In mathematics, Poisson's equation is a partial differential equation of elliptic type with broad utility in electrostatics, mechanical engineering and theoretical physics. Commonly used to model diffusion, it is named after the French mathematician, geometer, and physicist Siméon Denis Poisson.
Statement of the equation
Poisson's equation is
where is the Laplace operator, and f and φ are real or complex-valued functions on a manifold. When the manifold is Euclidean space, the Laplace operator is often denoted as ∇2 and so Poisson's equation is frequently written as
In three-dimensional Cartesian coordinates, it takes the form
When we retrieve Laplace's equation.
Poisson's equation may be solved using a Green's function; a general exposition of the Green's function for Poisson's equation is given in the article on the screened Poisson equation. There are various methods for numerical solution. The relaxation method, an iterative algorithm, is one example.
In the case of a gravitational field g due to an attracting massive object, of density ρ, Gauss' law for gravity in differential form can be used to obtain the corresponding Poisson equation for gravity. Gauss' law for gravity is:
and since the gravitational field is conservative, it can be expressed in terms of a scalar potential Φ:
substituting into Gauss' law
obtains Poisson's equation for gravity:
One of the cornerstones of electrostatics is setting up and solving problems described by the Poisson equation. Finding φ for some given f is an important practical problem, since this is the usual way to find the electric potential for a given charge distribution described by the density function.
where is the divergence operator, D = electric displacement field, and ρf = free charge density (describing charges brought from outside). Assuming the medium is linear, isotropic, and homogeneous (see polarization density), we have the constitutive equation:
In the absence of a changing magnetic field, B, Faraday's law of induction gives:
The derivation of Poisson's equation under these circumstances is straightforward. Substituting the potential gradient for the electric field
directly obtains Poisson's equation for electrostatics, which is:
Solving Poisson's equation for the potential requires knowing the charge density distribution. If the charge density is zero, then Laplace's equation results. If the charge density follows a Boltzmann distribution, then the Poisson-Boltzmann equation results. The Poisson–Boltzmann equation plays a role in the development of the Debye–Hückel theory of dilute electrolyte solutions.
The above discussion assumes that the magnetic field is not varying in time. The same Poisson equation arises even if it does vary in time, as long as the Coulomb gauge is used. In this more general context, computing φ is no longer sufficient to calculate E, since E also depends on the magnetic vector potential A, which must be independently computed. See Maxwell's equation in potential formulation for more on φ and A in Maxwell's equations and how Poisson's equation is obtained in this case.
Potential of a Gaussian charge density
If there is a static spherically symmetric Gaussian charge density
where Q is the total charge, then the solution φ(r) of Poisson's equation,
is given by
where erf(x) is the error function.
This solution can be checked explicitly by evaluating . Note that, for r much greater than σ, the erf function approaches unity and the potential φ (r) approaches the point charge potential
as one would expect. Furthermore the erf function approaches 1 extremely quickly as its argument increases; in practice for r > 3σ the relative error is smaller than one part in a thousand.
Poisson's equation is also used to reconstruct a smooth 2D surface (in the sense of curve fitting) based on a large number of points pi (a point cloud) where each point also carries an estimate of the local surface normal ni.
This technique reconstructs the implicit function f whose value is zero at the points pi and whose gradient at the points pi equals the normal vectors ni. The set of (pi, ni) is thus a sampling of a continuous vector ﬁeld V. The implicit function f is found by integrating the vector ﬁeld V. Since not every vector ﬁeld is the gradient of a function, the problem may or may not have a solution: the necessary and sufﬁcient condition for a smooth vector ﬁeld V to be the gradient of a function f is that the curl of V must be identically zero. In case this condition is difﬁcult to impose, it is still possible to perform a least-squares fit to minimize the difference between V and the gradient of f.
- Jackson, Julia A.; Mehl, James P.; Neuendorf, Klaus K. E., eds. (2005), Glossary of Geology, American Geological Institute, Springer, p. 503, ISBN 9780922152766.
- F. Calakli and G. Taubin, Smooth Signed Distance Surface Reconstruction, Paciﬁc Graphics Vol 30-7, 2011
- Poisson Equation at EqWorld: The World of Mathematical Equations.
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- A. D. Polyanin, Handbook of Linear Partial Differential Equations for Engineers and Scientists, Chapman & Hall/CRC Press, Boca Raton, 2002. ISBN 1-58488-299-9