Long Term Wind-Driven X-Ray Spectral Variability of NGC 1365 with Swift

We present long-term (months-years) X-ray spectral variability of the Seyfert 1.8 galaxy NGC 1365 as observed by Swift, which provides well sampled observations over a much longer timescale (6 years) and a much larger flux range than is afforded by other observatories. At very low luminosities the spectrum is very soft, becoming rapidly harder as the luminosity increases and then, above a particular luminosity, softening again. At a given flux level, the scatter in hardness ratio is not very large, meaning that the spectral shape is largely determined by the luminosity. The spectra were therefore summed in luminosity bins and fitted with a variety of models. The best fitting model consists of two power laws, one unabsorbed and another, more luminous, which is absorbed. In this model, we find a range of intrinsic 0.5-10.0 keV luminosities of approximately 1.1-3.5 ergs/s, and a very large range of absorbing columns, of approximately 10^22 - 10^24 cm^-2. Interestingly, we find that the absorbing column decreases with increasing luminosity, but that this result is not due to changes in ionisation. We suggest that these observations might be interpreted in terms of a wind model in which the launch radius varies as a function of ionising flux and disc temperature and therefore moves out with increasing accretion rate, i.e. increasing X-ray luminosity. Thus, depending on the inclination angle of the disc relative to the observer, the absorbing column may decrease as the accretion rate goes up. The weaker, unabsorbed, component may be a scattered component from the wind.Comment: 9 pages, 7 figures, accepted for publication in the Monthly Notices of the Royal Astronomical Societ

Long-Term X-ray Spectral Variability of Seyfert Galaxies with Swift

We present analysis of the long-term X-ray spectral variability of Seyfert galaxies as observed by Swift, which provides well-sampled observations over a much larger flux range and a much longer timescale than any other X-ray observatory. We examine long-term variability of three AGN: NGC 1365 (see Connolly et al. 2014), Mkn 335 and NGC 5548. At high fluxes, the 0.5-10 keV spectra soften with increasing flux, as seen previously within the 2-10 keV band. However, at very low fluxes the sources also become very soft. We have fitted a number of models to the data and find that both intrinsic luminosity variability and variable absorption are required to explain the observations. In some systems, e.g. NGC 1365, the best explanation is a two-component wind model in which one component represents direct emission absorbed by a disc wind wind, with the absorbing column inversely proportional to the intrinsic luminosity, and the second component represents unabsorbed emission reflected from the wind. In other AGN the situation is more complex.Comment: 6 pages, 5 figues, to appear in "Swift: 10 years of discovery", Proceedings of Scienc

Reconstructing Galaxy Spectral Energy Distributions from Broadband Photometry

We present a novel approach to photometric redshifts, one that merges the advantages of both the template fitting and empirical fitting algorithms, without any of their disadvantages. This technique derives a set of templates, describing the spectral energy distributions of galaxies, from a catalog with both multicolor photometry and spectroscopic redshifts. The algorithm is essentially using the shapes of the templates as the fitting parameters. From simulated multicolor data we show that for a small training set of galaxies we can reconstruct robustly the underlying spectral energy distributions even in the presence of substantial errors in the photometric observations. We apply these techniques to the multicolor and spectroscopic observations of the Hubble Deep Field building a set of template spectra that reproduced the observed galaxy colors to better than 10%. Finally we demonstrate that these improved spectral energy distributions lead to a photometric-redshift relation for the Hubble Deep Field that is more accurate than standard template-based approaches.Comment: 23 pages, 8 figures, LaTeX AASTeX, accepted for publication in A

Calculation of High Energy Neutrino-Nucleon Cross Sections and Uncertainties Using the MSTW Parton Distribution Functions and Implications for Future Experiments

We present a new calculation of the cross sections for charged current (CC) and neutral current (NC) $\nu N$ and $\bar{\nu} N$ interactions in the neutrino energy range $10^{4}<E_{\nu}<10^{12}$ GeV using the most recent MSTW parton distribution functions (PDFs), MSTW 2008. We also present the associated uncertainties propagated from the PDFs, as well as parametrizations of the cross section central values, their uncertainty bounds, and the inelasticity distributions for ease of use in Monte Carlo simulations. For the latter we only provide parametrizations for energies above $10^7$ GeV. Finally, we assess the feasibility of future neutrino experiments to constrain the $\nu N$ cross section in the ultra-high energy (UHE) regime using a technique that is independent of the flux spectrum of incident neutrinos. A significant deviation from the predicted Standard Model cross sections could be an indication of new physics, such as extra space-time dimensions, and we present expected constraints on such models as a function of the number of events observed in a future subterranean neutrino detector.Comment: 20 pages, 13 figures, 5 tables, published in Phys.Rev.D. This version fixes a typo in Equation 16 of the publication. Also since version v1, the following changes are in v2 and also in the published version: tables with cs values, parametrization of the y distribution at low-y improved, the discussions on likelihood and also earth absorption are expanded, added a needed minus sign in Eq. 17 of v

The Statistical Approach to Quantifying Galaxy Evolution

Studies of the distribution and evolution of galaxies are of fundamental importance to modern cosmology; these studies, however, are hampered by the complexity of the competing effects of spectral and density evolution. Constructing a spectroscopic sample that is able to unambiguously disentangle these processes is currently excessively prohibitive due to the observational requirements. This paper extends and applies an alternative approach that relies on statistical estimates for both distance (z) and spectral type to a deep multi-band dataset that was obtained for this exact purpose. These statistical estimates are extracted directly from the photometric data by capitalizing on the inherent relationships between flux, redshift, and spectral type. These relationships are encapsulated in the empirical photometric redshift relation which we extend to z ~ 1.2, with an intrinsic dispersion of dz = 0.06. We also develop realistic estimates for the photometric redshift error for individual objects, and introduce the utilization of the galaxy ensemble as a tool for quantifying both a cosmological parameter and its measured error. We present deep, multi-band, optical number counts as a demonstration of the integrity of our sample. Using the photometric redshift and the corresponding redshift error, we can divide our data into different redshift intervals and spectral types. As an example application, we present the number redshift distribution as a function of spectral type.Comment: 40 pages (LaTex), 21 Figures, requires aasms4.sty; Accepted by the Astrophysical Journa

Astronomy in the Cloud: Using MapReduce for Image Coaddition

In the coming decade, astronomical surveys of the sky will generate tens of terabytes of images and detect hundreds of millions of sources every night. The study of these sources will involve computation challenges such as anomaly detection and classification, and moving object tracking. Since such studies benefit from the highest quality data, methods such as image coaddition (stacking) will be a critical preprocessing step prior to scientific investigation. With a requirement that these images be analyzed on a nightly basis to identify moving sources or transient objects, these data streams present many computational challenges. Given the quantity of data involved, the computational load of these problems can only be addressed by distributing the workload over a large number of nodes. However, the high data throughput demanded by these applications may present scalability challenges for certain storage architectures. One scalable data-processing method that has emerged in recent years is MapReduce, and in this paper we focus on its popular open-source implementation called Hadoop. In the Hadoop framework, the data is partitioned among storage attached directly to worker nodes, and the processing workload is scheduled in parallel on the nodes that contain the required input data. A further motivation for using Hadoop is that it allows us to exploit cloud computing resources, e.g., Amazon's EC2. We report on our experience implementing a scalable image-processing pipeline for the SDSS imaging database using Hadoop. This multi-terabyte imaging dataset provides a good testbed for algorithm development since its scope and structure approximate future surveys. First, we describe MapReduce and how we adapted image coaddition to the MapReduce framework. Then we describe a number of optimizations to our basic approach and report experimental results comparing their performance.Comment: 31 pages, 11 figures, 2 table

Quantum Hall Effect and Quantum Point Contact in Bilayer-Patched Epitaxial Graphene

We study an epitaxial graphene monolayer with bilayer inclusions via magnetotransport measurements and scanning gate microscopy at low temperatures. We find that bilayer inclusions can be metallic or insulating depending on the initial and gated carrier density. The metallic bilayers act as equipotential shorts for edge currents, while closely spaced insulating bilayers guide the flow of electrons in the monolayer constriction, which was locally gated using a scanning gate probe.Comment: 5 pages, 5 figure