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Lecture
Molecular Dynamics and Monte Carlo: Computational Environment
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Molecular Dynamics Simulation: Trp-cage Miniprotein
Covers MD simulation of the Trp-cage miniprotein, focusing on implicit solvent modeling and practical analysis of simulation results.
Imaginary-Time Path Integrals
Covers Imaginary-Time Path Integrals, classical and quantum systems, convergence in simulations, and integration schemes for molecular dynamics.
Hybrid QM/MM Approaches
Covers Hybrid QM/MM Approaches, explaining system partitioning, MM potential forms, and practical QM/MM implementation.
Scientific Computing in Neuroscience
Explores scientific computing in neuroscience, emphasizing the simulation of neurons and networks using tools like NEURON, NEST, and BRIAN.
Quantum to Classical Mechanics: MD & MC Simulations
Covers Molecular Dynamics and Monte Carlo Simulations, transitioning from Quantum to Classical Mechanics in computational chemistry.
Modeling Prisoner's Dilemma: Naive vs. Optimal
Explores the modeling of the '100 prisoners' problem and compares naive and optimal approaches.
Integration Algorithms for Molecular Dynamics
Explores various Verlet algorithms for molecular dynamics simulations, emphasizing accuracy and efficiency.
Biased Monte Carlo Markov Chain
Explores Biased Monte Carlo Markov Chain, including Bayes-optimal estimation and Metropolis-Hastings algorithm.
Molecular Dynamics: Liquid Argon Simulation
Covers the molecular dynamics simulation of liquid argon using Lennard-Jones potential and focuses on equilibration and velocity distribution at equilibrium.
Scientific Computing in Neuroscience
Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.