Editing Poisson's equation (section)

== Applications in physics and engineering ==

=== Newtonian gravity ===
{{main|Gravitational field|Gauss's law for gravity}}

In the case of a gravitational field '''g''' due to an attracting massive object of density ''ρ'', Gauss's law for gravity in differential form can be used to obtain the corresponding Poisson equation for gravity. Gauss's law for gravity is
<math display="block">\nabla\cdot\mathbf{g} = -4\pi G\rho.</math>

Since the gravitational field is conservative (and [[irrotational]]), it can be expressed in terms of a [[scalar potential]] ''ϕ'':
<math display="block">\mathbf{g} = -\nabla \phi.</math>

Substituting this into Gauss's law,
<math display="block">\nabla\cdot(-\nabla \phi) = - 4\pi G \rho,</math>
yields '''Poisson's equation''' for gravity:
<math display="block">\nabla^2 \phi  =  4\pi G \rho.</math>

If the mass density is zero, Poisson's equation reduces to Laplace's equation. The [[Green's function for the three-variable Laplace equation|corresponding Green's function]] can be used to calculate the potential at distance {{mvar|r}} from a central point mass {{mvar|m}} (i.e., the [[fundamental solution]]). In three dimensions the potential is
<math display="block">\phi(r) = \frac{-G m}{r},</math>
which is equivalent to [[Newton's law of universal gravitation]].

=== Electrostatics ===
{{main|Electrostatics}}
{{refimprove|data=September 2024|date=September 2024}}

Many problems in [[electrostatics]] are governed by the Poisson equation, which relates the [[electric potential]]
{{mvar|φ}} to the free charge density 
<math>\rho_f</math>, such as those found in [[Electrical conductor|conductors]]. 

The mathematical details of Poisson's equation, commonly expressed in [[SI units]] (as opposed to [[Gaussian units]]), describe how the [[charge density|distribution of free charges]] generates the electrostatic potential in a given [[region (mathematics)|region]].

Starting with [[Gauss's law]] for electricity (also one of [[Maxwell's equations]]) in differential form, one has
<math display="block">\mathbf{\nabla} \cdot \mathbf{D} = \rho_f,</math>
where <math>\mathbf{\nabla} \cdot</math> is the [[divergence|divergence operator]], '''D''' is the [[electric displacement field]], and ''ρ<sub>f</sub>'' is the free-[[charge density]] (describing charges brought from outside).

Assuming the medium is linear, isotropic, and homogeneous (see [[polarization density]]), we have the [[constitutive equation#Electromagnetism|constitutive equation]]
<math display="block">\mathbf{D} = \varepsilon \mathbf{E},</math>
where {{mvar|ε}} is the [[permittivity]] of the medium, and '''E''' is the [[electric field]].

Substituting this into Gauss's law and assuming that {{mvar|ε}} is spatially constant in the region of interest yields
<math display="block">\mathbf{\nabla} \cdot \mathbf{E} = \frac{\rho_f}{\varepsilon}.</math>
In electrostatics, we assume that there is no magnetic field (the argument that follows also holds in the presence of a constant magnetic field).<ref>{{Cite book |last=Griffiths |first=D. J. |year=2017 |title=Introduction to Electrodynamics |edition=4th |publisher=Cambridge University Press |pages=77–78}}</ref>
Then, we have that
<math display="block">\nabla \times \mathbf{E} = 0,</math>
where {{math|∇×}} is the [[Curl (mathematics)|curl operator]]. This equation means that we can write the electric field as the gradient of a scalar function {{mvar|φ}} (called the [[electric potential]]), since the curl of any gradient is zero. Thus we can write
<math display="block">\mathbf{E} = -\nabla \varphi,</math>
where the minus sign is introduced so that {{mvar|φ}} is identified as the [[electric potential energy]] per unit charge.<ref>{{Cite book |last=Griffiths |first=D. J. |year=2017 |title=Introduction to Electrodynamics |edition=4th |publisher=Cambridge University Press |pages=83–84}}</ref>

The derivation of Poisson's equation under these circumstances is straightforward. Substituting the potential gradient for the electric field,
<math display="block">\nabla \cdot \mathbf{E} = \nabla \cdot (-\nabla \varphi) = -\nabla^2 \varphi = \frac{\rho_f}{\varepsilon},</math>
directly produces Poisson's equation for electrostatics, which is
<math display="block">\nabla^2 \varphi = -\frac{\rho_f}{\varepsilon}.</math>

Specifying the 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 equation|Debye–Hückel theory of dilute electrolyte solutions]].

Using a Green's function, the potential at distance {{mvar|r}} from a central point charge {{mvar|Q}} (i.e., the [[fundamental solution]]) is
<math display="block">\varphi(r) = \frac {Q}{4 \pi \varepsilon r},</math>
which is [[Coulomb's law]] of electrostatics. (For historical reasons, and unlike gravity's model above, the <math>4 \pi</math> factor appears here and not in Gauss's law.)

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 class of cases, computing {{mvar|φ}} is no longer sufficient to calculate '''E''', since '''E''' also depends on the [[magnetic vector potential]] '''A''', which must be independently computed. See [[Mathematical descriptions of the electromagnetic field#Maxwell's equations in potential formulation|Maxwell's equation in potential formulation]] for more on {{mvar|φ}} and '''A''' in Maxwell's equations and how an appropriate Poisson's equation is obtained in this case.

==== Potential of a Gaussian charge density ====
If there is a static spherically symmetric [[Gaussian distribution|Gaussian]] charge density
<math display="block">\rho_f(r) = \frac{Q}{\sigma^3\sqrt{2\pi}^3}\,e^{-r^2/(2\sigma^2)},</math>
where {{mvar|Q}} is the total charge, then the solution {{math|''φ''(''r'')}} of Poisson's equation
<math display="block">\nabla^2 \varphi = -\frac{\rho_f}{\varepsilon}</math>
is given by
<math display="block">\varphi(r) = \frac{1}{4 \pi \varepsilon} \frac{Q}{r} \operatorname{erf}\left(\frac{r}{\sqrt{2}\sigma}\right),</math>
where {{math|erf(''x'')}} is the [[error function]].<ref>{{Cite journal |last1=Salem |first1=M. |last2=Aldabbagh |first2=O. |title=Numerical Solution to Poisson's Equation for Estimating Electrostatic Properties Resulting from an Axially Symmetric Gaussian Charge Density Distribution |journal=Mathematics |volume=12 |issue=13 |pages=1948 |year=2024 |doi=10.3390/math12131948 |doi-access=free }}</ref> This solution can be checked explicitly by evaluating {{math|∇<sup>2</sup>''φ''}}.

Note that for {{mvar|r}} much greater than {{mvar|σ}}, <math display="inline">\operatorname{erf}(r/\sqrt{2} \sigma)</math> approaches unity,<ref name="Oldham">{{Cite book |last1=Oldham |first1=K. B. |last2=Myland |first2=J. C. |last3=Spanier |first3=J. |title=An Atlas of Functions |chapter=The Error Function erf(x) and Its Complement erfc(x) |pages=405–415 |year=2008 |publisher=Springer |location=New York, NY |doi=10.1007/978-0-387-48807-3_41 |isbn=978-0-387-48806-6 |chapter-url=https://link.springer.com/chapter/10.1007/978-0-387-48807-3_41}}</ref> and the potential {{math|''φ''(''r'')}} approaches the [[electrical potential|point-charge]] potential,
<math display="block">\varphi \approx \frac{1}{4 \pi \varepsilon} \frac{Q}{r},</math>
as one would expect. Furthermore, the error function approaches 1 extremely quickly as its argument increases; in practice, for {{math|''r'' > 3''σ''}} the relative error is smaller than one part in a thousand.<ref name="Oldham"/>

=== Surface reconstruction ===
Surface reconstruction is an [[inverse problem]]. The goal is to digitally reconstruct a smooth surface based on a large number of points ''p<sub>i</sub>'' (a [[point cloud]]) where each point also carries an estimate of the local [[surface normal]] '''n'''<sub>''i''</sub>.<ref>{{cite journal |first1=Fatih |last1=Calakli |first2=Gabriel |last2=Taubin |title=Smooth Signed Distance Surface Reconstruction |journal=Pacific Graphics |year=2011 |volume=30 |number=7 |url=http://mesh.brown.edu/ssd/pdf/Calakli-pg2011.pdf }}</ref> Poisson's equation can be utilized to solve this problem with a technique called Poisson surface reconstruction.<ref name="Kazhdan06">{{cite book |first1=Michael |last1=Kazhdan |first2=Matthew |last2=Bolitho |first3=Hugues |last3=Hoppe |year=2006 |chapter=Poisson surface reconstruction |title=Proceedings of the fourth Eurographics symposium on Geometry processing (SGP '06) |publisher=Eurographics Association, Aire-la-Ville, Switzerland |pages=61–70 |isbn=3-905673-36-3 |chapter-url=https://dl.acm.org/doi/abs/10.5555/1281957.1281965 }}</ref>

The goal of this technique is to reconstruct an [[implicit function]] ''f'' whose value is zero at the points ''p<sub>i</sub>'' and whose gradient at the points ''p<sub>i</sub>'' equals the normal vectors '''n'''<sub>''i''</sub>. The set of (''p<sub>i</sub>'', '''n'''<sub>''i''</sub>) is thus modeled as a continuous [[Euclidean vector|vector]] field '''V'''.  The implicit function ''f'' is found by [[Integral|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 (mathematics)|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''.

In order to effectively apply Poisson's equation to the problem of surface reconstruction, it is necessary to find a good discretization of the vector field '''V'''. The basic approach is to bound the data with a [[finite-difference]] grid. For a function valued at the nodes of such a grid, its gradient can be represented as valued on staggered grids, i.e. on grids whose nodes lie in between the nodes of the original grid. It is convenient to define three staggered grids, each shifted in one and only one direction corresponding to the components of the normal data. On each staggered grid we perform [[trilinear interpolation]] on the set of points. The interpolation weights are then used to distribute the magnitude of the associated component of ''n<sub>i</sub>'' onto the nodes of the particular staggered grid cell containing ''p<sub>i</sub>''. Kazhdan and coauthors give a more accurate method of discretization using an adaptive finite-difference grid, i.e. the cells of the grid are smaller (the grid is more finely divided) where there are more data points.<ref name="Kazhdan06"/> They suggest implementing this technique with an adaptive [[octree]].

=== Fluid dynamics ===
For the incompressible [[Navier–Stokes equations]], given by
<math display="block">\begin{aligned}
 \frac{\partial\mathbf{v}}{\partial t} + (\mathbf{v} \cdot \nabla) \mathbf{v} &= -\frac{1}{\rho} \nabla p + \nu\Delta\mathbf{v} + \mathbf{g}, \\
 \nabla \cdot \mathbf{v} &= 0.
\end{aligned}</math>

The equation for the pressure field <math>p</math> is an example of a nonlinear Poisson equation:
<math display="block">\begin{aligned}
 \Delta p &= -\rho \nabla \cdot(\mathbf{v} \cdot \nabla \mathbf{v}) \\
          &= -\rho \operatorname{Tr}\big((\nabla\mathbf{v}) (\nabla\mathbf{v})\big).
\end{aligned}</math>Notice that the above trace is not sign-definite.