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 (features), detail methods to robustly estimate periodic light-curve features, introduce treeensemble 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%. 5 High-precision photometry missions (Kepler, MOST, CoRoT, etc.) are already challenging the theoretical understanding of the origin of variability and the connection of some specific sources to established classes of variables. 6 General Catalog of Variable Stars, http://www.sai.msu.su/groups/cluster/gcvs/gcvs/ 7 Not discussed herein are the challenges associated with discovery of variability. See Shin et al. (2009) for a review.

We present extensive early photometric (ultraviolet through near-infrared) and spectroscopic (optical and near-infrared) data on supernova (SN) 2008D as well as X-ray data analysis on the associated Swift X-ray transient (XRT) 080109. Our data span a time range of 5 hours before the detection of the X-ray transient to 150 days after its detection, and detailed analysis allowed us to derive constraints on the nature of the SN and its progenitor; throughout we draw comparisons with results presented in the literature and find several key aspects that differ. We show that the X-ray spectrum of XRT 080109 can be fit equally well by an absorbed power law or a superposition of about equal parts of both power law and blackbody. Our data first established that SN 2008D is a spectroscopically normal SN Ib (i.e., showing conspicuous He lines), and show that SN 2008D had a relatively long rise time of 18 days and a modest optical peak luminosity. The early-time light curves of the SN are dominated by a cooling stellar envelope (for ∆t ≈ 0.1 − 4 day, most pronounced in the blue bands) followed by 56 Ni decay. We construct a reliable measurement of the bolometric output for this stripped-envelope SN, and, combined with estimates of E K and M ej from the literature, estimate the stellar radius R ⋆ of its probable Wolf-Rayet progenitor. According to the model of Waxman et al. and of Chevalier & Fransson, we derive R W07 ⋆ = 1.2 ± 0.7 R ⊙ and R CF08 ⋆ = 12 ± 7 R ⊙ , respectively; the latter being more in line with typical WN stars. Spectra obtained at 3 and 4 months after maximum light show double-peaked oxygen lines that we associate with departures from spherical symmetry, as has been suggested for the inner ejecta of a number of SN Ib cores.

We report on strong H 2 and CO absorption from gas within the host galaxy of gamma-ray burst (GRB) 080607. Analysis of our Keck/LRIS afterglow spectrum reveals a very large H I column density (N H I = 10 22.70±0.15 cm −2 ) and strong metal-line absorption at z GRB = 3.0363 with a roughly solar metallicity. We detect a series of A − X bandheads from CO and estimate N (CO) = 10 16.5±0.3 cm −2 and T CO ex > 100 K. We argue that the high excitation temperature results from UV pumping of the CO gas by the GRB afterglow. Similarly, we observe H 2 absorption via the Lyman-Werner bands and estimate N H2 = 10 21.2±0.2 cm −2 with T H2 ex = 10-300 K. The afterglow photometry suggests an extinction law with R V ≈ 4 and A V ≈ 3.2 mag and requires the presence of a modest 2175Å bump. Additionally, modeling of the Swift/XRT X-ray spectrum confirms a large column density with N H = 10 22.58±0.04 cm −2 . Remarkably, this molecular gas has extinction properties, metallicity, and a CO/H 2 ratio comparable to those of translucent molecular clouds of the Milky Way, suggesting that star formation at high z proceeds in similar environments as today. However, the integrated dust-to-metals ratio is sub-Galactic, suggesting the dust is primarily associated with the molecular phase while the atomic gas has a much lower dust-to-gas ratio. Sightlines like GRB 080607 serve as powerful probes of nucleosynthesis and star-forming regions in the young universe and contribute to the population of "dark" GRB afterglows.