X-Git-Url: https://hackdaworld.org/gitweb/?p=lectures%2Flatex.git;a=blobdiff_plain;f=physics_compact%2Fmath.tex;h=bd2a888430d738d62ddc7b8aa1911e2f423d7043;hp=4c8e6f9946efda96dfd874b2a2f90e79a0438fa5;hb=93808b285afe6d16ac131af43108b975a0cc9042;hpb=0929321d46ef53429ae8d78a0f08e452e96b3cd2

diff --git a/physics_compact/math.tex b/physics_compact/math.tex
index 4c8e6f9..bd2a888 100644
--- a/physics_compact/math.tex
+++ b/physics_compact/math.tex
@@ -1,26 +1,27 @@
 \part{Mathematical foundations}
 
-Reminder: Modern Quantum Chemistry \& Sakurai \& Group Theory \ldots
-
 \chapter{Linear algebra}
 
+Reminder: Modern Quantum Chemistry \& Sakurai \& Group Theory \ldots
+
 \section{Vectors and bases}
 
-A vector $\vec{a}$ of an $N$-dimensional vector space (see \ref{math_app:vector_space} for mathematical details) is represented by its components $a_i$ with respect to a set of $N$ basis vectors ${\vec{e}_i}$.
+A vector $\vec{a}$ of an $N$-dimensional vector space (see \ref{math_app:vector_space} for mathematical details) is represented by its components $a_i$ with respect to a set of $N$ basis vectors ${\vec{e}_i}$
 \begin{equation}
 \vec{a}=\sum_i^N \vec{e}_i a_i
 \label{eq:vec_sum}
 \end{equation}
-The scalar product for an $N$-dimensional real vector space is defined as
+i.e., if the basis set is complete, any vector can be written as a linear combination of these basis vectors.
+The scalar product in an $N$-dimensional Euclidean vector space is defined as
 \begin{equation}
 (\vec{a},\vec{b})=\sum_i^N a_i b_i \text{ ,}
 \label{eq:vec_sp}
 \end{equation}
-which enables to define a norm
+which satisfies the properties of an inner product (see \ref{math_app:product}) and enables to define a norm
 \begin{equation}
 ||\vec{a}||=\sqrt{(\vec{a},\vec{a})}
 \end{equation}
-that just corresponds to the length of vector \vec{a}.
+that just corresponds to the length of vector $\vec{a}$.
 Evaluating the scalar product $(\vec{a},\vec{b})$ by the sum representation of \eqref{eq:vec_sum} leads to
 \begin{equation}
 (\vec{a},\vec{b})=(\sum_i\vec{e}_ia_i,\sum_j\vec{e}_jb_j)=
@@ -46,8 +47,28 @@ Inserting the expression for the coefficients into \eqref{eq:vec_sum}, the vecto
 \begin{equation}
 \label{eq:complete}
 \vec{a}=\sum_i \vec{e}_i (\vec{e}_i,\vec{a}) \Leftrightarrow
-\sum_i\vec{e}_i\cdot \vec{e}_i=\vec{1}
+\sum_i\vec{e}_i\otimes \vec{e}_i=\vec{1}
 \end{equation}
 if the basis is complete.
-Indeed, the very important identity representation by the outer product ($\cdot$) in the second part of \eqref{eq:complete} is known as the completeness relation or closure.
+Indeed, the very important identity representation by the outer product ($\otimes$, see \ref{math_app:product}) in the second part of \eqref{eq:complete} is known as the completeness relation or closure.
+
+\section{Operators, matrices and determinants}
+
+An operator $O$ acts on a vector resulting in another vector
+\begin{equation}
+O\vec{a}=\vec{b} \text{ ,}
+\end{equation}
+which is linear if
+\begin{equation}
+O(\lambda\vec{a}+\mu\vec{b})=\lambda O\vec{a} + \mu O\vec{b} \text{ .}
+\end{equation}
+Thus, for a linear operator, it is sufficient to describe the effect on the complete set of basis vectors, which enables to describe the effect of the operator on any vector.
+Since the result of an operator acting on a basis vector is a vector itself, it can be expressed by a linear combination of the basis vectors
+\begin{equation}
+O\vec{e}_i=\vec{e}_jO_{ji}
+\text{ ,}
+\end{equation}
+with $O_{ji}$ determining the components of the new vector $O\vec{e}_i$ along $\vec{e}_j$.
+
+\section{Dirac notation}