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. See List of named differential equations. Software Some CAS software can solve differential equations. These CAS software and their commands are worth mentioning: Maple: dsolve Mathematica: DSolve[] Maxima: ode2(equation, y, x) SageMath: desolve() SymPy: sympy.solvers.ode.dsolve(equation) Xcas: desolve(y'=k*y,y) See also Exact differential equation Functional differential equation Initial condition Integral equations Numerical methods for ordinary differential equations Numerical methods for partial differential equations Picard–Lindelöf theorem on existence and uniqueness of solutions Recurrence relation, also known as 'difference equation' Abstract differential equation System of differential equations References Further reading In University of Michigan Historical Math Collection External links Lectures on Differential Equations MIT Open CourseWare Videos Online Notes / Differential Equations Paul Dawkins, Lamar University Differential Equations, S.O.S. Mathematics Introduction to modeling via differential equations Introduction to