An Estimation of the Gamma-Ray Burst Afterglow Apparent Optical Brightness Distribution Function

By using recent publicly available observational data obtained in conjunction with the NASA Swift gamma-ray burst mission and a novel data analysis technique, we have been able to make some rough estimates of the GRB afterglow apparent optical brightness distribution function. The results suggest that 71% of all burst afterglows have optical magnitudes with mR < 22.1 at 1000 seconds after the burst onset, the dimmest detected object in the data sample. There is a strong indication that the apparent optical magnitude distribution function peaks at mR ~ 19.5. Such estimates may prove useful in guiding future plans to improve GRB counterpart observation programs. The employed numerical techniques might find application in a variety of other data analysis problems in which the intrinsic distributions must be inferred from a heterogeneous sample.Comment: 15 pages including 2 tables and 7 figures, accepted for publication in Ap

A Deep Multicolor Survey V: The M Dwarf Luminosity Function

We present a study of M dwarfs discovered in a large area, multicolor survey. We employ a combination of morphological and color criteria to select M dwarfs to a limiting magnitude in V of 22, the deepest such ground-based survey for M dwarfs to date. We solve for the vertical disk stellar density law and use the resulting parameters to derive the M dwarf luminosity and mass functions from this sample. We find the stellar luminosity function peaks at M_V = 12 and declines thereafter. Our derived mass function for stars with M < 0.6 M_sun is inconsistent with a Salpeter function at the 3 sigma level; instead, we find the mass function is relatively flat for 0.6 M_sun > M > 0.1 M_sun.Comment: Accepted for publication in AJ. 19 pages including 4 embedded postscript figures (AASTEX

Likelihood Inference for Models with Unobservables: Another View

There have been controversies among statisticians on (i) what to model and (ii) how to make inferences from models with unobservables. One such controversy concerns the difference between estimation methods for the marginal means not necessarily having a probabilistic basis and statistical models having unobservables with a probabilistic basis. Another concerns likelihood-based inference for statistical models with unobservables. This needs an extended-likelihood framework, and we show how one such extension, hierarchical likelihood, allows this to be done. Modeling of unobservables leads to rich classes of new probabilistic models from which likelihood-type inferences can be made naturally with hierarchical likelihood.Comment: This paper discussed in: [arXiv:1010.0804], [arXiv:1010.0807], [arXiv:1010.0810]. Rejoinder at [arXiv:1010.0814]. Published in at http://dx.doi.org/10.1214/09-STS277 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Point Source Extraction with MOPEX

MOPEX (MOsaicking and Point source EXtraction) is a package developed at the Spitzer Science Center for astronomical image processing. We report on the point source extraction capabilities of MOPEX. Point source extraction is implemented as a two step process: point source detection and profile fitting. Non-linear matched filtering of input images can be performed optionally to increase the signal-to-noise ratio and improve detection of faint point sources. Point Response Function (PRF) fitting of point sources produces the final point source list which includes the fluxes and improved positions of the point sources, along with other parameters characterizing the fit. Passive and active deblending allows for successful fitting of confused point sources. Aperture photometry can also be computed for every extracted point source for an unlimited number of aperture sizes. PRF is estimated directly from the input images. Implementation of efficient methods of background and noise estimation, and modified Simplex algorithm contribute to the computational efficiency of MOPEX. The package is implemented as a loosely connected set of perl scripts, where each script runs a number of modules written in C/C++. Input parameter setting is done through namelists, ASCII configuration files. We present applications of point source extraction to the mosaic images taken at 24 and 70 micron with the Multiband Imaging Photometer (MIPS) as part of the Spitzer extragalactic First Look Survey and to a Digital Sky Survey image. Completeness and reliability of point source extraction is computed using simulated data.Comment: 20 pages, 13 Postscript figures, accepted for publication in PAS

LISA Science Results in the Presence of Data Disturbances

Each spacecraft in the Laser Interferometer Space Antenna houses a proof mass which follows a geodesic through spacetime. Disturbances which change the proof mass position, momentum, and/or acceleration will appear in the LISA data stream as additive quadratic functions. These data disturbances inhibit signal extraction and must be removed. In this paper we discuss the identification and fitting of monochromatic signals in the data set in the presence of data disturbances. We also present a preliminary analysis of the extent of science result limitations with respect to the frequency of data disturbances

The Star Formation History of the Local Group dwarf galaxy Leo I

We present a quantitative analysis of the star formation history (SFH) of the Local Group dSph galaxy Leo I, from the information in its HST [(V-I),I] color-magnitude diagram (CMD). The method we use is based in comparing, via synthetic CMDs, the expected distribution of stars in the CMD for different evolutionary scenarios, with the observed distribution. We consider the SFH to be composed by the SFR(t), the Z(t), the IMF, and a function $\beta(f,q)$, controlling the fraction $f$ and mass ratio distribution $q$ of binary stars. The comparison between the observed CMD and the model CMDs is done through chi-square minimization of the differences in the number of stars in a set of regions of the CMD. Our solution for the SFH of Leo I defines a minimum of chi-square in a well defined position of the parameter space, and the derived SFR(t) is robust, in the sense that its main characteristics are unchanged for different combinations of the remaining parameters. However, only a narrow range of assumptions for Z(t), IMF and $\beta(f,q)$ result in a good agreement between the data and the models, namely: Z=0.0004, a Kroupa et al. (1993) IMF or slightly steeper, and a relatively large fraction of binary stars. Most star formation activity (70% to 80%) occurred between 7 and 1 Gyr ago. At 1 Gyr ago, it abruptly dropped to a negligible value, but seems to have been active until at least ~ 300 Myr ago. Our results don't unambiguously answer the question of whether Leo I began forming stars around 15 Gyr ago, but it appears that the amount of this star formation, if existing at all, would be small.Comment: 25 pages + 14 figures. Accepted by The Astronomical Journa

Decoding the H-likelihood

Discussion of "Likelihood Inference for Models with Unobservables: Another View" by Youngjo Lee and John A. Nelder [arXiv:1010.0303]Comment: Published in at http://dx.doi.org/10.1214/09-STS277C the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org