6,039 research outputs found
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 () reactions on
. 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
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
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