arXiv subjects

Zbigniew Szadkowski

Publications and source records attributed to Zbigniew Szadkowski.

4 recordsLinked to original sources

arXiv2014

Artificial Neural Network as a FPGA Trigger for a Detection of Very Inclined Air Showers

Neutrinos can interact in the atmosphere (downward-going ν) or in the Earth crust (Earth-skimming ν), producing air showers that can be observed with arrays of detectors at the ground. The surface detector array of the Pierre Auger Observatory can detect these types of cascades. The distinguishing signature for neutrino events is the presence of very inclined showers produced close to the ground (i.e., after having traversed a large amount of atmosphere). Up to now, the Pierre Auger Observatory did not find any candidate for a neutrino event. A very low rate of events potentially generated by neutrinos is a significant challenge for a detection technique and requires both sophisticated algorithms and high-resolution hardware. We present a trigger based on a pipeline artificial neural network (ANN) implemented in a large FPGA which after learning can recognize traces corresponding to special types of events. The structure of an ANN algorithm being developed on the MATLAB platform has been implemented into the fast logic of the biggest Cyclone V E FPGA used for the prototype of the Front-End Board for the Auger-Beyond-2015 effort. Several algorithms were tested, however, the Levenberg-Marquardt one seems to be the most efficient. The network was taught: a) to recognize "old" showers (learning on a basis of real very inclined Auger showers (positive markers) and real standard showers especially triggered by Time over Threshold (negative marker), b) to recognize "young" showers (on the basis of simulated "young" events (positive markers) and standard Auger events as a negative reference). A three-layer neural network being taught by real very inclined Auger showers shows a good efficiency in pattern recognition of 16-point traces with profiles characteristic of "old" showers.

physics.ins-det↗

arXiv2014

Front-End Board with Cyclone V as a Test High-Resolution Platform for the Auger-Beyond-2015 Front End Electronics

The surface detector (SD) array of the Pierre Auger Observatory containing at present 1680 water Cherenkov detectors spread over an area of 3000 km^2 started to operate since 2004. The currently used Front-End Boards are equipped with no-more produced ACEX and obsolete Cyclone FPGA (40 MSps/15-bit of dynamic range). Huge progress in electronics and new challenges from physics impose a significant upgrade of the SD electronics either to improve a quality of measurements (much higher sampling and much wider dynamic range) or pick-up from a background extremely rare events (new FPGA algorithms based on sophisticated approaches like e.g. spectral triggers or neural networks). Much higher SD sensitivity is necessary to confirm or reject hypotheses critical for a modern astrophysics. The paper presents the Front-End Board (FEB) with the biggest Cyclone V E FPGA 5CEFA9F31I7N, supporting 8 channels sampled with max. 250 MSps @ 14-bit resolution. Considered sampling for the SD is 120 MSps, however, the FEB has been developed with external anti-aliasing filters to keep a maximal flexibility. Six channels are targeted to the SD, two the rest for other experiments like: Auger Engineering Radio Array and additional muon counters. The FEB is an intermediate design pluged-in the actually used Unified Board communicating with micro-controller at 40 MHz, however providing even 250 MSPs sampling with 20-bit dynamic range, equipped in a virtual NIOS processor and supporting 256 MB of SDRAM as well as with an implemented spectral trigger based on the Discrete Cosine Transform for a detection of very inclined "old" showers. The FEB can also support a neural network developing for a detection of "young" showers, potentially generated by neutrinos.

physics.ins-det↗

arXiv2014

An Optimization of the FPGA Based Wavelet Trigger in Radio Detection of Cosmic Rays

Experiments that observe coherent radio emission from extensive air showers induced by ultra-high energy cosmic rays are designed for a detailed study of the development of the electromagnetic part of air showers. Radio detectors can operate with 100% up time as e.g. surface detectors based on water-Cherenkov tanks. They are being developed for ground-based experiments (e.g. the Pierre Auger Observatory) as another type of air shower detector in addition to the fluorescence detectors, which operate with only ~10% of duty in dark nights. The radio signals from air showers are caused by the coherent emission due to geomagnetic radiation and charge excess processes. Currently used self-triggers in radio detectors often generate a dense stream of data, which is analyzed afterwards. Huge amounts of registered data requires a significant man-power for the off-line analysis. An improvement of the trigger efficiency becomes a relevant factor. In this work, Morlet wavelets with various scaling factors were used for an analysis of real data from the Auger Engineering Radio Array and for an optimization of the utilization of the resources in an FPGA. The wavelet analysis showed that the power of events is concentrated mostly in a limited range of the frequency spectrum (consistent with a range imposed by the input analog band-pass filter). However, we found several events with suspicious spectral characteristics, where the signal power is spread over the full band-width sampled by a 200 MHz digitizer with significant contribution of very high and very low frequencies. These events may not origin from cosmic ray showers but can be human-made contaminations. The engine of the wavelet analysis can be implemented into the modern powerful FPGA and can remove suspicious events on-line to reduce the trigger rate.

physics.ins-det↗

arXiv2014

First results from the FPGA/NIOS Adaptive FIR Filter Using Linear Prediction Implemented in the AERA Radio Stations to Reduce Narrow Band RFI for Radio Detection of Cosmic Rays

The FPGA/NIOS FIR filter based on linear prediction (LP) to suppress radio frequency interference (RFI) has been installed in several radio stations in the Auger Engineering Radio Array (AERA) experiment. AERA observes coherent radio emission from extensive air showers induced by ultra-high-energy cosmic rays to make a detailed study of the development of the electromagnetic part of air showers. Radio signals provide complementary information to that obtained from Auger surface detectors, which are predominantly sensitive to the particle content of an air shower at the surface. The radio signals from air showers are caused by the coherent emission due to geomagnetic and charge-excess processes. These emissions can be observed in the frequency band between 10 - 100 MHz. However, this frequency range is significantly contaminated by narrow-band RFI and other human-made distortions. A FIR filter implemented in the FPGA logic segment of the front-end electronics of a radio sensor significantly improves the signal-to-noise ratio. In this paper we present first results of the efficiency of the adaptive LP FIR filter, deployed in real AERA station on pampas, with a comparison to the currently used IIR notch filter with constant coefficients. The laboratory tests confirms the stability of the filter. Using constant LP coefficients the suppression efficiency remains the same for hours, which corresponds to more than $\bf 10^{12}$ clock cycles. We compared in real conditions several variants of the LP FIR filter with various lengths and various coefficients widths (due to fixed-point representations in the FPGA logic) with the aim to minimize the power consumption for the radio station while keeping sufficient accuracy for noise reduction.

physics.ins-det↗