Lie Groups and Lie Algebras Lecture 3 notes

Definition: Tangent Space

The tangent space TPMT_P M to MM at point PP is just the set of all tangent vectors at PP.
TPMT_PM is obviously a vector space of the same dimension as MM #-> because even though MM may be embedded in a higher dimensional space, the tangent space has same dimension as MM's local euclidian space

Definition: Tangent Bundle

The tangent bundle TMTM of a smooth manifold MM is the set of pairs (P,ξ)(P, \xi) where PMP\in M and ξTPM\xi \in T_PM.
The observation is that the tangent bundle is also a smooth manifold of dimension 2M2M. #-> Because the points have dimension MM and the vectors have dimension MM
The charts for TMTM are defined by taking a chart UU for MM, then considering the subset TUTU that corresponds to restricting TMTM to points in PP.
Then, because we have a fixed local coordinate system on UU (because MM is a smooth manifold), each tangent vector for some PUP\in U is uniquely determined by its components.
This means that there is a natural bijection between TUTU and ϕ(U)×Rm\phi(U) \times \mathbb{R}^m, which is a subset of R2m:(P,ξ)(x1,,xm,ξ1,,ξm)\mathbb{R}^{2m}: (P, \xi) \leftrightarrow (x_1, \dots, x_m, \xi_1, \dots, \xi_m)
The transition functions between charts TU1TU_1 and TU2TU_2 are smooth, so TMTM carries a natural structure of a smooth manifold of dimension 2m2m.

If we assume we have a particular tangent vector ξ(P)\xi(P) at each point PMP \in M, then we have a vector field on MM. We can think of components of ξ\xi being functions of the local coordinates of PP.
The vector field is said to be smooth if these functions are smooth.

We see that for every vector field ξ=ξ(P)\xi = \xi(P), we can assign it a system of first-order ODEs, where ddtx(t)=ξ(x)\frac{d}{dt}\mathbf{x}(t) = \xi(\mathbf{x}). In other words, we think of the vector assigned to each point as a derivative of that point, with each component of that vector being an ODE wrt components of the original point.
In other words, vector field as a "flow"
The opposite holds true as well: any system of ODEs of this kind determines a vector field on MM.
Smooth curves satisfying ddtx(t)=ξ(x)\frac{d}{dt}\mathbf{x}(t) = \xi(\mathbf{x}) are called integral curves.
According to the uniqueness and existence theorem for ODE, for each PMP \in M there exists a unique curve γ(t)\gamma(t) s.t. γ(0)=P\gamma(0) = P and t(ϵ,ϵ)t \in (-\epsilon, \epsilon).
If each curve γ(t)\gamma(t) can be defined for t(,)t \in (-\infty, \infty), then the vector field is called "complete."
If ξ\xi is complete, then for any tRt \in \mathbb{R} we can define a diffeomorphism ϕt=ϕξt:MM\phi^t = \phi^t_\xi: M \to M which is just the translation along integral curves by t.
To find the image of PP along ϕt\phi^t we take the integral curve γ(t)\gamma(t) s.t. γ(0)=P\gamma(0) = P and by definition ϕt(P)=γ(t)\phi^t(P) = \gamma(t). A property of this is that ϕsϕt=ϕt+s\phi^s\circ \phi^t = \phi^{t + s}. So, we say that ϕt\phi^t is a one-parameter group of diffeomorphisms.
On the other hand, a one-parameter group of diffeomorphisms ϕt\phi^t on MM defines a vector field by ξ(P)=ddtt=0ϕt(P)\xi(P) = \frac{d}{dt}|_{t=0} \phi^t(P)
Conclusion: vector fields on MM = autonomous ODE on MM = one-parameter groups of diffeomorphisms

Example:
If we have a vector field ξ=(x,y)R2\xi = (x, y) \in \mathbb{R}^2, then our integral curves are γ(t)=(x0et,y0et)\gamma(t) = (x_0 e^t, y_0 e^t)
the diffeomorphisms ϕt\phi^t are homotheties centered at the origin and with dilation factor ete^t #-> homotheties are translations of affine spaces, determined by a scaling point and a scaling factor

Example 2:
If on S3={x2+y2+u2+v2=1}S^3 = \{x^2 + y^2 + u^2 + v^2 = 1\} we consider a vector field ξ(P)=(y,x,v,u)\xi(P) = (-y, x, -v, u), where PS3P \in S^3, then the integral curve passing through P=(x0,y0,u0,v0)P = (x_0, y_0, u_0, v_0) can be described as follows:

(x0costy0sint,y0cost+x0sint,u0costv0sint,v0cost+u0sint) \begin{align*} (x_0 \cos{t} - y_0 \sin{t}, y_0 \cos{t} + x_0 \sin{t}, u_0 \cos{t} - v_0 \sin{t}, v_0 \cos{t} + u_0 \sin{t}) \end{align*}

This is a circle of radius 1 centered at the origin and lying in the 2-dim plane spanned by the vectors P=(x,y,u,v)P = (x, y, u, v) and γ(P)=(y,x,v,u)\gamma(P) = (-y, x, -v, u).
The corresponding ϕt\phi^t can be understood as the composition of two rotations by angle tt in the planes OxyO_{xy} and OuvO_{uv}.
This is an example of a left invariant vector field on SU(2)SU(2).

Definition: Lie Bracket

The Lie bracket of vector fields is a bilinear differential operator which assigns to any vector fields ξ\xi and η\eta on a smooth manifold MM, a new vector field denoted by [ξ,η][\xi, \eta].
In local coordinates, the components of [ξ,η][\xi, \eta] are defined by [ξ,η]k=ξi(ddxiηk)ηi(ddxiξk)[\xi, \eta]^k = \xi^i (\frac{d}{d x^i} \eta^k) - \eta^i (\frac{d}{d x^i} \xi^k)
where we sum along the ii index
If we think of vector fields as derivations then [ξ,η][\xi, \eta] is defined by [ξ,η](f)=ξ(η(f))η(ξ(f))[\xi, \eta](f) = \xi(\eta(f)) - \eta(\xi(f)) #-> What exactly is a derivation? Derivative as an abstract operation? Note to reader: At this point I didn't understand derivations
Properties:
- Bilinearity over R\mathbb{R}: [aξ1+bξ2,η]=a[ξ1,η]+b[ξ2,η][a\xi_1 + b\xi_2, \eta] = a[\xi_1, \eta] + b[\xi_2, \eta]
- Skew-symmetry: [ξ,η]=[η,ξ][\xi, \eta] = -[\eta, \xi]
- Leibnitz rule: [ξ,f(η)]=f[ξ,η]+ξ(f)η[\xi, f(\eta)] = f[\xi, \eta] + \xi(f)\eta for any ff smooth over MM #-> Can't conceptualize what this means without fully understanding
- Jacobi identity: [ζ,[ξ,η]]+[ξ,[η,ζ]]+[η,[ζ,ξ]]=0[\zeta, [\xi, \eta]] + [\xi, [\eta, \zeta]] + [\eta, [\zeta, \xi]] = 0
- if ξ1,,ξk\xi_1, \dots, \xi_k are pairwise commuting, linearly independent vector fields, there is locally a coordinate system (x1,,xm)(x_1, \dots, x_m) s.t. ξ1=x1,,ξk=xk\xi_1 = \frac{\partial}{\partial x_1}, \dots, \xi_k = \frac{\partial}{\partial x_k}
- If NN is a submanifold of MM and ξ\xi and η\eta are tangent to NN, then so is [ξ,η][\xi, \eta]
- If ξ\xi and η\eta commute (i.e. [ξ,η]=0[\xi, \eta] = 0), then the corresponding flows also commute

Definition: Differential

Let F:MNF: M \to N be a smooth map, PMP \in M and Q=F(P)Q = F(P).
Then, the differential dFdF (at point PP) is a linear map between tangent spaces TPMT_PM and TQNT_QN. The following are each definitions of dFdF:
- Take ξ\xi in TP(M)T_P(M) and choose any curve γ(t)\gamma(t) through PP such that γ(0)=ξ\gamma'(0) = \xi. Then, η=dF(ξ)\eta = dF(\xi) is the tangent vector to the image of γ\gamma at the point QQ:
η=dF(ξ)=ddtt=0F(γ(t))TQ(N)\eta = dF(\xi) = \frac{d}{dt}|_{t=0} F(\gamma(t)) \in T_Q(N) #-> In other words, we take some tangent vector, find its antiderivative, take its image, and then take its derivative
- Consider ξTP(M)\xi \in T_P(M) as a derivation. Then, η=dF(ξ)\eta = dF(\xi) is the derivation at QQ which acts on an arbitrary function g:NRg: N \to \mathbb{R} s.t. η(g)=ξ(gF)\eta(g) = \xi(g\circ F)
- Choosing local coordinates (x1,,xm)(x_1, \dots, x_m) and (y1,,yn)(y_1, \dots, y_n) in neighborhoods of PP and QQ, letting ξ=(ξ1,,ξm)\xi = (\xi_1, \dots, \xi_m) then the components of η=dF(ξ)\eta = dF(\xi) are as follows:
ηj=i=1mxifjξi\eta_j = \sum_{i=1}^m \frac{\partial}{\partial x_i} f_j \xi_i for j=1,,nj = 1, \dots, n #-> in other words, the sum of partials of f wrt each coordinate times corresponding ξ\xi
In matrix form, η=dF(ξ)=Jξ\eta = dF(\xi) = \mathbf{J} \xi, where J\mathbf{J} is the Jacobi matrix of FF at point PP

Definition: Immersion

A smooth map F:MNF: M \to N is called an immersion if its differential is a monomorphism (i.e. one-to-one) for any PMP \in M

Definition: Submersion

A smooth map F:MNF: M \to N is called a submersion if its differential is an epimorphism (i.e. onto) for any PMP \in M

Definition: Embedding

A smooth map FF is called an embedding if FF is an immersion and MM is homeomorphic with F(M)F(M)

Definition: Covering

If we assume dFdF to be an isomorphism for each point, then we have a local diffeomorphism between some neighborhoods of PP and F(P)F(P). If we assume that for each point QQ there is a neighborhood V(Q)V(Q) such that F1(V)F^{-1}(V) is a disjoint union of some neighborhoods U1,U2,U1, U2, \dots of MM s.t. FUi:UiVF|_{U_i}: U_i \to V is a diffeomorphism, then FF is called a covering. #-> how to interpret...

Examples:
- Smooth regular curve γ:RR2\gamma: \mathbb{R} \to \mathbb{R}^2 with self-intersections represents an immersion
- Letting M=T2M = T^2 a two-dimensional torus with standard angle coords ϕ1,ϕ2\phi_1, \phi_2, then the map RT2\mathbb{R} \to T^2 by F(t)=(at,bt)F(t) = (at, bt) where (a,b)(0,0)(a, b) \neq (0, 0) is an immersion. If abQ\frac{a}{b} \in \mathbb{Q}, then image of R\mathbb{R} is a closed curve on T2T^2; if abQ\frac{a}{b} \notin \mathbb{Q}, we have the so-called irrational winding on T2T^2. #-> This is intuitive, because if abQ\frac{a}{b} \in \mathbb{Q} then (a,b)(a, b) is proportional to (c,d)Z2(c, d) \in \mathbb{Z}^2 so F(4π)=F(0)F(4\pi) = F(0)
- Consider F:O(3)S2F: O(3) \to S^2 which assigns to each AO(3)A \in O(3) its first row (a11,a12,a13)S2(a_{11}, a_{12}, a_{13}) \in S^2. Exercise: FF is a submersion. #-> the Jacobian of FF looks like just the first row?
- If F:G1G2F: G_1 \to G_2 is a smooth homomorphism of Lie groups then FF is either immersion or submersion. If F:G1G2F: G_1 \to G_2 is such that dF:Te1G1Te2G2dF: T_{e_1}G_1 \to T_{e_2}G_2 is a linear isomorphism, then FF is a covering.
- The orthogonal projection p:S2R2=Oxyp: S^2 \to \mathbb{R}^2 = O_{xy} is neither an immersion nor submersion #-> Why? at the very least, the surjectivity seems like it would work. Maybe the intersection portion breaks?
- F:RS1F: \mathbb{R} \to S^1 defined by F(x)=eixF(x) = e^{ix} is a covering (and, consequently, both submersion and immersion) #-> dF=ieixdF = ie^{ix}? I guess I don't get the way the differentials on tangent spaces work
- The map f:(2π,2π)S1f: (-2\pi, 2\pi) \to S^1 defined by f(x)=eixf(x) = e^{ix} is not a covering (but still submersion and immersion) #-> I'm guessing that around f(0)f(0), the neighborhood will include (2π,a)(-2\pi, a) for some aa that will screw things up? Maybe not diffeomorphism?

Definition: Submanifold

A subset NMN \subseteq M is called a submanifold if NN is a smooth manifold and the inclusion p:NMp: N \hookrightarrow M is an embedding. #-> As long as the inclusion is homeomorphic, NN is a submanifold (as the inclusion is injective by definition)
Equivalent definition: NMN \subseteq M is a submanifold if locally NN can be given by a system of equations f1(x1,,xm)=0,,fmk(x1,,xm)=0f_1(x_1, \dots, x_m) = 0, \dots, f_{m - k}(x_1, \dots, x_m) = 0 satisfying the regularity condition (i.e. the rank of the Jacobi matrix = mkm - k)
If we let ourselves use any regular coordinate changes, we can always choose local coordinates in MM that NN will (locally) be given by zk+1=0,zk+2=0,,zm=0z_{k+1} = 0, z_{k+2} = 0, \dots, z_{m} = 0.

Theorem: Embedding of Manifolds

Theorem: Any connected smooth mm-dimensional manifold MmM^{m} can be smoothly embedded into the Euclidian 2m2m-space R2m\mathbb{R}^{2m}.