README.md

# ALF #
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**Project website: https://alf.physik.uni-wuerzburg.de/.**

-> Interested contributors please check our [CONTRIBUTING.md](https://git.physik.uni-wuerzburg.de/ALF/ALF/-/blob/master/CONTRIBUTING.md) guidelines.

-> This is the **development** version of ALF, the latest stable version is [ALF 2.4](https://git.physik.uni-wuerzburg.de/ALF/ALF/-/tree/ALF-2.4/).

## Description ##

The **A**lgorithms for **L**attice **F**ermions package provides a general code for the finite temperature  and projective auxiliary field Quantum Monte Carlo algorithm.       The code  is engineered to  be able simulate any model that can be written in terms of  sums of single body operators, of squares of single body operators and single body operators coupled to an Ising field with  given dynamics. We  provide predefined types that allow  the user to specify the model, the  Bravais lattice  as well as equal time and time displaced observables.     The code supports an MPI implementation.   Examples such as the Hubbard model, the SU(N) Kondo lattice model, tV models,  models with long ranged interactions as well as Z2 lattice gauge theories coupled to fermions adn Z2 matter are discussed in the [documentation](https://git.physik.uni-wuerzburg.de/ALF/ALF/-/jobs/artifacts/master/raw/Documentation/doc.pdf?job=create_doc). Slides on the auxiliary field QMC can be found [here.](https://git.physik.uni-wuerzburg.de/ALF/ALF_Tutorial/-/blob/master/Presentations/ALF_2020_Assaad.pdf)

The Hamiltonians we can consider read:
![The Hamiltonian0](Images/Hamiltonian0.png "The Hamiltonian")
where
![The Hamiltonian1](Images/Hamiltonian1.png "Parts explanation")

Here Z denotes a scalar field (Ising or real continuous field) with predefined dynamics. If your model can be written in this form then it will be amenable to the ALF. 

## pyALF ##

For ease of use, the  [pyALF](https://git.physik.uni-wuerzburg.de/ALF/pyALF) repository  provides a python interface to run the ALF-code

## Doxygen ##

You can find here [Doxygen](https://gitpages.physik.uni-wuerzburg.de/ALF/ALF/) formatted documentation. (Work in progress)

## Installation ##

* Please check the latest documentation (Documentation/doc.pdf) for more details and Sec. 6.1, "Quick Start", to try ALF out straight away.

### PREREQUISITES ###

* Make
* A Fortran compiler, such as `gfortran` or `ifort`
* Blas+Lapack libraries
* Python3
* MPI libraries (optional)
* For HDF5 (optional)
	* C++ preprocessor (default: g++)
	* Curl
	* gzip development libraries


* **Linux**   
  To install the relevant packages.

  **Debian/Ubuntu/Linux Mint**: 
  ```
  sudo apt install make gfortran libblas-dev liblapack-dev \
            python3 libopenmpi-dev g++ curl libghc-zlib-dev git
  ```

  **Red Hat/Fedora/CentOS**:
  ```
  sudo yum install make gfortran libblas-devel liblapack-devel \
            python3 libopenmpi-dev g++ curl zlib git
  ```

  **OpenSuSE/SLES**:
  ```
  sudo zypper install make gcc-fortran lapack-devel \
               python3 libopenmpi-devel gcc-c++ curl zlib-devel git
  ```

  **Arch Linux**:
  ```
  sudo pacman -S make gcc-fortran lapack python3 openmpi curl zlib git
  ```

* **Other Unixes**   
  gfortran and the lapack implementation from netlib.org should be available for your system. Consult the documentation of your system on how to install the relevant packages. The package names from linux should give good starting points for your search.

* **MacOS**   
  gfortran for MacOS can be found at https://gcc.gnu.org/wiki/GFortranBinaries#MacOS. Detailed information on how to install the package  can be found at: https://gcc.gnu.org/wiki/GFortranBinariesMacOS. You will need to have Xcode as well as the  Apple developer tools installed. 

* **Windows**   
  The easiest way to compile ALF in Windows is trough the [Windows Subsystem for Linux](https://docs.microsoft.com/en-us/windows/wsl/about) (WSL). It allows to run Linux within Windows. You can install the WSL and follow the instructions for Linux.


## CONFIGURATION FOR COMPILATION ##
<!--**setenv.sh**   sets the default set of envorinment variables.  Do not change  this since this default set of  environment variables is required for the tests to run adequaltely.-->

**configure.sh**  It is recommended to use this script to set the environment variables. Type ./configure.sh to  browse through a list of options. Notice that directory names containing **spaces are not supported**.

Once you have run the configuration script, change directory to Libraries, and to Analysis  and run the Makefiles there. In the Prog directory then type make examples.   The other programs are being updated to comply with the new version of the code.  

## FILES AND DIRECTORIES ##

**Libraries**    Libraries. Once that the environment is set in the file configure.sh  the Libraries can be compiled with the **make** command. 

**Prog**   Main program and subroutines.  

**Analysis** Analysis programs. 

**Scripts\_and\_Parameters\_files**  Helper scripts and the Start/ directory, which contains the files required to start a run. 

 
**Documentation**  We have included in the file  [doc.pdf](https://git.physik.uni-wuerzburg.de/ALF/ALF/-/jobs/artifacts/master/raw/Documentation/doc.pdf?job=create_doc) an extensive documentation.

**testsuite** An automatic test suite for various parts of the code


## TESTING ##

We have about 30 tests that test various parts of the program in the folder testsuite.
As testing framework we employ CTest.
From the subfolder testsuite the tests can be run as follows
- mkdir tests
- cd tests
- cmake ..
- make
- make test


## LICENSE ##
The various works that make up the ALF project are placed under licenses that put a strong emphasis on the attribution of the original authors and the sharing of the contained knowledge.
To that end we have placed the ALF source code under the GPL version 3 license and took the liberty as per GPLv3 section 7 to include additional terms that deal with the attribution
of the original authors (see license.GPL and license.additional).
The Documentation of the ALF project by the ALF contributors is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (see Documentation/license.CCBYSA). Note that we link against parts of lapack, which is licensed under a BSD license (see license.lapack).

## KNOWN ISSUES ##

We have detected a bug in both 2017 versions of Intel's MPI implementation (mpi.intel/2017(default) 
and mpi.intel/2017.2) if used in combination with the parallel (threaded) MKL library. The advise is to 
use either the 2016 suite (intel/16.0 (compiler), mpi.intel/5.1 and mkl/11.3 ) or the new 2018 suite 
(intel/18.0 (compiler), mpi.intel/2018 and mkl/2018). We did not detect this issue in both environments. 
You should also be aware the by default, dynamic linking is used. Hence if you use the 2016 or 2018 modules 
at compilations, the bug can reenter if you still load the 2017 versions at runtime. So please adapt your
configureHPC.sh as well as your Jobfiles for the loadleveler accordingly.
Additional note: In the serial version, the bug also seems to be absent. 
If you want to use the 2017 suite, you have to use the serial version of MKL (mkl/2017_s), which means you 
cannot profit from openMP multi-threading. This library is linked statically, hence taking care of this at 
compile time is sufficient and there is no need to adapt the Jobfiles.
WARNING: Even if you do not use parallel tempering actively, we still strongly suggest to take care of 
the above bug as it is extremely hard to estimate hidden influences and correlations of this memory 
allocation bug in the rest of the program. It is possible the other parts of the algorithm might be 
affected apart from the tempering exchange step even so we have absolutely no hint of additionally 
affected sections in ALF.

Intel suite 2017: Apparently, there seems to be a bug in the Intel MPI threaded memory allocator if both Intel MPI 
implementation and the PARALLEL version of MKL is used. This bug corrupts the data transmission during tempering moves such 
that the Monte Carlo is broken. The current advise is to either use an earlier version (2016 and before) or a newer one
(2018 and later). It should also be OK to use the sequential MKL library if openMP multi-threading is not required. 
Setting the environment variable OMP_NUM_THREADS=1 however does not fix the bug as this still uses the threaded MKL 
library (Date: 1. June 2018)