Related papers: Sequencing Silicates in the IRS Debris Disk Catalo…
We investigate the prospects for detecting dust from two body collisions during the late stages of planet formation at 1-150 AU. We develop an analytic model to describe the formation of a dusty cloud of debris and use numerical coagulation…
Clustering is a data analysis method for extracting knowledge by discovering groups of data called clusters. Among these methods, state-of-the-art density-based clustering methods have proven to be effective for arbitrary-shaped clusters.…
Interstellar dust plays a crucial role in gas cooling and molecule formation, influencing galaxy evolution. However, the composition and structure of dust in distant galaxies are still poorly understood. We have started a JWST MIRI MRS…
A "minimum model" for debris disks consists of a narrow ring of parent bodies, secularly forced by a single planet on a possibly eccentric orbit, colliding to produce dust grains that are perturbed by stellar radiation pressure. We…
Unsupervised clustering, also known as natural clustering, stands for the classification of data according to their similarities. Here we study this problem from the perspective of complex networks. Mapping the description of data…
This paper presents a novel method for mapping spectral features of the Moon using machine learning-based clustering of hyperspectral data from the Moon Mineral Mapper (M3) imaging spectrometer. The method uses a convolutional variational…
In machine learning and data mining, Cluster analysis is one of the most widely used unsupervised learning technique. Philosophy of this algorithm is to find similar data items and group them together based on any distance function in…
Clustering can be defined as the process of assembling objects into a number of groups whose elements are similar to each other in some manner. As a technique that is used in many domains, such as face clustering, plant categorization,…
Debris disks are evidence that stars harbor reservoirs of dust-producing plantesimals on spatial scales similar the solar system. Debris disks present a wide range of sizes and structural features and there is growing evidence that, in some…
Debris discs are a consequence of the planet formation process and constitute the fingerprints of planetesimal systems. Their solar system's counterparts are the asteroid and Edgeworth-Kuiper belts. The DUNES survey aims at detecting…
Clustering is the technique to partition data according to their characteristics. Data that are similar in nature belong to the same cluster [1]. There are two types of evaluation methods to evaluate clustering quality. One is an external…
In this paper, we address an issue of finding explainable clusters of class-uniform data in labelled datasets. The issue falls into the domain of interpretable supervised clustering. Unlike traditional clustering, supervised clustering aims…
Density-based clustering methodology has been widely considered in the statistical literature for classifying Euclidean observations. However, this approach has not been contemplated for directional data yet. In this work, directional…
The $Herschel$ Space telescope carried out an unprecedented survey of nearby stars for debris disks. The dust present in these debris disks scatters and polarizes stellar light in the visible part of the spectrum. We explore what can be…
The dust disks observed around mature stars are evidence that plantesimals are present in these systems on spatial scales that are similar to that of the asteroids and the KBOs in the Solar System. These dust disks (a.k.a. ``debris disks'')…
We present the clustering of galaxy clusters as a useful addition to the common set of cosmological observables. The clustering of clusters probes the large-scale structure of the Universe, extending galaxy clustering analysis to the…
Spatially resolved scattered-light images of circumstellar (CS) debris in exoplanetary systems constrain the physical properties and orbits of the dust particles in these systems. They also inform on co-orbiting (but unseen) planets,…
Clustering has long been a popular unsupervised learning approach to identify groups of similar objects and discover patterns from unlabeled data in many applications. Yet, coming up with meaningful interpretations of the estimated clusters…
Debris disks around main-sequence stars are believed to derive from planetesimal populations that have accreted at early epochs and survived possible planet formation processes. While debris disks must contain solids in a broad range of…
The use of supervised methods in space science have demonstrated powerful capability in classification tasks, but unsupervised methods have been less utilized for the clustering of spacecraft observations. We use a combination of…