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Dirichlet problem
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==History== {{unreferenced section|date=June 2021}} The Dirichlet problem goes back to [[George Green (mathematician)|George Green]], who studied the problem on general domains with general boundary conditions in his ''Essay on the Application of Mathematical Analysis to the Theories of Electricity and Magnetism'', published in 1828.<ref>{{cite arXiv |eprint=0807.0088 |last1=Green |first1=George |title=An Essay on the Application of mathematical Analysis to the theories of Electricity and Magnetism |date=2008 |class=physics.hist-ph }}</ref> He reduced the problem into a problem of constructing what we now call [[Green's function]]s, and argued that Green's function exists for any domain. His methods were not rigorous by today's standards, but the ideas were highly influential in the subsequent developments. The next steps in the study of the Dirichlet's problem were taken by [[Karl Friedrich Gauss]], William Thomson ([[Lord Kelvin]]) and [[Peter Gustav Lejeune Dirichlet]], after whom the problem was named, and the solution to the problem (at least for the ball) using the [[Poisson kernel]] was known to Dirichlet (judging by his 1850 paper submitted to the Prussian academy). Lord Kelvin and Dirichlet suggested a solution to the problem by a [[variational method]] based on the minimization of "Dirichlet's energy". According to Hans Freudenthal (in the ''Dictionary of Scientific Biography'', vol. 11), [[Bernhard Riemann]] was the first mathematician who solved this variational problem based on a method which he called [[Dirichlet's principle]]. The existence of a unique solution is very plausible by the "physical argument": any charge distribution on the boundary should, by the laws of [[electrostatics]], determine an [[electrical potential]] as solution. However, [[Karl Weierstrass]] found a flaw in Riemann's argument, and a rigorous proof of existence was found only in 1900 by [[David Hilbert]], using his [[direct method in the calculus of variations]]. It turns out that the existence of a solution depends delicately on the smoothness of the boundary and the prescribed data.
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