Diffusion on Curved Spaces
The animation above shows a sealed, rigid container whose walls curve inward and outward; inside, a swarm of particles begins concentrated near a single point and diffuses outward. The container is a closed 3-manifold (a deformed sphere), and its curvature is not decorative. It determines how the swarm spreads. Near the poles of the container, where the wall curves sharply, the particles are reflected at steeper angles than on the flatter equatorial band. The gold-to-blue colour encodes the heat kernel value evaluated at each particle's position: gold is high concentration, deep blue is low.
That formula is the heat kernel in flat space . On a curved manifold it is only an approximation; the true kernel acquires corrections at every order in whose coefficients are curvature invariants. The first such correction, which appears at order , is the scalar curvature .
This post derives that result from first principles. We begin with the classical heat equation on and its Gaussian fundamental solution (§1). We then build the Riemannian machinery (metric tensor, covariant gradient, divergence, and Laplace–Beltrami operator) from the ground up (§2). The heat equation on a Riemannian manifold has its own fundamental solution, derived through the parametrix construction (§3). We close with the spectral representation of the heat kernel and Weyl's law (§4).
Sign convention. The Laplace–Beltrami operator is defined as , which is negative semi-definite on functions. The heat equation is . The competing probabilistic convention replaces this by , matching the generator of Brownian motion; the two conventions differ only by the substitution throughout and produce kernels related by .
1. The Heat Equation on
1.1. Derivation from conservation
Let be the concentration of a diffusing substance. Fick's first law [1] states that diffusive flux opposes the concentration gradient:
Conservation of mass over any smooth bounded region requires
where is the outward unit normal to . Applying the divergence theorem to the right side of [eq:conservation] and substituting [eq:fick]:
Since is arbitrary and all integrands are continuous, we conclude:
1.2. Solution via the Fourier transform
For the Fourier transform and its inverse are
Differentiation in becomes multiplication in :
so applying [eq:fourier-deriv] twice in each coordinate and summing:
Taking the Fourier transform of [eq:heat-flat] in and applying [eq:fourier-laplacian]:
This is a first-order linear ODE in for each fixed , with solution
By the convolution theorem, this product in frequency space corresponds to convolution in physical space:
1.3. The Gaussian heat kernel
The inverse Fourier transform of factors over coordinates, reducing to a one-dimensional integral. Completing the square:
where and the contour shift is justified by Cauchy's theorem. Multiplying over all coordinates gives
By [eq:conv-soln], the solution to [eq:heat-flat] is , or written symmetrically:
The visualization below shows in one dimension for several values of : the bell flattens and widens as .
The kernel [eq:flat-kernel] satisfies, for all and :
- Positivity: .
- Mass conservation: .
- Symmetry: .
- Semigroup: .
- Approximate identity: for all , uniformly on compact sets.
Proof. (1) is immediate from the definition.
Proof of (2). Substitute , so . Then
where the last step uses the standard Gaussian integral , which factors as a product of one-dimensional integrals [2].
(3) is immediate from .
Proof of (4). Write . The prefactors contribute . The combined exponent is
Expanding and collecting powers of :
The coefficient of is , and the optimal point in is
Completing the square, the combined exponent equals
where the residual is independent of (verified by expanding both sides and cancelling). The Gaussian integral over now factors:
Combining the prefactors and residual:
(5) follows from (2) and the standard theory of approximate identities [2, Ch. 5]. □
The semigroup property has a direct visual interpretation. Hold the total time fixed and vary the split . The blue kernel and the gold kernel change shape continuously, yet their convolution—the muted silver curve —is constant throughout.
2. The Riemannian Setup
2.1. Metric tensor and volume form
A Riemannian metric on a smooth -manifold is a smooth, symmetric, positive-definite covariant 2-tensor field . In local coordinates it reads
with Einstein summation throughout. The matrix is symmetric positive definite at every point [3, Ch. 2].
Write for the determinant of the metric matrix. The Riemannian volume form, the natural measure on , is
This is independent of the chart: under a coordinate change the Jacobian determinant from the transformation of exactly cancels the factor from . The inner product on functions is
2.2. Gradient and divergence
The gradient of is the unique vector field characterised by
In local coordinates: , where .
Proof of the coordinate formula. We need components satisfying for all vectors . Setting gives , whence . □
The divergence of is the smooth function characterised by
where is the Lie derivative. In local coordinates:
Proof of the coordinate formula. By Cartan's formula applied to the closed top-degree form (for which ), we get . In coordinates, expanding and taking the exterior derivative yields . Comparing with [eq:div-def-eq] gives [eq:div-coords] [4, Ch. 16]. □
2.3. The Laplace–Beltrami operator
The Laplace–Beltrami operator on is
Substituting [eq:grad-def-eq] into [eq:div-coords] gives the coordinate formula:
On with the Euclidean metric, , , and [eq:lbo-coords] reduces to the standard Laplacian .
is the negative -gradient of the Dirichlet energy
Explicitly, for any :
Proof. Differentiating under the integral and using the symmetry of :
It remains to show that the last integral equals . Apply the Leibniz rule for the Riemannian divergence to the vector field :
Integrating over and applying the Riemannian divergence theorem (boundary term vanishes because ):
Rearranging yields , which is exactly [eq:first-variation] [3, Ch. 2]. □
2.4. Self-adjointness: Green's identity
For on a compact Riemannian manifold without boundary:
Proof. Apply the Leibniz rule to :
Integrating over and applying the divergence theorem (no boundary since is closed):
Rearranging:
Applying the same argument with and exchanged (the gradient inner product is symmetric):
The two left-hand sides are therefore equal, giving all three expressions in [eq:green] [5, Ch. 1]. □
Taking confirms is negative semi-definite: .
2.5. Examples
The round 2-sphere. In polar coordinates on :
The eigenfunctions of are the spherical harmonics with eigenvalues , multiplicity [5, App. B].
The flat torus. On with , the eigenfunctions are the Fourier modes for , eigenvalues , and the heat kernel is
which converges to the flat Gaussian [eq:flat-kernel] as (lattice images are exponentially suppressed).
3. Diffusion on a Curved Manifold
3.1. The heat equation on
Let be a smooth Riemannian manifold. The heat equation on is
For compact without boundary, a smooth solution for follows from the spectral theory of §4 via the heat semigroup . For complete non-compact , existence and uniqueness were established by Dodziuk [6] and Li–Yau [7].
3.2. The heat kernel
The heat kernel of is a smooth function such that
solves [eq:heat-curved] for every . It satisfies:
- for all , .
- (symmetry from self-adjointness).
- (equality for compact ).
- (semigroup).
- for all [6].
3.3. Geodesic distance as the natural substitute
On the kernel [eq:flat-kernel] depends on and only through the Euclidean distance . On a Riemannian manifold the canonical substitute is the geodesic distance . The heat kernel is not simply , since curvature introduces corrections at every order in , but this is the leading term. The parametrix ansatz [8] is
where the transport coefficients are smooth functions determined by substituting [eq:parametrix] into the heat equation and matching powers of .
3.4. The transport equations and the short-time expansion
We derive the coefficients by inserting [eq:parametrix] into and reading off each power of .
Setup. Fix and work in normal coordinates centred at (provided by the exponential map ). In these coordinates [3, Ch. 5]:
- and ,
- to second order,
- the volume density satisfies .
Set , so the exponential factor is . Write the ansatz as where .
Applying the heat operator. Using the product formula for with :
We evaluate two key quantities. The eikonal identity for geodesic distance:
which holds because is the unit radial vector and gives . The Laplacian of : writing and applying the Leibniz rule,
More precisely, since :
Assembling [eq:product-laplacian], subtracting from , and using [eq:laplacian-phi]:
Collecting terms at order and using :
(with ). Multiplying through by shows that the left side equals , yielding the -th transport ODE:
Coefficient . Set in [eq:transport-ODE]:
so . The normalisation condition as requires the leading coefficient to equal 1 at ; since , we get and
In particular, , recovering the flat-space leading term.
Coefficient on the diagonal. Integrate [eq:transport-ODE] for from to :
As both sides vanish; applying L'Hôpital:
It remains to compute at . In normal coordinates, has the expansion [8, Ch. 4]:
Since , applying to [eq:theta-expand] at and using (contraction of the Ricci tensor):
Substituting [eq:delta-theta] into [eq:u1-lhopital]:
The short-time diagonal expansion. Combining [eq:u0] and [eq:u1-diag] in [eq:parametrix] evaluated at [9]:
Return to the opening animation. Particles are coloured by , the flat-space approximation. Equation [eq:heat-expansion] quantifies the correction: at a point where (positive curvature, near the poles of the deformed container), the diagonal kernel exceeds the flat baseline; there is less room for the particle density to spread, so it stays more concentrated. Where (saddle regions), the kernel is below the flat value and particles disperse faster.
The higher coefficients are universal polynomials in the curvature tensor and its covariant derivatives. The next term is [10]:
3.5. Convergence of the parametrix
The parametrix [eq:parametrix] is not yet the true heat kernel; it satisfies but is not exactly zero on the right. To construct the true kernel, one writes where the correction solves a Volterra integral equation involving . For compact , the correction is smooth and , confirming that [eq:heat-expansion] is asymptotically exact [11, Ch. 4].
4. The Spectral Perspective
4.1. Spectral theorem for compact manifolds
Let be compact and connected without boundary. The operator extends to a self-adjoint unbounded operator on with domain . Its spectrum is a discrete sequence
and the corresponding eigenfunctions are smooth and form a complete orthonormal basis for :
The proof uses compactness of the Sobolev embedding (Rellich–Kondrachov), which forces the resolvent of to be compact. The spectral theorem for compact self-adjoint operators then gives the discrete spectrum; elliptic regularity implies smoothness of eigenfunctions [12, Ch. 8].
4.2. Heat kernel as a spectral series
The heat semigroup acts on by
which converges in for all and in for (exponential decay of dominates polynomial growth of ). The integral kernel of is
confirming that [eq:kernel-rep] with this kernel reproduces [eq:semigroup-def].
On the interval with Dirichlet boundary conditions, and . The figure below animates the solution : faded traces are individual modes, bright gold is the sum. Mode (eigenvalue ) decays 49 times faster than mode .
4.3. Weyl's law
Let . Then
where is the volume of the unit ball in . Equivalently, as .
Proof via the heat trace. Define the heat trace
The two expressions for are equal: substituting the spectral series [eq:spectral-kernel] into the integral gives by orthonormality.
Step 1: heat trace asymptotics. Integrating the diagonal expansion [eq:heat-expansion] over :
where is the average scalar curvature. The leading term is
Step 2: rewriting as a Laplace–Stieltjes transform. Regard as a right-continuous step function on . Since , the Lebesgue–Stieltjes measure is the sum of unit point masses at each , and
This is the Laplace–Stieltjes transform of .
Step 3: Karamata's Tauberian theorem. The general statement is: if is a non-negative measure on and its Laplace transform satisfies as , then as [2, App. B].
Apply this with , , and . The conclusion is
Recognising and :
so , which is exactly [eq:weyl].
Step 4: equivalent eigenvalue asymptotics. Inverting: if for large , then
□The figure below plots the exact trace (gold) against the Weyl leading term (blue) for the interval . The animated cursor sweeps from large to small: agreement is excellent near but breaks down at large , where only the mode survives.
4.4. Geometry encoded in the spectrum
The heat trace expansion [eq:trace-expansion] shows that the first two coefficients determine the volume and total scalar curvature . For a compact surface (), the Gauss–Bonnet theorem gives where , so the second heat invariant encodes the Euler characteristic—a topological invariant.
The higher heat invariants are integrals of local curvature polynomials. Their computation underlies the heat-kernel proof of the Atiyah–Singer index theorem [14, 15]: for an elliptic operator on a compact manifold, the alternating heat trace is constant in and equals the Fredholm index ; expanding via the parametrix and integrating expresses the index as an integral of characteristic classes. The heat kernel is thus a bridge between the analytic data of a differential operator, the geometric data of a Riemannian metric, and the topology of the underlying manifold.
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