3,776 research outputs found
Enhancing the Accuracy of Microwave Element Models by Artificial Neural Networks
In the recent PSpice programs, five types of the GaAs FET model have been implemented. However, some of them are too sophisticated and therefore very difficult to measure and identify afterwards, especially the realistic model of Parker and Skellern. In the paper, simple enhancements of one of the classical models are proposed first. The resulting modification is usable for the accurate modeling of both GaAs FETs and pHEMTs. Moreover, its updated capacitance function can serve as an accurate representation of microwave varactors, which is also important. The precision of the updated models can be strongly enhanced using the artificial neural networks. In the paper, both using an exclusive neural network without an analytic model and cooperating a corrective neural network with the updated analytic model will be discussed. The accuracy of the analytic models, the models based on the exclusive neural network, and the models created as a combination of the updated analytic model and the corrective neural network will be compared
On a scalable nonparametric denoising of time series signals
Denoising and filtering of time series signals is a problem emerging in many areas of computational science. Here we demonstrate how the nonparametric computational methodology of the finite element method of time series analysis with H1 regularization can be extended for denoising of very long and noisy time series signals. The main computational bottleneck is the inner quadratic programming problem. Analyzing the solvability and utilizing the problem structure, we suggest an adapted version of the spectral projected gradient method (SPG-QP) to resolve the problem. This approach increases the granularity of parallelization, making the proposed methodology highly suitable for graphics processing unit (GPU) computing. We demonstrate the scalability of our open-source implementation based on PETSc for the Piz Daint supercomputer of the Swiss Supercomputing Centre (CSCS) by solving large-scale data denoising problems and comparing their computational scaling and performance to the performance of the standard denoising methods
Electrochemical Carbonylation of Organoiron Methyl Complex: A Study of Reaction Intermediates
The one-electron reduction of CpFe(CO)2CH3 has been investigated by voltammetry and Fourier transform IR spectroelectrochemistry. The reduction initiates the insertion of CO ligand in the FeCH3 bond. The dissociation of a CO group proceeds in a parallel reaction. Reaction intermediates, the acyl derivative and released CO, form the radical anion of a complex CpFe(CO)2(COCH3) which is able to reduce the parent compound. The reversible redox potential − 1.8 V of CpFe(CO)2(COCH3) allows the regeneration of its radical anion which drives a catalytic cycle. The lifetime of intermediates is shortened by side reactions, one of which is the migration of the acyl group from the central atom to the cyclopentadienyl ring. This explains the apparent discrepancy between products observed in preparative scale electrolysis and the absence of catalytic effects in routine voltammetric experiments
Fluids of hard ellipsoids: Phase diagram including a nematic instability from Percus-Yevick theory
An important aspect of molecular fluids is the relation between orientation
and translation parts of the two-particle correlations. Especially the detailed
knowledge of the influence of orientation correlations is needed to explain and
calculate in detail the occurrence of a nematic phase.
The simplest model system which shows both orientation and translation
correlations is a system of hard ellipsoids. We investigate an isotropic fluid
formed of hard ellipsoids with Percus-Yevick theory.
Solving the Percus-Yevick equations self-consistently in the high density
regime gives a clear criterion for a nematic instability. We calculate in
detail the equilibrium phase diagram for a fluid of hard ellipsoids of
revolution. Our results compare well with Monte Carlo Simulations and density
functional theory.Comment: 7 pages including 4 figure
Penetrating particle ANalyzer (PAN)
PAN is a scientific instrument suitable for deep space and interplanetary
missions. It can precisely measure and monitor the flux, composition, and
direction of highly penetrating particles (100 MeV/nucleon) in deep
space, over at least one full solar cycle (~11 years). The science program of
PAN is multi- and cross-disciplinary, covering cosmic ray physics, solar
physics, space weather and space travel. PAN will fill an observation gap of
galactic cosmic rays in the GeV region, and provide precise information of the
spectrum, composition and emission time of energetic particle originated from
the Sun. The precise measurement and monitoring of the energetic particles is
also a unique contribution to space weather studies. PAN will map the flux and
composition of penetrating particles, which cannot be shielded effectively,
precisely and continuously, providing valuable input for the assessment of the
related health risk, and for the development of an adequate mitigation
strategy. PAN has the potential to become a standard on-board instrument for
deep space human travel.
PAN is based on the proven detection principle of a magnetic spectrometer,
but with novel layout and detection concept. It will adopt advanced particle
detection technologies and industrial processes optimized for deep space
application. The device will require limited mass (~20 kg) and power (~20 W)
budget. Dipole magnet sectors built from high field permanent magnet Halbach
arrays, instrumented in a modular fashion with high resolution silicon strip
detectors, allow to reach an energy resolution better than 10\% for nuclei from
H to Fe at 1 GeV/n
Design, Implementation and First Measurements with the Medipix Neutron Camera in CMS
The Medipix detector is the first device dedicated to measuring mixed-field
radiation in the CMS cavern and able to distinguish between different particle
types. Medipix2-MXR chips bump bonded to silicon sensors with various neutron
conversion layers developed by the IEAP CTU in Prague were successfully
installed for the 2008 LHC start-up in the CMS experimental and services
caverns to measure the flux of various particle types, in particular neutrons.
They have operated almost continuously during the 2010 run period, and the
results shown here are from the proton run between the beginning of July and
the end of October 2010. Clear signals are seen and different particle types
have been observed during regular LHC luminosity running, and an agreement in
the measured flux rate is found with the simulations. These initial results are
promising, and indicate that these devices have the potential for further and
future LHC and high energy physics applications as radiation monitoring devices
for mixed field environments, including neutron flux monitoring. Further
extensions are foreseen in the near future to increase the performance of the
detector and its coverage for monitoring in CMS.Comment: 15 pages, 16 figures, submitted to JINS
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