Detecting the Baryons in Matter Power Spectra

We examine power spectra from the Abell/ACO rich cluster survey and the 2dF Galaxy Redshift Survey (2dfGRS) for observational evidence of features produced by the baryons. A non-negligible baryon fraction produces relatively sharp oscillatory features at specific wavenumbers in the matter power spectrum. However, the mere existence of baryons will also produce a global suppression of the power spectrum. We look for both of these features using the false discovery rate (FDR) statistic. We show that the window effects on the Abell/ACO power spectrum are minimal, which has allowed for the discovery of discrete oscillatory features in the power spectrum. On the other hand, there are no statistically significant oscillatory features in the 2dFGRS power spectrum, which is expected from the survey's broad window function. After accounting for window effects, we apply a scale-independent bias to the 2dFGRS power spectrum, P_{Abell}(k) = b^2P_{2dF}(k) and b = 3.2. We find that the overall shapes of the Abell/ACO and the biased 2dFGRS power spectra are entirely consistent over the range 0.02 <= k <= 0.15hMpc^-1. We examine the range of Omega_{matter} and baryon fraction for which these surveys could detect significant suppression in power. The reported baryon fractions for both the Abell/ACO and 2dFGRS surveys are high enough to cause a detectable suppression in power (after accounting for errors, windows and k-space sampling). Using the same technique, we also examine, given the best fit baryon density obtained from BBN, whether it is possible to detect additional suppression due to dark matter-baryon interaction. We find that the limit on dark matter cross section/mass derived from these surveys are the same as those ruled out in a recent study by Chen, Hannestad and Scherrer.Comment: 11 pages of text, 6 figures. Submitted to Ap

Using AI libraries for Incompressible Computational Fluid Dynamics

Recently, there has been a huge effort focused on developing highly efficient open source libraries to perform Artificial Intelligence (AI) related computations on different computer architectures (for example, CPUs, GPUs and new AI processors). This has not only made the algorithms based on these libraries highly efficient and portable between different architectures, but also has substantially simplified the entry barrier to develop methods using AI. Here, we present a novel methodology to bring the power of both AI software and hardware into the field of numerical modelling by repurposing AI methods, such as Convolutional Neural Networks (CNNs), for the standard operations required in the field of the numerical solution of Partial Differential Equations (PDEs). The aim of this work is to bring the high performance, architecture agnosticism and ease of use into the field of the numerical solution of PDEs. We use the proposed methodology to solve the advection-diffusion equation, the non-linear Burgers equation and incompressible flow past a bluff body. For the latter, a convolutional neural network is used as a multigrid solver in order to enforce the incompressibility constraint. We show that the presented methodology can solve all these problems using repurposed AI libraries in an efficient way, and presents a new avenue to explore in the development of methods to solve PDEs and Computational Fluid Dynamics problems with implicit methods.Comment: 24 pages, 6 figure

A Tale of Two Narrow-Line Regions: Ionization, Kinematics, and Spectral Energy Distributions for a Local Pair of Merging Obscured Active Galaxies

We explore the gas ionization and kinematics, as well as the optical--IR spectral energy distributions for UGC 11185, a nearby pair of merging galaxies hosting obscured active galactic nuclei (AGNs), also known as SDSS J181611.72+423941.6 and J181609.37+423923.0 (J1816NE and J1816SW, $z \approx 0.04$). Due to the wide separation between these interacting galaxies ($\sim 23$ kpc), observations of these objects provide a rare glimpse of the concurrent growth of supermassive black holes at an early merger stage. We use BPT line diagnostics to show that the full extent of the narrow line emission in both galaxies is photoionized by an AGN and confirm the existence of a 10-kpc-scale ionization cone in J1816NE, while in J1816SW the AGN narrow-line region is much more compact (1--2 kpc) and relatively undisturbed. Our observations also reveal the presence of ionized gas that nearly spans the entire distance between the galaxies which is likely in a merger-induced tidal stream. In addition, we carry out a spectral analysis of the X-ray emission using data from {\em XMM-Newton}. These galaxies represent a useful pair to explore how the [\ion{O}{3}] luminosity of an AGN is dependent on the size of the region used to explore the extended emission. Given the growing evidence for AGN "flickering" over short timescales, we speculate that the appearances and impact of these AGNs may change multiple times over the course of the galaxy merger, which is especially important given that these objects are likely the progenitors of the types of systems commonly classified as "dual AGNs."Comment: 15 pages, 10 figures, accepted by the Astrophysical Journa

A Consistent Picture Emerges: A Compact X-ray Continuum Emission Region in the Gravitationally Lensed Quasar SDSS J0924+0219

We analyze the optical, UV, and X-ray microlensing variability of the lensed quasar SDSS J0924+0219 using six epochs of Chandra data in two energy bands (spanning 0.4-8.0 keV, or 1-20 keV in the quasar rest frame), 10 epochs of F275W (rest-frame 1089A) Hubble Space Telescope data, and high-cadence R-band (rest-frame 2770A) monitoring spanning eleven years. Our joint analysis provides robust constraints on the extent of the X-ray continuum emission region and the projected area of the accretion disk. The best-fit half-light radius of the soft X-ray continuum emission region is between 5x10^13 and 10^15 cm, and we find an upper limit of 10^15 cm for the hard X-rays. The best-fit soft-band size is about 13 times smaller than the optical size, and roughly 7 GM_BH/c^2 for a 2.8x10^8 M_sol black hole, similar to the results for other systems. We find that the UV emitting region falls in between the optical and X-ray emitting regions at 10^14 cm < r_1/2,UV < 3x10^15 cm. Finally, the optical size is significantly larger, by 1.5*sigma, than the theoretical thin-disk estimate based on the observed, magnification-corrected I-band flux, suggesting a shallower temperature profile than expected for a standard disk.Comment: Replaced with accepted version to Ap

Toward Precision Education: Educational Data Mining and Learning Analytics for Identifying Students’ Learning Patterns with Ebook Systems

Precision education is now recognized as a new challenge of applying artificial intelligence, machine learning, and learning analytics to improve both learning performance and teaching quality. To promote precision education, digital learning platforms have been widely used to collect educational records of students’ behavior, performance, and other types of interaction. On the other hand, the increasing volume of students’ learning behavioral data in virtual learning environments provides opportunities for mining data on these students’ learning patterns. Accordingly, identifying students’ online learning patterns on various digital learning platforms has drawn the interest of the learning analytics and educational data mining research communities. In this study, the authors applied data analytics methods to examine the learning patterns of students using an ebook system for one semester in an undergraduate course. The authors used a clustering approach to identify subgroups of students with different learning patterns. Several subgroups were identified, and the students’ learning patterns in each subgroup were determined accordingly. In addition, the association between these students’ learning patterns and their learning outcomes from the course was investigated. The findings of this study provide educators opportunities to predict students’ learning outcomes by analyzing their online learning behaviors and providing timely intervention for improving their learning experience, which achieves one of the goals of learning analytics as part of precision education

A smart itsy bitsy spider for the Web

Artificial Intelligence Lab, Department of MIS, University of ArizonaAs part of the ongoing Illinois Digital Library Initiative project, this research proposes an intelligent agent approach to Web searching. In this experiment, we developed two Web personal spiders based on best first search and genetic algorithm techniques, respectively. These personal spiders can dynamically take a userâ s selected starting homepages and search for the most closely related homepages in the Web, based on the links and keyword indexing. A graphical, dynamic, Java-based interface was developed and is available for Web access. A system architecture for implementing such an agent-based spider is presented, followed by detailed discussions of benchmark testing and user evaluation results. In benchmark testing, although the genetic algorithm spider did not outperform the best first search spider, we found both results to be comparable and complementary. In user evaluation, the genetic algorithm spider obtained significantly higher recall value than that of the best first search spider. However, their precision values were not statistically different. The mutation process introduced in genetic algorithm allows users to find other potential relevant homepages that cannot be explored via a conventional local search process. In addition, we found the Java-based interface to be a necessary component for design of a truly interactive and dynamic Web agent

In Situ Transmission X-Ray Microscopy of the Lead Sulfate Film Formation on Lead in Sulfuric Acid

Transmission X-ray microscopy is utilized to monitor, in real time, the behavior of the PbSO4 film that is formed on Pb in H2SO4. Images collected from the synchrotron x-rays are coupled with voltammetric data to study the initial formation, the resulting passivation, and the subsequent reduction of the film. It is concluded with support from quartz-crystal-microbalance experiments that the initial formation of PbSO4 crystals occurs as a result of acidic corrosion. In addition, the film is shown to coalesce during the early stages of galvanostatic oxidation and to passivate as a result of morphological changes in the existing film. Finally, it is observed that the passivation process results in the formation of large PbSO4 crystals with low area-to-volume ratios, which are difficult to reduce under both galvanostatic and potentiostatic conditions