Related papers: Sequencing Silicates in the IRS Debris Disk Catalo…
Dusty debris disks around main-sequence stars are signposts for the existence of planetesimals and exoplanets. From cross-correlating \hip stars with the \iras catalogs, we identify 146 stars within 120 pc of Earth that show excess emission…
Infrared spectra from the Spitzer Space Telescope (SSC) of many debris disks are well fit with a single black body temperature which suggest clearings within the disk. We assume that inside the clearing orbital instability due to planets…
(abridged) Debris disks around main sequence stars are produced by the erosion and evaporation of unseen parent bodies. AU Microscopii (GJ 803) is a compelling object to study in the context of disk evolution across different spectral…
The majority of debris discs discovered so far have only been detected through infrared excess emission above stellar photospheres. While disc properties can be inferred from unresolved photometry alone under various assumptions for the…
Cluster analysis is the distribution of objects into different groups or more precisely the partitioning of a data set into subsets (clusters) so that the data in subsets share some common trait according to some distance measure. Unlike…
Context. Clusters of galaxies are important for cosmology and astrophysics. They may be discovered through either the summed optical/IR radiation originating from their member galaxies or via X-ray emission originating from the hot…
We investigate the stellar disk properties of a sample of 19 nearby spiral galaxies with low inclination and late Hubble type (Scd or later). We combine our high-resolution HST I-band observations with existing ground-based optical images…
Advanced satellite-born remote sensing instruments produce high-resolution multi-spectral data for much of the globe at a daily cadence. These datasets open up the possibility of improved understanding of cloud dynamics and feedback, which…
(Abridged) A numerical model of a circumstellar debris disk is developed and applied to observations of the circumstellar dust orbiting beta Pictoris. The model accounts for the rates at which dust is produced by collisions among unseen…
A novel methodology is proposed for clustering multivariate time series data using energy distance defined in Sz\'ekely and Rizzo (2013). Specifically, a dissimilarity matrix is formed using the energy distance statistic to measure…
We characterize the crystalline silicate content and spatial distribution of small dust grains in a large sample of protoplanetary disks in the Taurus-Auriga young cluster, using Spitzer Space Telescope mid-infrared spectra. In turn we use…
Observations of dusty debris disks can be used to test theories of planetesimal coagulation. Planetesimals of sizes up to a couple thousand kms are embedded in these disks and their mutual collisions generate the small dust grains that are…
High-dimensional datasets often contain multiple meaningful clusterings in different subspaces. For example, objects can be clustered either by color, weight, or size, revealing different interpretations of the given dataset. A variety of…
Spectral clustering requires the time-consuming decomposition of the Laplacian matrix of the similarity graph, thus limiting its applicability to large datasets. To improve the efficiency of spectral clustering, a top-down approach was…
Debris disks are dusty, gas-poor disks around main sequence stars (Backman & Paresce 1993; Lagrange, Backman & Artymowicz 2000; Zuckerman 2001). Micron-sized dust grains are inferred to exist in these systems from measurements of their…
Theoretical formation models and exoplanet detection surveys indicate that systems with multiple giant planets are common. We investigate how multiple super-thermal mass planets embedded in a circumstellar disk shape the dust distribution…
The environment plays a critical role in galaxy evolution, with galaxy clusters and their infall regions offering diverse conditions that shape galaxies before they enter the dense cluster core, a process known as ``pre-processing''.…
Spectral clustering is one of the most prominent clustering approaches. The distance-based similarity is the most widely used method for spectral clustering. However, people have already noticed that this is not suitable for multi-scale…
We study unsupervised clustering of documents at both the category and template levels using frozen multimodal encoders and classical clustering algorithms. We systematize a model-agnostic pipeline that (i) projects heterogeneous last-layer…
Crucial steps in the formation of stars and planets can be studied only at mid-infrared to far-infrared wavelengths, where SIRTF provides an unprecedented improvement in sensitivity. We will use all three SIRTF instruments (IRAC, MIPS, and…