B. Connolly

Photometric Type Ia Supernova Candidates from the Three-year SDSS-II SN Survey Data

We analyze the three-year Sloan Digital Sky Survey II (SDSS-II) Supernova (SN) Survey data and identify a sample of 1070 photometric Type Ia supernova (SN Ia) candidates based on their multiband light curve data. This sample consists of SN candidates with no spectroscopic confirmation, with a subset of 210 candidates having spectroscopic redshifts of their host galaxies measured while the remaining 860 candidates are purely photometric in their identification. We describe a method for estimating the efficiency and purity of photometric SN Ia classification when spectroscopic confirmation of only a limited sample is available, and demonstrate that SN Ia candidates from SDSS-II can be identified photometrically with ~91% efficiency and with a contamination of ~6%. Although this is the largest uniform sample of SN candidates to date for studying photometric identification, we find that a larger spectroscopic sample of contaminating sources is required to obtain a better characterization of the background events. A Hubble diagram using SN candidates with no spectroscopic confirmation, but with host galaxy spectroscopic redshifts, yields a distance modulus dispersion that is only ~20%-40% larger than that of the spectroscopically confirmed SN Ia sample alone with no significant bias. A Hubble diagram with purely photometric classification and redshift-distance measurements, however, exhibits biases that require further investigation for precision cosmology.

AN EVOLUTIONARY PARADIGM FOR DUSTY ACTIVE GALAXIES AT LOW REDSHIFT

We apply methods from Bayesian inferencing and graph theory to a data set of 102 mid-infrared spectra, and archival data from the optical to the millimeter, to construct an evolutionary paradigm for z < 0.4 infrared-luminous galaxies. We propose that the ultraluminous infrared galaxies (ULIRG) lifecycle consists of three phases. The first phase lasts from the initial encounter until approximately coalescence. It is characterized by homogeneous mid-IR spectral shapes, and IR emission mainly from star formation, with a contribution from an active galactic nucleus (AGN) in some cases. At the end of this phase, a ULIRG enters one of two evolutionary paths depending on the dynamics of the merger, the available quantities of gas, and the masses of the black holes in the progenitors. On one branch, the contributions from the starburst and the AGN to the total IR luminosity decline and increase, respectively. The IR spectral shapes are heterogeneous, likely due to feedback from AGN-driven winds. Some objects go through a brief QSO phase at the end. On the other branch, the decline of the starburst relative to the AGN is less pronounced, and few or no objects go through a QSO phase. We show that the 11.2 μm polycyclic aromatic hydrocarbon feature is a remarkably good diagnostic of evolutionary phase, and identify six ULIRGs that may be archetypes of key stages in this lifecycle.

THE EXTRAORDINARY MID-INFRARED SPECTRAL PROPERTIES OF FeLoBAL QUASARS

We present mid-infrared (mid-IR) spectra of six FeLoBAL quasi-stellar objects (QSOs) at 1 < z < 1.8, taken with the Spitzer Space Telescope. The spectra span a range of shapes, from hot dust-dominated active galactic nuclei (AGNs) with silicate emission at 9.7 μm to moderately obscured starbursts with strong polycyclic aromatic hydrocarbon (PAH) emission. The spectrum of one object, SDSS 1214–0001, shows the most prominent PAHs yet seen in any QSO at any redshift, implying that the starburst dominates the mid-IR emission with an associated star formation rate on the order of 2700 M_⊙ yr^(–1). With the caveats that our sample is small and not robustly selected, we combine our mid-IR spectral diagnostics with previous observations to propose that FeLoBAL QSOs are at least largely comprised of systems in which (1) a merger-driven starburst is ending, (2) a luminous AGN is in the last stages of burning through its surrounding dust, and (3) we may be viewing over a restricted line-of-sight range.

Principal component analysis of the Spitzer IRS spectra of ultraluminous infrared galaxies

We present the first principal component analysis (PCA) applied to a sample of 119 Spitzer Infrared Spectrograph (IRS) spectra of local ultraluminous infrared galaxies (ULIRGs) at z < 0:35. The purpose of this study is to objectively and uniquely characterise the local ULIRG population using all information contained in the observed spectra. We have derived the first three principal components (PCs) from the covariance matrix of our dataset which account for over 90% of the variance. The first PC is characterised by dust temperatures and the geometry of the mix of source and dust. The second PC is a pure star formation component. The third PC represents an anticorrelation between star formation activity and a rising AGN. Using the first three PCs, we are able to accurately reconstruct most of the spectra in our sample. Our work shows that there are several factors that are important in characterising the ULIRG population, dust temperature, geometry, star formation intensity, AGN contribution, etc. We also make comparison between PCA and other diagnostics such as ratio of the 6.2 �m PAH emission feature to the 9.7 �m silicate absorption depth and other observables such as optical spectral type. An electronic version of the first three PCs of the local ULIRG population is available at http://astronomy.sussex.ac.uk/�lw94/PCA/.

Sequential Analysis Techniques for Correlation Studies in Particle Astronomy

Searches for statistically significant correlations between arrival directions of ultra-high-energy cosmic rays and classes of astrophysical objects are common in astroparticle physics. We present a method to test potential correlation signals of a priori unknown strength and evaluate their statistical significance sequentially, i.e., after each incoming new event in a running experiment. The method can be applied to data taken after the test has concluded, allowing for further monitoring of the signal significance. It adheres to the likelihood principle and rigorously accounts for our ignorance of the signal strength.

A Bayesian Approach to Comparing Cosmic Ray Energy Spectra

A common problem in ultra-high energy cosmic ray physics is the comparison of energy spectra. The question is whether the spectra from two experiments or two regions of the sky agree within their statistical and systematic uncertainties. We develop a method to directly compare energy spectra for ultra-high energy cosmic rays from two different regions of the sky in the same experiment without reliance on agreement with a theoretical model of the energy spectra. The consistency between the two spectra is expressed in terms of a Bayes factor, defined here as the ratio of the likelihood of the two-parent source hypothesis to the likelihood of the one-parent source hypothesis. Unlike other methods, for example χ2 tests, the Bayes factor allows for the calculation of the posterior odds ratio and correctly accounts for non-Gaussian uncertainties. The latter is particularly important at the highest energies, where the number of events is very small.