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The aim of this article is to demonstrate the useful role that can be played by spectropolarimetric observations of young and evolved emission line stars that analyse the linearly polarized component in their spectra. At the time of…

Astrophysics · Physics 2009-11-10 Janet Drew , Jorick Vink , Tim Harries , Ryuichi Kurosawa , Rene Oudmaijer

SDSS-V will obtain 100,000s of medium-resolution, optical spectra of M dwarfs with the BOSS instrument. M dwarfs have complex atmospheres, and their spectra contain many wide and dense, overlapping molecular features, so determining…

A decade of X-ray stellar observations with Chandra and XMM-Newton has led to significant advances in our understanding of the physical processes at work in hot (magnetized) plasmas in stars and their immediate environment, providing new…

Solar and Stellar Astrophysics · Physics 2010-08-26 Paola Testa

The paper reviews recent progress in photodetectors, discussing vacuum-based detectors, semiconductor sensors, and gas-based detectors. The emphasis in this review is on the detection of low light levels, enhanced timing resolution, and…

Instrumentation and Detectors · Physics 2024-01-12 Peter Krizan

We highlight recent theoretical and observational progress in several areas of neutron star astrophysics, and discuss the prospect for advances in the next decade.

High-resolution observations by visible and near-infrared interferometers of both single stars and binaries have made significant contributions to the foundations that underpin many aspects of our knowledge of stellar structure and…

We focus on spectral clustering of unlabeled graphs and review some results on clustering methods which achieve weak or strong consistent identification in data generated by such models. We also present a new algorithm which appears to…

Statistics Theory · Mathematics 2015-08-11 Sharmodeep Bhattacharyya , Peter J. Bickel

This is a review of the status of efforts to model the large-scale Galactic magnetic field (GMF). Though important for a variety of astrophysical processes, the GMF remains poorly understood despite some interesting new tracers being used…

Astrophysics of Galaxies · Physics 2019-05-14 Tess R. Jaffe

There is an increasing number of large, digital, synoptic sky surveys, in which repeated observations are obtained over large areas of the sky in multiple epochs. Likewise, there is a growth in the number of (often automated or robotic)…

Spectral clustering is a popular method for effectively clustering nonlinearly separable data. However, computational limitations, memory requirements, and the inability to perform incremental learning challenge its widespread application.…

Machine Learning · Computer Science 2023-11-15 Jo-Chun Chen , Hung-Hsuan Chen

The last two decades have seen remarkable progress in our long-standing goal of determining the abundance and diversity of worlds in the Galaxy. Understanding of this subject involves tracing the path of interstellar material from dense…

Spectral clustering is a popular method for community detection in network graphs: starting from a matrix representation of the graph, the nodes are clustered on a low dimensional projection obtained from a truncated spectral decomposition…

Machine Learning · Statistics 2022-08-10 Francesco Sanna Passino , Nicholas A. Heard , Patrick Rubin-Delanchy

The soft X-rays (SXRs: 90--150 $\r{A}$) are among the most interesting spectral ranges to be investigated in the next generation of solar missions due to their unique capability of diagnosing phenomena involving hot plasma with temperatures…

Instrumentation and Methods for Astrophysics · Physics 2021-05-13 Alain Jody Corso , Giulio Del Zanna , Vanessa Polito

This paper introduces a novel sector-based methodology for star-galaxy classification, leveraging the latest Sloan Digital Sky Survey data (SDSS-DR18). By strategically segmenting the sky into sectors aligned with SDSS observational…

Instrumentation and Methods for Astrophysics · Physics 2024-06-21 Anumanchi Agastya Sai Ram Likhit , Divyansh Tripathi , Akshay Agarwal

Machine learning (ML) is a rapidly growing area of research in the field of particle physics, with a vast array of applications at the CERN LHC. ML has changed the way particle physicists conduct searches and measurements as a versatile…

High Energy Physics - Experiment · Physics 2024-10-01 Javier M. Duarte

This is a review of recent observational and theoretical developments related to accreting neutron stars and black holes in binary systems.

Astrophysics · Physics 2007-05-23 Dimitrios Psaltis

Spectral algorithms are graph partitioning algorithms that partition a node set of a graph into groups by using a spectral embedding map. Clustering techniques based on the algorithms are referred to as spectral clustering and are widely…

Machine Learning · Computer Science 2021-09-08 Tomohiko Mizutani

The next generation of multi-object spectrographs (MOS) will deliver comprehensive surveys of the Galaxy, Magellanic Clouds and nearby dwarfs. These will provide us with the vast samples, spanning the full extent of the Hertzsprung-Russell…

Solar and Stellar Astrophysics · Physics 2015-06-05 C. J. Evans

Classification of galaxy spectral energy distributions in terms of orthogonal basis functions provides an objective means of estimating the number of significant spectral components that comprise a particular galaxy type. We apply the…

Astrophysics · Physics 2011-05-05 A. J. Connolly , A. S. Szalay , M. A. Bershady , A. L. Kinney , D. Calzetti

Millimter (mm) frequencies are primarily sensitive to thermal emission from layers across the stellar chromosphere up to the transition region, while metrewave (radio) frequencies probe the coronal heights. Together the mm and radio band…

Solar and Stellar Astrophysics · Physics 2025-10-16 Atul Mohan
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