Course

States and Operators

Introduction to unsupervised learning; dimensional reduction using principal component analysis

Standard Model Effective Field Theory and neutrino SM

Ghost Hilbert space 

Convolutional neural networks: local receptive fields, shared weights and biases, pooling

Spontaneous symmetry breaking continued, the puzzles of SM and the solutions

BRST quantization: a toy model, gauge fixing; BRST quantization for string theory, ghosts in String.

Monte Carlo sampling; summary of hyperparameters in feedforward neural networks

CKM matrix and spontaneous symmetry breaking

The string spectrum; BRST quantization, cohomological field theory, a basic model