morecomment=[l]{!\ }% Comment only with space after !
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@@ -60,7 +61,7 @@
\lstdefinestyle{fortran_pseudo_code}{
language=Fortran,
basicstyle=\ttfamily,
basicstyle=\ttfamily\small,
keywordstyle=\color{red},
commentstyle=\normalfont\color{black},
morecomment=[l]{!\ }% Comment only with space after !
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@@ -126,6 +127,7 @@
\numberwithin{exerciseitem}{exercise}% reset counter ; depends on the amsmath package
%%%
\input{Notebooks/notebooks_preamble.tex}
\makeindex
\begin{document}
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@@ -142,29 +144,56 @@
The ALF package provides a general code for auxiliary-field Quantum Monte Carlo simulations and default analysis. In this tutorial we show how users from beginners to specialists can profit from ALF. This document is divided in two parts:
\begin{description}
\item[Part I.] The first, introductory part of the tutorial is based on ALF's python interface -- \texttt{pyALF} -- which greatly simplifies using the code, making it ideal for: obtaining \emph{benchmark} results for established models; \emph{getting started} with QMC and ALF; or just \emph{quickly} running a simulation.
\item[Part I.] The first, introductory part of the tutorial is based on ALF's python interface -- \texttt{pyALF} -- which greatly simplifies using the code, making it ideal for: \emph{obtaining benchmark} results for established models; \emph{getting started} with QMC and ALF; or just \emph{quickly running} a simulation.
\item[Part II.] The second part is independent of the first and aimed at more advanced users who want to simulate their own systems. It guides the user on how to modify the package's Fortran source code and presents the resources implemented to facilitate this task.
\end{description}
This document is intended to be self-contained, but the interested reader should check \href{https://git.physik.uni-wuerzburg.de/ALF/ALF_code/blob/master/Documentation/ALF_v1.0.pdf}{ALF's documentation}, which contains a thorough, systematic description of the package. \red{[Update link when ALF 2 is open.]}
This document is intended to be self-contained, but the interested reader should check \href{https://git.physik.uni-wuerzburg.de/ALF/ALF_code/blob/master/Documentation/ALF_v1.0.pdf}{ALF's documentation}, which contains a thorough, systematic description of the package.
What follows is a collection of self-explanatory Jupyter notebooks written in Python, each centered on a detailed example followed by a few simple exercises. The notebooks printed bellow can be found, together with the necessary files and an increasing number of additional notebooks exploring ALF's capabilities, in the \href{https://git.physik.uni-wuerzburg.de/ALF/pyALF}{pyALF repository}.
This a collection of Jupyter notebooks, each centered on a detailed example followed by a few simple exercises, while Part II consists in a set of guided advanced exercises.
can be found, together with its accompanying files, in the \href{https://git.physik.uni-wuerzburg.de/ALF/pyALF}{pyAL repository}.
\section*{Requirements}
ALF is compiled from source, which is downloaded from the \href{https://git.physik.uni-wuerzburg.de:ALF}{ALF repository} when not found locally.
You can download pyALF from the its repository linked above, or simply run from the command line:
@@ -187,6 +216,8 @@ ALF is compiled from source, which is downloaded from the \href{https://git.phys
\part{Getting your hands dirty - changing the code}
%\setcounter{exercise}{0}
Part II consists in a set of guided advanced exercises.
A lot already comes implemented in ALF, but unavoidably, as one proceeds in their own investigations, a new model has to be implemented or a new observable defined -- and for that one has to grapple with the package's Fortran source code. However, in ALF this is made easy by means of predefined structures, templates, and the examples below.
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@@ -205,9 +236,8 @@ Here we will modify the code so as to allow for different hopping matrix eleme
\item Add an extra variable, \texttt{Ham\_Ty}, in the parameter file in the \texttt{VAR\_Hubbard} name space
\item Declare the variable \texttt{Ham\_Ty} in the \texttt{Hamiltonian\_Examples.f90 }.
\item Read in this variable in \texttt{Ham\_set} subroutine of the \texttt{Hamiltonian\_Examples.f90 } file.
\item Modify the hopping matrix in the subroutine \texttt{Ham\_Hop} in the \texttt{Hamiltonian\_Examples.f90 } file.
\lstset{style=fortran}
\begin{lstlisting}
\item Modify the hopping matrix in the subroutine \texttt{Ham\_Hop} in the \texttt{Hamiltonian\_Examples.f90 } file.
\begin{lstlisting}[style=fortran]
DO I = 1, Latt%N
I1 = Latt%nnlist(I,1,0)
I2 = Latt%nnlist(I,0,1)
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@@ -230,8 +260,7 @@ In the directory \texttt{Solutions/Exercise\_2} we have duplicated the ALF and
\noindent
As an application of this code, one can consider a ladder system, defined by the parameter file:
\PY{p}{\PYZob{}}\PY{c+c1}{\PYZsh{} Model and simulation parameters for each Simulation instance}
\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{Model}\PY{l+s+s2}{\PYZdq{}}\PY{p}{:}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{Hubbard}\PY{l+s+s2}{\PYZdq{}}\PY{p}{,}\PY{c+c1}{\PYZsh{} Base model}
\PY{n+nb}{print}\PY{p}{(}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+se}{\PYZbs{}n}\PY{l+s+s2}{Running again reduced the error from }\PY{l+s+s2}{\PYZdq{}}\PY{p}{,}\PY{n}{obs}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{Ener\PYZus{}scalJ}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{obs}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{,}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{ to }\PY{l+s+s2}{\PYZdq{}}\PY{p}{,}\PY{n}{obs2}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{Ener\PYZus{}scalJ}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{p}{[}\PY{l+s+s1}{\PYZsq{}}\PY{l+s+s1}{obs}\PY{l+s+s1}{\PYZsq{}}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{,}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{.}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
\end{Verbatim}
\end{tcolorbox}
\begin{Verbatim}[commandchars=\\\{\}]
Prepare directory "/home/jonas/Programs/pyALF/Hubbard\_Hubbard\_Square" for Monte
Carlo run.
Resuming previous run.
Run /home/jonas/Programs/pyALF/ALF/Prog/Hubbard.out
Analysing Part\_scal
Analysing Kin\_scal
Analysing Ener\_scal
Analysing Pot\_scal
Analysing SpinT\_eq
Analysing SpinZ\_eq
Analysing SpinXY\_eq
Analysing Green\_eq
Analysing Den\_eq
Analysing SpinZ\_tau
Analysing Den\_tau
Analysing SpinXY\_tau
Analysing SpinT\_tau
Analysing Green\_tau
[[-29.819654 0.135667]]
Running again reduced the error from 0.232685 to 0.135667 .
\end{Verbatim}
\textbf{Note}: To run a fresh simulation - instead of performing a
refinement over previous run(s) - the Monte Carlo run directory should
