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The measurement of cosmic shear requires deep imaging with high image quality on many lines of sight to sample the statistics of large-scale structure. The expected distortion of galaxy images by cosmic shear on the STIS angular scale is a…
Two new algorithms are described for matching two dimensional coordinate lists of point sources that are signifcantly faster than previous methods. By matching rarely occurring triangles (or more complex shapes) in the two lists, and by…
One of the most relevant problems in the extraction of scientifically useful information from wide field astronomical images (both photographic plates and CCD frames) is the recognition of the objects against a noisy background and their…
The volume of data that will be produced by the next generation of astrophysical instruments represents a significant opportunity for making unplanned and unexpected discoveries. Conversely, finding unexpected objects or phenomena within…
Conventional algorithms for rejecting cosmic-rays in single CCD exposures rely on the contrast between cosmic-rays and their surroundings, and may produce erroneous results if the Point Spread Function (PSF) is smaller than the largest…
By obtaining photometric redshift information, tomography allows us to cross-correlate galaxy ellipticities in different source redshift bins. The cross-correlation is non-vanishing because the different bins share much of the foreground…
We present an algorithm to optimally process uniformly sampled array image data obtained with a nondestructive readout. The algorithm discards full wells, removes cosmic ray (particle) hits and other glitches, and makes a nearly optimum…
Cosmic-ray positrons have long been considered a powerful probe of dark matter annihilation. In particular, myriad studies of the unexpected rise in the positron fraction have debated its dark matter or pulsar origins. In this paper, we…
A simple, yet general, formalism for the optimized linear combination of astrophysical images is constructed and demonstrated. The formalism allows the user to combine multiple undersampled images to provide oversampled output at high…
Deep learning is a powerful analysis technique that has recently been proposed as a method to constrain cosmological parameters from weak lensing mass maps. Due to its ability to learn relevant features from the data, it is able to extract…
We use cosmography to present constraints on the kinematics of the Universe, without postulating any underlying theoretical model. To this end, we use a Monte Carlo Markov Chain analysis to perform comparisons to the supernova Ia Union 2…
We explore strategies to extract cosmological constraints from a joint analysis of cosmic shear, galaxy-galaxy lensing, galaxy clustering, cluster number counts and cluster weak lensing. We utilize the CosmoLike software to simulate results…
It is a well-established fact that massive cosmological objects exhibit a ``geometrical bias'' that boosts their spatial correlations with respect to the underlying mass distribution. Although this geometrical bias is a simple function of…
Algebraic Subspace Clustering (ASC) is a simple and elegant method based on polynomial fitting and differentiation for clustering noiseless data drawn from an arbitrary union of subspaces. In practice, however, ASC is limited to…
Cosmic filaments are the channel through which galaxy groups assemble their mass. Cosmic connectivity, namely the number of filaments connected to a given group, is therefore expected to be an important ingredient in shaping group…
This paper describes a new approach to the optimization of information extraction in multi-wavelength image cubes of cosmological fields. The objective is to create a framework for the automatic identification and tagging of sources…
Weak lensing peak abundance analyses have been applied in different surveys and demonstrated to be a powerful statistics in extracting cosmological information complementary to cosmic shear two-point correlation studies. Future large…
Since the Universe is inhomogeneous on scales well below the Hubble radius, light bundles from distant galaxies are deflected and distorted by the tidal gravitational field of the large-scale matter distribution as they propagate through…
Precision cosmology is crucial to understand the different energy components in the Universe and their evolution through cosmic time. Gravitational wave sources are standard sirens that can accurately map out distances in the Universe.…
On small scales the observable Universe is highly inhomogeneous, with galaxies and clusters forming a complex web of voids and filaments. The optical properties of such configurations can be quite different from the perfectly smooth…