Coherent noise source identification in multi channel analysis

The evaluation of coherent noise can provide useful information in the study of detectors. The identification of coherent noise sources is also relevant for uncertainty calculations in analyse where several channels are combined. The study of the covariance matrix give information about coherent noises. Since covariance matrix of high dimension data could be difficult to analyse, the development of analysis tools is needed. Principal Component Analysis (PCA) is a powerful tool for such analysis. It has been shown that we can use PCA to find coherent noises in ATLAS calorimeter or the CALICE Si-W electromagnetic calorimeter physics prototype. However, if several coherent noise sources are combined, the interpretation of the PCA may become complicated. In this paper, we present another method based on the study of the covariance matrix to identify noise sources. This method has been developed for the study of front end ASICs dedicated to CALICE calorimeters. These calorimeters are designed and studied for experiments at the ILC. We also study the reliability of the method with simulations. Although this method has been developped for a specific application, it can be used for any multi channel analysis.Comment: Public version of the CALICE Internal Note CIN-02

Mesure de la luminosité pour l'expérience H1

At HERA, luminosity is determined on-line and bunch by bunch by measuring the bremsstrahlung spectrum from e-p collisions. The H1 collaboration has built a completely new luminosity system in order to sustain the harsh running conditions after the fourfold luminosity increase. Namely, the higher synchrotron radiation doses and the increased event pile-up have governed the design of the two major components, a radiation resistant quartz-fibre electro-magnetic calorimeter, and a fast read-out electronic with on-line energy histogramming at a rate of 500 kHz. The LLR group was in charge of the electronic and the on-line data analysis of the new luminosity system. In this thesis, I present analysis tools and methods to improve the precision of the luminosity measurement. The energy scale and acceptance calculation methods set out in this thesis permit these values to be determined every four minutes, to an accuracy of 0.5 parts per thousand for the energy scale and 2 parts per thousand for the acceptance. From these results, the degree of accuracy obtained on the luminosity measurement is between 6.5 and 9.5 parts per thousand. These results are currently undergoing validation, with the aim of becoming the standard H1 method.I also studied quasi-elastic Compton events to cross-check the luminosity measurement using the 2003-2004 and 2005 data. Indeed, this process has a well calculable cross section and a clear experimental signature. The leptonic final state consists of a coplanar e-gamma system, both observable in the central H1 detector.Depuis le début du fonctionnement de HERA, la mesure de la luminosité est réalisée en détectant les photons de bremsstrahlung émis par les électrons dans la région d'interaction. En raison des nouvelles conditions de fonctionnement, un nouveau détecteur de photons pour le système de luminosité de H1 a été développé et installé dans le tunnel à 104 mètres du point d'interaction. L'objet de cette thèse est d'analyser les données enregistrées par le détecteur de photons et d'étudier les variations de la luminosité dans H1 au cours des prises de données. Les méthodes de calcul de l'échelle d'énergie et de l'acceptance présentées dans cette thèse permettent de déterminer ces grandeurs toutes les quatre minutes avec une précision de l'ordre de 0,5 pour mille pour l'échelle d'énergie et de l'ordre de 2 pour mille pour l'acceptance. La position et la largeur du faisceau sont également mesurées toutes les quatre minutes avec une précision de l'ordre de 0,01 mm pour la position et de l'ordre de 0,05 mm pour la largeur. Ces résultats permettent de calculer la luminosité instantanée toutes les quatre minutes avec une erreur de l'ordre de 6,5 à 9,5 pour mille. Ces résultats sont en cours de validation pour devenir la méthode standard dans H1.J'ai également étudié les événements Compton élastique. La diffusion Compton élastique est utilisée pour une mesure complémentaire de la luminosité car sa section efficace est connue avec une bonne précision et la signature des événements dans le détecteur H1 est facilement identifiable

Commissioning of PENELOPE and GATE Monte Carlo models for 6 and 18 MV photon beams from the Siemens Artiste linac

International audiencePurpose: Monte Carlo (MC) simulations currently allow accurate calculation of the dose delivered to patients in radiotherapy treatments, provided that the linear accelerator can be modelled accurately. The commissioning of the linac model is thus an important task to ensure the overall accuracy of the calculated dose. This work aims at commissioning MC models developed with PENELOPE and GATE for the 6 and 18 MV photon beams of the Siemens ARTISTE linac, by comparing simulation to measurement.Materials: Linac photon beam models at 6 and 18 MV were commissioned. Percentage depth doses (PDD) and lateral beam profiles at dmax, 5 and 10 cm were measured for open square fields from 5x5 to 30x30 cm at 100 SSD using a PTW large MP3 water tank with a PTW Semiflex 0.125 cm3 ionization chamber. MC simulations were performed using PENELOPE 2006/PENFAST and GATE v6.0 (based on GEANT4 9.3.p02) in two steps: phase space files storing particles exiting the linac head were first computed and then used as input data for dose computation. Both codes are optimized for radiotherapy purposes and include commonly used variance reduction techniques. The linac geometry was described in the simulation based on the manufacturer specifications. The main parameters defining the incident electron beam, i.e. its mean energy and its radial intensity distribution, were determined following the methodology suggested by Pena et al (Med. Phys. 2007), using PDDs and lateral profiles of the 5x5, 10x10 and 30x30 cm fields. The incident electron beam was assumed to be monoenergetic and monodirectional. Dose computations in the water phantom were performed using PENFAST and GATE 6.0.0, with a voxel size of 4 mm in all directions for all field sizes.Results: At depth greater than dmax, simulated PDDs with GATE and PENELOPE both agreed with measurement to better than 1% for 6 and 18 MV. At shallower depths, both MC codes underestimated the measured dose. Lateral profiles matched measured ones within 1%/1 mm at 6 MV and within 2%/2 mm at 18 MV, for both codes. Larger discrepancies are however observed for field sizes larger than 25x25 cm. Work is ongoing to identify the reasons for these discrepancies; the impact of the initial electron energy distribution is particularly investigated.Conclusions: Photon beam models of the Siemens ARTISTE linac at 6 and 18 MV were developed with PENELOPE and GATE and commissioned. Good agreement was obtained between measured and simulated dose distributions, confirming the validity of the models

Optimization of GEANT4 settings for Proton Pencil Beam Scanning simulations using GATE

This study reports the investigation of different GEANT4 settings for proton therapy applications in the context of Treatment Planning System comparisons. The GEANT4.9.2 release was used through the GATE platform. We focused on the Pencil Beam Scanning delivery technique, which allows for intensity modulated proton therapy applications. The most relevant options and parameters (range cut, step size, database binning) for the simulation that influence the dose deposition were investigated, in order to determine a robust, accurate and efficient simulation environment. In this perspective, simulations of depth-dose profiles and transverse profiles at different depths and energies between 100 and 230 MeV have been assessed against reference measurements in water and PMMA. These measurements were performed in Essen, Germany, with the IBA dedicated Pencil Beam Scanning system, using Bragg-peak chambers and radiochromic films. GEANT4 simulations were also compared to the PHITS.2.14 and MCNPX.2.5.0 Monte Carlo codes. Depth-dose simulations reached 0.3 mm range accuracy compared to NIST CSDA ranges, with a dose agreement of about 1% over a set of five different energies. The transverse profiles simulated using the different Monte Carlo codes showed discrepancies, with up to 15% difference in beam widening between GEANT4 and MCNPX in water. A 8% difference between the GEANT4 multiple scattering and single scattering algorithms was observed. The simulations showed the inability of reproducing the measured transverse dose spreading with depth in PMMA, corroborating the fact that GEANT4 underestimates the lateral dose spreading. GATE was found to be a very convenient simulation environment to perform this study. A reference physics-list and an optimized parameters-list have been proposed. Satisfactory agreement against depth-dose profiles measurements was obtained. The simulation of transverse profiles using different Monte Carlo codes showed significant deviations. This point is crucial for Pencil Beam Scanning delivery simulations and suggests that the GEANT4 multiple scattering algorithm should be revised. (C) 2010 Elsevier B.V. All rights reserved

PYM: a new, affordable, image-based method using a Raspberry Pi to phenotype plant leaf area in a wide diversity of environments

Background: Plant science uses increasing amounts of phenotypic data to unravel the complex interactions between biological systems and their variable environments. Originally, phenotyping approaches were limited by manual, often destructive operations, causing large errors. Plant imaging emerged as a viable alternative allowing non-invasive and automated data acquisition. Several procedures based on image analysis were developed to monitor leaf growth as a major phenotyping target. However, in most proposals, a time-consuming parameterization of the analysis pipeline is required to handle variable conditions between images, particularly in the field due to unstable light and interferences with soil surface or weeds. To cope with these difficulties, we developed a low-cost, 2D imaging method, hereafter called PYM. The method is based on plant leaf ability to absorb blue light while reflecting infrared wavelengths. PYM consists of a Raspberry Pi computer equipped with an infrared camera and a blue filter and is associated with scripts that compute projected leaf area. This new method was tested on diverse species placed in contrasting conditions. Application to field conditions was evaluated on lettuces grown under photovoltaic panels. The objective was to look for possible acclimation of leaf expansion under photovoltaic panels to optimise the use of solar radiation per unit soil area. Results: The new PYM device proved to be efficient and accurate for screening leaf area of various species in wide ranges of environments. In the most challenging conditions that we tested, error on plant leaf area was reduced to 5% using PYM compared to 100% when using a recently published method. A high-throughput phenotyping cart, holding 6 chained PYM devices, was designed to capture up to 2000 pictures of field-grown lettuce plants in less than 2 h. Automated analysis of image stacks of individual plants over their growth cycles revealed unexpected differences in leaf expansion rate between lettuces rows depending on their position below or between the photovoltaic panels. Conclusions: The imaging device described here has several benefits, such as affordability, low cost, reliability and flexibility for online analysis and storage. It should be easily appropriated and customized to meet the needs of various users

MOESM1 of PYM: a new, affordable, image-based method using a Raspberry Pi to phenotype plant leaf area in a wide diversity of environments

Additional file 1. Photograph of the phenotyping cart operating on field grown lettuces. Plantation boards were composed of 6 rows. Each row was associated with a single camera, resulting in 6 cameras mounted on Raspberry Pi and attached to the cart at 1 m height above soil level. Two operators, one on each side of the crop plot, moved the cart row after row, one operator triggered the image capture. A, B and C: side views of the phenotyping cart. D: Wiring between contactor and one Raspberry Pi. E: Contactor triggering the image capture on each camera. F: Wiring at the 1st Raspberry Pi level, supplying power for image capture triggering. G: Detail of wiring at the pin levels for the 1st Raspberry Pi. H: Detail of wiring at the pin levels for all others Raspberry Pi. I: Blue filter glued to a camera