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  2. List of equations in classical mechanics - Wikipedia

    en.wikipedia.org/wiki/List_of_equations_in...

    Classical mechanics is the branch of physics used to describe the motion of macroscopic objects. [1] It is the most familiar of the theories of physics. The concepts it covers, such as mass, acceleration, and force, are commonly used and known. [2]

  3. Dirac equation - Wikipedia

    en.wikipedia.org/wiki/Dirac_equation

    In particle physics, the Dirac equation is a relativistic wave equation derived by British physicist Paul Dirac in 1928. In its free form , or including electromagnetic interactions, it describes all spin-1/2 massive particles , called "Dirac particles", such as electrons and quarks for which parity is a symmetry .

  4. Dioptre - Wikipedia

    en.wikipedia.org/wiki/Dioptre

    Illustration of the relationship between optical power in dioptres and focal length in metres. A dioptre (British spelling) or diopter (American spelling), symbol dpt, is a unit of measurement with dimension of reciprocal length, equivalent to one reciprocal metre, 1 dpt = 1 m −1.

  5. Quantum electrodynamics - Wikipedia

    en.wikipedia.org/wiki/Quantum_electrodynamics

    In particle physics, quantum electrodynamics (QED) is the relativistic quantum field theory of electrodynamics. [1] [2] [3] In essence, it describes how light and matter interact and is the first theory where full agreement between quantum mechanics and special relativity is achieved. [2]

  6. Einstein field equations - Wikipedia

    en.wikipedia.org/wiki/Einstein_field_equations

    The Einstein field equations (EFE) may be written in the form: [5] [1] + = EFE on a wall in Leiden, Netherlands. where is the Einstein tensor, is the metric tensor, is the stress–energy tensor, is the cosmological constant and is the Einstein gravitational constant.

  7. Physics-informed neural networks - Wikipedia

    en.wikipedia.org/wiki/Physics-informed_neural...

    Physics-informed neural networks for solving Navier–Stokes equations. Physics-informed neural networks (PINNs), [1] also referred to as Theory-Trained Neural Networks (TTNs), [2] 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).

  8. Equations for a falling body - Wikipedia

    en.wikipedia.org/wiki/Equations_for_a_falling_body

    A set of equations describing the trajectories of objects subject to a constant gravitational force under normal Earth-bound conditions.Assuming constant acceleration g due to Earth’s gravity, Newton's law of universal gravitation simplifies to F = mg, where F is the force exerted on a mass m by the Earth’s gravitational field of strength g.

  9. Acoustic wave equation - Wikipedia

    en.wikipedia.org/wiki/Acoustic_wave_equation

    In physics, the acoustic wave equation is a second-order partial differential equation that governs the propagation of acoustic waves through a material medium resp. a standing wavefield. The equation describes the evolution of acoustic pressure p or particle velocity u as a function of position x and time t. A simplified (scalar) form of the ...