The ATLAS ROBIN – A High-Performance Data-Acquisition Module

This work presents the re-configurable processor ROBIN, which is a key element of the data-acquisition-system of the ATLAS experiment, located at the new LHC at CERN. The ATLAS detector provides data over 1600 channels simultaneously towards the DAQ system. The ATLAS dataflow model follows the “PULL” strategy in contrast to the commonly used “PUSH” strategy. The data volume transported is reduced by a factor of 10, however the data must be temporarily stored at the entry to the DAQ system. The input layer consists of approx. 160 ROS read-out units comprising 1 PC and 4 ROBIN modules. Each ROBIN device acquires detector data via 3 input channels and performs local buffering. Board control is done via a 64-bit PCI interface. Event selection and data transmission runs via PCI in the baseline bus-based ROS. Alternatively, a local GE interface can take over part or all of the data traffic in the switch-based ROS, in order to reduce the load on the host PC. The performance of the ROBIN module stems from the close cooperation of a fast embedded processor with a complex FPGA. The efficient task-distribution lets the processor handle all complex management functionality, programmed in “C” while all movement of data is performed by the FPGA via multiple, concurrently operating DMA engines. The ROBIN-project was carried-out by and international team and comprises the design specification, the development of the ROBIN hardware, firmware (VHDL and C-Code), host-code (C++), prototyping, volume production and installation of 700 boards. The project was led by the author of this thesis. The hardware platform is an evolution of a FPGA processor previously designed by the author. He has contributed elementary concepts of the communication mechanisms and the “C”-coded embedded application software. He also organised and supervised the prototype and series productions including the various design reports and presentations. The results show that the ROBIN-module is able to meet its ambitious requirements of 100kHz incoming fragment rate per channel with a concurrent outgoing fragment rate of 21kHz per channel. At the system level, each ROS unit (12 channels) operates at the same rates, however for a subset of the channels only. The ATLAS DAQ system – with 640 ROBIN modules installed – has performed a successful data-taking phase at the start-up of the LHC in September

Elementary excitations of the symmetric spin-orbital model: The XY limit

The elementary excitations of the 1D, symmetric, spin-orbital model are investigated by studying two anisotropic versions of the model, the pure XY and the dimerized XXZ case, with analytical and numerical methods. While they preserve the symmetry between spin and orbital degrees of freedom, these models allow for a simple and transparent picture of the low--lying excitations: In the pure XY case, a phase separation takes place between two phases with free--fermion like, gapless excitations, while in the dimerized case, the low-energy effective Hamiltonian reduces to the 1D Ising model with gapped excitations. In both cases, all the elementary excitations involve simultaneous flips of the spin and orbital degrees of freedom, a clear indication of the breakdown of the traditional mean-field theory.Comment: Revtex, two figure

Orbital-order melting in rare-earth manganites: the role of super-exchange

We study the mechanism of orbital-order melting observed at temperature T_OO in the series of rare-earth manganites. We find that many-body super-exchange yields a transition-temperature T_KK that decreases with decreasing rare-earth radius, and increases with pressure, opposite to the experimental T_OO. We show that the tetragonal crystal-field splitting reduces T_KK further increasing the discrepancies with experiments. This proves that super-exchange effects, although very efficient, in the light of the experimentally observed trends, play a minor role for the melting of orbital ordering in rare-earth manganites.Comment: 4 pages, 5 figure

Results of On-Line Tests of the ENABLE Prototype, a 2nd Level Trigger Processor for the TRT of ATLAS/LHC

The Enable Machine is a systolic 2nd level trigger processor for the transition radiation detector (TRD) of ATLAS/LHC. The task of the processor is to find the best candidate for a lepton track in a high background of pions according to the EAST benchmark [2] in less than 10 5s. As described earlier [1, 2] the Enable Machine finds all reasonable tracks by histogramming the coincidence of the mask templates and the RoI for each track. A prototype has been developed and tested within the EAST/RD-11 collaboration at CERN. It operates at 50 MHz and finds up to 400 arbitrary tracks in less than 10 5s. It is assembled of an interface board and one or more histogrammer boards which makes the Enable Machine easily scalable. The histogrammer units are systolic arrays consisting of a matrix of 36 field- programmable gate arrays (Xilinx XC3190). Through this it is possible to optimize the trigger algorithm, to adapt it to a changed detector setup, and it allows even the implementation of completly new algorithms. For the beam tests in autumn 1993 at CERN the overall functionality within the detector environment could be shown. We were able to link successfully the Enable prototype to the detector raw data stream as well as to the data acquisition system. For the next beam period in 1994 we will focus on efficiency measurements and tests with maximal detector data rate

Enable++ : a second generation FPGA processor

In the computing community field programmable processors are going to fill the niche for special purpose computing devices. A typical example is ultra-fast pattern recognition in experimental particle physics - a task for which we constructed two years ago Enable- 1, an FPGA processor rather specialized for pattern recognition algorithms in μs domain, but also provided with modest features for coping with more general applications. This paper presents the follow-up modell Enable++, a 2nd generation FPGA processor that offers several substantial enhancements over the previous system for a wider range of applications: Enable++ is structured into three different state-of-the-art modules for providing computing power, flexible and high-speed I/O communication and powerful intermodule communication with a raw bandwidth of 3.2 GByte/s by an active backplane. The technical realization of all three modules is guided by the maximum usage of field programmable logic. The actual demand of computing-and I/O-power can be satisified by the number of modules plugged into the crate. Enhanced features of Enable++ comprise the configurable processor topology provided by programmable crossbar switches. In combination with the 4 x 4 FPGA array and 12 MByte distributed RAM the Enable++ computing core offers a strongly increased and scalable computing power. For building new applications the system offers a comfortable programming and debugging environment consisting of a compiler for the C-like hardware description language spC, a simulator and a source level debugger for hardware design. The goal in planning the hardware design environment for Enable++ from scratch is to transfer established methodologies in software design to the design of digital logic. Concerning pattern recognition tasks, we estimate that Enable++ surpasses modern RISC processors by a factor of 100 to 1000

Programmable active memories in real-time tasks: implementing data-driven triggers for LHC experiments

The future Large Hadron Collider (LHC), to be built at CERN, presents among other technological challenges a formidable problem of real-time data analysis. At a primary event rate of 40 MHz, a multi-stage trigger system has to analyze data to decide which is the fraction of events that should be preserved on permanent storage for further analysis. We report on implementations of local algorithms for feature extraction as part of triggering, using the detectors of the proposed ATLAS experiment as a model. The algorithms were implemented for a decision frequency of 100 kHz, on different data-driven programmable devices based on structures of field- programmable gate arrays and memories. The implementations were demonstrated at full speed with emulated input, and were also integrated into a prototype detector running in a test beam at CERN, in June 1994

Neuropeptide S receptor gene - converging evidence for a role in panic disorder

Animal studies have suggested neuropeptide S (NPS) and its receptor (NPSR) to be involved in the pathogenesis of anxiety-related behavior. In this study, a multilevel approach was applied to further elucidate the role of NPS in the etiology of human anxiety. The functional NPSR A/T (Asn¹⁰⁷Ile) variant (rs324981) was investigated for association with (1) panic disorder with and without agoraphobia in two large, independent case-control studies, (2) dimensional anxiety traits, (3) autonomic arousal level during a behavioral avoidance test and (4) brain activation correlates of anxiety-related emotional processing in panic disorder. The more active NPSR rs324981 T allele was found to be associated with panic disorder in the female subgroup of patients in both samples as well as in a meta-analytic approach. The T risk allele was further related to elevated anxiety sensitivity, increased heart rate and higher symptom reports during a behavioral avoidance test as well as decreased activity in the dorsolateral prefrontal, lateral orbitofrontal and anterior cingulate cortex during processing of fearful faces in patients with panic disorder. The present results provide converging evidence for a female-dominant role of NPSR gene variation in panic disorder potentially through heightened autonomic arousal and distorted processing of anxiety-relevant emotional stimuli

Apolipoprotein E Homozygous ε4 Allele Status: A Deteriorating Effect on Visuospatial Working Memory and Global Brain Structure

Theoretical background: The Apolipoprotein E (APOE) ε4 genotype is known to be one of the strongest single-gene predictors for Alzheimer disease, which is characterized by widespread brain structural degeneration progressing along with cognitive impairment. The ε4 allele status has been associated with brain structural alterations and lower cognitive ability in non-demented subjects. However, it remains unclear to what extent the visuospatial cognitive domain is affected, from what age onward changes are detectable and if alterations may interact with cognitive deficits in major depressive disorder (MDD). The current work investigated the effect of APOE ε4 homozygosity on visuospatial working memory (vWM) capacity, and on hippocampal morphometry. Furthermore, potential moderating roles of age and MDD were assessed.Methods: A sample of n = 31 homozygous ε4 carriers was contrasted with n = 31 non-ε4 carriers in a cross-sectional design. The sample consisted of non-demented, young to mid-age participants (mean age = 34.47; SD = 13.48; 51.6% female). Among them were n = 12 homozygous ε4 carriers and n = 12 non-ε4 carriers suffering from MDD (39%). VWM was assessed using the Corsi block-tapping task. Region of interest analyses of hippocampal gray matter density and volume were conducted using voxel-based morphometry (CAT12), and Freesurfer, respectively.Results: Homozygous ε4 carriers showed significantly lower Corsi span capacity than non-ε4 carriers did, and Corsi span capacity was associated with higher gray matter density of the hippocampus. APOE group differences in hippocampal volume could be detected but were no longer present when controlling for total intracranial volume. Hippocampal gray matter density did not differ between APOE groups. We did not find any interaction effects of age and MDD diagnosis on hippocampal morphometry.Conclusion: Our results point toward a negative association of homozygous ε4 allele status with vWM capacity already during mid-adulthood, which emerges independently of MDD diagnosis and age. APOE genotype seems to be associated with global brain structural rather than hippocampus specific alterations in young- to mid-age participants

The Influence of Spatial Registration on Detection of Cerebral Asymmetries Using Voxel-Based Statistics of Fractional Anisotropy Images and TBSS

The sensitivity of diffusion tensor imaging (DTI) for detecting microstructural white matter alterations has motivated the application of voxel-based statistics (VBS) to fractional anisotropy (FA) images (FA-VBS). However, detected group differences may depend on the spatial registration method used. The objective of this study was to investigate the influence of spatial registration on detecting cerebral asymmetries in FA-VBS analyses with reference to data obtained using Tract-Based Spatial Statistics (TBSS). In the first part of this study we performed FA-VBS analyses using three single-contrast and one multi-contrast registration: (i) whole-brain registration based on T2 contrast, (ii) whole-brain registration based on FA contrast, (iii) individual-hemisphere registration based on FA contrast, and (iv) a combination of (i) and (iii). We then compared the FA-VBS results with those obtained from TBSS. We found that the FA-VBS results depended strongly on the employed registration approach, with the best correspondence between FA-VBS and TBSS results when approach (iv), the “multi-contrast individual-hemisphere” method was employed. In the second part of the study, we investigated the spatial distribution of residual misregistration for each registration approach and the effect on FA-VBS results. For the FA-VBS analyses using the three single-contrast registration methods, we identified FA asymmetries that were (a) located in regions prone to misregistrations, (b) not detected by TBSS, and (c) specific to the applied registration approach. These asymmetries were considered candidates for apparent FA asymmetries due to systematic misregistrations associated with the FA-VBS approach. Finally, we demonstrated that the “multi-contrast individual-hemisphere” approach showed the least residual spatial misregistrations and thus might be most appropriate for cerebral FA-VBS analyses

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders