Present and Future Prospects for GRB Standard Candles

Following our previous work, we conclude that a GRB standard candle constructed from the Ghirlanda et al. power-law relation between the geometry-corrected energy (E_gamma) and the peak of the rest-frame prompt burst spectrum (E_p) is not yet cosmographically useful, despite holding some potential advantages over SNe Ia. This is due largely to the small sample of \~20 GRBs with the required measured redshifts, jet-breaks, and peak energies, and to the strong sensitivity of the goodness-of-fit of the power-law to input assumptions. The most important such finding concerns the sensitivity to the generally unknown density (and density profile), of the circumburst medium. Although the E_p-E_gamma relation is a highly significant correlation over many cosmologies, until the sample expands to include many low-z events, it will be most sensitive to Omega_M but essentially insensitive to Omega_Lambda and w, with some hope of constraining dw/dt with high-z GRB data alone. The relation clearly represents a significant improvement in the search for an empirical GRB standard candle, but is further hindered by an unknown physical basis for the relation, the lack of a low-z training set to calibrate the relation in a cosmology-independent way, and several major potential systematic uncertainties and selection effects. Until these concerns are addressed, a larger sample is acquired, and attempts are made to marginalize or perform Monte Carlo simulations over the unknown density distribution, we urge caution concerning claims of the utility of GRBs for cosmography and especially the attempts to combine GRBs with SNe Ia.Comment: 5 pages, 2 figures, "Proceedings, Gamma-Ray Bursts in the Afterglow Era: 4th Workshop, Rome, Italy, Oct 18-22, 2004". Accepted to Il Nuovo Cimento. For more details, see astro-ph/0408413 (ApJ accepted), and other work from the cosmicbooms.net Team at http://www.cosmicbooms.net

Towards precision distances and 3D dust maps using broadband Period--Magnitude relations of RR Lyrae stars

We determine the period-magnitude relations of RR Lyrae stars in 13 photometric bandpasses from 0.4 to 12 {\mu}m using timeseries observations of 134 stars. The Bayesian formalism, extended from our previous work to include the effects of line-of-sight dust extinction, allows for the simultaneous inference of the posterior distribution of the mean absolute magnitude, slope of the period-magnitude power-law, and intrinsic scatter about a perfect power-law for each bandpass. In addition, the distance modulus and line-of-sight dust extinction to each RR Lyrae star in the calibration sample is determined, yielding a sample median fractional distance error of 0.66%. The intrinsic scatter in all bands appears to be larger than the photometric errors, except in WISE W1 (3.4 {\mu}m) and W2 (4.6 {\mu}m) where the photometric error ($\sigma \approx 0.05$ mag) is to be comparable or larger than the intrinsic scatter. Additional observations at these wavelengths could improve the inferred distances to these sources further. As an application of the methodology, we infer the distance to the RRc-type star RZCep at low Galactic latitude ($b = 5.5^\circ$) to be $\mu=8.0397\pm0.0123$ mag ($405.4\pm2.3$ pc) with colour excess $E(B-V)=0.2461\pm0.0089$ mag. This distance, equivalent to a parallax of $2467\pm14$ microarcsec, is consistent with the published HST parallax measurement but with an uncertainty that is 13 times smaller than the HST measurement. If our measurements (and methodology) hold up to scrutiny, the distances to these stars have been determined to an accuracy comparable to those expected with Gaia. As RR Lyrae are one of the primary components of the cosmic distance ladder, the achievement of sub-1% distance errors within a formalism that accounts for dust extinction may be considered a strong buttressing of the path to eventual 1% uncertainties in Hubble's constant.Comment: 21 pages, 29 figures, 2 tables, abstract abridged for arXiv. Comments solicited on referee report (received June 9, 2014) linked: https://gist.github.com/profjsb/c6c4e2f3a20ea02f1762 . Public archive of code used to generate results and figures: https://github.com/ckleinastro/period_luminosity_relation_fittin

The Genetic Basis of Mutation Rate Variation in Yeast.

Mutations are the root source of genetic variation and underlie the process of evolution. Although the rates at which mutations occur vary considerably between species, little is known about differences within species, or the genetic and molecular basis of these differences. Here, we leveraged the power of the yeast Saccharomyces cerevisiae as a model system to uncover natural genetic variants that underlie variation in mutation rate. We developed a high-throughput fluctuation assay and used it to quantify mutation rates in seven natural yeast isolates and in 1040 segregant progeny from a cross between BY, a laboratory strain, and RM, a wine strain. We observed that mutation rate varies among yeast strains and is heritable (H 2 = 0.49). We performed linkage mapping in the segregants and identified four quantitative trait loci underlying mutation rate variation in the cross. We fine-mapped two quantitative trait loci to the underlying causal genes, RAD5 and MKT1, that contribute to mutation rate variation. These genes also underlie sensitivity to the DNA-damaging agents 4NQO and MMS, suggesting a connection between spontaneous mutation rate and mutagen sensitivity

Toward an Understanding of the Progenitors of Gamma-Ray Bursts

The various possibilities for the progenitors of gamma-ray bursts (GRBs) manifest in differing observable properties. Through deep spectroscopic and high-resolution imaging observations of some GRB hosts, I demonstrate that well-localized long-duration GRBs are connected with otherwise normal star-forming galaxies at moderate redshifts of order unity. I test various progenitor scenarios by examining the offset distribution of GRBs about their apparent hosts, making extensive use of ground-based optical data from Keck and Palomar and space-based imaging from the Hubble Space Telescope. The offset distribution appears to be inconsistent with the coalescing neutron star binary hypothesis but statistically consistent with a population of progenitors that closely traces the ultra-violet light of galaxies. This is naturally explained by bursts which originate from the collapse of massive stars. This claim is further supported by the unambiguous detections of emission ''bumps'' which can be explained as supernovae that occur at approximately the same time as the associated GRB; if true, GRB 980326 and GRB 011121 provide strong observational evidence connecting cosmological GRBs to high-redshift supernovae and implicate massive stars as the progenitors of some long-duration GRBs. Interestingly, most alternative models of these bumps require wind-stratified circumburst media; this too, implicates massive stars. In addition to this work, I also constructed the Jacobs Camera (JCAM), a dual-beam optical camera for the Palomar 200-inch Telescope designed to follow-up rapid GRB localizations (abridged).Comment: Ph.D. thesis, Caltech. 196 pages including low-resolution figures. Abstract to be published in PASP, February 2003. Defended April 1, 2002. A high-resolution PDF version may be found at http://www-cfa.harvard.edu/~jbloom/thesis.htm

The Corrected Log N-Log Fluence Distribution of Cosmological Gamma-Ray Bursts

Recent analysis of relativistically expanding shells of cosmological gamma-ray bursts has shown that if the bursts are cosmological, then most likely total energy (E_0) is standard and not peak luminosity (L_0). Assuming a flat Friedmann cosmology (q_o = 1/2, Lambda = 0) and constant rate density (rho_0) of bursting sources, we fit a standard candle energy to a uniformly selected log N-log S in the BATSE 3B catalog correcting for fluence efficiency and averaging over 48 observed spectral shapes. We find the data consistent with E_0 = 7.3^{+0.7}_{-1.0} X 10^{51} ergs and discuss implications of this energy for cosmological models of gamma-ray bursts.Comment: A five page LateX file that uses the Revtex conference proceedings macro aipbook.sty, and includes three postscript figures using psfig. To Be published in the Proceedings of the Third Hunstville Symposium on Gamma-Ray Bursts, eds. C. Kouveliotou, M.S. Briggs and G.J. Fishman (New York:AIP). Postscript version availible at http://nis-www.lanl.gov/~jsbloom/LOG_S.p

On Neural Architectures for Astronomical Time-series Classification with Application to Variable Stars

Despite the utility of neural networks (NNs) for astronomical time-series classification, the proliferation of learning architectures applied to diverse datasets has thus far hampered a direct intercomparison of different approaches. Here we perform the first comprehensive study of variants of NN-based learning and inference for astronomical time-series, aiming to provide the community with an overview on relative performance and, hopefully, a set of best-in-class choices for practical implementations. In both supervised and self-supervised contexts, we study the effects of different time-series-compatible layer choices, namely the dilated temporal convolutional neural network (dTCNs), Long-Short Term Memory (LSTM) NNs, Gated Recurrent Units (GRUs) and temporal convolutional NNs (tCNNs). We also study the efficacy and performance of encoder-decoder (i.e., autoencoder) networks compared to direct classification networks, different pathways to include auxiliary (non-time-series) metadata, and different approaches to incorporate multi-passband data (i.e., multiple time-series per source). Performance---applied to a sample of 17,604 variable stars from the MACHO survey across 10 imbalanced classes---is measured in training convergence time, classification accuracy, reconstruction error, and generated latent variables. We find that networks with Recurrent NN (RNNs) generally outperform dTCNs and, in many scenarios, yield to similar accuracy as tCNNs. In learning time and memory requirements, convolution-based layers are more performant. We conclude by discussing the advantages and limitations of deep architectures for variable star classification, with a particular eye towards next-generation surveys such as LSST, WFIRST and ZTF2.Comment: Submitted to ApJ