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Over the past century, rooted in the theory of general relativity, cosmology has developed a very successful physical model of the universe: the {\em big-bang model}. Its construction followed different stages to incorporate nuclear…

Cosmology and Nongalactic Astrophysics · Physics 2016-06-21 Jean-Philippe Uzan

Coherent effects manifested in light scattering from cold, optically dense and disordered atomic systems are reviewed from a primarily theoretical point of view. Development of the basic theoretical tools is then elaborated through several…

Quantum Physics · Physics 2017-12-15 D. V. Kupriyanov , I. M. Sokolov , M. D. Havey

This article addresses gaps in definitions and a lack of standard measurement techniques to assess the spatial resolution in atom probe tomography. This resolution is known to be anisotropic, being better in the depth than laterally.…

Under sufficient permanent random covalent bonding, a fluid of atoms or small molecules is transformed into an amorphous solid network. Being amorphous, local structural properties in such networks vary across the sample. A natural order…

Disordered Systems and Neural Networks · Physics 2009-10-31 Konstantin A. Shakhnovich , Paul M. Goldbart

End-to-end deep learning models fed with multi-band galaxy images are powerful data-driven tools used to estimate galaxy physical properties in the absence of spectroscopy. However, due to a lack of interpretability and the associational…

Instrumentation and Methods for Astrophysics · Physics 2025-11-26 Wei Zhang , Qiufan Lin , Yuan-Sen Ting , Shupei Chen , Hengxin Ruan , Song Li , Yifan Wang

Complex data usually results from the interaction of objects produced by different generating mechanisms. Here we introduce a universal, unsupervised and parameter-free model-oriented approach, based upon the seminal concept of algorithmic…

Artificial Intelligence · Computer Science 2018-09-14 Hector Zenil , Narsis A. Kiani , Allan A. Zea , Jesper Tegnér

We present a graph theory-based method to characterise flow defects and structural shifts in condensed matter. We explore the connection between dynamical properties, particularly the recently introduced concept of ''softness'', and…

Disordered Systems and Neural Networks · Physics 2024-08-13 An Wang , Gabriele C. Sosso

Scattering transforms are a new type of summary statistics recently developed for the study of highly non-Gaussian processes, which have been shown to be very promising for astrophysical studies. In particular, they allow one to build…

Instrumentation and Methods for Astrophysics · Physics 2024-11-22 Louise Mousset , Erwan Allys , Matthew A. Price , Jonathan Aumont , Jean-Marc Delouis , Ludovic Montier , Jason D. McEwen

Learning meaningful causal representations from observations has emerged as a crucial task for facilitating machine learning applications and driving scientific discoveries in fields such as climate science, biology, and physics. This…

Machine Learning · Computer Science 2026-02-06 Jiaxu Ren , Yixin Wang , Biwei Huang

Computing atomic-scale properties of chemically disordered materials requires an efficient exploration of their vast configuration space. Traditional approaches such as Monte Carlo or Special Quasirandom Structures either entail sampling an…

Materials Science · Physics 2026-03-17 Maciej J. Karcz , Luca Messina , Eiji Kawasaki , Emeric Bourasseau

We present results of theoretical description of ultrasonic phenomena in molecular liquids. In particular, we are interested in the development of microscopical, i.e., statistical-mechanical framework capable to explain the long living…

Statistical Mechanics · Physics 2007-08-30 A. E. Kobryn , F. Hirata

Atomic force microscopy (AFM) with molecule-functionalized tips has emerged as the primary experimental technique for probing the atomic structure of organic molecules on surfaces. Most experiments have been limited to nearly planar…

Medical ultrasound imaging relies heavily on high-quality signal processing to provide reliable and interpretable image reconstructions. Conventionally, reconstruction algorithms where derived from physical principles. These algorithms rely…

Signal Processing · Electrical Eng. & Systems 2023-09-21 Ben Luijten , Nishith Chennakeshava , Yonina C. Eldar , Massimo Mischi , Ruud J. G. van Sloun

It has been a long-standing materials science challenge to establish structure-property relations in amorphous solids. Here we introduce a rotation-variant local structure representation that enables different predictions for different…

Materials Science · Physics 2022-03-15 Zhao Fan , Evan Ma

Information Theory provides a fundamental basis for analysis, and for a variety of subsequent methodological approaches, in relation to uncertainty quantification. The transversal character of concepts and derived results justifies its…

Statistics Theory · Mathematics 2024-11-27 Jose M. Angulo , Francisco J. Esquivel , Ana E. Madrid , Francisco J. Alonso

In order to account for the observable Universe, any comprehensive theory or model of cosmology must draw from many disciplines of physics, including gauge theories of strong and weak interactions, the hydrodynamics and microphysics of…

General Relativity and Quantum Cosmology · Physics 2015-06-25 Peter Anninos

Starting from a new principle inspired by quantum tomography rather than from Born's rule, this paper gives a self-contained deductive approach to quantum mechanics and quantum measurement. A suggestive notion for what constitutes a quantum…

Quantum Physics · Physics 2024-05-22 Arnold Neumaier

The thermodynamics and microstructure of confined fluids with small particle number are best described using the canonical ensemble. However, practical calculations can usually only be performed in the grand-canonical ensemble, which can…

Soft Condensed Matter · Physics 2025-03-13 Emmanuel di Bernardo , Joseph Brader

Time-resolved scattering experiments enable imaging of materials at the molecular scale with femtosecond time resolution. However, in disordered media they provide access to just one radial dimension thus limiting the study of orientational…

Recent advances in Foundation Models for Materials Science are poised to revolutionize the discovery, manufacture, and design of novel materials with tailored properties and responses. Although great strides have been made, successes have…

Machine Learning · Computer Science 2025-06-16 Michael Buzzy , Andreas Robertson , Peng Chen , Surya Kalidindi