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t. e. Computational physics is the study and implementation of numerical analysis to solve problems in physics. [1] Historically, computational physics was the first application of modern computers in science, and is now a subset of computational science. It is sometimes regarded as a subdiscipline (or offshoot) of theoretical physics, but ...
List of unsolved problems in physics. The following is a list of notable unsolved problems grouped into broad areas of physics. [1] Some of the major unsolved problems in physics are theoretical, meaning that existing theories seem incapable of explaining a certain observed phenomenon or experimental result. The others are experimental, meaning ...
Computational science, also known as scientific computing, technical computing or scientific computation ( SC ), is a division of science that uses advanced computing capabilities to understand and solve complex physical problems. This includes. In practical use, it is typically the application of computer simulation and other forms of ...
Pure physics is a branch of fundamental science (also called basic science). Physics is also called " the fundamental science" because all branches of natural science like chemistry, astronomy, geology, and biology are constrained by laws of physics. [60] Similarly, chemistry is often called the central science because of its role in linking ...
The halting problem is a decision problem about properties of computer programs on a fixed Turing-complete model of computation, i.e., all programs that can be written in some given programming language that is general enough to be equivalent to a Turing machine. The problem is to determine, given a program and an input to the program, whether ...
The Stanford Research Institute Problem Solver, known by its acronym STRIPS, is an automated planner developed by Richard Fikes and Nils Nilsson in 1971 at SRI International. [1] The same name was later used to refer to the formal language of the inputs to this planner. This language is the base for most of the languages for expressing ...
Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks ( PINNs) 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). [1]
e. In mathematics, an ordinary differential equation ( ODE) is a differential equation (DE) dependent on only a single independent variable. As with other DE, its unknown (s) consists of one (or more) function (s) and involves the derivatives of those functions. [1] The term "ordinary" is used in contrast with partial differential equations ...