Time-resolved Neutron-gamma-ray Data Acquisition for in Situ Subsurface Planetary Geochemistry

The current gamma-ray/neutron instrumentation development effort at NASA Goddard Space Flight Center aims to extend the use of active pulsed neutron interrogation techniques to probe the subsurface elemental composition of planetary bodies in situ. Previous NASA planetary science missions, that used neutron and/or gamma-ray spectroscopy instruments, have relied on neutrons produced from galactic cosmic rays. One of the distinguishing features of this effort is the inclusion of a high intensity 14.1 MeV pulsed neutron generator synchronized with a custom data acquisition system to time each event relative to the pulse. With usually only one opportunity to collect data, it is difficult to set a priori time-gating windows to obtain the best possible results. Acquiring time-tagged, event-by-event data from nuclear induced reactions provides raw data sets containing channel/energy, and event time for each gamma ray or neutron detected. The resulting data set can be plotted as a function of time or energy using optimized analysis windows after the data are acquired. Time windows can now be chosen to produce energy spectra that yield the most statistically significant and accurate elemental composition results that can be derived from the complete data set. The advantages of post-processing gamma-ray time-tagged event-by-event data in experimental tests using our prototype instrument will be demonstrated

CfAIR2: Near Infrared Light Curves of 94 Type Ia Supernovae

CfAIR2 is a large homogeneously reduced set of near-infrared (NIR) light curves for Type Ia supernovae (SN Ia) obtained with the 1.3m Peters Automated InfraRed Imaging TELescope (PAIRITEL). This data set includes 4607 measurements of 94 SN Ia and 4 additional SN Iax observed from 2005-2011 at the Fred Lawrence Whipple Observatory on Mount Hopkins, Arizona. CfAIR2 includes JHKs photometric measurements for 88 normal and 6 spectroscopically peculiar SN Ia in the nearby universe, with a median redshift of z~0.021 for the normal SN Ia. CfAIR2 data span the range from -13 days to +127 days from B-band maximum. More than half of the light curves begin before the time of maximum and the coverage typically contains ~13-18 epochs of observation, depending on the filter. We present extensive tests that verify the fidelity of the CfAIR2 data pipeline, including comparison to the excellent data of the Carnegie Supernova Project. CfAIR2 contributes to a firm local anchor for supernova cosmology studies in the NIR. Because SN Ia are more nearly standard candles in the NIR and are less vulnerable to the vexing problems of extinction by dust, CfAIR2 will help the supernova cosmology community develop more precise and accurate extragalactic distance probes to improve our knowledge of cosmological parameters, including dark energy and its potential time variation.Comment: 31 pages, 15 figures, 10 tables. Accepted to ApJS. v2 modified to more closely match journal versio

Type IIb Supernova SN 2011dh: Spectra and Photometry from the Ultraviolet to the Near-Infrared

We report spectroscopic and photometric observations of the Type IIb SN 2011dh obtained between 4 and 34 days after the estimated date of explosion (May 31.5 UT). The data cover a wide wavelength range from 2,000 Angstroms in the UV to 2.4 microns in the NIR. Optical spectra provide line profiles and velocity measurements of HI, HeI, CaII and FeII that trace the composition and kinematics of the SN. NIR spectra show that helium is present in the atmosphere as early as 11 days after the explosion. A UV spectrum obtained with the STIS reveals that the UV flux for SN 2011dh is low compared to other SN IIb. The HI and HeI velocities in SN 2011dh are separated by about 4,000 km/s at all phases. We estimate that the H-shell of SN 2011dh is about 8 times less massive than the shell of SN 1993J and about 3 times more massive than the shell of SN 2008ax. Light curves (LC) for twelve passbands are presented. The maximum bolometric luminosity of $1.8 \pm 0.2 \times 10^{42}$ erg s$^{-1}$ occurred about 22 days after the explosion. NIR emission provides more than 30% of the total bolometric flux at the beginning of our observations and increases to nearly 50% of the total by day 34. The UV produces 16% of the total flux on day 4, 5% on day 9 and 1% on day 34. We compare the bolometric light curves of SN 2011dh, SN 2008ax and SN 1993J. The LC are very different for the first twelve days after the explosions but all three SN IIb display similar peak luminosities, times of peak, decline rates and colors after maximum. This suggests that the progenitors of these SN IIb may have had similar compositions and masses but they exploded inside hydrogen shells that that have a wide range of masses. The detailed observations presented here will help evaluate theoretical models for this supernova and lead to a better understanding of SN IIb.Comment: 23 pages, 14 figures, 9 tables, accepted by Ap

On Machine-Learned Classification of Variable Stars with Sparse and Noisy Time-Series Data

With the coming data deluge from synoptic surveys, there is a growing need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly-observed variables based on a small number of time-series measurements. In this paper, we introduce a methodology for variable-star classification, drawing from modern machine-learning techniques. We describe how to homogenize the information gleaned from light curves by selection and computation of real-numbered metrics ("feature"), detail methods to robustly estimate periodic light-curve features, introduce tree-ensemble methods for accurate variable star classification, and show how to rigorously evaluate the classification results using cross validation. On a 25-class data set of 1542 well-studied variable stars, we achieve a 22.8% overall classification error using the random forest classifier; this represents a 24% improvement over the best previous classifier on these data. This methodology is effective for identifying samples of specific science classes: for pulsational variables used in Milky Way tomography we obtain a discovery efficiency of 98.2% and for eclipsing systems we find an efficiency of 99.1%, both at 95% purity. We show that the random forest (RF) classifier is superior to other machine-learned methods in terms of accuracy, speed, and relative immunity to features with no useful class information; the RF classifier can also be used to estimate the importance of each feature in classification. Additionally, we present the first astronomical use of hierarchical classification methods to incorporate a known class taxonomy in the classifier, which further reduces the catastrophic error rate to 7.8%. Excluding low-amplitude sources, our overall error rate improves to 14%, with a catastrophic error rate of 3.5%.Comment: 23 pages, 9 figure

GJ 3236: a new bright, very low-mass eclipsing binary system discovered by the MEarth observatory

We report the detection of eclipses in GJ 3236, a bright (I = 11.6) very low mass binary system with an orbital period of 0.77 days. Analysis of light- and radial velocity curves of the system yielded component masses of 0.38 +/- 0.02 and 0.28 +/- 0.02 Msol. The central values for the stellar radii are larger than the theoretical models predict for these masses, in agreement with the results for existing eclipsing binaries, although the present 5% observational uncertainties limit the significance of the larger radii to approximately 1 sigma. Degeneracies in the light curve models resulting from the unknown configuration of surface spots on the components of GJ 3236 currently dominate the uncertainties in the radii, and could be reduced by obtaining precise, multi-band photometry covering the full orbital period. The system appears to be tidally synchronized and shows signs of high activity levels as expected for such a short orbital period, evidenced by strong Halpha emission lines in the spectra of both components. These observations probe an important region of mass-radius parameter space around the predicted transition to fully-convective stellar interiors, where there are a limited number of precise measurements available in the literature.Comment: 14 pages, 5 figures, 10 tables, emulateapj format. Accepted for publication in Ap

The Rapidly Flaring Afterglow of the Very Bright and Energetic GRB 070125

We report on multi-wavelength observations, ranging from the X-ray to radio wave bands, of the IPN-localized gamma-ray burst GRB 070125. Spectroscopic observations reveal the presence of absorption lines due to O I, Si II, and C IV, implying a likely redshift of z = 1.547. The well-sampled light curves, in particular from 0.5 to 4 days after the burst, suggest a jet break at 3.7 days, corresponding to a jet opening angle of ~7.0 degrees, and implying an intrinsic GRB energy in the 1 - 10,000 keV band of around E = (6.3 - 6.9)x 10^(51) erg (based on the fluences measured by the gamma-ray detectors of the IPN network). GRB 070125 is among the brightest afterglows observed to date. The spectral energy distribution implies a host extinction of Av < 0.9 mag. Two rebrightening episodes are observed, one with excellent time coverage, showing an increase in flux of 56% in ~8000 seconds. The evolution of the afterglow light curve is achromatic at all times. Late-time observations of the afterglow do not show evidence for emission from an underlying host galaxy or supernova. Any host galaxy would be subluminous, consistent with current GRB host-galaxy samples. Evidence for strong Mg II absorption features is not found, which is perhaps surprising in view of the relatively high redshift of this burst and the high likelihood for such features along GRB-selected lines of sight.Comment: 50 pages, 9 figures, 5 tables Accepted to the Astrophysical Journa

Type Ia Supernovae are Good Standard Candles in the Near Infrared: Evidence from PAIRITEL

We have obtained 1087 NIR (JHKs) measurements of 21 SNe Ia using PAIRITEL, nearly doubling the number of well-sampled NIR SN Ia light curves. These data strengthen the evidence that SNe Ia are excellent standard candles in the NIR, even without correction for optical light-curve shape. We construct fiducial NIR templates for normal SNe Ia from our sample, excluding only the three known peculiar SNe Ia: SN 2005bl, SN 2005hk, and SN 2005ke. The H-band absolute magnitudes in this sample of 18 SNe Ia have an intrinsic rms of only 0.15 mag with no correction for light-curve shape. We found a relationship between the H-band extinction and optical color excess of AH=0.2E(B-V). This variation is as small as the scatter in distance modulus measurements currently used for cosmology based on optical light curves after corrections for light-curve shape. Combining the homogeneous PAIRITEL measurements with 23 SNe Ia from the literature, these 41 SNe Ia have standard H-band magnitudes with an rms scatter of 0.16 mag. The good match of our sample with the literature sample suggests there are few systematic problems with the photometry. We present a nearby NIR Hubble diagram that shows no correlation of the residuals from the Hubble line with light-curve properties. Future samples that account for optical and NIR light-curve shapes, absorption, spectroscopic variation, or host-galaxy properties may reveal effective ways to improve the use of SNe Ia as distance indicators. Since systematic errors due to dust absorption in optical bands remain the leading difficulty in the cosmological use of supernovae, the good behavior of SN Ia NIR light curves and their relative insensitivity to reddening make these objects attractive candidates for future cosmological work.Comment: 37 pages. 8 Figures. 3 Tables. Revised to ApJ-accepted versio

PTF10fqs: A Luminous Red Nova in the Spiral Galaxy Messier 99

The Palomar Transient Factory (PTF) is systematically charting the optical transient and variable sky. A primary science driver of PTF is building a complete inventory of transients in the local Universe (distance less than 200 Mpc). Here, we report the discovery of PTF10fqs, a transient in the luminosity "gap" between novae and supernovae. Located on a spiral arm of Messier 99, PTF 10fqs has a peak luminosity of Mr = -12.3, red color (g-r = 1.0) and is slowly evolving (decayed by 1 mag in 68 days). It has a spectrum dominated by intermediate-width H (930 km/s) and narrow calcium emission lines. The explosion signature (the light curve and spectra) is overall similar to thatof M85OT2006-1, SN2008S, and NGC300OT. The origin of these events is shrouded in mystery and controversy (and in some cases, in dust). PTF10fqs shows some evidence of a broad feature (around 8600A) that may suggest very large velocities (10,000 km/s) in this explosion. Ongoing surveys can be expected to find a few such events per year. Sensitive spectroscopy, infrared monitoring and statistics (e.g. disk versus bulge) will eventually make it possible for astronomers to unravel the nature of these mysterious explosions.Comment: 12 pages, 12 figures, Replaced with published versio

Active Learning to Overcome Sample Selection Bias: Application to Photometric Variable Star Classification

Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because a) standard assumptions for machine-learned model selection procedures break down and b) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting (IW), co-training (CT), and active learning (AL). We argue that AL---where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up---is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and OGLE, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply active learning to classify variable stars in the ASAS survey, finding dramatic improvement in our agreement with the ACVS catalog, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.Comment: 43 pages, 11 figures, submitted to Ap