Lectures related to Replica Symmetric Models

Covers the theoretical background and applications of the 3-state Ising model.

Introduces the Potts model, a generalization of the Ising model used in statistical mechanics to study phase transitions.

Statistical Physics of Learning

Offers insights into the statistical physics of learning, exploring the relationship between neural network structure and disordered systems.

Renormalization Group in Field Theory

Explores the Renormalization Group in field theory, discussing scaling functions, critical exponents, and Gaussian fixed points.

Maximum of Gaussians

Explores the p-spin model in spin glass theory and the convergence to the Random Energy Model using Gaussian integrals and the replica method.

Approximation Landau: Ising Model

Explores the Landau approximation applied to the Ising model in statistical physics.

Molecular dynamics under constraints

Explores molecular dynamics simulations under holonomic constraints, focusing on numerical integration and algorithm formulation.

Statistical Physics: Systems Isolation

Explores statistical physics concepts in isolated systems, focusing on entropy and disorder.

Existence of Gibbs measures

Explores quasilocality in statistical mechanics and the existence conditions of Gibbs measures.

Electron Configurations and Quantum Physics

Explores electron configurations, quantum numbers, and the implications of electron spin.

Quantum Statistics: Canonical & Grand Canonical Ensembles

Explores quantum statistics in canonical and grand canonical ensembles, discussing distinguishability, microstates, and the Pauli exclusion principle.

Statistical Field Theory

Covers the basics of statistical field theory, focusing on Ising models and the Ginsburg-Landau theory.

Atomic Physics: Pauli Exclusion Principle and Periodic Table

Explores the Pauli exclusion principle, electron states in atoms, and the periodic table.

Random Field Ising Model on Graphs

Explores the Random Field Ising Model on random graphs, discussing belief propagation updates and population dynamics.

Replica Field Theory: Cavity and Replica Method

Explains the Replica Field Theory in RFIM, emphasizing the Cavity and Replica methods and the exponential dominance of certain values.

Conditional Entropy and Data Compression Techniques

Discusses conditional entropy and its role in data compression techniques.

Scientific Machine Learning: Introduction to Spin Glass Models

Introduces Scientific Machine Learning, emphasizing its application in various scientific fields and the connection between machine learning and physics.

Coarse Graining in Statistical Physics

Explores coarse graining in statistical physics, focusing on real space renormalization and the Ising model.

Universality and Rotational Invariance in Isoradial Graphs

Covers universality and rotational invariance in isoradial graphs and their implications in statistical mechanics.

Replica Symmetry Breaking: REM

Explores Replica Symmetry Breaking in the Random Energy Model, focusing on entropy and probability states.