Computational Quantum Physics

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Computational Science and Engineering: Master Program Overview

Outlines the Master in Computational Science and Engineering program at EPFL, detailing its structure, projects, and career opportunities for graduates.

Double Slit Experiment and Quantum Information Processing

Explores the historical development of quantum mechanics and information theory, focusing on the double slit experiment and quantum phenomena.

Quantum Physics: Exercises on General Physics

Covers exercises related to quantum physics and mathematical calculations involving trigonometric functions.

Efficient Stochastic Numerical Methods

Explores efficient stochastic numerical methods for modeling and learning, covering topics like the Analytical Engine and kinase inhibitors.

Stochastic numerical methods for many-body quantum systems

Explores stochastic methods for quantum systems, including exact diagonalization, variational methods, neural networks, and machine learning.

Density Operators in Quantum Physics II

Explores density operators in quantum physics, emphasizing their role in describing quantum system states.

Quantum Physics: Wave Nature and Measurement Interpretation

Explores wave nature, Schrödinger's equation solutions, and quantum measurement interpretation.

Quantum Mechanics: Sidney Coleman's Lecture

Explores Sidney Coleman's humorous take on Quantum Mechanics, emphasizing deterministic evolution and the challenges of interpreting quantum reality.

Quantum to Classical Mechanics: MD & MC Simulations

Covers Molecular Dynamics and Monte Carlo Simulations, transitioning from Quantum to Classical Mechanics in computational chemistry.

Quantum Physics: Historical Introduction and Schtenger-Lach Experiment

Delves into the historical development and significance of quantum physics, highlighting the failure of classical physics and the key Schtenger-Lach experiment.