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This book provides an ideal introduction to the use of Feynman path integrals in the fields of quantum mechanics and statistical physics. It is written for graduate students and researchers in physics, mathematical physics, applied mathematics as well as chemistry. The material is presented in an accessible manner for readers with little knowledge of quantum mechanics and no prior exposure to path integrals. It begins with elementary concepts and a review of quantum mechanics that gradually builds the framework for the Feynman path integrals and how they are applied to problems in quantum mechanics and statistical physics. Problem sets throughout the book allow readers to test their understanding and reinforce the explanations of the theory in real situations.
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Machine Learning: An Applied Mathematics Introduction
Machine Learning: An Applied Mathematics Introduction
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$14.99
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Div, Grad, Curl, and All That: An Informal Text on Vector Calculus
Div, Grad, Curl, and All That: An Informal Text on Vector Calculus
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$19.99
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