The NOAO Data Lab aims to provide infrastructure to maximize community use of the high-value survey datasets now being collected with NOAO telescopes and instruments. As a science exploration framework, the Data Lab allow users to access and search databases containing large (i.e. terabyte-scale) catalogs, visualize, analyze, and store the results of these searches, combine search results with data from other archives or facilities, and share these results with collaborators using a shared workspace and/or data publication service. In the process of implementing the needed tools and services, specific science cases are used to guide development of the system framework and tools. The result is a Year-1 capability demonstration that (fully or partially) implements each of the major architecture components in the context of a real-world science use-case. In this paper, we discuss how this model of science-driven development helped us to build a fully functional system capable of executing the chosen science case, and how we plan to scale this system to support general use in the next phase of the project.

Collaborative research/computing environments are essential for working with the next generations of large astronomical data sets. A key component of them is a distributed storage system to enable data hosting, sharing, and publication. VOSpace1 is a lightweight interface providing network access to arbitrary backend storage solutions and endorsed by the International Virtual Observatory Alliance (IVOA). Although similar APIs exist, such as Amazon S3, WebDav, and Dropbox, VOSpace is designed to be protocol agnostic, focusing on data control operations, and supports asynchronous and third-party data transfers, thereby minimizing unnecessary data transfers. It also allows arbitrary computations to be triggered as a result of a transfer operation: for example, a file can be automatically ingested into a database when put into an active directory or a data reduction task, such as Sextractor, can be run on it. In this paper, we shall describe the VOSpace implementations that we have developed for the NOAO Data Lab. These offer both dedicated remote storage, accessible as a local file system via FUSE, and a local VOSpace service to easily enable data synchronization.

High precision Kepler photometry is used to explore the details of AGB light curves. Since AGB variability has a typical time scale on order of a year we present methods for the removal of long term trends and quarterly changes in Kepler data. While undergoing long period variations of many magnitudes, the light curves are shown to be smooth at the millimagnitude level over much shorter time intervals. No flares or other rapid events were detected down to the sub-day time scale.

We describe the NOAO Data Lab to help community users take advantage of current large surveys and prepare them even larger surveys in the era of LSST. The Data Lab will allow users to efficiently utilize catalogs of billions of objects, combine traditional telescope image and spectral data with external archives, share custom results with collaborators, publish data products to other users, and experiment with analysis toolkits. Specific science cases will be used to develop a prototype framework and tools, allowing us to work directly with scientists from survey teams to ensure development remains focused on scientifically productive tasks.

The discovery of variable and transient sources is an essential product of synoptic surveys. The alert stream will require filtering for personalized criteria-a process managed by a functionality commonly described as a Broker. In order to understand quantitatively the magnitude of the alert generation and Broker tasks, we have undertaken an analysis of the most numerous types of variable targets in the sky-Galactic stars, quasi-stellar objects (QSOs), active galactic nuclei (AGNs), and asteroids. It is found that the Large Synoptic Survey Telescope (LSST) will be capable of discovering similar to 10(5) high latitude (|b| > 20 degrees.) variable stars per night at the beginning of the survey. (The corresponding number for |b| < 20 degrees. is orders of magnitude larger, but subject to caveats concerning extinction and crowding.) However, the number of new discoveries may well drop below 100 per night within less than one year. The same analysis applied to GAIA clarifies the complementarity of the GAIA and LSST surveys. Discovery of AGNs and QSOs are each predicted to begin at similar to 3000 per night and decrease by 50 times over four years. Supernovae are expected at similar to 1100 per night, and after several survey years will dominate the new variable discovery rate. LSST asteroid discoveries will start at > 10(5) per night, and if orbital determination has a 50% success rate per epoch, they will drop below 1000 per night within two years.

We present the first secondary eclipse and phase curve observations for the highly eccentric hot Jupiter HAT-P-2b in the 3.6, 4.5, 5.8, and 8.0 mu m bands of the Spitzer Space Telescope. The 3.6 and 4.5 mu m data sets span an entire orbital period of HAT-P-2b (P = 5.6334729 d), making them the longest continuous phase curve observations obtained to date and the first full-orbit observations of a planet with an eccentricity exceeding 0.2. We present an improved non-parametric method for removing the intrapixel sensitivity variations in Spitzer data at 3.6 and 4.5 mu m that robustly maps position-dependent flux variations. We find that the peak in planetary flux occurs at 4.39 +/- 0.28, 5.84 +/- 0.39, and 4.68 +/- 0.37 hr after periapse passage with corresponding maxima in the planet/star flux ratio of 0.1138% +/- 0.0089%, 0.1162% +/- 0.0080%, and 0.1888% +/- 0.0072% in the 3.6, 4.5, and 8.0 mu m bands, respectively. Our measured secondary eclipse depths of 0.0996% +/- 0.0072%, 0.1031% +/- 0.0061%, 0.071% (+0.029%)(-0.013%), and 0.1392% +/- 0.0095% in the 3.6, 4.5, 5.8, and 8.0 mu m bands, respectively, indicate that the planet cools significantly from its peak temperature before we measure the dayside flux during secondary eclipse. We compare our measured secondary eclipse depths to the predictions from a one-dimensional radiative transfer model, which suggests the possible presence of a transient day side inversion in HAT-P-2b's atmosphere near periapse. We also derive improved estimates for the system parameters, including its mass, radius, and orbital ephemeris. Our simultaneous fit to the transit, secondary eclipse, and radial velocity data allows us to determine the eccentricity (e = 0.50910 +/- 0.00048) and argument of periapse (omega = 188 degrees. 09 +/- 0 degrees.39) of HAT-P-2b's orbit with a greater precision than has been achieved for any other eccentric extrasolar planet. We also find evidence for a long-term linear trend in the radial velocity data. This trend suggests the presence of another substellar companion in the HAT-P-2 system, which could have caused HAT-P-2b to migrate inward to its present-day orbit via the Kozai mechanism.

The Kepler Eclipsing Binary Catalog (KEBC)describes 2165 eclipsing binaries identified in the 115 deg^2 Kepler Field based on observations from Kepler quarters Q0, Q1, and Q2. The periods in the KEBC are given in units of days out to six decimal places but no period errors are provided. We present the PEC (Period Error Calculator) algorithm which can be used to estimate the period errors of strictly periodic variables observed by the Kepler Mission. The PEC algorithm is based on propagation of error theory and assumes that observation of every light curve peak/minimum in a long time-series observation can be unambiguously identified. The PEC algorithm can be efficiently programmed using just a few lines of C computer language code. The PEC algorithm was used to develop a simple model which provides period error estimates for eclipsing binaries in the KEBC with periods less than 62.5 days. KEBC systems with periods >=62.5 days have KEBC period errors of about 0.0144 days. Periods and period errors of 7 eclipsing binary systems in the KEBC were measured using the NASA Exoplanet Archive Periodogram Service and compared to period errors estimated using the PEC algorithm.

Currently, most microprocessors use multiple cores to increase performance while limiting power usage. Some processors use not just a few cores, but tens of cores or even 100 cores. One such many-core microprocessor is the Maestro processor, which is based on Tilera's TILE64 processor. The Maestro chip is a 49-core, general-purpose, radiation-hardened processor designed for space applications. The Maestro processor, unlike the TILE64, has a floating-point coprocessor in each core for improved floating point performance. The Maestro processor runs at up to 350 MHz clock frequency. On the Maestro processor, we implemented an FFT and an image processing application called CRBLASTER and evaluated the performance. The FFT is a well-known and commonly used signal processing kernel. CRBLASTER is a parallel-processing image-analysis application that does cosmic-ray rejection on CCD (charge-coupled device) images using the embarrassingly-parallel L. A. COSMIC algorithm. Both applications were written in C. CRBLASTER uses the high-performance computing industry standard Message Passing Interface (MPI) library. The achieved performance of the FFT was up to 3,813 MFLOPS, and the speedup compared to single tile was 46.4 using 49 tiles. The speedup for CRBLASTER, which was memory-bound, was up to 12.5 using 36 tiles.

I describe the performance of the CRBLASTER computational framework on a 350-MHz 49-core Maestro Development Board (MDB). The 49-core Interim Test Chip (ITC) was developed by the U.S. Government and is based on the intellectual property of the 64-core TILE64 processor of the Tilera Corporation. The Maestro processor is intended for use in the high radiation environments found in space; the ITC was fabricated using IBM 90-nm CMOS 9SF technology and Radiation-Hardening-by-Design (RHDB) rules. CRBLASTER is a parallel-processing cosmic-ray rejection application based on a simple computational framework that uses the high-performance computing industry standard Message Passing Interface (MPI) library. CRBLASTER was designed to be used by research scientists to easily port image-analysis programs based on embarrassingly-parallel algorithms to a parallel-processing environment such as a multi-node Beowulf cluster or multi-core processors using MPI. I describe my experience of porting CRBLASTER to the 64-core TILE64 processor, the Maestro simulator, and finally the 49-core Maestro processor itself. Performance comparisons using the ITC are presented between emulating all floating-point operations in software and doing all floating point operations with hardware assist from an IEEE-754 compliant Aurora FPU (floating point unit) that is attached to each of the 49 cores. Benchmarking of the CRBLASTER computational framework using the memory-intensive L.A.COSMIC cosmic ray rejection algorithm and a computational-intensive Poisson noise generator reveal subtleties of the Maestro hardware design. Lastly, I describe the importance of using real scientific applications during the testing phase of next-generation computer hardware; complex real-world scientific applications can stress hardware in novel ways that may not necessarily be revealed while executing simple applications or unit tests.

We use deep Hubble Space Telescope Advanced Camera for Surveys/High Resolution Channel observations of a field within M32 (F1) and an M31 background field (F2) to determine the star formation history (SFH) of M32 from its resolved stellar population. We find that 2–5 Gyr old stars contribute ∼40% ± 17% of M32's mass, while ∼55% ± 21% of M32's mass comes from stars older than 5 Gyr. The mass-weighted mean age and metallicity of M32 at F1 are 〈Age〉 = 6.8 ± 1.5 Gyr and 〈[M/H]〉 = −0.01 ± 0.08 dex. The SFH additionally indicates the presence of young (<2 Gyr old), metal-poor ([M/H] ∼ −0.7) stars, suggesting that blue straggler stars contribute ∼2% of the mass at F1; the remaining ∼3% of the mass is in young metal-rich stars. Line-strength indices computed from the SFH imply a light-weighted mean age and metallicity of 4.9 Gyr and [M/H] = -0.12 dex, and single stellar population-equivalent parameters of 2.9 ± 0.2 Gyr and [M/H] = 0.02 ± 0.01 dex at F1 (∼2.7 re). This contradicts spectroscopic studies that show a steep age gradient from M32's center to 1 re. The inferred SFH of the M31 background field F2 reveals that the majority of its stars are old, with ∼95% of its mass already acquired 5–14 Gyr ago. It is composed of two dominant populations; ∼30% ± 7.5% of its mass is in a 5–8 Gyr old population, and ∼65% ± 9% of the mass is in an 8–14 Gyr old population. The mass-weighted mean age and metallicity of F2 are 〈Age〉 = 9.2 ± 1.2 Gyr and 〈[M/H]〉 = −0.10 ± 0.10 dex, respectively. Our results suggest that the inner disk and spheroid populations of M31 are indistinguishable from those of the outer disk and spheroid. Assuming the mean age of M31's disk at F2 (∼1 disk scale length) to be ∼5–9 Gyr, our results agree with an inside-out disk formation scenario for M31's disk.

We present PHAST, a new IDL astronomical image viewer, based on the existing ATVapplication, which has been optimized for astrometry of Near Earth Objects (NEOs). After describing the features of PHAST, we describe how PHAST enabled the recovery of the Virtual Impactor (VI) 2011AX22 and the Potentially Hazardous Asteroid (PHA) 2008OX1. The recovery of 2011AX22 led to a large improvement in the time of perihelion passage and in the semimajor axis and eccentricity of its orbit. The distance of closest approach in May 2055 was moved away from Earth to > 1 lunar distance. As a result of the orbital improvement made possible by the successful recovery, NEODyS downgraded 2011AX22 from a VI to a PHA, having ruled out the chance of an Earth impact this century. The recovery of 2008OX1 extended its observational arc to 1303 days-more than 2.5 orbital revolutions. It was confirmed to be a PHA and its orbit was improved sufficiently to permit prediction of its sky position to within 1 '' over an interval of 10 years into the future. We discuss the astrometric and photometric performance of PHAST and then conclude by briefly describing future enhancements in the application.

We present a new computational approach to the inversion of solar photospheric Stokes polarization profiles, under the Milne–Eddington model, for vector magnetography. Our code, named GENESIS, employs multi-threaded parallel-processing techniques to harness the computing power of graphics processing units (GPUs), along with algorithms designed to exploit the inherent parallelism of the Stokes inversion problem. Using a genetic algorithm (GA) engineered specifically for use with a GPU, we produce full-disk maps of the photospheric vector magnetic field from polarized spectral line observations recorded by the Synoptic Optical Long-term Investigations of the Sun (SOLIS) Vector Spectromagnetograph (VSM) instrument. We show the advantages of pairing a population-parallel GA with data-parallel GPU-computing techniques, and present an overview of the Stokes inversion problem, including a description of our adaptation to the GPU-computing paradigm. Full-disk vector magnetograms derived by this method are shown using SOLIS/VSM data observed on 2008 March 28 at 15:45 UT.

I describe the performance of the CRBLASTER computational framework on a 350-MHz 49-core Maestro Development Board (MBD). The.49-core Interim Test Chip (ITC) was developed by the U.S. Government and is based on the intellectual property of the 64-core TILE64 processor of the Tilera Corporation. The Maestro processor is intended for use in the high radiation environments found in space; the ITC was fabricated using IBM 90-nm CMOS 9SF technology and Radiation-Hardening-by-Design (RHDB) rules. CRBLASTER is a parallel-processing cosmic-ray rejection application based on a simple computational framework that uses the high-performance computing industry standard Message Passing Interface (MPI) library. CRBLASTER was designed to be used by research scientists to easily port image-analysis programs based on embarrassingly-parallel algorithms to a parallel-processing environment such as a multi-node Beowulf cluster or multi-core processors using MPI. I describe my experience of porting CRBLASTER to the 64-core TILE64 processor, the Maestro simulator, and finally the 49-core Maestro processor itself. Performance comparisons using the ITC are presented between emulating all floating-point operations in software and doing all floating point operations with hardware assist from an IEEE-754 compliant Aurora FPU (floating point unit) that is attached to each of the 49 cores. Benchmarking of the CRBLASTER computational framework using the memory-intensive L.A.COSMIC cosmic ray rejection algorithm and a computational-intensive Poisson noise generator reveal subtleties of the Maestro hardware design. Lastly, I describe the importance of using real scientific applications during the testing phase of next-generation computer hardware; complex real-world scientific applications can stress hardware in novel ways that may not necessarily be revealed while executing simple applications or unit tests.