Gaussian and Mean Curvature
How curved is a surface at a point? Can a single number capture it? A sphere curves the same way in every direction. A saddle curves oppositely in perpendicular directions. A cylinder curves in one direction but not the other. Principal, Gaussian, and mean curvature are the precise numerical answers to "how curved." They are built directly from the Second Fundamental Form and the shape operator. This operator packages a surface's bending into a single symmetric linear map at each point. This matters because curvature is the bridge between two views of a surface. One is the extrinsic picture — how it sits and bends in . The other is its intrinsic geometry, the geometry an inhabitant of the surface could measure without ever leaving it. Gauss's astonishing discovery, the Theorema Egregium, concerns one particular combination of the two principal curvatures: their product. This product is secretly intrinsic. It depends only on the first fundamental form, not on the embedding. Mean curvature, by contrast, is stubbornly extrinsic. It governs soap films, minimal surfaces, and the physics of surface tension. The big picture is this: at each point of a regular surface, the shape operator (also called the Weingarten map) is a symmetric linear operator on the tangent plane. Being symmetric, it is diagonalizable with real eigenvalues — the principal curvatures. It also has orthogonal eigenvectors — the principal directions. Gaussian curvature and mean curvature are the elementary symmetric functions of these eigenvalues. They correspond exactly to the determinant and trace (up to normalization) of the shape operator. This article develops principal curvatures rigorously from the second fundamental form. It proves the diagonalization theorem underlying their existence. It derives the standard coordinate formulas for and . It also works two fully computed examples — a torus and a hyperbolic paraboloid. These were chosen precisely because they are asymmetric enough to expose every sign and factor. It closes by previewing why , unlike , turns out to be an intrinsic invariant.
- At each point of a regular surface , the shape operator is a symmetric linear map on the tangent plane .
- Its eigenvalues (with by convention) are the principal curvatures; the eigenvectors give the principal directions.
- Gaussian curvature ; mean curvature .
- In local coordinates with first fundamental form and second fundamental form ,
- The sign of classifies points as elliptic (), hyperbolic (), parabolic (, shape operator singular but nonzero), or planar (shape operator zero).
- Key idea: Gaussian and mean curvature are, respectively, the determinant and (half the) trace of the shape operator, and this spectral viewpoint is what makes both quantities well-defined, coordinate-free, and computable.
Where this lives today
Gaussian curvature's intrinsic nature (foreshadowed here, proved in the Theorema Egregium) is the seed of Riemannian geometry, which underlies general relativity's description of spacetime curvature via the Riemann Curvature Tensor. Mean curvature governs minimal surfaces and soap films through the Young–Laplace equation, where pressure difference across a membrane is proportional to ; mean curvature flow, in which a surface evolves in the direction that most decreases area, is a fundamental tool in geometric analysis and has been used to attack the Poincaré conjecture and to model image processing and denoising. In computer graphics and geometry processing, discrete curvature estimates drive mesh smoothing, remeshing, and fairing algorithms. In cartography, Gauss's theorem explains rigorously why no flat map can perfectly preserve distances on a sphere (), a fact underlying every choice of map projection. The classification of points by the sign of (elliptic/hyperbolic/parabolic) also connects directly to the Gauss-Bonnet Theorem, which integrates over a closed surface to recover a purely topological invariant, the Euler characteristic.
Ask the tutor: Why does the Theorema Egregium let us conclude is intrinsic while is not, given that both come from the same shape operator?
Let be a regular surface with a chosen unit normal field , and let . The shape operator (or Weingarten map) at is the linear map
where is any curve in with , . (Because is unit length, ; differentiating shows , so indeed lies in .) The second fundamental form at is the associated quadratic form
which is related to the (symmetric) bilinear form . Since is a self-adjoint (symmetric) linear operator on the 2-dimensional inner product space (proved below), it has two real eigenvalues , called the principal curvatures at , with corresponding orthogonal (or orthonormal, if ) eigenvectors , the principal directions. The Gaussian curvature and mean curvature at are
Equivalently, are the roots of the characteristic polynomial of , and are also the extreme values of the normal curvature over unit vectors .
Intuition
Picture standing at a point on a surface and looking in every possible tangent direction. In each direction , the surface bends toward or away from the normal with some normal curvature — the curvature of the planar curve cut out by the plane through and . As sweeps around the unit circle in the tangent plane, oscillates between a maximum and a minimum value. These extreme values are exactly the principal curvatures , and they are achieved in perpendicular directions — a fact that is not obvious a priori but follows from the spectral theorem applied to the symmetric shape operator. Gaussian curvature multiplies these two extremes together. If both principal curvatures have the same sign (the surface bends the same way in every direction, like a sphere or the inside of a bowl), and the point is called elliptic. If they have opposite signs (the surface bends up in one direction and down in the perpendicular direction, like a saddle or the middle of a torus), and the point is hyperbolic. If one principal curvature vanishes, : this is a parabolic point (e.g. anywhere on a cylinder), unless both vanish, giving a planar point (e.g. a flat plane, or the flat point at the "waist" of certain surfaces of revolution). Mean curvature is the average of the two extremes. It measures the surface's tendency to feel a net normal force from surface tension — a physical soap film with no pressure difference across it satisfies everywhere, a minimal surface. Unlike , mean curvature genuinely depends on how the surface sits in space: reflecting a surface through a plane, or embedding two isometric surfaces differently in , can change while , remarkably, cannot change at all — this is the content of the Theorema Egregium waiting in the wings.
Let be a regular surface, , and a unit normal field defined on a neighborhood of in . Then: 1. The shape operator is a self-adjoint linear operator with respect to the first fundamental form; that is,
2. Consequently is diagonalizable over : there exist real eigenvalues (the principal curvatures) and an orthonormal basis of of corresponding eigenvectors (the principal directions), unless is a scalar multiple of the identity, in which case every direction is principal. 3. For a unit vector , the normal curvature satisfies
with equality (resp. ) if and only if is a unit eigenvector for (resp. ).
Proof technique: local coordinate computation to establish self-adjointness, followed by the spectral theorem for symmetric operators on an inner product space, followed by a Lagrange-multiplier (constrained extremum) argument for part 3.
Step 1: Self-adjointness. Let be a local parametrization near , open, with coordinates , and write for the coordinate tangent vectors, which form a basis of at each . It suffices to prove
since is a basis and both sides are bilinear in . By definition of applied to a coordinate curve, and (partial derivatives of ). Since is normal to , we have and identically on . Differentiate the first identity with respect to and the second with respect to :
Since is smooth (at least ), mixed partials commute: . Subtracting the two displayed equations gives
which is exactly using commutativity of the dot product. This proves self-adjointness at every point of , in particular at .
Step 2: Diagonalizability (spectral theorem, dimension 2 case, proved directly). is a 2-dimensional real inner product space (inner product = restriction of the Euclidean dot product). Fix an orthonormal basis of and let be the matrix of in this basis. By Step 1, is symmetric: for real (the off-diagonal entries agree because self-adjointness with respect to an orthonormal basis is exactly matrix symmetry). The characteristic polynomial is
Its discriminant is
a sum of squares, hence nonnegative. Therefore both roots are real. If , the discriminant vanishes, forcing and , so and : every nonzero vector is an eigenvector, and any orthonormal basis serves as principal directions. If , let be a unit eigenvector for (it exists since makes singular, so it has nontrivial kernel; normalize a kernel vector). We claim any vector is an eigenvector for . Indeed, by self-adjointness,
so is orthogonal to , hence a scalar multiple of itself (as is 2-dimensional and is an orthonormal basis): for some scalar . Since diagonalizes with eigenvalues , and the eigenvalues of are exactly (roots of the characteristic polynomial, which is basis-independent), . This proves are orthonormal eigenvectors with eigenvalues .
Step 3: Extremal characterization of . Write an arbitrary unit vector as in the eigenbasis from Step 2. Using bilinearity of and , , :
Wait — sign check: with the convention , and noting that for a sphere with outward normal (computed directly: so for tangent, giving for outward-pointing convention issues aside), the formula below is standard once signs are fixed consistently; we record the clean algebraic form:
(This is the classical Euler's formula, obtained directly from and together with orthonormality of : — carried out with the sign convention baked into the definition of as eigenvalues of in some texts and of in others; throughout this article we fix and = eigenvalues of , and Euler's formula reads consistently, since evaluated in the eigenbasis of gives precisely this, term by term, because would introduce an extra sign — to avoid this bookkeeping trap we instead define directly as an eigenvalue statement: since and share eigenvectors with eigenvalues of opposite sign in a naive reading, the standard and universally adopted convention in the literature is to define principal curvatures as the eigenvalues of the shape operator associated to via the metric, i.e. as the eigenvalues of where ; concretely in the convention with outward normal on a sphere giving positive curvature. We adopt = eigenvalues of from this point on for sign consistency, matching the definition block's intent that for a sphere with outward normal.) Since diagonalizes with eigenvalues , and , the same computation gives cleanly
Since and , this expression lies in for every , attaining exactly when (i.e. ) and exactly when (i.e. ). This proves part 3.
∎Remark on the sign convention. The proof above surfaces a genuine and universal bookkeeping subtlety: whether one defines principal curvatures via or via is a matter of convention, and different textbooks (do Carmo uses directly and defines , which makes come out with the sign such that a sphere with inward normal has ; with outward normal the signs of flip but is unaffected since in dimension 2). The theorem's content — symmetry, real eigenvalues, orthogonal eigendirections, extremal property — is convention-independent; only the overall sign of (never of , in dimension 2) depends on the choice of normal.
Let be a local parametrization of with first fundamental form coefficients , , , and second fundamental form coefficients
Then at every point of ,
Proof technique: express in the coordinate basis , using the Weingarten equations, then take determinant and trace via a change-of-basis (matrix similarity) argument. Write and (the Weingarten equations), so that in the basis the shape operator (extended by , ) has matrix . From , , (the middle equality using the symmetry proved above), and substituting :
In matrix form, with , , these four scalar equations read
where using columns for coefficients (a standard bookkeeping identity in do Carmo's exposition). Hence
(using that , are symmetric, so ; exists since by regularity, as are linearly independent). By definition (with the sign convention fixed so that principal curvatures are eigenvalues of ), we want and where has matrix in the basis — but this basis is not orthonormal, so determinant and trace of the matrix in this basis are not directly unless corrected for the change of basis (determinant transforms by conjugation-invariance so of the matrix representative is basis-independent regardless of orthonormality; trace is likewise conjugation-invariant, so trace of any matrix representative of a linear operator equals the operator's trace, no orthonormality needed). Concretely:
since and in dimension 2 (as ). For the trace, we must be careful: of a linear operator equals of any matrix representing it in any basis — this is a standard fact of linear algebra (trace is a similarity invariant, ), so no orthonormality is required. Thus
Compute , so
The trace is the sum of diagonal entries:
Therefore
as claimed.
∎Worked examples
Example 1: A torus of revolution. Let and parametrize the torus by
Here is the angle around the small (tube) circle and the angle around the big circle; we take , concretely for a fully numeric check at a specific asymmetric point. Compute the tangent vectors:
First fundamental form:
( is easily checked: the two vectors have a -component of and respectively contributing nothing, and the components form a dot product .) The outward unit normal is
(this is unit length and one checks directly). Second fundamental form via , etc. Compute
Now apply the formulas:
Simplify the bracket: . So
Numeric check at , , : , so , and
Check via solving , i.e. : discriminant , root , so . Indeed ✓ and ✓. At (outer-ish region since ), the point is elliptic (), consistent with the torus's outer band curving like a sphere in all directions. At : , , giving : a hyperbolic point on the inner band, as expected, since the tube curves one way while wrapping the other way around the hole.
Example 2: A hyperbolic paraboloid (non-symmetric scaling). Let be the graph , parametrized by , and evaluate at the asymmetric point . Compute derivatives: , , , , . At : , . Tangent vectors: , . First fundamental form:
For a graph , the standard normal is , and the second fundamental form coefficients are
(This is a standard consequence of etc. dotted with ; we take it as a known formula for graphs, derivable directly from the definitions exactly as in the coordinate corollary above.) At : , so .
Now:
Let's double check numerically: ; dividing by gives . And ✓. So , confirming a hyperbolic point, exactly as expected for a saddle surface. For :
Numerator: , and . Sum: . Denominator: .
Numerically: , , so .
Consistency check via and : solving gives discriminant , , roots , i.e. , . Check product: ✓ (matches to rounding), and sum ✓. Opposite signs confirm the hyperbolic (saddle) point, matching the geometric picture of curving upward in and downward in .
Suppose we drop the hypothesis that is symmetric and instead consider an arbitrary real linear operator, to see why the argument genuinely needs Step 1 of the theorem (self-adjointness) rather than merely "some linear map on the tangent plane." Take the non-symmetric matrix
representing a rotation on . Its characteristic polynomial is , with discriminant . The eigenvalues are , not real. If the shape operator failed to be symmetric — which would happen, for instance, if one attempted to define an analogous "curvature operator" using a non-normal vector field instead of the genuine surface normal , or on a non-orientable or singular "surface" where is not smoothly well-defined so that — then there would be no guarantee of real eigenvalues at all, and hence no real principal curvatures, no real Gaussian or mean curvature as defined via eigenvalues, and Euler's formula (part 3 of the theorem) would fail to make sense, since could not be bounded between real "extremes" that don't exist. Concretely, the proof of self-adjointness relied crucially on equality of mixed partial derivatives , which requires the parametrization to be at least . If were merely (a hypothesis implicitly needed but easy to overlook), this step fails and self-adjointness — hence real eigenvalues, hence the entire edifice of principal curvatures — is no longer guaranteed. This shows the smoothness hypothesis on the surface is not a technicality: it is exactly what makes symmetric.
Scope, edge cases & common traps
| Situation | What happens | Why |
|---|---|---|
| Umbilic point () | Every direction is principal; actually always at umbilics | Shape operator is a scalar multiple of the identity there |
| Planar point () | , shape operator is the zero map | Second fundamental form vanishes identically at that point |
| Parabolic point (, not planar) | Exactly one ; occurs on developable surfaces like cylinders/cones | Shape operator singular but nonzero |
| Choice of unit normal vs. | unchanged; changes sign | in dimension 2, but |
| Non-orientable surface (e.g. Möbius band) | No globally consistent , so is only locally/sign-ambiguously defined | , being intrinsic, is still globally well-defined (Theorema Egregium) but needs an orientation choice |
| Reparametrization of the surface | all unchanged | They are properties of the point and the map , not of coordinates |
The mathematician behind it
Origins · 1 minCarl Friedrich Gauss and how this was discovered
Gauss developed the theory of curved surfaces largely while directing the geodetic survey of the Kingdom of Hanover in the 1820s, a practical project measuring the Earth's true shape via triangulation over hilly terrain. This hands-on engagement with real, non-flat surfaces led him to his 1827 treatise Disquisitiones generales circa superficies curvas, in which he introduced the curvature that now bears his name and proved — to his own evident astonishment, he called it "egregium" (outstanding, remarkable) — that it is an intrinsic quantity, measurable by an inhabitant of the surface using only lengths and angles, with no reference to any ambient space.
Why are and always real numbers, never complex?
Because the shape operator is symmetric (self-adjoint) with respect to the inner product on the tangent plane, a fact proved directly from equality of mixed partial derivatives of a parametrization. Any symmetric real matrix has characteristic polynomial with discriminant equal to a sum of squares — concretely for a symmetric matrix — which is automatically nonnegative. Nonnegative discriminant guarantees two real roots (possibly equal). This is a small instance of the general spectral theorem for symmetric operators, and it is precisely why "curvature" can be reported as ordinary real numbers rather than complex or undefined quantities.
Is Gaussian curvature the same thing as "curvature" in the sense of a plane curve's curvature?
No, though they are related by Euler's formula. A plane curve has a single real-valued curvature at each point, describing how fast its tangent turns. A surface point instead has infinitely many normal curvatures, one for each tangent direction, ranging continuously between and as the direction sweeps around. Gaussian curvature is a single number built from the two extremes of this whole family, not a curvature of any one curve on the surface (although it does equal the normal curvature times something specific only at umbilic points, where all normal curvatures coincide).
Why does the sign of classify the local shape of the surface?
Because is the product of the two extreme normal curvatures, and a product of two reals is positive iff they share a sign. If have the same sign, the surface bends toward the same side of its tangent plane in every direction (elliptic, locally convex, like a sphere). If they have opposite signs, it bends to opposite sides in perpendicular directions (hyperbolic, saddle-shaped). If one vanishes, the surface is "flat" in exactly one direction (parabolic), and if both vanish it's flat to second order in every direction (planar). This local classification is purely algebraic, following straight from the eigenvalue picture.
Does mean curvature depend on the surface's intrinsic (metric) geometry, or only on how it's embedded?
Mean curvature genuinely depends on the embedding. Two isometric surfaces (identical intrinsic geometry, same distances and angles) can have different mean curvatures if embedded differently in — for instance, a flat sheet of paper ( when lying flat) rolled into a cylinder acquires , even though rolling it preserves all intrinsic distances. Gaussian curvature, by contrast, is invariant here ( for both the flat sheet and the cylinder), which is the essential content of the Theorema Egregium: is intrinsic, is not.
What is a minimal surface, and how does it relate to ?
A minimal surface is one with mean curvature identically zero, , at every point. The name comes from the calculus of variations: such surfaces are critical points (often, but not always, local area minimizers) of the surface area functional among surfaces spanning a fixed boundary curve, which is exactly the mathematical model of a soap film spanning a wire frame with no pressure difference across it. Examples include the plane, the catenoid, and the helicoid; none of these need have (indeed the catenoid has everywhere except along its central circle), showing is compatible with a wide range of Gaussian curvature behavior.
How do principal curvatures relate to the eigenvalues of the "shape operator matrix" used in computations?
When computing in a coordinate parametrization, one often forms the matrix (first fundamental form inverse times second fundamental form) in the coordinate basis . This matrix represents the shape operator in a (generally non-orthonormal) basis, so it is not symmetric as a literal array of numbers unless and . However its eigenvalues are still exactly (up to the sign convention chosen), because eigenvalues, determinant, and trace of a linear operator do not depend on which basis is used to represent it as a matrix — only genuine matrix symmetry (which requires an orthonormal basis) is basis-dependent, not the operator's spectrum.
Can Gaussian curvature be negative everywhere on a closed (compact, boundaryless) surface?
No. This is a consequence of the Gauss–Bonnet theorem: for a closed orientable surface of genus , , which is strictly positive for a sphere () and can be negative for higher genus, but on any compact surface without boundary there must exist at least one point with — indeed a point of maximal distance from some origin (or the point of maximum "outward bulge") is elliptic, by a direct argument comparing the surface locally to a supporting sphere. So everywhere is impossible on a closed surface, though it is entirely possible on complete non-compact surfaces like the hyperbolic plane model or a catenoid.