Metric tensor

Definition

Let M be a smooth manifold of dimension n; for instance a surface (in the case n = 2) or hypersurface in the Cartesian space ${\displaystyle {\mathbb{R}}^{n+1}}$. At each point p ∈ M there is a vector space T_pM, called the tangent space, consisting of all tangent vectors to the manifold at the point p. A metric tensor at p is a function g_p(X_p, Y_p) which takes as inputs a pair of tangent vectors X_p and Y_p at p, and produces as an output a real number (scalar), so that the following conditions are satisfied:

• g_p is bilinear. A function of two vector arguments is bilinear if it is linear separately in each argument. Thus if U_p, V_p, Y_p are three tangent vectors at p and a and b are real numbers, then $${\displaystyle \begin{array}{cc}{g}_p(a{U}_p+b{V}_p,Y_p)& =a{g}_p(U_p,Y_p)+b{g}_p(V_p,Y_p),\text{and}\\ g_p(Y_p,a{U}_p+b{V}_p)& =a{g}_p(Y_p,U_p)+b{g}_p(Y_p,V_p).\end{array}}$$
• g_p is symmetric. A function of two vector arguments is symmetric provided that for all vectors X_p and Y_p, $${\displaystyle g_p(X_p,Y_p)=g_p(Y_p,X_p).}$$
• g_p is nondegenerate. A bilinear function is nondegenerate provided that, for every tangent vector X_p ≠ 0, the function $${\displaystyle Y_p\mapsto g_p(X_p,Y_p)}$$ obtained by holding X_p constant and allowing Y_p to vary is not identically zero. That is, for every X_p ≠ 0 there exists a Y_p such that g_p(X_p, Y_p) ≠ 0.

A metric tensor field g on M assigns to each point p of M a metric tensor g_p in the tangent space at p in a way that varies smoothly with p. More precisely, given any open subset U of manifold M and any (smooth) vector fields X and Y on U, the real function $${\displaystyle g(X,Y)(p)=g_p(X_p,Y_p)}$$ is a smooth function of p.

Components of the metric

The components of the metric in any basis of vector fields, or frame, f = (X₁, ..., X_n) are given by

The n² functions g_ij[f] form the entries of an n × n symmetric matrix, G[f]. If

${\displaystyle v=\sum _{i=1}^n{v}^i{X}_i,w=\sum _{i=1}^n{w}^i{X}_i}$

are two vectors at p ∈ U, then the value of the metric applied to v and w is determined by the coefficients (4) by bilinearity:

${\displaystyle g(v,w)=\sum _{i,j=1}^n{v}^i{w}^{j}g\left(X_i,X_j\right)=\sum _{i,j=1}^n{v}^i{w}^j{g}_{ij}[\mathbf{f}]}$

Denoting the matrix (g_ij[f]) by G[f] and arranging the components of the vectors v and w into column vectors v[f] and w[f],

${\displaystyle g(v,w)=\mathbf{v}[\mathbf{f}{]}^{\mathsf{T}}G[\mathbf{f}]\mathbf{w}[\mathbf{f}]=\mathbf{w}[\mathbf{f}{]}^{\mathsf{T}}G[\mathbf{f}]\mathbf{v}[\mathbf{f}]}$

where v[f]^T and w[f]^T denote the transpose of the vectors v[f] and w[f], respectively. Under a change of basis of the form

${\displaystyle \mathbf{f}\mapsto {\mathbf{f}}^{\prime }=\left(\sum _k{X}_k{a}_{k1},\dots ,\sum _k{X}_k{a}_{kn}\right)=\mathbf{f}A}$

for some invertible n × n matrix A = (a_ij), the matrix of components of the metric changes by A as well. That is,

${\displaystyle G[\mathbf{f}A]=A^{\mathsf{T}}G[\mathbf{f}]A}$

or, in terms of the entries of this matrix,

${\displaystyle g_{ij}[\mathbf{f}A]=\sum _{k,l=1}^n{a}_{ki}{g}_{kl}[\mathbf{f}]a_{lj}.}$

For this reason, the system of quantities g_ij[f] is said to transform covariantly with respect to changes in the frame f.

Metric in coordinates

A system of n real-valued functions (x¹, ..., xⁿ), giving a local coordinate system on an open set U in M, determines a basis of vector fields on U

${\displaystyle \mathbf{f}=\left(X_1=\frac{\mathrm{\partial }}{\mathrm{\partial }{x}^1},\dots ,X_n=\frac{\mathrm{\partial }}{\mathrm{\partial }{x}^n}\right).}$

The metric g has components relative to this frame given by

${\displaystyle g_{ij}\left[\mathbf{f}\right]=g\left(\frac{\mathrm{\partial }}{\mathrm{\partial }{x}^i},\frac{\mathrm{\partial }}{\mathrm{\partial }{x}^j}\right).}$

Relative to a new system of local coordinates, say

${\displaystyle y^i=y^i(x^1,x^2,\dots ,x^n),i=1,2,\dots ,n}$

the metric tensor will determine a different matrix of coefficients,

${\displaystyle g_{ij}\left[{\mathbf{f}}^{\prime }\right]=g\left(\frac{\mathrm{\partial }}{\mathrm{\partial }{y}^i},\frac{\mathrm{\partial }}{\mathrm{\partial }{y}^j}\right).}$

This new system of functions is related to the original g_ij(f) by means of the chain rule

${\displaystyle \frac{\mathrm{\partial }}{\mathrm{\partial }{y}^i}=\sum _{k=1}^n\frac{\mathrm{\partial }{x}^k}{\mathrm{\partial }{y}^i}\frac{\mathrm{\partial }}{\mathrm{\partial }{x}^k}}$

so that

${\displaystyle g_{ij}\left[{\mathbf{f}}^{\prime }\right]=\sum _{k,l=1}^n\frac{\mathrm{\partial }{x}^k}{\mathrm{\partial }{y}^i}{g}_{kl}\left[\mathbf{f}\right]\frac{\mathrm{\partial }{x}^l}{\mathrm{\partial }{y}^j}.}$

Or, in terms of the matrices G[f] = (g_ij[f]) and G[f′] = (g_ij[f′]),

${\displaystyle G\left[{\mathbf{f}}^{\prime }\right]={\left((Dy{)}^{-1}\right)}^{\mathsf{T}}G\left[\mathbf{f}\right](Dy{)}^{-1}}$

where Dy denotes the Jacobian matrix of the coordinate change.

Signature of a metric

Associated to any metric tensor is the quadratic form defined in each tangent space by

${\displaystyle q_m(X_m)=g_m(X_m,X_m),X_m\in T_{m}M.}$

If q_m is positive for all non-zero X_m, then the metric is positive-definite at m. If the metric is positive-definite at every m ∈ M, then g is called a Riemannian metric. More generally, if the quadratic forms q_m have constant signature independent of m, then the signature of g is this signature, and g is called a pseudo-Riemannian metric. If M is connected, then the signature of q_m does not depend on m.

By Sylvester's law of inertia, a basis of tangent vectors X_i can be chosen locally so that the quadratic form diagonalizes in the following manner

${\displaystyle q_m\left(\sum _i{\xi }^i{X}_i\right)={\left({\xi }^1\right)}^2+{\left({\xi }^2\right)}^2+\cdots +{\left({\xi }^p\right)}^2-{\left({\xi }^{p+1}\right)}^2-\cdots -{\left({\xi }^n\right)}^2}$

for some p between 1 and n. Any two such expressions of q (at the same point m of M) will have the same number p of positive signs. The signature of g is the pair of integers (p, n − p), signifying that there are p positive signs and n − p negative signs in any such expression. Equivalently, the metric has signature (p, n − p) if the matrix g_ij of the metric has p positive and n − p negative eigenvalues.

Certain metric signatures which arise frequently in applications are:

• If g has signature (n, 0), then g is a Riemannian metric, and M is called a Riemannian manifold. Otherwise, g is a pseudo-Riemannian metric, and M is called a pseudo-Riemannian manifold (the term semi-Riemannian is also used).
• If M is four-dimensional with signature (1, 3) or (3, 1), then the metric is called Lorentzian. More generally, a metric tensor in dimension n other than 4 of signature (1, n − 1) or (n − 1, 1) is sometimes also called Lorentzian.
• If M is 2n-dimensional and g has signature (n, n), then the metric is called ultrahyperbolic.

Inverse metric

Let f = (X₁, ..., X_n) be a basis of vector fields, and as above let G[f] be the matrix of coefficients

${\displaystyle g_{ij}[\mathbf{f}]=g\left(X_i,X_j\right).}$

One can consider the inverse matrix G[f]⁻¹, which is identified with the inverse metric (or conjugate or dual metric). The inverse metric satisfies a transformation law when the frame f is changed by a matrix A via

The inverse metric transforms contravariantly, or with respect to the inverse of the change of basis matrix A. Whereas the metric itself provides a way to measure the length of (or angle between) vector fields, the inverse metric supplies a means of measuring the length of (or angle between) covector fields; that is, fields of linear functionals.

To see this, suppose that α is a covector field. To wit, for each point p, α determines a function α_p defined on tangent vectors at p so that the following linearity condition holds for all tangent vectors X_p and Y_p, and all real numbers a and b:

${\displaystyle {\alpha }_p\left(a{X}_p+b{Y}_p\right)=a{\alpha }_p\left(X_p\right)+b{\alpha }_p\left(Y_p\right).}$

As p varies, α is assumed to be a smooth function in the sense that

${\displaystyle p\mapsto {\alpha }_p\left(X_p\right)}$

is a smooth function of p for any smooth vector field X.

Any covector field α has components in the basis of vector fields f. These are determined by

${\displaystyle {\alpha }_i=\alpha \left(X_i\right),i=1,2,\dots ,n.}$

Denote the row vector of these components by

${\displaystyle \alpha [\mathbf{f}]=[\begin{array}{cccc}{\alpha }_1& {\alpha }_2& \dots & {\alpha }_n\end{array}].}$

Under a change of f by a matrix A, α[f] changes by the rule

${\displaystyle \alpha [\mathbf{f}A]=\alpha [\mathbf{f}]A.}$

That is, the row vector of components α[f] transforms as a covariant vector.

For a pair α and β of covector fields, define the inverse metric applied to these two covectors by

The resulting definition, although it involves the choice of basis f, does not actually depend on f in an essential way. Indeed, changing basis to fA gives

${\displaystyle \begin{array}{cc}& \alpha [\mathbf{f}A]G[\mathbf{f}A{]}^{-1}\beta [\mathbf{f}A{]}^{\mathsf{T}}\\ =& \left(\alpha [\mathbf{f}]A\right)\left(A^{-1}G[\mathbf{f}{]}^{-1}{\left(A^{-1}\right)}^{\mathsf{T}}\right)\left(A^{\mathsf{T}}\beta [\mathbf{f}{]}^{\mathsf{T}}\right)\\ =& \alpha [\mathbf{f}]G[\mathbf{f}{]}^{-1}\beta [\mathbf{f}{]}^{\mathsf{T}}.\end{array}}$

So that the right-hand side of equation (6) is unaffected by changing the basis f to any other basis fA whatsoever. Consequently, the equation may be assigned a meaning independently of the choice of basis. The entries of the matrix G[f] are denoted by g^ij, where the indices i and j have been raised to indicate the transformation law (5).

Raising and lowering indices

In a basis of vector fields f = (X₁, ..., X_n), any smooth tangent vector field X can be written in the form

for some uniquely determined smooth functions v¹, ..., vⁿ. Upon changing the basis f by a nonsingular matrix A, the coefficients vⁱ change in such a way that equation (7) remains true. That is,

${\displaystyle X=\mathbf{f}\mathbf{A}v[\mathbf{f}\mathbf{A}]=\mathbf{f}v[\mathbf{f}].}$

Consequently, v[fA] = A⁻¹v[f]. In other words, the components of a vector transform contravariantly (that is, inversely or in the opposite way) under a change of basis by the nonsingular matrix A. The contravariance of the components of v[f] is notationally designated by placing the indices of vⁱ[f] in the upper position.

A frame also allows covectors to be expressed in terms of their components. For the basis of vector fields f = (X₁, ..., X_n) define the dual basis to be the linear functionals (θ¹[f], ..., θⁿ[f]) such that

${\displaystyle {\theta }^i[\mathbf{f}](X_j)=\{\begin{array}{ll}1& \mathrm{i}\mathrm{f}i=j\\ 0& \mathrm{i}\mathrm{f}i\ne j.\end{array}}$

That is, θⁱ[f](X_j) = δ_jⁱ, the Kronecker delta. Let

${\displaystyle \theta [\mathbf{f}]=\left[\begin{array}{c}{\theta }^1[\mathbf{f}]\\ {\theta }^2[\mathbf{f}]\\ ⋮\\ {\theta }^n[\mathbf{f}]\end{array}\right].}$

Under a change of basis f ↦ fA for a nonsingular matrix A, θ[f] transforms via

${\displaystyle \theta [\mathbf{f}A]=A^{-1}\theta [\mathbf{f}].}$

Any linear functional α on tangent vectors can be expanded in terms of the dual basis θ

where a[f] denotes the row vector [ a₁[f] ... a_n[f] ]. The components a_i transform when the basis f is replaced by fA in such a way that equation (8) continues to hold. That is,

${\displaystyle \alpha =a[\mathbf{f}A]\theta [\mathbf{f}A]=a[\mathbf{f}]\theta [\mathbf{f}]}$

whence, because θ[fA] = A⁻¹θ[f], it follows that a[fA] = a[f]A. That is, the components a transform covariantly (by the matrix A rather than its inverse). The covariance of the components of a[f] is notationally designated by placing the indices of a_i[f] in the lower position.

Now, the metric tensor gives a means to identify vectors and covectors as follows. Holding X_p fixed, the function

${\displaystyle g_p(X_p,-):Y_p\mapsto g_p(X_p,Y_p)}$

of tangent vector Y_p defines a linear functional on the tangent space at p. This operation takes a vector X_p at a point p and produces a covector g_p(X_p, −). In a basis of vector fields f, if a vector field X has components v[f], then the components of the covector field g(X, −) in the dual basis are given by the entries of the row vector

${\displaystyle a[\mathbf{f}]=v[\mathbf{f}{]}^{\mathsf{T}}G[\mathbf{f}].}$

Under a change of basis f ↦ fA, the right-hand side of this equation transforms via

${\displaystyle v[\mathbf{f}A{]}^{\mathsf{T}}G[\mathbf{f}A]=v[\mathbf{f}{]}^{\mathsf{T}}{\left(A^{-1}\right)}^{\mathsf{T}}{A}^{\mathsf{T}}G[\mathbf{f}]A=v[\mathbf{f}{]}^{\mathsf{T}}G[\mathbf{f}]A}$

so that a[fA] = a[f]A: a transforms covariantly. The operation of associating to the (contravariant) components of a vector field v[f] = [ v¹[f] v²[f] ... vⁿ[f] ]^T the (covariant) components of the covector field a[f] = [ a₁[f] a₂[f] … a_n[f] ], where

${\displaystyle a_i[\mathbf{f}]=\sum _{k=1}^n{v}^k[\mathbf{f}]g_{ki}[\mathbf{f}]}$

is called lowering the index.

To raise the index, one applies the same construction but with the inverse metric instead of the metric. If a[f] = [ a₁[f] a₂[f] ... a_n[f] ] are the components of a covector in the dual basis θ[f], then the column vector

has components which transform contravariantly:

${\displaystyle v[\mathbf{f}A]=A^{-1}v[\mathbf{f}].}$

Consequently, the quantity X = fv[f] does not depend on the choice of basis f in an essential way, and thus defines a vector field on M. The operation (9) associating to the (covariant) components of a covector a[f] the (contravariant) components of a vector v[f] given is called raising the index. In components, (9) is

${\displaystyle v^i[\mathbf{f}]=\sum _{k=1}^n{g}^{ik}[\mathbf{f}]a_k[\mathbf{f}].}$

Induced metric

Let U be an open set in ℝⁿ, and let φ be a continuously differentiable function from U into the Euclidean space ℝ^m, where m > n. The mapping φ is called an immersion if its differential is injective at every point of U. The image of φ is called an immersed submanifold. More specifically, for m = 3, which means that the ambient Euclidean space is ℝ³, the induced metric tensor is called the first fundamental form.

Suppose that φ is an immersion onto the submanifold M ⊂ R^m. The usual Euclidean dot product in ℝ^m is a metric which, when restricted to vectors tangent to M, gives a means for taking the dot product of these tangent vectors. This is called the induced metric.

Suppose that v is a tangent vector at a point of U, say

${\displaystyle v=v^1{\mathbf{e}}_1+\cdots +v^n{\mathbf{e}}_n}$

where e_i are the standard coordinate vectors in ℝⁿ. When φ is applied to U, the vector v goes over to the vector tangent to M given by

${\displaystyle {\phi }_{\ast }(v)=\sum _{i=1}^n\sum _{a=1}^m{v}^i\frac{\mathrm{\partial }{\phi }^a}{\mathrm{\partial }{x}^i}{\mathbf{e}}_a.}$

(This is called the pushforward of v along φ.) Given two such vectors, v and w, the induced metric is defined by

${\displaystyle g(v,w)={\phi }_{\ast }(v)\cdot {\phi }_{\ast }(w).}$

It follows from a straightforward calculation that the matrix of the induced metric in the basis of coordinate vector fields e is given by

${\displaystyle G(\mathbf{e})=(D\phi {)}^{\mathsf{T}}(D\phi )}$

where Dφ is the Jacobian matrix:

${\displaystyle D\phi =\left[\begin{array}{cccc}\frac{\mathrm{\partial }{\phi }^1}{\mathrm{\partial }{x}^1}& \frac{\mathrm{\partial }{\phi }^1}{\mathrm{\partial }{x}^2}& \dots & \frac{\mathrm{\partial }{\phi }^1}{\mathrm{\partial }{x}^n}\\ \frac{\mathrm{\partial }{\phi }^2}{\mathrm{\partial }{x}^1}& \frac{\mathrm{\partial }{\phi }^2}{\mathrm{\partial }{x}^2}& \dots & \frac{\mathrm{\partial }{\phi }^2}{\mathrm{\partial }{x}^n}\\ ⋮& ⋮& \ddots & ⋮\\ \frac{\mathrm{\partial }{\phi }^m}{\mathrm{\partial }{x}^1}& \frac{\mathrm{\partial }{\phi }^m}{\mathrm{\partial }{x}^2}& \dots & \frac{\mathrm{\partial }{\phi }^m}{\mathrm{\partial }{x}^n}\end{array}\right].}$

Intrinsic definitions of a metric

The notion of a metric can be defined intrinsically using the language of fiber bundles and vector bundles. In these terms, a metric tensor is a function

from the fiber product of the tangent bundle of M with itself to R such that the restriction of g to each fiber is a nondegenerate bilinear mapping

${\displaystyle g_p:{\mathrm{T}}_{p}M\times {\mathrm{T}}_{p}M\to \mathbf{R}.}$

The mapping (10) is required to be continuous, and often continuously differentiable, smooth, or real analytic, depending on the case of interest, and whether M can support such a structure.

Metric as a section of a bundle

By the universal property of the tensor product, any bilinear mapping (10) gives rise naturally to a section g_⊗ of the dual of the tensor product bundle of TM with itself

${\displaystyle g_{\otimes }\in \mathrm{\Gamma }\left((\mathrm{T}M\otimes \mathrm{T}M{)}^{\ast }\right).}$

The section g_⊗ is defined on simple elements of TM ⊗ TM by

${\displaystyle g_{\otimes }(v\otimes w)=g(v,w)}$

and is defined on arbitrary elements of TM ⊗ TM by extending linearly to linear combinations of simple elements. The original bilinear form g is symmetric if and only if

${\displaystyle g_{\otimes }\circ \tau =g_{\otimes }}$

where

${\displaystyle \tau :\mathrm{T}M\otimes \mathrm{T}M\stackrel{\cong }{\to }TM\otimes TM}$

is the braiding map.

Since M is finite-dimensional, there is a natural isomorphism

${\displaystyle (\mathrm{T}M\otimes \mathrm{T}M{)}^{\ast }\cong {\mathrm{T}}^{\ast }M\otimes {\mathrm{T}}^{\ast }M,}$

so that g_⊗ is regarded also as a section of the bundle T*M ⊗ T*M of the cotangent bundle T*M with itself. Since g is symmetric as a bilinear mapping, it follows that g_⊗ is a symmetric tensor.

Metric in a vector bundle

More generally, one may speak of a metric in a vector bundle. If E is a vector bundle over a manifold M, then a metric is a mapping

${\displaystyle g:E{\times }_{M}E\to \mathbf{R}}$

from the fiber product of E to R which is bilinear in each fiber:

${\displaystyle g_p:E_p\times E_p\to \mathbf{R}.}$

Using duality as above, a metric is often identified with a section of the tensor product bundle E* ⊗ E*.

Tangent–cotangent isomorphism

The metric tensor gives a natural isomorphism from the tangent bundle to the cotangent bundle, sometimes called the musical isomorphism. This isomorphism is obtained by setting, for each tangent vector X_p ∈ T_pM,

${\displaystyle S_g{X}_p\stackrel{\text{def}}{=}g(X_p,-),}$

the linear functional on T_pM which sends a tangent vector Y_p at p to g_p(X_p,Y_p). That is, in terms of the pairing [−, −] between T_pM and its dual space T^∗
_pM,

${\displaystyle [S_g{X}_p,Y_p]=g_p(X_p,Y_p)}$

for all tangent vectors X_p and Y_p. The mapping S_g is a linear transformation from T_pM to T^∗
_pM. It follows from the definition of non-degeneracy that the kernel of S_g is reduced to zero, and so by the rank–nullity theorem, S_g is a linear isomorphism. Furthermore, S_g is a symmetric linear transformation in the sense that

${\displaystyle [S_g{X}_p,Y_p]=[S_g{Y}_p,X_p]}$

for all tangent vectors X_p and Y_p.

Conversely, any linear isomorphism S : T_pM → T^∗
_pM defines a non-degenerate bilinear form on T_pM by means of

${\displaystyle g_S(X_p,Y_p)=[S{X}_p,Y_p].}$

This bilinear form is symmetric if and only if S is symmetric. There is thus a natural one-to-one correspondence between symmetric bilinear forms on T_pM and symmetric linear isomorphisms of T_pM to the dual T^∗
_pM.

As p varies over M, S_g defines a section of the bundle Hom(TM, T*M) of vector bundle isomorphisms of the tangent bundle to the cotangent bundle. This section has the same smoothness as g: it is continuous, differentiable, smooth, or real-analytic according as g. The mapping S_g, which associates to every vector field on M a covector field on M gives an abstract formulation of "lowering the index" on a vector field. The inverse of S_g is a mapping T*M → TM which, analogously, gives an abstract formulation of "raising the index" on a covector field.

The inverse S⁻¹
_g defines a linear mapping

${\displaystyle S_g^{-1}:{\mathrm{T}}^{\ast }M\to \mathrm{T}M}$

which is nonsingular and symmetric in the sense that

${\displaystyle \left[S_g^{-1}\alpha ,\beta \right]=\left[S_g^{-1}\beta ,\alpha \right]}$

for all covectors α, β. Such a nonsingular symmetric mapping gives rise (by the tensor-hom adjunction) to a map

${\displaystyle {\mathrm{T}}^{\ast }M\otimes {\mathrm{T}}^{\ast }M\to \mathbf{R}}$

or by the double dual isomorphism to a section of the tensor product

${\displaystyle \mathrm{T}M\otimes \mathrm{T}M.}$

Arclength and the line element

Suppose that g is a Riemannian metric on M. In a local coordinate system xⁱ, i = 1, 2, …, n, the metric tensor appears as a matrix, denoted here by G, whose entries are the components g_ij of the metric tensor relative to the coordinate vector fields.

Let γ(t) be a piecewise-differentiable parametric curve in M, for a ≤ t ≤ b. The arclength of the curve is defined by

${\displaystyle L={\int }_a^b\sqrt{\sum _{i,j=1}^n{g}_{ij}(\gamma (t))\left(\frac{d}{dt}{x}^i\circ \gamma (t)\right)\left(\frac{d}{dt}{x}^j\circ \gamma (t)\right)}dt.}$

In connection with this geometrical application, the quadratic differential form

${\displaystyle d{s}^2=\sum _{i,j=1}^n{g}_{ij}(p)d{x}^{i}d{x}^j}$

is called the first fundamental form associated to the metric, while ds is the line element. When ds² is pulled back to the image of a curve in M, it represents the square of the differential with respect to arclength.

For a pseudo-Riemannian metric, the length formula above is not always defined, because the term under the square root may become negative. We generally only define the length of a curve when the quantity under the square root is always of one sign or the other. In this case, define

${\displaystyle L={\int }_a^b\sqrt{\left|\sum _{i,j=1}^n{g}_{ij}(\gamma (t))\left(\frac{d}{dt}{x}^i\circ \gamma (t)\right)\left(\frac{d}{dt}{x}^j\circ \gamma (t)\right)\right|}dt.}$

While these formulas use coordinate expressions, they are in fact independent of the coordinates chosen; they depend only on the metric, and the curve along which the formula is integrated.

The energy, variational principles and geodesics

Given a segment of a curve, another frequently defined quantity is the (kinetic) energy of the curve:

${\displaystyle E=\frac{1}{2}{\int }_a^b\sum _{i,j=1}^n{g}_{ij}(\gamma (t))\left(\frac{d}{dt}{x}^i\circ \gamma (t)\right)\left(\frac{d}{dt}{x}^j\circ \gamma (t)\right)dt.}$

This usage comes from physics, specifically, classical mechanics, where the integral E can be seen to directly correspond to the kinetic energy of a point particle moving on the surface of a manifold. Thus, for example, in Jacobi's formulation of Maupertuis' principle, the metric tensor can be seen to correspond to the mass tensor of a moving particle.

In many cases, whenever a calculation calls for the length to be used, a similar calculation using the energy may be done as well. This often leads to simpler formulas by avoiding the need for the square-root. Thus, for example, the geodesic equations may be obtained by applying variational principles to either the length or the energy. In the latter case, the geodesic equations are seen to arise from the principle of least action: they describe the motion of a "free particle" (a particle feeling no forces) that is confined to move on the manifold, but otherwise moves freely, with constant momentum, within the manifold.

Canonical measure and volume form

In analogy with the case of surfaces, a metric tensor on an n-dimensional paracompact manifold M gives rise to a natural way to measure the n-dimensional volume of subsets of the manifold. The resulting natural positive Borel measure allows one to develop a theory of integrating functions on the manifold by means of the associated Lebesgue integral.

A measure can be defined, by the Riesz representation theorem, by giving a positive linear functional Λ on the space C₀(M) of compactly supported continuous functions on M. More precisely, if M is a manifold with a (pseudo-)Riemannian metric tensor g, then there is a unique positive Borel measure μ_g such that for any coordinate chart (U, φ), $${\displaystyle \mathrm{\Lambda }f={\int }_{U}fd{\mu }_g={\int }_{\phi (U)}f\circ {\phi }^{-1}(x)\sqrt{\left|detg\right|}dx}$$ for all f supported in U. Here det g is the determinant of the matrix formed by the components of the metric tensor in the coordinate chart. That Λ is well-defined on functions supported in coordinate neighborhoods is justified by Jacobian change of variables. It extends to a unique positive linear functional on C₀(M) by means of a partition of unity.

If M is also oriented, then it is possible to define a natural volume form from the metric tensor. In a positively oriented coordinate system (x¹, ..., xⁿ) the volume form is represented as $${\displaystyle \omega =\sqrt{\left|detg\right|}d{x}^1\wedge \cdots \wedge d{x}^n}$$ where the dxⁱ are the coordinate differentials and ∧ denotes the exterior product in the algebra of differential forms. The volume form also gives a way to integrate functions on the manifold, and this geometric integral agrees with the integral obtained by the canonical Borel measure.

Examples

Euclidean metric

The most familiar example is that of elementary Euclidean geometry: the two-dimensional Euclidean metric tensor. In the usual Cartesian (x, y) coordinates, we can write

${\displaystyle g=\left[\begin{array}{cc}1& 0\\ 0& 1\end{array}\right].}$

The length of a curve reduces to the formula:

${\displaystyle L={\int }_a^b\sqrt{(dx{)}^2+(dy{)}^2}.}$

The Euclidean metric in some other common coordinate systems can be written as follows.

Polar coordinates (r, θ):

${\displaystyle \begin{array}{cc}x& =r\cos \theta \\ y& =r\sin \theta \\ J& =\left[\begin{array}{cc}\cos \theta & -r\sin \theta \\ \sin \theta & r\cos \theta \end{array}\right].\end{array}}$

So

${\displaystyle g=J^{\mathsf{T}}J=\left[\begin{array}{cc}{\cos }^2\theta +{\sin }^2\theta & -r\sin \theta \cos \theta +r\sin \theta \cos \theta \\ -r\cos \theta \sin \theta +r\cos \theta \sin \theta & r^2{\sin }^2\theta +r^2{\cos }^2\theta \end{array}\right]=\left[\begin{array}{cc}1& 0\\ 0& r^2\end{array}\right]}$

by trigonometric identities.

In general, in a Cartesian coordinate system xⁱ on a Euclidean space, the partial derivatives ∂ / ∂xⁱ are orthonormal with respect to the Euclidean metric. Thus the metric tensor is the Kronecker delta δ_ij in this coordinate system. The metric tensor with respect to arbitrary (possibly curvilinear) coordinates qⁱ is given by

${\displaystyle g_{ij}=\sum _{kl}{\delta }_{kl}\frac{\mathrm{\partial }{x}^k}{\mathrm{\partial }{q}^i}\frac{\mathrm{\partial }{x}^l}{\mathrm{\partial }{q}^j}=\sum _k\frac{\mathrm{\partial }{x}^k}{\mathrm{\partial }{q}^i}\frac{\mathrm{\partial }{x}^k}{\mathrm{\partial }{q}^j}.}$

The round metric on a sphere

The unit sphere in ℝ³ comes equipped with a natural metric induced from the ambient Euclidean metric, through the process explained in the induced metric section. In standard spherical coordinates (θ, φ), with θ the colatitude, the angle measured from the z-axis, and φ the angle from the x-axis in the xy-plane, the metric takes the form

${\displaystyle g=\left[\begin{array}{cc}1& 0\\ 0& {\sin }^2\theta \end{array}\right].}$

This is usually written in the form

${\displaystyle d{s}^2=d{\theta }^2+{\sin }^2\theta d{\phi }^2.}$

Lorentzian metrics from relativity

In flat Minkowski space (special relativity), with coordinates

${\displaystyle r^{\mu }\to \left(x^0,x^1,x^2,x^3\right)=(ct,x,y,z),}$

the metric is, depending on choice of metric signature,

${\displaystyle g=\left[\begin{array}{cccc}1& 0& 0& 0\\ 0& -1& 0& 0\\ 0& 0& -1& 0\\ 0& 0& 0& -1\end{array}\right]\text{or}g=\left[\begin{array}{cccc}-1& 0& 0& 0\\ 0& 1& 0& 0\\ 0& 0& 1& 0\\ 0& 0& 0& 1\end{array}\right].}$

For a curve with—for example—constant time coordinate, the length formula with this metric reduces to the usual length formula. For a timelike curve, the length formula gives the proper time along the curve.

In this case, the spacetime interval is written as

${\displaystyle d{s}^2=c^{2}d{t}^2-d{x}^2-d{y}^2-d{z}^2=d{r}^{\mu }d{r}_{\mu }=g_{\mu \nu }d{r}^{\mu }d{r}^{\nu }.}$

The Schwarzschild metric describes the spacetime around a spherically symmetric body, such as a planet, or a black hole. With coordinates

${\displaystyle \left(x^0,x^1,x^2,x^3\right)=(ct,r,\theta ,\phi ),}$

we can write the metric as

${\displaystyle g_{\mu \nu }=\left[\begin{array}{cccc}\left(1-\frac{2GM}{r{c}^2}\right)& 0& 0& 0\\ 0& -{\left(1-\frac{2GM}{r{c}^2}\right)}^{-1}& 0& 0\\ 0& 0& -r^2& 0\\ 0& 0& 0& -r^2{\sin }^2\theta \end{array}\right],}$

where G (inside the matrix) is the gravitational constant and M represents the total mass–energy content of the central object.