Lectures related to Computing leading eigenvalues of the transfer operator

Explores the construction of the Lebesgue function on the Cantor set and its unique properties.

Explores countable and uncountable sets, Cantor set, Mandelbrot set, and Box dimension in nonlinear dynamics and complex systems.

Explores the Hausdorff dimension of Brownian motion zeros, demonstrating a dimension of 1/2 with certainty.

Introduces measurable sets, functions, and the Cantor set properties, including ternary development of numbers.

Explores transfer operators, Patterson-Sullivan measure, FUP, spectral gaps, and resonances in Schottky groups.

Discusses eigenvalues, their calculation methods, and their applications in optimization and numerical analysis.

Explores a change of variable formula and the intriguing Devil's Staircase.

Explores eigenvalues, eigenvectors, and methods for solving linear systems with a focus on rounding errors and preconditioning matrices.

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

Covers the analysis of linear systems, focusing on methods such as Jacobi and Richardson for solving linear equations.

Explores equilibria and stability analysis in multivariable control systems, focusing on eigenvalues and system modes.

Covers the process of diagonalizing matrices, focusing on symmetric matrices and the spectral theorem.

Explores stability analysis in linear systems, emphasizing eigenvalues, eigenvectors, and stable manifolds.

Explores stability in linear 2D systems, covering fixed points, vector fields, and phase portraits.

Discusses the Fourier transform and its application to solving differential equations, focusing on the wave equation and its transformations.

Explores linear recurrences, applications between sets, and the significance of functions and operators in mathematics and physics.

Covers quantum eigenfunctions and the importance of A and B commuting for the same set of eigenfunctions.

Covers selected topics in mathematics, including Taylor approximations and algebraic structures of Z and K[X].

Covers the calculation of eigenvalues and eigenvectors, emphasizing their significance and applications.

Explores eigenvalues, eigenvectors, diagonalization, and spectral theorem in linear algebra.