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'''A differential equation''' is an equation that relates an unknown function to its own derivatives. An algebraic equation such as ''x''² − 3''x'' + 2 = 0 asks for numbers; a differential equation asks for functions. Because a derivative measures how fast a quantity changes, differential equations describe change itself, and they form the mathematical language of much of science and engineering: the fall of a body, the swing of a pendulum, the decay of a radioactive nucleus, the flow of heat in a rod, the vibration of a string and the growth of a population are all described by differential equations.<ref>{{#cite:Q1576}}</ref><ref>{{#cite:Q1579}}</ref>
'''A differential equation''' is an equation that relates an unknown function to its own derivatives.  


A few features are common to all differential equations:
Two features are common to all differential equations:


* the unknown is a function, not a number;
* the unknown is a function, not a number;
* a solution is rarely unique: it is a family of functions containing arbitrary constants, and a particular member is singled out by extra conditions, such as the state of the system at some starting time;
* a solution is rarely unique, but instead often a family of functions containing arbitrary constants. A particular member of the solution family can be singled out by extra conditions, such as the state of the system at some time;
* they are classified as ordinary or partial, by their order, and as linear or nonlinear.


== Types of differential equations ==
== Types of differential equations ==
Line 11: Line 10:
=== Ordinary and partial differential equations ===
=== Ordinary and partial differential equations ===


If the unknown function depends on a single independent variable, only ordinary derivatives occur, and the equation is an '''ordinary differential equation''' (ODE). Writing the unknown as ''y''(''x''), an ODE can be expressed in implicit form as a relation between the independent variable, the function, and its derivatives up to some order ''n'':
==== Ordinary differential equations ====
 
An '''ordinary differential equation''' (ODE) describes an unknown function which depends on a single independent variable.
 
Writing the unknown as ''y''(''x''), an ODE can be expressed in its implicit form:


{{#content:Q1580}}
{{#content:Q1580}}


where ''F'' is a given function. If the equation can be solved for the highest derivative, it takes an explicit form, for a first-order equation:
where ''F'' is a given function.


{{#content:Q1581}}
If the equation can be solved for the highest derivative, it takes an explicit form.


The right-hand side ''f''(''x'', ''y'') prescribes, at every point (''x'', ''y''), the slope that the graph of a solution must have as it passes through that point.
For a first-order equation:


If the unknown function depends on two or more variables and partial derivatives appear, the equation is a '''partial differential equation''' (PDE). PDEs govern fields, quantities that vary from point to point and, often, with time. The classical linear examples are the heat equation, the wave equation and Laplace's equation:
{{#content:Q1581}}


{{#content:Q1590}}
The right-hand side ''f''(''x'', ''y'') prescribes the slope of any solution function must have at point (''x'', ''y'').


{{#content:Q1591}}
<!-- for higher orders? -->


{{#content:Q1592}}
==== Partial differential equations ====


[[File:One-dimensional wave equation animation.gif|thumb|A pulse travelling on a string fixed at both ends: a solution of the one-dimensional wave equation. Credit: Oleg Alexandrov (public domain).]]
If the unknown function depends on two or more variables and partial derivatives appear, the equation is a '''partial differential equation''' (PDE).


In the wave equation ''u''(''x'', ''t'') is the displacement of the string at position ''x'' and time ''t'', and ''c'' is the wave speed; in the heat equation ''u'' is the temperature and α the thermal diffusivity; in Laplace's equation ''u'' is a potential in equilibrium, for instance a steady temperature or an electrostatic potential.<ref>{{#cite:Q1579}}</ref>
<!-- general formula? -->


=== Order and linearity ===
=== Order and linearity ===


The '''order''' of a differential equation is the order of the highest derivative that appears in it: an equation containing ''y''⁽''ⁿ''⁾ but no higher derivative has order ''n''. Newton's second law of motion is a second-order equation because it involves a second derivative, whereas the heat and wave equations are first order in time and second order in space.
The '''order''' of a differential equation is the order of the highest derivative that appears in it: an equation containing ''y''⁽''ⁿ''⁾ but no higher derivative has order ''n''. The special case is when ''n''=1 AND there is no multiplication of two different orders of derivatives (i.e., no term containing ''yy'''), where the differential equation is said to be linear.
 
A differential equation is '''linear''' if the unknown function and its derivatives occur only to the first power and are never multiplied together; otherwise it is '''nonlinear'''. Linear homogeneous equations obey the superposition principle: any linear combination of solutions is again a solution. This principle underlies the method of Fourier series for the heat and wave equations. Nonlinearity, by contrast, typically makes closed-form solution impossible and produces qualitatively new behaviour, as the model equations below illustrate.
 
<uml>
@startuml
!theme bluegray
title A first classification of differential equations
 
rectangle "Differential equation" as DE
 
rectangle "Ordinary (ODE)\nunknown function of one\nindependent variable" as ODE {
  component "order: first, second, …" as O1
  component "linear / nonlinear" as O2
}
 
rectangle "Partial (PDE)\nunknown function of several\nindependent variables" as PDE {
  component "heat, wave, Laplace,\nSchrödinger, Navier–Stokes" as P1
  component "linear / nonlinear" as P2
}
 
DE --> ODE
DE --> PDE
 
@enduml
</uml>


== Differential equations as mathematical models ==
== Differential equations as mathematical models ==


When a question from physics, biology, chemistry or economics is turned into mathematics, the quantities whose evolution matters become the unknown functions, and the laws connecting their rates of change to the quantities themselves become differential equations. Together with a statement of the initial state, the resulting equation predicts the behaviour of the system at all later times.<ref>{{#cite:Q1576}}</ref><ref>{{#cite:Q1578}}</ref>
=== Mechanics ===


<uml>
==== Force and acceleration ====
@startuml
!theme bluegray
title From the world to a differential equation and back


node "Real-world system\n(mass on a spring, cooling body,\npopulation, pendulum)" as SYS
Newton's second law of motion states that the acceleration of a body is proportional to the net force acting on it:
node "Assumptions and laws\n(Newton's second law,\nempirical rate laws)" as ASM
node "Differential equation\nplus initial condition" as DEQ
node "Solution or simulation\nprediction of later behaviour" as SOL


SYS --> ASM : idealisation
{{#content:Q1583}}
ASM --> DEQ : translation into mathematics
DEQ --> SOL : analysis
SOL --> SYS : comparison with observation


@enduml
where ''x''(''t'') is the position of the body, ''m'' its mass, and the force ''F'' may itself depend on time, position and velocity.
</uml>


=== Mechanics ===
==== Harmonic oscillations ====  
 
Newton's second law of motion states that the acceleration of a body is proportional to the net force acting on it:


{{#content:Q1583}}
For a mass attached to a spring whose restoring force is linear in the displacement, this becomes the harmonic oscillator equation:
 
where ''x''(''t'') is the position of the body, ''m'' its mass, and the force ''F'' may itself depend on time, position and velocity. For a mass attached to a spring whose restoring force is linear in the displacement, this becomes the harmonic oscillator equation:


{{#content:Q1588}}
{{#content:Q1588}}
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[[File:Simple harmonic motion animation.gif|thumb|A mass on a spring executing simple harmonic motion, the solution of the harmonic oscillator equation. Credit: Evil saltine (public domain).]]
[[File:Simple harmonic motion animation.gif|thumb|A mass on a spring executing simple harmonic motion, the solution of the harmonic oscillator equation. Credit: Evil saltine (public domain).]]


=== Growth, decay and heat transfer ===
=== Exponential growth and decay ===


A quantity that changes at a rate proportional to its current size satisfies the exponential growth and decay equation:
A quantity that changes at a rate proportional to its current size satisfies the exponential growth or decay equation:


{{#content:Q1584}}
{{#content:Q1584}}
Line 108: Line 72:
{{#content:Q1585}}
{{#content:Q1585}}


so a population with unlimited resources grows exponentially (''k'' &gt; 0), whereas a radioactive substance, for which ''k'' &lt; 0, decays exponentially towards zero. Newton's law of cooling describes a body whose temperature ''T'' differs from a constant ambient temperature ''T''ₐ:
When ''k'' &gt; 0, it can describe a population with unlimited resources that grows exponentially, whereas ''k'' &lt; 0 describes a radioactive substance that decays exponentially towards zero.  
 
=== Heat transfer ===
 
Newton's law of cooling describes a body whose temperature ''T'' differs from a constant ambient temperature ''T''ₐ:


{{#content:Q1586}}
{{#content:Q1586}}


The temperature difference decays exponentially, so the body approaches the ambient temperature but never quite reaches it.<ref>{{#cite:Q1576}}</ref>
The temperature difference decays exponentially, so the body approaches the ambient temperature but never quite reaches it.<ref>{{#cite:Q1576}}</ref>
Real populations are not unlimited. The logistic equation adds a term that slows growth as the population ''P'' approaches a carrying capacity ''K'':
{{#content:Q1587}}
where ''r'' is the intrinsic growth rate. Solutions rise from a small initial population and level off at ''K'', giving the characteristic S-shaped curve of logistic growth.<ref>{{#cite:Q1576}}</ref>
=== A nonlinear example: the pendulum ===
An ideal pendulum, a mass on a rigid rod of length ''L'' swinging under gravity, obeys
{{#content:Q1589}}
where θ is the angle from the vertical and ''g'' the gravitational acceleration. The equation is nonlinear because sin θ is not a linear function of θ. For small oscillations, sin θ ≈ θ, and the equation reduces to the harmonic oscillator equation with frequency √(''g''/''L''). For larger swings the nonlinearity matters: the period lengthens and, if damping or driving is added, the pendulum exhibits the whole range of nonlinear phenomena, from limit cycles to chaos.<ref>{{#cite:Q1578}}</ref>


== Geometry of first-order equations ==
== Geometry of first-order equations ==
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=== Direction fields ===
=== Direction fields ===


A first-order equation of the form d''y''/d''x'' = ''f''(''x'', ''y''), as introduced above, assigns to every point (''x'', ''y'') the slope that a solution curve must have there. Drawing a short line segment of that slope at many points produces a direction field (or slope field), and every solution curve is a curve that stays tangent to the segments everywhere. Direction fields make the qualitative behaviour of solutions visible even when no closed-form solution exists.<ref>{{#cite:Q1576}}</ref>
As described above, a first-order equation has the explicit form  
d''y''/d''x'' = ''f''(''x'', ''y'')


[[File:Slope field of exponential growth.png|thumb|Direction field of the equation d''y''/d''x'' = ''y'', with several solution curves. Each segment shows the local slope; the solutions are exponential curves. Credit: jjbeard (public domain).]]
which assigns to every point (''x'', ''y'') the slope that a solution curve must have there.


The illustration shows the direction field of the exponential equation d''y''/d''x'' = ''y''. The field makes visible both the growth of the solution curves and the fact that through every point, apart from the special constant solution ''y'' = 0, exactly one solution curve passes.
Drawing a short line segment of that slope at many points produces a direction field (or slope field). Every solution curve must stay tangent to the field directions everywhere.  


=== Existence and uniqueness ===
[[File:Slope field of exponential growth.png|thumb|Direction field of the equation d''y''/d''x'' = ''y'', with several solution curves. Each segment shows the local slope; the solutions are exponential curves. Credit: jjbeard (public domain).]]


Because most differential equations cannot be solved in closed form, the first question about an equation is usually whether a solution exists and whether it is unique. This is asked for an initial value problem, which fixes the state of the system at a starting point ''x''₀:
As such, direction fields make the qualitative behaviour of solutions visible even when no closed-form solution exists.<ref>{{#cite:Q1576}}</ref>


{{#content:Q1582}}
== Solving differential equations ==
 
According to the Picard–Lindelöf theorem, if ''f'' is continuous in a neighbourhood of (''x''₀, ''y''₀) and satisfies a Lipschitz condition in ''y'' there, then a unique solution exists on some interval containing ''x''₀.<ref>{{#cite:Q1576}}</ref><ref>{{#cite:Q1577}}</ref> If ''f'' is merely continuous, a solution is still guaranteed to exist (the Peano existence theorem), but uniqueness may fail: the problem d''y''/d''x'' = 3''y''^⅔ with ''y''(0) = 0 has two different solutions through the origin, namely ''y''(''x'') = 0 and ''y''(''x'') = ''x''³, because the right-hand side is not Lipschitz continuous at ''y'' = 0.<ref>{{#cite:Q1576}}</ref>
 
Any explicit equation of order ''n'' can be rewritten as a system of ''n'' first-order equations by declaring the derivatives to be new unknown functions. This reduction to a first-order system is the starting point of most theory and of almost all numerical methods.<ref>{{#cite:Q1576}}</ref>


== Solving differential equations ==
<!-- what is closed form? what is open form? give examples for each of the classical methods-->


=== Analytical methods ===
=== Analytical methods ===
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=== Numerical methods ===
=== Numerical methods ===


<!-- show a graph -->
When no closed-form solution is available, solutions are approximated by numerical integration. The simplest scheme, Euler's method, advances an approximate solution ''y''ₙ at points ''x''ₙ = ''x''₀ + ''nh'' by repeatedly applying one step:
When no closed-form solution is available, solutions are approximated by numerical integration. The simplest scheme, Euler's method, advances an approximate solution ''y''ₙ at points ''x''ₙ = ''x''₀ + ''nh'' by repeatedly applying one step:


Line 172: Line 124:
=== Qualitative methods ===
=== Qualitative methods ===


<!-- simple, real-world examples -->
For nonlinear equations, and especially for systems of two or more equations, the geometry of solutions matters as much as their formulas. Qualitative analysis studies the equilibrium points at which the system does not change, the stability of those equilibria, and the way solutions flow between them in the phase plane; as parameters change, the behaviour can reorganise itself in bifurcations, and in three or more dimensions a system can settle onto a chaotic attractor, whose solutions are deterministic yet aperiodic and extremely sensitive to initial conditions.<ref>{{#cite:Q1578}}</ref>
For nonlinear equations, and especially for systems of two or more equations, the geometry of solutions matters as much as their formulas. Qualitative analysis studies the equilibrium points at which the system does not change, the stability of those equilibria, and the way solutions flow between them in the phase plane; as parameters change, the behaviour can reorganise itself in bifurcations, and in three or more dimensions a system can settle onto a chaotic attractor, whose solutions are deterministic yet aperiodic and extremely sensitive to initial conditions.<ref>{{#cite:Q1578}}</ref>


Line 178: Line 131:
[[File:Isaac Newton portrait.jpg|thumb|left|Portrait of Isaac Newton (after Godfrey Kneller, 1689). Newton's laws of motion and of universal gravitation, published in the ''Principia'' (1687), are differential equations. Credit: James Thronill after Godfrey Kneller (public domain).]]
[[File:Isaac Newton portrait.jpg|thumb|left|Portrait of Isaac Newton (after Godfrey Kneller, 1689). Newton's laws of motion and of universal gravitation, published in the ''Principia'' (1687), are differential equations. Credit: James Thronill after Godfrey Kneller (public domain).]]


Differential equations arose with the calculus that [[Person:Isaac Newton|Isaac Newton]] and [[Person:Gottfried Wilhelm Leibniz|Gottfried Wilhelm Leibniz]] developed independently in the late 17th century. Newton's laws of motion and of universal gravitation, published in his ''Principia'' of 1687, are differential equations, and solving them explained the orbits of the planets; Leibniz introduced the notation d''y''/d''x'' still used today. The first differential equations were solved by the brothers Jacob and Johann Bernoulli, and in the 18th century [[Person:Leonhard Euler|Leonhard Euler]] turned a collection of ad hoc tricks into a systematic theory, developing the general treatment of linear equations with constant coefficients, series methods, and the first numerical integration scheme, which still bears his name.<ref>{{#cite:Q1577}}</ref><ref>{{#cite:Q1576}}</ref>
Differential equations arose with the calculus that [[Person:Isaac Newton|Isaac Newton]] and [[Person:Gottfried Wilhelm Leibniz|Gottfried Wilhelm Leibniz]] developed independently in the late 17th century. Newton's laws of motion and of universal gravitation, published in his ''Principia'' of 1687, are differential equations. However, it was Leibniz who introduced the notation d''y''/d''x'' still used today.  
 
In the 18th century [[Person:Leonhard Euler|Leonhard Euler]] turned a collection of ad hoc tricks into a systematic theory, developing the general treatment of linear equations with constant coefficients, series methods, and the first numerical integration scheme, which still bears his name.<ref>{{#cite:Q1577}}</ref><ref>{{#cite:Q1576}}</ref>


[[File:Leonhard Euler portrait.jpg|thumb|Leonhard Euler (portrait by Jakob Emanuel Handmann, 1753). Euler created much of the systematic theory of differential equations and gave his name to Euler's method. Credit: Jakob Emanuel Handmann (public domain).]]
[[File:Leonhard Euler portrait.jpg|thumb|Leonhard Euler (portrait by Jakob Emanuel Handmann, 1753). Euler created much of the systematic theory of differential equations and gave his name to Euler's method. Credit: Jakob Emanuel Handmann (public domain).]]


Alongside the theory of ordinary equations, the 18th and 19th centuries created the partial differential equations of physics. Jean le Rond d'Alembert wrote down and solved the one-dimensional wave equation for the vibrating string in the 1740s, and Joseph Fourier derived the heat equation from the physics of conduction and solved it with trigonometric series in his ''Théorie analytique de la chaleur'' of 1822, founding Fourier analysis.<ref>{{#cite:Q1579}}</ref>
Alongside the theory of ordinary equations, the 18th and 19th centuries saw the development of partial differential equations of physics. Jean le Rond d'Alembert wrote down and solved the one-dimensional wave equation for the vibrating string in the 1740s, and Joseph Fourier derived the heat equation from the physics of conduction and solved it with trigonometric series in his ''Théorie analytique de la chaleur'' of 1822, founding Fourier analysis.<ref>{{#cite:Q1579}}</ref> [[Person:Augustin-Louis Cauchy|Augustin-Louis Cauchy]] and, later, Rudolf Lipschitz and Émile Picard placed the existence and uniqueness of solutions on a rigorous footing.<ref>{{#cite:Q1576}}</ref>  


[[Person:Augustin-Louis Cauchy|Augustin-Louis Cauchy]] and, later, Rudolf Lipschitz and Émile Picard placed the existence and uniqueness of solutions on a rigorous footing in the 19th century.<ref>{{#cite:Q1576}}</ref> In the 20th century, Henri Poincaré's qualitative approach grew into the modern theory of dynamical systems: in 1963 the meteorologist Edward Lorenz found chaotic behaviour in a simple system of three differential equations modelling atmospheric convection, a landmark in the study of nonlinear dynamics.<ref>{{#cite:Q1578}}</ref> Since the middle of the 20th century, numerical computing has made differential equations the everyday working tool of science and engineering that they are today.
The 20th century saw the development of the modern theory of dynamical systems. <!-- expand --> In 1963, meteorologist Edward Lorenz found chaotic behaviour in a simple system of three differential equations modelling atmospheric convection, a landmark in the study of nonlinear dynamics.<ref>{{#cite:Q1578}}</ref>  


== References ==
== References ==

Revision as of 12:37, 3 September 2026

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A differential equation is an equation that relates an unknown function to its own derivatives.

Two features are common to all differential equations:

  • the unknown is a function, not a number;
  • a solution is rarely unique, but instead often a family of functions containing arbitrary constants. A particular member of the solution family can be singled out by extra conditions, such as the state of the system at some time;

Types of differential equations

Ordinary and partial differential equations

Ordinary differential equations

An ordinary differential equation (ODE) describes an unknown function which depends on a single independent variable.

Writing the unknown as y(x), an ODE can be expressed in its implicit form:

F\bigl(x,y,y',y'',\ldots,y^{(n)}\bigr)=0

where F is a given function.

If the equation can be solved for the highest derivative, it takes an explicit form.

For a first-order equation:

\frac{dy}{dx}=f(x,y)

The right-hand side f(x, y) prescribes the slope of any solution function must have at point (x, y).


Partial differential equations

If the unknown function depends on two or more variables and partial derivatives appear, the equation is a partial differential equation (PDE).


Order and linearity

The order' of a differential equation is the order of the highest derivative that appears in it: an equation containing y⁽ⁿ⁾ but no higher derivative has order n. The special case is when n=1 AND there is no multiplication of two different orders of derivatives (i.e., no term containing yy), where the differential equation is said to be linear.

Differential equations as mathematical models

Mechanics

Force and acceleration

Newton's second law of motion states that the acceleration of a body is proportional to the net force acting on it:

m\frac{d^{2}x}{dt^{2}}=F

where x(t) is the position of the body, m its mass, and the force F may itself depend on time, position and velocity.

Harmonic oscillations

For a mass attached to a spring whose restoring force is linear in the displacement, this becomes the harmonic oscillator equation:

\frac{d^{2}x}{dt^{2}}+\omega_{0}^{2}x=0

whose solutions are sinusoidal oscillations at the natural frequency ω₀; such motion is called simple harmonic motion.

A mass on a spring executing simple harmonic motion, the solution of the harmonic oscillator equation. Credit: Evil saltine (public domain).

Exponential growth and decay

A quantity that changes at a rate proportional to its current size satisfies the exponential growth or decay equation:

\frac{dy}{dt}=k\,y

Its solutions are exponentials:

y(t)=y_{0}\,e^{kt}

When k > 0, it can describe a population with unlimited resources that grows exponentially, whereas k < 0 describes a radioactive substance that decays exponentially towards zero.

Heat transfer

Newton's law of cooling describes a body whose temperature T differs from a constant ambient temperature Tₐ:

\frac{dT}{dt}=-k\bigl(T-T_{a}\bigr)

The temperature difference decays exponentially, so the body approaches the ambient temperature but never quite reaches it.[1]

Geometry of first-order equations

Direction fields

As described above, a first-order equation has the explicit form dy/dx = f(x, y)

which assigns to every point (x, y) the slope that a solution curve must have there.

Drawing a short line segment of that slope at many points produces a direction field (or slope field). Every solution curve must stay tangent to the field directions everywhere.

Direction field of the equation dy/dx = y, with several solution curves. Each segment shows the local slope; the solutions are exponential curves. Credit: jjbeard (public domain).

As such, direction fields make the qualitative behaviour of solutions visible even when no closed-form solution exists.[1]

Solving differential equations

Analytical methods

For the relatively small class of equations that can be solved in closed form, a toolkit of classical methods exists:

  • first-order equations: separation of variables, integrating factors for linear equations, substitutions such as the Bernoulli substitution;
  • linear equations with constant coefficients: exponential trial solutions and the characteristic equation, variation of parameters;
  • equations with variable coefficients: power-series solutions about ordinary points and Frobenius series about regular singular points;
  • integral transforms, in particular the Laplace transform, which turns differential equations into algebraic ones;
  • for partial differential equations: separation of variables combined with Fourier series, and transform methods.

The theory of these methods is treated in standard textbooks on ordinary and partial differential equations.[2][3] Still, only a minority of differential equations, almost all of them linear, can be solved explicitly; most equations that arise in applications are treated by numerical or qualitative methods.[4]

Numerical methods

When no closed-form solution is available, solutions are approximated by numerical integration. The simplest scheme, Euler's method, advances an approximate solution yₙ at points xₙ = x₀ + nh by repeatedly applying one step:

y_{n+1}=y_{n}+h\,f(x_{n},y_{n})

More accurate and more stable methods, such as the Runge–Kutta family, are built on the same idea of using the differential equation to extrapolate from known values, and are implemented in essentially every numerical computing environment.[1]

Qualitative methods

For nonlinear equations, and especially for systems of two or more equations, the geometry of solutions matters as much as their formulas. Qualitative analysis studies the equilibrium points at which the system does not change, the stability of those equilibria, and the way solutions flow between them in the phase plane; as parameters change, the behaviour can reorganise itself in bifurcations, and in three or more dimensions a system can settle onto a chaotic attractor, whose solutions are deterministic yet aperiodic and extremely sensitive to initial conditions.[4]

History

Portrait of Isaac Newton (after Godfrey Kneller, 1689). Newton's laws of motion and of universal gravitation, published in the Principia (1687), are differential equations. Credit: James Thronill after Godfrey Kneller (public domain).

Differential equations arose with the calculus that Isaac Newton and Gottfried Wilhelm Leibniz developed independently in the late 17th century. Newton's laws of motion and of universal gravitation, published in his Principia of 1687, are differential equations. However, it was Leibniz who introduced the notation dy/dx still used today.

In the 18th century Leonhard Euler turned a collection of ad hoc tricks into a systematic theory, developing the general treatment of linear equations with constant coefficients, series methods, and the first numerical integration scheme, which still bears his name.[2][1]

Leonhard Euler (portrait by Jakob Emanuel Handmann, 1753). Euler created much of the systematic theory of differential equations and gave his name to Euler's method. Credit: Jakob Emanuel Handmann (public domain).

Alongside the theory of ordinary equations, the 18th and 19th centuries saw the development of partial differential equations of physics. Jean le Rond d'Alembert wrote down and solved the one-dimensional wave equation for the vibrating string in the 1740s, and Joseph Fourier derived the heat equation from the physics of conduction and solved it with trigonometric series in his Théorie analytique de la chaleur of 1822, founding Fourier analysis.[3] Augustin-Louis Cauchy and, later, Rudolf Lipschitz and Émile Picard placed the existence and uniqueness of solutions on a rigorous footing.[1]

The 20th century saw the development of the modern theory of dynamical systems. In 1963, meteorologist Edward Lorenz found chaotic behaviour in a simple system of three differential equations modelling atmospheric convection, a landmark in the study of nonlinear dynamics.[4]

References

  1. ↑ ↑ ↑ ↑ ↑ Boyce, W. E. (2012). Elementary Differential Equations and Boundary Value Problems (Book). In Elementary Differential Equations and Boundary Value Problems (Book). John Wiley & Sons.
  2. ↑ ↑ Tenenbaum, M. (1985). Ordinary Differential Equations (Book). In Ordinary Differential Equations (Book). Dover Publications.
  3. ↑ ↑ Strauss, W. A. (2008). Partial Differential Equations: An Introduction (Book). In Partial Differential Equations: An Introduction (Book). John Wiley & Sons.
  4. ↑ ↑ ↑ Strogatz, S. H. (2015). Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering (Book). In Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering (Book). Westview Press.

Further reading