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Register a new userAn In-Situ Movable Calibration Source for Cryogenic Particle Detectors
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A prototype device capable of moving a radioactive calibration source to multiple positions was operated at millikelvin temperatures using a modified commercial stepper motor. It was developed as an in-situ calibration strategy for cryogenic dark matter detectors. Data taken by scanning a calibration source across multiple radial positions of a prototype dark matter detector demonstrated its functionality. Construction, heat load, and operation of the device are discussed, as is the effect of the motor on the detector operation. A sample dataset taken over multiple positions of a SuperCDMS detector is presented as an example of the utility of such a device.
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A stable reference light source based on an LED (Light Emission Diode) is presented for stabilizing the conversion gain of the opto-electronic system of a gamma- and fast-neutron radiographic and tomographic imaging device. A constant fraction of the LED light is transported to the image plane of the camera and provides a stable reference exposure. This is used to normalize the images during off-line image processing. We have investigated parameters influencing the stability of LEDs and developed procedures and criteria to prepare and select LEDs suitable for delivering stable light outputs for several 100 h of operation.
This article reviews the progress made over the last 20 years in the development and applications of liquid xenon detectors in particle physics, astrophysics and medical imaging experiments. We begin with a summary of the fundamental properties of liquid xenon as radiation detection medium, in light of the most current theoretical and experimental information. After a brief introduction of the different type of liquid xenon detectors, we continue with a review of past, current and future experiments using liquid xenon to search for rare processes and to image radiation in space and in medicine. We will introduce each application with a brief survey of the underlying scientific motivation and experimental requirements, before reviewing the basic characteristics and expected performance of each experiment. Within this decade it appears likely that large volume liquid xenon detectors operated in different modes will contribute to answering some of the most fundamental questions in particle physics, astrophysics and cosmology, fulfilling the most demanding detection challenges. From experiments like MEG, currently the largest liquid xenon scintillation detector in operation, dedicated to the rare mu -> e + gamma decay, to the future XMASS which also exploits only liquid xenon scintillation to address an ambitious program of rare event searches, to the class of time projection chambers like XENON and EXO which exploit both scintillation and ionization of liquid xenon for dark matter and neutrinoless double beta decay, respectively, we anticipate unrivaled performance and important contributions to physics in the next few years.
This is part of a document, which is devoted to the developments of pixel detectors in the context of the International Linear Collider. From the early developments of the MIMOSAs to the proposed DotPix I recall some of the major progresses. The need for very precise vertex reconstruction is the reason for the Research and Development of new pixel detectors, first derived from the CMOS sensors and in further steps with new semiconductors structures. The problem of radiation effects was investigated and this is the case for the noise level with emphasis of the benefits of downscaling. Specific semiconductor processing and characterisation techniques are also described, with the perspective of a new pixel structure.
Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision. Reconstruction algorithms identify and measure the kinematic properties of particles produced in high energy collisions and recorded with complex detector systems. Two critical applications are the reconstruction of charged particle trajectories in tracking detectors and the reconstruction of particle showers in calorimeters. These two problems have unique challenges and characteristics, but both have high dimensionality, high degree of sparsity, and complex geometric layouts. Graph Neural Networks (GNNs) are a relatively new class of deep learning architectures which can deal with such data effectively, allowing scientists to incorporate domain knowledge in a graph structure and learn powerful representations leveraging that structure to identify patterns of interest. In this work we demonstrate the applicability of GNNs to these two diverse particle reconstruction problems.
The Cryogenic Underground Observatory for Rare Events (CUORE) is a ton-scale cryogenic experiment designed to search for neutrinoless double-beta decay of $^{130}$Te and other rare events. The CUORE detector consists of 988 TeO$_2$ bolometers operated underground at 10 mK in a dilution refrigerator at the Laboratori Nazionali del Gran Sasso. Candidate events are identified through a precise measurement of their energy. The absolute energy response of the detectors is established by the regular calibration of each individual bolometer using gamma sources. The close-packed configuration of the CUORE bolometer array combined with the extensive shielding surrounding the detectors requires the placement of calibration sources within the array itself. The CUORE Detector Calibration System is designed to insert radioactive sources into and remove them from the cryostat while respecting the stringent heat load, radiopurity, and operational requirements of the experiment. This paper describes the design, commissioning, and performance of this novel source calibration deployment system for ultra-low-temperature environments.
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