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Related lectures (27)

Covers fluid quantities, moments of kinetic equation, two-fluid model, and plasma turbulence simulation.

Covers the concept of moments of the distribution function in plasma physics and their relation to fluid dynamics.

Explores turbulence characteristics, simulation methods, and modeling challenges, providing guidelines for choosing and validating turbulence models.

Plasma Physics: Self-consistent Description

Covers the self-consistent description of a plasma and conservation principles.

Kinetic Theory: Distribution Function Evolution

Explores the evolution of the distribution function describing particles in phase space.

Continuous Random Variables

Explores continuous random variables, density functions, joint variables, independence, and conditional densities.

Probability and Statistics

Explores joint random variables, conditional density, and independence in probability and statistics.

Plasma Physics: Impact Ionisation and Random Walk

Explores impact ionisation in plasma physics and the random walk model as a key challenge in understanding plasma confinement.

MHD Model: One-Fluid Variables

Covers the derivation of the one-fluid model for Magneto-hydro dynamics (MHD) by introducing one-fluid variables.

Brownian Motion: Fundamentals and Applications

Explores the fundamentals of Brownian motion, including particle positions and distribution functions.

Turbulent Caminar Visualization

Explores turbulent caminar visualization, current lines, and the significance of turbulence in classical physics and research.

Continuous Random Variables

Covers continuous random variables, probability density functions, and distributions, with practical examples.

Fundamental Limits of Gradient-Based Learning

Delves into the fundamental limits of gradient-based learning on neural networks, covering topics such as binomial theorem, exponential series, and moment-generating functions.

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Collisionless Boltzmann Equation

Explores the Collisionless Boltzmann equation, distribution functions, Jeans theorems, resonances, chaotic orbits, and equilibria in stellar systems.

Normal Distribution: Properties and Calculations

Covers properties and calculations related to the normal distribution, including probabilities and quantiles.

Causal Systems & Transforms: Delay Operator Interpretation

Covers z Variable as a Delay Operator, realizable systems, probability theory, stochastic processes, and Hilbert Spaces.

Martingales and Brownian Motion: Reflection Principle

Explores the reflection principle in martingales and Brownian motion, simplifying probability calculations.

From Boltzmann to Vlasov equation

Discusses the derivation of Vlasov equation from Boltzmann equation, conservation laws, and formal solutions.

Random Vectors & Distribution Functions

Covers random vectors, joint distribution, conditional density functions, independence, covariance, correlation, and conditional expectation.