Input noise approximation in tracker modeling

The validity of approximating random Gaussian distributed inputs used in human response modeling by sums of discrete sine waves is studied. An ideal rectangular power density spectrum is simulated using both filtered Gaussian white noise and sums-of-discrete sine waves with three different input cutoff frequencies in the same compensatory tracking task. Resulting normalized tracking error and quality operator observations are used to investigate apparent discrepancies in human operator characteristics. Results show that discrete and continuous input tracking data compare favorable when the power in the crossover region is taken into account

An Integral Field Study of Abundance Gradients in Nearby LIRGs

We present for the first time metallicity maps generated using data from the Wide Field Spectrograph (WiFeS) on the ANU 2.3m of 9 Luminous Infrared Galaxies (LIRGs) and discuss the abundance gradients and distribution of metals in these systems. We have carried out optical integral field spectroscopy (IFS) of several several LIRGs in various merger phases to investigate the merger process. In a major merger of two spiral galaxies with preexisting disk abundance gradients, the changing distribution of metals can be used as a tracer of gas flows in the merging system as low metallicity gas is transported from the outskirts of each galaxy to their nuclei. We employ this fact to probe merger properties by using the emission lines in our IFS data to calculate the gas-phase metallicity in each system. We create abundance maps and subsequently derive a metallicity gradient from each map. We compare our measured gradients to merger stage as well as several possible tracers of merger progress and observed nuclear abundances. We discuss our work in the context of previous abundance gradient observations and compare our results to new galaxy merger models which trace metallicity gradient. Our results agree with the observed flattening of metallicity gradients as a merger progresses. We compare our results with new theoretical predictions that include chemical enrichment. Our data show remarkable agreement with these simulations.Comment: Accepted for publication in ApJ. 26 pages, 18 figure

The Dynamics of Galaxy Pairs in a Cosmological Setting

We use the Millennium Simulation, and an abundance-matching framework, to investigate the dynamical behaviour of galaxy pairs embedded in a cosmological context. Our main galaxy-pair sample, selected to have separations under 250 kpc/h, consists of over 1.3 million pairs at redshift z = 0, with stellar masses greater than 10^9 Msun, probing mass ratios down to 1:1000. We use dark matter halo membership and energy to classify our galaxy pairs. In terms of halo membership, central-satellite pairs tend to be in isolation (in relation to external more massive galaxies), are energetically- bound to each other, and are also weakly-bound to a neighbouring massive galaxy. Satellite-satellite pairs, instead, inhabit regions in close proximity to a more massive galaxy, are energetically-unbound, and are often bound to that neighbour. We find that 60% of our paired galaxies are bound to both their companion and to a third external object. Moreover, only 9% of our pairs resemble the kind of systems described by idealised binary merger simulations in complete isolation. In sum, we demonstrate the importance of properly connecting galaxy pairs to the rest of the Universe.Comment: 25 pages, 14 figures, accepted by MNRA

NASA advanced design program: Analysis, design, and construction of a solar powered aircraft

Increase in energy demands coupled with rapid depletion of natural energy resources have deemed solar energy as the most logical alternative source of power. The major objective of this project was to build a solar powered remotely controlled aircraft to demonstrate the feasibility of solar energy as an effective, alternate source of power. The final design was optimized for minimum weight and maximum strength of the structure. These design constraints necessitated a carbon fiber composite structure. Surya is a lightweight, durable aircraft capable of achieving level flight powered entirely by solar cells

A Deep Learning Approach to Galaxy Cluster X-ray Masses

We present a machine-learning approach for estimating galaxy cluster masses from Chandra mock images. We utilize a Convolutional Neural Network (CNN), a deep machine learning tool commonly used in image recognition tasks. The CNN is trained and tested on our sample of 7,896 Chandra X-ray mock observations, which are based on 329 massive clusters from the IllustrisTNG simulation. Our CNN learns from a low resolution spatial distribution of photon counts and does not use spectral information. Despite our simplifying assumption to neglect spectral information, the resulting mass values estimated by the CNN exhibit small bias in comparison to the true masses of the simulated clusters (-0.02 dex) and reproduce the cluster masses with low intrinsic scatter, 8% in our best fold and 12% averaging over all. In contrast, a more standard core-excised luminosity method achieves 15-18% scatter. We interpret the results with an approach inspired by Google DeepDream and find that the CNN ignores the central regions of clusters, which are known to have high scatter with mass.Comment: 10 pages, 6 figures, accepted for publication in The Astrophysical Journa

First results from the IllustrisTNG simulations: A tale of two elements -- chemical evolution of magnesium and europium

The distribution of elements in galaxies provides a wealth of information about their production sites and their subsequent mixing into the interstellar medium. Here we investigate the distribution of elements within stars in the IllustrisTNG simulations. In particular, we analyze the abundance ratios of magnesium and europium in Milky Way-like galaxies from the TNG100 simulation (stellar masses ${\log} (M_\star / {\rm M}_\odot) \sim 9.7 - 11.2$). As abundances of magnesium and europium for individual stars in the Milky Way are observed across a variety of spatial locations and metallicities, comparison with the stellar abundances in our more than $850$ Milky Way-like galaxies provides stringent constraints on our chemical evolutionary methods. To this end we use the magnesium to iron ratio as a proxy for the effects of our SNII and SNIa metal return prescription, and a means to compare our simulated abundances to a wide variety of galactic observations. The europium to iron ratio tracks the rare ejecta from neutron star -- neutron star mergers, the assumed primary site of europium production in our models, which in turn is a sensitive probe of the effects of metal diffusion within the gas in our simulations. We find that europium abundances in Milky Way-like galaxies show no correlation with assembly history, present day galactic properties, and average galactic stellar population age. In general, we reproduce the europium to iron spread at low metallicities observed in the Milky Way, with the level of enhancement being sensitive to gas properties during redshifts $z \approx 2-4$. We show that while the overall normalization of [Eu/Fe] is susceptible to resolution and post-processing assumptions, the relatively large spread of [Eu/Fe] at low [Fe/H] when compared to that at high [Fe/H] is very robust.Comment: 18 pages, 14 figures, accepted to MNRA

Ex. 279-US-403

A 2006 annual report on the spawning migration movements of Klamath largescale, Lost River, and shortnose suckers in the Williamson and Sprague rivers, Oregon, prior to the removal of Chiloquin Da

Ex. 277-US-415

The 2004 annual report on riverine movements of adult Lost River, shortnose, and Klamath largescale suckers in the Williamson and Sprague rivers, Orego

Ex. 279-US-403

A 2006 annual report on the spawning migration movements of Klamath largescale, Lost River, and shortnose suckers in the Williamson and Sprague rivers, Oregon, prior to the removal of Chiloquin Da