Related papers: Sequencing Silicates in the IRS Debris Disk Catalo…
The immense amount of time series data produced by astronomical surveys has called for the use of machine learning algorithms to discover and classify several million celestial sources. In the case of variable stars, supervised learning…
"Debris disks" around young stars (analogues of the Kuiper Belt in our Solar System) show a variety of non-trivial structures attributed to planetary perturbations and used to constrain the properties of the planets. However, these analyses…
Resolved debris disk features (e.g., warps, offsets, edges and gaps, azimuthal asymmetries, radially thickened rings, scale heights) contain valuable information about the underlying planetary systems, such as the posited planet's mass,…
We have collected a catalog of 1095 debris disks with properties and classification (resolved, planet, gas) information. From the catalog, we defined a less biased sample with 612 objects and presented the distributions of their stellar and…
We address the problem of un-supervised soft-clustering called micro-clustering. The aim of the problem is to enumerate all groups composed of records strongly related to each other, while standard clustering methods separate records at…
Polarisation is a powerful remote-sensing tool to study the nature of particles scattering the starlight. It is widely used to characterise interplanetary dust particles in the Solar System and increasingly employed to investigate…
Clustering is a popular unsupervised learning tool often used to discover groups within a larger population such as customer segments, or patient subtypes. However, despite its use as a tool for subgroup discovery and description - few…
We investigate the nature of the innermost regions of seven circumstellar disks around pre-main-sequence stars. Our object sample contains disks apparently at various stages of their evolution. Both single stars and spatially resolved…
Clustering is a well-known unsupervised machine learning approach capable of automatically grouping discrete sets of instances with similar characteristics. Constrained clustering is a semi-supervised extension to this process that can be…
The crystalline silicates features are mainly reflected in infrared bands. The Spitzer Infrared Spectrograph (IRS) collected numerous spectra of various objects and provided a big database to investigate crystalline silicates in a wide…
We herein introduce a new method of interpretable clustering that uses unsupervised binary trees. It is a three-stage procedure, the first stage of which entails a series of recursive binary splits to reduce the heterogeneity of the data…
Debris discs consist of belts of bodies ranging in size from dust grains to planetesimals; these belts are visible markers of planetary systems around other stars that can reveal the influence of extrasolar planets through their shape and…
Cluster analysis is a popular unsupervised learning tool used in many disciplines to identify heterogeneous sub-populations within a sample. However, validating cluster analysis results and determining the number of clusters in a data set…
We present 5 to 15 micron Spitzer Infrared Spectrograph (IRS) low resolution spectral data of a candidate debris disk around an M4.5 star identified as a likely member of the ~40 Myr old cluster NGC2547. The IRS spectrum shows a silicate…
Debris disks -- collisionally sustained belts of dust and sometimes gas around main sequence stars -- are remnants of planet formation processes and are found in systems ${\gtrsim}10$ Myr old. Millimeter-wavelength observations are…
Debris disks are intimately linked to planetary system evolution since the rocky material surrounding the host stars is due to secondary generation from the collisions of planetesimals. With the conclusion and lack of future large scale…
Multiple clustering aims at discovering diverse ways of organizing data into clusters. Despite the progress made, it's still a challenge for users to analyze and understand the distinctive structure of each output clustering. To ease this…
Submillimeter and near-infrared images of cool dusty debris disks and rings suggest the existence of unseen planets. At dusty but non-imaged stars, semi-major axes of associated planets can be estimated from the dust temperature. For some…
Clustering is an effective tool for astronomical spectral analysis, to mine clustering patterns among data. With the implementation of large sky surveys, many clustering methods have been applied to tackle spectroscopic and photometric data…
The connection between the nature of a protoplanetary disk and that of a debris disk is not well understood. Dust evolution, planet formation, and disk dissipation likely play a role in the processes involved. We aim to reconcile both…