Search results for "Pattern recognition"
showing 10 items of 2301 documents
Interlocking content and attitude: a reply to the anti-normativist
2021
Anti-normativists have advanced the view that the involvement of content in norms is not an essential feature of content, but a contingent feature or side effect of the normativity governing attitu...
Operation and first results of the NEXT-DEMO prototype using a silicon photomultiplier tracking array
2013
NEXT-DEMO is a high-pressure xenon gas TPC which acts as a technological test-bed and demonstrator for the NEXT-100 neutrinoless double beta decay experiment. In its current configuration the apparatus fully implements the NEXT-100 design concept. This is an asymmetric TPC, with an energy plane made of photomultipliers and a tracking plane made of silicon photomultipliers (SiPM) coated with TPB. The detector in this new configuration has been used to reconstruct the characteristic signature of electrons in dense gas, demonstrating the ability to identify the MIP and "blob" regions. Moreover, the SiPM tracking plane allows for the definition of a large fiducial region in which an excellent e…
Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks
2021
The Pierre Auger Observatory, at present the largest cosmic-ray observatory ever built, is instrumented with a ground array of 1600 water-Cherenkov detectors, known as the Surface Detector (SD). The SD samples the secondary particle content (mostly photons, electrons, positrons and muons) of extensive air showers initiated by cosmic rays with energies ranging from $10^{17}~$eV up to more than $10^{20}~$eV. Measuring the independent contribution of the muon component to the total registered signal is crucial to enhance the capability of the Observatory to estimate the mass of the cosmic rays on an event-by-event basis. However, with the current design of the SD, it is difficult to straightfo…
Nanosecond-level time synchronization of autonomous radio detector stations for extensive air showers
2016
To exploit the full potential of radio measurements of cosmic-ray air showers at MHz frequencies, a detector timing synchronization within 1 ns is needed. Large distributed radio detector arrays such as the Auger Engineering Radio Array (AERA) rely on timing via the Global Positioning System (GPS) for the synchronization of individual detector station clocks. Unfortunately, GPS timing is expected to have an accuracy no better than about 5 ns. In practice, in particular in AERA, the GPS clocks exhibit drifts on the order of tens of ns. We developed a technique to correct for the GPS drifts, and an independent method is used to cross-check that indeed we reach a nanosecond-scale timing accura…
A layer correlation technique for pion energy calibration at the 2004 ATLAS Combined Beam Test
2010
A new method for calibrating the hadron response of a segmented calorimeter is developed and successfully applied to beam test data. It is based on a principal component analysis of energy deposits in the calorimeter layers, exploiting longitudinal shower development information to improve the measured energy resolution. Corrections for invisible hadronic energy and energy lost in dead material in front of and between the calorimeters of the ATLAS experiment were calculated with simulated Geant4 Monte Carlo events and used to reconstruct the energy of pions impinging on the calorimeters during the 2004 Barrel Combined Beam Test at the CERN H8 area. For pion beams with energies between 20GeV…
Hyperspectral terahertz microscopy via nonlinear ghost imaging
2020
Ghost imaging, based on single-pixel detection and multiple pattern illumination, is a crucial investigative tool in difficult-to-access wavelength regions. In the terahertz domain, where high-resolution imagers are mostly unavailable, ghost imaging is an optimal approach to embed the temporal dimension, creating a “hyperspectral” imager. In this framework, high resolution is mostly out of reach. Hence, it is particularly critical to developing practical approaches for microscopy. Here we experimentally demonstrate time-resolved nonlinear ghost imaging, a technique based on near-field, optical-to-terahertz nonlinear conversion and detection of illumination patterns. We show how space–time c…
Design, upgrade and characterization of the silicon photomultiplier front-end for the AMIGA detector at the Pierre Auger Observatory
2021
The successful installation, commissioning, and operation of the Pierre Auger Observatory would not have been possible without the strong commitment and effort from the technical and administrative staff in Malargue. We are very grateful to the following agencies and organizations for financial support: Argentina -Comision Nacional de Energia Atomica; Agencia Nacional de Promocion Cientifica y Tecnologica (ANPCyT); Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET); Gobierno de la Provincia de Mendoza; Municipalidad de Malargue; NDM Holdings and Valle Las Lenas; in gratitude for their continuing cooperation over land access; Australia -the Australian Research Council; Braz…
Fingerprint classification based on deep learning approaches: Experimental findings and comparisons
2021
Biometric classification plays a key role in fingerprint characterization, especially in the identification process. In fact, reducing the number of comparisons in biometric recognition systems is essential when dealing with large-scale databases. The classification of fingerprints aims to achieve this target by splitting fingerprints into different categories. The general approach of fingerprint classification requires pre-processing techniques that are usually computationally expensive. Deep Learning is emerging as the leading field that has been successfully applied to many areas, such as image processing. This work shows the performance of pre-trained Convolutional Neural Networks (CNNs…
Classification of gravitational-wave glitches via dictionary learning
2018
We present a new method for the classification of transient noise signals (or glitches) in advanced gravitational-wave interferometers. The method uses learned dictionaries (a supervised machine learning algorithm) for signal denoising, and untrained dictionaries for the final sparse reconstruction and classification. We use a data set of 3000 simulated glitches of three different waveform morphologies, comprising 1000 glitches per morphology. These data are embedded in non-white Gaussian noise to simulate the background noise of advanced LIGO in its broadband configuration. Our classification method yields a 96% accuracy for a large range of initial parameters, showing that learned diction…
Cost-Effective Treatment of Scalar Relativistic Effects for Multireference Systems: A CASSCF Implementation Based on the Spin-free Dirac-Coulomb Hami…
2016
We present an implementation of the complete active space-self-consistent field (CASSCF) method specifically designed to be used in four-component scalar relativistic calculations based on the spin-free Dirac-Coulomb (SFDC) Hamiltonian. Our implementation takes full advantage of the properties of the SFDC Hamiltonian that allow us to use real algebra and to exploit point-group and spin symmetry to their full extent while including in a rigorous way scalar relativistic effects in the treatment. The SFDC-CASSCF treatment is more expensive than its non-relativistic counterpart only in the orbital optimization step, while exhibiting the same computational cost for the rate-determining full conf…