Deep u*- and g-band Imaging of the Spitzer Space Telescope First Look Survey Field : Observations and Source Catalogs

We present deep u*-, and g-band images taken with the MegaCam on the 3.6 m Canada-France-Hawaii Telescope (CFHT) to support the extragalactic component of the Spitzer First Look Survey (hereafter, FLS). In this paper we outline the observations, present source catalogs and characterize the completeness, reliability, astrometric accuracy and number counts of this dataset. In the central 1 deg2 region of the FLS, we reach depths of g~26.5 mag, and u*~26.2 mag (AB magnitude, 5$\sigma$ detection over a 3" aperture) with ~4 hours of exposure time for each filter. For the entire FLS region (~5 deg2 coverage), we obtained u*-band images to the shallower depth of u*=25.0--25.4 mag (5$\sigma$, 3" aperture). The average seeing of the observations is 0.85" for the central field, and ~1.00" for the other fields. Astrometric calibration of the fields yields an absolute astrometric accuracy of 0.15" when matched with the SDSS point sources between 18<g<22. Source catalogs have been created using SExtractor. The catalogs are 50% complete and greater than 99.3% reliable down to g~26.5 mag and u*~26.2 mag for the central 1 deg2 field. In the shallower u*-band images, the catalogs are 50% complete and 98.2% reliable down to 24.8--25.4 mag. These images and source catalogs will serve as a useful resource for studying the galaxy evolution using the FLS data.Comment: 15 pages, 16 figure

Automatic Reconstruction of Fault Networks from Seismicity Catalogs: 3D Optimal Anisotropic Dynamic Clustering

We propose a new pattern recognition method that is able to reconstruct the 3D structure of the active part of a fault network using the spatial location of earthquakes. The method is a generalization of the so-called dynamic clustering method, that originally partitions a set of datapoints into clusters, using a global minimization criterion over the spatial inertia of those clusters. The new method improves on it by taking into account the full spatial inertia tensor of each cluster, in order to partition the dataset into fault-like, anisotropic clusters. Given a catalog of seismic events, the output is the optimal set of plane segments that fits the spatial structure of the data. Each plane segment is fully characterized by its location, size and orientation. The main tunable parameter is the accuracy of the earthquake localizations, which fixes the resolution, i.e. the residual variance of the fit. The resolution determines the number of fault segments needed to describe the earthquake catalog, the better the resolution, the finer the structure of the reconstructed fault segments. The algorithm reconstructs successfully the fault segments of synthetic earthquake catalogs. Applied to the real catalog constituted of a subset of the aftershocks sequence of the 28th June 1992 Landers earthquake in Southern California, the reconstructed plane segments fully agree with faults already known on geological maps, or with blind faults that appear quite obvious on longer-term catalogs. Future improvements of the method are discussed, as well as its potential use in the multi-scale study of the inner structure of fault zones

Segmentation of Fault Networks Determined from Spatial Clustering of Earthquakes

We present a new method of data clustering applied to earthquake catalogs, with the goal of reconstructing the seismically active part of fault networks. We first use an original method to separate clustered events from uncorrelated seismicity using the distribution of volumes of tetrahedra defined by closest neighbor events in the original and randomized seismic catalogs. The spatial disorder of the complex geometry of fault networks is then taken into account by defining faults as probabilistic anisotropic kernels, whose structures are motivated by properties of discontinuous tectonic deformation and previous empirical observations of the geometry of faults and of earthquake clusters at many spatial and temporal scales. Combining this a priori knowledge with information theoretical arguments, we propose the Gaussian mixture approach implemented in an Expectation-Maximization (EM) procedure. A cross-validation scheme is then used and allows the determination of the number of kernels that should be used to provide an optimal data clustering of the catalog. This three-steps approach is applied to a high quality relocated catalog of the seismicity following the 1986 Mount Lewis ($M_l=5.7$) event in California and reveals that events cluster along planar patches of about 2 km$^2$, i.e. comparable to the size of the main event. The finite thickness of those clusters (about 290 m) suggests that events do not occur on well-defined euclidean fault core surfaces, but rather that the damage zone surrounding faults may be seismically active at depth. Finally, we propose a connection between our methodology and multi-scale spatial analysis, based on the derivation of spatial fractal dimension of about 1.8 for the set of hypocenters in the Mnt Lewis area, consistent with recent observations on relocated catalogs

Variable Point Sources in Sloan Digital Sky Survey Stripe 82. I. Project Description and Initial Catalog (0 h < R.A. < 4 h)

We report the first results of a study of variable point sources identified using multi-color time-series photometry from Sloan Digital Sky Survey (SDSS) Stripe 82 over a span of nearly 10 years (1998-2007). We construct a light-curve catalog of 221,842 point sources in the R.A. 0-4 h half of Stripe 82, limited to r = 22.0, that have at least 10 detections in the ugriz bands and color errors of < 0.2 mag. These objects are then classified by color and by cross-matching them to existing SDSS catalogs of interesting objects. We use inhomogeneous ensemble differential photometry techniques to greatly improve our sensitivity to variability. Robust variable identification methods are used to extract 6520 variable candidates in this dataset, resulting in an overall variable fraction of ~2.9% at the level of 0.05 mag variability. A search for periodic variables results in the identification of 30 eclipsing/ellipsoidal binary candidates, 55 RR Lyrae, and 16 Delta Scuti variables. We also identify 2704 variable quasars matched to the SDSS Quasar catalog (Schneider et al. 2007), as well as an additional 2403 quasar candidates identified by their non-stellar colors and variability properties. Finally, a sample of 11,328 point sources that appear to be nonvariable at the limits of our sensitivity is also discussed. (Abridged.)Comment: 67 pages, 27 figures. Accepted for publication in ApJS. Catalog available at http://shrike.pha.jhu.edu/stripe82-variable

Earthquake Arrival Association with Backprojection and Graph Theory

The association of seismic wave arrivals with causative earthquakes becomes progressively more challenging as arrival detection methods become more sensitive, and particularly when earthquake rates are high. For instance, seismic waves arriving across a monitoring network from several sources may overlap in time, false arrivals may be detected, and some arrivals may be of unknown phase (e.g., P- or S-waves). We propose an automated method to associate arrivals with earthquake sources and obtain source locations applicable to such situations. To do so we use a pattern detection metric based on the principle of backprojection to reveal candidate sources, followed by graph-theory-based clustering and an integer linear optimization routine to associate arrivals with the minimum number of sources necessary to explain the data. This method solves for all sources and phase assignments simultaneously, rather than in a sequential greedy procedure as is common in other association routines. We demonstrate our method on both synthetic and real data from the Integrated Plate Boundary Observatory Chile (IPOC) seismic network of northern Chile. For the synthetic tests we report results for cases with varying complexity, including rates of 500 earthquakes/day and 500 false arrivals/station/day, for which we measure true positive detection accuracy of > 95%. For the real data we develop a new catalog between January 1, 2010 - December 31, 2017 containing 817,548 earthquakes, with detection rates on average 279 earthquakes/day, and a magnitude-of-completion of ~M1.8. A subset of detections are identified as sources related to quarry and industrial site activity, and we also detect thousands of foreshocks and aftershocks of the April 1, 2014 Mw 8.2 Iquique earthquake. During the highest rates of aftershock activity, > 600 earthquakes/day are detected in the vicinity of the Iquique earthquake rupture zone

Projection, Spatial Correlations, and Anisotropies in a Large and Complete Sample of Abell Clusters

An analysis of R >= 1 Abell clusters is presented for samples containing recent redshifts from the MX Northern Abell Cluster Survey. The newly obtained redshifts from the MX Survey as well as those from the ESO Nearby Abell Cluster Survey (ENACS) provide the necessary data for the largest magnitude-limited correlation analysis of rich clusters in the entire sky (excluding the galactic plane) to date. We find 19.4 <= r_0 <= 23.3 h^-1Mpc, -1.92 <= gamma <= -1.83 for four different subsets of Abell/ACO clusters, including a large sample (N=104) of cD clusters. We have used this dataset to look for line-of-sight anisotropies within the Abell/ACO catalogs. We show that the strong anisotropies present in previously studied Abell cluster datasets are not present in our R >= 1 samples. There are, however, indications of residual anisotropies which we show are the result of two elongated superclusters, Ursa Majoris and Corona Borealis, whose axes lie near the line-of-sight. After rotating these superclusters so that their semi-major axes are prependicular to the line-of-sight, we find no anisotropies as indicated by the correlation function. The amplitude and slope of the two-point correlation function remain the same before and after these rotations. We also remove a subset of R = 1 Abell/ACO clusters that show sizable foreground/background galaxy contamination and again find no change in the amplitude or slope of the correlation function. We conclude that the correlation length of R >= 1 Abell clusters is not artificially enhanced by line-of-sight anisotropies.Comment: 37 pages, 8 figures, AASTeX Accepted for publication in Ap