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Applying machine learning (ML) (including deep learning) methods to the study of quantum systems is an emergent area of physics research.A basic example of this is quantum state tomography, where a quantum state is learned from measurement. [1]
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).
Journal of Astronomical Telescopes, Instruments, and Systems; Journal of the British Astronomical Association; Journal of the British Interplanetary Society; Journal of Cosmology; Journal of Cosmology and Astroparticle Physics; Journal of Geophysical Research; Journal of the Korean Astronomical Society; Journal of the Royal Astronomical Society ...
Astrophysics and Space Science; Canadian Journal of Physics; European Physical Journal D; IEEE Transactions on Plasma Science; Journal of Applied Physics; Journal of Geophysical Research; Journal of Nuclear Materials; Journal of Physics D; Journal of Technological and Space Plasmas; Journal of Vacuum Science and Technology; Physical Review E ...
The 2024 Nobel Prize in physics has been awarded to John Hopfield and Geoffrey Hinton for their fundamental discoveries in machine learning, which paved the way for how artificial intelligence is ...
Vast Space is a private company that proposes to build the world's first artificial gravity space station using the rotating spacecraft concept. [23] A Mars gravity simulator could be built on the Moon to prepare for Mars missions. The surface gravity of Mars is somewhat more than twice that of the Moon.
The core technology used to achieve these goals is a novel approach referred to as "artificial physics" or "physicomimetics". With physicomimetics, robotic agents perceive and react to artificial physics forces.
John Hopfield dreamed up the modern neural network while at Caltech. Geoffrey Hinton built on it, creating an AI firm that Google bought for $44 million.