Renormalization: Why Bigger is Simpler
A submission to #SoME2. A short introduction to renormalization techniques as they appear in statistical physics, aiming to simplify the mathematics as much as possible. The goal is to explain why matter becomes simpler as you zoom out from the microscopic, and how this leads naturally to
From playlist Summer of Math Exposition 2 videos
Renormalization: The Art of Erasing Infinity
Renormalization is perhaps one of the most controversial topics in high-energy physics. On the surface, it seems entirely ad-hoc and made up to subtract divergences which appear in particle physics calculations. However, when we dig a little deeper, we see that renormalization is nothing t
From playlist Standard Model
Understanding and computing the Riemann zeta function
In this video I explain Riemann's zeta function and the Riemann hypothesis. I also implement and algorithm to compute the return values - here's the Python script:https://gist.github.com/Nikolaj-K/996dba1ff1045d767b10d4d07b1b032f
From playlist Programming
Simplify the Negation of Statements with Quantifiers and Predicates
This video provides two examples of how to determine simplified logically equivalent statements containing quantifiers and predicates. mathispower4u.com
From playlist Symbolic Logic and Proofs (Discrete Math)
Dirichlet Eta Function - Integral Representation
Today, we use an integral to derive one of the integral representations for the Dirichlet eta function. This representation is very similar to the Riemann zeta function, which explains why their respective infinite series definition is quite similar (with the eta function being an alte rna
From playlist Integrals
The Field With One Element and The Riemann Hypothesis (Full Video)
A crash course of Deninger's program to prove the Riemann Hypothesis using a cohomological interpretation of the Riemann Zeta Function. You can Deninger talk about this in more detail here: http://swc.math.arizona.edu/dls/ Leave some comments!
From playlist Riemann Hypothesis
Lecture: Numerical Differentiation Methods
From simple Taylor series expansions, the theory of numerical differentiation is developed.
From playlist Beginning Scientific Computing
An Introduction to Gauge/gravity duality and Holographic... (Lecture 2) by Kostas Skenderis
PROGRAM NONPERTURBATIVE AND NUMERICAL APPROACHES TO QUANTUM GRAVITY, STRING THEORY AND HOLOGRAPHY (HYBRID) ORGANIZERS: David Berenstein (University of California, Santa Barbara, USA), Simon Catterall (Syracuse University, USA), Masanori Hanada (University of Surrey, UK), Anosh Joseph (II
From playlist NUMSTRING 2022
Functional Renormalisation Group Approach to Turbulence by Léonie Canet
PROGRAM TURBULENCE: PROBLEMS AT THE INTERFACE OF MATHEMATICS AND PHYSICS ORGANIZERS Uriel Frisch (Observatoire de la Côte d'Azur and CNRS, France), Konstantin Khanin (University of Toronto, Canada) and Rahul Pandit (IISc, India) DATE & TIME 16 January 2023 to 27 January 2023 VENUE Ramanuj
From playlist Turbulence: Problems at the Interface of Mathematics and Physics 2023
Constructing a solution of the 2D Kardar-Parisi-Zhang equation (Lecture - 03) by Sourav Chatterjee
INFOSYS-ICTS RAMANUJAN LECTURES SOME OPEN QUESTIONS ABOUT SCALING LIMITS IN PROBABILITY THEORY SPEAKER Sourav Chatterjee (Stanford University, California, USA) DATE & TIME 14 January 2019 to 18 January 2019 VENUE Madhava Lecture Hall, ICTS campus GALLERY Lecture 1: Yang-Mills for mathemat
From playlist Infosys-ICTS Ramanujan Lectures
Ian Alevy: "Renormalizable Rectangle Exchange Maps"
Asymptotic Algebraic Combinatorics 2020 "Renormalizable Rectangle Exchange Maps" Ian Alevy - University of Rochester Abstract: A domain exchange map (DEM) is a dynamical system defined on a smooth Jordan domain which is a piecewise translation. We explain how to use cut-and-project sets
From playlist Asymptotic Algebraic Combinatorics 2020
Fluid Turbulence, Thermal Noise and Spontaneous Stochasticity - Gregory Eyink
Workshop on Turbulence Topic: Fluid Turbulence, Thermal Noise and Spontaneous Stochasticity Speaker: Gregory Eyink Affiliation: Johns Hopkins University Date: December 11, 2020 For more video please visit http://video.ias.edu
From playlist Mathematics
The Fourier Transform and Derivatives
This video describes how the Fourier Transform can be used to accurately and efficiently compute derivatives, with implications for the numerical solution of differential equations. Book Website: http://databookuw.com Book PDF: http://databookuw.com/databook.pdf These lectures follow
From playlist Fourier
Convolution Theorem: Fourier Transforms
Free ebook https://bookboon.com/en/partial-differential-equations-ebook Statement and proof of the convolution theorem for Fourier transforms. Such ideas are very important in the solution of partial differential equations.
From playlist Partial differential equations
Cosmology Lunch Discussion - April 4, 2022
Topic 1: The two-loop bispectrum of large-scale structure Topic 2: Theoretical modeling of probability distribution function for cosmological counts in cell Abstract 1: The bispectrum is the leading non-Gaussian statistic in large-scale structure, providing complementary information to the
From playlist IAS/PU Cosmology Discussion
Evaluating the composition of Functions
👉 Learn how to evaluate an expression with the composition of a function and a function inverse. Just like every other mathematical operation, when given a composition of a trigonometric function and an inverse trigonometric function, you first evaluate the one inside the parenthesis. We
From playlist Evaluate a Composition of Inverse Trigonometric Functions