Th. Lindblad

Properties of optical greases for BaF2 scintillators

Abstract Properties of different optical oils and greases in the UV light region were studied using transmission and photoelectron measurements. The results show that not all of the greases commonly used for scintillators are applicable to the BaF2 detector, which have a fast component in the UV region. Results obtained for a spectrometer consisting of a cylindrical well-polished 48 mm diam. × 50 mm BaF2 crystal indicate improved properties for the fast component, compared to the nonpolished crystals.

Intelligent detectors modelled from the cat's eye

Abstract Biologically inspired image/signal processing, in particular neural networks like the Pulse-Coupled Neural Network (PCNN), are revisited. Their use with high granularity high-energy physics detectors, as well as optical sensing devices, for filtering, de-noising, segmentation, object isolation and edge detection is discussed.

Electron drift velocity and characteristics of ionization of alpha and beta particles in liquid argon doped with ethylene for LHC calorimeter

Abstract Drift velocity and change response to α and β particles of liquid argon doped with 200 ppm to 0.5% (vol.) of ethylene have been studied. The addition of ethylene increases the drift velocity by at least a factor of 2 and, at low concentrations, improves the collected charge of α particles through photoionization. At larger concentrations, a degradation of the saturation properties of the mixture is observed. The present results demonstrate that simultaneous improvement of drift velocity and compensation in hadron calorimetry is incompatible. The consequences of using doped liquid argon for the large hadron collider (LHC) detectors in the high radiation environment are discussed.

Properties of BaF2 scintillator working with p-terphenyl wavelength shifter

Abstract Properties of a 4 cm diameter × 0.5 cm BaF 2 crystal coated with a 2 mg/cm 2 thick layer of p-terphenyl wavelength shifter were studied in comparison to a pure BaF 2 scintillator of the same dimensions. The light yield (expressed in the number of photoelectrons), the energy and time resolutions and the light pulse shape were determined for crystals coupled to the XP2020Q and XP2020 photomultipliers. This study shows an efficient shifting of the UV light by p-terphenyl, confirmed by the light yield comparable to that of the pure BaF 2 crystal, as well as a slightly better energy resolution. However, the time resolution measured for 60 Co γ-rays, ( E γ > 1 MeV), was degraded by a factor of 2, from 108 to 224 ps. This is associated with the slowing down of the light pulse caused by the energy transfer process from the BaF 2 emission to that of p-terphenyl. A light pulse with decay time constant equal to 2.5 ns and FWHM equal to 3.7 ns confirms the above conclusion.

Hybrid neural networks for automatic target recognition

The paper presents a hybrid neural network system for automatic target recognition, or ATR. The ATR system uses a hybrid of a biological inspired neural net called the Pulse Coupled Neural Net, PCNN, and traditional feedforward neural nets. The PCNN is an iterative neural network in which, for example, a grey scale input image results in a 1D time signal invariant to rotation, scale and translation alternations. The PCNN can also extract edges, perform object segmentation and extract texture information. The PCNN pre-processor generates a 1D time signal that is input to a feedforward pattern recognition net.

Implementing the new Zero Instruction Set Computer (ZISC036) from IBM for a Higgs search

Abstract Implementation of the new IBM Zero Instruction Set Computer (ZISC036) on a PC/ISA-bus card as well as on a VME-card is reported. The ZISC circuit has 36 processing elements of a type similar to that of Radial Basis Function (RBF) neurons. It is a highly parallel and cascadable building block with on-chip learning capability, and is well suited for pattern recognition, signal processing, etc. Results of a test on identification of simulated Higgs events are given.

Investigation of a VLSI neural network chip as part of a secondary vertex trigger

Abstract An analog VLSI neural network chip (ETANN) has been trained to detect secondary vertices in simulated data for a fixed target heavy flavour production experiment. The detector response and associative memory track finding were modelled by a simulation, but the vertex detection was performed in hardware by the neural network chip and requires only a few microseconds per event. The chip correctly tags 30% of the heavy flavour events while rejecting 99% of the background, and is thus well adapted for secondary vertex triggering applications. A general purpose VME module for interfacing the ETANN to experiments, equipped with ADC/DAC circuits and a 68070 CPU, is also presented.

Using software and hardware neural networks in a Higgs search

Abstract The present investigation uses information from computer simulations to train neural networks to identify decays of heavy Higgs particles (mH ⪢ mz). Results are presented both for software and hardware analog neural networks. The hardware tests include the Intel ETANN and the CLNN32/CLNS64 (experimental, research prototype developed at Bellcore) chip-set implemented in VME-modules. The processing and learning times for the networks are discussed.

A hardware neural network for on-line particle identification

Abstract The possibility of implementing a neural network in hardware to make an on-line particle identification of pions and kaons based on scintillation signals is demonstrated. The main aim of the investigation is to show the simplicity of implementing commercial neural network integrated circuits in high energy physics experiments.

Three-dimensional image processing in the analysis of triple γ-ray energy coincidences

Abstract A first approach to analyze triple coincidence events from nuclear γ-ray spectroscopy is presented. Emphasis is laid on tracing rotational correlation properties in nuclei. Possible ways of reducing the necessary data storage volume are discussed. Data are presented as different cuts in the three-dimensional volume, transverse planes and rotational planes. An improvement in the peak-to-background ratio of a factor 7 is found compared to a two-dimensional data set. Different ways to extract the nuclear moment of inertia parameters are presented.