Science and math

Oskar Morgenstern

Oskar Morgenstern (January 24, 1902 – July 26, 1977) was a German-born economist. In collaboration with mathematician John von Neumann, he founded the mathematical field of game theory as applied to the social sciences and strategic decision-making (see von Neumann–Morgenstern utility theorem).

Companies he served as founder/co-founder of included Market Research Corporation of America, Mathematica and Mathematica Policy Research.

https://en.wikipedia.org/wiki/Oskar_Morgenstern

Hilbert space

In mathematicsHilbert spaces (named after David Hilbert) allow the methods of linear algebra and calculus to be generalized from (finite-dimensional) Euclidean vector spaces to spaces that may be infinite-dimensional. Hilbert spaces arise naturally and frequently in mathematics and physics, typically as function spaces. Formally, a Hilbert space is a vector space equipped with an inner product that defines a distance function for which the space is a complete metric space.

The earliest Hilbert spaces were studied from this point of view in the first decade of the 20th century by David HilbertErhard Schmidt, and Frigyes Riesz. They are indispensable tools in the theories of partial differential equationsquantum mechanicsFourier analysis (which includes applications to signal processing and heat transfer), and ergodic theory (which forms the mathematical underpinning of thermodynamics). John von Neumann coined the term Hilbert space for the abstract concept that underlies many of these diverse applications. The success of Hilbert space methods ushered in a very fruitful era for functional analysis. Apart from the classical Euclidean vector spaces, examples of Hilbert spaces include spaces of square-integrable functionsspaces of sequencesSobolev spaces consisting of generalized functions, and Hardy spaces of holomorphic functions.

Geometric intuition plays an important role in many aspects of Hilbert space theory. Exact analogs of the Pythagorean theorem and parallelogram law hold in a Hilbert space. At a deeper level, perpendicular projection onto a linear subspace or a subspace (the analog of “dropping the altitude” of a triangle) plays a significant role in optimization problems and other aspects of the theory. An element of a Hilbert space can be uniquely specified by its coordinates with respect to an orthonormal basis, in analogy with Cartesian coordinates in classical geometry. When this basis is countably infinite, it allows identifying the Hilbert space with the space of the infinite sequences that are square-summable. The latter space is often in the older literature referred to as the Hilbert space.

https://en.wikipedia.org/wiki/Hilbert_space

For all the self learners out there, there is a really good YouTube channel called eigenchris. He teachers Tensor Analysis He’s doing these videos for free, so please support him!

Hey guys! For all the self learners out there, there is a really good YouTube channel called eigenchris. He teachers Tensor Analysis (from the beginner level up to complex level) and is starting a series on special and general relativity. He’s doing these videos for free, so please support him!
by in math