First experiences with the ATLAS Pixel Detector Control System at the Combined Test Beam 2004

Detector control systems (DCS) include the read out, control and supervision of hardware devices as well as the monitoring of external systems like cooling system and the processing of control data. The implementation of such a system in the final experiment has also to provide the communication with the trigger and data acquisition system (TDAQ). In addition, conditions data which describe the status of the pixel detector modules and their environment must be logged and stored in a common LHC wide database system. At the combined test beam all ATLAS subdetectors were operated together for the first time over a longer period. To ensure the functionality of the pixel detector a control system was set up. We describe the architecture chosen for the pixel detector control system, the interfaces to hardware devices, the interfaces to the users and the performance of our system. The embedding of the DCS in the common infrastructure of the combined test beam and also its communication with surrounding systems will be discussed in some detail.Comment: 6 pages, 9 figures, Pixel 2005 proceedings preprin

Local Support Assembly of the ATLAS Pixel Detector

The barrel part of the ATLAS pixel detector will consist of 112 carbon-carbon structures called "staves" with 13 hybrid detector modules being glued on each stave. The demands on the glue joints are high, both in terms of mechanical precision and thermal contact. To achieve this precision a custom-made semi-automated mounting machine has been constructed in Wuppertal, which provides a precision in the order of tens of microns. As this is the last stage of the detector assembly providing an opportunity for stringent tests, a detailed procedure has been defined for assessing both mechanical and electrical properties. This note gives an overview of the procedure for affixation and tests, and summarizes the first results of the production.Comment: 6 pages, 8 figure

Optical Readout in a Multi-Module System Test for the ATLAS Pixel Detector

The innermost part of the ATLAS experiment at the LHC, CERN, will be a pixel detector. The command messages and the readout data of the detector are transmitted over an optical data path. The readout chain consists of many components which are produced at several locations around the world, and must work together in the pixel detector. To verify that these parts are working together as expected a system test has been built up. In this paper the system test setup and the operation of the readout chain is described. Also, some results of tests using the final pixel detector readout chain are given.Comment: 6 pages, 10 figures, Pixel 2005 proceedings preprin

Validation Studies of the ATLAS Pixel Detector Control System

The ATLAS pixel detector consists of 1744 identical silicon pixel modules arranged in three barrel layers providing coverage for the central region, and three disk layers on either side of the primary interaction point providing coverage of the forward regions. Once deployed into the experiment, the detector will employ optical data transfer, with the requisite powering being provided by a complex system of commercial and custom-made power supplies. However, during normal performance and production tests in the laboratory, only single modules are operated and electrical readout is used. In addition, standard laboratory power supplies are used. In contrast to these normal tests, the data discussed here was obtained from a multi-module assembly which was powered and read out using production items: the optical data path, the final design power supply system using close to final services, and the Detector Control System (DCS). To demonstrate the functionality of the pixel detector system a stepwise transition was made from the normal laboratory readout and power supply systems to the ones foreseen for the experiment, with validation of the data obtained at each transition.Comment: 8 pages, 8 figures, proceedings for the Pixel2005 worksho

Genetics of Dispersal

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal-related phenotypes or evidence for the micro-evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment-dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non-additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non-equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context-dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.Peer reviewe