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Consider the following problem:

A function $g:\mathbb R\to\mathbb R$ given by $g(t)=yt+x$, $t$,$x$,$y\in\mathbb R$, $y>0$, is called a proper affine function. The subset of all such functions with respect to the usual composition law is a Lie group $G$. As a differentiable manifold $G$ is simply the upper half-plane, that is, $\{(x,y)\in\mathbb R^2|y>0\}$ with the usual differentiable structure. Prove that:

(a) The left-invariant Riemannian metric of $G$ which at the neutral element $e=(0,1)$ coincides with the Euclidean metric ($g_{11}=g_{22}=1,g_{12}=0$) is given by $g_{11}=g_{22}=\frac{1}{y^2},g_{12}=0$.

This question already has an answer here, but I did not understand the argument. Also, I took another path and I would like to know if what I did is reasonable and how to finnish the question following this line of thought.

Here is my attempt:

Note that the tangent space of $G$ at the point $g \in G$ is nothing but $\mathbb R^2$. The parametrization $x$ is just the identity of $\mathbb R^2$. Then $$ d x_g(1, 0) = (1, 0), \quad d x_g(0, 1) = (0, 1) $$ for all $g \in G$ and therefore $$ g_{ij}(0, 1) = \delta_{ij}, $$ since $\langle \cdot, \cdot \rangle_e$ coincides with the euclidean inner product.

Now, for $g \in G$ we have \begin{align*} g_{11}( x^{-1}(g)) = & \langle d x_g(1, 0), d x_g(1, 0) \rangle_g \\ = & \langle d (L_{g^{-1}})_g(1, 0), d (L_{g^{-1}})_g(1, 0) \rangle_e \end{align*}

I am stuck on how to compute the derivative $d(L_{g^{-1}})_g$. Any hints will be the most appreciated.

Thanks in advance and kind regards.

Ivo Terek
  • 77,665

2 Answers2

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There's no point in computing $g_{ij}(0,1) = \delta_{ij}$. That was given to you and the point of the exercise is to spread that to the whole half-plane. Let $h(t) = a+bt$ with $b>0$. Then for $g(t) = x+yt$, with $y>0$ we have that $$(L_gh)(t) = g(h(t)) = x+yh(t) = x+y(bt+a) = ya+x+ybt.$$This means that under the identification of the manifold of proper affine functions with the upper half-plane, the group operation is $$L_gh = L_{(x,y)}(a,b) = (x,y)(a,b) = (ya+x, yb).$$Since $L_{(x,y)}$ differs from a linear map (namely, $y\,{\rm Id}$) by the constant $(x,0)$, the derivative is $${\rm d}(L_{(x,y)})_{(a,b)} = \begin{pmatrix} y & 0 \\ 0 & y \end{pmatrix}\implies{\rm d}(L_{(x,y)^{-1}})_{(x,y)} = {\rm d}(L_{(x,y)})_{(0,1)}^{-1} = \begin{pmatrix} 1/y & 0 \\ 0 & 1/y \end{pmatrix} $$Since all left translations are isometries, then $g_{(x,y)} = (L_{(x,y)^{-1}})^*(g_{(0,1)})$. In matrix form this means that $$(g_{ij}(x,y))_{i,j=1}^2 =\begin{pmatrix} 1/y & 0 \\ 0 & 1/y \end{pmatrix}^\top \begin{pmatrix} 1 & 0 \\ 0 & 1 \end{pmatrix}\begin{pmatrix} 1/y & 0 \\ 0 & 1/y \end{pmatrix} = \frac{1}{y^2}\begin{pmatrix} 1 & 0 \\ 0 & 1\end{pmatrix}. $$

Ivo Terek
  • 77,665
  • Thank you very much. Using your hint of decomposing $L_{(x, y)} = y Id + (x, 0)$ I was able to complete the solution. However, I did not understand the meaning of $g_{(x, y)} = (L_{(x, y)^{-1}})^*(g_{(0, 1)})$. What does it mean? And why did you compute the square of $g_{ij}$ in the last line? – Danilo Gregorin Afonso Jun 23 '20 at 14:41
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  • the metric at $(x,y)$ is the pull-back of the metric at $(0,1)$ under $L_{(x,y)^{-1}}$; 2) Not a square. Standard matrix notation such as $(a_{ij})_{i,j=1}^n$.
  • – Ivo Terek Jun 23 '20 at 15:58
  • I looked for pullbacks in Lee's book on smooth manifolds and there is an uncountable number of them. Which one am I looking for? – Danilo Gregorin Afonso Jun 23 '20 at 20:12
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    The metric is a $(0,2)$-tensor. You're looking for pull-backs of covariant tensor fields. Here's the definition: if $f:M\to N$ is smooth and $T$ is a covariant tensor field on $N$, the covariant tensor field $f^T$ on $M$ is defined by $$(f^T)p(v_1,...,v_k)=T{f(p)}({\rm d}f_p(v_1),...,{\rm d}f_p(v_k)).$$ – Ivo Terek Jun 23 '20 at 20:16