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David M. Ceperley

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  1. [Illinois] PHYS 466 Lecture 12: Constraints

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    08 Mar 2013 | Online Presentations | Contributor(s): David M. Ceperley

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  2. [Illinois] PHYS 466 Lecture 13: Random Number Generators

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    08 Mar 2013 | Online Presentations | Contributor(s): David M. Ceperley

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  3. [Illinois] PHYS 466 Lecture 9: Correlations II

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    08 Mar 2013 | Online Presentations | Contributor(s): David M. Ceperley

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  4. [Illinois] PHYS 466 Lecture 10: Dynamics

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    06 Mar 2013 | Online Presentations | Contributor(s): David M. Ceperley

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  5. [Illinois] PHYS 466 Lecture 8: Correlations I

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    06 Mar 2013 | Online Presentations | Contributor(s): David M. Ceperley

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  6. [Illinois] PHYS 466 Lecture 7: Atomic Potential

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    04 Mar 2013 | Online Presentations | Contributor(s): David M. Ceperley

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  7. [Illinois] PHYS 466: Atomic Scale Simulations

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    06 Feb 2013 | Courses | Contributor(s): David M. Ceperley

    Application of Monte Carlo and Molecular Dynamics techniques in primarily classical simulations to understand and predict properties of microscopic systems in materials science, physics, biology, and chemistry. Numerical algorithms, connections between simulation results and real properties of …

  8. [Illinois] PHYS 466 Lecture 4: Molecular Dynamics I

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    06 Feb 2013 | Online Presentations | Contributor(s): David M. Ceperley

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  9. [Illinois] PHYS 466 Lecture 6: Interatomic Potentials

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    06 Feb 2013 | Online Presentations | Contributor(s): David M. Ceperley, NanoBio Node

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  10. [Illinois] PHYS 466 Lecture 3: Basics of Mechanical Statistics

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    06 Feb 2013 | Online Presentations | Contributor(s): David M. Ceperley, NanoBio Node

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  11. Illinois PHYS 466, Lecture 19: The Ising Model

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    01 Jun 2009 | Online Presentations | Contributor(s): David M. Ceperley, Omar N Sobh

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  12. Illinois PHYS 466, Lecture 18: Kinetic Monte Carlo (KMC)

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    04 May 2009 | Online Presentations | Contributor(s): David M. Ceperley, Omar N Sobh

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  13. Illinois PHYS 466, Lecture 17: Simulation of Polymers

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    30 Apr 2009 | Online Presentations | Contributor(s): David M. Ceperley, Omar N Sobh

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  14. Illinois PHYS 466, Lecture 16: Free Energies from Simulations

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    28 Apr 2009 | Online Presentations | Contributor(s): David M. Ceperley, Omar N Sobh

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  15. Illinois PHYS 466, Lecture 15: Constraints

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    22 Apr 2009 | Online Presentations | Contributor(s): David M. Ceperley, Omar N Sobh

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  16. Illinois PHYS 466, Lecture 14: Neighbor Tables, Long-Range Potentials, Ewald Sums

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    22 Apr 2009 | Online Presentations | Contributor(s): David M. Ceperley, Omar N Sobh

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  17. Illinois PHYS 466, Lecture 13: Brownian Dynamics

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    08 Apr 2009 | Online Presentations | Contributor(s): David M. Ceperley

    Brownian Dynamics Let’s explore the connection between Brownian motion and Metropolis Monte Carlo. Why? Connection with smart MC Introduce the idea of kinetic Monte Carlo Get rid of solvent degrees of freedom and have much longer time steps. Content: Local Markov process …

  18. Illinois PHYS 466, Lecture 12: Random Walks

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    30 Mar 2009 | Online Presentations | Contributor(s): David M. Ceperley

    Random Walks Today we will discuss Markov chains (random walks), detailed balance and transition rules. These methods were introduced by Metropolis et al. in 1953 who applied it to a hard sphere liquid. It is one of the most powerful and used algorithms Content: Equation of …

  19. Illinois PHYS 466, Lecture 11: Importance Sampling

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    20 Mar 2009 | Online Presentations | Contributor(s): David M. Ceperley

    Importance sampling Today We will talk about the third option: Importance sampling and correlated sampling Content: Importance Sampling Finding Optimal p*(x) for Sampling Example of importance sampling What are allowed values of a? What does infinite variance look like? General …

  20. Illinois PHYS 466, Lecture 10: Sampling

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    20 Mar 2009 | Online Presentations | Contributor(s): David M. Ceperley, Omar N Sobh

    Fundamentals of Monte Carlo What is Monte Carlo? Named at Los Alamos in 1940’s after the casino. Any method which uses (pseudo)random numbers> as an essential part of the algorithm. Stochastic - not deterministic! A method for doing highly dimensional integrals by sampling the …

  21. Illinois PHYS 466, Lecture 9: Probability tools & Random number generators

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    03 Mar 2009 | Online Presentations | Contributor(s): David M. Ceperley

    Random Number Generation (RNG) read “Numerical Recipes” on random numbers and chi-squared test Today we discuss how to generate and test random numbers. What is a random number? A single number is not random.Only an infinite sequence can be described as random. Random means the …

  22. Illinois PHYS 466, Lecture 8: Temperature and Pressure Controls

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    03 Mar 2009 | Online Presentations | Contributor(s): David M. Ceperley

    Temperature and Pressure Controls Content: Constant Temperature MD Quench method Brownian dynamics/Anderson thermostat Nose-Hoover thermostat (FS 6.1.2) Nose-Hoover thermodynamics Effect of thermostat Comparison of Thermostats Constant pressure or constant volume Constant …

  23. Illinois PHYS 466, Lecture 6: Scalar Properties and Static Correlations

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    03 Mar 2009 | Online Presentations | Contributor(s): David M. Ceperley

    Scalar Properties, Static Correlations and Order Parameters What do we get out of a simulation? Static properties: pressure, specific heat, etc. Density Pair correlations in real space and Fourier space Order parameters and broken symmetry: How to tell a liquid from a solid Dynamical …

  24. Illinois PHYS 466, Lecture 7: Dynamical Correlations & Transport Coefficients

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    02 Mar 2009 | Online Presentations | Contributor(s): David M. Ceperley

    Dynamical correlations and transport coefficients Dynamics is why we do molecular dynamics! Perturbation theory Linear-response theory Diffusion constants, velocity-velocity auto correlation fct. Transport coefficients Diffusion: Particle flux Viscosity: …

  25. Illinois PHYS 466, Lecture 5: Interatomic Potentials

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    18 Feb 2009 | Online Presentations | Contributor(s): David M. Ceperley

    Interatomic Potentials Before we can start a simulation, we need the model! Interaction between atoms and molecules is determined by quantum mechanics But we don’t know V(R)! Content: The electronic-structure problem Born-Oppenheimer (1927) Approximation Semi-empirical …

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