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 R3\mathbb{R}^3. 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 k1,k2k_1, k_2 — the principal curvatures. It also has orthogonal eigenvectors — the principal directions. Gaussian curvature K=k1k2K = k_1 k_2 and mean curvature H=k1+k22H = \tfrac{k_1+k_2}{2} 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 KK and HH. 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 KK, unlike HH, turns out to be an intrinsic invariant.

Key takeaways
  • At each point pp of a regular surface SS, the shape operator dNpdN_p is a symmetric linear map on the tangent plane TpST_pS.
  • Its eigenvalues k1,k2k_1, k_2 (with k1≥k2k_1 \geq k_2 by convention) are the principal curvatures; the eigenvectors give the principal directions.
  • Gaussian curvature K=k1k2=det⁡(dNp)K = k_1 k_2 = \det(dN_p); mean curvature H=k1+k22=12tr⁡(dNp)H = \frac{k_1+k_2}{2} = \frac{1}{2}\operatorname{tr}(dN_p).
  • In local coordinates with first fundamental form (E,F,G)(E,F,G) and second fundamental form (e,f,g)(e,f,g),
K=eg−f2EG−F2,H=eG−2fF+gE2(EG−F2).K = \frac{eg-f^2}{EG-F^2}, \qquad H = \frac{eG - 2fF + gE}{2(EG-F^2)}.
  • The sign of KK classifies points as elliptic (K>0K>0), hyperbolic (K<0K<0), parabolic (K=0K=0, 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 HH; 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 (Ksphere=1/r2≠0=KplaneK_{\text{sphere}} = 1/r^2 \neq 0 = K_{\text{plane}}), a fact underlying every choice of map projection. The classification of points by the sign of KK (elliptic/hyperbolic/parabolic) also connects directly to the Gauss-Bonnet Theorem, which integrates KK over a closed surface to recover a purely topological invariant, the Euler characteristic.

Ask the tutor: Why does the Theorema Egregium let us conclude KK is intrinsic while HH is not, given that both come from the same shape operator?

DefinitionShape operator, principal curvatures, Gaussian and mean curvature

Let S⊂R3S \subset \mathbb{R}^3 be a regular surface with a chosen unit normal field NN, and let p∈Sp \in S. The shape operator (or Weingarten map) at pp is the linear map

dNp:TpS→TpS,dNp(v)=ddt∣t=0N(α(t)),dN_p : T_pS \to T_pS, \qquad dN_p(v) = \frac{d}{dt}\Big|_{t=0} N(\alpha(t)),

where α\alpha is any curve in SS with α(0)=p\alpha(0) = p, α′(0)=v\alpha'(0) = v. (Because N(α(t))N(\alpha(t)) is unit length, N(α(t))⋅N(α(t))≡1N(\alpha(t))\cdot N(\alpha(t)) \equiv 1; differentiating shows dNp(v)⋅N(p)=0dN_p(v)\cdot N(p) = 0, so dNp(v)dN_p(v) indeed lies in TpST_pS.) The second fundamental form at pp is the associated quadratic form

IIp(v)=−dNp(v)⋅v,v∈TpS,\mathrm{II}_p(v) = -dN_p(v)\cdot v, \qquad v \in T_pS,

which is related to the (symmetric) bilinear form IIp(v,w)=−dNp(v)⋅w\mathrm{II}_p(v,w) = -dN_p(v)\cdot w. Since dNpdN_p is a self-adjoint (symmetric) linear operator on the 2-dimensional inner product space TpST_pS (proved below), it has two real eigenvalues k1(p)≥k2(p)k_1(p) \geq k_2(p), called the principal curvatures at pp, with corresponding orthogonal (or orthonormal, if k1≠k2k_1 \neq k_2) eigenvectors e1,e2∈TpSe_1, e_2 \in T_pS, the principal directions. The Gaussian curvature and mean curvature at pp are

K(p)=k1(p) k2(p)=det⁡(dNp),H(p)=k1(p)+k2(p)2=12tr⁡(dNp).K(p) = k_1(p)\,k_2(p) = \det(dN_p), \qquad H(p) = \frac{k_1(p) + k_2(p)}{2} = \frac{1}{2}\operatorname{tr}(dN_p).

Equivalently, k1,k2k_1, k_2 are the roots of the characteristic polynomial λ2−2Hλ+K=0\lambda^2 - 2H\lambda + K = 0 of dNpdN_p, and k1,k2k_1, k_2 are also the extreme values of the normal curvature kn(v)=IIp(v)/⟨v,v⟩k_n(v) = \mathrm{II}_p(v)/\langle v, v\rangle over unit vectors v∈TpSv \in T_pS.

Intuition

Picture standing at a point on a surface and looking in every possible tangent direction. In each direction vv, the surface bends toward or away from the normal NN with some normal curvature kn(v)k_n(v) — the curvature of the planar curve cut out by the plane through NN and vv. As vv sweeps around the unit circle in the tangent plane, kn(v)k_n(v) oscillates between a maximum and a minimum value. These extreme values are exactly the principal curvatures k1≥k2k_1 \geq k_2, 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), K>0K>0 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), K<0K<0 and the point is hyperbolic. If one principal curvature vanishes, K=0K=0: 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 H≡0H \equiv 0 everywhere, a minimal surface. Unlike KK, mean curvature genuinely depends on how the surface sits in space: reflecting a surface through a plane, or embedding two isometric surfaces differently in R3\mathbb{R}^3, can change HH while KK, remarkably, cannot change at all — this is the content of the Theorema Egregium waiting in the wings.

Figure
Normal curvature kn(θ)k_n(\theta) traces an ellipse of extremes: principal curvatures at perpendicular directions, illustrated for k1=3, k2=−1k_1=3,\ k_2=-1
θ (direction) k_n k₁=3 0 k₂=−1 k_n(θ)=H+(k₁−k₂)/2·cos2θ 0 π/2 π
TheoremSymmetry of the shape operator and existence of principal curvatures

Let S⊂R3S \subset \mathbb{R}^3 be a regular surface, p∈Sp \in S, and NN a unit normal field defined on a neighborhood of pp in SS. Then: 1. The shape operator dNp:TpS→TpSdN_p : T_pS \to T_pS is a self-adjoint linear operator with respect to the first fundamental form; that is,

dNp(v)⋅w=v⋅dNp(w)for all v,w∈TpS.dN_p(v) \cdot w = v \cdot dN_p(w) \quad \text{for all } v, w \in T_pS.

2. Consequently dNpdN_p is diagonalizable over R\mathbb{R}: there exist real eigenvalues k1≥k2k_1 \geq k_2 (the principal curvatures) and an orthonormal basis e1,e2e_1, e_2 of TpST_pS of corresponding eigenvectors (the principal directions), unless dNpdN_p is a scalar multiple of the identity, in which case every direction is principal. 3. For a unit vector v∈TpSv \in T_pS, the normal curvature kn(v)=IIp(v,v)k_n(v) = \mathrm{II}_p(v,v) satisfies

k2≤kn(v)≤k1,k_2 \leq k_n(v) \leq k_1,

with equality kn(v)=k1k_n(v) = k_1 (resp. k2k_2) if and only if vv is a unit eigenvector for k1k_1 (resp. k2k_2).

Proof

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 x:U→S\mathbf{x}: U \to S be a local parametrization near pp, U⊂R2U \subset \mathbb{R}^2 open, with coordinates (u,v)(u,v), and write xu,xv\mathbf{x}_u, \mathbf{x}_v for the coordinate tangent vectors, which form a basis of TqST_qS at each q=x(u,v)q = \mathbf{x}(u,v). It suffices to prove

dN(xu)⋅xv=xu⋅dN(xv),dN(\mathbf{x}_u) \cdot \mathbf{x}_v = \mathbf{x}_u \cdot dN(\mathbf{x}_v),

since {xu,xv}\{\mathbf{x}_u, \mathbf{x}_v\} is a basis and both sides are bilinear in (v,w)(v,w). By definition of dNdN applied to a coordinate curve, dN(xu)=NudN(\mathbf{x}_u) = N_u and dN(xv)=NvdN(\mathbf{x}_v) = N_v (partial derivatives of N∘xN \circ \mathbf{x}). Since NN is normal to SS, we have N⋅xu≡0N \cdot \mathbf{x}_u \equiv 0 and N⋅xv≡0N \cdot \mathbf{x}_v \equiv 0 identically on UU. Differentiate the first identity with respect to vv and the second with respect to uu:

Nv⋅xu+N⋅xuv=0,Nu⋅xv+N⋅xvu=0.N_v \cdot \mathbf{x}_u + N \cdot \mathbf{x}_{uv} = 0, \qquad N_u \cdot \mathbf{x}_v + N \cdot \mathbf{x}_{vu} = 0.

Since x\mathbf{x} is smooth (at least C2C^2), mixed partials commute: xuv=xvu\mathbf{x}_{uv} = \mathbf{x}_{vu}. Subtracting the two displayed equations gives

Nv⋅xu−Nu⋅xv=0,i.e.Nu⋅xv=Nv⋅xu,N_v \cdot \mathbf{x}_u - N_u \cdot \mathbf{x}_v = 0, \quad\text{i.e.}\quad N_u \cdot \mathbf{x}_v = N_v \cdot \mathbf{x}_u,

which is exactly dN(xu)⋅xv=dN(xv)⋅xu=xu⋅dN(xv)dN(\mathbf{x}_u)\cdot \mathbf{x}_v = dN(\mathbf{x}_v)\cdot \mathbf{x}_u = \mathbf{x}_u \cdot dN(\mathbf{x}_v) using commutativity of the dot product. This proves self-adjointness at every point of x(U)\mathbf{x}(U), in particular at pp.

Step 2: Diagonalizability (spectral theorem, dimension 2 case, proved directly). TpST_pS is a 2-dimensional real inner product space (inner product = restriction of the Euclidean dot product). Fix an orthonormal basis {e1′,e2′}\{e_1', e_2'\} of TpST_pS and let AA be the matrix of dNpdN_p in this basis. By Step 1, AA is symmetric: A=(abbc)A = \begin{pmatrix} a & b \\ b & c\end{pmatrix} for real a,b,ca,b,c (the off-diagonal entries agree because self-adjointness with respect to an orthonormal basis is exactly matrix symmetry). The characteristic polynomial is

det⁡(A−λI)=λ2−(a+c)λ+(ac−b2).\det(A - \lambda I) = \lambda^2 - (a+c)\lambda + (ac - b^2).

Its discriminant is

(a+c)2−4(ac−b2)=(a−c)2+4b2≥0,(a+c)^2 - 4(ac-b^2) = (a-c)^2 + 4b^2 \geq 0,

a sum of squares, hence nonnegative. Therefore both roots k1≥k2k_1 \geq k_2 are real. If k1=k2k_1 = k_2, the discriminant vanishes, forcing a=ca = c and b=0b = 0, so A=k1IA = k_1 I and dNp=k1 iddN_p = k_1 \,\mathrm{id}: every nonzero vector is an eigenvector, and any orthonormal basis serves as principal directions. If k1>k2k_1 > k_2, let e1e_1 be a unit eigenvector for k1k_1 (it exists since det⁡(A−k1I)=0\det(A - k_1I) = 0 makes A−k1IA - k_1 I singular, so it has nontrivial kernel; normalize a kernel vector). We claim any vector e2⊥e1e_2 \perp e_1 is an eigenvector for k2k_2. Indeed, by self-adjointness,

dNp(e2)⋅e1=e2⋅dNp(e1)=e2⋅(k1e1)=k1(e2⋅e1)=0,dN_p(e_2) \cdot e_1 = e_2 \cdot dN_p(e_1) = e_2 \cdot (k_1 e_1) = k_1 (e_2 \cdot e_1) = 0,

so dNp(e2)∈TpSdN_p(e_2) \in T_pS is orthogonal to e1e_1, hence a scalar multiple of e2e_2 itself (as TpST_pS is 2-dimensional and {e1,e2}\{e_1,e_2\} is an orthonormal basis): dNp(e2)=μe2dN_p(e_2) = \mu e_2 for some scalar μ\mu. Since {e1,e2}\{e_1,e_2\} diagonalizes dNpdN_p with eigenvalues k1,μk_1, \mu, and the eigenvalues of dNpdN_p are exactly {k1,k2}\{k_1,k_2\} (roots of the characteristic polynomial, which is basis-independent), μ=k2\mu = k_2. This proves e1,e2e_1, e_2 are orthonormal eigenvectors with eigenvalues k1,k2k_1, k_2.

Step 3: Extremal characterization of k1,k2k_1, k_2. Write an arbitrary unit vector as v=cos⁡θ e1+sin⁡θ e2v = \cos\theta\, e_1 + \sin\theta\, e_2 in the eigenbasis from Step 2. Using bilinearity of IIp(v,w)=−dNp(v)⋅w\mathrm{II}_p(v,w) = -dN_p(v)\cdot w and dNp(e1)=k1e1dN_p(e_1) = k_1 e_1, dNp(e2)=k2e2dN_p(e_2) = k_2 e_2, e1⋅e2=0e_1 \cdot e_2 = 0:

kn(v)=IIp(v,v)=−dNp(v)⋅v=−(k1cos⁡θ e1+k2sin⁡θ e2)⋅(cos⁡θ e1+sin⁡θ e2).k_n(v) = \mathrm{II}_p(v,v) = -dN_p(v)\cdot v = -(k_1\cos\theta\, e_1 + k_2 \sin\theta\, e_2)\cdot(\cos\theta\, e_1 + \sin\theta\, e_2).

Wait — sign check: with the convention IIp(v,v)=−dNp(v)⋅v\mathrm{II}_p(v,v) = -dN_p(v)\cdot v, and noting that for a sphere with outward normal dNp=−1riddN_p = -\frac{1}{r}\mathrm{id} (computed directly: N(p)=p/rN(p) = p/r so dNp(v)=v/rdN_p(v) = v/r for vv tangent, giving dNp=1riddN_p = \frac{1}{r}\mathrm{id} for outward-pointing convention issues aside), the formula below is standard once signs are fixed consistently; we record the clean algebraic form:

kn(v)=k1cos⁡2θ+k2sin⁡2θ.k_n(v) = k_1 \cos^2\theta + k_2 \sin^2\theta.

(This is the classical Euler's formula, obtained directly from IIp(v,v)=−dNp(v)⋅v\mathrm{II}_p(v,v) = -dN_p(v)\cdot v and dNp(ei)=kieidN_p(e_i) = k_i e_i together with orthonormality of {e1,e2}\{e_1,e_2\}: −dNp(v)⋅v=−(k1cos⁡θ)2−…-dN_p(v)\cdot v = -(k_1\cos\theta)^2 - \dots — carried out with the sign convention baked into the definition of kik_i as eigenvalues of −dNp-dN_p in some texts and of dNpdN_p in others; throughout this article we fix IIp(v)=−dNp(v)⋅v\mathrm{II}_p(v)=-dN_p(v)\cdot v and kik_i = eigenvalues of dNpdN_p, and Euler's formula reads kn(v)=k1cos⁡2θ+k2sin⁡2θk_n(v) = k_1\cos^2\theta + k_2\sin^2\theta consistently, since kn(v):=IIp(v,v)k_n(v) := \mathrm{II}_p(v,v) evaluated in the eigenbasis of dNpdN_p gives precisely this, term by term, because IIp(ei,ei)=−dNp(ei)⋅ei=−ki\mathrm{II}_p(e_i,e_i) = -dN_p(e_i)\cdot e_i = -k_i would introduce an extra sign — to avoid this bookkeeping trap we instead define kn(v)=IIp(v,v)k_n(v) = \mathrm{II}_p(v,v) directly as an eigenvalue statement: since IIp\mathrm{II}_p and −dNp-dN_p 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 II\mathrm{II} via the metric, i.e. as the eigenvalues of SpS_p where IIp(v,w)=⟨Spv,w⟩\mathrm{II}_p(v,w) = \langle S_p v, w\rangle; concretely Sp=−dNpS_p = -dN_p in the convention with outward normal on a sphere giving positive curvature. We adopt kik_i = eigenvalues of Sp:=−dNpS_p := -dN_p from this point on for sign consistency, matching the definition block's intent that K,H>0K,H>0 for a sphere with outward normal.) Since {e1,e2}\{e_1, e_2\} diagonalizes Sp=−dNpS_p = -dN_p with eigenvalues k1,k2k_1, k_2, and IIp(v,v)=⟨Spv,v⟩\mathrm{II}_p(v,v) = \langle S_p v, v\rangle, the same computation gives cleanly

kn(v)=k1cos⁡2θ+k2sin⁡2θ=k2+(k1−k2)cos⁡2θ.k_n(v) = k_1\cos^2\theta + k_2 \sin^2\theta = k_2 + (k_1 - k_2)\cos^2\theta.

Since k1≥k2k_1 \geq k_2 and 0≤cos⁡2θ≤10 \leq \cos^2\theta \leq 1, this expression lies in [k2,k1][k_2, k_1] for every θ\theta, attaining k1k_1 exactly when cos⁡2θ=1\cos^2\theta = 1 (i.e. v=±e1v = \pm e_1) and k2k_2 exactly when cos⁡2θ=0\cos^2\theta = 0 (i.e. v=±e2v = \pm e_2). This proves part 3. ■\blacksquare

∎

Remark on the sign convention. The proof above surfaces a genuine and universal bookkeeping subtlety: whether one defines principal curvatures via dNpdN_p or via Sp=−dNpS_p = -dN_p is a matter of convention, and different textbooks (do Carmo uses dNpdN_p directly and defines IIp(v)=−⟨dNp(v),v⟩\mathrm{II}_p(v) = -\langle dN_p(v),v\rangle, which makes K,HK,H come out with the sign such that a sphere with inward normal has K>0K>0; with outward normal the signs of HH flip but K=det⁡(dNp)K = \det(dN_p) is unaffected since det⁡(−A)=det⁡(A)\det(-A) = \det(A) in dimension 2). The theorem's content — symmetry, real eigenvalues, orthogonal eigendirections, extremal property — is convention-independent; only the overall sign of HH (never of KK, in dimension 2) depends on the choice of normal.

CorollaryCoordinate formula for KK and HH

Let x(u,v)\mathbf{x}(u,v) be a local parametrization of SS with first fundamental form coefficients E=xu⋅xuE = \mathbf{x}_u\cdot \mathbf{x}_u, F=xu⋅xvF = \mathbf{x}_u \cdot \mathbf{x}_v, G=xv⋅xvG = \mathbf{x}_v \cdot \mathbf{x}_v, and second fundamental form coefficients

e=xuu⋅N,f=xuv⋅N,g=xvv⋅N.e = \mathbf{x}_{uu}\cdot N, \qquad f = \mathbf{x}_{uv}\cdot N, \qquad g = \mathbf{x}_{vv}\cdot N.

Then at every point of x(U)\mathbf{x}(U),

K=eg−f2EG−F2,H=eG−2fF+gE2(EG−F2).K = \frac{eg - f^2}{EG - F^2}, \qquad H = \frac{eG - 2fF + gE}{2(EG - F^2)}.
Proof

Proof technique: express dNdN in the coordinate basis {xu,xv}\{\mathbf{x}_u,\mathbf{x}_v\}, using the Weingarten equations, then take determinant and trace via a change-of-basis (matrix similarity) argument. Write Nu=a11xu+a21xvN_u = a_{11}\mathbf{x}_u + a_{21}\mathbf{x}_v and Nv=a12xu+a22xvN_v = a_{12}\mathbf{x}_u + a_{22}\mathbf{x}_v (the Weingarten equations), so that in the basis {xu,xv}\{\mathbf{x}_u,\mathbf{x}_v\} the shape operator dNdN (extended by dN(xu)=NudN(\mathbf{x}_u)=N_u, dN(xv)=NvdN(\mathbf{x}_v)=N_v) has matrix A=(aij)A = (a_{ij}). From II(xu,xu)=e=−Nu⋅xu\mathrm{II}(\mathbf{x}_u,\mathbf{x}_u) = e = -N_u\cdot \mathbf{x}_u, II(xu,xv)=f=−Nu⋅xv=−Nv⋅xu\mathrm{II}(\mathbf{x}_u,\mathbf{x}_v) = f = -N_u\cdot\mathbf{x}_v = -N_v\cdot\mathbf{x}_u, II(xv,xv)=g=−Nv⋅xv\mathrm{II}(\mathbf{x}_v,\mathbf{x}_v)=g=-N_v\cdot\mathbf{x}_v (the middle equality using the symmetry proved above), and substituting Nu=a11xu+a21xvN_u = a_{11}\mathbf{x}_u + a_{21}\mathbf{x}_v:

−e=Nu⋅xu=a11E+a21F,−f=Nu⋅xv=a11F+a21G,-e = N_u\cdot \mathbf{x}_u = a_{11}E + a_{21}F, \qquad -f = N_u\cdot\mathbf{x}_v = a_{11}F + a_{21}G,
−f=Nv⋅xu=a12E+a22F,−g=Nv⋅xv=a12F+a22G.-f = N_v\cdot \mathbf{x}_u = a_{12}E + a_{22}F, \qquad -g = N_v\cdot\mathbf{x}_v = a_{12}F + a_{22}G.

In matrix form, with I=(EFFG)I = \begin{pmatrix}E&F\\F&G\end{pmatrix}, II=(effg)\mathrm{II} = \begin{pmatrix}e&f\\f&g\end{pmatrix}, these four scalar equations read

−II=ATI,-\mathrm{II} = A^T I,

where A=(aij)A = (a_{ij}) using columns for Nu,NvN_u, N_v coefficients (a standard bookkeeping identity in do Carmo's exposition). Hence

AT=−II I−1,soA=−I−1IIA^T = -\mathrm{II}\, I^{-1}, \qquad \text{so} \qquad A = -I^{-1}\mathrm{II}

(using that II, II\mathrm{II} are symmetric, so (−II I−1)T=−I−1II(-\mathrm{II}\,I^{-1})^T = -I^{-1}\mathrm{II}; I−1I^{-1} exists since det⁡I=EG−F2>0\det I = EG-F^2 >0 by regularity, as xu,xv\mathbf{x}_u,\mathbf{x}_v are linearly independent). By definition (with the sign convention fixed so that principal curvatures are eigenvalues of S=−dNS = -dN), we want det⁡(S)\det(S) and tr⁡(S)\operatorname{tr}(S) where SS has matrix −A-A in the basis {xu,xv}\{\mathbf{x}_u,\mathbf{x}_v\} — but this basis is not orthonormal, so determinant and trace of the matrix in this basis are not directly K,HK,H unless corrected for the change of basis (determinant transforms by conjugation-invariance so det⁡\det 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:

K=det⁡(S)=det⁡(−A)=det⁡(A)=det⁡(I−1)det⁡(II)=eg−f2EG−F2,K = \det(S) = \det(-A) = \det(A) = \det(I^{-1})\det(\mathrm{II}) = \frac{eg-f^2}{EG-F^2},

since det⁡(I−1)=1/det⁡(I)=1/(EG−F2)\det(I^{-1}) = 1/\det(I) = 1/(EG-F^2) and det⁡(−I−1II)=det⁡(I−1II)\det(-I^{-1}\mathrm{II}) = \det(I^{-1}\mathrm{II}) in dimension 2 (as det⁡(−M)=(−1)2det⁡M=det⁡M\det(-M)=(-1)^2\det M = \det M). For the trace, we must be careful: tr⁡\operatorname{tr} of a linear operator equals tr⁡\operatorname{tr} of any matrix representing it in any basis — this is a standard fact of linear algebra (trace is a similarity invariant, tr⁡(P−1MP)=tr⁡(M)\operatorname{tr}(P^{-1}MP)=\operatorname{tr}(M)), so no orthonormality is required. Thus

H=tr⁡(S)⋅12=12tr⁡(−A)=12tr⁡(I−1II).H = \operatorname{tr}(S) \cdot \tfrac12 = \tfrac12 \operatorname{tr}(-A) = \tfrac12\operatorname{tr}(I^{-1}\mathrm{II}).

Compute I−1=1EG−F2(G−F−FE)I^{-1} = \frac{1}{EG-F^2}\begin{pmatrix}G & -F\\-F & E\end{pmatrix}, so

I−1II=1EG−F2(G−F−FE)(effg)=1EG−F2(Ge−FfGf−Fg−Fe+Ef−Ff+Eg).I^{-1}\mathrm{II} = \frac{1}{EG-F^2}\begin{pmatrix}G&-F\\-F&E\end{pmatrix}\begin{pmatrix}e&f\\f&g\end{pmatrix} = \frac{1}{EG-F^2}\begin{pmatrix}Ge-Ff & Gf-Fg\\ -Fe+Ef & -Ff+Eg\end{pmatrix}.

The trace is the sum of diagonal entries:

tr⁡(I−1II)=(Ge−Ff)+(Eg−Ff)EG−F2=Ge−2Ff+EgEG−F2.\operatorname{tr}(I^{-1}\mathrm{II}) = \frac{(Ge - Ff) + (Eg - Ff)}{EG-F^2} = \frac{Ge - 2Ff + Eg}{EG-F^2}.

Therefore

H=12⋅eG−2fF+gEEG−F2,H = \frac{1}{2}\cdot \frac{eG - 2fF + gE}{EG-F^2},

as claimed. ■\blacksquare

∎

Worked examples

Example 1: A torus of revolution. Let 0<r<R0 < r < R and parametrize the torus by

x(u,v)=((R+rcos⁡u)cos⁡v, (R+rcos⁡u)sin⁡v, rsin⁡u),u,v∈[0,2π).\mathbf{x}(u,v) = \big((R + r\cos u)\cos v,\ (R+r\cos u)\sin v,\ r\sin u\big), \qquad u,v \in [0,2\pi).

Here uu is the angle around the small (tube) circle and vv the angle around the big circle; we take R=3R=3, r=1r=1 concretely for a fully numeric check at a specific asymmetric point. Compute the tangent vectors:

xu=(−rsin⁡ucos⁡v, −rsin⁡usin⁡v, rcos⁡u),xv=(−(R+rcos⁡u)sin⁡v, (R+rcos⁡u)cos⁡v, 0).\mathbf{x}_u = (-r\sin u\cos v,\ -r\sin u \sin v,\ r\cos u), \qquad \mathbf{x}_v = (-(R+r\cos u)\sin v,\ (R+r\cos u)\cos v,\ 0).

First fundamental form:

E=xu⋅xu=r2,F=xu⋅xv=0,G=xv⋅xv=(R+rcos⁡u)2.E = \mathbf{x}_u\cdot\mathbf{x}_u = r^2, \qquad F = \mathbf{x}_u\cdot\mathbf{x}_v = 0, \qquad G = \mathbf{x}_v\cdot\mathbf{x}_v = (R+r\cos u)^2.

(F=0F=0 is easily checked: the two vectors have a zz-component of rcos⁡ur\cos u and 00 respectively contributing nothing, and the x,yx,y components form a dot product rsin⁡u(R+rcos⁡u)(cos⁡vsin⁡v−sin⁡vcos⁡v)=0r\sin u (R+r\cos u)(\cos v\sin v - \sin v\cos v) = 0.) The outward unit normal is

N(u,v)=(cos⁡ucos⁡v, cos⁡usin⁡v, sin⁡u)N(u,v) = (\cos u\cos v,\ \cos u \sin v,\ \sin u)

(this is unit length and one checks N⋅xu=N⋅xv=0N\cdot \mathbf{x}_u = N\cdot\mathbf{x}_v=0 directly). Second fundamental form via e=xuu⋅Ne = \mathbf{x}_{uu}\cdot N, etc. Compute

xuu=(−rcos⁡ucos⁡v, −rcos⁡usin⁡v, −rsin⁡u),e=xuu⋅N=−rcos⁡2u−rsin⁡2u=−r.\mathbf{x}_{uu} = (-r\cos u\cos v,\ -r\cos u\sin v,\ -r\sin u), \quad e = \mathbf{x}_{uu}\cdot N = -r\cos^2 u - r\sin^2 u = -r.
xuv=(rsin⁡usin⁡v, −rsin⁡ucos⁡v, 0),f=xuv⋅N=rsin⁡usin⁡vcos⁡ucos⁡v−rsin⁡ucos⁡vcos⁡usin⁡v=0.\mathbf{x}_{uv} = (r\sin u\sin v,\ -r\sin u\cos v,\ 0), \quad f = \mathbf{x}_{uv}\cdot N = r\sin u\sin v\cos u\cos v - r\sin u\cos v\cos u\sin v = 0.
xvv=(−(R+rcos⁡u)cos⁡v, −(R+rcos⁡u)sin⁡v, 0),g=xvv⋅N=−(R+rcos⁡u)cos⁡u.\mathbf{x}_{vv} = (-(R+r\cos u)\cos v,\ -(R+r\cos u)\sin v,\ 0), \quad g = \mathbf{x}_{vv}\cdot N = -(R+r\cos u)\cos u.

Now apply the formulas:

K=eg−f2EG−F2=(−r)(−(R+rcos⁡u)cos⁡u)−0r2(R+rcos⁡u)2=r(R+rcos⁡u)cos⁡ur2(R+rcos⁡u)2=cos⁡ur(R+rcos⁡u).K = \frac{eg-f^2}{EG-F^2} = \frac{(-r)\big(-(R+r\cos u)\cos u\big) - 0}{r^2(R+r\cos u)^2} = \frac{r(R+r\cos u)\cos u}{r^2(R+r\cos u)^2} = \frac{\cos u}{r(R+r\cos u)}.
H=eG−2fF+gE2(EG−F2)=(−r)(R+rcos⁡u)2+0+(−(R+rcos⁡u)cos⁡u)(r2)2 r2(R+rcos⁡u)2=−(R+rcos⁡u)[r(R+rcos⁡u)+r2cos⁡u]2r2(R+rcos⁡u)2.H = \frac{eG - 2fF + gE}{2(EG-F^2)} = \frac{(-r)(R+r\cos u)^2 + 0 + \big(-(R+r\cos u)\cos u\big)(r^2)}{2\, r^2(R+r\cos u)^2} = \frac{-(R+r\cos u)\big[r(R+r\cos u) + r^2\cos u\big]}{2r^2(R+r\cos u)^2}.

Simplify the bracket: r(R+rcos⁡u)+r2cos⁡u=rR+r2cos⁡u+r2cos⁡u=rR+2r2cos⁡u=r(R+2rcos⁡u)r(R+r\cos u) + r^2\cos u = rR + r^2\cos u + r^2 \cos u = rR + 2r^2\cos u = r(R + 2r\cos u). So

H=−(R+rcos⁡u)⋅r(R+2rcos⁡u)2r2(R+rcos⁡u)2=−R+2rcos⁡u2r(R+rcos⁡u).H = \frac{-(R+r\cos u)\cdot r(R+2r\cos u)}{2r^2(R+r\cos u)^2} = -\frac{R+2r\cos u}{2r(R+r\cos u)}.

Numeric check at u=π/3u = \pi/3, R=3R=3, r=1r=1: cos⁡u=1/2\cos u = 1/2, so R+rcos⁡u=3.5R + r\cos u = 3.5, and

K=1/21⋅3.5=17≈0.1429,H=−3+12(3.5)=−47≈−0.5714.K = \frac{1/2}{1\cdot 3.5} = \frac{1}{7} \approx 0.1429, \qquad H = -\frac{3 + 1}{2(3.5)} = -\frac{4}{7}\approx -0.5714.

Check via k1,k2k_1,k_2 solving λ2−2Hλ+K=0\lambda^2 - 2H\lambda + K=0, i.e. λ2+87λ+17=0\lambda^2 + \frac{8}{7}\lambda + \frac17=0: discriminant =6449−47=64−2849=3649= \frac{64}{49} - \frac{4}{7} = \frac{64-28}{49} = \frac{36}{49}, root ⋅=6/7\sqrt{\cdot} = 6/7, so λ=−8/7±6/72=−2/72,−14/72=−17,−1\lambda = \frac{-8/7 \pm 6/7}{2} = \frac{-2/7}{2}, \frac{-14/7}{2} = -\frac17, -1. Indeed k1k2=(−17)(−1)=17=Kk_1k_2 = (-\tfrac17)(-1) = \tfrac17 = K ✓ and 12(k1+k2)=12(−17−1)=12⋅(−87)=−47=H\tfrac12(k_1+k_2) = \tfrac12(-\tfrac17-1) = \tfrac12\cdot(-\tfrac87) = -\tfrac47 = H ✓. At u=π/3u=\pi/3 (outer-ish region since cos⁡u>0\cos u>0), the point is elliptic (K>0K>0), consistent with the torus's outer band curving like a sphere in all directions. At u=2π/3u = 2\pi/3: cos⁡u=−1/2\cos u = -1/2, R+rcos⁡u=2.5R+r\cos u = 2.5, giving K=−1/22.5=−0.2<0K = \frac{-1/2}{2.5} = -0.2 < 0: 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 SS be the graph z=f(x,y)=x22−y23z = f(x,y) = \dfrac{x^2}{2} - \dfrac{y^2}{3}, parametrized by x(x,y)=(x,y,f(x,y))\mathbf{x}(x,y) = (x,y,f(x,y)), and evaluate at the asymmetric point (x,y)=(1, 2)(x,y) = (1,\ 2). Compute derivatives: fx=xf_x = x, fy=−2y3f_y = -\tfrac{2y}{3}, fxx=1f_{xx}=1, fxy=0f_{xy}=0, fyy=−23f_{yy} = -\tfrac23. At (1,2)(1,2): fx=1f_x = 1, fy=−43f_y = -\tfrac43. Tangent vectors: xx=(1,0,fx)=(1,0,1)\mathbf{x}_x = (1,0,f_x) = (1,0,1), xy=(0,1,fy)=(0,1,−43)\mathbf{x}_y = (0,1,f_y) = (0,1,-\tfrac43). First fundamental form:

E=1+fx2=1+1=2,F=fxfy=(1)(−43)=−43,G=1+fy2=1+169=259.E = 1 + f_x^2 = 1+1 = 2, \qquad F = f_xf_y = (1)(-\tfrac43) = -\tfrac43, \qquad G = 1+f_y^2 = 1 + \tfrac{16}{9} = \tfrac{25}{9}.
EG−F2=2⋅259−169=509−169=349.EG - F^2 = 2\cdot\tfrac{25}{9} - \tfrac{16}{9} = \tfrac{50}{9}-\tfrac{16}{9} = \tfrac{34}{9}.

For a graph z=f(x,y)z=f(x,y), the standard normal is N=(−fx,−fy,1)1+fx2+fy2N = \dfrac{(-f_x,-f_y,1)}{\sqrt{1+f_x^2+f_y^2}}, and the second fundamental form coefficients are

e=fxx1+fx2+fy2,f(coef)=fxy1+fx2+fy2,g=fyy1+fx2+fy2.e = \frac{f_{xx}}{\sqrt{1+f_x^2+f_y^2}}, \quad f_{\text{(coef)}} = \frac{f_{xy}}{\sqrt{1+f_x^2+f_y^2}}, \quad g = \frac{f_{yy}}{\sqrt{1+f_x^2+f_y^2}}.

(This is a standard consequence of xxx=(0,0,fxx)\mathbf{x}_{xx}=(0,0,f_{xx}) etc. dotted with NN; we take it as a known formula for graphs, derivable directly from the definitions exactly as in the coordinate corollary above.) At (1,2)(1,2): 1+fx2+fy2=1+1+169=3491+f_x^2+f_y^2 = 1 + 1 + \tfrac{16}{9} = \tfrac{34}{9}, so 1+fx2+fy2=34/3\sqrt{1+f_x^2+f_y^2} = \sqrt{34}/3.

e=134/3=334,fcoef=0,g=−2/334/3=−234.e = \frac{1}{\sqrt{34}/3} = \frac{3}{\sqrt{34}}, \qquad f_{\text{coef}} = 0, \qquad g = \frac{-2/3}{\sqrt{34}/3} = \frac{-2}{\sqrt{34}}.

Now:

K=eg−fcoef2EG−F2=(334)(−234)−034/9=−6/3434/9=−634⋅934=−541156=−27578.K = \frac{eg - f_{\text{coef}}^2}{EG-F^2} = \frac{\left(\tfrac{3}{\sqrt{34}}\right)\left(\tfrac{-2}{\sqrt{34}}\right) - 0}{34/9} = \frac{-6/34}{34/9} = \frac{-6}{34}\cdot\frac{9}{34} = \frac{-54}{1156} = -\frac{27}{578}.

Let's double check numerically: −6/34=−0.176470588-6/34 = -0.176470588; dividing by 34/9=3.7777‾34/9 = 3.777\overline{7} gives −0.176470588/3.77778=−0.046713...-0.176470588/3.77778 = -0.046713.... And −27/578=−0.046713...-27/578 = -0.046713... ✓. So K=−27/578≈−0.0467K = -27/578 \approx -0.0467, confirming a hyperbolic point, exactly as expected for a saddle surface. For HH:

H=eG−2fcoefF+gE2(EG−F2)=(334)(259)−0+(−234)(2)2⋅34/9.H = \frac{eG - 2f_{\text{coef}}F + gE}{2(EG-F^2)} = \frac{\left(\tfrac{3}{\sqrt{34}}\right)\left(\tfrac{25}{9}\right) - 0 + \left(\tfrac{-2}{\sqrt{34}}\right)(2)}{2\cdot 34/9}.

Numerator: 334⋅259=75934=25334\dfrac{3}{\sqrt{34}}\cdot\dfrac{25}{9} = \dfrac{75}{9\sqrt{34}} = \dfrac{25}{3\sqrt{34}}, and −234⋅2=−434=−12334\dfrac{-2}{\sqrt{34}}\cdot 2 = \dfrac{-4}{\sqrt{34}} = \dfrac{-12}{3\sqrt{34}}. Sum: 25−12334=13334\dfrac{25-12}{3\sqrt{34}} = \dfrac{13}{3\sqrt{34}}. Denominator: 2⋅349=6892\cdot \tfrac{34}{9} = \tfrac{68}{9}.

H=13/(334)68/9=13334⋅968=11720434=396834.H = \frac{13/(3\sqrt{34})}{68/9} = \frac{13}{3\sqrt{34}}\cdot\frac{9}{68} = \frac{117}{204\sqrt{34}} = \frac{39}{68\sqrt{34}}.

Numerically: 34≈5.83095\sqrt{34}\approx 5.83095, 6834≈396.50568\sqrt{34}\approx 396.505, so H≈39/396.505≈0.09836H \approx 39/396.505 \approx 0.09836.

Consistency check via k1+k2=2H≈0.19672k_1 + k_2 = 2H \approx 0.19672 and k1k2=K≈−0.046713k_1k_2 = K \approx -0.046713: solving λ2−0.19672λ−0.046713=0\lambda^2 - 0.19672\lambda - 0.046713=0 gives discriminant 0.196722+4(0.046713)=0.038699+0.186851=0.2255510.19672^2 + 4(0.046713) = 0.038699+0.186851=0.225551, ⋅≈0.47493\sqrt{\cdot}\approx 0.47493, roots ≈0.19672±0.474932\approx \frac{0.19672\pm 0.47493}{2}, i.e. k1≈0.33582k_1\approx 0.33582, k2≈−0.13910k_2\approx -0.13910. Check product: 0.33582×(−0.13910)≈−0.0467150.33582\times(-0.13910)\approx -0.046715 ✓ (matches KK to rounding), and sum ≈0.19672=2H\approx 0.19672 = 2H ✓. Opposite signs confirm the hyperbolic (saddle) point, matching the geometric picture of z=x2/2−y2/3z=x^2/2 - y^2/3 curving upward in xx and downward in yy.

Counterexamplewhy symmetry of the shape operator is needed for real eigenvalues

Suppose we drop the hypothesis that AA is symmetric and instead consider an arbitrary 2×22\times 2 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

A=(0−110),A = \begin{pmatrix} 0 & -1 \\ 1 & 0 \end{pmatrix},

representing a 90°90° rotation on R2\mathbb{R}^2. Its characteristic polynomial is λ2−0⋅λ+1=λ2+1\lambda^2 - 0\cdot\lambda + 1 = \lambda^2+1, with discriminant 0−4(1)=−4<00 - 4(1) = -4 < 0. The eigenvalues are ±i\pm i, 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 NN, or on a non-orientable or singular "surface" where NN is not smoothly well-defined so that Nu⋅xv≠Nv⋅xuN_u\cdot\mathbf{x}_v \ne N_v\cdot\mathbf{x}_u — 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 kn(v)k_n(v) 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 xuv=xvu\mathbf{x}_{uv} = \mathbf{x}_{vu}, which requires the parametrization to be at least C2C^2. If x\mathbf{x} were merely C1C^1 (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 dNpdN_p symmetric.

Scope, edge cases & common traps

SituationWhat happensWhy
Umbilic point (k1=k2k_1=k_2)Every direction is principal; K=k12≥0K=k_1^2\ge 0 actually always ≥0\geq 0 at umbilicsShape operator is a scalar multiple of the identity there
Planar point (k1=k2=0k_1=k_2=0)K=H=0K=H=0, shape operator is the zero mapSecond fundamental form vanishes identically at that point
Parabolic point (K=0K=0, not planar)Exactly one ki=0k_i=0; occurs on developable surfaces like cylinders/conesShape operator singular but nonzero
Choice of unit normal NN vs. −N-NKK unchanged; HH changes signdet⁡(−A)=det⁡A\det(-A)=\det A in dimension 2, but tr⁡(−A)=−tr⁡A\operatorname{tr}(-A) = -\operatorname{tr}A
Non-orientable surface (e.g. Möbius band)No globally consistent NN, so HH is only locally/sign-ambiguously definedKK, being intrinsic, is still globally well-defined (Theorema Egregium) but HH needs an orientation choice
Reparametrization of the surfaceK,H,k1,k2K, H, k_1, k_2 all unchangedThey are properties of the point p∈Sp\in S and the map dNpdN_p, not of coordinates

The mathematician behind it

Origins · 1 minCarl Friedrich Gauss and how this was discovered
CF
Carl Friedrich Gauss
1777–1855 · Göttingen, geodetic surveying and the founding of intrinsic differential geometry

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.

History
- 1827 — Gauss publishes Disquisitiones generales circa superficies curvas, defining Gaussian curvature via the spherical (Gauss) map and proving the Theorema Egregium.
- 1850s — Bonnet and others develop the second fundamental form and mean curvature systematically, connecting HH to minimal surfaces and Plateau's soap-film problem.
- 1868 — Riemann's posthumously published habilitation lecture generalizes curvature to arbitrary dimensions, founding Riemannian geometry from Gauss's intrinsic viewpoint.
- 1900s–1930s — Global consequences (Gauss–Bonnet, rigidity theorems) are proved connecting local curvature to global topology.
- 20th–21st century — Mean curvature flow (Huisken and others) and Gaussian curvature bounds become central tools in geometric analysis, general relativity, and computer graphics.
Why are k1k_1 and k2k_2 always real numbers, never complex?

Because the shape operator dNpdN_p 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 C2C^2 parametrization. Any symmetric real matrix has characteristic polynomial with discriminant equal to a sum of squares — concretely (a−c)2+4b2(a-c)^2+4b^2 for a 2×22\times 2 symmetric matrix (abbc)\begin{pmatrix}a&b\\b&c\end{pmatrix} — 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 k2k_2 and k1k_1 as the direction sweeps around. Gaussian curvature K=k1k2K=k_1k_2 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 KK classify the local shape of the surface?

Because K=k1k2K=k_1k_2 is the product of the two extreme normal curvatures, and a product of two reals is positive iff they share a sign. If k1,k2k_1,k_2 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 R3\mathbb{R}^3 — for instance, a flat sheet of paper (H=0H=0 when lying flat) rolled into a cylinder acquires H=1/(2r)≠0H = 1/(2r) \neq 0, even though rolling it preserves all intrinsic distances. Gaussian curvature, by contrast, is invariant here (K=0K=0 for both the flat sheet and the cylinder), which is the essential content of the Theorema Egregium: KK is intrinsic, HH is not.

What is a minimal surface, and how does it relate to HH?

A minimal surface is one with mean curvature identically zero, H≡0H\equiv 0, 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 K≡0K\equiv 0 (indeed the catenoid has K<0K<0 everywhere except along its central circle), showing H=0H=0 is compatible with a wide range of Gaussian curvature behavior.

How do principal curvatures relate to the eigenvalues of the "shape operator matrix" I−1III^{-1}\mathrm{II} used in computations?

When computing in a coordinate parametrization, one often forms the matrix I−1III^{-1}\mathrm{II} (first fundamental form inverse times second fundamental form) in the coordinate basis {xu,xv}\{\mathbf{x}_u,\mathbf{x}_v\}. This matrix represents the shape operator in a (generally non-orthonormal) basis, so it is not symmetric as a literal array of numbers unless E=GE=G and F=0F=0. However its eigenvalues are still exactly k1,k2k_1,k_2 (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 gg, ∫SK dA=2π(2−2g)\int_S K\,dA = 2\pi(2-2g), which is strictly positive for a sphere (g=0g=0) and can be negative for higher genus, but on any compact surface without boundary there must exist at least one point with K≥0K\geq 0 — 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 K<0K<0 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.

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Where this leads