Shot by Web of Stories.

The amount of detail in which he remembers all that happened is astounding. Not too different from the Murray Gell-Mann interview in that aspect.

Head of the theoretical division at the Los Alamos Laboratory during the Manhattan Project.

Richard Feynman was working under him there, and was promoted to team lead by him because Richard impressed Hans.

He was also the person under which Freeman Dyson was originally under when he moved from the United Kingdom to the United States.

And Hans also impressed Feynman, both were problem solvers, and liked solving mental arithmetic and numerical analysis.

This relationship is what brought Feynman to Cornell University after World War II, Hans' institution, which is where Feynman did the main part of his Nobel prize winning work on quantum electrodynamics.

Hans must have been the perfect PhD advisor. He's always smiling, and he seemed so approachable. And he was incredibly capable, notably in his calculation skills, which were much more important in those pre-computer days.

WTF is wrong with that family???

The Morphy number is a concept in the field of chess, specifically related to the analysis and evaluation of chess positions. It is named after the famous 19th-century American chess player Paul Morphy, known for his tactical prowess and ability to capitalize on the weaknesses of his opponents. The Morphy number measures the effectiveness of a piece's placement and its ability to contribute to a player's position.

Published on the session reports of the Royal Prussian Academy of Sciences at Berlin 1918 page 464.

Is about Maxwell's equations in curved spacetime, and notably introduces gauge theory.

Viewable for free at: archive.org/details/mobot31753002089727/page/464/mode/2up.

He was a leading figure at the MIT Radiation Laboratory, and later he was head at the Columbia University laboratory that carried out the crucial Lamb-Retherford experiment and the anomalous magnetic dipole moment of the electron published at The Magnetic Moment of the Electron by Kusch and Foley (1948) using related techniques.

Personal website: jakobschwichtenberg.com/

PhD at Karlsruhe Institute of Technology in 2019: www-kseta.ttp.kit.edu/fellows/Jakob.Schwichtenberg/ on the strong CP problem.

Books:

Pavle Savić could refer to a specific individual, and without more context, it's difficult to provide a precise answer. There might be several notable individuals with that name.

Pontryagin's Maximum Principle is a fundamental result in optimal control theory that provides necessary conditions for optimality in control problems. Formulated by the Soviet mathematician Lev Pontryagin in the 1950s, the principle is applied when aiming to maximize (or minimize) a given performance criterion over a system described by a set of differential equations.

Adaptive Coordinate Descent (ACD) is an optimization algorithm that is used to minimize a loss function in high-dimensional spaces. It is a variant of the coordinate descent method that incorporates adaptive features to improve performance, particularly in situations where the gradients can vary significantly in scale and direction.

Evolutionary algorithms (EAs) are a class of optimization algorithms inspired by the principles of natural evolution and selection. These algorithms are used to solve complex optimization problems by iteratively improving a population of candidate solutions based on ideas borrowed from biological evolution, such as selection, crossover (recombination), and mutation. ### Key Components of Evolutionary Algorithms 1. **Population**: A set of candidate solutions to the optimization problem.

Evolutionary programming (EP) is a type of evolutionary algorithm that is inspired by the process of natural evolution. It is a method used for solving optimization problems by mimicking the mechanisms of biological evolution, such as selection, mutation, and reproduction. The key characteristics and components of evolutionary programming include: 1. **Population**: EP operates on a population of candidate solutions (individuals). Each individual represents a potential solution to the optimization problem.

Basin-hopping is a global optimization technique used to find the minimum of a function that may have many local minima. It is particularly useful for problems where the objective function is complex, non-convex, or high-dimensional. The method combines two key components: local minimization and random sampling. Here's a brief overview of how basin-hopping works: 1. **Initial Guess**: The algorithm starts with an initial point in the search space.

The Bregman Lagrangian is a concept used in the field of optimization and variational analysis, particularly in connection with Bregman divergences. A Bregman divergence is a measure of difference between two points based on a convex function.

Cunningham's Rule is a guideline in the field of project management and scheduling that relates to the estimation of time required to complete tasks or projects. While it isn’t as widely known as other project management principles, it refers to a method for adjusting the estimated duration of tasks based on their complexity or difficulty.