NumPyNumPy (pronounced ˈnʌmpaɪ () or sometimes ˈnʌmpi ()) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. The predecessor of NumPy, Numeric, was originally created by Jim Hugunin with contributions from several other developers. In 2005, Travis Oliphant created NumPy by incorporating features of the competing Numarray into Numeric, with extensive modifications.
Magneto-inertial fusionMagneto-inertial fusion (MIF) describes a class of fusion devices which combine aspects of magnetic confinement fusion and inertial confinement fusion in an attempt to lower the cost of fusion devices. MIF uses magnetic fields to confine an initial warm, low-density plasma, then compresses that plasma to fusion conditions using an impulsive driver or "liner." Magneto-inertial fusion approaches differ in the degree of magnetic organization present in the initial target, as well as the nature and speed of the imploding liner.
Collision resistanceIn cryptography, collision resistance is a property of cryptographic hash functions: a hash function H is collision-resistant if it is hard to find two inputs that hash to the same output; that is, two inputs a and b where a ≠ b but H(a) = H(b). The pigeonhole principle means that any hash function with more inputs than outputs will necessarily have such collisions; the harder they are to find, the more cryptographically secure the hash function is.
GyroradiusThe gyroradius (also known as radius of gyration, Larmor radius or cyclotron radius) is the radius of the circular motion of a charged particle in the presence of a uniform magnetic field. In SI units, the non-relativistic gyroradius is given by where is the mass of the particle, is the component of the velocity perpendicular to the direction of the magnetic field, is the electric charge of the particle, and is the strength of the magnetic field.
Distribution function (physics)In molecular kinetic theory in physics, a system's distribution function is a function of seven variables, , which gives the number of particles per unit volume in single-particle phase space. It is the number of particles per unit volume having approximately the velocity near the position and time . The usual normalization of the distribution function is where N is the total number of particles and n is the number density of particles – the number of particles per unit volume, or the density divided by the mass of individual particles.
