add some monte carlo theory

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hiro98 2020-04-07 20:51:03 +02:00
parent f4496ba3ef
commit f6e172f85f
9 changed files with 217 additions and 34 deletions

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@ -3,7 +3,7 @@ twoside=false,toc=listof,toc=bibliography,fleqn,leqno,
captions=nooneline,captions=tableabove,english]{scrbook}
\usepackage{hirostyle}
%\addbibresource{thesis.bib}
\addbibresource{thesis.bib}
\title{Title}
\author{Valentin Boettcher}
@ -16,15 +16,15 @@ captions=nooneline,captions=tableabove,english]{scrbook}
\input{./tex/qqgammagamma/calculation.tex}
\input{./tex/qqgammagamma/comparison.tex}
\listoffigures
\listoftables
\input{./tex/monte-carlo.tex}
\input{./tex/monte-carlo/theory.tex}
\appendix
\input{./tex/appendix.tex}
% Bibliography:
\clearpage
% \input{./tex/mybibliography.tex}
\listoffigures
\listoftables
\printbibliography
\end{document}

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@ -10,7 +10,7 @@
\usepackage{graphicx, booktabs, float, scrhack}
\usepackage{amsmath,amssymb}
\usepackage[automark]{scrlayer-scrpage}
%\usepackage[backend=biber,style=verbose,sortcase=false,language=english]{biblatex}
\usepackage[backend=biber, language=english, style=phys]{biblatex}
\usepackage{siunitx}
\usepackage[pdfencoding=auto]{hyperref} % load late
% \usepackage[activate={true,nocompatibility},final,tracking=true,spacing=true,factor=1100,stretch=10,shrink=10]{microtype}
@ -57,9 +57,10 @@ labelformat=brace, position=top]{subcaption}
\captionsetup{justification=centering}
%% Labels
\labelformat{section}{section #1}
\labelformat{figure}{figure #1}
\labelformat{table}{table #1}
\labelformat{chapter}{chapter~#1}
\labelformat{section}{section~#1}
\labelformat{figure}{figure~#1}
\labelformat{table}{table~#1}
% Macros
@ -93,3 +94,13 @@ labelformat=brace, position=top]{subcaption}
%% Notes on Equations
\newcommand{\shorteqnote}[1]{ & & \text{\small\llap{#1}}}
%% Sherpa
\newcommand{\sherpa}{\texttt{Sherpa}}
%% Expected Value and Variance
\newcommand{\EX}[1]{\operatorname{E}\qty[#1]}
\newcommand{\VAR}[1]{\operatorname{VAR}\qty[#1]}
%% Uppercase Rho
\newcommand{\Rho}{P}

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@ -7,4 +7,4 @@ thesis: document.tex
.PHONY: clean
clean:
rm -f $(OUTDIR)/*
rm -rf $(OUTDIR)/*

12
latex/tex/monte-carlo.tex Normal file
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@ -0,0 +1,12 @@
%%% Local Variables: ***
%%% mode: latex ***
%%% TeX-master: "../document.tex" ***
%%% End: ***
\chapter{Survey of Elementary Monte-Carlo Methods}%
\label{chap:mc}
As monte-carlo methods for multidimensional integration and sampling
of probability distributions are central tools of modern particle
physics, their basics shall be studied. Some simple algorithms will
be implemented and applied to the results from~\ref{chap:qqgg}.

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@ -0,0 +1,99 @@
%%% Local Variables: ***
%%% mode: latex ***
%%% TeX-master: "../../document.tex" ***
%%% End: ***
\section{Monte-Carlo Integration}
\label{sec:mctheory}
Consider a function
\(f: \vb{x}\in\Omega\subset\mathbb{R}^n\mapsto\mathbb{R}\) and a
probability density on \(\Omega\)
\(\rho: \vb{x}\in\mathbb{R}^n\mapsto\mathbb{R}_{\geq 0}\) with
\(\int_{\Omega}\rho(\vb{x})\dd{\vb{x}} = 1\). By multiplying \(f\)
with a \(1\) in the fashion of~\eqref{eq:baseintegral}, the Integral
of \(f\) over \(\Omega\) can be interpreted as the expected value
\(\EX{F/\Rho}\) of the random variable \(F/\Rho\)
under the distribution \(\rho\).
\begin{equation}
\label{eq:baseintegral}
I = \int_\Omega f(\vb{x}) \dd{\vb{x}} = \int_\Omega
\qty[\frac{f(\vb{x})}{\rho(\vb{x})}] \rho(\vb{x}) \dd{\vb{x}} = \EX{\frac{F}{\Rho}}
\end{equation}
The expected value \(\EX{F/\Rho}\) can be approximate by taking the
mean of \(F/\Rho\) with \(N\) finite samples
\(\{\vb{x}_i\}_{i\in\overline{1,N}}\sim\rho\) (distributed according to
\(\rho\)), where \(N\) is usually a very large integer.
\begin{equation}
\label{eq:approxexp}
\EX{\frac{F}{\Rho}} \approx
\frac{1}{N}\sum_{i=1}^N\frac{f(\vb{x_i})}{\rho(\vb{x_i})}
\xrightarrow{N\rightarrow\infty} I
\end{equation}
The convergence of~\eqref{eq:approxexp} is due to the nature of the
expected value~\eqref{eq:evalue-mean} and
variance~\eqref{eq:variance-mean} of the mean
\(\overline{X} = \frac{1}{N}\sum_i X_i\) of \(N\) uncorrelated random
variables \(\{X_i\}_{i\in\overline{1,N}}\) with the same distribution,
expected value \(\EX{X_i}=\mathbb{E}\) and variance
\(\sigma_i^2 = \sigma^2\).
\begin{align}
\EX{\overline{X}} = \frac{1}{N}\sum_i\EX{X_i} = \mathbb{E} \label{eq:evalue-mean}\\
\sigma^2_{\overline{X}} = \sum_i\frac{\sigma_i^2}{N^2} =
\frac{\sigma^2}{N} \label{eq:variance-mean}
\end{algin}
Evidently \(\frac{\sigma^2}{N}\xrightarrow{N\rightarrow\infty} 0\)
thus the~\eqref{eq:approxexp} really converges to \(I\). For finite
\(N\) value of~\eqref{eq:approxexp} varies around \(I\) with the
variance \(\VAR{F/\Rho}\cdot N^{-1}\) as in~\eqref{eq:varI}.
\begin{align}
\VAR{\frac{F}{\Rho}} &= \int_\Omega \qty[I -
\frac{f(\vb{x})}{\rho(\vb{x})}]^2 \rho({\vb{x}}) \dd{\vb{x}} =
\int_\Omega \qty[\qty(\frac{f(\vb{x})}{\rho(\vb{x})})^2 -
I^2]\rho({\vb{x}}) \dd{\vb{x}} \label{eq:varI}
\\
&\approx \frac{1}{N - 1}\sum_i \qty[I -
\frac{f(\vb{x_i})}{\rho(\vb{x_i})}]^2 \label{eq:varI-approx}
\end{align}
The name of the game is thus to reduce \(\VAR{F/\Rho}\) to speed up
the convergence of~\eqref{eq:approxexp} and achieve higher accuracy
with fewer function evaluations.
The simplest choice for \(\rho\) is clearly given
by~\eqref{eq:simplep}, the uniform distribution.
\begin{equation}
\label{eq:simplep}
\rho(\vb{x}) = \frac{1}{\int_{\Omega}1\dd{\vb{x'}}} =
\frac{1}{\abs{\Omega}}
\end{equation}
With this distribution~\eqref{eq:approxexp}
becomes~\eqref{eq:approxexp-uniform}. In other words, \(I\) is just
the mean of \(f\) in \(\Omega\), henceforth
called \(\bar{f}\), multiplied with the volume.
\begin{equation}
\label{eq:approxexp-uniform}
\EX{\frac{F}{\Rho}} \approx
\frac{\abs{\Omega}}{N}\sum_{i=1}^N f(\vb{x_i}) = \abs{\Omega}\cdot\bar{f}
\end{equation}
The variance \(\VAR{I}=\VAR{F/\Rho}\) is now given
by~\ref{eq:approxvar-I}. Note that the factor \(\abs{\omega}\) gets
squared when approximating the integral to the sum.
\begin{equation}
\label{eq:approxvar-I}
\VAR{I} = \abs{\Omega}\int_\Omega f(\vb{x})^2 -
I^2 \dd{\vb{x}} \equiv \abs{\Omega}\cdot\sigma_f^2 \approx
\frac{\abs{\Omega}^2}{N-1}\sum_{i}\qty[f(\vb{x}_i) - \bar{f}]^2
\end{equation}

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@ -1,6 +1,11 @@
%%% Local Variables: ***
%%% mode:latex ***
%%% TeX-master: "../document.tex" ***
%%% End: ***
\chapter{Quark-Antiquark Annihilation into
two Photons}%
\label{sec:qqgg}
\label{chap:qqgg}
Consider the scattering reaction \(\qqgg\). The first order expansion
of this process is being described by the Feynman diagrams

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@ -1,3 +1,8 @@
%%% Local Variables: ***
%%% mode:latex ***
%%% TeX-master: "../../document.tex" ***
%%% End: ***
\section{Calulation of the Cross Section to first Order}%
\label{sec:qqggcalc}

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@ -1,23 +1,30 @@
\section{Discussion and Comparison with Sherpa}%
%%% Local Variables: ***
%%% mode:latex ***
%%% TeX-master: "../../document.tex" ***
%%% End: ***
\section{Discussion and Comparison with \sherpa}%
\label{sec:compsher}
The result obtained in~\ref{sec:qqggcalc} shall now be verified by
monte-carlo in \verb|Sherpa|. To facilitate this, an expression for
the total cross section for a range of \(\theta\) or \(\eta\) has to
be obtained. Using the golden rule for \(2\rightarrow 2\) processes
and observing that the initial and final momenta are equal
(\(p_i=p_f\)) and \(g=\sqrt{4\pi\alpha}\), the
result~\eqref{eq:crossec} arises.
monte-carlo in \sherpa{}~\cite{Gleisberg:2008ta}. To facilitate this, an
expression for the total cross section for a range of \(\theta\) or
\(\eta\) has to be obtained. Using the golden rule for
\(2\rightarrow 2\) processes and observing that the initial and final
momenta are equal (\(p_i=p_f\)) and \(g=\sqrt{4\pi\alpha}\), the
result~\eqref{eq:crossec} arises. The differential cross section is
also given in terms of the pseudo-rapidity in~\ref{eq:xs-eta}.
An additional factor of \(\frac{1}{2}\) comes in due to there being
two identical photons in the final state.
\begin{equation}
\label{eq:crossec}
\dv{\sigma}{\Omega} =
\frac{1}{2}\frac{1}{(8\pi)^2}\cdot\frac{\abs{\mathcal{M}}^2}{\ecm^2}\cdot\frac{\abs{p_f}}{\abs{p_i}}
= \overbrace{\frac{\alpha^2Q^4}{6\ecm^2}}^{\mathfrak{C}}\frac{1+\cos^2(\theta)}{\sin^2(\theta)}
\end{equation}
\begin{align}
\dv{\sigma}{\Omega} &=
\frac{1}{2}\frac{1}{(8\pi)^2}\cdot\frac{\abs{\mathcal{M}}^2}{\ecm^2}\cdot\frac{\abs{p_f}}{\abs{p_i}}
=
\underbrace{\frac{\alpha^2Q^4}{6\ecm^2}}_{\mathfrak{C}}\frac{1+\cos^2(\theta)}{\sin^2(\theta)}\label{eq:crossec}
\\
\dv{\sigma}{\eta} &= \frac{\alpha^2Q^4}{6\ecm^2}\cdot\qty(\tanh(\eta)^2 + 1)\label{eq:xs-eta}
\end{align}
\begin{figure}[ht]
\centering
@ -43,12 +50,16 @@ also~\ref{fig:diffxs}) is divergent for angles near zero or
divergence. Because \(m=0\) is the limit for
\(\ecm\rightarrow\infty\), the cross section would still have strong
peaks for angles near \(0,\pi\) at high energies so that the result is
not altogether nonphysical. It is clearly symmetric around
not altogether nonphysical. The divergence of the cross section itself
is also not, the problem here, because it can be transformed into a
form where the divergence does not occur (see~\eqref{eq:xs-eta}).
The differential cross section is clearly symmetric around
\(\theta=\frac{pi}{2}\) as was to be expected, because the photons are
indistinguishable. To compare the cross section to experiment and to
simulation an interval around \(\theta=\frac{\pi}{2}\) has to be
chosen, where the first order, mass-less approximation may yield
sensible results.
chosen, where the first order, mass-less approximation may yield a
useful result.
The total cross section in such an interval, given by
integrating~\eqref{eq:crossec} for \(\theta\in [\theta_1, \theta_2]\)
@ -73,10 +84,12 @@ an interval of \([-\eta, \eta]\), is dominated by the linear
contributions in~\ref{eq:total-crossec} and would result in an
infinity if no cut on \(\eta\) would be made. Choosing
\(\eta\in [-2.5,2.5]\) and \(\ecm=\SI{100}{\giga\electronvolt}\) the
process was monte carlo integrated in sherpa using the runcard
process was monte carlo integrated in \sherpa\ using the runcard
in~\ref{sec:qqggruncard}. This runcard describes the exact same (first
order) process as the calculated cross section.
Sherpa yields \result{xs/sherpa_xs}. Plugging the same parameters
into~\eqref{eq:total-crossec} gives \result{xs/xs} which is
within the uncertainty range of the Sherpa value.
The monte carlo integration in \sherpa\ yields
\result{xs/sherpa_xs}. Plugging the same parameters
into~\eqref{eq:total-crossec} gives \result{xs/xs} which is within the
uncertainty range of the \sherpa\ value. This verifies the result for
the total cross section.

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@ -0,0 +1,38 @@
@article{Gleisberg:2008ta,
author = "Gleisberg, T. and Hoeche, Stefan. and Krauss, F. and Schonherr, M. and Schumann, S. and Siegert, F. and Winter, J.",
archivePrefix = "arXiv",
doi = "10.1088/1126-6708/2009/02/007",
eprint = "0811.4622",
journal = "JHEP",
pages = "007",
primaryClass = "hep-ph",
reportNumber = "FERMILAB-PUB-08-477-T, SLAC-PUB-13420, ZU-TH-17-08, DCPT-08-138, IPPP-08-69, EDINBURGH-2008-30, MCNET-08-14",
title = "{Event generation with SHERPA 1.1}",
volume = "02",
year = "2009"
}
@article{Krauss:2001iv,
author = "Krauss, F. and Kuhn, R. and Soff, G.",
archivePrefix = "arXiv",
doi = "10.1088/1126-6708/2002/02/044",
eprint = "hep-ph/0109036",
journal = "JHEP",
pages = "044",
reportNumber = "CAVENDISH-HEP-01-11",
title = "{AMEGIC++ 1.0: A Matrix element generator in C++}",
volume = "02",
year = "2002"
}
@article{Gleisberg:2008fv,
author = "Gleisberg, Tanju and Hoeche, Stefan",
archivePrefix = "arXiv",
doi = "10.1088/1126-6708/2008/12/039",
eprint = "0808.3674",
journal = "JHEP",
pages = "039",
primaryClass = "hep-ph",
reportNumber = "SLAC-PUB-13232, IPPP-08-31, DCPT-08-62, MCNET-08-08",
title = "{Comix, a new matrix element generator}",
volume = "12",
year = "2008"
}