[Illinois] PHYS466 2013 Lecture 15: Sampling

By David M. Ceperley

Department of Physics, University of Illinois at Urbana-Champaign, Urbana, IL

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Abstract


Bio

Professor Ceperley received his BS in physics from the University of Michigan in 1971 and his Ph.D. in physics from Cornell University in 1976. After one year at the University of Paris and a second postdoc at Rutgers University, he worked as a staff scientist at both Lawrence Berkeley and Lawrence Livermore National Laboratories. In 1987, he joined the Department of Physics at Illinois. Professor Ceperley is a staff scientist at the National Center for Supercomputing Applications at Illinois.

Professor Ceperley's work can be broadly classified into technical contributions to quantum Monte Carlo methods and contributions to our physical or formal understanding of quantum many-body systems. His most important contribution is his calculation of the energy of the electron gas, providing basic input for most numerical calculations of electronic structure. He was one of the pioneers in the development and application of path integral Monte Carlo methods for quantum systems at finite temperature, such as superfluid helium and hydrogen under extreme conditions.

Professor Ceperley is a Fellow of the American Physical Society and a member of the American Academy of Arts and Sciences. He was elected to the National Academy of Sciences in 2006.

Cite this work

Researchers should cite this work as follows:

  • David M. Ceperley (2013), "[Illinois] PHYS466 2013 Lecture 15: Sampling," https://nanohub.org/resources/18086.

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University of Illinois, Urbana-Champaign, IL

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University of Illinois at Urbana-Champaign

Tags

[Illinois] Phys 466 Lecture 15: Sampling
  • Discrete Distributions 1. Discrete Distributions 0
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  • Continuous Distributions 2. Continuous Distributions 187.04731569733516
    00:00/00:00
  • Discrete Distributions 3. Discrete Distributions 484.70917225950785
    00:00/00:00
  • Rejection technique 4. Rejection technique 484.95710533994747
    00:00/00:00
  • Composition method 5. Composition method 891.56735726096679
    00:00/00:00
  • Normal distribution 6. Normal distribution 1021.6082579515612
    00:00/00:00
  • Example: Box-Mueller Code to sample a Normal Distribution 7. Example: Box-Mueller Code to s… 1029.6660830658498
    00:00/00:00
  • Multivariate normal distributions 8. Multivariate normal distributi… 1213.2605291314073
    00:00/00:00
  • Bias 9. Bias 1566.1932691372435
    00:00/00:00
  • Reduction of Variance 10. Reduction of Variance 1566.9370683785623
    00:00/00:00
  • Importance Sampling 11. Importance Sampling 2312.4718412605775
    00:00/00:00
  • Finding Optimal p*(x) for Sampling 12. Finding Optimal p*(x) for Samp… 2323.2569302597026
    00:00/00:00
  • Example of importance sampling 13. Example of importance sampling 2503.0084135784459
    00:00/00:00