Laplace's Equation and Harmonic Functions
What temperature distribution does a metal plate settle into? This happens once you stop waiting for it to change. This question is the search for equilibrium. It seeks the state left over after all transients have died away. It leads directly to one of the most important equations in mathematics: Laplace's equation. Solutions to this equation are called harmonic functions. They describe steady-state heat flow, electrostatic potentials, and incompressible irrotational fluid flow. They also describe the real and imaginary parts of every complex-analytic function. Understanding them opens the door to potential theory. This subject threads through physics, complex analysis, probability, and geometry. The big idea is deceptively simple. Laplace's equation asks a function to have "no wrinkles." Its value at any point must equal the average of its values on any surrounding sphere. This averaging property is proved rigorously below. It is the source of nearly every deep fact about harmonic functions. They cannot have interior local maxima. They are automatically smooth. They are determined completely by their boundary values. This property converts a differential statement into a beautifully geometric, almost mechanical, one. This article builds the theory from the ground up. We define the Laplacian and harmonic functions precisely. We connect them to the classification of second-order linear PDEs. We then prove the Mean Value Theorem for harmonic functions — the central theorem here. From it we derive the strong maximum principle. We also derive a uniqueness result for the Dirichlet problem. All proofs are complete and self-contained. Worked examples cover the two-dimensional Laplace equation on a disk. One example uses an explicitly non-symmetric boundary datum. Another is a genuinely three-dimensional example arising from electrostatics. By the end you will be able to state precisely what it means for a function to be harmonic. You will prove the mean value property from first principles using the divergence theorem. You will deduce the maximum principle from it. You will also see why these results are the seed. From them grow the general Maximum Principle for Parabolic and Elliptic Equations and the theory of Green's Functions for Boundary Value Problems.
- Laplace's equation is ; solutions are called harmonic functions.
- It is the steady-state (time-independent) limit of the heat equation and the source-free case of Poisson's equation.
- The Mean Value Property: a harmonic function's value at a point equals its average over any centered sphere or ball.
- This property forces the Maximum Principle: a nonconstant harmonic function on a bounded domain attains no interior max or min.
- The maximum principle gives uniqueness for the Dirichlet problem on bounded domains, with continuous boundary data.
- Harmonic functions model steady heat, electrostatic potential, and incompressible irrotational flow.
- Key idea: harmonicity is exactly the property of being "locally an average," and this single geometric fact generates the entire theory.
Where this lives today
Harmonic functions and Laplace's equation are foundational across mathematics and its applications. In complex analysis, the real and imaginary parts of any holomorphic function are harmonic (a consequence of the Cauchy–Riemann equations), linking Laplace's equation to conformal mapping and the theory of analytic functions. In electromagnetism, electrostatic potentials in charge-free regions and magnetostatic scalar potentials both solve Laplace's equation, with boundary conditions on conductors set by the physical geometry. In fluid dynamics, the velocity potential of an incompressible, irrotational flow is harmonic, underlying classical aerodynamic theory and the study of ideal fluids. In probability, harmonic functions correspond exactly to the values left invariant, in expectation, by Brownian motion — the mean value property is the continuous analogue of a martingale property, connecting PDE theory to stochastic processes. In numerical analysis and engineering, finite-difference and finite-element methods for Laplace's and Poisson's equations underlie simulations of heat conduction, electrostatic fields, and structural stress. In computer graphics and geometry processing, discrete harmonic functions and the graph Laplacian are used for mesh smoothing, image inpainting, and manifold learning. This chain of ideas continues directly into the Maximum Principle for Parabolic and Elliptic Equations, which generalizes the argument given here to time-dependent and more general elliptic operators, and into Green's Functions for Boundary Value Problems, which builds explicit solution formulas for the Dirichlet and Neumann problems atop the uniqueness result proved above.
Ask the tutor: How does the mean value property generalize to prove existence of solutions via Perron's method, and how does that connect to Green's functions?
Let () be an open set, and let be a function of class (twice continuously differentiable). The Laplacian of is the second-order differential operator
In two variables, ; in three, .
Laplace's equation is the PDE
A function satisfying everywhere on is called harmonic on . The related inhomogeneous equation for a given function is Poisson's equation; Laplace's equation is the special case , corresponding physically to the absence of internal sources or sinks. In the Classification of Second-Order Linear PDEs, Laplace's equation is the archetypal elliptic equation: its principal symbol vanishes only at , so it has no real characteristic directions. This is why, unlike the wave or heat equations, Laplace's equation carries no notion of time evolution — it describes equilibrium, not propagation.
Intuition
Imagine a thin, uniform metal plate whose edge is held at fixed but spatially varying temperatures, and wait until the interior temperature stops changing. The resulting steady-state temperature satisfies the two-dimensional heat equation with , i.e. exactly . The condition says, pointwise, that : any concavity in the -direction is exactly compensated by convexity in the -direction. There is no room left for the function to have an interior "bump" — a local max would require and simultaneously (with at least one strict), forcing , contradicting harmonicity. This is the seed of the maximum principle, made rigorous below. A second, more geometric way to see it: harmonicity means the value at the center of any small ball equals the average of the values on its boundary sphere. A harmonic function has no preferred direction to "lean" — every direction of averaging gives the same answer as being at the center. Electrostatic potentials in charge-free regions, and steady fluid-flow potentials in source-free, irrotational, incompressible flow, both obey this same averaging law, which is why Laplace's equation appears across so many branches of physics.
Let be open, let be harmonic on , and let be an open ball with closure .
(A) Mean Value Property. Then
where and denote surface area and volume, respectively.
(B) Strong Maximum (and Minimum) Principle. Suppose in addition that is open, bounded, and connected, that is harmonic on , and that attains its maximum over at some interior point . Then is constant on . The same conclusion holds for the minimum.
(C) Corollary — Comparison of Boundary Max. Under the hypotheses of (B), if is not constant, then
(D) Uniqueness for the Dirichlet Problem. Let be bounded and connected, and let . There is at most one function solving
We prove (A), (B), (C), (D) in order; each uses only the preceding parts and standard vector calculus (the divergence theorem), so the chain is non-circular.
Proof of (A), the sphere mean value identity. Fix and with . For define
using the substitution to fix the domain of integration to the unit sphere; this is legitimate since makes the integrand smooth in . Differentiate under the integral sign (justified since the integrand and its -derivative are continuous on the compact set for any ):
where is the outward unit normal on (since is precisely that outward normal, and ). By the divergence theorem applied to the vector field on ,
since is harmonic. Hence for every , so is constant on . Since is continuous at ,
by uniform continuity of on a compact neighborhood of (the integrand converges uniformly to the constant as ). Combining constancy of with this limit gives for all ; taking up to (and by continuity, at too) proves the sphere mean value identity for every , in particular at with . For the solid ball average, integrate the sphere identity in polar-type coordinates:
using for every and the standard formula . Dividing by gives the solid mean value identity. This proves (A).
Proof of (B), the strong maximum principle. Let , attained at by hypothesis (recall is compact since is bounded, and is continuous there, so the maximum is attained somewhere in ; here we are given it is attained at an interior point). Define
is nonempty (it contains ) and relatively closed in (as the preimage of the closed set under the continuous function ). We show is also open in . Let . Choose small enough that (possible since is open). By part (A),
Since everywhere on , the function on , and
A nonnegative continuous function with zero integral over a set of positive measure must vanish identically on that set (if at some point , continuity gives on a small ball around , forcing the integral to be strictly positive — a contradiction). Hence on , so . This shows is open in . Thus is a nonempty subset of that is both open and closed in the relative topology of . Since is connected, the only such subsets are and itself; as , we conclude , i.e. on . This proves the maximum case; the minimum case follows by applying the maximum case to , which is harmonic since .
Proof of (C). If is nonconstant, part (B) (contrapositive) shows cannot attain its maximum over at an interior point of ; since is compact and continuous, the maximum is attained somewhere on , hence necessarily on . Thus . The minimum statement follows identically using the minimum case of (B).
Proof of (D), uniqueness. Suppose both solve in with on . Let . Since the Laplacian is linear, in , so is harmonic; also and on . If is constant on , continuity onto (where ) forces that constant to be , so and . If is not constant, part (C) gives
so everywhere on , forcing — contradicting the assumption that is nonconstant. Hence must be constant, and by the previous paragraph , i.e. on .
∎Worked examples
Example 1: Dirichlet problem on a disk with asymmetric boundary data. Solve on the open unit disk , with boundary condition, in polar coordinates ,
In polar coordinates the Laplacian is
Separation of variables with periodic of period gives the standard family of bounded-at-the-origin solutions
each individually harmonic (direct substitution: , and similarly for ). By linearity of , any finite sum of such terms is harmonic. Match the boundary data directly, since it is already a finite trigonometric sum:
This matches ( term), ( cosine term), ( sine term), all other coefficients zero. Hence
Check. In Cartesian coordinates, and , so
Direct differentiation: , ; , . So , confirming harmonicity independently of the polar-coordinate computation. At the center . The average of over the boundary circle is
since . This matches exactly, confirming the mean value property (A) in this concrete case. By the maximum principle (C), the extreme values of on the closed disk occur on the boundary; since is a smooth function of on a compact interval, its extrema can be found by calculus on the circle rather than by searching the whole disk — a genuine computational saving the maximum principle guarantees is valid.
Example 2: A genuinely 3-D harmonic function from electrostatics — the Newtonian/Coulomb potential. Let and consider
This is the potential (up to a physical constant) of a point charge at the origin. We verify for directly, without symmetry shortcuts, differentiating term by term.
By the symmetry of the formula under permuting (the algebra is identical for each variable, so we only need write it once and cyclically permute):
Summing,
So is harmonic on , matching the physical fact that the Coulomb potential satisfies away from the charge itself (at the origin blows up and is not even defined, let alone — this is precisely why the domain excludes the origin, and why a point charge appears as a singular source, or delta function, on the right side of Poisson's equation in the distributional sense). Note this example shows the mean value property must be applied only to balls entirely contained in the domain of harmonicity: the spherical average of over a sphere of radius centered at the origin equals (by symmetry, since everywhere on that sphere), but is undefined — there is no contradiction with Theorem (A) because .
Theorem (B)/(C) require to be connected. Drop this hypothesis and the conclusion fails. Let , the disjoint union of two open unit disks centered at and — an open but disconnected set. Define
Each constant function is trivially harmonic () on its own disk, so and on all of : is harmonic on . But attains its maximum value at every point of — all of them interior points of — while is manifestly not constant on (it equals on the other component). This directly contradicts the conclusion of (B), which asserted that attaining an interior max forces global constancy. The proof of (B) breaks down exactly at the connectedness step: the set is still open and (relatively) closed in — that part of the argument used only the mean value property and is unaffected — but with disconnected, can be a proper nonempty clopen subset (here, exactly), so the conclusion no longer follows. This shows connectedness is not a technical nicety but the load-bearing hypothesis that makes "clopen everything or nothing" valid.
Scope, edge cases & common traps
| Situation | What holds | What fails / must be checked |
|---|---|---|
| bounded, connected, | Maximum principle, uniqueness of Dirichlet problem | Existence of a solution is a separate, harder question (Perron's method, Green's functions) |
| unbounded (e.g. or exterior domains) | Mean value property still holds locally | Maximum principle / uniqueness can fail without a growth or decay condition at infinity |
| disconnected | Mean value property holds on each component | Maximum principle conclusion (constancy) fails globally, only holds per-component |
| Point singularities (e.g. in 3D, in 2D) | Harmonic away from the singularity | Not harmonic (not even defined) at the singular point; mean value theorem inapplicable there |
| Only known, no boundary regularity | is automatically , even real-analytic, inside (a genuinely deeper elliptic regularity fact) | Boundary behavior can still be irregular if or is irregular |
The mathematician behind it
Origins · 1 minPierre-Simon Laplace and how this was discovered
Laplace was among the most influential mathematical physicists of his era, celebrated for his monumental Traité de mécanique céleste and his foundational work in probability. The equation now bearing his name arose from his studies of gravitational potential theory, where he showed that the Newtonian potential of a mass distribution satisfies in regions free of mass — precisely the equation verified for the Coulomb potential in Example 2 above. Laplace's methodical, calculational style, oriented toward physical applications in astronomy and mechanics, shaped how the equation was understood for generations: not as an abstract object but as the mathematical signature of equilibrium.
What is the difference between Laplace's equation and the heat equation?
The heat equation describes how temperature evolves over time toward equilibrium; Laplace's equation describes that equilibrium itself, once time-dependence has vanished. If you seek a steady-state solution of the heat equation — one with — you are precisely solving Laplace's equation. This is why Laplace's equation is sometimes called the "steady-state heat equation." More generally, Laplace's equation is elliptic (no real characteristics, per the Classification of Second-Order Linear PDEs), while the heat equation is parabolic; this classification difference explains why heat equation solutions smooth out and evolve forward in time, while harmonic functions have no time variable and are governed entirely by boundary data.
Why is the mean value property considered the "central" fact about harmonic functions?
Almost every major structural fact about harmonic functions can be derived from the mean value property once it is established. The strong maximum principle follows directly from it (as proved above), and from the maximum principle come uniqueness of the Dirichlet problem, continuous dependence on boundary data, and comparison theorems. It is also true, though a substantially deeper fact requiring more machinery, that the mean value property alone (assumed merely for continuous, not a priori , functions) forces a function to be harmonic and even real-analytic — so the mean value property doesn't just follow from harmonicity, it essentially characterizes it.
Does every harmonic function attain a maximum somewhere?
Only under the right hypotheses. If is bounded and extends continuously to (a compact set), then attains a maximum on by the extreme value theorem, and the maximum principle tells us it occurs on the boundary unless is constant. But on an unbounded domain, a harmonic function may have no maximum at all: is harmonic on (since ) but is unbounded above and below, so it attains neither a max nor a min anywhere. Boundedness of the domain (or of the function itself, in more refined Liouville-type theorems) is essential.
Are harmonic functions automatically smooth?
Yes, and this is one of the striking regularity features of elliptic equations. Although the definition only requires to state that , one can show — using tools beyond this article, such as convolution with smooth mollifiers combined with the mean value property, or complex-analytic representations in two dimensions — that any harmonic function is automatically , and in fact real-analytic on . This "elliptic regularity" phenomenon is in sharp contrast to hyperbolic equations, where solutions can retain sharp discontinuities (e.g., traveling wave fronts) indefinitely.
How does this connect to complex analysis?
If is holomorphic on an open set , the Cauchy–Riemann equations , imply, upon differentiating and adding, that both and satisfy Laplace's equation: (using equality of mixed partials, valid since holomorphic functions are automatically smooth). Such are called harmonic conjugates. Conversely, every harmonic function on a simply connected planar domain is the real part of some holomorphic function. This makes two-dimensional potential theory and complex analysis two languages for the same subject.
What role does Laplace's equation play in the classification of PDEs?
Laplace's equation is the model elliptic equation. For a general second-order linear PDE , ellipticity means ; for Laplace's equation , giving . Elliptic equations describe equilibrium phenomena and have no real characteristic curves, unlike hyperbolic equations (wave-like, with real characteristics along which information propagates) or parabolic equations (diffusion-like, one family of real characteristics). This classification, covered in Classification of Second-Order Linear PDEs, predicts in advance that Laplace's equation should exhibit boundary-value-problem behavior (specify on the entire boundary of a bounded region) rather than initial-value behavior (specify at one time and let it evolve).
What comes next after mastering harmonic functions?
Two natural directions extend this material. The Maximum Principle for Parabolic and Elliptic Equations generalizes the argument given here — which used only the divergence theorem and connectedness — to more general elliptic operators with variable coefficients and to time-dependent parabolic equations like the heat equation, where an analogous but subtler principle holds. Separately, Green's Functions for Boundary Value Problems builds explicit integral representation formulas for solutions of the Dirichlet and Neumann problems, turning the uniqueness result proved here into a genuine existence and construction theory, using the fundamental solution ( in 2D, in 3D, as verified in Example 2) as a building block.