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-============================================
-Tensors, Differential Geometry, Manifolds
-============================================
-
-.. note:: Most of this content is based on a 2002 Caltech course taught by
-    Kip Thorn [PH237]_
-
-
-On a manifold, only "short" vectors exist. Longer vectors are in a space tangent to the manifold.
-
-There are points (:m:`$P$`), separation vectors (:m:`$\Delta \vector P$`),
-curves (:m:`$Q(\zeta)$`), tangent vectors (:m:`$\delta P / \delta \zeta \equiv
-\lim_{\Delta \zeta \rightarrow 0} \frac{ \vector{ Q(\zeta+\delta \zeta) -
-Q(\zeta) } }{\delta \zeta}$`)
-
-Coordinates: :m:`$\Chi^\alpha (P)$`, where :m:`$\alpha = 0,1,2,3$`;
-:m:`$Q(\Chi_0, \Chi_1, ...)$`
-    there is an isomorphism between points and coordinates
-
-Coordinate basis: :m:`$\vector{e_\alpha} \equiv \left( \frac{\partial
-Q}{\partial \Chi^\alpha} \right$`)
-    
-    for instance, on a sphere with angles :m:`$\omega, \phi$`: 
-    
-    :m:`$\vector{e_\phi} = \left( \frac{\partial Q(\phi, \theta)}{\partial \phi}\right)_\theta$`
-
-Components of a vector:
-
-    :m:`$\vector{A} = \frac{\partial P}{\partial \Chi^\alpha }$`
-
-Directional Derivatives: consider a scalar function defined on a manifold \Psi(P)
-    :m:`$\partial_\vector{A} \Psi = A^\alpha \frac{\partial \Psi}{\partial \Chi^\alpha}$`
-
-Mathematicians like to say that the coordinate bases are actually directional derivatives
-
-Tensors
-------------
-
-A **tensor** :m:`$\bold{T}$` has a number of slots (called it's **rank**), takes a vector in each slot, and returns a real number. It is linear in vectors; 
-as an example for a rank-3 tensor:
-
-:m:`$$\bold{T} ( \alpha \vector{A} + \beta \vector{B}, \vector{C}, \vector{D}) =
-\alpha \bold{T} (\vector{A}, \vector{C}, \vector{D}) + \beta \bold{T}
-(\vector{B}, \vector{C}, \vector{D}) $$`
-
-Even a regular vector is a tensor: pass it a second vector and take the 
-inner product (aka dot product) to get a real.
-
-Define the **metric tensor** 
-:m:`$\bold{g}(\vector{A}, \vector{B}) = \vector{A} \cdot \vector{B}$`. The 
-metric tensor is rank two and symetric (the vectors A and B could be swapped 
-without changing the scalar output value) and is the same as the inner product. 
-
-:m:`$$\Delta P \cdot \Delta P \equiv \Delta P^2 \equiv (length of \Delta P)^2 A \cdot B = 1/4[ (A+B)^2 - (A-B)^2 ]$$`
-
-Starting with individual vectors, we can construct tensors by taking the 
-product of their inner products with empty slots; for example
-
-:m:`$$\vector{A} \crossop \vector{B} \crossop \vector{C} (\_ ,\_ ,\_)$$` 
-:m:`$$\vector{A} \crossop \vector{B} \crossop \vector{C} (\vector{E}, \vector{F}, \vector{G}) = ( \vector{A} \cdot \vector{E})(\vector{B} \cdot \vector{F})(\vecotr{C} \cdot \vector{G}) $$` 
-
-Spacetime
---------------
-
-Two types of vectors.
-
-Timelike: :m:`$\vector{\Delta P}$`
-    :m:`$(\vector{\Delta P})^2 = -(\Delta \Tau)^2$`
-
-Spacelike: :m:`$\vector{\Delta Q}$`
-    :m:`$(\vector{\Delta Q})^2 = +(\Delta S)^2$`
-
-Because product of "up" and "down" basis vectors must be a positive Kronecker 
-delta, and timelikes squared come out negative, the time "up" basis must be  negative of the time "down" basis vector.