Duration: (20:36) ?Subscribe5835 2025-02-14T00:30:04+00:00
8.EFTx, Module 1 Lecture 1, Introduction to Effective Field Theory
(17:56)
8 EFTx Module 2 Lecture 1, Bottom Quarks in Hydrogen
(15:)
8.EFTx, Module 52 Lecture 14, NonRelativistic Conformal Symmetry and Wigner's SU(4)
(21:21)
8.EFTx, Module 39 Lecture 10, Renormalons in Quantum Field Theory
(45:48)
8.EFTx, Module 4 Lecture 1, Standard Model as an EFT
(19:20)
8.EFTx, Module 93 Lecture 25, Rapidity Divergences in SCET2
(48:41)
8.EFTx, Module 48 Lecture 12, EFT with a Fine Tuning
(20:36)
1. Introduction to Effective Field Theory (EFT)
(1:19:40)
Effective Field Theories in Nuclear and Particle Physics (Part 1)
(1:35:24)
Why is Mathematics so Unreasonably Effective in Physics ? I Dr. Pervez Hoodbhoy
(51:14)
Rupert FRANK - 1/3 A microscopic derivation of Ginzburg-Landau theory
(1:1:20)
Lecture 5: Complex Scalar Field Theory and Anti-Particle
(1:19:42)
An Euler System for the Symmetric Square of a Modular Form - Chris Skinner
(1:12:54)
W mass in SMEFT discussion
(1:13:54)
Watch this first! Advanced quantum field theory, Lecture 8
(1:29:13)
Quantum Field Theory I Lecture 8: Cross sections. LSZ reduction formula. Dimensional regularization.
(1:31:51)
Introduction to conformal field theory, Lecture 1
(1:20:27)
8.EFTx, Module 27 Lecture 7, ChPT power counting theorem
(13:39)
8.EFTx, Module 59 Lecture 15, Collinear Propagator \u0026 Power Counting
(18:15)
8.EFTx, Module 14 Lecture 4, Counterterms
(19:59)
8.EFTx, Module 53 Lecture 14, Detueron Bound State in a NonRelativistic EFT
(28:27)
8.EFTx, Module 78 Lecture 21, Cusp Anomalous Dimension
(6:1econd)
8.EFTx, Module 44 Lecture 12, Renormalon Pole is Landau Pole
(20:38)
8.EFTx, Module 54 Lecture 14, Coupling to Conserved Charges, Axion Example
(8:4)
8.EFTx, Module 94 Lecture 26, Rapidity Renormalization Group
(30:35)
8.EFTx, Module 83 Lecture 22, When do we have Convolutions?
(12:53)
8.EFTx, Module 89 Lecture 24, SCET2
(32:54)
8.EFTx, Module 38 Lecture 10, OPE for Heavy Quark Effective Theory
(19:14)
8.EFTx, Module 50 Lecture 13, Fine Tuning via Matching
(23:46)