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Showing 20 of 526 academic articles

Lagrangian Neural Networks

Miles Cranmer, Sam Greydanus, Stephan Hoyer, Peter Battaglia et al. • arXiv (Cornell University) (2020)

Accurate models of the world are built upon notions of its underlying symmetries. In physics, these symmetries correspond to conservation laws, such as for energy and momentum. Yet even though neural network models see increasing use in the...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.2003.04630

Quantum Entanglement in Neural Network States

Dong-Ling Deng, Xiaopeng Li, S. Das Sarma • Physical Review X (2017)

Machine learning has recently gained attention as a possible way to understand phase transitions in many-body quantum systems. A new entanglement analysis reveals crucial properties of the data structures that encode quantum states in a neu...

OPENALEX cc-by DOI: https://doi.org/10.1103/physrevx.7.021021

Spin-glass models of neural networks

Daniel J. Amit, Hanoch Gutfreund, Haim Sompolinsky • Physical Review A (1985)

Two dynamical models, proposed by Hopfield and Little to account for the collective behavior of neural networks, are analyzed. The long-time behavior of these models is governed by the statistical mechanics of infinite-range Ising spin-glas...

OPENALEX DOI: https://doi.org/10.1103/physreva.32.1007

Discovering Physical Concepts with Neural Networks

Raban Iten, Tony Metger, Henrik Wilming, Lídia del Rio et al. • Physical Review Letters (2020)

Despite the success of neural networks at solving concrete physics problems, their use as a general-purpose tool for scientific discovery is still in its infancy. Here, we approach this problem by modeling a neural network architecture afte...

OPENALEX Open Access DOI: https://doi.org/10.1103/physrevlett.124.010508

Introduction to Neural Networks.

Nanette S. Holder • Defense Technical Information Center (DTIC) (1992)

1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks....

OPENALEX Open Access DOI: https://doi.org/10.21236/ada248258

Hamiltonian Neural Networks

Sam Greydanus, Misko Dzamba, Jason Yosinski • arXiv (Cornell University) (2019)

Even though neural networks enjoy widespread use, they still struggle to learn the basic laws of physics. How might we endow them with better inductive biases? In this paper, we draw inspiration from Hamiltonian mechanics to train models th...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1906.01563

Applications of Neural Networks in Electromagnetics

Christos Christodoulou, Michael Georgiopoulos • CERN Document Server (European Organization for Nuclear Research) (2001)

From the Book: Since the early 1990s, a plethora of electromagnetic problems have been tackled using neural networks, some more successfully than others. Because neural networks and electromagnetics are two different scientific fields, not...

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An IXPE-led X-Ray Spectropolarimetric Campaign on the Soft State of Cygnus X-1: X-Ray Polarimetric Evidence for Strong Gravitational Lensing

James F. Steiner, Edward Nathan, Kun Hu, Henric Krawczynski et al. • The Astrophysical Journal Letters (2024)

We present the first X-ray spectropolarimetric results for Cygnus X-1 in its soft state from a campaign of five IXPE observations conducted during 2023 May–June. Companion multiwavelength data during the campaign are likewise shown. The 2–8...

DOAJ Open Access (DOAJ) DOI: 10.3847/2041-8213/ad58e4

A Deep SETI Search for Technosignatures in the TRAPPIST-1 System with FAST

Guang-Yuan Song, Zhen-Zhao Tao, Bo-Lun Huang, Bo Yu et al. • The Astronomical Journal (2026)

The Five-hundred-meter Aperture Spherical Telescope (FAST) is the world’s largest single-dish radio telescope, and the search for extraterrestrial intelligence (SETI) is one of its five key science objectives. We conducted a targeted search...

DOAJ Open Access (DOAJ) DOI: 10.3847/1538-3881/ae8516

An invitation to astrophysics

• Choice Reviews Online (2007)

This unique book provides a clear and lucid description of several aspects of astrophysics and cosmology in a language understandable to a physicist or beginner in astrophysics. It presents the key topics in all branches of astrophysics and...

OPENALEX DOI: https://doi.org/10.5860/choice.44-2679

Nuclear astrophysics

M. Arnould, K. Takahashi • Reports on Progress in Physics (1999)

Nuclear astrophysics is that branch of astrophysics which helps understanding some of the many facets of the Universe through the knowledge of the microcosm of the atomic nucleus. In the last decades much advance has been made in nuclear as...

OPENALEX Open Access DOI: https://doi.org/10.1088/0034-4885/62/3/003

Plasma Physics for Astrophysics

Russell M. Kulsrud • Princeton University Press eBooks (2005)

In this book, a distinguished expert introduces plasma physics from the ground up, presenting it as a comprehensible field that can be grasped largely on the basis of physical intuition and qualitative reasoning, similar to other fields of ...

OPENALEX DOI: https://doi.org/10.1515/9780691213354