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Related papers: Sequencing Silicates in the IRS Debris Disk Catalo…

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Silicates are an important component of interstellar dust and the structure of these grains -- amorphous versus crystalline -- is sensitive to the local physical conditions. We have studied the infrared spectra of a sample of ultra-luminous…

We present a study to estimate the dust content in galaxy clusters by using one the most complete existing catalogues of galaxy clusters based on SDSS data and following two methods: the first one compares the colours of samples of galaxies…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-11 C. M. Gutierrez , M. Lopez-Corredoira

From biological organs to soft robotics, highly deformable materials are essential components of natural and engineered systems. These highly deformable materials can have heterogeneous material properties, and can experience heterogeneous…

Machine Learning · Computer Science 2023-08-31 Quan Nguyen , Emma Lejeune

[abridged] Aims. Our Herschel Open Time Key Programme DUNES aims at detecting and characterizing debris disks around nearby, sun-like stars. In addition to the statistical analysis of the data, the detailed study of single objects through…

We present the scientific motivation and observing plan for an upcoming detection survey for debris disks using the James Clerk Maxwell Telescope. The SCUBA-2 Unbiased Nearby Stars (SUNS) Survey will observe 500 nearby main sequence and…

We have constructed a set of supercluster catalogues for the galaxies from the SDSS survey main and luminous red galaxy (LRG) flux-limited samples. To delineate superclusters, we calculated luminosity density fields using the B3-spline…

Cosmology and Nongalactic Astrophysics · Physics 2012-01-17 L. J. Liivamägi , E. Tempel , E. Saar

Context. Rotational instability of rubble-pile asteroids can trigger mass shedding, forming transient debris clouds that may provide the initial conditions for secondary formation in binary systems. Aims. We investigate the dynamical and…

Earth and Planetary Astrophysics · Physics 2025-12-16 Yutian Wu , Xiaojing Zhang , Chenyang Huang , Yang Yu

Context. An automatic tool to derive structural parameters of semi-resolved star clusters located in crowded stellar fields in nearby galaxies is needed for homogeneous processing of archival frames. Aims. We have developed a program that…

Astrophysics of Galaxies · Physics 2015-12-31 D. Narbutis , D. Semionov , R. Stonkutė , P. de Meulenaer , T. Mineikis , A. Bridžius , V. Vansevičius

Structures observed in debris disks may be caused by gravitational interaction with planetary or stellar companions. These perturbed disks are often thought to indicate the presence of planets and offer insights into the properties of both…

Earth and Planetary Astrophysics · Physics 2017-09-29 Maryam Tabeshian , Paul A. Wiegert

Clustering is a crucial task in various domains of knowledge, including medicine, epidemiology, genomics, environmental science, economics, and visual sciences, among others. Methodologies for inferring the number of clusters have often…

Methodology · Statistics 2025-05-26 Clara Grazian

Disintegrating planets are ultra-short-period exoplanets that appear to have a comet-like dust tail. They are commonly interpreted as low-mass planets whose solid surface is evaporating and whose tail is made of recondensing minerals.…

Earth and Planetary Astrophysics · Physics 2020-10-14 Ayaka Okuya , Satoshi Okuzumi , Kazumasa Ohno , Teruyuki Hirano

A novel nonparametric clustering algorithm is proposed using the interpoint distances between the members of the data to reveal the inherent clustering structure existing in the given set of data, where we apply the classical nonparametric…

Methodology · Statistics 2024-09-02 Soumita Modak

This work presents a novel method for fitting superquadrics to point clouds under the contamination of noise and outliers, which has many applications for shape modeling across diverse fields. Unlike prior approaches that either exclusively…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Mingyang Zhao , Sipu Ruan , Xiaohong Jia

Clustering is a popular machine learning technique for data mining that can process and analyze datasets to automatically reveal sample distribution patterns. Since the ubiquitous categorical data naturally lack a well-defined metric space…

Machine Learning · Computer Science 2025-09-01 Yiqun Zhang , Mingjie Zhao , Hong Jia , Yang Lu , Mengke Li , Yiu-ming Cheung

An efficient method for obtaining low-density hyperplane separators in the unsupervised context is proposed. Low density separators can be used to obtain a partition of a set of data based on their allocations to the different sides of the…

Machine Learning · Statistics 2021-08-10 David P. Hofmeyr

Currently, density-based clustering algorithms are widely applied because they can detect clusters with arbitrary shapes. However, they perform poorly in measuring global density, determining reasonable cluster centers or structures,…

Machine Learning · Computer Science 2023-11-02 Mingjie Cai , Zhishan Wu , Qingguo Li , Feng Xu , Jie Zhou

Despite the fundamental importance of clustering, to this day, much of the relevant research is still based on ambiguous foundations, leading to an unclear understanding of whether or how the various clustering methods are connected with…

Machine Learning · Computer Science 2025-01-29 Yorgos Tsitsikas , Evangelos E. Papalexakis

A detailed analysis of the Nuclear Stellar Cluster (NSC) concedes not only the existence of the Scluster with its fast-moving stars and the supermassive black hole (SMBH) Sgr A*. It also reveals an embedded region of gas and dust with an…

Media content in large repositories usually exhibits multiple groups of strongly varying sizes. Media of potential interest often form notably smaller groups. Such media groups differ so much from the remaining data that it may be worthy to…

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