Math 2.0

Partial differential equations Definition

Heat kernel

Builds on Heat equationNormal distribution

Definition

Let n≥1n \ge 1. The heat kernel of ℝn\R^n is the function Φ ⁣:ℝn×(0,∞)→(0,∞)\Phi \colon \R^n \times (0, \infty) \to (0, \infty) given by Φ(x,t)=1(4πt)n/2exp⁡(−∣x∣24t).\Phi(x, t) = \frac{1}{(4 \pi t)^{n/2}} \exp\left( -\frac{\abs{x}^2}{4t} \right). It solves the heat equation ∂tΦ=ΔΦ\partial_t \Phi = \Delta \Phi on ℝn×(0,∞)\R^n \times (0, \infty), satisfies ∫ℝnΦ(x,t) dx=1\int_{\R^n} \Phi(x, t) \, dx = 1 for every t>0t > 0, and Φ(⋅,t)\Phi(\cdot, t) tends to the Dirac measure at 00 as t→0+t \to 0^+.

Remarks

Check for n=1n = 1: ∂tΦ=Φ⋅(−12t+x24t2)\partial_t \Phi = \Phi \cdot \big( -\tfrac{1}{2t} + \tfrac{x^2}{4t^2} \big) and ∂xΦ=−x2tΦ\partial_x \Phi = -\tfrac{x}{2t} \Phi, so ∂x2Φ=Φ⋅(x24t2−12t)\partial_x^2 \Phi = \Phi \cdot \big( \tfrac{x^2}{4t^2} - \tfrac{1}{2t} \big), which is the same. For bounded continuous gg, the function u(x,t)=∫ℝnΦ(x−y,t)g(y) dyu(x, t) = \int_{\R^n} \Phi(x - y, t) g(y) \, dy solves the heat equation for t>0t > 0 and tends to g(x)g(x) as t→0+t \to 0^+. For each tt, Φ(⋅,t)\Phi(\cdot, t) is the density of a normal distribution with mean 00 and covariance 2t2t times the identity. Non-example: p(x,t)=(2πt)−n/2e−∣x∣2/(2t)p(x, t) = (2 \pi t)^{-n/2} e^{-\abs{x}^2/(2t)} is not the heat kernel of ∂t=Δ\partial_t = \Delta; it solves ∂tp=12Δp\partial_t p = \tfrac12 \Delta p and is the transition density of Brownian motion. More generally, a domain with a boundary condition, or a Riemannian manifold, has a heat kernel K(x,y,t)K(x, y, t). It is the function such that u(x,t)=∫K(x,y,t)g(y) dyu(x, t) = \int K(x, y, t) g(y) \, dy solves the heat equation with that boundary condition and initial value gg.

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Further reading

  1. Web https://en.wikipedia.org/wiki/Heat_kernel
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Kinddefinition
WritingW0 stub
MSC35K08, 35K05
DefinesHeat kernel
UsesHeat equation, Normal distribution
Changed2 November 2026

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