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A core challenge for both physics and artificial intellicence (AI) is symbolic regression: finding a symbolic expression that matches data from an unknown function. Although this problem is likely to be NP-hard in principle, functions of…

Computational Physics · Physics 2020-04-16 Silviu-Marian Udrescu , Max Tegmark

Recent progress in artificial intelligence (AI) is unlocking transformative capabilities for mathematics. There is great hope that AI will help solve major open problems and autonomously discover new mathematical concepts. In this essay, we…

Artificial Intelligence · Computer Science 2026-04-08 Maissam Barkeshli , Michael R. Douglas , Michael H. Freedman

AI video generation is undergoing a revolution, with quality and realism advancing rapidly. These advances have led to a passionate scientific debate: Do video models learn "world models" that discover laws of physics -- or, alternatively,…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Saman Motamed , Laura Culp , Kevin Swersky , Priyank Jaini , Robert Geirhos

Finding self-similarity is a key step for understanding the governing law behind complex physical phenomena. Traditional methods for identifying self-similarity often rely on specific models, which can introduce significant bias. In this…

Soft Condensed Matter · Physics 2025-02-05 Ryota Watanabe , Takanori Ishii , Yuji Hirono , Hirokazu Maruoka

The discovery of physical laws consistent with empirical observations lies at the heart of (applied) science and engineering. These laws typically take the form of nonlinear differential equations depending on parameters, dynamical systems…

Pattern Formation and Solitons · Physics 2016-12-13 Or Yair , Ronen Talmon , Ronald R. Coifman , Ioannis G. Kevrekidis

Generative AI has the potential to transform personalization and accessibility of education. However, it raises serious concerns about accuracy and helping students become independent critical thinkers. In this study, we designed a helpful…

Artificial intelligence has demonstrated remarkable capability in predicting scientific properties, yet scientific discovery remains an inherently physical, long-horizon pursuit governed by experimental cycles. Most current computational…

Artificial Intelligence · Computer Science 2026-03-23 Xiang Zhuang , Chenyi Zhou , Kehua Feng , Zhihui Zhu , Yunfan Gao , Yijie Zhong , Yichi Zhang , Junjie Huang , Keyan Ding , Lei Bai , Haofen Wang , Qiang Zhang , Huajun Chen

First formulated by Sir Isaac Newton in his work "Philosophiae Naturalis Principia Mathematica", the concept of the Three-Body Problem was put forth as a study of the motion of the three celestial bodies within the Earth-Sun-Moon system. In…

Machine Learning · Computer Science 2025-03-07 Manuel Santos Pereira , Luís Tripa , Nélson Lima , Francisco Caldas , Cláudia Soares

The fact that accurately predicted information can serve as an energy source paves the way for new approaches to autonomous learning. The energy derived from a sequence of successful predictions can be recycled as an immediate incentive and…

Emerging Technologies · Computer Science 2024-07-09 Alex Ushveridze

This article is an attempt for a new vision of the basics of Physics, and of Relativity, in particular. A new generalized principle of inertia is proposed, as an universal principle, based on universality of the conservation laws, not…

General Physics · Physics 2007-05-23 Emil Marinchev

In a landscape where scientific discovery is increasingly driven by data, the integration of machine learning (ML) with traditional scientific methodologies has emerged as a transformative approach. This paper introduces a novel,…

Machine Learning · Computer Science 2024-06-26 Yunjin Tong

Incorporating the Hamiltonian structure of physical dynamics into deep learning models provides a powerful way to improve the interpretability and prediction accuracy. While previous works are mostly limited to the Euclidean spaces, their…

Machine Learning · Computer Science 2022-10-04 Oswin So , Gongjie Li , Evangelos A. Theodorou , Molei Tao

Neural operators, which emerge as implicit solution operators of hidden governing equations, have recently become popular tools for learning responses of complex real-world physical systems. Nevertheless, the majority of neural operator…

Machine Learning · Computer Science 2023-01-31 Ning Liu , Yue Yu , Huaiqian You , Neeraj Tatikola

The paper surveys automated scientific discovery, from equation discovery and symbolic regression to autonomous discovery systems and agents. It discusses the individual approaches from a "big picture" perspective and in context, but also…

Artificial Intelligence · Computer Science 2026-05-01 Stefan Kramer , Mattia Cerrato , Jannis Brugger , Sašo Džeroski , Ross King

This document is a hands-on, comprehensive guide to deep learning in the realm of physical simulations. Rather than just theory, we emphasize practical application: every concept is paired with interactive Jupyter notebooks to get you up…

Machine Learning · Computer Science 2025-03-28 N. Thuerey , B. Holzschuh , P. Holl , G. Kohl , M. Lino , Q. Liu , P. Schnell , F. Trost

Scientific progress in Earth science depends on integrating data across the planet's interconnected spheres. However, the accelerating volume and fragmentation of multi-sphere knowledge and data have surpassed human analytical capacity.…

I discuss the main features of the concept of law in physics. Fundamental laws from Newtonian mechanics to general relativity are reviewed. I end with an outlook on the new form of laws in the emerging theory of quantum gravity.

History and Philosophy of Physics · Physics 2014-06-09 Claus Kiefer

This paper presents a novel approach to scientific discovery using an artificial intelligence (AI) environment known as ChatGPT, developed by OpenAI. This is the first paper entirely generated with outputs from ChatGPT. We demonstrate how…

Other Computer Science · Computer Science 2023-09-18 Gerardo Adesso

Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation. Despite these powerful applications, there…

Neurons and Cognition · Quantitative Biology 2023-01-23 Luyao Chen , Zhiqiang Chen , Longsheng Jiang , Xiang Liu , Linlu Xu , Bo Zhang , Xiaolong Zou , Jinying Gao , Yu Zhu , Xizi Gong , Shan Yu , Sen Song , Liangyi Chen , Fang Fang , Si Wu , Jia Liu
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