Lectures related to Spin Glass Model: Replica Method

Quantum Chemistry

Explores quantum chemistry, covering the Heisenberg Uncertainty Principle and mathematical aspects of quantum mechanics.

Residue Theorem: Applications in Complex Analysis

Discusses the residue theorem and its applications in calculating complex integrals.

Advanced Analysis II: Differential Equations and Timers

Discusses advanced analysis concepts, focusing on differential equations and timers in microcontrollers.

Computational Quantum Physics

Explores computational methods in quantum physics, emphasizing exact diagonalization and space discretization techniques.

Taylor Series and Secant Method: Numerical Analysis Techniques

Discusses the Taylor series and secant method, focusing on their applications in numerical analysis and root-finding techniques.

Elliptic Problems: Model and Deformation

Covers elliptic problems related to a model and deformation, discussing concepts such as the model problem and deformation energy.

Root Finding Methods: Bisection and Secant Techniques

Covers root-finding methods, focusing on the bisection and secant techniques, their implementations, and comparisons of their convergence rates.

Scientific Computing in Neuroscience

Explores scientific computing in neuroscience, emphasizing the simulation of neurons and networks using tools like NEURON, NEST, and BRIAN.

Canonical Transformations: Properties and Applications

Explores canonical transformations, their properties, and applications in Hamiltonian mechanics, emphasizing their role in simplifying the analysis of complex systems.

Finite Differences and Finite Elements: Variational Formulation

Discusses finite differences and finite elements, focusing on variational formulation and numerical methods in engineering applications.

Introduction to Electronic Structure Methods: Quantum Mechanics Repetition

Covers electronic structure calculations using quantum mechanics and introduces fundamental concepts in computational quantum chemistry.

Trade-offs in Data and Time

Explores trade-offs between data and time in computational problems, emphasizing diminishing returns and continuous trade-offs.

Data-Driven Modeling in Neuroscience: Meenakshi Khosla

By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.

Verifying Single Qubit Hamiltonians

Covers the verification of single qubit Hamiltonians using various techniques and methods.

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Irreducible Representations of Rotations Group

Explores irreducible representations of the rotations group and their mathematical properties.

Computing leading eigenvalues of the transfer operator

Explores computing the leading eigenvalue of a transfer operator beyond periodic points, focusing on mathematical settings, spectral radius estimation, and the Zaremba Conjecture.

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.

Computational Quantum Physics

Covers path-integral ground state methods and Monte Carlo simulations in computational quantum physics.

Numerical Integration: Order and Convergence

Explores numerical integration order and convergence for accuracy in numerical methods.