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Random number generators a la Boltzmann

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dc.contributor.advisor Ansumali, Santosh
dc.contributor.author Agrawal, Samarth
dc.date.accessioned 2019-07-26T10:34:01Z
dc.date.available 2019-07-26T10:34:01Z
dc.date.issued 2018-06-23
dc.identifier.citation Agrawal, Samarth. 2018, Random number generators a la Boltzmann, MS thesis, Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru en_US
dc.identifier.uri https://libjncir.jncasr.ac.in/xmlui/handle/10572/2723
dc.description.abstract In the last few decades, simulations of stochastic processes have gained prominence in many elds of science and engineering. These simulations rely on Random Number generators (RNGs), routines that produce seemingly random sequence of numbers. Currently two paradigms exist for building RNGs | extracting noise from physical devices and complicated mathematical constructs based mostly on number theory. In this thesis we show that a synergy of these two paradigms, that a simulation of a stochastic process can in fact form the basis of an RNG. We illustrate this via simulating gas molecules which follow a collectively chaotic motion. This thesis also shows that various numerical schemes that can solve for hydrodynamics at a mesoscopic level generate random sequences of numbers. We propose a new algorithm with these concepts as foundation that can generate Gaussian and exponential random numbers orders-of-magnitude faster than existing methods. By employing this algorithm we simulate reaction-di usion problem and binary gas mixtures modeled at a mesoscopic level. vii en_US
dc.language.iso English en_US
dc.publisher Jawaharlal Nehru Centre for Advanced Scientific Research en_US
dc.rights © 2018 JNCASR
dc.subject Boltzmann statistics en_US
dc.subject Kinetic theories en_US
dc.subject Rarefied gases en_US
dc.title Random number generators a la Boltzmann en_US
dc.type Thesis en_US
dc.type.qualificationlevel Master en_US
dc.type.qualificationname MS-Engg en_US
dc.publisher.department Engineering Mechanics Unit (EMU) en_US


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