Differential equation
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A differential equation is a mathematical equation for an unknown function of one or several variables that relates the values of the function itself and its derivatives of various orders. Differential equations play a prominent role in engineering, physics, economics and other disciplines.
A simplified real world example of a differential equation is modeling the acceleration of a ball falling through the air (considering only gravity and air resistance). The ball's acceleration towards the ground is the acceleration due to gravity minus the deceleration due to air resistance. Gravity is a constant but air resistance is proportional to the ball's velocity. This means the ball's acceleration is dependent on its velocity. Because acceleration is the derivative of velocity, solving this problem requires a differential equation.
Differential equations arise in many areas of science and technology; whenever a deterministic relationship involving some continuously changing quantities (modeled by functions) and their rates of change (expressed as derivatives) is known or postulated. This is well illustrated by classical mechanics, where the motion of a body is described by its position and velocity as the time varies. Newton's Laws allow one to relate the position, velocity, acceleration and various forces acting on the body and state this relation as a differential equation for the unknown position of the body as a function of time. In many cases, this differential equation may be solved explicitly, yielding the law of motion.
Differential equations are mathematically studied from several different perspectives, mostly concerned with their solutions, functions that make the equation hold true. Only the simplest differential equations admit solutions given by explicit formulas. Many properties of solutions of a given differential equation may be determined without finding their exact form. If a selfcontained formula for the solution is not available, the solution may be numerically approximated using computers. The theory of dynamical systems puts emphasis on qualitative analysis of systems described by differential equations, while many numerical methods have been developed to determine solutions with a given degree of accuracy.
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[edit] Directions of study
The study of differential equations is a wide field in pure and applied mathematics, physics, and engineering. All of these disciplines are concerned with the properties of differential equations of various types. Pure mathematics focuses on the existence and uniqueness of solutions, while applied mathematics emphasizes the rigorous justification of the methods for approximating solutions. Differential equations play an important role in modeling virtually every physical, technical, or biological process, from celestial motion to bridge design, to interactions between neurons. Differential equations such as those used to solve reallife problems may not necessarily be directly solvable, i.e. do not have closed form solutions. Instead, solutions can be approximated using numerical methods.
Mathematicians also study weak solutions (relying on weak derivatives), which are types of solutions that do not have to be differentiable everywhere. This extension is often necessary for solutions to exist, and it also results in more physically reasonable properties of solutions, such as possible presence of shocks for equations of hyperbolic type.
The study of the stability of solutions of differential equations is known as stability theory.
[edit] Nomenclature
The theory of differential equations is quite developed and the methods used to study them vary significantly with the type of the equation.
 An ordinary differential equation (ODE) is a differential equation in which the unknown function (also known as the dependent variable) is a function of a single independent variable. In the simplest form, the unknown function is a real or complex valued function, but more generally, it may be vectorvalued or matrixvalued: this corresponds to considering a system of ordinary differential equations for a single function. Ordinary differential equations are further classified according to the order of the highest derivative with respect to the dependent variable appearing in the equation. The most important cases for applications are first order and second order differential equations. In the classical literature also distinction is made between differential equations explicitly solved with respect to the highest derivative and differential equations in an implicit form.
 A partial differential equation (PDE) is a differential equation in which the unknown function is a function of multiple independent variables and the equation involves its partial derivatives. The order is defined similarly to the case of ordinary differential equations, but further classification into elliptic, hyperbolic, and parabolic equations, especially for second order linear equations, is of outmost importance. Some partial differential equations do not fall into any of these categories over the whole domain of the independent variables and they are said to be of mixed type.
Both ordinary and partial differential equations are broadly classified as linear and nonlinear. A differential equation is linear if the unknown function and its derivatives appear to the power 1 (products are not allowed) and nonlinear otherwise. The characteristic property of linear equations is that their solutions form an affine subspace of an appropriate function space, which results in much more developed theory of linear differential equations. Homogeneous linear differential equations are a further subclass for which the space of solutions is a linear subspace. The coefficients of the unknown function and its derivatives in a linear differential equation are allowed to be (known) functions of the independent variable or variables; if these coefficients are constants then one speaks of a constant coefficient linear differential equation.
There are very few methods of explicitly solving nonlinear differential equations, which typically exploit their symmetries. Nonlinear differential equations can exhibit very complicated behavior over extended time intervals, characteristic of chaos. Even the fundamental questions of existence, uniqueness, and extendability of solutions for nonlinear differential equations, and wellposedness of initial and boundary value problems for nonlinear PDEs are hard problems and their resolution in special cases is considered to be a significant advance in the mathematical theory (cf Navier–Stokes existence and smoothness). On the other hand, linear differential equations frequently appear as approximations to nonlinear equations. These approximations are only valid under restricted conditions, for example, the harmonic oscillator and the nonlinear pendulum equations below.
[edit] Examples
In the first group of examples, let u be the unknown function of x, u′ denotes its first derivative, and c and ω are known constants.
 Inhomogeneous first order linear constant coefficient ordinary differential equation:
 u' = cu + x^{2}.
 Homogeneous second order linear ordinary differential equation:
 u'' − xu' + u = 0.
 Homogeneous second order constant coefficient linear ordinary differential equation describing the harmonic oscillator:
 u'' + ω^{2}u = 0.
 First order nonlinear ordinary differential equation:
 u' = u^{2} + 1.
 Second order nonlinear ordinary differential equation describing the motion of a pendulum of length L:
 gu'' + Lsinu = 0.
In the next group of examples, the unknown function u depends on two variables x and t or x and y. Partial derivatives are denoted by subscripts, for example, u_{tx} stands for the second order mixed partial derivative with respect to t and x.
 Homogeneous first order linear partial differential equation:
 u_{t} + tu_{x} = 0.
 Homogeneous second order linear constant coefficient partial differential equation of elliptic type, the Laplace equation:
 u_{xx} + u_{yy} = 0.
 Third order nonlinear differential equation, the Korteweg–de Vries equation:
 u_{t} = 6uu_{x} − u_{xxx}.
[edit] Related concepts
 A delay differential equation (DDE) is an equation for a function of a single variable, usually called time, in which the derivative of the function at a certain time is given in terms of the values of the function at earlier times.
 A stochastic differential equation (SDE) is an equation in which the unknown quantity is a stochastic process and the equation involves some known stochastic processes, for example, the Wiener process in the case of diffusion equations.
 A differential algebraic equation (DAE) is a differential equation comprising differential and algebraic terms, given in implicit form.
[edit] Connection to difference equations
The theory of differential equations is closely related to the theory of difference equations, in which the coordinates assume only discrete values, and the relationship involves values of the unknown function or functions and values at nearby coordinates. Many methods to compute numerical solutions of differential equations or study the properties of differential equations involve approximation of the solution of a differential equation by the solution of a corresponding difference equation. See also: Time scale calculus.
Differential equations are also divided into homogeneous and heterogeneous equations.
Homogeneous equations are equations where the variables are not separated easily. In heterogeneous equations the variables can be separated with no difficulty in order to solve the equations.
[edit] Universality of mathematical description
Many fundamental laws of physics and chemistry can be formulated as differential equations. In biology and economics differential equations are used to model the behavior of complex systems. The mathematical theory of differential equations first developed together with the sciences where the equations had originated and where the results found application. However, diverse problems, sometimes originating in quite distinct scientific fields, may give rise to identical differential equations. Whenever this happens, mathematical theory behind the equations can be viewed as a unifying principle behind diverse phenomena. As an example, consider propagation of light and sound in the atmosphere, and of waves on the surface of a pond. All of them may be described by the same second order partial differential equation, the wave equation, which allows us to think of light and sound as forms of waves, much like familiar waves in the water. Conduction of heat, whose theory was developed by Joseph Fourier, is governed by another second order partial differential equation, the heat equation. It turned out that many diffusion processes, while seemingly different, are described by the same equation; BlackScholes equation in finance is for instance, related to the heat equation.
[edit] Notable differential equations
 Newton's Second Law in dynamics (mechanics)
 NavierStokes Equation in Fluid dynamics
 Hamilton's equations in classical mechanics
 Radioactive decay in nuclear physics
 Newton's law of cooling in thermodynamics
 The wave equation
 Maxwell's equations in electromagnetism
 The heat equation in thermodynamics
 Laplace's equation, which defines harmonic functions
 Poisson's equation
 Einstein's field equation in general relativity
 The Schrödinger equation in quantum mechanics
 The geodesic equation
 The NavierStokes equations in fluid dynamics
 The LotkaVolterra equation in population dynamics
 The BlackScholes equation in finance
 The CauchyRiemann equations in complex analysis
 The PoissonBoltzmann equation in molecular dynamics
 The shallow water equations
[edit] Biology
 Verhulst equation  biological population growth
 LotkaVolterra equations  biological population dynamics
 Replicator dynamics  may be found in theoretical biology
[edit] Economics
[edit] See also
Wikibooks has a book on the topic of 
 PicardLindelöf theorem on existence and uniqueness of solutions
 Integral equations
 Complex differential equation
[edit] References
 D. Zwillinger, Handbook of Differential Equations (3rd edition), Academic Press, Boston, 1997.
 A. D. Polyanin and V. F. Zaitsev, Handbook of Exact Solutions for Ordinary Differential Equations (2nd edition), Chapman & Hall/CRC Press, Boca Raton, 2003. ISBN 1584882972.
 W. Johnson, A Treatise on Ordinary and Partial Differential Equations, John Wiley and Sons, 1913, in University of Michigan Historical Math Collection
 E.L. Ince, Ordinary Differential Equations, Dover Publications, 1956
 E.A. Coddington and N. Levinson, Theory of Ordinary Differential Equations, McGrawHill, 1955
[edit] External links
 lectures on differential equations MIT Open CourseWare video
 Online Notes / Differential Equations Paul Dawkins, Lamar University
 Differential Equations, S.O.S. Mathematics
 Introduction to modeling via differential equations Introduction to modeling by means of differential equations, with critical remarks.
 Differential Equation Solver Java applet tool used to solve differential equations.
 Mathematical Assistant on Web online solving first order (linear and with separated variables) and second order linear differential equations (with constant coefficients), including intermediate steps in the solution, powered by Maxima
 Exact Solutions of Ordinary Differential Equations
 A bibliography of books about differential equations, from the Mathematical Association of America
 Collection of ODE and DAE models of physical systems MATLAB models
 ODE Examples with Solutions
 Plus teacher and student package: Differential Equations. Brings together all the material on differential equations from Plus, the online mathematics magazine produced by the Millennium Mathematics Project at the University of Cambridge.
