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Teaching Materials

• 10.0 Ranking Grossman: Computational Nanoscience, Lecture ...

  Computational Nanoscience, Lecture 4: Geometry Optimization and Seeing What You're Doing

  Type	Teaching Materials
  Contributor(s)	Jeffrey C Grossman, Elif Ertekin
  Date	13 Feb. 2008
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  In this lecture, we discuss various methods for finding the ground state structure of a given system by minimizing its energy. Derivative and non-derivative methods are discussed, as well as the importance of the starting guess and how to find or generate good initial structures. We also briefly ...

• 9.9 Ranking Ertekin: Computational Nanoscience, Lecture ...

  Computational Nanoscience, Lecture 20: Quantum Monte Carlo, part I

  Type	Teaching Materials
  Contributor(s)	Elif Ertekin, Jeffrey C Grossman
  Date	20 May. 2008
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  This lecture provides and introduction to Quantum Monte Carlo methods. We review the concept of electron correlation and introduce Variational Monte Carlo methods as an approach to going beyond the mean field approximation. We describe briefly the Slater-Jastrow expansion of the wavefunction, and ...

• 9.8 Ranking Grossman: Computational Nanoscience, Lecture ...

  Computational Nanoscience, Lecture 21: Quantum Monte Carlo, part II

  Type	Teaching Materials
  Contributor(s)	Jeffrey C Grossman, Elif Ertekin
  Date	20 May. 2008
  Avg. Rating	5.0 out of 5 stars  (1)
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  This is our second lecture in a series on Quantum Monte Carlo methods. We describe the Diffusion Monte Carlo approach here, in which the approximation to the solution is not restricted by choice of a functional form for the wavefunction. The DMC approach is explained, and the fixed node ...