Spectral function at high missing energies and momenta

The nuclear spectral function at high missing energies and momenta has been determined from a self-consistent calculation of the Green's function in nuclear matter using realistic nucleon-nucleon interactions. The results are compared with recent experimental data derived from ($e,e'p$) reactions on $^{12}C$. A rather good agreement is obtained if the Green's functions are calculated in a non-perturbative way.Comment: 10 pages, 3 figure

Performance of the CMS Pixel Detector at an upgraded LHC

The CMS experiment will include a pixel detector for pattern recognition and vertexing. It will consist of three barrel layers and two endcaps on each side, providing three space-points up to a pseudoraditity of 2.1. Taking into account the expected limitations of its performance in the LHC environment an 8-9 layer pixel detector for an upgraded LHC is discussed.Comment: Contribution to the 10th European Symposium on Semiconductor Detectors, June 12 - 16, 2005 in Wildbad Kreuth, Germany. 6 pages, 4 figures, 1 table. Referee's comments implemente

Covariate-assisted spectral clustering

Biological and social systems consist of myriad interacting units. The interactions can be represented in the form of a graph or network. Measurements of these graphs can reveal the underlying structure of these interactions, which provides insight into the systems that generated the graphs. Moreover, in applications such as connectomics, social networks, and genomics, graph data are accompanied by contextualizing measures on each node. We utilize these node covariates to help uncover latent communities in a graph, using a modification of spectral clustering. Statistical guarantees are provided under a joint mixture model that we call the node-contextualized stochastic blockmodel, including a bound on the mis-clustering rate. The bound is used to derive conditions for achieving perfect clustering. For most simulated cases, covariate-assisted spectral clustering yields results superior to regularized spectral clustering without node covariates and to an adaptation of canonical correlation analysis. We apply our clustering method to large brain graphs derived from diffusion MRI data, using the node locations or neurological region membership as covariates. In both cases, covariate-assisted spectral clustering yields clusters that are easier to interpret neurologically.Comment: 28 pages, 4 figures, includes substantial changes to theoretical result

Causal inference in multisensory perception and the brain

To build coherent and veridical multisensory representations of the environment, human observers consider the causal structure of multisensory signals: If they infer a common source of the signals, observers integrate them weighted by their reliability. Otherwise, they segregate the signals. Generally, observers infer a common source if the signals correspond structurally and spatiotemporally. In six projects, the current PhD thesis investigated this causal inference model with the help of audiovisual spatial signals presented to human observers in a ventriloquist paradigm. A first psychophysical study showed that sensory reliability determines causal inference via two mechanisms: Sensory reliability modulates how observers infer the causal structure from spatial signal disparity. Further, sensory reliability determines the weight of audiovisual signals if observers integrate the signals under assumption of a common source. Using multivariate decoding of fMRI signals, three PhD projects revealed that auditory and visual cortical hierarchies jointly implement causal inference. Specific regions of the hierarchies represented constituent spatial estimates of the causal inference model. In line with this model, anterior regions of intraparietal sulcus (IPS) represent audiovisual signals dependent on visual reliability, task-relevance, and spatial disparity of the signals. However, even in case of small signal discrepancies suggesting a common source, reliability-weighting in IPS was suboptimal as compared to a Maximum Estimation Likelihood model. By temporally manipulating visual reliability, the fifth PhD project demonstrated that human observers learn sensory reliability from current and past signals in order to weight audiovisual signals, consistent with a Bayesian learner. Finally, the sixth project showed that if visual flashes were rendered unaware by continuous flash suppression, the visual bias of the perceived auditory location was strongly reduced but still significant. The reduced ventriloquist effect was presumably mediated by the drop of visual reliability accompanying perceptual unawareness. In conclusion, the PhD thesis suggests that human observers integrate multisensory signals according to their causal structure and temporal regularity: They integrate the signals if a common source is likely by weighting them proportional to the reliability which they learnt from the signals’ history. Crucially, specific regions of cortical hierarchies jointly implement these multisensory processes

Fluence Dependence of Charge Collection of irradiated Pixel Sensors

The barrel region of the CMS pixel detector will be equipped with ``n-in-n'' type silicon sensors. They are processed on DOFZ material, use the moderated p-spray technique and feature a bias grid. The latter leads to a small fraction of the pixel area to be less sensitive to particles. In order to quantify this inefficiency prototype pixel sensors irradiated to particle fluences between $4.7\times 10^{13}$ and 2.6\times 10^{15} \Neq have been bump bonded to un-irradiated readout chips and tested using high energy pions at the H2 beam line of the CERN SPS. The readout chip allows a non zero suppressed analogue readout and is therefore well suited to measure the charge collection properties of the sensors. In this paper we discuss the fluence dependence of the collected signal and the particle detection efficiency. Further the position dependence of the efficiency is investigated.Comment: 11 Pages, Presented at the 5th Int. Conf. on Radiation Effects on Semiconductor Materials Detectors and Devices, October 10-13, 2004 in Florence, Italy, v3: more typos corrected, minor changes required by the refere

Pseudogap at hot spots in the two-dimensional Hubbard model at weak coupling

We analyze the interaction-induced renormalization of single-particle excitations in the two-dimensional Hubbard model at weak coupling using the Wick-ordered version of the functional renormalization group. The self energy is computed for real frequencies by integrating a flow equation with renormalized two-particle interactions. In the vicinity of hot spots, that is points where the Fermi surface intersects the umklapp surface, self energy effects beyond the usual quasi-particle renormalizations and damping occur near instabilities of the normal, metallic phase. Strongly enhanced renormalized interactions between particles at different hot spots generate a pronounced low-energy peak in the imaginary part of the self energy, leading to a pseudogap-like double-peak structure in the spectral function for single-particle excitations.Comment: 14 pages, 7 figure

Test Beam Results of Geometry Optimized Hybrid Pixel Detectors

The Multi-Chip-Module-Deposited (MCM-D) technique has been used to build hybrid pixel detector assemblies. This paper summarises the results of an analysis of data obtained in a test beam campaign at CERN. Here, single chip hybrids made of ATLAS pixel prototype read-out electronics and special sensor tiles were used. They were prepared by the Fraunhofer Institut fuer Zuverlaessigkeit und Mikrointegration, IZM, Berlin, Germany. The sensors feature an optimized sensor geometry called equal sized bricked. This design enhances the spatial resolution for double hits in the long direction of the sensor cells.Comment: Contribution to Proceedings of Pixel2005 Workshop, Bonn Germany 200

Tests of silicon sensors for the CMS pixel detector

The tracking system of the CMS experiment, currently under construction at the Large Hadron Collider (LHC) at CERN (Geneva, Switzerland), will include a silicon pixel detector providing three spacial measurements in its final configuration for tracks produced in high energy pp collisions. In this paper we present the results of test beam measurements performed at CERN on irradiated silicon pixel sensors. Lorentz angle and charge collection efficiency were measured for two sensor designs and at various bias voltages.Comment: Talk presented at 6th International Conference on Large Scale Applications and Radiation Hardness of Semiconductor Detectors, September 29-October 1, 2003, Firenze, Italy. Proceedings will be published in Nuclear Instr. & Methods in Phys. Research, Section

Building CMS Pixel Barrel Detectur Modules

For the barrel part of the CMS pixel tracker about 800 silicon pixel detector modules are required. The modules are bump bonded, assembled and tested at the Paul Scherrer Institute. This article describes the experience acquired during the assembly of the first ~200 modules.Comment: 5 pages, 7 figures, Vertex200

Qualification Procedures of the CMS Pixel Barrel Modules

The CMS pixel barrel system will consist of three layers built of about 800 modules. One module contains 66560 readout channels and the full pixel barrel system about 48 million channels. It is mandatory to test each channel for functionality, noise level, trimming mechanism, and bump bonding quality. Different methods to determine the bump bonding yield with electrical measurements have been developed. Measurements of several operational parameters are also included in the qualification procedure. Among them are pixel noise, gains and pedestals. Test and qualification procedures of the pixel barrel modules are described and some results are presented.Comment: 7 Pages, 7 Figures. Contribution to Pixel 2005, September 5-8, 2005, Bonn, Germna