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The diffusion equation is a parabolic partial differential equation. In physics, it describes the macroscopic behavior of many micro-particles in
Brownian motion Brownian motion is the random motion of particles suspended in a medium (a liquid or a gas). The traditional mathematical formulation of Brownian motion is that of the Wiener process, which is often called Brownian motion, even in mathematical ...
, resulting from the random movements and collisions of the particles (see Fick's laws of diffusion). In mathematics, it is related to
Markov processes Markov (Bulgarian language, Bulgarian, ), Markova, and Markoff are common surnames used in Russia and Bulgaria. Notable people with the name include: Academics *Ivana Markova (1938–2024), Czechoslovak-British emeritus professor of psychology at t ...
, such as random walks, and applied in many other fields, such as
materials science Materials science is an interdisciplinary field of researching and discovering materials. Materials engineering is an engineering field of finding uses for materials in other fields and industries. The intellectual origins of materials sci ...
,
information theory Information theory is the mathematical study of the quantification (science), quantification, Data storage, storage, and telecommunications, communication of information. The field was established and formalized by Claude Shannon in the 1940s, ...
, and
biophysics Biophysics is an interdisciplinary science that applies approaches and methods traditionally used in physics to study biological phenomena. Biophysics covers all scales of biological organization, from molecular to organismic and populations ...
. The diffusion equation is a special case of the convection–diffusion equation when bulk velocity is zero. It is equivalent to the
heat equation In mathematics and physics (more specifically thermodynamics), the heat equation is a parabolic partial differential equation. The theory of the heat equation was first developed by Joseph Fourier in 1822 for the purpose of modeling how a quanti ...
under some circumstances.


Statement

The equation is usually written as: \frac = \nabla \cdot \big D(\phi,\mathbf) \ \nabla\phi(\mathbf,t) \big where is the
density Density (volumetric mass density or specific mass) is the ratio of a substance's mass to its volume. The symbol most often used for density is ''ρ'' (the lower case Greek letter rho), although the Latin letter ''D'' (or ''d'') can also be u ...
of the diffusing material at location and time and is the collective diffusion coefficient for density at location ; and represents the vector
differential operator In mathematics, a differential operator is an operator defined as a function of the differentiation operator. It is helpful, as a matter of notation first, to consider differentiation as an abstract operation that accepts a function and retur ...
del Del, or nabla, is an operator used in mathematics (particularly in vector calculus) as a vector differential operator, usually represented by the nabla symbol ∇. When applied to a function defined on a one-dimensional domain, it denotes ...
. If the diffusion coefficient depends on the density then the equation is nonlinear, otherwise it is linear. The equation above applies when the diffusion coefficient is
isotropic In physics and geometry, isotropy () is uniformity in all orientations. Precise definitions depend on the subject area. Exceptions, or inequalities, are frequently indicated by the prefix ' or ', hence '' anisotropy''. ''Anisotropy'' is also ...
; in the case of anisotropic diffusion, is a symmetric positive definite matrix, and the equation is written (for three dimensional diffusion) as: \frac = \sum_^3\sum_^3 \frac\left _(\phi,\mathbf)\frac\right/math> The diffusion equation has numerous analytic solutions. If is constant, then the equation reduces to the following
linear differential equation In mathematics, a linear differential equation is a differential equation that is linear equation, linear in the unknown function and its derivatives, so it can be written in the form a_0(x)y + a_1(x)y' + a_2(x)y'' \cdots + a_n(x)y^ = b(x) wher ...
: : \frac = D\nabla^2\phi(\mathbf,t), which is identical to the
heat equation In mathematics and physics (more specifically thermodynamics), the heat equation is a parabolic partial differential equation. The theory of the heat equation was first developed by Joseph Fourier in 1822 for the purpose of modeling how a quanti ...
.


Historical origin

The particle diffusion equation was originally derived by Adolf Fick in 1855.


Derivation

The diffusion equation can be trivially derived from the continuity equation, which states that a change in density in any part of the system is due to inflow and outflow of material into and out of that part of the system. Effectively, no material is created or destroyed: \frac+\nabla\cdot\mathbf=0, where j is the flux of the diffusing material. The diffusion equation can be obtained easily from this when combined with the phenomenological Fick's first law, which states that the flux of the diffusing material in any part of the system is proportional to the local density gradient: \mathbf=-D(\phi,\mathbf)\,\nabla\phi(\mathbf,t). If drift must be taken into account, the
Fokker–Planck equation In statistical mechanics and information theory, the Fokker–Planck equation is a partial differential equation that describes the time evolution of the probability density function of the velocity of a particle under the influence of drag (physi ...
provides an appropriate generalization.


Discretization

The diffusion equation is continuous in both space and time. One may discretize space, time, or both space and time, which arise in application. Discretizing time alone just corresponds to taking time slices of the continuous system, and no new phenomena arise. In discretizing space alone, the Green's function becomes the discrete Gaussian kernel, rather than the continuous Gaussian kernel. In discretizing both time and space, one obtains the
random walk In mathematics, a random walk, sometimes known as a drunkard's walk, is a stochastic process that describes a path that consists of a succession of random steps on some Space (mathematics), mathematical space. An elementary example of a rand ...
.


Discretization in image processing

The
product rule In calculus, the product rule (or Leibniz rule or Leibniz product rule) is a formula used to find the derivatives of products of two or more functions. For two functions, it may be stated in Lagrange's notation as (u \cdot v)' = u ' \cdot v ...
is used to rewrite the anisotropic tensor diffusion equation, in standard discretization schemes, because direct discretization of the diffusion equation with only first order spatial central differences leads to checkerboard artifacts. The rewritten diffusion equation used in image filtering: \frac = \nabla\cdot \left (\phi,\mathbf)\right\nabla \phi(\mathbf,t) + \Big D(\phi,\mathbf)\big(\nabla\nabla^\text \phi(\mathbf,t)\big)\Big where "tr" denotes the trace of the 2nd rank
tensor In mathematics, a tensor is an algebraic object that describes a multilinear relationship between sets of algebraic objects associated with a vector space. Tensors may map between different objects such as vectors, scalars, and even other ...
, and superscript "T" denotes
transpose In linear algebra, the transpose of a Matrix (mathematics), matrix is an operator which flips a matrix over its diagonal; that is, it switches the row and column indices of the matrix by producing another matrix, often denoted by (among other ...
, in which in image filtering ''D''(''ϕ'', r) are symmetric matrices constructed from the
eigenvectors In linear algebra, an eigenvector ( ) or characteristic vector is a Vector (mathematics and physics), vector that has its direction (geometry), direction unchanged (or reversed) by a given linear map, linear transformation. More precisely, an e ...
of the image structure tensors. The spatial derivatives can then be approximated by two first order and a second order central
finite difference A finite difference is a mathematical expression of the form . Finite differences (or the associated difference quotients) are often used as approximations of derivatives, such as in numerical differentiation. The difference operator, commonly d ...
s. The resulting diffusion algorithm can be written as an image
convolution In mathematics (in particular, functional analysis), convolution is a operation (mathematics), mathematical operation on two function (mathematics), functions f and g that produces a third function f*g, as the integral of the product of the two ...
with a varying kernel (stencil) of size 3 × 3 in 2D and 3 × 3 × 3 in 3D.


See also

* Continuity equation *
Heat equation In mathematics and physics (more specifically thermodynamics), the heat equation is a parabolic partial differential equation. The theory of the heat equation was first developed by Joseph Fourier in 1822 for the purpose of modeling how a quanti ...
* Self-similar solutions * Reaction-diffusion equation *
Fokker–Planck equation In statistical mechanics and information theory, the Fokker–Planck equation is a partial differential equation that describes the time evolution of the probability density function of the velocity of a particle under the influence of drag (physi ...
* Fick's laws of diffusion * Maxwell–Stefan equation * Radiative transfer equation and diffusion theory for photon transport in biological tissue * Streamline diffusion * Numerical solution of the convection–diffusion equation


References


Further reading

* * Carslaw, H. S. and Jaeger, J. C. (1959). ''Conduction of Heat in Solids'' Oxford: Clarendon Press * Jacobs, M.H. (1935). ''Diffusion Processes'' Berlin/Heidelberg: Springer * Crank, J. (1956). ''The Mathematics of Diffusion'' Oxford: Clarendon Press * Mathews, Jon; Walker, Robert L. (1970). ''Mathematical methods of physics'' (2nd ed.), New York: W. A. Benjamin, * Thambynayagam, R. K. M (2011). ''The Diffusion Handbook: Applied Solutions for Engineers''. McGraw-Hill * Ghez, R. (1988). ''A Primer Of Diffusion Problems,'' Wiley * Ghez, R. (2001). ''Diffusion Phenomena''. Long Island, NY, USA: Dover Publication Inc * Pekalski, A. (1994). ''Diffusion Processes: Experiment, Theory, Simulations,'' Springer * Bennett, T.D. (2013). ''Transport by Advection and Diffusion.'' John Wiley & Sons * Vogel, G. (2019). ''Adventure Diffusion'' Springer * Gillespie, D.T.; Seitaridou, E (2013). ''Simple Brownian Diffusion,''Oxford University Press * Nakicenovic, N.; Griübler, A.: (1991). ''Diffusion of Technologies and Social Behavior''; Springer * Michaud, G.; Alecian, G.; Richer, G.: (2013). ''Atomic Diffusion in Stars'', Springer * Stroock, D. W.:, Varadhan, S.R.S.: (2006). ''Multidimensional diffusion processes,'' Springer * Zhuoqun, W., Yin J., Li H., Zhao J., Jingxue Y., and Huilai L. (2001). ''Nonlinear diffusion equations,'' World Scientific * Shewmon, P. (1989). ''Diffusion in Solids'', Wiley * Banks, R.B. (2010). ''Growth and diffusion phenomena,'' Springer * Roque-Malherbe, R.M.A. (2007). ''Adsorption and Diffusion in Nanoporous Materials,'' CRC Press * Cunningham, R. (1980). ''Diffusion in gases and porous media,'' Plenum * Pasquill, F., Smith, F.B. (1983). ''Atmospheric diffusion,'' Horwood * Ikeda, N., Watanabe, S. (1981). ''Stochastic Differential Equations and Diffusion Processes, Elsevier,'' Academic Press *Philibert, J., Laskar, A.L., Bocquet, J.L., Brebec, G., Monty, C. (1990). ''Diffusion in Materials,'' Springer Netherlands *Freedman, D., (1983). ''Brownian Motion and Diffusion'', Springer-Verlag New York *Nagasawa, M., (1993). ''Schrödinger Equations and Diffusion Theory,'' Birkhäuser * Burgers, J.M., (1974). T''he Nonlinear Diffusion Equation: Asymptotic Solutions and Statistical Problems,''Springer Netherlands *Ito, S., (1992). ''Diffusion Equations'', American Mathematical Society *Krylov, N. V. (1994). ''Introduction to the Theory of Diffusion Processes,'' American Mathematical Society *Knight, F.B., (1981). ''Essentials of Brownian Motion and Diffusion,'' American Mathematical Society *Ibe, O.C., (2013''). Elements of random walk and diffusion processes,'' Wiley *Dattagupta, S. (2013). ''Diffusion: Formalism and Applications'', CRC Press


External links


Diffusion Calculator for Impurities & Dopants in Silicon

A tutorial on the theory behind and solution of the Diffusion Equation.


{{DEFAULTSORT:Diffusion Equation Diffusion Partial differential equations Parabolic partial differential equations Functions of space and time it:Leggi di Fick