How to run SIESTA
Víctor M. García Suárez
Gollum School. MOLESCO network
20-May-2015
Partially based on a talk by Javier Junquera
Gollum School. MOLESCO network
Outline
- Developers
- General features
- FDF. Input variables
- How to run the code
- Output files
- Saving and reading information
- Pseudopotential generation
- Visualization tools
Víctor M. García Suárez. Oviedo. 20-May-2015
Gollum School. MOLESCO network
Developers
http://departments.icmab.es/leem/siesta
Víctor M. García Suárez. Oviedo. 20-May-2015
Gollum School. MOLESCO network
General features of Siesta
Born-Oppenheimer approximation. Structure relaxation (CG) and
molecular dynamics (MD)
Density functional theory (DFT). LDA, GGA, VdW functionals
Pseudopotentials. Norm-conserving
Linear combination of atomic orbitals (LCAO). Numerical atomic
orbitals. Order N (sparse matrices)
Numerical evaluation of the matrix elements (Smn, Hmn)
Víctor M. García Suárez. Oviedo. 20-May-2015
Gollum School. MOLESCO network
To run Siesta you need:
1. Access to the executable file
Compile Siesta with your favourite compiler
Watch out for BLAS and LAPACK libraries
Serial versus parallel compilation
2. An input file, called whatever.fdf
Written in Flexible Data Format (A. García and J. M. Soler)
Contains:
Physical data of the system
Variables to control the approximations
3. A pseudopotential file for all different elements in the input file
Unformatted binary (.vps)
Formatted ASCII (.psf) (more portable and easy to read)
Víctor M. García Suárez. Oviedo. 20-May-2015
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Features of the Flexible Data Format language. FDF-I
Data can be given in any order
Data can be omitted in favour of default values
Syntax: ‘data label’ followed by its value
Character string:
SystemLabel
h2o
Integer:
NumberOfAtoms
3
Real:
PAO.SplitNorm
0.15
Logical:
SpinPolarized
.false.
Physical magnitudes:
LatticeConstant
5.43 Ang
Víctor M. García Suárez. Oviedo. 20-May-2015
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Features of the Flexible Data Format language. FDF-II
Labels are case insensitive and characters -_. are ignored
LatticeConstant is equivalent to lattice_constant
Text following # is a comment
Logical values:
T, .true., true, yes
F, .false., false, no
Character strings, not in apostrophes
Complex data structures: blocks
%block label
…
%endblock label
Víctor M. García Suárez. Oviedo. 20-May-2015
Gollum School. MOLESCO network
Features of the Flexible Data Format language. FDF-III
Physical magnitudes: real number followed by its units
Many physical units are recognized for each magnitude
Length: m, cm, nm, Ang, bohr
Energy: eV, Rydberg
Automatic conversion to the ones internally required.
Allows to ‘include’ other FDF files or redirect the search to another file
block PAO.Basis
< BaTiO3basis.fdf
AtomicCoordinatesAndAtomicSpecies
< Interface.coor
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Clasification of the basic input variables
1. General system descriptors
2. Structural and geometrical variables
3. Basis set generation
4. Solution method
5. Method to solve the Hamiltonian
6. Control of the self-consistent cycle
7. Structural relaxation or molecular dynamics
8. Analysis of the results
9. Parallelization
Víctor M. García Suárez. Oviedo. 20-May-2015
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General system descriptors
SystemName: descriptive name of the system
SystemName Si bulk, diamond structure
If properly updated, this variable might contain very useful
information to know what has been run
SystemLabel: nickname of the system to name output files
SystemLabel Si
(After a succesful run, you should have files like
Si.DM :
Density matrix
Si.XV:
Final positions and velocities
Si.bands:
Electronic band structure
Si.DOS:
Total density of states
...and many more, depending on your requests)
Víctor M. García Suárez. Oviedo. 20-May-2015
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Structural and geometrical variables:
number of atoms and species in the simulation box
NumberOfAtoms: number of atoms in the simulation box
NumberOfAtoms
2
NumberOfSpecies: number of different atomic species
NumberOfSpecies 1
ChemicalSpeciesLabel: spcecify the different chemical species
%block ChemicalSpeciesLabel
1 14 Si
%endblock ChemicalSpeciesLabel
All these variables are MANDATORY
Víctor M. García Suárez. Oviedo. 20-May-2015
From 1 to NumberOfSpecies
Atomic number of a given species
plus a label to identify
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Structural and geometrical variables:
lattice constant and lattice vectors
LatticeConstant: real length to define the scale of the lattice vectors
LatticeConstant 5.43 Ang
LatticeVectors (also LatticeParameters): read as a matrix, 1 Vect. → 1 line
(units of LatticeConstant)
%block LatticeVectors
0.000 0.500 0.500
0.500 0.000 0.500
0.500 0.500 0.000
%endblock LatticeVectors
Coordinates. Followed by the species index
%block AtomicCoordinatesAndAtomicSpecies
0.000 0.000 0.000 1 Si
1
0.000 0.000 1.280 1 Si
2
%endblock AtomicCoordinatesAndAtomicSpecies
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Basis set definition
Straightforward definition of the basis
%block PAO.BasisSizes
C SZ
%endblock PAO.BasisSizes
Full definition of the basis
%block PAO.Basis
C 2
n=2 0 2
7.0 0.0
n=2 1 2
7.0 0.0
%endblock PAO.Basis
Víctor M. García Suárez. Oviedo. 20-May-2015
Number of shells
Principal quantum number (n),
angular quantum number (l)
and number of z
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Real-space and k-grids
S m n   m n
Real-space mesh
MeshCutoff
150 Ry
Hmn
k-grid (Monkhorst-Pack)
%block kgrid_Monkhorst_Pack
1 0 0 0.0
0 1 0 0.0
0 0 90 0.0
%endblock kgrid_Monkhorst_Pack
k-grid (energy cut-off)
kgrid_cutoff
20 Ang
Víctor M. García Suárez. Oviedo. 20-May-2015
 * 

  dr m (r )n (r )
 *  ˆ

ˆ
  m H n   dr m (r ) Hn (r )
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Exchange and correlation functional
DFT
XC.Functional
XC.authors
LDA
CA
PZ
GGA
PW92
PBE
revPBE PBEsol RPBE WC BLYP
CA
 Ceperley-Alder
PZ
 Perdew-Zunger
LDA  Local Density Approximation
PW92
 Perdew-Wang-92
GGA  Generalized Gradient
Approximation
PBE
 Perdew-Burke-Ernzerhof
WC
 Wu-Cohen
BLYP
 Becke-Lee-Yang-Parr
SpinPolarized
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The density matrix, a basic ingredient in Siesta
Expansion of the eigenvectors in a basis of localized atomic orbitals


n (r )   cnm m (r )
Secular equation:
m
The electron density is given by

 2
n ( r )   n ( r ) f n
( H m n  E S m n )c m

n
n
fn is the occupation of state n
n
Inserting the expansion into the definition of the density


* 
n(r )    m n m (r )n (r )
mn
The density matrix is then defined as follows:
m n   c c fn
*
nm nn
n
Víctor M. García Suárez. Oviedo. 20-May-2015
Controls the SCF convergence
Used to restart calculations
n
0
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The Kohn-Sham equations must be solved self-consistently
The potential (input) depends on the density (output)
Initial guess

 
n (r ), n (r )

Calculate the effective potential



Veff (r )  Vext (r )  VHartree (r )  Vxc[n , n ]

Solve the KS equation
 1 2
    
  
 2   Veff (r )n (r )   n n (r )


Calculate electron density

 2
n ( r )   n ( r ) f n
No
Yes
Self-consistent?
n
m n   m n   DM.Tolerance
max
mn
out
Víctor M. García Suárez. Oviedo. 20-May-2015
Output quantities
Energy, forces,
stresses…
in
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Control of the convergence
Maximum number of iterations
MaxSCFIterations
1000
Pulay mixing
DM.NumberPulay
DM.MixingWeight

n 1
in
 
n 1
out
5
0.1
 (1   ) 
n
in
Tolerance
DM.Tolerance
Víctor M. García Suárez. Oviedo. 20-May-2015
1.d-4
N
   i 
n
in
i 1
N
( n  N i )
in
n
( n  N i )
 out
   i  out
i 1
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Relaxation of the coordinates
Type of run (CG, MD)
MD.TypeOfRun
cg
Number of steps, maximum displacement and force tolerance
MD.NumCGsteps
MD.MaxCGDispl
MD.MaxForceTol
1000
0.2 Bohr
0.05 eV/Ang
Variable cell
MD.VariableCell
T
MD.PreconditionVariableCell 5.0 Ang
MD.MaxStressTol
1.0 GPa
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Saving and reading information: restarting files
Some information is stored by Siesta to restart simulations from:
FDF tag to reuse
Name of the file
Density matrix
DM.UseSaveDM
SystemLabel.DM
Atomic positions and Vel.
MD.UseSaveXV
SystemLabel.XV
Conjugate gradient history
MD.UseSaveCG
SystemLabel.CG
Localized W. Funct. (Order-N) ON.UseSaveLWF
Logical variables
Very useful to save a lot of time
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SystemLabel.LWF
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Saving and reading information: information needed as
Input for various post-processing programs
For example, to visualize:
FDF tag to reuse
Name of the file
Total charge density
SaveRho
SystemLabel.RHO
Deformation charge density
SaveDeltaRho
SystemLabel.DRHO
Electrostatic potential
SaveElectrostaticP… SystemLabel.VH
Total potential
SaveTotalPotential
Local density of states
LocalDensityOfStates SystemLabel.LDOS
Charge density contours
WriteDenchar
SystemLabel.DIM
Atomic coordinates
WriteCoorXmol
SystemLabel.xyz
Animation of MD
WriteDXMol
SystemLabel.ANI
Logical variables
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SystemLabel.VT
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How to run the serial version of Siesta
To run the serial version:
[path]siesta < myinput > myoutput
To see the output while it runs
[path]siesta < myinput |tee myouput
To run the job in the background add &
[path]siesta < myinput > myoutput &
To see the information dumped in the output file during the run:
tail -f myoutput
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Output: the header
Information about:
- The version of Siesta
- The compiler
- Compilation flags
- Mode (serial or parallel)
- Date and time when the run starts
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Useful to reproduce the
results of a simulation
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Output: dumping the input file
Exact copy of the input file
Víctor M. García Suárez. Oviedo. 20-May-2015
Useful to reproduce the
results of a simulation
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Output: processing the input
The input file is digested
Siesta prints out the value
of some variables (some
of them might take the
default value)
A complete list of the
parameters used,
including default values,
can be found in the file
fdf.log
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Output: coordinates, cell and k-samling
Coordinates, cell
vectors and k cutoff
and mesh
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Output: first molecular dynamic (MD) or conjugate gradient
(CG) step
Real space mesh
and energies
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Output: forces and stress tensor
WriteForces (logical): write the forces to the output file at the end of
every MD or relaxation step
The forces of the last step can be found in the file SystemLabel.FA
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Output: decomposition of the energy
Different types of energy
that have been calculated
(ionic, neutral atom,
kinetic, XC, free energy,
etc)
Víctor M. García Suárez. Oviedo. 20-May-2015
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Output: timer. How many times (and how much time) the
code has gone through the most important subroutines
Useful to optimize the
performance of the code
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Pseudopotential generation
The pseudopotential is generated with the atom program
Edit the makefile and include the Fortran compiler after the FC
variable. The compiler flags can also be defined after FLAGS
The generation of the pseudopotential and other data and plotting
files is done with the scripts ae.sh (all electrons), pg.sh
(pseudopotential) and pt.sh tests
The scripts need to know where the atm program and other scritps
are located. The simplest way of doing this is writing the its
location after the DEFAULT_DIR and default variable. For instance:
DEFAULT_DIR=../../../Pseudo.3.3/atom/Tutorial/Utils (*)
default="../../Pseudo.3.3/atom/atm”
An additional “../” is needed here because the script searches
these scripts from the generated directory
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All-electron calculation
ae.sh generates the all-electron eigenvalues, wave functions, total
energy and charge densities
Input file (for instance Si): Si.ae.inp
ae Si ground state all-electron
Si ca
0.0
3 2
3 0 2.00
0.00
3 1 2.00
0.00
Core shells
Valence shells
Generation: ae.sh Si.ae.inp
Produces the directory Si.ae with all information
Plotting: gnuplot -persist “.gnuplot or .gps file”
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Pseudopotential calculation
pg.sh generates the eigenvalues, wave functions, total energy and
charge densities
Input file (for instance Si): Si.inp
Core corrections?
pg Silicon
tm2
3.0
# PS flavor, logder R
n=Si
c=car
# Symbol, XC flavor,{ |r|s}
0.0
0.0
0.0
0.0
0.0
0.0
3 4
# norbs_core, norbs_valence
3 0 2.00
0.00
# 3s2
3 1 2.00
0.00
# 3p2
3 2 0.00
0.00
# 3d0
4 3 0.00
0.00
# 4f0
1.90
1.90
1.90
1.90
0.00
0.00
# Last line (above):
# rc(s) rc(p) rc(d) rc(f) rcore_flag rcore
Core radius. If
negative or 0, the
5th number gives
the charge density
Generation: pg.sh Si.inp
Produces the directory Si with all information and Si.vps (binary)
and Si.psf files
Víctor M. García Suárez. Oviedo. 20-May-2015
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Pseudopotential test
pt.sh performs a transferability test by comparing the all-electron
calculation to the generated pseuopotential with various charges in
the valence shells (different environments)
Input file (for instance Si): Si.test.inp
# A-E calculations
ae Si Test -- GS 3s2 3p2
Si ca
0.0
3 2
3 0 2.00
3 1 2.00
# Pseudopotential test calculations
pt Si Test -- GS 3s2 3p2
Si ca
0.0
3 2
3 0 2.00
3 1 2.00
Generation: pt.sh Si.test.inp Si.vps
Produces the directory Si.test with all information. Compares the
all-electron excitation energies (different configurations) and
eigenvalues
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Generated data
A lot of data is available in the generated directory
Charge densities
r(r)
Log. Der.
Pseudopot.
Fourier Trans.
From these graphs it is possible to see for instance if the core and
valence overlap, how the wave functions match if they are broad
enough and how smooth the pseudopotential is
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How are the radii chosen?
The radii of each channel (s, p, d, etc) have to be chosen in such a
way that the wave function and the pseudopotential are smooth
and broad inside the radii
If the radii increases the wave function becomes broader but the
transferability decreases
A good choice would start around radii closer to the maximum of
r(r). Longer radii go into the region where wave function overlaps
with the WF of other atoms
The radius of the core
corrections has to be
chosen so that the pseudo-core
charge density reproduces the
core charge density in the region
where the core and the valence
overlap
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Fe
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Summary of different tools for post-processing and
visualization
Denchar
Plrho
DOS, PDOS
DOS and PDOS
total
Fe, d
Macrowave
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XCrySDen
Fin
Siesta2Gollum interface
Víctor M. García Suárez
Gollum School. MOLESCO network
20-May-2015
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Outline
- What is needed from Siesta
- How to obtain the Siesta information
- Program files and structure
- How to compile the code
- How to run the code
- Generated files
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- What is needed from a Siesta calculation
Data
Number of spin components
Fermi energy
Information on the atomic orbitals
Transversal k-points
Hamiltonian and overlap matrices
Siesta files
 Orbitals and geneneral system
information
SystemLabel.HSX  Number of spin components, orbitals,
Hamiltonian and overlap matrices
SystemLabel.KP  k-points
SystemLabel.EIG  Fermi energy and eigenvalues
XX.Out
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- How that information can be obtained from Siesta
FDF flags to include in XX.fdf
SaveHS .true.
WriteEigenvalues
.true.
Generates the SystemLabel.HSX file
Generates the SystemLabel.EIG file
Default files
Siesta hould also generate by default the SystemLabel.KP file
Outuput file
The Siesta ouput, which has a lot of information, has to be redirected to a
XX.out file
$ siesta < SystemLabel.fdf |tee XX.out
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- Siesta2Gollum program files and structure
Directory
tools/interface-to-siesta
Files
Hsx_m.f90
Module that reads and processes the
Hamiltonian and overlap from the .HSX file
siesta2gollum.f90 Main program, which reads the rest of the
information and generates the
Extended_Molecule and Lead_i files
Makefile
Makes the siesta2gollum executable
(Linux and Mac)
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- How to compile the code
Fortran compiler
Edit the Makefile to specify the Fortran compiler after the FC (Fortran
compiler) variable
You can also specify the compiler flags after the FLAGS variable
Compilation in Linux or Mac
Type make. The code should compile and generate the siesta2gollum file
Compilation in Windows
Execute the following (with for instance the g95 compiler):
$ g95 siesta2gollum -o hsx_m.f90 siesta2gollum.f90
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- How to run the code. Generation of the Gollum files
Location
The siesta2gollum executable should be in the same directory where the
Siesta calculation has been run or linked to it
It can also be in a directory with just the .out, .HSX, .KP and .EIG files
Generation of the Extended_Molecule file
Siesta2gollum “XX.out file” “0”
For example, in a simulation of a BDT molecule between gold electrodes
where the Siesta output has been redirected to the BDT-Au.out file, type
the following:
$ siesta2gollum BDT-Au.out 0
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Generation of the Lead_i files
Siesta2gollum “XX.out file” “number between 1 and 123456789”
This tells siest2gollum to generate a number of Lead_i files, where “i”
runs to the numbers specified in the command line
For example, in a simulation of a gold lead which is going to be used in
electodes 1, 2 and 5 of a multiterminal simulation and which has been
redirected to the Au.out file, type the following:
$ siesta2gollum Au.out 125
This generates the following files:
Lead_1, Lead_2 and Lead_5
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- Generated files
File Extended_Molecule
There should be only one file in the simulation. Contains information
about the orbitals, spin, k-points, overlap and Hamiltonian of the
extended molecule.
It should contain the following data from the DFT calculation of the extended
molecule:
• nspin. Defines wether the calculation is spin-unpolarized (1) or
polarized (2)
• FermiE. Value of the Fermi energy at the extended molecule in eV.
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• iorb. Contains information about the orbitals used in the simulation. It
has as many rows as orbitals in the EM region.
- iorb(1): Atom to which orbital belongs.
- iorb(2): Principal quantum number n.
- iorb(3): Quantum number lz using real spherical harmonics.
- iorb(4): z-number (basis set with multiple zetas)
At the moment Gollum only uses iorb(1).
• kpoints_EM. Transverse k-poins used in the DFT simulation of the EM.
- kpoints(1): Value of kx.
- kpoints(2): Value of ky.
- kpoints(3): Weight in the k summation.
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• HSM. Contains the overlap S(k,i,j) and Hamiltonian H(k,i,j,s) for a given
transverse k-point, given orbital pairs (i,j) and spin s.
The number of columns is 7 if nspin = 1 or 9 if nspin = 2.
There are as many rows as non-zero overlap or Hamiltonian elements. If
for a given (k,i,j,s) all elements are zero, then this row is skipped.
- HSM(1): Defines the k-point number as defined in kpoints.
- HSM(2): Defines the orbital number i as defined in iorb.
- HSM(3): Defines the orbital number j as defined in iorb.
- HSM(4): Real part of S(k,i,j).
- HSM(5): Imaginary part of S(k,i,j).
- HSM(6): Real part of H(k,i,j) (nspin = 1) or H(k,i,j,1) (nspin = 2).
- HSM(7): Imaginary part of H(k,i,j) (nspin = 1) or H(k,i,j,1) (nspin = 2).
- HSM(8): Exists only if nspin = 2. Real part of H(k,i,j,2).
- HSM(9): Exists only if nspin = 2. Imaginary part of H(k,i,j,2).
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Files Lead_i
There should be one of these files for each lead. The file will be read and
used if the corresponding variable leadp(3) is set to ±1.
It should contain the following data from the DFT calculation of the
leads:
• kpoints_Lead. Transverse k-poins used in the DFT simulation of the lead.
It must be given because the ordering of the k-points in the DFT
simulation of the Leads and the EM need not to coincide.
- kpoints(1): Value of kx.
- kpoints(2): Value of ky.
- kpoints(3): Weight in the k summation.
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Gollum School. MOLESCO network
• HSL. Contains the intra- and inter-PL overlap S0,1(k,i,j) and Hamiltonian
H0,1 (k,i,j,s) for a given transverse k-point, given orbital pairs (i,j) and spin s.
The number of columns is 11 if nspin = 1 or 15 if nspin = 2.
There are as many rows as non-zero overlap or Hamiltonian elements. If
for a given (k,i,j,s) all elements are zero, then this row is skipped.
- Ordering of the variable.
For nspin = 1: k i j Real[S0] Imag[S0] Real[H0] Imag[H0] Real[S1] Imag[S1]
Real[H1] Imag[H1]
For nspin = 2: k i j Real[S0] Imag[S0] Real[H0,1] Imag[H0,1] Real[H0,2] Imag[H0,2]
Real[S1] Imag[S1] Real[H1,1] Imag[H1,1] Real[H1,2] Imag[H1,2]
Víctor M. García Suárez. Oviedo. 20-May-2015
Fin