On 2D Inverse Problems/Harmonic functions

Harmonic functions can be defined as solutions of differential and difference Laplace equation as follows.

A function/vector u defined on the vertices of a graph w/boundary is harmonic if its value at every interior vertex p is the average of its values at neighboring vertices. That is,

$u(p)=\sum _{p\rightarrow q}\gamma (pq)u(q)/\sum _{p\rightarrow q}\gamma (pq).$ Or, alternatively, u satisfies Kirchhoff's law for potential at every interior vertex p:

$\sum _{p\rightarrow q}\gamma (pq)(u(p)-u(q))=0.$ A harmonic function on a manifold M is a twice continuously differentiable function u : M → R, where u satisfies Laplace equation:

$\Delta _{\gamma }u=\nabla \cdot (\gamma \nabla u)=0.$ A harmonic function defined on open subset of the plane satisfies the following differential equation:

$(\gamma u_{x})_{x}+(\gamma u_{y})_{y}=0.$ The harmonic functions satisfy the following properties:

• mean-value property

The value of a harmonic function is a weighted average of its values at the neighbor vertices,

• maximum principle

Corollary: the maximum (and the minimum) of a harmonic functions occurs on the boundary of the graph or the manifold,

• harmonic conjugate

One can use the system of Cauchy-Riemann equations

${\begin{cases}\gamma u_{x}=v_{y},\\\gamma u_{y}=-v_{x}\end{cases}}$ to define the harmonic conjugate.

Analytic/harmonic continuation is an extension of the domain of a given harmonic function.

Dirichlet problem

Harmonic functions minimize the energy integral or the sum

$\int _{\Omega }\gamma |\nabla u|^{2}{\mbox{ and }}\sum _{e=(p,q)\in E}\gamma (e)(u(p)-u(q))^{2}$ if the values of the functions are fixed at the boundary of the domain or the network in the continuous and discrete models respectively. The minimizing function/vector is the solution of the Dirichlet problem with the prescribed boundary data.