Partial differential equation
In mathematics, a partial differential equation (PDE) is an equation relating the partial derivatives of an unknown function of several variables. A solution of the equation is a function satisfying this relation. The idea is to try to deduce information about an unknown function by first discovering a relationship between itself and its partial derivatives in the form of a PDE. The PDE can then be used to uncover information about the unknown function, and sometimes an explicit formula for the unknown function can be discovered.
A PDE usually has many (possibly infinitely many) solutions; a particular problem often requires additional boundary conditions which constrain the solution set. Where ordinary differential equations have solutions that are families with each solution characterized by the values of some parameters, for a PDE the solutions often are parametrized by functions (informally put, this means that the set of solutions is much larger).
Partial differential equations are ubiquitous in science and especially in physics, as physical laws can usually be written in form of PDEs. They describe phenomena such as fluid flow, the growth of crystals, diffusion, gravitation, and the behavior of electromagnetic fields. They are important in fields such as aircraft simulation, computer graphics, and weather prediction. The central equations of general relativity and quantum mechanics are also partial differential equations.
- 1 Notation and examples
- 2 Methods to solve PDEs
- 3 Classification
- 4 External links
- 5 References
Notation and examples
In PDEs, it is common to write the unknown function as u and its partial derivative with respect to the variable x as ux, that is:
A very important and basic PDE is Laplace's equation:
for the unknown function u(x,y,z). Solutions to this equation, known as harmonic functions, serve as the potentials of vector fields in physics, such as the gravitational or electrostatic fields.
A generalization of Laplace's equation is Poisson's equation:
where f(x,y,z) is a given function. The solutions to this equation describe potentials of gravitational and electrostatic fields in the presence of masses or electrical charges, respectively.
The wave equation is an equation for an unknown function u(x,y,z,t) (where we think of t as a time variable) which reads:
Its solutions describe waves such as sound or light waves; c is a number which represents the speed of the wave. In lower dimensions, this equation describes the vibration of a string or drum. Solutions will typically be combinations of oscillating sine waves.
The heat equation describes the temperature in a given region over time. It is:
Solutions will typically "even out" over time. The number k describes the thermal diffusivity of the material.
The advection equation describes the transport of a conserved scalar in a velocity field . It is:
If the velocity field is solenoidal (that is, ), then the equation may be simplified to
The Ginzburg-Landau equation occurs in a wide variety of applications. It is
where and are constants and is the imaginary unit.
The Dym equation
Except for Burgers' equation, all the above equations are linear in the sense that they can be written in the form Au = f for a given linear operator A and a given function f. Other important non-linear equations include the Navier-Stokes equations describing the flow of fluids, and Einstein's field equations of general relativity.
Methods to solve PDEs
Linear PDEs are generally solved, when possible, by decomposing the equation according to a set of basis functions, solving those individually and using superposition to find the solution corresponding to the boundary conditions. The method of separation of variables has many important particular applications.
There are no generally applicable methods to solve non-linear PDEs. Still, existence and uniqueness results (such as the Cauchy-Kovalevskaya theorem) are often possible, as are proofs of important qualitative and quantitative properties of solutions (getting these results is a major part of analysis).
Nevertheless, some techniques can be used for several types of equations. The h-principle is the most powerful method to solve underdetermined equations. The Riquier-Janet theory is an effective method for obtaining information about many analytic overdetermined systems.
The method of characteristics can be used in some very special cases to solve partial differential equations.
In some cases, a PDE can be solved via perturbation analysis in which the solution is considered to be a correction to an equation with a known solution. Alternatives are numerical analysis techniques from simple finite difference schemes to the more mature multigrid and finite element methods. Many interesting problems in science and engineering are solved in this way using computers, sometimes high performance supercomputers.
Second-order partial differential equations, and systems of second-order PDEs, can usually be classified as parabolic, hyperbolic or elliptic. This classification gives an intuitive insight into the behavior of the system itself. Assuming the general second-order PDE is of the form
which looks remarkably similar to the equation for a conic section:
- : elliptic equations tend to smooth out any disturbances. A typical example is Laplace's equation. The motion of a fluid at sub-sonic speeds can be approximated with elliptic PDEs.
- : parabolic equations tend to smooth out any pre-existing disturbances in the data. A typical example is the heat equation.
- : hyperbolic equations tend to amplify any disturbances in the data. A typical example is the wave equation. The motion of a fluid at super-sonic speeds can be approximated with hyperbolic PDEs.
This method of classification can easily be extended to systems of partial differential equations by examining the eigenvalues of the coefficient matrix. In this situation, the classification scheme becomes:
- Elliptic: The eigenvalues are all positive or all negative.
- Parabolic : The eigenvalues are all positive or all negative, save one which is zero.
- Hyperbolic : There is at least one negative and at least one positive eigenvalue, and none of the eigenvalues are zero.
The matrix associated with the system
The eigenvectors are (0,1) and (1,0) with eigenvalues 2 and -1. Thus, the system is hyperbolic.
Equations of mixed type
If a PDE has coefficients which are not constant, it is possible that it will not belong to any of these categories but rather be of mixed type. A simple but important example is the Euler-Tricomi equation
which is called elliptic-hyperbolic because it is elliptic in the region x > 0, hyperbolic in the region x < 0, and degenerate parabolic on the line x = 0.
- Partial Differential Equations: Exact Solutions at EqWorld: The World of Mathematical Equations.
- Partial Differential Equations: Index at EqWorld: The World of Mathematical Equations.
- Partial Differential Equations: Methods at EqWorld: The World of Mathematical Equations.
- L.C. Evans, Partial Differential Equations, American Mathematical Society, Providence, 1998. ISBN 0-8218-0772-2
- 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
- A. D. Polyanin and V. F. Zaitsev, Handbook of Nonlinear Partial Differential Equations, Chapman & Hall/CRC Press, Boca Raton, 2004. ISBN 1-58488-355-3
- A. D. Polyanin, V. F. Zaitsev, and A. Moussiaux, Handbook of First Order Partial Differential Equations, Taylor & Francis, London, 2002. ISBN 0-415-27267-X
- D. Zwillinger, Handbook of Differential Equations (3rd edition), Academic Press, Boston, 1997.de:Partielle Differentialgleichung