Navier–Stokes existence and smoothness

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https://en.wikipedia.org/wiki/Navier%E2%80%93Stokes_existence_and_smoothness

 

Flow visualization of a turbulent jet, made by laser-induced fluorescence. The jet exhibits a wide range of length scales, an important characteristic of turbulent flows.

 

The Navier–Stokes existence and smoothness problem concerns the mathematical properties of solutions to the Navier–Stokes equations, a system of partial differential equations that describe the motion of a fluid in space. Solutions to the Navier–Stokes equations are used in many practical applications. However, theoretical understanding of the solutions to these equations is incomplete. In particular, solutions of the Navier–Stokes equations often include turbulence, which remains one of the greatest unsolved problems in physics, despite its immense importance in science and engineering.

Even more basic properties of the solutions to Navier–Stokes have never been proven. For the three-dimensional system of equations, and given some initial conditions, mathematicians have not yet proved that smooth solutions always exist, or that if they do exist, they have bounded energy. This is called the Navier–Stokes existence and smoothness problem. 

Since understanding the Navier–Stokes equations is considered to be the first step to understanding the elusive phenomenon of turbulence, the Clay Mathematics Institute in May 2000 made this problem one of its seven Millennium Prize problems in mathematics. It offered a US $1,000,000 prize to the first person providing a solution for a specific statement of the problem:

Prove or give a counter-example of the following statement:
In three space dimensions and time, given an initial velocity field, there exists a vector velocity and a scalar pressure field, which are both smooth and globally defined, that solve the Navier–Stokes equations.

The Navier–Stokes equations

In mathematics, the Navier–Stokes equations are a system of nonlinear partial differential equations for abstract vector fields of any size. In physics and engineering, they are a system of equations that models the motion of liquids or non-rarefied gases (in which the mean free path is short enough so that it can be thought of as a continuum mean instead of a collection of particles) using continuum mechanics. The equations are a statement of Newton's second law, with the forces modeled according to those in a viscous Newtonian fluid—as the sum of contributions by pressure, viscous stress and an external body force. Since the setting of the problem proposed by the Clay Mathematics Institute is in three dimensions, for an incompressible and homogeneous fluid, only that case is considered below.

Let ${\displaystyle \mathbf {v} ({\boldsymbol {x}},t)}$ be a 3-dimensional vector field, the velocity of the fluid, and let ${\displaystyle p({\boldsymbol {x}},t)}$ be the pressure of the fluid. The Navier–Stokes equations are:

${\displaystyle {\frac {\partial \mathbf {v} }{\partial t}}+(\mathbf {v} \cdot \nabla )\mathbf {v} =-{\frac {1}{\rho }}\nabla p+\nu \Delta \mathbf {v} +\mathbf {f} ({\boldsymbol {x}},t)}$

where ${\displaystyle \nu >0}$ is the kinematic viscosity, ${\displaystyle \mathbf {f} ({\boldsymbol {x}},t)}$ the external volumetric force, ${\displaystyle \nabla }$ is the gradient operator and ${\displaystyle \displaystyle \Delta }$ is the Laplacian operator, which is also denoted by ${\displaystyle \nabla \cdot \nabla }$ or ${\displaystyle \nabla ^{2}}$. Note that this is a vector equation, i.e. it has three scalar equations. Writing down the coordinates of the velocity and the external force

${\displaystyle \mathbf {v} ({\boldsymbol {x}},t)={\big (}\,v_{1}({\boldsymbol {x}},t),\,v_{2}({\boldsymbol {x}},t),\,v_{3}({\boldsymbol {x}},t)\,{\big )}\,,\qquad \mathbf {f} ({\boldsymbol {x}},t)={\big (}\,f_{1}({\boldsymbol {x}},t),\,f_{2}({\boldsymbol {x}},t),\,f_{3}({\boldsymbol {x}},t)\,{\big )}}$

then for each ${\displaystyle i=1,2,3}$ there is the corresponding scalar Navier–Stokes equation:

${\displaystyle {\frac {\partial v_{i}}{\partial t}}+\sum _{j=1}^{3}{\frac {\partial v_{i}}{\partial x_{j}}}v_{j}=-{\frac {1}{\rho }}{\frac {\partial p}{\partial x_{i}}}+\nu \sum _{j=1}^{3}{\frac {\partial ^{2}v_{i}}{\partial x_{j}^{2}}}+f_{i}({\boldsymbol {x}},t).}$

The unknowns are the velocity ${\displaystyle \mathbf {v} ({\boldsymbol {x}},t)}$ and the pressure ${\displaystyle p({\boldsymbol {x}},t)}$. Since in three dimensions, there are three equations and four unknowns (three scalar velocities and the pressure), then a supplementary equation is needed. This extra equation is the continuity equation for incompressible fluids that describes the conservation of mass of the fluid:

${\displaystyle \nabla \cdot \mathbf {v} =0.}$

Due to this last property, the solutions for the Navier–Stokes equations are searched in the set of solenoidal ("divergence-free") functions. For this flow of a homogeneous medium, density and viscosity are constants. 

Since only its gradient appears, the pressure p can be eliminated by taking the curl of both sides of the Navier–Stokes equations. In this case the Navier–Stokes equations reduce to the vorticity-transport equations. 

Two settings: unbounded and periodic space

There are two different settings for the one-million-dollar-prize Navier–Stokes existence and smoothness problem. The original problem is in the whole space ${\displaystyle \mathbb {R} ^{3}}$, which needs extra conditions on the growth behavior of the initial condition and the solutions. In order to rule out the problems at infinity, the Navier–Stokes equations can be set in a periodic framework, which implies that they are no longer working on the whole space ${\displaystyle \mathbb {R} ^{3}}$ but in the 3-dimensional torus ${\displaystyle \mathbb {T} ^{3}=\mathbb {R} ^{3}/\mathbb {Z} ^{3}}$. Each case will be treated separately. 

Statement of the problem in the whole space

Hypotheses and growth conditions

The initial condition ${\displaystyle \mathbf {v} _{0}(x)}$ is assumed to be a smooth and divergence-free function (see smooth function) such that, for every multi-index ${\displaystyle \alpha }$ (see multi-index notation) and any ${\displaystyle K>0}$, there exists a constant ${\displaystyle C=C(\alpha ,K)>0}$ such that

${\displaystyle \vert \partial ^{\alpha }\mathbf {v_{0}} (x)\vert \leq {\frac {C}{(1+\vert x\vert )^{K}}}\qquad }$ for all ${\displaystyle \qquad x\in \mathbb {R} ^{3}.}$

The external force ${\displaystyle \mathbf {f} (x,t)}$ is assumed to be a smooth function as well, and satisfies a very analogous inequality (now the multi-index includes time derivatives as well):

${\displaystyle \vert \partial ^{\alpha }\mathbf {f} (x,t)\vert \leq {\frac {C}{(1+\vert x\vert +t)^{K}}}\qquad }$for all${\displaystyle \qquad (x,t)\in \mathbb {R} ^{3}\times [0,\infty ).}$

For physically reasonable conditions, the type of solutions expected are smooth functions that do not grow large as ${\displaystyle \vert x\vert \to \infty }$. More precisely, the following assumptions are made:

1. ${\displaystyle \mathbf {v} (x,t)\in \left[C^{\infty }(\mathbb {R} ^{3}\times [0,\infty ))\right]^{3}\,,\qquad p(x,t)\in C^{\infty }(\mathbb {R} ^{3}\times [0,\infty ))}$
2. There exists a constant ${\displaystyle E\in (0,\infty )}$ such that
   ${\displaystyle \int _{\mathbb {R} ^{3}}\vert \mathbf {v} (x,t)\vert ^{2}\,dx$ for all ${\displaystyle t\geq 0\,.}$

Condition 1 implies that the functions are smooth and globally defined and condition 2 means that the kinetic energy of the solution is globally bounded. 

The Millennium Prize conjectures in the whole space

(A) Existence and smoothness of the Navier–Stokes solutions in ${\displaystyle \mathbb {R} ^{3}}$

Let ${\displaystyle \mathbf {f} (x,t)\equiv 0}$. For any initial condition ${\displaystyle \mathbf {v} _{0}(x)}$ satisfying the above hypotheses there exist smooth and globally defined solutions to the Navier–Stokes equations, i.e. there is a velocity vector ${\displaystyle \mathbf {v} (x,t)}$ and a pressure ${\displaystyle p(x,t)}$ satisfying conditions 1 and 2 above.

(B) Breakdown of the Navier–Stokes solutions in ${\displaystyle \mathbb {R} ^{3}}$

There exists an initial condition ${\displaystyle \mathbf {v} _{0}(x)}$ and an external force ${\displaystyle \mathbf {f} (x,t)}$ such that there exists no solutions ${\displaystyle \mathbf {v} (x,t)}$ and ${\displaystyle p(x,t)}$ satisfying conditions 1 and 2 above.

Statement of the periodic problem

Hypotheses

The functions sought now are periodic in the space variables of period 1. More precisely, let ${\displaystyle e_{i}}$ be the unitary vector in the i- direction:

${\displaystyle e_{1}=(1,0,0)\,,\qquad e_{2}=(0,1,0)\,,\qquad e_{3}=(0,0,1)}$

Then ${\displaystyle \mathbf {v} (x,t)}$ is periodic in the space variables if for any ${\displaystyle i=1,2,3}$, then:

${\displaystyle \mathbf {v} (x+e_{i},t)=\mathbf {v} (x,t){\text{ for all }}(x,t)\in \mathbb {R} ^{3}\times [0,\infty ).}$

Notice that this is considering the coordinates mod 1. This allows working not on the whole space ${\displaystyle \mathbb {R} ^{3}}$ but on the quotient space ${\displaystyle \mathbb {R} ^{3}/\mathbb {Z} ^{3}}$, which turns out to be the 3-dimensional torus:

${\displaystyle \mathbb {T} ^{3}=\{(\theta _{1},\theta _{2},\theta _{3}):0\leq \theta _{i}<2 i="1,2,3\}.}</annotation" pi="" quad="">$

Now the hypotheses can be stated properly. The initial condition ${\displaystyle \mathbf {v} _{0}(x)}$ is assumed to be a smooth and divergence-free function and the external force ${\displaystyle \mathbf {f} (x,t)}$ is assumed to be a smooth function as well. The type of solutions that are physically relevant are those who satisfy these conditions:

3. ${\displaystyle \mathbf {v} (x,t)\in \left[C^{\infty }(\mathbb {T} ^{3}\times [0,\infty ))\right]^{3}\,,\qquad p(x,t)\in C^{\infty }(\mathbb {T} ^{3}\times [0,\infty ))}$
4. There exists a constant ${\displaystyle E\in (0,\infty )}$ such that
   ${\displaystyle \int _{\mathbb {T} ^{3}}\vert \mathbf {v} (x,t)\vert ^{2}\,dx$ for all ${\displaystyle t\geq 0\,.}$

Just as in the previous case, condition 3 implies that the functions are smooth and globally defined and condition 4 means that the kinetic energy of the solution is globally bounded.

The periodic Millennium Prize theorems

(C) Existence and smoothness of the Navier–Stokes solutions in ${\displaystyle \mathbb {T} ^{3}}$

Let ${\displaystyle \mathbf {f} (x,t)\equiv 0}$. For any initial condition ${\displaystyle \mathbf {v} _{0}(x)}$ satisfying the above hypotheses there exist smooth and globally defined solutions to the Navier–Stokes equations, i.e. there is a velocity vector ${\displaystyle \mathbf {v} (x,t)}$ and a pressure ${\displaystyle p(x,t)}$ satisfying conditions 3 and 4 above.

(D) Breakdown of the Navier–Stokes solutions in ${\displaystyle \mathbb {T} ^{3}}$

There exists an initial condition ${\displaystyle \mathbf {v} _{0}(x)}$ and an external force ${\displaystyle \mathbf {f} (x,t)}$ such that there exists no solutions ${\displaystyle \mathbf {v} (x,t)}$ and ${\displaystyle p(x,t)}$ satisfying conditions 3 and 4 above. 

Partial results

1. The Navier–Stokes problem in two dimensions has already been solved positively since the 1960s: there exist smooth and globally defined solutions.
2. If the initial velocity ${\displaystyle \mathbf {v} (x,t)}$ is sufficiently small then the statement is true: there are smooth and globally defined solutions to the Navier–Stokes equations.
3. Given an initial velocity ${\displaystyle \mathbf {v} _{0}(x)}$ there exists a finite time T, depending on ${\displaystyle \mathbf {v} _{0}(x)}$ such that the Navier–Stokes equations on ${\displaystyle \mathbb {R} ^{3}\times (0,T)}$ have smooth solutions ${\displaystyle \mathbf {v} (x,t)}$ and ${\displaystyle p(x,t)}$. It is not known if the solutions exist beyond that "blowup time" T.
4. Jean Leray in 1934 proved the existence of so-called weak solutions to the Navier–Stokes equations, satisfying the equations in mean value, not pointwise.
5. Terence Tao in 2016 published a finite time blowup result for an averaged version of the 3-dimensional Navier–Stokes equation. He writes that the result formalizes a "supercriticality barrier" for the global regularity problem for the true Navier–Stokes equations, and claims that the method of proof in fact hints at a possible route to establishing blowup for the true equations.
6. Tristan Buckmaster and Vlad Vicol showed in 2018 that very weak solutions (weaker than Leray's above) are not unique in the class of finite energy solutions 

In popular culture

Unsolved problems have been used to indicate a rare mathematical talent in fiction. The Navier-Stokes problem features in The Mathematician's Shiva (2014), a book about a prestigious, deceased, fictional mathematician named Rachela Karnokovitch taking the proof to her grave in protest of academia. The movie Gifted (2017) referenced the Millennium Prize problems and dealt with the potential for a 7-year-old girl and her deceased mathematician mother for solving the Navier–Stokes problem.

Differential equation (updated)

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Differential_equation

 

Visualization of heat transfer in a pump casing, created by solving the heat equation. Heat is being generated internally in the casing and being cooled at the boundary, providing a steady state temperature distribution.

 

In mathematics, a differential equation is an equation that relates one or more functions and their derivatives. In applications, the functions generally represent physical quantities, the derivatives represent their rates of change, and the differential equation defines a relationship between the two. Because such relations are extremely common, differential equations play a prominent role in many disciplines including engineering, physics, economics, and biology. 

The study of differential equations consists mainly of the study of their solutions (the set of functions that satisfy the equation), and of the properties of their solutions. Only the simplest differential equations are solvable by explicit formulas; however, many properties of solutions of a given differential equation may be determined without computing them exactly.

If a closed-form expression for the solutions is not available, the solutions 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.

 

 

History

Differential equations first came into existence with the invention of calculus by Newton and Leibniz. In Chapter 2 of his 1671 work Methodus fluxionum et Serierum Infinitarum, Isaac Newton listed three kinds of differential equations:

${\displaystyle {\begin{aligned}&{\frac {dy}{dx}}=f(x)\\[5pt]&{\frac {dy}{dx}}=f(x,y)\\[5pt]&x_{1}{\frac {\partial y}{\partial x_{1}}}+x_{2}{\frac {\partial y}{\partial x_{2}}}=y\end{aligned}}}$

In all these cases, y is an unknown function of x (or of ${\displaystyle x_{1}}$ and ${\displaystyle x_{2}}$), and f is a given function. 

He solves these examples and others using infinite series and discusses the non-uniqueness of solutions.

Jacob Bernoulli proposed the Bernoulli differential equation in 1695. This is an ordinary differential equation of the form

${\displaystyle y'+P(x)y=Q(x)y^{n}\,}$

for which the following year Leibniz obtained solutions by simplifying it.

Historically, the problem of a vibrating string such as that of a musical instrument was studied by Jean le Rond d'Alembert, Leonhard Euler, Daniel Bernoulli, and Joseph-Louis Lagrange. In 1746, d’Alembert discovered the one-dimensional wave equation, and within ten years Euler discovered the three-dimensional wave equation.

The Euler–Lagrange equation was developed in the 1750s by Euler and Lagrange in connection with their studies of the tautochrone problem. This is the problem of determining a curve on which a weighted particle will fall to a fixed point in a fixed amount of time, independent of the starting point. Lagrange solved this problem in 1755 and sent the solution to Euler. Both further developed Lagrange's method and applied it to mechanics, which led to the formulation of Lagrangian mechanics.

In 1822, Fourier published his work on heat flow in Théorie analytique de la chaleur (The Analytic Theory of Heat), in which he based his reasoning on Newton's law of cooling, namely, that the flow of heat between two adjacent molecules is proportional to the extremely small difference of their temperatures. Contained in this book was Fourier's proposal of his heat equation for conductive diffusion of heat. This partial differential equation is now taught to every student of mathematical physics.

Example

In classical mechanics, the motion of a body is described by its position and velocity as the time value varies. Newton's laws allow these variables to be expressed dynamically (given the position, velocity, acceleration and various forces acting on the body) as a differential equation for the unknown position of the body as a function of time.

In some cases, this differential equation (called an equation of motion) may be solved explicitly.

An example of modeling a real-world problem using differential equations is the determination of the velocity 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 acceleration due to air resistance. Gravity is considered constant, and air resistance may be modeled as proportional to the ball's velocity. This means that the ball's acceleration, which is a derivative of its velocity, depends on the velocity (and the velocity depends on time). Finding the velocity as a function of time involves solving a differential equation and verifying its validity.

Types

Differential equations can be divided into several types. Apart from describing the properties of the equation itself, these classes of differential equations can help inform the choice of approach to a solution. Commonly used distinctions include whether the equation is: Ordinary/Partial, Linear/Non-linear, and Homogeneous/heterogeneous. This list is far from exhaustive; there are many other properties and subclasses of differential equations which can be very useful in specific contexts.

Ordinary differential equations

An ordinary differential equation (ODE) is an equation containing an unknown function of one real or complex variable x, its derivatives, and some given functions of x. The unknown function is generally represented by a variable (often denoted y), which, therefore, depends on x. Thus x is often called the independent variable of the equation. The term "ordinary" is used in contrast with the term partial differential equation, which may be with respect to more than one independent variable.

Linear differential equations are the differential equations that are linear in the unknown function and its derivatives. Their theory is well developed, and, in many cases, one may express their solutions in terms of integrals.

Most ODEs that are encountered in physics are linear, and, therefore, most special functions may be defined as solutions of linear differential equations.

As, in general, the solutions of a differential equation cannot be expressed by a closed-form expression, numerical methods are commonly used for solving differential equations on a computer. 

Partial differential equations

A partial differential equation (PDE) is a differential equation that contains unknown multivariable functions and their partial derivatives. (This is in contrast to ordinary differential equations, which deal with functions of a single variable and their derivatives.) PDEs are used to formulate problems involving functions of several variables, and are either solved in closed form, or used to create a relevant computer model.

PDEs can be used to describe a wide variety of phenomena in nature such as sound, heat, electrostatics, electrodynamics, fluid flow, elasticity, or quantum mechanics. These seemingly distinct physical phenomena can be formalized similarly in terms of PDEs. Just as ordinary differential equations often model one-dimensional dynamical systems, partial differential equations often model multidimensional systems. PDEs find their generalization in stochastic partial differential equations. 

Non-linear differential equations

A non-linear differential equation is a differential equation that is not a linear equation in the unknown function and its derivatives (the linearity or non-linearity in the arguments of the function are not considered here). There are very few methods of solving nonlinear differential equations exactly; those that are known typically depend on the equation having particular 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 well-posedness 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). However, if the differential equation is a correctly formulated representation of a meaningful physical process, then one expects it to have a solution.

Linear differential equations frequently appear as approximations to nonlinear equations. These approximations are only valid under restricted conditions. For example, the harmonic oscillator equation is an approximation to the nonlinear pendulum equation that is valid for small amplitude oscillations (see below). 

Equation order

Differential equations are described by their order, determined by the term with the highest derivatives. An equation containing only first derivatives is a first-order differential equation, an equation containing the second derivative is a second-order differential equation, and so on. Differential equations that describe natural phenomena almost always have only first and second order derivatives in them, but there are some exceptions, such as the thin film equation, which is a fourth order partial differential equation.

Examples

In the first group of examples, u is an unknown function of x, and c and ω are constants that are supposed to be known. Two broad classifications of both ordinary and partial differential equations consists of distinguishing between linear and nonlinear differential equations, and between homogeneous differential equations and heterogeneous ones.

• heterogeneous first-order linear constant coefficient ordinary differential equation:

${\displaystyle {\frac {du}{dx}}=cu+x^{2}.}$

• Homogeneous second-order linear ordinary differential equation:

${\displaystyle {\frac {d^{2}u}{dx^{2}}}-x{\frac {du}{dx}}+u=0.}$

• Homogeneous second-order linear constant coefficient ordinary differential equation describing the harmonic oscillator:

${\displaystyle {\frac {d^{2}u}{dx^{2}}}+\omega ^{2}u=0.}$

• heterogeneous first-order nonlinear ordinary differential equation:

${\displaystyle {\frac {du}{dx}}=u^{2}+4.}$

• Second-order nonlinear (due to sine function) ordinary differential equation describing the motion of a pendulum of length L:

${\displaystyle L{\frac {d^{2}u}{dx^{2}}}+g\sin u=0.}$

In the next group of examples, the unknown function u depends on two variables x and t or x and y.

• Homogeneous first-order linear partial differential equation:

${\displaystyle {\frac {\partial u}{\partial t}}+t{\frac {\partial u}{\partial x}}=0.}$

• Homogeneous second-order linear constant coefficient partial differential equation of elliptic type, the Laplace equation:

${\displaystyle {\frac {\partial ^{2}u}{\partial x^{2}}}+{\frac {\partial ^{2}u}{\partial y^{2}}}=0.}$

• Homogeneous third-order non-linear partial differential equation :

${\displaystyle {\frac {\partial u}{\partial t}}=6u{\frac {\partial u}{\partial x}}-{\frac {\partial ^{3}u}{\partial x^{3}}}.}$

Existence of solutions

Solving differential equations is not like solving algebraic equations. Not only are their solutions often unclear, but whether solutions are unique or exist at all are also notable subjects of interest.

For first order initial value problems, the Peano existence theorem gives one set of circumstances in which a solution exists. Given any point ${\displaystyle (a,b)}$ in the xy-plane, define some rectangular region ${\displaystyle Z}$, such that ${\displaystyle Z=[l,m]\times [n,p]}$ and ${\displaystyle (a,b)}$ is in the interior of ${\displaystyle Z}$. If we are given a differential equation ${\displaystyle {\frac {\mathrm {d} y}{\mathrm {d} x}}=g(x,y)}$ and the condition that ${\displaystyle y=b}$ when ${\displaystyle x=a}$, then there is locally a solution to this problem if ${\displaystyle g(x,y)}$ and ${\displaystyle {\frac {\partial g}{\partial x}}}$ are both continuous on ${\displaystyle Z}$. This solution exists on some interval with its center at ${\displaystyle a}$. The solution may not be unique.

However, this only helps us with first order initial value problems. Suppose we had a linear initial value problem of the nth order:

${\displaystyle f_{n}(x){\frac {\mathrm {d} ^{n}y}{\mathrm {d} x^{n}}}+\cdots +f_{1}(x){\frac {\mathrm {d} y}{\mathrm {d} x}}+f_{0}(x)y=g(x)}$

such that

${\displaystyle y(x_{0})=y_{0},y'(x_{0})=y'_{0},y''(x_{0})=y''_{0},\cdots }$

For any nonzero ${\displaystyle f_{n}(x)}$, if ${\displaystyle \{f_{0},f_{1},\cdots \}}$ and ${\displaystyle g}$ are continuous on some interval containing ${\displaystyle x_{0}}$, ${\displaystyle y}$ is unique and exists.

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.
• An integro-differential equation (IDE) is an equation that combines aspects of a differential equation and an integral equation.
• 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 stochastic partial differential equation (SPDE) is an equation that generalizes SDEs to include space-time noise processes, with applications in quantum field theory and statistical mechanics.
• A differential algebraic equation (DAE) is a differential equation comprising differential and algebraic terms, given in implicit form.

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 the approximation of the solution of a differential equation by the solution of a corresponding difference equation.

Applications

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 real-life problems may not necessarily be directly solvable, i.e. do not have closed form solutions. Instead, solutions can be approximated using numerical methods.

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 the 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, the theory of which was developed by Joseph Fourier, is governed by another second-order partial differential equation, the heat equation. It turns out that many diffusion processes, while seemingly different, are described by the same equation; the Black–Scholes equation in finance is, for instance, related to the heat equation. 

The number of differential equations that have received a name, in various scientific areas is a witness of the importance of the topic.