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Geochemically discriminating between magmatism in different tectonic settings remains a fundamental part of understanding the processes of magma generation within the Earth's mantle. Here, we present an approach where machine-learning (ML)…

Geophysics · Physics 2018-05-29 Kenta Ueki , Hideitsu Hino , Tatsu Kuwatani

Geological processes determine the distribution of resources such as critical minerals, water, and geothermal energy. However, direct observation of geology is often prevented by surface cover such as overburden or vegetation. In such…

Computer Vision and Pattern Recognition · Computer Science 2023-03-22 Conrad P. Koziol , Eldad Haber

Crystal structure prediction algorithms have become powerful tools for materials discovery in recent years, however, they are usually limited to relatively small systems. The main challenge is that the number of local minima grows…

Materials Science · Physics 2022-02-09 Hao Gao , Junjie Wang , Yu Han , Jian Sun

We present a new algorithm for detecting filamentary structure FilFinder. The algorithm uses the techniques of mathematical morphology for filament identification, presenting a complementary approach to current algorithms which use matched…

Astrophysics of Galaxies · Physics 2015-07-10 Eric W. Koch , Erik W. Rosolowsky

Analysis of nanoscale short-range chemical and/or structural order via (scanning) transmission electron microscopy (S/TEM) imaging is fundamentally limited by projection of the three dimensional sample, which averages informational along…

Materials Science · Physics 2022-08-25 Michael Xu , Abinash Kumar , James M. LeBeau

Linear structural equation models, which relate random variables via linear interdependencies and Gaussian noise, are a popular tool for modeling multivariate joint distributions. These models correspond to mixed graphs that include both…

Computation · Statistics 2015-04-14 Mathias Drton , Luca Weihs

In this study, we establish a basis for selecting similarity measures when applying machine learning techniques to solve materials science problems. This selection is considered with an emphasis on the distinctiveness between materials that…

Machine Learning · Computer Science 2019-03-27 Tran-Thai Dang , Tien-Lam Pham , Hiori Kino , Takashi Miyake , Hieu-Chi Dam

Observations of Milky Way stars by multiplexed spectroscopic instruments and of gas in nearby galaxies using integral field units have made it possible to measure the abundances of multiple elements in both the interstellar medium and the…

Astrophysics of Galaxies · Physics 2025-11-27 Mark R. Krumholz , Yuan-Sen Ting , Zefeng Li , Chuhan Zhang , Jennifer Mead , Melissa K. Ness

The predictability of a certain effect or phenomenon is often equated with the knowledge of relevant physical laws, typically understood as a functional or numerically derived relationship between the observations and known states of the…

Geochemical systems are known to exhibit highly variable spatiotemporal behavior. This may be observed both in non-smooth concentration curves in space for a single sampling time and also in variability between samples taken from the same…

The application of infrared hyperspectral imagery to geological problems is becoming more popular as data become more accessible and cost-effective. Clustering and classifying spectrally similar materials is often a first step in…

Image and Video Processing · Electrical Eng. & Systems 2021-06-28 Angela F. Gao , Brandon Rasmussen , Peter Kulits , Eva L. Scheller , Rebecca Greenberger , Bethany L. Ehlmann

We present a new method for fitting simple hydrodynamical models to the (l,v) distribution of atomic and molecular gas observed in the Milky Way. The method works by matching features found in models and observations. It is based on the…

Astrophysics of Galaxies · Physics 2015-06-23 Mattia C. Sormani , John Magorrian

Successful scientific applications of large-scale molecular dynamics often rely on automated methods for identifying the local crystalline structure of condensed phases. Many existing methods for structural identification, such as Common…

Materials Science · Physics 2016-05-24 Peter Mahler Larsen , Søren Schmidt , Jakob Schiøtz

The local arrangement of atoms is one of the most important predictors of mechanical and functional properties of materials. However, algorithms for identifying the geometrical arrangements of atoms in complex materials systems are lacking.…

Materials Science · Physics 2019-04-15 Arash Dehghan Banadaki , Jason J. Maldonis , Paul M. Voyles , Srikanth Patala

Context. Filamentary structures appear to be ubiquitous in the interstellar medium. Being able to detect and characterize them is the first step toward understanding their origin, their evolution, and their role in the Galactic cycle of…

Astrophysics of Galaxies · Physics 2022-12-14 J. -S. Carrière , L. Montier , K. Ferrière , I. Ristorcelli

Strategic decisions to develop a mineral deposit are subject to geological uncertainty, due to the sparsity of drill core samples. The selection of metallurgical equipment is especially critical, since it restricts the processing options…

Optimization and Control · Mathematics 2017-04-24 Alessandro Navarra , Tassos Grammatikopoulos , Kristian Waters

We propose a model-based geostatistical approach to deal with regionalized compositions. We combine the additive-log-ratio transformation with multivariate geostatistical models whose covariance matrix is adapted to take into account the…

Within the calibration of material models, often the numerical results of a simulation model $y$ are compared with the experimental measurements $y^*$. Usually, the differences between measurements and simulation are minimized using least…

Materials Science · Physics 2024-08-14 Thomas Most

Metals -- heavy elements synthesized during various phases of stellar evolution or during supernova explosions -- play a fundamental role in shaping galaxy evolution. In fact, their relative abundances, spatial distribution, and scaling…

Astrophysics of Galaxies · Physics 2025-04-15 Mirko Curti

In this paper, a new approach is presented to determine common eigenvalues of two matrices. It is based on Gerschgorin theorem and Bisection method. The proposed approach is simple and can be useful in image processing and noise estimation.

Numerical Analysis · Computer Science 2010-03-10 D. Roopamala , S. K. Katti