X-Git-Url: https://hackdaworld.org/gitweb/?p=lectures%2Flatex.git;a=blobdiff_plain;f=physics_compact%2Fmath_app.tex;h=f1ac777ea2a51d8168b426991d5fca0a05b3e8c1;hp=edee2ff6549050a69fa098232f8e9a61eb4a1e69;hb=bc36ee251b928962cf2431d6582e5a5dd9cca682;hpb=69b350d82ab4382625484e3edbffd933f267aa50 diff --git a/physics_compact/math_app.tex b/physics_compact/math_app.tex index edee2ff..f1ac777 100644 --- a/physics_compact/math_app.tex +++ b/physics_compact/math_app.tex @@ -5,7 +5,7 @@ \subsection{Vector space} \label{math_app:vector_space} -\begin{definition} +\begin{definition}[Vector space] A vector space $V$ over a field $(K,+,\cdot)$ is an additive abelian group $(V,+)$ and an additionally defined scalar multiplication of $\vec{v}\in V$ by $\lambda\in K$, which fullfills: \begin{itemize} \item $\forall \vec{v} \, \exists 1$ with: $\vec{v}1=\vec{v}$ @@ -19,6 +19,7 @@ A vector space $V$ over a field $(K,+,\cdot)$ is an additive abelian group $(V,+ \end{itemize} The elements $\vec{v}\in V$ are called vectors. \end{definition} + \begin{remark} Due to the additive abelian group, the following properties are additionally valid: \begin{itemize} @@ -36,17 +37,147 @@ The addition of two vectors is called vector addition. \subsection{Dual space} +\begin{definition}[Dual space] +The dual space $V^{\dagger}$ of vector space $V$ over field $K$ is defined as the set of all linear maps from the vector space $V$ into its field $K$ +\begin{equation} +\varphi:V\rightarrow K \text{ .} +\end{equation} +These type of linear maps are termed linear functionals. +The dual space $V^{\dagger}$ becomes a vector space over $K$ itself by the following additional definitions +\begin{eqnarray} +(\varphi+\psi)(\vec{v}) & = & \varphi(\vec{v})+\psi(\vec{v}) \\ +(\lambda\varphi)(\vec{v}) & = & \lambda\varphi(\vec{v}) +\end{eqnarray} +for all $\vec{v}\in V$, $\varphi,\psi\in V^{\dagger}$ and $\lambda\in K$. + +The map $V^{\dagger}\times V \rightarrow K: [\varphi,\vec{v}]=\varphi(\vec{v})$ is termed dual pairing of a functional $\varphi\in V^{\dagger}$ and an elemnt $\vec{v}\in V$. +\end{definition} + \subsection{Inner and outer product} \label{math_app:product} -\begin{definition} -The inner product ... +\begin{definition}[Inner product] +The inner product on a vector space $V$ over $K$ is a map +$(\cdot,\cdot):V\times V \rightarrow K$, which satisfies +\begin{itemize} +\item $(\vec{u},\vec{v})=(\vec{v},\vec{u})^*$ + (conjugate symmetry, symmetric for $K=\mathbb{R}$) +\item $(\lambda\vec{u},\vec{v})=\lambda(\vec{u},\vec{v})$ and + $(\vec{u}'+\vec{u}'',\vec{v})=(\vec{u}',\vec{v})+(\vec{u}'',\vec{v})$ + (linearity in first argument) +\item $(\vec{u},\vec{u})\geq 0 \text{, } ``=" \Leftrightarrow \vec{u}=0$ + (positive definite) +\end{itemize} +for $\vec{u},\vec{v}\in V$ and $\lambda\in K$. +Taking the complex conjugate $(\cdot)^*$ is the map from +\begin{equation} +z=a+bi\mapsto z^*=a-bi \text{, } z,z^*\in K \text{.} +\end{equation} \end{definition} -\begin{definition} -If $\vec{u}\in U$ and $\vec{v}\in V$ are vectors within the respective vector spaces and $V^{\dagger}$ is the dual space of $V$, the outer product of $\vec{u}$ and $\vec{v}$ is defined as the tensor product ... +\begin{remark} +\label{math_app:ip_remark} +Due to conjugate symmetry, linearity in the first argument results in conjugate linearity (also termed antilinearity) in the second argument. +\begin{equation} +(\vec{u},\lambda(\vec{v}'+\vec{v}''))=(\lambda(\vec{v}'+\vec{v}''),\vec{u})^*= +\lambda^*(\vec{v}',\vec{u})^*+\lambda^*(\vec{v}'',\vec{u})^*= +\lambda^*(\vec{u},\vec{v}')+\lambda^*(\vec{u},\vec{v}'') +\end{equation} +This is called a sesquilinear form. +If $K=\mathbb{R}$, conjugate symmetry reduces to symmetry and the sesquilinear form gets a bilinear form. + +Furtermore, the inner product $(\cdot,\cdot)$ provides a mapping +\begin{equation} +V\rightarrow V^{\dagger}:\vec{v}\mapsto \varphi_{\vec{v}} +\quad +\text{ defined by } +\quad +\varphi_{\vec{v}}(\vec{u})=(\vec{v},\vec{u}) \text{ .} +\label{eq:ip_mapping} +\end{equation} +Since the inner product is linear in the first argument, the same is true for the defined mapping. +\begin{equation} +\lambda(\vec{u}+\vec{v}) \mapsto +\varphi_{\lambda(\vec{u}+\vec{v})}= +\lambda\varphi_{\vec{u}}+\lambda\varphi_{\vec{v}}\\ +\end{equation} +If the inner product is nondegenerate, i.e.\ $\forall\vec{u}\, (\vec{v},\vec{u})=0 \Leftrightarrow \vec{v}=0$, as it applies for the scalar product for instance, the mapping is injective. +Since the dimension of $V$ and $V^{\dagger}$ is equal, it is additionally surjective. +Then, $V$ is isomorphic to $V^{\dagger}$. +Vector $\vec{v}^{\dagger}\equiv \varphi_{\vec{v}}\in V^{\dagger}$ is said to be the dual vector of $\vec{v}\in V$. +The dual pairing $[\vec{v}^{\dagger},\vec{u}]=[\varphi_{\vec{v}},\vec{u}]=\varphi_{\vec{v}}(\vec{u})$ is associated with the inner product $(\vec{v},\vec{u})$. + +Now, in physics and matrix algebra, the inner product is often defined with linearity in the second argument and conjugate linearity in the first argument. +In this case, the antilinearity property is assigned to the element $\varphi_{\vec{v}}=\vec{v}^{\dagger}$ of dual space +\begin{equation} +\varphi_{\lambda\vec{v}}(\vec{u})= +(\lambda\vec{v},\vec{u})= +\lambda^*(\vec{v},\vec{u})= +\lambda^*\varphi_{\vec{v}}(\vec{u}) +\end{equation} +and $V$ is found to be isomorphic to the conjugate complex of its dual space. +Then, the inner product $(\vec{v},\vec{u})$ is associated with the dual pairing of element $\vec{u}$ of the vector space and $\vec{v}^{\dagger}$ of its conjugate complex dual space +\begin{equation} +(\vec{v},\vec{u})\rightarrow +[\varphi_{\vec{v}},\vec{u}]= +[\vec{v}^{\dagger},\vec{u}] +\text{ .} +\end{equation} + +The standard sesquilinear form $\langle\cdot,\cdot\rangle$, also called Hermitian form, on $\mathbb{C}^n$ and linearity in the second argument, is given by +\begin{equation} +\langle\vec{v},\vec{u}\rangle=\sum_i^nv_i^*u_i +\text{ .} +\end{equation} +In this case, in matrix formalism, the inner product is reformulated +\begin{equation} +(\vec{v},\vec{u}) \rightarrow \vec{v}^{\dagger}\vec{u} +\text{ ,} +\end{equation} +where the dual vector is associated with the conjugate transpose $\vec{v}^{\dagger}$ of the corresponding vector $\vec{v}$ +and the usual rules of matrix multiplication. +\end{remark} + +\begin{definition}[Outer product] +If $\vec{u}\in U$, $\vec{v},\vec{w}\in V$ are vectors within the respective vector spaces and $\varphi_{\vec{v}}\in V^{\dagger}$ is a linear functional of the dual space $V^{\dagger}$ of $V$ (determined in some way by $\vec{v}$), +the outer product $\vec{u}\otimes\vec{v}$ is defined as the tensor product of $\varphi_{\vec{v}}$ and $\vec{u}$, +which constitutes a map $A:V\rightarrow U$ by +\begin{equation} +\vec{w}\mapsto\varphi_{\vec{v}}(\vec{w})\vec{u} +\text{ ,} +\end{equation} +where $\varphi_{\vec{v}}(\vec{w})$ denotes the linear functional $\varphi_{\vec{v}}\in V^{\dagger}$ on $V$ when evaluated at some $\vec{w}\in V$, a scalar that in turn is multiplied with $\vec{u}\in U$. \end{definition} +\begin{remark} + +In matrix formalism, if $\varphi_{\vec{v}}$ is defined as in \eqref{eq:ip_mapping} and +if $\vec{u}=\sum_i^m \vec{e}_iu_i$ and $\vec{v}=\sum_i^n\vec{e}'_iv_i$, +the standard form of the outer product can be written as the matrix +\begin{equation} +\vec{u}\otimes\vec{v}=A=\left( +\begin{array}{c c c c} +u_1v_1^* & u_1v_2^* & \cdots & u_1v_n^*\\ +u_2v_1^* & u_2v_2^* & \cdots & u_2v_n^*\\ +\vdots & \vdots & \ddots & \vdots\\ +u_mv_1^* & u_mv_2^* & \cdots & u_mv_n^*\\ +\end{array} +\right) +\text{ ,} +\end{equation} +which can be equivalently obtained by the rulrs of matrix multiplication +\begin{equation} +\vec{u}\otimes\vec{v}=\vec{u}\vec{v}^{\dagger} \text{ ,} +\end{equation} +if $\vec{u}$ and $\vec{v}$ are represented as $m\times 1$ and $n\times 1$ column vectors, respectively. +Here, again, $\vec{v}^{\dagger}$ represents the conjugate transpose of $\vec{v}$. +By definition, and as can be easily seen in matrix representation, the identity +\begin{equation} +(\vec{u}\otimes\vec{v})\vec{w}=\vec{u}(\vec{v},\vec{w}) +\end{equation} +holds. +\end{remark} + \section{Spherical coordinates} \section{Fourier integrals}