, named \texttt{O.BFD.upf}, \texttt{O.BFD.xml}, \texttt{H.BFD.upf}, and \texttt{H.BFD.xml}, respectively) and the following XYZ file (named \texttt{H2O.xyz})
\begin{lstlisting}
3
O 0.0000000000e+00 0.0000000000e+00 0.0000000000e+00
H 0.0000000000e+00 -1.4308249289e+00 1.1078707576e+00
H 0.0000000000e+00 1.4308249289e+00 1.1078707576e+00
\end{lstlisting}
in the working directory, a Python script using Nexus to generate the orbitals using Quantum ESPRESSO, then run QMCPACK to optimize the Jastrow and then do DMC for H$_2$O in a box is:
%\begin{minipage}{\linewidth}
\begin{lstlisting}[caption=Nexus example for H$_2$O using Quantum ESPRESSO orbitals and BFD pseudopotentials]
#! /usr/bin/env python
from project import settings,Job,run_project
from project import Structure,PhysicalSystem
from project import generate_pwscf
from project import generate_pw2qmcpack
from project import generate_qmcpack,vmc,loop,linear,dmc
# General Settings (Directories For I/O, Machine Type, etc.)
settings(
pseudo_dir = 'pseudopotentials',
runs = 'runs',
results = 'results',
sleep = 3,
generate_only = 0,
status_only = 0,
machine = 'ws1',
)
# Executables (Indicate Path If Needed)
pwscf = 'pw.x'
pw2qmcpack = 'pw2qmcpack.x'
qmcpack = 'qmcapp'
# Pseudopotentials
dft_pps = ['O.BFD.upf','H.BFD.upf']
qmc_pps = ['O.BFD.xml','H.BFD.xml']
# Job Definitions (MPI Tasks, MP Threading, PBS Queue, Time, etc.)
scf_job = Job(app=pwscf,serial=True)
p2q_job = Job(app=pw2qmcpack,serial=True)
opt_job = Job(threads=4,app=qmcpack,serial=True)
dmc_job = Job(threads=4,app=qmcpack,serial=True)
# System To Be Simulated
structure = Structure()
structure.read_xyz('H2O.xyz')
structure.bounding_box(
box = 'cubic',
scale = 1.5
)
structure.add_kmesh(
kgrid = (1,1,1),
kshift = (0,0,0)
)
H2O_molecule = PhysicalSystem(
structure = structure,
net_charge = 0,
net_spin = 0,
O = 6,
H = 1,
)
sims = []
# DFT SCF To Generate Converged Density
scf = generate_pwscf(
identifier = 'scf',
path = '.',
job = scf_job,
input_type = 'scf',
system = H2O_molecule,
pseudos = dft_pps,
ecut = 50,
ecutrho = 400,
conv_thr = 1.0e-5,
mixing_beta = 0.7,
mixing_mode = 'local-TF',
degauss = 0.001
)
sims.append(scf)
# Convert DFT Wavefunction Into HDF5 File For QMCPACK
p2q = generate_pw2qmcpack(
identifier = 'p2q',
path = '.',
job = p2q_job,
write_psir = False,
dependencies = (scf,'orbitals')
)
sims.append(p2q)
# QMC Optimization Parameters - Coarse Sampling Set
linopt1 = linear(
energy = 0.0,
unreweightedvariance = 1.0,
reweightedvariance = 0.0,
timestep = 0.4,
samples = 8192,
warmupsteps = 50,
blocks = 64,
substeps = 4,
nonlocalpp = True,
usebuffer = True,
walkers = 1,
minwalkers = 0.5,
maxweight = 1e9,
usedrift = True,
minmethod = 'quartic',
beta = 0.0,
exp0 = -16,
bigchange = 15.0,
alloweddifference = 1e-4,
stepsize = 0.2,
stabilizerscale = 1.0,
nstabilizers = 3
)
# QMC Optimization Parameters - Finer Sampling Set
linopt2 = linopt1.copy()
linopt2.samples = 16384
# QMC Optimization
opt = generate_qmcpack(
identifier = 'opt',
path = '.',
job = opt_job,
input_type = 'basic',
system = H2O_molecule,
twistnum = 0,
bconds = 'nnn',
pseudos = qmc_pps,
jastrows = [('J1','bspline',8,4),
('J2','bspline',8,4)],
calculations = [loop(max=4,qmc=linopt1),
loop(max=4,qmc=linopt2)],
dependencies = (p2q,'orbitals')
)
sims.append(opt)
# QMC VMC/DMC With Optimized Jastrow Parameters
qmc = generate_qmcpack(
identifier = 'dmc',
path = '.',
job = dmc_job,
input_type = 'basic',
system = H2O_molecule,
pseudos = qmc_pps,
bconds = 'nnn',
jastrows = [],
calculations = [
vmc(
walkers = 1,
samplesperthread = 64,
stepsbetweensamples = 1,
substeps = 5,
warmupsteps = 100,
blocks = 1,
timestep = 1.0,
usedrift = False
),
dmc(
minimumtargetwalkers = 128,
reconfiguration = 'no',
warmupsteps = 100,
timestep = 0.005,
steps = 10,
blocks = 200,
nonlocalmoves = True
)
],
dependencies = [(p2q,'orbitals'),(opt,'jastrow')]
)
sims.append(qmc)
run_project(sims)
\end{lstlisting}
%\end{minipage}
\subsection{LiH Crystal with Quantum ESPRESSO Orbitals}
With CASINO-formatted Trail-Needs pseudopotentials (see Section \ref{subsec:CASINO}) for O and H in a subdirectory named \texttt{pseudopotentials} (both UPF and CASINO formats, named \texttt{O.TN-DF.upf}, \texttt{O.pp.data}, \texttt{H.TN-DF.upf}, and \texttt{H.pp.data}, respectively), a Python script using Nexus to generate the orbitals using Quantum ESPRESSO, then run QMCPACK to optimize the Jastrow and then do DMC for LiH with periodic boundary conditions is:
\begin{lstlisting}[caption=Nexus example for bulk LiH using Quantum ESPRESSO orbitals and CASINO pseudopotentials]
#! /usr/bin/env python
from project import settings,Job,run_project
from project import generate_physical_system
from project import generate_pwscf
from project import generate_pw2qmcpack
from project import generate_qmcpack,vmc,loop,linear,dmc
# General Settings (Directories For I/O, Machine Type, etc.)
settings(
pseudo_dir = 'pseudopotentials',
runs = 'runs',
results = 'results',
sleep = 3,
generate_only = 1,
status_only = 0,
machine = 'ws1',
)
# Executables (Indicate Path If Needed)
pwscf = 'pw.x'
pw2qmcpack = 'pw2qmcpack.x'
qmcpack = 'qmcapp'
# Pseudopotentials
dft_pps = ['Li.TN-DF.upf','H.TN-DF.upf']
qmc_pps = ['Li.pp.data','H.pp.data']
# Job Definitions (MPI Tasks, MP Threading, PBS Queue, Time, etc.)
scf_job = Job(app=pwscf,serial=True)
nscf_job = Job(app=pwscf,serial=True)
p2q_job = Job(app=pw2qmcpack,serial=True)
opt_job = Job(threads=4,app=qmcpack,serial=True)
dmc_job = Job(threads=4,app=qmcpack,serial=True)
# System To Be Simulated
rocksalt_LiH = generate_physical_system(
lattice = 'cubic',
cell = 'primitive',
centering = 'F',
atoms = ('Li','H'),
basis = [[0.0,0.0,0.0],
[0.5,0.5,0.5]],
basis_vectors = 'conventional',
constants = 7.1,
units = 'B',
kgrid = (17,17,17),
kshift = (1,1,1),
net_charge = 0,
net_spin = 0,
Li = 1,
H = 1,
)
sims = []
# DFT SCF To Generate Converged Density
scf = generate_pwscf(
identifier = 'scf',
path = '.',
job = scf_job,
input_type = 'scf',
system = rocksalt_LiH,
pseudos = dft_pps,
ecut = 450,
ecutrho = 1800,
conv_thr = 1.0e-10,
mixing_beta = 0.7,
)
sims.append(scf)
# DFT NSCF To Generate Wave Function At Specified K-points
nscf = generate_pwscf(
identifier = 'nscf',
path = '.',
job = nscf_job,
input_type = 'nscf',
system = rocksalt_LiH,
pseudos = dft_pps,
ecut = 450,
ecutrho = 1800,
conv_thr = 1.0e-10,
mixing_beta = 0.7,
kgrid = (1,1,1),
kshift = (0,0,0),
dependencies = (scf,'charge-density')
)
sims.append(nscf)
# Convert DFT Wavefunction Into HDF5 File For QMCPACK
p2q = generate_pw2qmcpack(
identifier = 'p2q',
path = '.',
job = p2q_job,
write_psir = False,
dependencies = (nscf,'orbitals')
)
sims.append(p2q)
# QMC Optimization Parameters - Coarse Sampling Set
linopt1 = linear(
energy = 0.0,
unreweightedvariance = 1.0,
reweightedvariance = 0.0,
timestep = 0.4,
samples = 8192,
warmupsteps = 50,
blocks = 64,
substeps = 4,
nonlocalpp = True,
usebuffer = True,
walkers = 1,
minwalkers = 0.5,
maxweight = 1e9,
usedrift = True,
minmethod = 'quartic',
beta = 0.0,
exp0 = -16,
bigchange = 15.0,
alloweddifference = 1e-4,
stepsize = 0.2,
stabilizerscale = 1.0,
nstabilizers = 3
# QMC Optimization Parameters - Finer Sampling Set
linopt2 = linopt1.copy()
linopt2.samples = 16384
# QMC Optimization
opt = generate_qmcpack(
identifier = 'opt',
path = '.',
job = opt_job,
input_type = 'basic',
system = rocksalt_LiH,
twistnum = 0,
bconds = 'ppp',
pseudos = qmc_pps,
jastrows = [('J1','bspline',8),
('J2','bspline',8)],
calculations = [loop(max=4,qmc=linopt1),
loop(max=4,qmc=linopt2)],
dependencies = (p2q,'orbitals')
)
pp = opt.input.get('pseudos')
pp.Li.format='casino'
pp.Li['l-local']='s'
pp.Li.nrule=2
pp.Li.lmax=2
pp.Li.cutoff=2.19
pp.H.format='casino'
pp.H['l-local']='s'
pp.H.nrule=2
pp.H.lmax=2
pp.H.cutoff=0.50
sims.append(opt)
# QMC VMC/DMC With Optimized Jastrow Parameters
qmc = generate_qmcpack(
identifier = 'dmc',
path = '.',
job = dmc_job,
input_type = 'basic',
system = rocksalt_LiH,
pseudos = qmc_pps,
bconds = 'ppp',
jastrows = [],
calculations = [
vmc(
walkers = 1,
samplesperthread = 64,
stepsbetweensamples = 1,
substeps = 5,
warmupsteps = 100,
blocks = 1,
timestep = 1.0,
usedrift = False
),
dmc(
minimumtargetwalkers = 128,
reconfiguration = 'no',
warmupsteps = 100,
timestep = 0.005,
steps = 10,
blocks = 200,
nonlocalmoves = True
)
],
dependencies = [(p2q,'orbitals'),(opt,'jastrow')]
)
pp = qmc.input.get('pseudos')
pp.Li.format='casino'
pp.Li['l-local']='s'
pp.Li.nrule=2
pp.Li.lmax=2
pp.Li.cutoff=2.37
pp.H.format='casino'
pp.H['l-local']='s'
pp
pp.H.lmax=2
pp.H.cutoff=0.50
sims.append(qmc)
run_project(sims)
\end{lstlisting}

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manual/pseudopotentials.tex
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@ -12,6 +12,7 @@ ppconvert --upf_pot Li.upf --xml Li.xml
\end{lstlisting}
\subsection{Burkatzki-Filippi-Dolg}
\label{subsec:BFD}
Burkatzki \textit{et al.} developed a set of energy-consistent pseudopotenitals for use in QMC~\cite{Burkatzki07,Burkatzki08}, available at \url{http://www.burkatzki.com/pseudos/index.2.html}. To convert for use in QMCPACK, select a pseudopotential (choice of basis set is irrelevant to conversion) in GAMESS format and copy the ending (pseudopotential) lines beginning with(element symbol)-QMC GEN: