The Massive End of the Stellar Mass Function

We derive average flux corrections to the \texttt{Model} magnitudes of the Sloan Digital Sky Survey (SDSS) galaxies by stacking together mosaics of similar galaxies in bins of stellar mass and concentration. Extra flux is detected in the outer low surface brightness part of the galaxies, leading to corrections ranging from 0.05 to 0.32 mag for the highest stellar mass galaxies. We apply these corrections to the MPA-JHU (Max-Planck Institute for Astrophysics - John Hopkins University) stellar masses for a complete sample of half a million galaxies from the SDSS survey to derive a corrected galaxy stellar mass function at $z=0.1$ in the stellar mass range $9.5<\log(M_\ast/M_\odot)<12.0$. We find that the flux corrections and the use of the MPA-JHU stellar masses have a significant impact on the massive end of the stellar mass function, making the slope significantly shallower than that estimated by Li \& White (2009), but steeper than derived by Bernardi et al. (2013). This corresponds to a mean comoving stellar mass density of galaxies with stellar masses $\log(M_\ast/M_\odot) \ge 11.0$ that is a factor of 3.36 larger than the estimate by Li \& White (2009), but is 43\% smaller than reported by Bernardi et al. (2013).Comment: 11 pages, 8 figures, Accepted to MNRA

Parametrizing the Stellar Haloes of Galaxies

We study the stellar haloes of galaxies out to 70-100 kpc as a function of stellar mass and galaxy type by stacking aligned $r$ and $g$ band images from a sample of 45508 galaxies from SDSS DR9 in the redshift range $0.06\,\le\,z\,\le\,0.1$ and in the mass range $10^{10.0} M_{\odot} < M_{*} < 10^{11.4} M_{\odot}$r. We derive surface brightness profiles to a depth of almost $\mu_r \sim 32 \,\mathrm{mag\,arcsec}^{-2}$. We find that the ellipticity of the stellar halo is a function of galaxy stellar mass and that the haloes of high concentration ($C > 2.6$) galaxies are more elliptical than those of low concentration ($C < 2.6$) galaxies. The $g$-$r$ colour profile of high concentration galaxies reveals that the $g$-$r$ colour of the stellar population in the stellar halo is bluer than in the main galaxy, and the colour of the stellar halo is redder for higher mass galaxies. We further demonstrate that the full two-dimensional surface intensity distribution of our galaxy stacks can only be fit through multi-component S\'{e}rsic models. Using the fraction of light in the outer component of the models as a proxy for the fraction of accreted stellar light, we show that this fraction is a function of stellar mass and galaxy type. For high concentration galaxies, the fraction of accreted stellar light rises from $30\%$ to $70\%$ for galaxies in the stellar mass range from $10^{10.0} M_{\odot}$ to $10^{11.4} M_{\odot}$. The fraction of accreted light is much smaller in low concentration systems, increasing from $2\%$ to $25\%$ over the same mass range. This work provides important constraints for the theoretical understanding of the formation of stellar haloes of galaxies.Comment: Submitted to MNRAS, 18 pages, 19 figure

A Case Study in Matching Service Descriptions to Implementations in an Existing System

A number of companies are trying to migrate large monolithic software systems to Service Oriented Architectures. A common approach to do this is to first identify and describe desired services (i.e., create a model), and then to locate portions of code within the existing system that implement the described services. In this paper we describe a detailed case study we undertook to match a model to an open-source business application. We describe the systematic methodology we used, the results of the exercise, as well as several observations that throw light on the nature of this problem. We also suggest and validate heuristics that are likely to be useful in partially automating the process of matching service descriptions to implementations.Comment: 20 pages, 19 pdf figure

Quantifying dynamical spillover in co-evolving multiplex networks

Multiplex networks (a system of multiple networks that have different types of links but share a common set of nodes) arise naturally in a wide spectrum of fields. Theoretical studies show that in such multiplex networks, correlated edge dynamics between the layers can have a profound effect on dynamical processes. However, how to extract the correlations from real-world systems is an outstanding challenge. Here we provide a null model based on Markov chains to quantify correlations in edge dynamics found in longitudinal data of multiplex networks. We use this approach on two different data sets: the network of trade and alliances between nation states, and the email and co-commit networks between developers of open source software. We establish the existence of "dynamical spillover" showing the correlated formation (or deletion) of edges of different types as the system evolves. The details of the dynamics over time provide insight into potential causal pathways

mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds

Connectomics has emerged as a powerful tool in neuroimaging and has spurred recent advancements in statistical and machine learning methods for connectivity data. Despite connectomes inhabiting a matrix manifold, most analytical frameworks ignore the underlying data geometry. This is largely because simple operations, such as mean estimation, do not have easily computable closed-form solutions. We propose a geometrically aware neural framework for connectomes, i.e., the mSPD-NN, designed to estimate the geodesic mean of a collections of symmetric positive definite (SPD) matrices. The mSPD-NN is comprised of bilinear fully connected layers with tied weights and utilizes a novel loss function to optimize the matrix-normal equation arising from Fr\'echet mean estimation. Via experiments on synthetic data, we demonstrate the efficacy of our mSPD-NN against common alternatives for SPD mean estimation, providing competitive performance in terms of scalability and robustness to noise. We illustrate the real-world flexibility of the mSPD-NN in multiple experiments on rs-fMRI data and demonstrate that it uncovers stable biomarkers associated with subtle network differences among patients with ADHD-ASD comorbidities and healthy controls.Comment: Accepted into IPMI 202

PI-FLAME: A parallel immune system simulator using the FLAME graphic processing unit environment

Agent-based models (ABMs) are increasingly being used to study population dynamics in complex systems, such as the human immune system. Previously, Folcik et al. (The basic immune simulator: an agent-based model to study the interactions between innate and adaptive immunity. Theor Biol Med Model 2007; 4: 39) developed a Basic Immune Simulator (BIS) and implemented it using the Recursive Porous Agent Simulation Toolkit (RePast) ABM simulation framework. However, frameworks such as RePast are designed to execute serially on central processing units and therefore cannot efficiently handle large model sizes. In this paper, we report on our implementation of the BIS using FLAME GPU, a parallel computing ABM simulator designed to execute on graphics processing units. To benchmark our implementation, we simulate the response of the immune system to a viral infection of generic tissue cells. We compared our results with those obtained from the original RePast implementation for statistical accuracy. We observe that our implementation has a 13× performance advantage over the original RePast implementation

Robust Bain distortion in the premartensite phase of platinum substituted Ni2MnGa magnetic shape memory alloy

The premartensite phase of shape memory and magnetic shape memory alloys (MSMAs) is believed to be a precursor state of the martensite phase with preserved austenite phase symmetry. The thermodynamic stability of the premartensite phase and its relation to the martensitic phase is still an unresolved issue, even though it is critical to the understanding of the functional properties of MSMAs. We present here unambiguous evidence for macroscopic symmetry breaking leading to robust Bain distortion in the premartensite phase of 10% Pt substituted Ni2MnGa. We show that the robust Bain distorted premartensite (T2) phase results from another premartensite (T1) phase with preserved cubic-like symmetry through an isostructural phase transition. The T2 phase finally transforms to the martensite phase with additional Bain distortion on further cooling. Our results demonstrate that the premartensite phase should not be considered as a precursor state with the preserved symmetry of the cubic austenite phase