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SciPy. SciPy (pronounced / ˈsaɪpaɪ / "sigh pie" [2]) is a free and open-source Python library used for scientific computing and technical computing. [3] SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and ...
Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), also referred to as Theory-Trained Neural Networks (TTNs), are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations (PDEs).They ...
Newton's first law expresses the principle of inertia: the natural behavior of a body is to move in a straight line at constant speed. A body's motion preserves the status quo, but external forces can perturb this. The modern understanding of Newton's first law is that no inertial observer is privileged over any other.
Dot product. In mathematics, the dot product or scalar product [note 1] is an algebraic operation that takes two equal-length sequences of numbers (usually coordinate vectors ), and returns a single number. In Euclidean geometry, the dot product of the Cartesian coordinates of two vectors is widely used. It is often called the inner product (or ...
A critical mass is a mass of fissile material that self-sustains a fission chain reaction. In this case, called criticality, k = 1. A steady rate of spontaneous fission causes a proportionally steady level of neutron activity. A supercritical mass is a mass which, once fission has started, will proceed at an increasing rate. [1]
Python is a free, text-based programming language that has already been used by those who do physics research to great effect. But students can also learn to use it and, through its use, learn other aspects of physics--especially ones that are difficult or impossible to perform as physical labs.
QuTiP, short for the Quantum Toolbox in Python, is an open-source computational physics software library for simulating quantum systems, particularly open quantum systems. [1] [2] QuTiP allows simulation of Hamiltonians with arbitrary time-dependence, allowing simulation of situations of interest in quantum optics, ion trapping, superconducting circuits and quantum nanomechanical resonators.
In this technology report, we use the Python programming environment and the three-point finite-difference numerical method to find the solutions and plot the results (wave functions or probability densities) for a particle in an infinite, finite, double finite, harmonic, Morse, or Kronig-Penney finite potential energy well.