About computing the tangent space at 1 of certain lie groups

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Discussion Overview

The discussion revolves around methods for computing the tangent spaces at the identity element of certain Lie groups, specifically ##T_ISL_n(R)##, ##T_IU(n)##, and ##T_ISU(n)##. Participants explore definitions, examples, and approaches related to the calculation of these tangent spaces, focusing on theoretical and mathematical reasoning.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant outlines a method for defining tangent vectors using smooth curves and equivalence classes, emphasizing the role of charts and the Jacobi matrix in the definition of tangent spaces.
  • Another participant references an external example related to ##GL(n)## and ##SL(n)##, suggesting that similar methods could be applied to compute the tangent spaces in question.
  • Several participants propose defining curves that map to the identity matrix and expanding these curves into Taylor series to find tangent vectors, highlighting the importance of covering all dimensions of the manifold.
  • There is a suggestion to use canonical Cartesian coordinate systems to facilitate the calculation of tangent spaces, with specific equations provided for the determinant condition and matrix differentiation.
  • Some participants express uncertainty about the completeness of their proposed methods and the necessity of finding all possible curves to span the tangent space.

Areas of Agreement / Disagreement

Participants generally agree on the need to define curves and use Taylor expansions to compute tangent spaces, but there is no consensus on the best method or approach to be used. Multiple competing views and methods remain present in the discussion.

Contextual Notes

Participants note the importance of defining appropriate curves and the conditions that must be satisfied for these curves to lie within the manifold. There is also mention of the potential complexity involved in finding all necessary curves to span the tangent space.

aalma
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Hello :),

I am wondering of the right and direct method to calculate the following tangent spaces at ##1##: ##T_ISL_n(R)##, ##T_IU(n)## and ##T_ISU(n)##.

Definitions I know:
Given a smooth curve ##γ : (− ,) → R^n## with ##γ(0) = x##, a tangent vector ##˙γ(0)## is a vector with components ##(˙γ1,..., ˙γn)##.
Two (smooth) curves ##γ,γ': (− ,) → M## with ##γ(0) = γ'(0) = x## are called equivalent if in a certain chart containing x (or in any chart) they define the same tangent vector at ##x##.
We define ##T_x(M)## to be the set of equivalence classes of curves as above. We note that ##T_x(M)## is a vector space: Choose a chart ##a : U → R^n## containing x. Then the assignment ##γ → d/dt (a ◦ γ)(0)## defines a bijection from ##T_x(M)## to ##R^n##. Different charts define different bijections, but they differ by the Jacobi matrix: if ##b : U → R^n## is another chart, the bijections from ##Tx(M)## to ##R^n## differ by the Jacobi matrix at ##a(x)## of the transformation ##b◦a^{−1} : a(U) → b(U)##.
Example: Let ##G = SO(n,R)## and let ##γ## be a curve in ##G## with ##γ(0) = 1##. Then we can write ##γ(s) = 1 + sA + o(s^2)## where ##A ∈ M_{n× n}## and we want to describe possible values for ##A##. Obviously ##γ(s)^t = 1 + sA^t + o(s^2)## so ##1 = γ(s)γ(s)^t = 1 + s(A + A^t) + o(s^2)## which implies that ##A## is skewsymmetric. In the opposite direction, if ##A## is skew-symmetric, ##γ(s) = e^{sA}## is orthogonal and ##e^{sA} = 1 + sA + o(s^2)##. We have proven that ##T_1(G)## in this case is the vector space of skew-symmetric matrices.

Can you please suggest a way to compute such tangent spaces.
 
Last edited:
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aalma said:
Is there a way to calculate the above tangent spaces in a way similar to the example I added?
You need to define curves ##\gamma \, : \,(-1,1) \longrightarrow M## with ##\gamma(0)=x## where ##x=I## is the identity matrix in your case. Then you expand ##\gamma(t)## into a Taylor series, and ##\dot\gamma(0)## will be your tangent vectors. Next, gather so many curves ##\gamma(t) ## such that you cover all ##\operatorname{dim}M## many possible directions to be able to span ##T_x(M).##

The procedure in the link does the same, only that it uses the canonical Cartesian coordinate system:
$$
T_x(M)=\operatorname{span}\left\{\sum_{i,j}^{\operatorname{dim}M} \left. a_{ij} \dfrac{\partial }{\partial x_{ij}}\right|_{t=0} \gamma(t)\right\}
$$
and the obvious curves
\begin{align*}
\gamma \, : \,(-1,1) &\longrightarrow M\\
t &\longmapsto \begin{pmatrix}1 &0 &\ldots &0\\ \ldots &x_{ij}&\ldots&0 \\ 0&0&\ldots& 1\end{pmatrix} \in M
\end{align*}
plus the defining equations, e.g. ##\det(a_{ij})=1## and / or ##(a_{ij}) + (a_{ij})^*=0.##The next problem is to find all curves. These are ##\operatorname{dim}M## many different ones since ##\operatorname{dim}T_x(M)=\operatorname{dim}M.##

In the linked article, I have chosen the easiest ones, still given the Cartesian coordinate system. E.g. a typical element of ##M=\operatorname{SL}(2)## looks like
\begin{align*}
X(t)&=\begin{pmatrix}x_{11}(t)&x_{12}(t)\\ x_{21}(t)&x_{22}(t) \end{pmatrix}\; \\&\wedge \;x_{11}(t)\cdot x_{22}(t)- x_{21}(t)\cdot x_{12}(t)=1\; \\&\wedge \;x_{11}(0)=1\, , \,x_{12}(0)=0\, , \,x_{21}(0)=0\, , \,x_{22}(0)=1
\end{align*}

and a typical curve accordingly
$$
\gamma (t)=X(t)\, , \,\gamma(0)=X(0)=I
$$
Differentiation for those matrices is easier than the full Taylor expansion. We are only interested in the second term evaluated at the identity matrix ##I## anyway. This would be the calculation in equations (26) and (27) for the determinant condition:
$$
\left. \dfrac{d}{dt}\right|_{t=0}\operatorname{det}(\gamma(t))=\left. \dfrac{d}{dt}\right|_{t=0}1=0=\operatorname{trace}\left(a_{ij}\right)
$$

Of course, you can choose your own charts (providing the coordinate system), curves (providing the tangent vectors at ##x=I##), and calculate the entire Taylor series, but the Cartesian charts, coordinate functions ##t\mapsto (x_{ij}(t))##, and the first derivative ##\left(\left. \dfrac{d}{dt}\right|_{t=0}x_{ij}(t)\right)## are likely the easiest you can get. The crucial condition is ##\gamma(t)\in M## with ##\gamma(0)=I.##
 
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fresh_42 said:
You need to define curves ##\gamma \, : \,(-1,1) \longrightarrow M## with ##\gamma(0)=x## where ##x=I## is the identity matrix in your case. Then you expand ##\gamma(t)## into a Taylor series, and ##\dot\gamma(0)## will be your tangent vectors. Next, gather so many curves ##\gamma(t) ## such that you cover all ##\operatorname{dim}M## many possible directions to be able to span ##T_x(M).##

The procedure in the link does the same, only that it uses the canonical Cartesian coordinate system:
$$
T_x(M)=\operatorname{span}\left\{\sum_{i,j}^{\operatorname{dim}M} \left. a_{ij} \dfrac{\partial }{\partial x_{ij}}\right|_{t=0} \gamma(t)\right\}
$$
and the obvious curves
\begin{align*}
\gamma \, : \,(-1,1) &\longrightarrow M\\
t &\longmapsto \begin{pmatrix}1 &0 &\ldots &0\\ \ldots &x_{ij}&\ldots&0 \\ 0&0&\ldots& 1\end{pmatrix} \in M
\end{align*}
plus the defining equations, e.g. ##\det(a_{ij})=1## and / or ##(a_{ij}) + (a_{ij})^*=0.##The next problem is to find all curves. These are ##\operatorname{dim}M## many different ones since ##\operatorname{dim}T_x(M)=\operatorname{dim}M.##

In the linked article, I have chosen the easiest ones, still given the Cartesian coordinate system. E.g. a typical element of ##M=\operatorname{SL}(2)## looks like
\begin{align*}
X(t)&=\begin{pmatrix}x_{11}(t)&x_{12}(t)\\ x_{21}(t)&x_{22}(t) \end{pmatrix}\; \\&\wedge \;x_{11}(t)\cdot x_{22}(t)- x_{21}(t)\cdot x_{12}(t)=1\; \\&\wedge \;x_{11}(0)=1\, , \,x_{12}(0)=0\, , \,x_{21}(0)=0\, , \,x_{22}(0)=1
\end{align*}

and a typical curve accordingly
$$
\gamma (t)=X(t)\, , \,\gamma(0)=X(0)=I
$$
Differentiation for those matrices is easier than the full Taylor expansion. We are only interested in the second term evaluated at the identity matrix ##I## anyway. This would be the calculation in equations (26) and (27) for the determinant condition:
$$
\left. \dfrac{d}{dt}\right|_{t=0}\operatorname{det}(\gamma(t))=\left. \dfrac{d}{dt}\right|_{t=0}1=0=\operatorname{trace}\left(a_{ij}\right)
$$

Of course, you can choose your own charts (providing the coordinate system), curves (providing the tangent vectors at ##x=I##), and calculate the entire Taylor series, but the Cartesian charts, coordinate functions ##t\mapsto (x_{ij}(t))##, and the first derivative ##\left(\left. \dfrac{d}{dt}\right|_{t=0}x_{ij}(t)\right)## are likely the easiest you can get. The crucial condition is ##\gamma(t)\in M## with ##\gamma(0)=I.##
fresh_42 said:
You need to define curves ##\gamma \, : \,(-1,1) \longrightarrow M## with ##\gamma(0)=x## where ##x=I## is the identity matrix in your case. Then you expand ##\gamma(t)## into a Taylor series, and ##\dot\gamma(0)## will be your tangent vectors. Next, gather so many curves ##\gamma(t) ## such that you cover all ##\operatorname{dim}M## many possible directions to be able to span ##T_x(M).##

The procedure in the link does the same, only that it uses the canonical Cartesian coordinate system:
$$
T_x(M)=\operatorname{span}\left\{\sum_{i,j}^{\operatorname{dim}M} \left. a_{ij} \dfrac{\partial }{\partial x_{ij}}\right|_{t=0} \gamma(t)\right\}
$$
and the obvious curves
\begin{align*}
\gamma \, : \,(-1,1) &\longrightarrow M\\
t &\longmapsto \begin{pmatrix}1 &0 &\ldots &0\\ \ldots &x_{ij}&\ldots&0 \\ 0&0&\ldots& 1\end{pmatrix} \in M
\end{align*}
plus the defining equations, e.g. ##\det(a_{ij})=1## and / or ##(a_{ij}) + (a_{ij})^*=0.##The next problem is to find all curves. These are ##\operatorname{dim}M## many different ones since ##\operatorname{dim}T_x(M)=\operatorname{dim}M.##

In the linked article, I have chosen the easiest ones, still given the Cartesian coordinate system. E.g. a typical element of ##M=\operatorname{SL}(2)## looks like
\begin{align*}
X(t)&=\begin{pmatrix}x_{11}(t)&x_{12}(t)\\ x_{21}(t)&x_{22}(t) \end{pmatrix}\; \\&\wedge \;x_{11}(t)\cdot x_{22}(t)- x_{21}(t)\cdot x_{12}(t)=1\; \\&\wedge \;x_{11}(0)=1\, , \,x_{12}(0)=0\, , \,x_{21}(0)=0\, , \,x_{22}(0)=1
\end{align*}

and a typical curve accordingly
$$
\gamma (t)=X(t)\, , \,\gamma(0)=X(0)=I
$$
Differentiation for those matrices is easier than the full Taylor expansion. We are only interested in the second term evaluated at the identity matrix ##I## anyway. This would be the calculation in equations (26) and (27) for the determinant condition:
$$
\left. \dfrac{d}{dt}\right|_{t=0}\operatorname{det}(\gamma(t))=\left. \dfrac{d}{dt}\right|_{t=0}1=0=\operatorname{trace}\left(a_{ij}\right)
$$

Of course, you can choose your own charts (providing the coordinate system), curves (providing the tangent vectors at ##x=I##), and calculate the entire Taylor series, but the Cartesian charts, coordinate functions ##t\mapsto (x_{ij}(t))##, and the first derivative ##\left(\left. \dfrac{d}{dt}\right|_{t=0}x_{ij}(t)\right)## are likely the easiest you can get. The crucial condition is ##\gamma(t)\in M## with ##\gamma(0)=I.##
Thanks. Can you please give more deatils of how to do the calculations with taylor series expansion?
 

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