Next-to-Leading Order QCD Corrections to the Polarized Photoproduction of Heavy Flavors

We present a calculation of the next-to-leading order (O(alpha_s^2 alpha)) QCD corrections to heavy flavor photoproduction with longitudinally polarized beams. We apply our results to study the longitudinal spin asymmetry for the total charm quark production cross section which will be utilized by the forthcoming COMPASS experiment at CERN to obtain first direct information on the polarized gluon density Delta g. We also briefly discuss the main theoretical uncertainties inherent in this calculation. In particular we demonstrate that the factorization scale dependence is considerably reduced in next-to-leading order.Comment: 18 pages, LaTeX, 4 figures, uses epsfig and amssymb style

NLO QCD Corrections to the Polarized Photo- and Hadroproduction of Heavy Quarks

The complete details of our calculation of the NLO QCD corrections to heavy flavor photo- and hadroproduction with longitudinally polarized initial states are presented. The main motivation for investigating these processes is the determination of the polarized gluon density at the COMPASS and RHIC experiments, respectively, in the near future. All methods used in the computation are extensively documented, providing a self-contained introduction to this type of calculations. Some employed tools also may be of general interest, e.g., the series expansion of hypergeometric functions. The relevant parton level results are collected and plotted in the form of scaling functions. However, the simplification of the obtained gluon-gluon virtual contributions has not been completed yet. Thus NLO phenomenological predictions are only given in the case of photoproduction. The theoretical uncertainties of these predictions, in particular with respect to the heavy quark mass, are carefully considered. Also it is shown that transverse momentum cuts can considerably enhance the measured production asymmetries. Finally unpolarized heavy quark production is reviewed in order to derive conditions for a successful interpretation of future spin-dependent experimental data.Comment: PhD thesis, LaTeX, 189 pages, 57 figures, for double-sided printing, other formats (one-sided, 2-on-1) at http://doom.physik.uni-dortmund.de/~boja

Metabifurcation analysis of a mean field model of the cortex

Mean field models (MFMs) of cortical tissue incorporate salient features of neural masses to model activity at the population level. One of the common aspects of MFM descriptions is the presence of a high dimensional parameter space capturing neurobiological attributes relevant to brain dynamics. We study the physiological parameter space of a MFM of electrocortical activity and discover robust correlations between physiological attributes of the model cortex and its dynamical features. These correlations are revealed by the study of bifurcation plots, which show that the model responses to changes in inhibition belong to two families. After investigating and characterizing these, we discuss their essential differences in terms of four important aspects: power responses with respect to the modeled action of anesthetics, reaction to exogenous stimuli, distribution of model parameters and oscillatory repertoires when inhibition is enhanced. Furthermore, while the complexity of sustained periodic orbits differs significantly between families, we are able to show how metamorphoses between the families can be brought about by exogenous stimuli. We unveil links between measurable physiological attributes of the brain and dynamical patterns that are not accessible by linear methods. They emerge when the parameter space is partitioned according to bifurcation responses. This partitioning cannot be achieved by the investigation of only a small number of parameter sets, but is the result of an automated bifurcation analysis of a representative sample of 73,454 physiologically admissible sets. Our approach generalizes straightforwardly and is well suited to probing the dynamics of other models with large and complex parameter spaces

Small x resummations confronted with F_2(x,Q^2) data

It has been observed recently that a consistent LO BFKL gluon evolution leads to a steep growth of F_2(x,Q^2) for x -> 0 almost independently of Q^2. We show that current data from the DESY HERA collider are precise enough to finally rule out a pure BFKL behaviour in the accessible small x region. Several attempts have been made by other groups to treat the BFKL type small x resummations instead as additions to the conventional anomalous dimensions of the successful renormalization group ``Altarelli-Parisi'' equations. We demonstrate that all presently available F_2 data, in particular at lower values of Q^2, can not be described using the presently known NLO (two-loop consistent) small x resummations. Finally we comment on the common reason for the failure of these BFKL inspired methods which result, in general, in too steep x-dependencies as x -> 0.Comment: Revised, to be published in Phys. Lett. B., 18 pages, LaTeX2e, 3 figures, uses amssymb and epsfig style

A brain-wave equation incorporating axo-dendritic connectivity

We introduce an integral model of a two-dimensional neural field that includes a third dimension representing space along a dendritic tree that can incorporate realistic patterns of axo-dendritic connectivity. For natural choices of this connectivity we show how to construct an equivalent brainwave partial differential equation that allows for effcient numerical simulation of the model. This is used to highlight the effects that passive dendritic properties can have on the speed and shape of large scale traveling cortical waves

Emergence of spatially heterogeneous burst suppression in a neural field model of electrocortical activity

Burst suppression in the electroencephalogram (EEG) is a well-described phenomenon that occurs during deep anesthesia, as well as in a variety of congenital and acquired brain insults. Classically it is thought of as spatially synchronous, quasi-periodic bursts of high amplitude EEG separated by low amplitude activity. However, its characterization as a “global brain state” has been challenged by recent results obtained with intracranial electrocortigraphy. Not only does it appear that burst suppression activity is highly asynchronous across cortex, but also that it may occur in isolated regions of circumscribed spatial extent. Here we outline a realistic neural field model for burst suppression by adding a slow process of synaptic resource depletion and recovery, which is able to reproduce qualitatively the empirically observed features during general anesthesia at the whole cortex level. Simulations reveal heterogeneous bursting over the model cortex and complex spatiotemporal dynamics during simulated anesthetic action, and provide forward predictions of neuroimaging signals for subsequent empirical comparisons and more detailed characterization. Because burst suppression corresponds to a dynamical end-point of brain activity, theoretically accounting for its spatiotemporal emergence will vitally contribute to efforts aimed at clarifying whether a common physiological trajectory is induced by the actions of general anesthetic agents. We have taken a first step in this direction by showing that a neural field model can qualitatively match recent experimental data that indicate spatial differentiation of burst suppression activity across cortex