Differential Geometry

Table of Contents

1. Differentiable Curve

1.1. Abstract Definition

  • A \(C^k\)-curve is a subset \(C\) of a differentialble manifold \(X\) where every point of \(C\) has a neighborhood such that \(C\cap U\) is \(C^k\)-diffeomorphic to an interval of the real numbers.
  • In other words, differentiable manifold of dimension one.

1.2. Constructive Definition

1.2.1. Parametric Curve

  • Parametrization
  • A vector-valued continuous function \(\gamma\colon I\to \mathbb{R}^n\) form an interval \(I\) to a Euclidean space.
1.2.1.1. Parametric Cᵏ-Curve
  • \(C^k\)-Parametrization
  • The component functions of the parametrization \(\gamma\) are \(r\)-times continuously differentiable.
1.2.1.2. Analytic Curve
1.2.1.3. Regular of Order m
  • For every \(t\in I\), \[ \{\gamma'(t), \gamma''(t),\dots,\gamma^{(m)}(t)\} \] is a linearly independent subset of \(\mathbb{R}^n\).
  • In particular, a parametric \(C^1\)-curve \(\gamma\) is regular if and only if \(\gamma'(t) \neq 0\) for any \(t\in I\).
    • This is usually what is meant when a curve is said to be regular.

1.2.2. Equivalence Relation

  • Two parametric \(C^k\)-curves \(\gamma_1\colon I_1 \to \mathbb{R}^n, \gamma_2\colon I_2 \to \mathbb{R}^n\) are said to be equivalent if there exists a bijective \(C^r\)-map \(\varphi\colon I_1 \to I_2\) such that \[ \forall t\in I_1, \varphi'(t) \neq 0, \gamma_2\circ \varphi = \gamma_2 \]
  • \(\gamma_2\) is said to be a re-parametrization of \(\gamma_1\).
  • Notice that the same subset of \(\mathbb{R}^n\) can be parameterized in multiple non-equivalent ways, with varying self-crossing and differentiablity.

1.2.3. Cᵏ-Curve

  • The equivalence classes are called \(C^k\)-curves.
  • The equivalence class may be alternatively called the \(C^k\)-arc, and the parametrization is called the \(C^k\)-curve.

1.2.4. Oriented Cᵏ-Curve

  • The equivalence classes under the equivalence relation with additional requirement \(\varphi(t) >0\).

1.3. Destructive Definitions

1.3.1. Differentiable Curve

  • A curve \(C\) is differentiable if there exists a differentiable parametrization \(\gamma\).

1.3.2. Cᵏ-Curve

  • A curve \(C\) is \(C^{k}\) if there exists a \(C^k\)-parametrization \(\gamma\).

1.3.3. Regular Curve

  • A curve \(C\) is regular if there exists a \(C^1\)-parametrization \(\gamma\) with \(\forall t,\gamma'(t) \neq 0\).
  • \(C^1\)-curve may have cusps, for the case of the pathological equivalence class that is other than the usual one although describing the same curve. The equivalence class that is regular will not have such pathological cases.
  • It would coincide with the constructive definition of regular curve? at least for the regular of order 1?
  • Theorem
    • Regular curves does not have cusps
    • For a regular curve \(\gamma\colon I_1\to \mathbb{R}^2\),
    • At every point \(t_0\in I_1\), there is a reparametrization \(\alpha\colon I_2\to \mathbb{R}^2\) and a Cartesian coordinate system \(\bar{x}, \bar{y}\colon \mathbb{R}^2\to \mathbb{R}\) in which \(\alpha(t)\) is identical to \((t,f(t))\) for a locally \(C^1\)-function \(f\)

1.3.4. Cᵏ Regular Curve

  • A curve \(C\) is smooth regular if there exists a parametrization that is both \(C^r\) and regular.
1.3.4.1. Non-Example
  • Example of a curve that is both smooth and regular, but not smooth regular.
  • Line * Arc of a Circle * Line

1.3.5. Closed Curve

  • A curve \(C\) is closed if the infinite concatenation of any parametrizations with itself is periodic.
1.3.5.1. Closed Regular
  • The periodic parametrization is regular.
1.3.5.2. Closed Cᵏ
  • The periodic parametrization is \(C^k\).

1.3.6. Simple Curve

  • A curve that does not intersect itself.
  • A curve \(C\) is simple if there exists an injective parametrization.

1.3.7. Simple Closed Curve

  • A curve \(C\) is simple closed if there exists an injective parametrization except at one point, and its periodic when infinitely concatenated.
  • Theorem (Jordan Curve)
    • Any Jordan (simple closed) curve separates \(\mathbb{R}^2\) in two connected components, one of them bounded and the other unbounded.

1.4. Concatenation

  • Concatenation, denoted \(\gamma_1\ast \gamma_2\), of two parametric curve \(\gamma_1\colon I_1\to \mathbb{R}^n, \gamma_2\colon I_2\to \mathbb{R}^n\) with the coinciding terminal and initial endpoint is given by a parametric curve \(\gamma_3\colon I_3 \to \mathbb{R}^n\) with the \(C^k\)-maps \(\varphi_1\colon I_1\to I_3, \varphi_2\colon I_2\to I_3\) such that
    • the images of two maps are partition of \(I_3\)
    • \(\gamma_3\circ \varphi_1 = \gamma_1\) and \(\gamma_3\circ \varphi_2 = \gamma_2\)
  • The concatenated curve is said to be piecewise regular (or \(C^r\), smooth) if each curves that are being concatenated are regular (or \(C^r\), smooth).

1.5. Rectifiable Curve

Informally, a curve that has finite number of segments in its "sufficiently good" rectification, or a curve that can be stretched out in a line.

1.5.1. Properties

  • Finite length.

1.5.2. Rectification

  • Approximation of a given curve by finite number of connected line segments.
  • The arclength may not be obtained by the rectification itself, but the supremum can give the arclenth in the case of the rectifiable curves.

1.5.3. Koch Snowflake

  • Koch Curve, Koch Star, Koch Island

Example of a non-rectifiable curve.

  • Bounded curve with infinite length.
  • Continuous curve where tangent line at any point is indetermined.
  • Koch snowflake - Wikipedia

1.6. Length

1.6.1. Definition

  • \[ \operatorname{length}(\gamma) := \sup_P\left\{\sum_{j=1}^k|\gamma(t_j) - \gamma(t_{j-1})|\right\} \]
  • where \(P\) is the partition on the domain \([a,b]\) of the parametrization \(\gamma\).
  • The reparametrization induces natural isomorphism in terms of the length between partitions of two intervals, therefore the length is invariant under reparametrization. (Property 2)

1.6.2. Properties

  • \(\operatorname{length}(\gamma) \ge |\gamma(b) - \gamma(a)|\), with equality when \(\gamma\) is a straight line.
  • For two equivalent parametrization \(\gamma_1,\gamma_2\), \(\operatorname{length}(\gamma_1) = \operatorname{length}(\gamma_2)\)
  • \(\operatorname{length}(\gamma_1\ast \gamma_2) = \operatorname{length}(\gamma_1) + \operatorname{length}(\gamma_2)\) where \(\ast\) denotes the concatenation.
  • The length is invariant under isometry.
  • Given a sequence of curves \((\gamma_n)_{n=1}^\infty\) that converges pointwise to \(\gamma\), \[ \operatorname{length}(\gamma) \le \operatorname*{lim\,inf}_{n\to \infty}\operatorname{length}(\gamma_n) \]
  • \(\operatorname{length}\) is the only function satisfying that satisfying the above five properties.
    • If a function \(\lambda\colon \mathbf{Curve} \to \mathbb{R}\cup \{\infty\}\) satisfies the above five properties, then \(\lambda = \operatorname{length}\).
  • If a curve can be parameterized by a Lipschitz continuous function \(\gamma\colon [a,b] \to X\), then it is rectifiable, and the speed of \(\gamma\) at \(t\in [a,b]\) can be defined as a metric derivative: \[ \operatorname{speed}_\gamma(t) := \operatorname*{lim\,sup}_{s\to t}\frac{d(\gamma(s),\gamma(t))}{|s-t|} \] which then satisfies: \[ \operatorname{length}(\gamma) = \int_a^b\operatorname{speed}_\gamma(t)\,dt. \]

1.7. Crofton Formula

Cauchy-Crofton Formula

1.7.1. Statement

  • Given a rectifiable plane curve \(\gamma\),
  • \(n_\gamma(\ell)\colon \mathbf{2\text{-}OrientedLines}\to \mathbb{Z}\) which defined as
    • the number of intersections between a line \(\ell \in \mathbf{2\text{-}OrientedLines}\) and the curve \(\gamma\),
    • and can be parametrized by the signed distance from the origin \(p\) and the direction \(\varphi\) in which it points
  • satisfies: \[ \operatorname{length}(\gamma) = \frac{1}{4}\iint n_\gamma(\varphi, p)\,d\varphi\,dp. \]
    • The right hand side is usually called the Favard length.
  • Equivalently, using the projection \(\pi_\theta\) onto the line through the origin with angle \(\theta\): \[ \operatorname{length}(\gamma) = \frac{1}{4}\int_0^{2\pi}\operatorname{length}(\pi_\theta\circ\gamma)\,d\theta. \]

1.7.2. Properties

  • The differential form \(d\varphi\wedge dp\), which is called the kinematic measure, is invariant under rigid motions, and therefore the integral itself, constituting a natural integration measure for an "average" number of intersections,

1.7.3. Generalization

  • In \(\mathbb{R}^n\), the integration over the space of oriented lines is: \[ \operatorname{area}(S) = \frac{1}{2|B_1^{n-1}|}\iint n_S(\varphi, p)\,d\varphi\,dp \]
  • where \(S\) is the surface of codimension 1, and \(|B_1^{n-1}|\) is the \((n-1)\)-volume of the unit ball in \(\mathbb{R}^{n-1}\), and \(d\varphi\wedge, dp\) is the appropriate kinematic measure.
  • The space of oriented lines in \(\mathbb{R}^n\) is the tangent bundle of \(S^{n-1}\).

1.8. Arclength Parametrization

  • Natural Parametrization

1.8.1. Arclength

  • Given a parametric curve \(\gamma\colon [a,b]\to \mathbb{R}^n\), the arclength function \(s\colon [a,b] \to [0,\infty]\) is defined to be:
  • \[ s(t) := \operatorname{length}\left(\gamma\big|_{[a,t]}\right). \]
  • It admits the inverse function \(s^{-1}\colon [0, \operatorname{length}(\gamma)] \to [a,b]\), since it is an monotone injection.
  • For a parametric \(C^1\)-curve \(\gamma\colon [a,b]\to \mathbb{R}^n\), the arclength can equivalently be obtained by \[ s(t) = \int_a^t |\gamma'(t)|\,dt. \]
    • Notice that this formula is invariant under reparametrization, since \[ \gamma'(t)\,dt = \tilde{\gamma}'(\tilde{t})\,d\tilde{t} = \tilde{\gamma}'(\varphi(t))\varphi'(t)\,dt \] and the arclength is taken to be positive. If the curve was oriented it might introduces a sign change.

1.8.2. Definition

  • A parametrization \(\gamma\colon I\to X\) such that for any \(t_1, t_2 \in I\) with \(t_1 \le t_2\), \[ \operatorname{length}\left(\gamma\big|_{[t_1,t_2]}\right) = t_2 - t_1. \]
  • Equivalently, the reparametrization of a parametrization \(\gamma\) by the arclength: \[ \gamma\circ s^{-1}(t). \]

1.8.3. Properties

  • \(C^1\)-parametrization \(\gamma\) is the arclength parametrization if and only if \(\forall t\in [a,b], |\gamma'(t)| = 1\).
  • The arclength parametrization of a smooth regular curve is smooth and regular.

1.9. Frenet-Serret Formulas

  • Formulas regarding tangent, normal, binormal unit vectors.
  • \begin{align*} \frac{d\mathbf{T}}{ds} &= \kappa \mathbf{N}\\ \frac{d\mathbf{N}}{ds} &= -\kappa \mathbf{T} + \tau \mathbf{B}\\ \frac{d\mathbf{B}}{ds} &= -\tau \mathbf{N}\\ \end{align*}
  • where \(s\) is the arclength parameter.
  • The reference frame using these unit vectors is called the Frenet-Serret frame.

1.9.1. Frenet-Serret Frame

  • Frenet Frame, TNB Frame
  • It is a reference frame that moves along a curve.
1.9.1.1. Definition
  • Vector space with basis \( \{T,N,B\} \).

1.10. Shape

1.10.1. Tangent Vector

  • Given a locally regular \(C^1\)-curve \(\gamma\),
  • \[ \mathbf{T}(t) := \frac{\gamma'(t)}{|\gamma'(t)|} = \tilde{\gamma}'(s) \]

1.10.2. Curvature

1.10.2.1. Absolute Curvature
  • Given a locally 2-regular \(C^2\)-curve \(\gamma\)
  • \[ \kappa(t) := \frac{|\mathbf{T}'(t)|}{|\gamma'(t)|} = |\tilde{\gamma}''(s)| \]
    • For the curves in three dimensional space, \[ \kappa(t) = \frac{|\gamma''(t)\times \gamma'(t)|}{|\gamma'(t)|^3}. \]
1.10.2.2. Signed Curvature
  • For a smooth regular natural parametrization \(\alpha\colon I\to \mathbb{R}^2\), the angle \(\theta\colon I\to \mathbb{R}\) to the positive \(x\)-axis can always be determined form the tangent vector.
  • The signed curvature is then, \[ k(s) := \theta'(s). \]
    • For a smooth regular curve \(\gamma\colon I\to \mathbb{R}^2\) with component functions \(x(t), y(t)\), \[ k(t) = \frac{x'y'' - y'x''}{((x')^2 + (y')^2)^{3/2}} \]
1.10.2.3. Total Curvature
  • For smooth regular curve \(\gamma\), the total curvature is \[ \Phi(\gamma) := \int_a^b\kappa(t)|\gamma'(t)|\,dt \]
  • Even if \(\gamma\) is only piecewise smooth regular, for a partition \(P\), \[ \Phi(\gamma) := \sum_{P} \int_{t_{i-1}}^{t_i} \kappa(t)|\gamma'|\,dt + \sum_{i=1}^{n-1}\angle(\gamma'(t_i^+), \gamma'(t_i^-)). \]
  • \[ \Phi(\gamma) = \operatorname{length}(\mathbf{T}) \]
1.10.2.4. Total Signed Curvature
  • For a smooth regular curve \(\gamma\colon [a,b]\to \mathbb{R}^2\), \[ \Psi(\gamma) := \int_a^b k(t)|\gamma'(t)|\,dt \]

1.10.3. Normal Vector

  • \[ \mathbf{N}(s) := \frac{\tilde{\gamma}''(s)}{\kappa(s)} \]

1.10.4. Binormal Vector

  • \[ \mathbf{B} := \mathbf{T}\times \mathbf{N} \]

1.10.5. Torsion

  • \[ -\tau\mathbf{N} := \mathbf{B}'(s) \]

1.11. Spherical Curve

1.11.1. Hemisphere Lemma

  • If a spherical curve \(\gamma\colon : I\to \mathbb{S}^2\) is closed and has length less than \(2\pi\), then it is strictly contained in a hemisphere.
  • Corollary
    • There is \(v\in \mathbb{S}^2\) with \(\forall t, \langle v,\gamma(t)\rangle >0\)

1.11.2. Fenchel's Theorem

  • If \(\gamma\colon I\to \mathbb{R}^3\) is closed and piecewise smooth regular, then \(\Phi(\gamma) \ge 2\pi\).
1.11.2.1. Chord Lemma
  • If \(\gamma\colon [a,b]\to \mathbb{R}^3\) is piecewise smooth regular, then: \[ \Phi(\gamma) \ge \angle(\gamma(b) - \gamma(a), \gamma'(a)) + \angle(\gamma(b) - \gamma(a), \gamma'(a)) \]
1.11.2.2. Discrete Chord Lemma
  • If \(a,b,c,d,x\in \mathbb{R}^3\) are distinct, then the piecewise linear curve satisfies: \[ \Phi(abcd) \le \Phi(abxcd). \]

1.11.3. Theorem

  • For a piecewise smooth regular curve \(\gamma\colon I\to \mathbb{R}^3\), \[ \Phi(\gamma) = \sup_{p_i\ \text{rectification}}\{\Phi(p_0,\dots,p_n)\} \]

1.11.4. Theorem

  • If \(\gamma\colon I\to \mathbb{R}^3\) is closed and \(\forall t, |\gamma(t)|\le 1\), then \[ \Phi(\gamma)\ge \operatorname{length}(\gamma). \]

1.11.5. Theorem

  • Crofton formula for spherical curves.
  • If \(\gamma\colon I\to \mathbb{S}^2\) is piecewise smooth regular, then \[ \operatorname{length}(\gamma) = \frac{1}{4\pi}\int_{\mathbb{S}^2}\operatorname{length}(\gamma_v^*)\,dv \]
    • where \(\gamma_v^*\) is the projection of \(\gamma\) onto the unit circle perpendicular to \(v\).

1.11.6. Turning Tangents Theorem

  • If \(\gamma\colon I\to \mathbb{R}^2\) is piecewise smooth regular and closed, \[ \Psi(\gamma) = 2\pi m, m\in \mathbb{Z} \]
    • where \(m\) being the winding numbers.
    • In particular, for the case of simple closed curve, it is either \(\pm 2\pi\).
  • If \(\gamma\) is smooth, \[ \Psi(\gamma) = \theta(b) - \theta(a). \]

1.12. Tangent Curve

  • Two curve \(\gamma_1\colon I_1\to \mathbb{R}^2, \gamma_2\colon I_2\to \mathbb{R}^2\) is said to be tangent at point \(p_0\), if
    • \[ \exists t_1\in I_1, \exists t_2\in I_2, p_0 = \gamma_1(t_1) =\gamma_2(t_2) \]
    • and \[ \gamma_1'(t_1)\parallel \gamma_2'(t_2) \]

1.12.1. Co- and Counter-Oriented

  • Tangent curves \(\gamma_1\) and \(\gamma_2\) are co-oriented if \(\gamma_1'\cdot \gamma_2' > 0\).
  • Likewise, they are counter-oriented if \(\gamma_1' \cdot \gamma_2' < 0\).

1.12.2. Supporting Curve

  • For two tangent curves \(\gamma_1, \gamma_2\) at \(p_0\),
  • \(\gamma_1\) locally supports \(\gamma_2\) at \(p_0\) if \[ \exists \varepsilon >0, \exists R\subset \mathbb{R}^2, \gamma_1[(t_1-\varepsilon, t_1+\varepsilon)] \subset \partial R\land \gamma_2[(t_2-\varepsilon, t_2+\varepsilon)] \subset R \]
  • If the curves are co-oriented and \(\gamma_1\) goes counter-clockwise (or clockwise) around \(R\), then it is said that \(\gamma_1\) locally supports \(\gamma_2\) from the right (or from the left).
    • In some local coordinate system \(f_1(x) \le f_2(x)\).
    • If \(k_1(t_1) < k_2(t_2)\), then \(\gamma_1\) supports \(\gamma_2\) form the right.
  • \(\gamma_1\) globally supports \(\gamma_2\) from the outside, if \(\gamma_2\) lies entirely within the interior of \(\gamma_1\).

1.12.3. Osculating Circle

  • Co-oriented tangent circle, with the same curvature.

1.12.4. Moon In a Puddle Theorem

  • For a simple smooth regular closed curve,
  • If \(\forall t, \kappa(t) \le 1\), then \(\gamma\) contains a unit disk in its interior.

1.12.5. Vertex

  • For a smooth regular curve \(\gamma\colon [a,b]\to \mathbb{R}^2\),
  • the point \(\gamma(t_0)\) is called a vertex if \(k'(t_0)=0\)

1.12.6. Four-Vertex Theorem

  • A closed smooth regular curve \(\gamma\colon \mathbb{S}^1\to \mathbb{R}^2\) has at least four vertices.

1.13. Contact

  • Osculation

1.13.1. Definition

  • Two curves in the plane intersecting at a point \(p\) are said to have:
    • 0th-order contact if the curves have a simple crossing (not tangent).
    • 1st-order contact if the two curves are tangent.
    • 2nd-order contact if the curvatures of the curves are equal. Such curves are said to be osculating.
    • 3rd-order contact if the derivatives of the curvature are equal.
    • 4th-order contact if the second derivatives of the curvature are equal.

1.13.2. Osculating Curve

  • Osculate, "to touch", from Latin osculum, "kiss"
  • Plane curve from a given family that has the highest possible order of contact with another curve.
1.13.2.1. Examples
  • Tangent Line: Order 1
  • Osculating Circle: Order 2
  • Osculating Conic

1.13.3. Jet

  • The equivalence class with respect to the equivalence relation of the same contact.

1.14. Fundamental Theorem of Space Curves

  • Two scalar function, namely, curvature \( \kappa \) and torsion \( \tau \), uniquely defines a curve up to isometry.

1.15. Cusp

  • Spinode
  • The sharp point

1.15.1. Definition

  • It is a point on a curve where a moving point must reverse direction.

1.15.2. Classification

  • A function \(f\) is said to be of type \(A_k^\pm\) if it lies in the orbit of \(x^2\pm y^{k+1}\), i.e. there exists a diffeomorphic change of coordinate in source and target which takes \(f\) into one of these form.
  • Equivalence class \(A_k^\pm\) of the normal form \(x^2\pm y^{k+1}\).

1.15.3. Ordinary Cusp

  • Type \(A_2\)-singularity, given by \(x^2 - y^3 = 0\).

1.15.4. Rhamphoid Cusp

  • From Greek, 'beak-like'

2. Differentiable Surface

2.1. Definition

  • Differentiable manifold of dimension two.
  • Roughly: Smooth surface is a connected subset of the space that is locally a graph of a smooth function.
  • A \(C^k\)-surface is a subset \(\Sigma\) of a differentiable manifold \(X\) where every point of \(\Sigma\) has a neighborhood such that \(\Sigma\cap U\) is \(C^k\)-diffeomorphic to an open subset of \(\mathbb{R}^2\).

2.1.1. Naïve Definition

In particular, if the manifold is a Euclidean space \(\mathbb{R}^n\), then the existence of \(C^k\)-diffeomorphism can be reduced to the existence of coordinate systems at each point for which a neighborhood is a graph of a \(C^k\)-function.

2.1.1.1. Theorem
  • If \(f\colon \mathbb{R}^3 \to \mathbb{R}\) is smooth and \(c\in\mathbb{R}\) satisfies \(\forall p\in f^{-1}[c], \nabla f(p)\neq 0\),
  • then each connected component of \(f^{-1}[c]\) is a smooth surface.
  • Reformulation of inverse function theorem in three variables.

2.1.2. Extension

  • The neighborhood can instead be described by the smooth regular \(\varphi\colon U\to \mathbb{R}^n\), called ((66806d22-8f92-488f-a5d9-fc26c16fcb09)), from a open connected subset \(U\subset\mathbb{R}^2\).
2.1.2.1. Theorem
  • If \(\varphi\colon U\subset \mathbb{R}^2\to \mathbb{R}^3\) is a smooth regular embedding, then \(\varphi[U]\) is a surface.
  • Since: by , there is homeomorphism with smooth inverse from the coordinate space to \(U\).

2.1.3. Regular Map

  • For an open subset \(U\subset \mathbb{R}^{m}\) and a smooth map \(\varphi\colon U\to \mathbb{R}^n\) with \(n\ge m\),
  • \(\varphi\) is said to be regular if \[ \left\{\frac{\partial \varphi}{\partial x_i}\right\}_{i=1}^m \]
  • is a linearly indepnedent set of vectors?

2.2. Differentiation

  • See

2.3. Integration

  • For a continuous function \(f\colon \Sigma \to \mathbb{R}\), the integral of \(f\) over a region \(R\subset \Sigma\) is given by: \[ \int_R f\,du\wedge dv := \int_{\phi^{-1}(R)} (f\circ\phi)\bigg|\frac{\partial \phi}{\partial u}\times \frac{\partial \phi}{\partial v}\bigg|\,du\,dv \]
    • where \(\phi\colon U \to \Sigma\) is a chart that covers \(R\).
    • Notated with 2-form

2.4. Curvature

2.4.1. Gauss Map

  • A smooth surface \(\Sigma\) is orientable if there exists a continuous map \(N\colon\Sigma \to \mathbb{S}^2\), called orientation or Gauss map, such that \(\forall p\in \Sigma, N(p)\perp T_p\Sigma\).

2.4.2. Shape Operator

  • Shape operator \(S_p\colon T_p\Sigma \to T_{p}\Sigma\) is (inclusion of) the negative of the ((66806d1e-2876-45c0-978c-8c4c00f8eb84)) \(d_pN\colon T_p\Sigma \to T_{N(p)}\mathbb{S}^2\) of the Gauss map \(N\): \[ S_p(X) = -d_pN(X). \]
2.4.2.1. Properties
  • Shape Operator is self-adjoint linear map with respect to the standard dot product.
  • By the , it admits two orthonormal eigenvectors with corresponding eigenvalues.
  • For a natural parametric curve \(\gamma\) with \(\gamma(0) = p, \gamma'(0) = X\),
    • \(S_p(X)\cdot X = N\cdot \gamma''(0)\)
    • The magnitude of curvature in the direction of \(N\).
  • It is a generalization of .

2.4.3. Principal Curvature

  • The eigenvalues \(k_1, k_2\) of shape operator are called the principal curvatures, and the corresponding eigenvectros \(E_1, E_2\) are called the principal directions.

2.4.4. Gaussian Curvature

2.4.4.1. Definition
  • The product of the two 2.4.3: \( K := \kappa_1\kappa_2 \).
  • \[ K = \frac{\langle (\nabla_2\nabla_1 - \nabla_1\nabla_2)\mathbf{e}_1, \mathbf{e}_2\rangle}{\det g} \]
    • where \( g \) is the 5.7
  • The Gaussian curvature at a point \(p\in \Sigma\) is defined as: \[ K(p) := \det(S_p) = \det(d_pN) = k_1k_2. \]

2.4.5. Mean Curvature

  • What is "mean" about the mean curvature? - YouTube
  • The mean of the principal curvatures, which is also the average line curvature
  • The line curvature of cross section \(\Gamma\) is given by:
    • \[ -\mathbf{v}\cdot S_\Gamma(\mathbf{v}) = -\mathbf{v}\cdot S_\Sigma(\mathbf{v}) \]
    • where \(S_\Sigma\) is the shape operator of the surface, \(S_\Gamma\) is the shape operator of the cross section, and \(\mathbf{v}\) is a tangent vector at a point.
    • \(S_\Gamma(\mathbf{v})\) is in the direction of \(\mathbf{v}\).
  • It is also \(\frac{1}{2} \operatorname{tr} S_\Sigma\).

2.4.6. Lagunov's Fishbowl

  • It is a counterexample to the statement that smooth closed surface with principal curvature, or Gaussian curvature for that matters, less than one everywhere, does not always contain a unit sphere in its interior.
  • This is contrary to the two dimensional case in which the unit disc is always contained within a simple smooth regular closed curve with curvature less than or equal to 1 everywhere.

2.5. Geodesics

2.5.1. Minimizing Curve

  • Given a smooth surface \(\Sigma\), the induced distance between two points \(p, q\in \Sigma\) is given by: \[ d(p,q) := \operatorname{inf}\{\operatorname{length}(\gamma)\mid \gamma\colon [a,b]\to \Sigma, \gamma(a) = p, \gamma(b) = q\}. \]
  • And the curve that attains the infimum is called a minimizing curve.

2.5.2. Theorem (Hopf-Rinow I)

  • If \((\Sigma, d)\) is a complete metric space, then for all \(p, q\in \Sigma\), there is a minimizing curve between \(p\) and \(q\).

2.5.3. Energy

  • For a curve \(\gamma\colon [a,b]\to \Sigma\), the energy of the curve is: \[ E(\gamma) := \frac{1}{2}\int_a^b|\gamma'(t)|^2\,dt. \]
  • Energy of a curve depends on parametrization.
2.5.3.1. Properties
  • A smooth curve \(\gamma\colon I\to \Sigma\) attains the minimum energy among all curves defined on the same interval with the same endpoint, if and only if it has constant speed and it attains the minimum length among those curves.

\[ \operatorname*{arg\,min}_{\begin{smallmatrix}\gamma\colon [a,b]\to \Sigma,\\ \gamma(a) = p_1, \gamma(b) = p_2\end{smallmatrix}} E(\gamma) = \operatorname*{arg\,min}_{\begin{smallmatrix}\gamma\colon [a,b]\to \Sigma,\\ \gamma(a) = p_1, \gamma(b) = p_2\end{smallmatrix}} \operatorname{length}(\gamma) \]

2.5.4. Variation

  • A smooth map \(\theta\colon (-\varepsilon, \varepsilon)\times [a,b]\to \Sigma\) is a variation of \(\gamma\colon [a,b]\to \Sigma\), if \(\forall t\in [a,b],\theta(0,t) = \gamma(t)\).
  • \(V(t) := \theta_s(0,t)\) is called the direction of \(\theta\).
2.5.4.1. Proper
  • A variation \(\theta\) is proper if \(\forall s\in (-\varepsilon, \varepsilon), \theta(s,a) = \gamma(a), \theta(s,b) = \gamma(b)\).
  • For a proper variation \(V(a) = V(b) = 0\).
2.5.4.2. First Variation Formula
  • For a proper variation \(\theta\colon (-\varepsilon, \varepsilon)\times [a,b]\to \Sigma\) of a smooth curve \(\gamma\colon [a,b]\to \Sigma\),
  • The energy \(E\colon (-\varepsilon,\varepsilon)\to \mathbb{R}\) defined to be \[ E(s) := \frac{1}{2}\int_a^b|\theta_t(s,t)|^2\,dt. \]
  • satisfies: \[ E'(0) = -\int_a^bV(t)\cdot \gamma''(t)\,dt. \]
  • This means by perturbing the curve in the direction it curves the energy would be decreased.

2.5.5. Geodesics

  • A \(C^2\)-curve \(\gamma\colon I\to \Sigma\) is called a geodesic if: \[ \forall t\in I, \gamma''(t) \perp T_{\gamma(t)}\Sigma. \]
  • It minimizes the energy.

2.5.6. Geodesic Curvature

  • For a naturally parametrized smooth curve \(\gamma\colon I\to \Sigma\) on a oriented surface with Gauss map \(N\), the geodesic curvature is: \[ k_\gamma(t) := \gamma''(t)\cdot(N(\gamma(t))\times \gamma'(t)). \]
  • A curve is geodesic precisely when the geodesic curvature is zero everywhere.

2.5.7. Covariant Derivative

  • Given a vector field \(V\) along \(\gamma\),
  • The vector field \(D_tV := \pi_t(V'(t))\) is called the covariant derivative of \(V\), where \(\pi_t\colon \mathbb{R}^3\to T_{\gamma(t)}\Sigma\) is the orthogonal projection.
    • Acceleration into the manifold.
2.5.7.1. Properties
  • For a naturally parametrized curve \(\gamma\colon I\to \Sigma\),
  • \[ \forall t\in I, |D_t\gamma'(t)| = |k_\gamma(t)|. \]

2.5.8. Exponential Map

2.5.8.1. Theorem
  • For a chart \(\phi\colon U\to\Sigma\) from an open subset \(U\subset\mathbb{R}^2\) containing \(p\),
  • there is an open set \(A\subset \mathbb{R}^4\) with \(0\in A\), and exists \(\varepsilon >0\), such that \(\forall (u,v,a,b)\in A,\)
  • \[ \exists \gamma \colon (-\varepsilon, \varepsilon)\to \Sigma\ \text{geodesic}, \gamma(0) = \phi(u,v), \gamma'(0) = a\phi_u + b\phi_v \]
  • And the point \(\gamma(t;u,v,a,b)\) depneds smoothly on \((u,v,a,b,t)\in A\times (-\varepsilon, \varepsilon)\).
2.5.8.2. Corollary
  • \(\forall p\in \Sigma, \exists B\text{ ball}\subset T_p\Sigma\), that admits a smooth map \(\exp_p\colon B\to \Sigma\) with
    • \[ \exp_p(v) = \gamma_v(1) \]
      • where \(\gamma_v\) is a geodesic, \(\gamma_v(0) = p, \gamma_v'(0) = v\)
    • \[ d_p\exp = \mathrm{id}_{T_p\Sigma}. \]
2.5.8.3. Theorem
  • If there is two geodesics \(\gamma_1\colon I\to \Sigma,\gamma_2\colon J\to \Sigma\), with
    • \[ \gamma_1(0) = \gamma_2(0) = p \]
    • \[ \gamma_1'(0) = \gamma_2'(0) = v \]
  • then, \(\forall t\in I\cap J, \gamma_1(t) =\gamma_2(t)\).

2.5.9. Theorem (Hopf-Rinow II)

  • For a surface \(\Sigma\subset \mathbb{R}^3\), the following are equivalent:
    • The metric space \((\Sigma, d)\) is complete.
    • For all \(q\in \Sigma\), the map \(\exp_q\colon T_q\Sigma\to \Sigma\) is defined.
    • There is \(p\in \Sigma\) such that the map \(\exp_p\colon T_p\Sigma\to \Sigma\) is defined.

2.5.10. Semigeodesic Chart

  • Motivation: \(\exists B\text{ ball}\in T_p\Sigma\), such that \(s := \exp_p\colon B\to \Sigma\) is a chart.
    • Polar coordinates within \(B\) induce vector fields \(s_r, s_\theta\colon B\setminus\{0\}\to \mathbb{R}^3\).
    • Gauss Lemma: The vector fields \(s_r\) and \(s_\theta\) are orthogonal.
    • \(|s_r| = 1.\)
  • A chart \(s\colon U\to \Sigma\) is called a semigeodesic chart if
    • For each \(v\), the map \(u\mapsto s(u,v)\) is a unit speed geodesic.
    • The vectors \(s_u\) and \(s_v\) are orthogonal.

2.5.11. Jacobi Equation

  • For a semigeodesic chart \(s\colon U\to \Sigma\), and \(b = |s_v|\): \[ bK + b_{uu} = 0. \]
  • \(b\) is the measure of how spread out the geodesics are.
  • If the surface is elliptic, then the geodesics tends to converge, on the other hand if the surface is hyperbolic, then the geodesics tends to diverge.

2.5.12. Theorema Egregium

  • Latin for "Remarkable Theorem"
  • Under the local isomety \(\phi\colon \Sigma_1\to \Sigma_2\), that is,
    • \[ \forall p\in \Sigma_1, \forall X\in T_p\Sigma, |d_p\phi(X)| = |X|, \]
  • The 2.4.4 is invariant: \[ \forall p\in \Sigma_1, K_{\Sigma_2}(\phi(p)) = K_{\Sigma_1}(p). \]

2.6. Gauss-Bonnet Theorem

  • Gauss-Bonnet Formula

2.6.1. Statement

  • For a compact two-dimensional \(M\) with boundary \(\partial M\), \[ \int_M K\,dA + \int_{\partial M}k_g\,ds = 2\pi\chi(M) \]
  • where \(K\) is the 2.4.4 of \(M\), \(k_g\) is the 2.5.6 of \(\partial M\), and \(\chi(M)\) is the of \(M\).
  • This implies that the global curvature is invariant.

2.6.2. Intuition

\( K\,dA \) is the signed area on the unit sphere with the same solid angle. For a each hole the entire surface of the sphere is covered with the direction of the area reversed, so the formula becomes:

\begin{equation*} \int_M K\,dA = 2\pi(2 - 2g). \end{equation*}

2.6.3. Local Gauss-Bonnet Theorem

\begin{equation*} \int_T K\,dA = \alpha + \beta + \gamma - \pi \end{equation*}

where \( T \) is a geodesic triangle, and \( \alpha, \beta, \gamma \) are the interior angles of it.

Notice that the parallel transport is preserved by the differential of the Gauss map, and the holonomy at the triangle on the unit sphere is equal to the area of the triangle.

3. Differentiable Manifold

3.1. Definition

  • and [second countable]( ((6692eb0e-1550-4a37-9e16-25352b2aa2e6)) ) topological space, with a maximal differentiable atlas on it.

3.2. Differentiable Atlas

  • Every ((65d5ca32-3776-4013-806c-f56784343d10)) of is differentiable.

3.2.1. Differentiably Compatible Chart

  • The inclusion of the chart into a differentiable chart results in a differentiable atlas.

3.2.2. Maximal Differentiable Atlas

  • Consists of all charts that are differentiably compatible with the given atlas.
  • Maximal smooth atlas is called the smooth structure.
  • Maximal holomorphic atlas is called the complex structure.

3.3. Differentiable Function

  • \(f\colon M \to \mathbb{R}\) is called differentiable at a point \(p\in M\) if it is differentiable in any coordinate chart defined around \(p\).
  • For a differentiable chart \((U, \phi)\), \(f\) is differentiable at \(p\) if and only if: \[ f\circ\phi^{-1}\colon \phi(U)\subset\mathbb{R}^n \to \mathbb{R} \] is differentiable at \(\phi(p)\).

3.3.1. Tangent Vector

  • Tangent vector at \(p\in M\) is an equivalence class of differentiable curves \(\gamma\) with \(\gamma(0) = p\) with the equivalence relation of first-order 1.13
  • Tangent vector \(X\) at \(p\) uniquely determines the directional derivative of the differentiable function \(f\) at \(p\): \[ Xf(p) := \frac{d}{dt}f(\gamma(t))\bigg|_{t=0}. \]
    • \(X\) can be thought of as \(\gamma'(0)\).

3.3.2. Differential

  • Fixing \(f\), the mapping \(X \mapsto Xf(p)\) which is a linear functional on the tangent space, is called the differential of \(f\) at \(p\): \[ d_pf\colon T_pM \to \mathbb{R}. \]

3.4. Differentiable Map

  • \(f\colon M\to N\) is differentiable if it is differentiable with any composition with charts.

3.5. Differential

  • Pushforward, Derivative, Total Derivative
  • The linear approximation of smooth maps on tangent spaces.
  • \(d\phi_x\) pushes tangent vectors \(T_xM\) forward to tangent vectors \(T_{\phi(x)}N\), along with \(\phi\).
  • For a smooth map \(\phi\colon M\to N\) between smooth manifolds \(M\) and \(N\), the differential of \(\phi\) at \(x\in M\) is a linear map: \[ d\phi_x\colon T_xM \to T_{\phi(x)}N. \]

3.5.1. Definition

3.5.1.1. Via Equivalence Classes of Curves
  • The differential is given by: \[ d\phi_x(\gamma'(0)) = (\varphi\circ \gamma)'(0) \]
  • where \(\gamma\colon [0,1]\to M\) is a curve based at \(x\).
  • In Euclidean spaces, ./Vector and Matrix Calculus.html#orgabf21e2 of \(\phi\) is the total derivative of \(\phi\).

3.6. Pushforward

  • \(\phi_*X\), \(\phi_\sharp X\)

3.6.1. Of Tangent Vector

  • The image \(d\phi_x(X)\) of the tangent vector \(X\in T_xM\) under \(d\phi_x\) is sometimes called the pushforward of \(X\) by \(\phi\).

3.6.2. Of Measure

  • Pushforward Measure, Pushforward, Image Measure
3.6.2.1. Definition
  • Pushforward \(f_*\mu\) of a measure \(\mu\colon \Sigma_X\to [0, \infty]\) by a measurable mapping \(f\colon X \to Y\) between measurable spaces \((X, \Sigma_X)\) and \((Y, \Sigma_Y)\) is defined by \[ f_*\mu (A) = \mu(f^{-1}[A]). \]
3.6.2.2. Properties
  • Change of Variables
    • \[ \int_Y g\,d(f_*\mu) = \int_X g\circ f\,d\mu. \]

3.7. Pullback

  • \(\phi^*X\), \(\phi_\flat X\)
  • Pullback of functions and maps, bundles and sections, multilinear forms, tensor fields, differential forms are all possible.

3.7.1. Of function

  • For a smooth map \(\phi\colon M\to N\) between manifolds \(M\) and \(N\), the pullback of a smooth function \(f\colon N\to \mathbb{R}\) by \(\phi\) is the smooth function \(\phi^*f\colon M\to \mathbb{R}\) defined by \[ \phi^*f(x) = f(\phi(x)). \]

3.7.2. Of 1-Form

  • For a smooth map \(\phi\colon M\to N\) between smooth manifolds \(M\) and \(N\), there is an associated linear map \(d\phi\) from the space of 1-forms on \(N\) to the space of 1-forms on \(M\).
3.7.2.1. Definition
  • For a smooth map \(\phi\colon M\to N\) between smooth manifolds \(M\) and \(N\), the pullback of 1-form on \(N\) \(\alpha\) by \(\phi\) is the 1-form \(\phi^*\alpha\) on \(M\) defined by: \[ (\phi^*\alpha)_x(X) = \alpha_{\phi(x)}(d\phi_x(X)). \]

3.8. Immersion

3.8.1. Definition

  • A 3.4 \(f\colon M\to N\) between 3 \(M\) and \(N\), whose 3.5 is everywhere injective, that is,
    • \[ d_pf\colon T_pM \to T_{f(p)}N \] is an injective function at every point \(p\in M\).
  • Equivalently, the derivative of \(f\) has constant rank equal to the dimension of \(M\),
    • \[ \operatorname{rank}d_pf = \dim M. \]
  • The function \(f\) itself need not be injective.

3.8.2. Properties

  • Immersion is presicely a local

3.9. Submersion

3.9.1. Definition

  • A differentiable map \(f\colon M\to N\) between differentiable manifolds \(M, N\) is a submersion if its 3.5 is everywhere surjective linear.

3.9.2. Properties

  • The notion of submersion dual to the notion of an 3.8

3.10. Diffeomorphism

  • \(\simeq\)
  • of 3

3.10.1. Definition

  • A 3.4 \(f\colon M\to N\) is called diffeomorphism if
    • \(f\) is bijection
    • \(f^{-1}\) is differentiable
  • \(r\) times continuously differentiable diffeomorphism \(f\) is called \(C^r\)-diffeomorphism.

3.11. Tangent Space

  • Vector space \(T_pM\) spanned by the basis vectors: \[ \frac{\partial }{\partial x_i}\phi^{-1}(x_1, x_2, \dots,x_n)\bigg|_{q : \phi^{-1}(q) = p} \]
    • where \(\phi\) is some chart containing \(p\).
    • They are linearly independent by definition.
    • It is independent of parametrization.

3.11.1. Jacobian

3.11.2. Inner Product

  • See Also

4. Differential Form

4.1. Definition

  • \(\omega \in \bigwedge^kT_p^*M\) is a linear function \(\omega: \bigwedge^kT_pM\to \mathbb{R}\), or ((6684199c-ef04-46c0-8d2f-a968bf9d34c2)) \(\omega\colon \bigoplus^k T_pM\to \mathbb{R}\), such that \[ \left(\bigwedge\limits_{k=1}^{n}\omega_k\right)(\mathbf{v}_1, \dots, \mathbf{v}_n) = \det\left[\omega_j(\mathbf{v}_i)\right]_{n\times n}. \]
  • n-form is totally antisymmetric (0, n)-tensor.

4.2. Exterior Product

  • Wedge Product

4.2.1. Definition

  • For a \(n\)-form \(\omega\) and \(m\)-form \(\sigma\), \(\wedge: (\omega, \sigma) \mapsto \omega\wedge \sigma\) such that: \[ (\omega\wedge\sigma)(X_1,\dots,X_{n+m}) \vcentcolon= \frac{1}{n!}\frac{1}{m!}\sum_{\pi\in S_{n+m}}\operatorname{sgn}(\pi)(\omega\otimes\sigma)(X_{\pi(1)},\dots,X_{\pi(n+m)}) \] where \(S\) is the ((655459b8-19b7-4009-9a15-f023279bb87a)).

4.3. Integration

  • \[ \int_S \omega = \iint\!\cdots\!\int_D \omega_{\varphi(u_1, u_2, \dots, u_n)}\left(\frac{\partial \varphi}{\partial u_1}, \frac{\partial \varphi}{\partial u_2},\dots, \frac{\partial \varphi}{\partial u_n}\right) dV \] where \(\omega\) is a \(n\)-form, \(\varphi: D \to S\) is a smooth function.
    • Note that \(\omega\) is linear, therefore the \(dV = du_1du_2\dots du_n\) is free to move in and out of the arguments.
  • \(m\)-form is to be integrated over m-chain \(\Sigma\) and consequently, m-cell \(\sigma\) which is defined using \(\varphi\).

4.4. Transformation

4.4.1. Geometric Intuition

  • For 2-forms in three dimension:
    • \[ dx^i\wedge dx^j = \sum_{k, l} \begin{vmatrix} \dfrac{\partial x^i}{\partial \tilde{x}^k} & \dfrac{\partial x^i}{\partial \tilde{x}^l} \\[10pt] \dfrac{\partial x^j}{\partial \tilde{x}^k} & \dfrac{\partial x^j}{\partial \tilde{x}^l} \end{vmatrix} d\tilde{x}^k\wedge d\tilde{x}^l \]
  • The determinants is the scaling factors, which becomes the determinant of the Jacobian if the order of the form coincides with the number of dimensions, i.e. the form is a pseudoscalar.

4.4.2. Direct Transformation

  • \[ \bigwedge_i dx^i = \bigwedge_i \frac{\partial x^i}{\partial \tilde{x}^j} d\tilde{x}^j \]
  • This can be seen as using the inverse .

4.4.3. Tensor Transformation

  • Since differential form is a tensor with special properties, it follows the normal transformation rules of the , which is equivalent to the above two methods.

4.5. Example

  • \(\omega = adx + bdy + xdz\) takes one vector: \(\omega(\mathbf{v}) = av_x + bv_y + xv_z\).
  • \[ \int_S \omega = \int_0^1 \omega_{\mathbf{x}(t)}\left(\frac{\partial \mathbf{x}}{\partial t}\right)dt = \int_0^1 \left(a\frac{\partial x}{\partial t} + b\frac{\partial y}{\partial t} + x\frac{\partial z}{\partial t}\right)dt \]
    • The \(dx\) is replaced by \(\partial_t x\,dt\). The \(dx\) still means the change in \(x\) coordinate, sometimes it is non-infinitesimal, but in this specific evaluation, it is the change in \(x\) due to the change in \(t\).

4.6. Exterior Derivative

  • A generalization of high dimensional derivatives on a manifold.
  • Exterior derivative of a scalar field yields a ((655459b9-8584-48ba-82a3-a521a935e24b)) field, which is the 1-form.

4.6.1. Definition

  • \[ d\omega = d(f_Idx^I) = \frac{\partial f_I}{\partial x^j}dx^j\wedge dx^I \] where \(I\) is the multi-index such that \(dx^I = dx^{i_1}\wedge dx^{i_2}\wedge\dots\wedge dx^{i_m}\).

4.6.2. Properties

  • \[ d(\omega\wedge\mu) = (d\omega)\wedge \mu + (-1)^m\omega\wedge(d\mu) \] where \(\omega\) is an \(m\)-form.
  • \[ d^2\omega = 0 \]

4.7. Hodge Duality

  • Note that \[ \dim \bigwedge\nolimits^m(\mathbb{R}^n)=\binom{n}{m} = \binom{n}{n-m} = \dim \bigwedge\nolimits^{n-m}(\mathbb{R}^n) \] which establishes the Hodge duality.

4.7.1. Hodge Operator

  • \(\star\), Hodge Star
  • It is the complement. Formally: \[ \star dx_I = dx_J: dx_I\wedge dx_J = dx_1\wedge dx_2\wedge \dots \wedge dx_n \] where \(I\) and \(J\) are the multi-indices.
  • e.g. In \(\mathbb{R}^3\), \(\star dx = dy\wedge dz\).

4.8. Differential Operators

4.8.1. Gradient

  • \[ \nabla f \rightsquigarrow df \]

4.8.2. Curl

  • \[ \nabla \times \mathbf{F} \rightsquigarrow \star d \omega_{F} \]

4.8.3. Divergence

  • \[ \nabla \cdot \mathbf{F} \rightsquigarrow \star d(\star \omega_F) \]

4.9. Inner Product

4.9.1. Definition

  • \(\langle \cdot ,\cdot \rangle: \bigwedge^m(\mathbb{R}^n)\times \bigwedge^m(\mathbb{R}^n)\to \mathbb{R}\).
  • Only the inner product for the basis needs to be defined for the entire inner product to be defined, since the lifting.

4.9.2. Lifting

  • Inner product for a lower form can be lifted for a higher form with \[ \langle dx_I, dx_J \rangle = \sum_{\sigma \in S_m}\left(\operatorname{sgn}(\sigma)\prod_{k=1}^m\langle dx_{i_k}, dx_{j_{\sigma(k)}}\rangle\right) \] where \(I\) and \(J\) are multi-indices and \(S_m\) is the set of all permutations of \(m\) elements.

4.9.3. Properties

  • \(\omega_1\wedge\star\omega_2 = \langle \omega_1, \omega_2\rangle dx_1\wedge dx_2\wedge\dots\wedge dx_n\), where \(\omega_1\) and \(\omega_2\) are of the same order.

4.10. Volume Form

  • Top-Dimensional Form
  • The form of degree equal to the dimension of a given manifold.
  • It is notated as \(\mathrm{d}^n\mathbf{x}\) in physics, and it is right-hand oriented.

5. Tensor Calculus

  • Tensor Analysis, Ricci Calculus
  • Calculus of on Manifolds.

5.1. Vector

  • (1, 0)-Tensor
  • \[ \mathbf{v}=\frac{d}{d\lambda} \] in which \(\lambda \mapsto \mathbf{x}\) is defined. \(\mathbf{v}\) is the tangent vector on the curve defined by \(\mathbf{x}(\lambda)\).
    • This definition is due to the form of the directional derivative along the curve \(\mathbf{x}\).
    • Also the remnant of the explicit formula.

5.1.1. Basis Vectors

  • \[ \mathbf{e}_i=\frac{\partial}{\partial x^i} \]
  • This works everywhere on a manifold. \(\vec{e}_i\) may change its direction and magnitude.
  • \[ \frac{d}{d\lambda}=\frac{\partial}{\partial x^i}\frac{dx^i}{d\lambda} \]

5.1.2. Transformation

  • \[ \frac{\partial}{\partial x^i}\frac{dx^i}{d\lambda}=\frac{\partial}{\partial x^i}J^{-1}\vphantom{J}^i_jJ^j_k\frac{dx^k}{d\lambda}=\frac{\partial}{\partial \tilde{x}^j}\frac{d\tilde{x}^j}{d\lambda} \]
  • Basis vectors are covariant and vector components are contravariant.

5.2. Kronecker Delta

5.2.1. Definition

  • \(\delta_{ij}\), \(\delta_i^j\), \(\delta^{ij}\)
  • 1 if the indices are the same, 0 if not.

5.2.2. Generalized Kronecker Delta

  • \(\delta^{\mu_1\dots\mu_p}_{\nu_1\dots\nu_p}\)
    • 1 if \(\nu_i\)s are distinct integers and are an even permutation of \(\mu_i\)s,
    • -1 if \(\nu_i\)s are distinct integers and are an odd permutation of \(\mu_i\)s,
    • 0 otherwise.
  • \[ \delta^{\mu_1\dots\mu_p}_{\nu_1\dots\nu_p} = \sum_{\sigma\in S_p}\mathrm{sgn}(\sigma)\delta^{\mu_1}_{\nu_{\sigma(1)}}\cdots \delta^{\mu_p}_{\nu_{\sigma(p)}} = \sum_{\sigma\in S_p}\mathrm{sgn}(\sigma)\delta^{\mu_{\sigma(1)}}_{\nu_1}\cdots \delta^{\mu_{\sigma(p)}}_{\nu_p} \]

5.3. Levi-Civita Symbols

  • Levi-Civita Epsilon, Permutation Symbol, Antisymmetric Symbol, Alternating Symbol

5.3.1. Definition

  • Levi-Civita symbol \(\epsilon_{\mu_1\mu_2\dots\mu_n}\) is \(1\) when \(\mu_i\) are distinct and \((\mu_1\mu_2\dots\mu_n)\) is an even permutaion, and \(-1\) when \(\mu_i\) are distinct and it's an odd permutation, and \(0\) otherwise.

5.3.2. Properties

  • Using the Einstein notation:
  • \(\varepsilon_{ijk} \varepsilon^{pqr}=\delta_i{}^p\delta_j{}^q\delta_k{}^r - \delta_i{}^p\delta_j{}^r\delta_k{}^q + \delta_i{}^r\delta_j{}^p\delta_k{}^q - \delta_i{}^r\delta_j{}^q\delta_k{}^p + \delta_i{}^q\delta_j{}^r\delta_k{}^p - \delta_i{}^q\delta_j{}^p\delta_k{}^r.\)
  • \(\varepsilon_{ijk}\varepsilon^{pqk} = \delta_i^p\delta_j^q - \delta_i^q\delta_j^p.\)
  • \(\varepsilon_{jmn}\varepsilon^{imn} = 2\delta_j^i.\)
  • \(\varepsilon_{ijk}\varepsilon_{ijk}=6.\)

5.4. Covector

  • (0, 1)-Tensor

Differential forms are covectors

  • \(d\) is interpreted as an operator that takes a scalar field \(f\) and returns a covector field \(df\).
  • Since \(df\) is a covector, \[ df(\mathbf{v})=\nabla_{\mathbf{v}}f \]

5.4.1. Basis covectors

  • \[ \epsilon^i=dx^i \]
  • \[ df=\frac{\partial f}{\partial x^i}dx^i \]

5.4.2. Transformation

  • \[\frac{\partial f}{\partial x^i}dx^i=\frac{\partial f}{\partial x^i}J^{-1}\vphantom{J}^i_j J^j_k dx^k=\frac{\partial f}{\partial \tilde{x}^j}d\tilde{x}^j\]
  • Basis covectors are contravariant and covector components are covariant.

5.5. Integration

  • \[ \int_{P[a,b]}d\phi \]
  • Evaluate the path \(P\) on the covector field \(d\phi\)
  • This covector field is entirely geometric object which means it is invariant with respect to the choice of coordinate systems.

5.6. Duality

  • Differential \(df\) and the \(\nabla f\) are dual where one is covector field and the other is vector field.
  • \[ df=(\nabla f)^ig_{ij}dx^j \]
  • Which means \[ (\nabla f)^i=\frac{\partial f}{\partial x^j}g^{ij} \] where \(g^{ij}\) is the inverse metric tensor satisfying \(g_{ij}g^{jk}=\delta_i^k\).

5.7. Metric Tensor

  • (0, 2)-Tensor

5.7.1. Definition

  • \[ g_{ij}(\epsilon^i\otimes\epsilon^j)=\frac{\partial}{\partial x^i}\cdot\frac{\partial}{\partial x^j}(\epsilon^i\otimes\epsilon^j) \]

5.7.2. Properties

  • Bilinear
  • Symmetric

5.7.3. Transformation

  • \[ g_{ij}\epsilon^{i}\epsilon^{j}=\frac{\partial}{\partial x^i}\cdot\frac{\partial}{\partial x^j}\epsilon^{i}\epsilon^{j}=\frac{\partial}{\partial x^i}\cdot\frac{\partial}{\partial x^j}J^{-1}\vphantom{J}^i_kJ^{-1}\vphantom{J}^j_lJ^k_{m}J^l_{n}\epsilon^{m}\epsilon^{n}=\frac{\partial}{\partial \tilde{x}^k}\cdot\frac{\partial}{\partial \tilde{x}^l}\tilde{\epsilon}^{k}\tilde{\epsilon}^{l}=\tilde{g}_{kl}\tilde{\epsilon}^{k}\tilde{\epsilon}^{l} \]
  • \[ \left(\mathbf{J}^{-1}\right)^\mathrm{T}\mathbf{g}\mathbf{J}^{-1}=\tilde{\mathbf{g}} \]

5.8. Christoffel Symbols

5.8.1. Definition

5.8.1.1. Extrinsic
  • \[ \frac{\partial \mathbf{e}_i}{\partial x^j}=\Gamma^k_{ij}\mathbf{e}_k \]
5.8.1.2. Levi-Civita Connection
  • Informally, \(\partial_y\mathbf{e}_x=\partial_x\mathbf{e}_y\).
    • This way space can line up.
  • \[ {\Gamma^k}_{ij} = \frac{1}{2}g^{kl} \left( \frac{\partial g_{li}}{\partial x^{j}} + \frac{\partial g_{lj}}{\partial x^i} - \frac{\partial g_{ij}}{\partial x^l} \right) \]

5.8.2. Transformation

  • \[ \tilde{\Gamma}^k_{ij}=\frac{\partial \tilde{x}^k}{\partial x^n}\left( \frac{\partial x^l}{\partial \tilde{x}^i}\frac{\partial x^m}{\partial \tilde{x}^j} \Gamma^{n}_{lm}+\frac{\partial^2 x^n}{\partial \tilde{x}^i\partial \tilde{x}^j}\right) \]

5.9. Geodesic

  • A straightest possible line along a manifold.
  • Geodesic is created when a vector is parallel transported along itself.

5.9.1. Definition

  • A curve with zero tangential acceleration, which means a curve \(C: \lambda \mapsto \mathbf{x}\) satisfying the geodesic equation.

5.9.2. Geodesic Equation

  • \[ \frac{d^2}{d\lambda^2} = 0 \]
  • Component form \[ \frac{d^2 x^k}{d\lambda^2} + \frac{d x^i}{d\lambda}\frac{d x^j}{d\lambda}\Gamma^k_{ij}=0 \] where \(\Gamma^k_{ij}\) is the 5.8.
  • It is about the covariant derivative of the tangent vectors along the curve being equal to zero.
5.9.2.1. Derivation
\begin{align*} \frac{d^2}{d\lambda^2}&=\frac{d}{d\lambda}\left( \frac{d x^i}{d\lambda}\frac{\partial}{\partial x^i} \right)\\ &=\frac{d^2 x^i}{d\lambda^2}\frac{\partial}{\partial x^i} + \frac{d x^i}{d\lambda}\frac{d}{d\lambda}\left(\frac{\partial}{\partial x^i}\right)\\ &=\frac{d^2 x^i}{d\lambda^2}\frac{\partial}{\partial x^i} + \frac{d x^i}{d\lambda}\frac{d x^j}{d\lambda}\frac{\partial^2}{\partial x^j\partial x^i}\\ &=\frac{d^2 x^k}{d\lambda^2}\frac{\partial}{\partial x^k} + \frac{d x^i}{d\lambda}\frac{d x^j}{d\lambda}\Gamma^k_{ij}\frac{\partial}{\partial x^k} + \frac{d x^i}{d\lambda}\frac{d x^j}{d\lambda}L_{ij}\hat{\mathbf{n}}\\ &=\left(\frac{d^2 x^k}{d\lambda^2} + \frac{d x^i}{d\lambda}\frac{d x^j}{d\lambda}\Gamma^k_{ij}\right)\frac{\partial}{\partial x^k} + \frac{d x^i}{d\lambda}\frac{d x^j}{d\lambda}L_{ij}\hat{\mathbf{n}} \end{align*}

5.10. Covariant Derivative

  • It is about the rate of deviation of the vector field from the parallel transport. If the vector field are in such a way that a parallel transport of a vector at one point is the vector near that point in the direction of other vector field, this vector field represents the parallel transport.
  • Covariant: Derivative that is invariant under the change of coordinates.
  • It is required to take the derivative of arbitrary tensor field on a 3

5.10.1. Definition

5.10.1.1. In flat space
  • Derivative that take the change in basis vectors into account.
  • \[ \frac{\partial}{\partial x^i}(\mathbf{v})=\left( \frac{\partial v^k}{\partial x^i} + v^j\Gamma^k_{ji} \right)\frac{\partial}{\partial x^k} \]
  • \[ f^k\vphantom{f}_{;i}=\frac{\partial v^k}{\partial x^i} + v^j\Gamma^k_{ji} \] is a (1, 1)-Tensor that follows the transformation rule.
  • The full equation is: \[ \frac{d}{d\lambda}(\mathbf{v})=\left( \frac{d v^k}{d \lambda} + v^j\frac{dx^i}{d\lambda}\Gamma^k_{ji} \right)\frac{\partial}{\partial x^k} \]
5.10.1.2. Extrinsic
  • Rate of change in vector field with the normal component substracted.
  • \[ \nabla_{\frac{d}{d\lambda}}\mathbf{v}=\frac{d\mathbf{v}}{d\lambda}-\mathbf{n} \]
    • \begin{align*} \frac{d\mathbf{v}}{dλ}-\mathbf{n}&=\left(\frac{d v^k}{d\lambda} + vi\frac{d xj}{dλ}Γkij\right)\frac{\partial}{\partial x^k} + vi\frac{d xj}{dλ}Lij\hat{\mathbf{n}}-\mathbf{n}
      &=\left(\frac{d v^k}{d\lambda} + vi\frac{d xj}{dλ}Γkij\right)\frac{\partial}{\partial x^k} \end{align*}
5.10.1.3. Intrinsic
  • Given a metric tensor \(g_{ij}\), the Christoffel symbol of the 5.8.1.2 can be calculated under metric compatibility \[ \Gamma^k_{ij}=\frac{1}{2}\mathfrak{g}^{kl}\left(\frac{\partial g_{li}}{\partial x^j}+\frac{\partial g_{jl}}{\partial x^i}-\frac{\partial g_{ij}}{\partial x^l}\right) \]
5.10.1.4. Αbstract
  • Covariant derivative \(\nabla\), also called connection, is defined to be
    • \[ \nabla_{\partial_i}(a) = \frac{\partial a}{\partial x^i} \]
    • \[ \nabla_{a\mathbf{v}+b\mathbf{w}}\mathbf{u}=a\nabla_{\mathbf{v}}\mathbf{u}+b\nabla_{\mathbf{w}}\mathbf{u} \]
    • \[ \nabla_{\mathbf{w}}(\mathbf{u}+\mathbf{v})=\nabla_{\mathbf{w}}\mathbf{u}+\nabla_{\mathbf{w}}\mathbf{v} \]
    • \[ \nabla_{\mathbf{w}}(a\mathbf{u})=(\nabla_{\mathbf{w}}a)\mathbf{u}+a(\nabla_{\mathbf{w}}\mathbf{u}) \]
  • The Christoffel symbols, or sometimes, connection coefficients \(\Gamma^k_{ij}\) are to be determined
  • By 6.1, there always exists a unique connection that is torsion-free and metric-compatible, which is Levi-Civita connection.
5.10.1.4.1. Metric-Compatibility
  • \[ \nabla_{\mathbf{w}}(\mathbf{u}\cdot\mathbf{v})=(\nabla_{\mathbf{w}}\mathbf{u})\cdot\mathbf{v}+\mathbf{u}\cdot(\nabla_{\mathbf{w}}\mathbf{v}) \]
5.10.1.4.2. Torsion-Free
  • \[ \nabla_{\mathbf{w}}\mathbf{v}-\nabla_{\mathbf{v}}\mathbf{w}=[\mathbf{w}, \mathbf{v}] \]

5.10.2. Covector

  • \[ \nabla_{\partial_i}(\alpha)=\left( \frac{\partial \alpha_k}{\partial x^i} - \alpha_j\Gamma^j_{ik} \right)dx^k \]

5.10.3. Tensor

  • Assert \[ \nabla_{\mathbf{w}}(T\otimes S)=(\nabla_{\mathbf{w}}T)\otimes S+T\otimes(\nabla_{\mathbf{w}}S) \]
  • For a (n, m)-Tensor we have \(n\) positive Christoffel symbol terms and \(m\) negative ones.

5.11. Parallel Transport

  • A vector \(\mathbf{v}\) is parallel transported if for \(\mathbf{v}: \lambda\mapsto \mathbf{v}(\lambda)\) \[ \nabla_{\frac{d}{d\lambda}}\mathbf{v}=0. \]

5.12. Lie Bracket

  • It is the vector between two vector fields that describes the antisymmetry.
  • It does not account for the change of the basis vectors.
  • It is a form of Lie derivative \( \mathcal{L}_XY \).

5.12.1. Definitions

  • Coordinate definition

\[ [X, Y](f) = (X^j\partial_jY^i - Y^j\partial_jX^i)\partial_i \]

5.13. Torsion Tensor

\[ T(\mathbf{u},\mathbf{v})=\nabla_{\mathbf{u}}\mathbf{v}-\nabla_{\mathbf{v}}\mathbf{u}-[\mathbf{u}, \mathbf{v}] \]

\[ T^k_{ij}=\Gamma^k_{ij}-\Gamma^k_{ji} \]

  • It is the rate of failure of the parallel transported vectors does not connects.

5.14. Riemann Curvature Tensor

  • Rate of holonomy of \(\mathbf{w}\) along an infinitesimal parallelogram obtained by \(\mathbf{u}\) and \(\mathbf{v}\)
  • \[ R(\mathbf{u},\mathbf{v})\mathbf{w}=\nabla_{\mathbf{u}}\nabla_{\mathbf{v}}\mathbf{w}-\nabla_{\mathbf{v}}\nabla_{\mathbf{u}}\mathbf{w}-\nabla_{[\mathbf{u},\mathbf{v}]}\mathbf{w} \]
  • It is measured indirectly using arbitrary vector fields \( \mathbf{u}, \mathbf{v} \). The change of vector fields itself is canceled out, and the contribution of the curved space remains.
  • The direction is from the changed vector to the original vector.
  • Explicitly:

\[ R^i_{jkl} = \frac{\partial \Gamma^i_{lj}}{\partial x^k} -\frac{\partial \Gamma^i_{kj}}{\partial x^l} + (\Gamma^i_{kp}\Gamma^p_{lj} - \Gamma^i_{lp}\Gamma^p_{kj}). \]

  • The upper index is the output vector index, first lower index is for the transported vector, second and third lower indices are for the two vectors that define a plane for the holonomy.

5.14.1. Properties

  • Bianchi Identity: \( R_{dcab} + R_{dbca} + R_{dabc} = 0 \) from torsion-free
  • 12-symmetry: \( R_{abcd} = - R_{bacd} \) from metric compatibility.
  • 34-symmetry: \( R^a_{bcd} = -R^a_{bdc} \)
  • Flip: \( R_{abcd} = R_{cdab} \)

5.15. Ricci Curvature Tensor

  • \[ \mathrm{Ric}(\mathbf{v},\mathbf{v})=\sum_i K(\partial_i, \mathbf{v})=(R(\partial_i, \mathbf{v})\mathbf{v})\cdot\partial_i=v^jv^kR^i_{kij} \] where \(K\) is sectional curvature and \(\partial_i, \mathbf{v}\) are orthonormal basis.
  • \[ R_{kj}=R^i_{kij} \]
  • It also represents the change in the volume element.

Ricci curvature can tell us about size, but can't tell us about shape.

5.15.1. Sectional Curvature

  • From the geodesic equation \( \nabla_\mathbf{v}\mathbf{v} = 0 \) and the torsion-free condition, the relation between the geodesic deviation and the Riemann curvature tensor is derived:

\[ \nabla_\mathbf{v}\nabla_\mathbf{v} \mathbf{s} = - R(\mathbf{s},\mathbf{v})\mathbf{v}, \] where \(\mathbf{s}\) is the separation vector between a geodesic and nearby ones, and \(\mathbf{v}\) are the tangent vector along a geodesic.

  • The sectional curvature is defined as follows:

\[ K(\mathbf{s}, \mathbf{v}) := \frac{R(\mathbf{s}, \mathbf{v})\mathbf{v} \cdot \mathbf{s}}{(\mathbf{s}\cdot\mathbf{s})(\mathbf{v}\cdot\mathbf{v}) - (\mathbf{s}\cdot\mathbf{v})^2} \]

  • The manifold is elliptic, in other words, geodesics converges if this is positive, and otherwise, negative.
  • It is independent of the choice of vectors, only on the plane that contains those vectors.

5.15.2. Ricci Scalar

  • \[ R=g^{ij}R_{ij} \]
  • Positive Ricci scalar means the space is elliptic and negative means hyperbolic.

5.15.3. Volumn Form

\[ \omega(\mathbf{u},\mathbf{v},\mathbf{w})=\sqrt{\det(g)}\epsilon_{ijk}u^iv^jw^k \] where \(\epsilon_{ijk}\) is the .

  • \[ \nabla_\mathbf{v}V = 0 \implies \nabla_\mathbf{v}\omega = 0 \] using the Levi-Civita connection that preserves the lengths and angles.
  • Using separation vectors \( \mathbf{s}_1, \mathbf{s}_2, \mathbf{s}_3 \), and the geodesic deviation \( \ddot{s}_j^{\mu_j} = -R^{\mu_j}_{xyz}s_j^yv^zv^x \), the second derivative of the volume is given by: \[ \frac{d^2V}{d\lambda^2} = -R_{xy}v^xv^z(V) + \left( \dot{s}_j^{\mu_j}\dot{s}_k^{\mu_k}\prod_{i\neq j, k, i=1}^D s_i^{\mu_i} \right) \sqrt{\det g} \epsilon_{\mu_1\dots\mu_D} \]
    • The first term is the acceleration term and the second term is velocity term, therefore the first term tells the curvature.

6. Riemannian Geometry

6.1. Fundamental Theorem of Riemannian Geometry

7. References

Created: 2025-05-06 Tue 23:34