Diffuse Gamma Rays: Galactic and Extragalactic Diffuse Emission

"Diffuse" gamma rays consist of several components: truly diffuse emission from the interstellar medium, the extragalactic background, whose origin is not firmly established yet, and the contribution from unresolved and faint Galactic point sources. One approach to unravel these components is to study the diffuse emission from the interstellar medium, which traces the interactions of high energy particles with interstellar gas and radiation fields. Because of its origin such emission is potentially able to reveal much about the sources and propagation of cosmic rays. The extragalactic background, if reliably determined, can be used in cosmological and blazar studies. Studying the derived "average" spectrum of faint Galactic sources may be able to give a clue to the nature of the emitting objects.Comment: 32 pages, 28 figures, kapproc.cls. Chapter to the book "Cosmic Gamma-Ray Sources," to be published by Kluwer ASSL Series, Edited by K. S. Cheng and G. E. Romero. More details can be found at http://www.gamma.mpe-garching.mpg.de/~aws/aws.htm

Mutual information rate and bounds for it

The amount of information exchanged per unit of time between two nodes in a dynamical network or between two data sets is a powerful concept for analysing complex systems. This quantity, known as the mutual information rate (MIR), is calculated from the mutual information, which is rigorously defined only for random systems. Moreover, the definition of mutual information is based on probabilities of significant events. This work offers a simple alternative way to calculate the MIR in dynamical (deterministic) networks or between two data sets (not fully deterministic), and to calculate its upper and lower bounds without having to calculate probabilities, but rather in terms of well known and well defined quantities in dynamical systems. As possible applications of our bounds, we study the relationship between synchronisation and the exchange of information in a system of two coupled maps and in experimental networks of coupled oscillators

Evaluating psychometric properties of the Emotional Eating Scale Adapted for Children and Adolescents (EES-C) in a clinical sample of children seeking treatment for obesity: a case for the unidimensional model.

BackgroundThe Emotional Eating Scale - Adapted for Children and Adolescents (EES-C) assesses children's urge to eat in response to experiences of negative affect. Prior psychometric studies have demonstrated the high reliability, concurrent validity, and test-retest reliability of theoretically defined subconstructs among non-clinical samples of children and adolescents who were primarily healthy weight; however, no psychometric studies exist investigating the EES-C among clinical samples of children with overweight/obesity (OW/OB). Furthermore, studies conducted in different contexts have suggested a discordant number of subconstructs of emotions related to eating. The purpose of this study was to evaluate the validity of the EES-C in a clinical sample of children seeking weight-loss treatment.MethodUsing a hierarchical bi-factor approach, we evaluated the validity of the EES-C to measure a single general construct, a set of two separate correlated subconstructs, or a hierarchical arrangement of two constructs, and determined reliability in a clinical sample of treatment-seeking children with OW/OB aged 8-12 years (N = 147, mean age = 10.4 years.; mean BMI z = 2.0; female = 66%; Hispanic = 32%, White and other = 68%).ResultsComparison of factor-extraction methods suggested a single primary construct underlying EES-C in this clinical sample. The bi-factor indices provided clear evidence that most of the reliable variance in the total score (90.8 for bi-factor model with three grouping factors and 95.2 for bi-factor model with five grouping factors) was attributed to the general construct. After adjusting for relationships with the primary construct, remaining correlations among sets of items did not suggest additional reliable constructs.ConclusionResults suggest that the primary interpretive emphasis of the EES-C among treatment-seeking children with overweight or obesity should be placed on a single general construct, not on the 3- or 5- subconstructs as was previously suggested

General Analysis of Antideuteron Searches for Dark Matter

Low energy cosmic ray antideuterons provide a unique low background channel for indirect detection of dark matter. We compute the cosmic ray flux of antideuterons from hadronic annihilations of dark matter for various Standard Model final states and determine the mass reach of two future experiments (AMS-02 and GAPS) designed to greatly increase the sensitivity of antideuteron detection over current bounds. We consider generic models of scalar, fermion, and massive vector bosons as thermal dark matter, describe their basic features relevant to direct and indirect detection, and discuss the implications of direct detection bounds on models of dark matter as a thermal relic. We also consider specific dark matter candidates and assess their potential for detection via antideuterons from their hadronic annihilation channels. Since the dark matter mass reach of the GAPS experiment can be well above 100 GeV, we find that antideuterons can be a good indirect detection channel for a variety of thermal relic electroweak scale dark matter candidates, even when the rate for direct detection is highly suppressed.Comment: 44 pages, 15 Figure

Consequences of converting graded to action potentials upon neural information coding and energy efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ~50% in generator potentials, to ~3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation

Weak pairwise correlations imply strongly correlated network states in a neural population

Biological networks have so many possible states that exhaustive sampling is impossible. Successful analysis thus depends on simplifying hypotheses, but experiments on many systems hint that complicated, higher order interactions among large groups of elements play an important role. In the vertebrate retina, we show that weak correlations between pairs of neurons coexist with strongly collective behavior in the responses of ten or more neurons. Surprisingly, we find that this collective behavior is described quantitatively by models that capture the observed pairwise correlations but assume no higher order interactions. These maximum entropy models are equivalent to Ising models, and predict that larger networks are completely dominated by correlation effects. This suggests that the neural code has associative or error-correcting properties, and we provide preliminary evidence for such behavior. As a first test for the generality of these ideas, we show that similar results are obtained from networks of cultured cortical neurons.Comment: Full account of work presented at the conference on Computational and Systems Neuroscience (COSYNE), 17-20 March 2005, in Salt Lake City, Utah (http://cosyne.org

Stimulus-dependent maximum entropy models of neural population codes

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. To be able to infer a model for this distribution from large-scale neural recordings, we introduce a stimulus-dependent maximum entropy (SDME) model---a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. The model is able to capture the single-cell response properties as well as the correlations in neural spiking due to shared stimulus and due to effective neuron-to-neuron connections. Here we show that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. As a result, the SDME model gives a more accurate account of single cell responses and in particular outperforms uncoupled models in reproducing the distributions of codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like surprise and information transmission in a neural population.Comment: 11 pages, 7 figure

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Cosmic rays and molecular clouds

This paper deals with the cosmic-ray penetration into molecular clouds and with the related gamma--ray emission. High energy cosmic rays interact with the dense gas and produce neutral pions which in turn decay into two gamma rays. This makes molecular clouds potential sources of gamma rays, especially if they are located in the vicinity of a powerful accelerator that injects cosmic rays in the interstellar medium. The amplitude and duration in time of the cosmic--ray overdensity around a given source depend on how quickly cosmic rays diffuse in the turbulent galactic magnetic field. For these reasons, gamma-ray observations of molecular clouds can be used both to locate the sources of cosmic rays and to constrain the properties of cosmic-ray diffusion in the Galaxy.Comment: To appear in the proceedings of the San Cugat Forum on Astrophysics 2012, 27 pages, 10 figure

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal