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https://github.com/molgw/molgw

Accurate many-body perturbation theory calculations of the electronic structure of molecules and clusters
https://github.com/molgw/molgw

bethe-salpeter dft fortran greens-functions hartree-fock molecule mpi quantum-mechanics scalapack tddft

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Accurate many-body perturbation theory calculations of the electronic structure of molecules and clusters

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README 

        
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#                 MOLGW

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Many-body perturbation theory for atoms, molecules, and clusters



## Getting started



This is a minimalistic README file.

Many more details can be found on the web site [molgw.org](http://www.molgw.org/).

A tutorial section exists there.



## Features



MOLGW implements the following schemes:

- Hartree-Fock

- LDA (PW, VWN)

- GGA (PBE, PW91, BLYP)

- potential-only meta-GGA (BJ, RPP)

- hybrid functionals (PBE0, B3LYP)

- double-hybrid functionals (PBE0-DH, PBE-QIDH, B2PLYP, and RSX-QIDH)

- screened hybrid functionals (HSE03, HSE06, CAM-B3LYP, and LC-BLYP)

- any user-developped range-separated hybrid based on wPBEH

- GW@HF or GW@DFT

- GW/PT2 density-matrix

- QSGW

- QSMP2

- MP2@HF (MP2 correlation energy used in double-hybrid DFT functionals)

- PT2@HF or PT2@DFT

- PT3@HF or PT3@DFT

- CI for few electrons 

- Linear-response TDDFT or TDHF

- Bethe-Salpeter equation

- real-time TDDFT

- X2C relativistic HF/DFT calculations

- HF/DFT+NOFT (MULLER, CGA, CA, GU, POWER, PNOF5, PNOF7, and GNOF)

- Molecules subject to external finite electric fields



The Python3 module `molgw.py` is available for automation.



## Installation



MOLGW needs Fortran 2003 (and a few Fortran2008 features) and C++ compilers.

MOLGW is being tested with `gfortran`, `g++` (version 11.x.x) and `ifort` (version 21).

MOLGW can run in parallel using OPENMP and MPI parallelization.



All the machine dependent variables should be set in file `~molgw/src/my_machine.arch`

Examples for this file can be found in the folder `~molgw/config/`.

Then

`cd ~molgw/src`

`make`



- BLAS and LAPACK linear algebra libraries are required.

- [LIBINT](https://github.com/evaleev/libint/releases) or [LIBCINT](https://github.com/sunqm/libcint/releases) is required for Gaussian integrals

- [LIBXC](https://www.tddft.org/programs/libxc/download/) is required for DFT calculations (else only HF is available)



To run on multi-node computers

- MPI and SCALAPACK are both required



## Basis sets



Many standard Gaussian basis sets are shipped with MOLGW.



More basis sets can be obtained from [Basis Set Exchange](https://bse.pnl.gov/bse/portal)

The file can be generated from a NWChem file using the script

`~molgw/utils/basisset_nwchem2molgw.py aug-cc-pVDZ.nwchem`



You may even create your own.



## Usage



`/path/to/molgw/molgw helium.in > helium.out`



Many example input files can be found in `~molgw/tests/inputs/`



## Known issues



- QSGW scf loop might be quite unstable for large basis sets, use a large eta

- TDDFT GGA kernel can induce very large numerical values that hinders the numerical stability and breaks some comparison with other codes.



## Bug reporting



Please use the [issues](https://github.com/molgw/molgw/issues) section on MOLGW github.



## Information for developers



Besides the wrapper calls to the LIBINT library, MOLGW is entirely written in Fortran2003/2008.

Fortran C bindings are used to call LIBXC and LIBCINT.

The source files can be found in ~molgw/src/.



### Coding Rules 



The Fortran intent in/out/inout is compulsory for the arguments of a subroutine.

One character variable names are discouraged.



The careful developer should try

- to follow the overall layout and the conventions of the code (double space indent, separation of the list of variables arguments/local, loop counters naming, etc.)

- to protect the data contained in a module with private or protected attribute as much as possible.

- to avoid cascading object access, such as a%b%c (Create methods instead)

- to hide the MPI statements with a generic wrapper in subroutine src/m_mpi.f90.

- to hide the SCALAPACK statements with a generic wrapper in subroutine src/m_scalapack.f90 (not implemented as of today).



### Automatically generated files



A few fortran source files are generated by python scripts:

- src/basis_path.f90

- src/revision.f90 

are generated by src/prepare_sourcecode.py (that is run at each "make" operation)

and

- src/input_variables.f90

is generated by utils/input_variables.py from a YAML file src/input_variables.yaml .

Do not attempt to edit the fortran files. You should rather edit the yaml file.



To add a new input variable, append a new variable description in the YAML file src/input_variables.yaml.

Then execute the python script utils/input_variables.py.

This will generate automatically the Fortran source file src/input_variables.f90

and the HTML and markdown documentation files docs/input_variables.html docs/input_variables.md.



### Adding a new source file



It requires the manual editing of the src/Makefile (sorry).

Please check carefully the module dependence so to compile and add it to the right "level" of the Makefile.

The code should compile properly in parallel with `make -j`.



## Contributors



- Fabien Bruneval

- Ivan Maliyov

- Mauricio Rodriguez-Mayorga 

- Xixi Qi

- Young-Moo Byun

- Meiyue Shao