forked from lazierthanthou/Lecture_Notes_GR
-
Notifications
You must be signed in to change notification settings - Fork 2
/
lecture5.tex
268 lines (234 loc) · 16 KB
/
lecture5.tex
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
\section{Tangent Spaces}
Lead question: ``What is the velocity of a curve $\gamma : \R \to M$ at the point $p$ of the curve in $M$?''
\subsection{Velocities}
% \url{https://youtu.be/pepU_7NJSGM?t=1m30s}
\begin{definition} Let $\mfd$ be a smooth manifold. Let there be a curve $\gamma : \R \to M$, which is at least $C^1$. Suppose $\gamma(\lambda_0) =p$. The \textbf{velocity} of $\gamma$ at the point $p$ of the curve $\gamma$ is the linear map \\
\begin{equation}\label{eq_velocity}
v_{\gamma, p} : C^{\infty}(M) \linearmapto \R \text{ with }
f \mapsto v_{\gamma,p}(f):= (f \after \gamma)^{\prime}(\lambda_0)
\end{equation}
where $C^{\infty}(M) := \lbrace f: M \to \R \, | \, f \text{ is a smooth function } \rbrace$ equipped with \\
$(f \oplus g)(p) := f(p) + g(p)$ and $(\lambda \otimes g)(p) := \lambda \cdot g(p)$ is a vector space.
\end{definition}
\begin{SCfigure}[5][h]
\label{fig:L5_fAfterGamma}
\centering
\begin{tikzpicture}
\matrix (m) [matrix of math nodes, row sep=4em, column sep=6em, minimum width=2em]
{
\R & M & \R \\
};
\path[->]
(m-1-1) edge node [auto] {$\gamma$} (m-1-2)
edge [bend right=30] node [auto] {$f \after \gamma$} (m-1-3)
(m-1-2) edge node [auto] {$f $} (m-1-3);
\end{tikzpicture}
\caption{$f \after \gamma$. Intuition: If the first $\R$ is thought of as time, and $f$ as temperature, then $f \after \gamma$ relates time and temperature and $(f \after \gamma)^\prime$ is the rate of change of temperature as you run around the curve.}
\end{SCfigure}
\underline{past}: `` $\underbrace{v^i}_{\text{vector in past}} (\partial_i f) = (\underbrace{v^i \partial_i}_{\text{vector as map}})f$ \\
\textit{In an imprecise way, we could say that we want vectors to survive as the directional derivatives they induce. This is a very slight shift of perspective which is extremely powerful and leads to idea of tangent space in differential geometry.}
\underline{Terminology}: If $X$ is a vector seen as a map, then $X$ acting on a function $f$, i.e. $Xf$ is called the \textbf{directional derivative of $f$ in the $X$ direction}.
\subsection{Tangent vector space}
\begin{definition}
For each point $p \in M$, the \textbf{tangent space} to $M$ at the point $p$ is the set \\
\begin{equation}\label{Eq:L5_defTangentSpace}
T_p M := \lbrace v_{\gamma, p} \, | \, \text{ for all smooth curves } \gamma \text{ through } p \rbrace
\end{equation}
\end{definition}
\begin{SCfigure}[5][h]
\label{fig:L5_TangentPlane}
\centering
\includegraphics[width=0.3\textwidth]{5_Tangent_plane}
\caption{A pictorial representation of the tangent space $T_xM$ of a single point, x, on a manifold. A vector in this $T_xM$ can represent a possible velocity at x. After moving in that direction to a nearby point, one's velocity would then be given by a vector in the tangent space of that nearby point — a different tangent space, not shown. \textit{By Alexwright at English Wikipedia - Transferred from en.wikipedia to Commons by Ylebru., Public Domain \url{https://commons.wikimedia.org/w/index.php?curid=3941393}}}
\end{SCfigure}
\begin{SCfigure}[5][h]
\label{fig:L5_TangentVector}
\centering
\includegraphics[width=0.3\textwidth]{5_Tangential_vector}
\caption{The tangent space $T_xM$ and a tangent vector $v \in T_xM$, along a curve travelling through $x \in M$. \textit{By derivative work: McSush (talk)Tangentialvektor.png: TNThe original uploader was TN at German Wikipedia - Tangentialvektor.png, Public Domain, \url{https://commons.wikimedia.org/w/index.php?curid=4821938}}}
\end{SCfigure}
\textit{\textbf{Caution}: Although the Fig. \ref{fig:L5_TangentPlane} and \ref{fig:L5_TangentVector} refer to an ambient space in which $M$ is embedded, the tangent space has been defined intrinsically. There is a velocity corresponding to each curve along a different path in $M$ passing through $p$. Velocity along two different curves could be same, or curves along same paths but having different parameter speeds would yield different velocities.}
\begin{theorem}
$(T_pM, \oplus, \otimes)$ is a vector space with
\begin{align*}
\oplus : & T_pM \times T_pM \to Hom(C^\infty(M),\R) \\
& (v_{\gamma,p} \oplus v_{\delta,p})(\underbrace{f}_{ \in C^{\infty}(M)} ) := v_{\gamma,p}(f) +_{\R} v_{\delta,p}(f) \\
\odot : & \R \times T_pM \to Hom(C^{\infty}(M),\R) \\
& (\alpha \odot v_{\gamma,p} )(f) := \alpha \cdot_{\R} v_{\gamma, p}(f)
\end{align*}
\end{theorem}
\begin{proof} Various conditions that must be satisfied by a vector space, are trivially satisfied. It remains to be shown that
\begin{enumerate}[i)]
\item For product, $\exists \, \tau $ curve : $\alpha \odot v_{\gamma,p} = v_{\tau,p}$
\item For sum, $\exists \, \sigma$ curve : $v_{\gamma,p} \oplus v_{\delta,p} = v_{\sigma,p}$
\end{enumerate}
\underline{Product}: Let $\tau : \R \to M$ with $\lambda \mapsto \tau(\lambda) := \gamma(\alpha \lambda + \lambda_0) = (\gamma \after \mu_{\alpha})(\lambda)$
where $\mu_{\alpha} : \R \to \R$ with $r \mapsto \alpha \cdot r + \lambda_0$. Then $\tau(0) = \gamma(\lambda_0) = p$, and
\[
v_{\tau,p} = (f \after \tau)^{\prime}(0) = (f \after \gamma \after \mu_{\alpha})^{\prime}(0) = \mu_{\alpha}^{\prime}(0) \cdot (f \after \gamma)^{\prime}(\mu_{\alpha}(0)) = \alpha \cdot (f \after \gamma)^{\prime}(\lambda_0) = \alpha \cdot v_{\gamma,p}
\]
\underline{Sum}: Choose a chart $(U,x)$ and $p \in U$. \textit{(If the proof will depend on the choice of a chart, alarm bells should ring. But we shall see that the result is finally independent of the chart.)} \\
Let $p = \gamma(\lambda_0) = \delta(\lambda_1)$. \\
Now define $\sigma : \R \to M$ with $\lambda \mapsto \sigma(\lambda) := x^{-1}(\underbrace{(x \after \gamma)(\lambda_0 + \lambda)}_{\R \to \R^d} + (x \after \delta)(\lambda_1 + \lambda) - (x \after \gamma)(\lambda_0))$. \\
Then, $\sigma_x(0) = x^{-1}((x \after \gamma)(\lambda_0) + (x \after \delta)(\lambda_1) - (x \after \gamma)(\lambda_0)) = \delta(\lambda_1) = p$. \\
Now
\begin{align*}
v_{\sigma_x,p}(f) & := (f \after \sigma_x)^{\prime}(0) \\
& = ( \underbrace{(f \after x^{-1})}_{\R^d \to \R} \after \underbrace{(x \after \sigma_x)}_{\R \to \R^d})^{\prime}(0) \\
& = \underbrace{(x \after \sigma_x)^{\prime}(0)}_{(x \after \gamma)^{\prime}(\lambda_0) + (x \after \delta)^{\prime}(\lambda_1)} \cdot \left( \partial_i (f \after x^{-1}) \right)(x(\underbrace{\sigma(0)}_{p})) \\
& = (x \after \gamma)^{\prime}(\lambda_0)(\partial_i (f \after x^{-1}))(x(p)) + (x \after \delta)(\lambda_1)(\partial_i (f \after x^{-1}))(x(p)) \\
& = (f \after \gamma)^{\prime}(\lambda_0) + (f \after \delta)^{\prime}(\lambda_1) \\
& = v_{\gamma,p}(f) + v_{\delta,p}(f) && \forall \, f \in C^{\infty}(M)
\end{align*}
\end{proof}
\textit{\textbf{Note}: If we push $\gamma$ and $\delta$ to one chart, and add them there, then bring the sum back to $M$, we would get a curve which would be different from the curve we would get if we used another chart. But it turns out, irrespective of the charts selected, we get the same tangent/velocity. Conclusion: Adding trajectories is chart dependent; hence, bad. Adding velocities is good because, whatever the charts, they yield the same derivative at the point of intersection. Of course, you cannot add two curves $(\gamma \oplus \delta)(\lambda) := \gamma(\lambda) +_M \delta(\lambda)$ because there is no addition $+_M$ in $M$. Defining $+$ through charts results in chart-dependent results, which is, therefore, not real.}
\subsection{Components of a vector w.r.t. a chart}
\begin{tikzpicture}
\matrix (m) [matrix of math nodes, row sep=4em, column sep=6em, minimum width=2em]
{
\R & M & \R \\
& \R^d & \\
};
\path[->]
(m-1-1) edge node[auto] {$\gamma$} (m-1-2)
edge node[sloped, anchor=center, below] {$x \after \gamma$} (m-2-2)
(m-1-2) edge node[auto] {$x$} (m-2-2)
edge node[auto] {$f$} (m-1-3)
(m-2-2) edge node[sloped, anchor=center, below] {$f \after x^{-1}$} (m-1-3);
\end{tikzpicture}
Let $(U,x) \in \A_{\text{smooth}}, \, \gamma : \R \to U$ and $\gamma(0) = p$. Then
\begin{align*}
v_{\gamma,p}(f) & := (f \after \gamma)^\prime(0) \\
& = (\underbrace{(f \after x^{-1})}_{\R^d \to \R} \after \underbrace{(x \after \gamma)}_{\R \to \R^d})^\prime(0) \\
& = \displaystyle\left(\left(x \after \gamma\right)^\prime\right)^i(0) \cdot \left(f \after x^{-1}\right)^\prime_i(x(p)) \\
& = \underbrace{\displaystyle\left(\left(x \after \gamma\right)^\prime\right)^i(0)}_{=: \dot{\gamma}_x^i(0)} \cdot \underbrace{(\partial_i(f \after x^{-1}))(x(p))}_{=: \left(\cibasis[f]{x^i}\right)_p} \\
& = \dot{\gamma}_x^i(0) \cdot \left(\cibasis{x^i}\right)_p f && \forall \, f \in C^{\infty}(M), f : M \to \R
\end{align*}
\begin{definition}
For velocity $v_{\gamma,p}$, as a map under use of a chart $(U,x)$,
\begin{equation}\label{eq:defVelocityExpansion}
\boxed{v_{\gamma,p} = \dot{\gamma}_x^i(0) \cdot \left(\cibasis{x^i}\right)_p}
\end{equation}
where
\begin{equation}\label{eq:defVelocityComponents}
\displaystyle\dot{\gamma}_x^i = \left(\left(x \after \gamma\right)^\prime\right)^i
\end{equation}
are the \textbf{components of the velocity} $v_{\gamma,p}$ and
\begin{equation}\label{eq:defCIBasis}
\displaystyle\left(\cibasis{x^i}\right) = \partial_i\left(\,\cdot \after x^{-1}\right) = \left(\left(\, \cdot \after x^{-1}\right)^\prime\right)^i
\end{equation}
which eat a function, form a basis of $T_pM$ w.r.t. which the components of the velocity need to be understood.
\end{definition}
\textit{Note: The components of a vector are always w.r.t. a chart. In $M$, there is just the vector, no components.} \\
\begin{theorem}
\label{thm:L5_dxiupondxj}
For a chart $(U,x)$,
\begin{equation}
\boxed{\cibasis[x^i]{x^j} = \delta^i_j}
\end{equation}
\end{theorem}
\begin{proof}
\begin{align*}
\cibasis[x^i]{x^j} = \partial_j (x^i \after x^{-1})(x(p)) = \delta^i_j && \text{(since } x^i \after x^{-1} : \R^d \to \R \text{ s.t. } (\alpha^1 , \dots , \alpha^d) \mapsto \alpha^i)
\end{align*}
\end{proof}
\subsection{Chart-induced basis}
\begin{definition}
If $(U,x) \in \A_{\text{smooth}}$, then $\displaystyle\left(\cibasis{x^1}\right)_p, \dotsc, \left(\cibasis{x^d}\right)_p \in T_pU \subseteq T_pM$ constitute a \textbf{chart-induced basis} of $T_pU$.
\end{definition}
\begin{proof} We have already shown that any vector in $T_pU$ can be expressed in terms of $\displaystyle\left(\cibasis{x^i}\right)_p$. It remains to be shown that they are linearly independent. That is, we require $\displaystyle\lambda^i \left(\cibasis{x^i}\right)_p = 0 \implies \lambda^i = 0$ for all $i = 1, \dotsc, d$. Or,
\begin{align*}
0 & = \lambda^i \left(\cibasis{x^i}\right)_p(x^j) && x^j : U \to \R \text{ is differentiable}\\
& = \lambda^i \partial_i (x^j \after x^{-1})(x(p)) && \text{by Eq. \ref{eq:defCIBasis}} \\
& = \lambda^i \delta^j_i && \text{by Theorem \ref{thm:L5_dxiupondxj}} \\
& = \lambda^j && \text{for all } j = 1, \dotsc, d
\end{align*}
\end{proof}
\begin{corollary}
$dim \, T_pM = d = dim \, M$. \\
This follows from the fact $d$ vectors are needed to express any vector in $T_pM$, and these $d$ vectors arise from the $d$ coordinates of chart which shows that $M$ has $d$ dimensions.
\end{corollary}
\underline{Terminology}: $X \in T_pM \implies \exists \, \gamma : \R \to M : X = v_{\gamma,p}$ and $\displaystyle \exists \, \underbrace{X^1, \dotsc, X^d}_{\in \R} : X = X^i \left(\cibasis{x^i}\right)_p$. $X^i$ are called \textbf{components of the vector $X$ w.r.t chart-induced basis}.
\subsection{Change of vector components under a change of chart}
\ding{56} A vector does not change under change of chart; only the vector components do.
Let $(U,x)$ and $(V,y)$ be overlapping charts and $p \in U \cap V$. Let $X \in T_pM$. Then, $X$ can be expanded in terms of chart-induced basis of the two charts as follows:
\begin{equation}\label{eq:L5_VecExpandedIn2Charts}
X^i_{(y)} \cdot \left(\cibasis{y^i}\right)_p \underbrace{=}_{(V,y)} X \underbrace{=}_{(U,x)} X^i_{(x)} \cdot \left(\cibasis{x^i}\right)_p
\end{equation}
\begin{align*}
\text{Now, } \quad \quad \left(\cibasis{x^i}\right)_p f & = \partial_i(f \after x^{-1})(x(p)) \\
& = \partial_i (\underbrace{(f \after y^{-1})}_{\R^d \to \R} \after (\underbrace{y \after x^{-1}}_{\R^d \to \R^d})(x(p)) \\
& = (\partial_i (y \after x^{-1})^j)(x(p)) \cdot (\partial_j (f \after y^{-1}))(y(p)) \\
& = (\partial_i (y^j \after x^{-1}))(x(p)) \cdot (\partial_j (f \after y^{-1}))(y(p)) \\
& = \boxed{\left(\cibasis[y^j]{x^i}\right)_p \cdot \left(\cibasis[f]{y^j}\right)_p}
\end{align*}
\begin{equation}\label{eq:L5_cibasisIn2Charts}
\therefore \boxed{\left(\cibasis{x^i}\right)_p = \left(\cibasis[y^j]{x^i}\right)_p \cdot \left(\cibasis{y^j}\right)_p}
\end{equation}
Using Eq. \ref{eq:L5_VecExpandedIn2Charts} and Eq. \ref{eq:L5_cibasisIn2Charts},
\[
X^i_{(x)} \left(\cibasis[y^j]{x^i}\right)_p \left(\cibasis{y^j}\right)_p = X^j_{(y)}\left(\cibasis{y^j}\right)_p
\]
\begin{equation}
\therefore \boxed{X^j_{(y)} = \left(\cibasis[y^j]{x^i}\right)_p X^i_{(x)}}
\end{equation}
\subsection{Cotangent spaces}
% \url{https://youtu.be/pepU_7NJSGM?t=1h24m36s}
Since $T_pM$ is a vector space, therefore it is trivial to define cotangent space as follows.
\begin{definition}
For the tangent space $T_pM$ at $p \in M$, \textbf{cotangent space} is defined as
\begin{equation}
(T_pM)^* := \lbrace \varphi : T_pM \linearmapto \R \rbrace
\end{equation}
\end{definition}
\begin{definition}
\label{def:gradient}
If $f \in C^{\infty}(M)$, then the \textbf{gradient of $f$ at the point $p \in M$} is defined as
\begin{align}
\label{eq:defGradient}
(df)_p : & T_p M \linearmapto \R \nonumber \\
& X \mapsto (df)_p(X) := Xf
\end{align}
\end{definition}
i.e. $\boxed{(df)_p \in T_pM^*}$
$(df)_p$ is a $(0,1)$-tensor over the underlying vector space $T_pM$. We define the components of the gradient the same way as we define the components of a tensor (refer section \ref{ss:L3_TensorComponents}).
\begin{definition}
\textbf{Components of gradient w.r.t. chart-induced basis of $(U,x)$} are defined as
\begin{equation}
\left((df)_p \right)_j := (df)_p\left(\left(\cibasis{x^j}\right)_p \right) = \left(\cibasis[f]{x^j}\right)_p = \partial_j (f \after x^{-1})(x(p))
\end{equation}
\end{definition}
\begin{theorem}
A chart $(U,x) \implies x^i : U \to \R$ are smooth functions. Then, $(dx^1)_p, (dx^2)_p, \dotsc, (dx^d)_p$ form a basis of $T_p^*M$.
\end{theorem}
\begin{proof}
In fact, $(dx^i)_p$ form a dual basis since
\begin{equation}
(dx^a)_p \left(\left(\cibasis{x^b}\right)_p \right) = \left(\cibasis[x^a]{x^b}\right)_p = \delta_b^a \textit{ (using Theorem \ref{thm:L5_dxiupondxj})}
\end{equation}
\end{proof}
\subsection{Change of components of a covector under a change of chart}
\ding{56} A covector does not change under change of chart; only the covector components do.
Let $(U,x)$ and $(V,y)$ be overlapping charts and $p \in U \cap V$. Let $\omega \in T_p^*M$. Then, $\omega$ can be expanded in terms of chart-induced basis of the two charts as follows:
\begin{equation}\label{eq:L5_CovecExpandedIn2Charts}
\displaystyle\omega_{(y)k}(dy^k)_p \underbrace{=}_{(V,y)} \omega \underbrace{=}_{(U,x)} \omega_{(x)j}(dx^j)_p
\end{equation}
\begin{align*}
\implies && \displaystyle\omega_{(y)k}(dy^k)_p \left(\cibasis{y^i}\right)_p & = \omega_{(x)j}(dx^j)_p \left(\cibasis{y^i}\right)_p \\
\implies && \displaystyle\omega_{(y)k} \left(\cibasis[y^k]{y^i}\right)_p & = \omega_{(x)j} \left(\cibasis[x^j]{y^i}\right)_p && \text{by Eq. \ref{eq:defGradient}} \\
\implies && \displaystyle\omega_{(y)k} \delta^k_i & = \omega_{(x)j} \left(\cibasis[x^j]{y^i}\right)_p && \text{by Theorem \ref{thm:L5_dxiupondxj}}
\end{align*}
\begin{align}
\implies && \boxed{\omega_{(y)i} = \left(\cibasis[x^j]{y^i}\right)_p \omega_{(x)j}} &&
\end{align}
%\begin{align*}
%\implies && \omega_{(y)i}(dy^i)_p & = \left(\cibasis[x^j]{y^i}\right)_p \omega_{(x)j}(dy^i)_p \\
%\implies && \omega & = \left(\cibasis[x^j]{y^i}\right)_p \omega_{(x)j}(dy^i)_p \\
%\implies && \omega (dx^j)_p & = \left(\cibasis[x^j]{y^i}\right)_p \omega_{(x)j}(dy^i)_p (dx^j)_p \\
%\implies && \omega (dx^j)_p & = \left(\cibasis[x^j]{y^i}\right)_p \omega (dy^i)_p \\
%\implies && (dx^j)_p & = \left(\cibasis[x^j]{y^i}\right)_p (dy^i)_p
%\end{align*}
%
%\begin{equation}\label{eq:L5_cicobasisIn2Charts}
%\therefore \boxed{(dx^j)_p = \left(\cibasis[x^j]{y^i}\right)_p (dy^i)_p}
%\end{equation}