Hubble Space TelescopeThe Hubble Space Telescope (often referred to as HST or Hubble) is a space telescope that was launched into low Earth orbit in 1990 and remains in operation. It was not the first space telescope, but it is one of the largest and most versatile, renowned both as a vital research tool and as a public relations boon for astronomy. The Hubble telescope is named after astronomer Edwin Hubble and is one of NASA's Great Observatories.
The Feynman Lectures on PhysicsThe Feynman Lectures on Physics is a physics textbook based on some lectures by Richard Feynman, a Nobel laureate who has sometimes been called "The Great Explainer". The lectures were presented before undergraduate students at the California Institute of Technology (Caltech), during 1961–1963. The book's co-authors are Feynman, Robert B. Leighton, and Matthew Sands. A 2013 review in Nature described the book as having "simplicity, beauty, unity ... presented with enthusiasm and insight". The textbook comprises three volumes.
Landing Ship, TankLanding Ship, Tank (LST), or tank landing ship, is the naval designation for ships first developed during World War II (1939–1945) to support amphibious operations by carrying tanks, vehicles, cargo, and landing troops directly onto a low slope beach with no docks or piers. The shallow draft and bow doors and ramps. enabled amphibious assaults on almost any beach. The LST had a highly specialized design that enabled ocean crossings as well as shore groundings. The bow had a large door that could open, deploy a ramp and unload vehicles.
Rank (linear algebra)In linear algebra, the rank of a matrix A is the dimension of the vector space generated (or spanned) by its columns. This corresponds to the maximal number of linearly independent columns of A. This, in turn, is identical to the dimension of the vector space spanned by its rows. Rank is thus a measure of the "nondegenerateness" of the system of linear equations and linear transformation encoded by A. There are multiple equivalent definitions of rank. A matrix's rank is one of its most fundamental characteristics.
Rank–nullity theoremThe rank–nullity theorem is a theorem in linear algebra, which asserts: the number of columns of a matrix M is the sum of the rank of M and the nullity of M; and the dimension of the domain of a linear transformation f is the sum of the rank of f (the dimension of the of f) and the nullity of f (the dimension of the kernel of f). It follows that for linear transformations of vector spaces of finite dimension, either injectivity or surjectivity implies bijectivity.
