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Covariant Derivative of Vector Fields 📂Geometry

Covariant Derivative of Vector Fields

Theorem1

Let MM be a differentiable manifold, and let \nabla be an affine connection on MM. Then, there exists a unique function Ddt:VDVdt\dfrac{D}{dt} : V \mapsto \dfrac{DV}{dt} that maps a vector field VV following a differentiable curve c:IM(tI)c : I \to M(t\in I) to another vector field DVdt\dfrac{D V}{dt} following cc. Such a mapping is referred to as the covariant derivative of VV along cc, and it has the following properties. When WW is a vector field following cc, and ff is a differentiable function defined on II,

(a) Ddt(V+W)=DVdt+DWdt\dfrac{D}{dt}(V+W) = \dfrac{DV}{dt} + \dfrac{DW}{dt}

(b) Ddt(fV)=dfdtV+fDVdt\dfrac{D}{dt}(fV) = \dfrac{df}{dt}V + f \dfrac{DV}{dt}

(c) If VV is a contraction map of YX(M)Y \in \mathfrak{X}(M), that is, if V(t)=Y(c(t))V(t) = Y(c(t)), then DVdt=dc/dtY\dfrac{DV}{dt} = \nabla_{dc/dt}Y

DVdt\dfrac{D V}{d t} is explicitly given as follows.

DVdt=j(dvjdt+j,kvjdckdtXk)Xj \dfrac{DV}{dt} = \sum_{j} \left( \dfrac{d v^{j}}{dt} + \sum_{j,k} v^{j}\frac{dc_{k}}{dt} \nabla_{ X_{k}} \right) X_{j}

where V=vjXjV = v^{j}X_{j}, Xj=xjX_{j} = \dfrac{\partial }{\partial x_{j}}.

Explanation

From (a) and (b), there is no reason not to denote such a vector field corresponding to VV as DVdt\dfrac{D V}{dt}, because it has the properties that differentiation should have.

Proof

  • Part 1. Uniqueness

    Assume that there exists a mapping VDVdtV \mapsto \dfrac{DV}{dt} that satisfies (a)~(c). Let x:UM\mathbf{x} : U \to M be the coordinates overlapping with curve cc.

    c(I)x(U) c(I) \cap \mathbf{x}(U) \ne \varnothing

    Let’s denote c(t)=x(c1(t),,cn(t))c(t) = \mathbf{x}(c_{1}(t), \dots, c_{n}(t)). Consider VV as a vector field.

    V=vjxj=vjXj V = v^{j}\dfrac{\partial }{\partial x_{j}} = v^{j}X_{j}

    Here, Xj=xj=xjc(t)X_{j} = \dfrac{\partial }{\partial x_{j}} = \left.\dfrac{\partial }{\partial x_{j}}\right|_{c(t)}, vj=vj(t)v^{j} = v^{j}(t). Then, by properties (a) and (b), the following holds.

    DVdt= Ddt(jvjXj)= jDdt(vjXj)by (a)= j(dvjdtXj+vjDXjdt)by (b) \begin{align*} \dfrac{DV}{dt} =&\ \dfrac{D}{dt}\left( \sum_{j} v^{j}X_{j} \right) \\ =&\ \sum_{j} \dfrac{D}{dt}\left( v^{j}X_{j} \right) & \text{by (a)} \\ =&\ \sum_{j} \left( \dfrac{d v^{j}}{dt}X_{j} + v^{j}\dfrac{D X_{j}}{dt} \right) & \text{by (b)} \\ \end{align*}

    Based on property (c) and property 1 of the affine connection, the following is true.

    DXjdt= dc/dtXjby (c)= kdckdtXkXj= kdckdtXkXjby 1. \begin{align*} \dfrac{D X_{j}}{dt} =&\ \nabla_{dc/dt} X_{j} &\text{by (c)} \\ =&\ \nabla_{\sum_{k} \frac{dc_{k}}{dt} X_{k}} X_{j} \\ =&\ \sum_{k} \frac{dc_{k}}{dt} \nabla_{ X_{k}} X_{j} & \text{by 1.} \\ \end{align*}

    By substituting this into the original equation, the following is obtained.

    DVdt= j(dvjdtXj+vjkdckdtXkXj)= jdvjdtXj+j,kvjdckdtXkXj \begin{align*} \dfrac{DV}{dt} =&\ \sum_{j} \left( \dfrac{d v^{j}}{dt}X_{j} + v^{j}\sum_{k} \frac{dc_{k}}{dt} \nabla_{ X_{k}} X_{j} \right) \\ =&\ \sum_{j} \dfrac{d v^{j}}{dt}X_{j} + \sum_{j,k} v^{j}\frac{dc_{k}}{dt} \nabla_{ X_{k}} X_{j} & \cdots \circledast \end{align*}

    Auxiliary theorem

    (XY)(p)(\nabla_{X}Y)(p) depends solely on X(p)X(p) and Y(γ(t))Y(\gamma (t)).

    According to the auxiliary theorem, xkxj\nabla_{ \frac{\partial }{\partial x_{k}}} \dfrac{\partial }{\partial x_{j}} is determined by the coordinates. The rest is uniquely determined by the coordinates as well. Therefore, if it exists, it is unique.

  • Part 2. Existence

    Define DVdt\dfrac{DV}{dt} as follows; then it satisfies properties (a)~(c).


  1. Manfredo P. Do Carmo, Riemannian Geometry (Eng Edition, 1992), p50-52 ↩︎