Self-Organisation of Neural Topologies by Evolutionary Reinforcement Learning

In this article we present EANT, "Evolutionary Acquisition of Neural Topologies", a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation operators, starting from a minimal structure. Their parameters are optimised using CMA-ES. EANT can create NNs that are very specialised; they achieve a very good performance while being relatively small. This can be seen in experiments where our method competes with a different one, called NEAT, "NeuroEvolution of Augmenting Topologies", to create networks that control a robot in a visual serving scenario

Correlations between total cell concentration, total adenosine tri-phosphate concentration and heterotrophic plate counts during microbial monitoring of drinking water

The general microbial quality of drinking water is normally monitored by heterotrophic plate counts (HPC). This method has been used for more than 100 years and is recommended in drinking water guidelines. However, the HPC method is handicapped because it is time-consuming and restricted to culturable bacteria. Recently, rapid and accurate detection methods have emerged, such as adenosine tri-phosphate (ATP) measurements to assess microbial activity in drinking water, and flow cytometry (FCM) to determine the total cell concentration (TCC). It is necessary and important for drinking water quality control to understand the relationships among the conventional and new methods. In the current study, all three methods were applied to 200 drinking water samples obtained from two local buildings connected to the same distribution system. Samples were taken both on normal working days and weekends, and the correlations between the different microbiological parameters were determined. TCC in the samples ranged from 0.37–5.61×10<sup>5</sup> cells/ml, and two clusters, the so-called high (HNA) and low (LNA) nucleic acid bacterial groups, were clearly distinguished. The results showed that the rapid determination methods (i.e., FCM and ATP) correlated well (<i>R</i><sup>2</sup>=0.69), but only a weak correlation (<i>R</i><sup>2</sup>=0.31) was observed between the rapid methods and conventional HPC data. With respect to drinking water monitoring, both FCM and ATP measurements were confirmed to be useful and complimentary parameters for rapid assessing of drinking water microbial quality

Axisymmetric core collapse simulations using characteristic numerical relativity

We present results from axisymmetric stellar core collapse simulations in general relativity. Our hydrodynamics code has proved robust and accurate enough to allow for a detailed analysis of the global dynamics of the collapse. Contrary to traditional approaches based on the 3+1 formulation of the gravitational field equations, our framework uses a foliation based on a family of outgoing light cones, emanating from a regular center, and terminating at future null infinity. Such a coordinate system is well adapted to the study of interesting dynamical spacetimes in relativistic astrophysics such as stellar core collapse and neutron star formation. Perhaps most importantly this procedure allows for the unambiguous extraction of gravitational waves at future null infinity without any approximation, along with the commonly used quadrupole formalism for the gravitational wave extraction. Our results concerning the gravitational wave signals show noticeable disagreement when those are extracted by computing the Bondi news at future null infinity on the one hand and by using the quadrupole formula on the other hand. We have strong indication that for our setup the quadrupole formula on the null cone does not lead to physical gravitational wave signals. The Bondi gravitational wave signals extracted at infinity show typical oscillation frequencies of about 0.5 kHz.Comment: 17 pages, 18 figures, submitted to Phys. Rev.

Self-Organisation of Neural Topologies by Evolutionary Reinforcement Learning

In this article we present EANT, "Evolutionary Acquisition of Neural Topologies", a method that creates neural networks (NNs) by evolutionary reinforcement learning. The structure of NNs is developed using mutation operators, starting from a minimal structure. Their parameters are optimised using CMA-ES. EANT can create NNs that are very specialised; they achieve a very good performance while being relatively small. This can be seen in experiments where our method competes with a different one, called NEAT, "NeuroEvolution of Augmenting Topologies", to create networks that control a robot in a visual serving scenario

Small-x Dipole Evolution Beyond the Large-N_c Limit

We present a method to include colour-suppressed effects in the Mueller dipole picture. The model consistently includes saturation effects both in the evolution of dipoles and in the interactions of dipoles with a target in a frame-independent way. When implemented in a Monte Carlo simulation together with our previous model of energy--momentum conservation and a simple dipole description of initial state protons and virtual photons, the model is able to reproduce to a satisfactory degree both the gamma*-p cross sections as measured at HERA as well as the total p-p cross section all the way from ISR energies to the Tevatron and beyond

Combining central pattern generators with the electromagnetism-like algorithm for head motion stabilization during quadruped robot locomotion

Visually-guided locomotion is important for autonomous robotics. However, there are several difficulties, for instance, the head shaking that results from the robot locomotion itself that constraints stable image acquisition and the possibility to rely on that information to act accordingly. In this article, we propose a controller architecture that is able to generate locomotion for a quadruped robot and to generate head motion able to minimize the head motion induced by locomotion itself. The movement controllers are biologically inspired in the concept of Central Pattern Generators (CPGs). CPGs are modelled based on nonlinear dynamical systems, coupled Hopf oscillators. This approach allows to explicitly specify parameters such as amplitude, offset and frequency of movement and to smoothly modulate the generated oscillations according to changes in these parameters. We take advantage of this particularity and propose a combined approach to generate head movement stabilization on a quadruped robot, using CPGs and a global optimization algorithm. The best set of parameters that generates the head movement are computed by the electromagnetism-like algorithm in order to reduce the head shaking caused by locomotion. Experimental results on a simulated AIBO robot demonstrate that the proposed approach generates head movement that does not eliminate but reduces the one induced by locomotion

Gravitational waves from axisymmetrically oscillating neutron stars in general relativistic simulations

Gravitational waves from oscillating neutron stars in axial symmetry are studied performing numerical simulations in full general relativity. Neutron stars are modeled by a polytropic equation of state for simplicity. A gauge-invariant wave extraction method as well as a quadrupole formula are adopted for computation of gravitational waves. It is found that the gauge-invariant variables systematically contain numerical errors generated near the outer boundaries in the present axisymmetric computation. We clarify their origin, and illustrate it possible to eliminate the dominant part of the systematic errors. The best corrected waveforms for oscillating and rotating stars currently contain errors of magnitude $\sim 10^{-3}$ in the local wave zone. Comparing the waveforms obtained by the gauge-invariant technique with those by the quadrupole formula, it is shown that the quadrupole formula yields approximate gravitational waveforms besides a systematic underestimation of the amplitude of $O(M/R)$ where $M$ and $R$ denote the mass and the radius of neutron stars. However, the wave phase and modulation of the amplitude can be computed accurately. This indicates that the quadrupole formula is a useful tool for studying gravitational waves from rotating stellar core collapse to a neutron star in fully general relativistic simulations. Properties of the gravitational waveforms from the oscillating and rigidly rotating neutron stars are also addressed paying attention to the oscillation associated with fundamental modes

ATLAS Tracking Event Data Model

In this report the event data model (EDM) relevant for tracking in the ATLAS experiment is presented. The core component of the tracking EDM is a common track object which is suited to describe tracks in the innermost tracking sub-detectors and in the muon detectors in offline as well as online reconstruction. The design of the EDM was driven by a demand for modularity and extensibility while taking into account the different requirements of the clients. The structure of the track object and the representation of the tracking-relevant information are described in detail