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44 result(s) for "XENON Collaboration"
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The XENON1T dark matter experiment
The XENON1T experiment at the Laboratori Nazionali del Gran Sasso (LNGS) is the first WIMP dark matter detector operating with a liquid xenon target mass above the ton-scale. Out of its 3.2 t liquid xenon inventory, 2.0 t constitute the active target of the dual-phase time projection chamber. The scintillation and ionization signals from particle interactions are detected with low-background photomultipliers. This article describes the XENON1T instrument and its subsystems as well as strategies to achieve an unprecedented low background level. First results on the detector response and the performance of the subsystems are also presented.
Material radiopurity control in the XENONnT experiment
The selection of low-radioactive construction materials is of the utmost importance for rare-event searches and thus critical to the XENONnT experiment. Results of an extensive radioassay program are reported, in which material samples have been screened with gamma-ray spectroscopy, mass spectrometry, and 222Rn emanation measurements. Furthermore, the cleanliness procedures applied to remove or mitigate surface contamination of detector materials are described. Screening results, used as inputs for a XENONnT Monte Carlo simulation, predict a reduction of materials background (∼17%) with respect to its predecessor XENON1T. Through radon emanation measurements, the expected 222Rn activity concentration in XENONnT is determined to be 4.2 (-0.7+0.5) μBq/kg, a factor three lower with respect to XENON1T. This radon concentration will be further suppressed by means of the novel radon distillation system.
Material radioassay and selection for the XENON1T dark matter experiment
The XENON1T dark matter experiment aims to detect weakly interacting massive particles (WIMPs) through low-energy interactions with xenon atoms. To detect such a rare event necessitates the use of radiopure materials to minimize the number of background events within the expected WIMP signal region. In this paper we report the results of an extensive material radioassay campaign for the XENON1T experiment. Using gamma-ray spectroscopy and mass spectrometry techniques, systematic measurements of trace radioactive impurities in over one hundred samples within a wide range of materials were performed. The measured activities allowed for stringent selection and placement of materials during the detector construction phase and provided the input for XENON1T detection sensitivity estimates through Monte Carlo simulations.
Removing krypton from xenon by cryogenic distillation to the ppq level
The XENON1T experiment aims for the direct detection of dark matter in a detector filled with 3.3 tons of liquid xenon. In order to achieve the desired sensitivity, the background induced by radioactive decays inside the detector has to be sufficiently low. One major contributor is the β -emitter 85 Kr which is present in the xenon. For XENON1T a concentration of natural krypton in xenon nat Kr / Xe < 200 ppq   (parts per quadrillion,  1 ppq = 10 - 15 mol / mol ) is required. In this work, the design, construction and test of a novel cryogenic distillation column using the common McCabe–Thiele approach is described. The system demonstrated a krypton reduction factor of 6.4 · 10 5 with thermodynamic stability at process speeds above 3 kg/h. The resulting concentration of nat Kr / Xe < 26 ppq is the lowest ever achieved, almost one order of magnitude below the requirements for XENON1T and even sufficient for future dark matter experiments using liquid xenon, such as XENONnT and DARWIN.
The neutron veto of the XENONnT experiment: results with demineralized water
Radiogenic neutrons emitted by detector materials are one of the most challenging backgrounds for the direct search of dark matter in the form of weakly interacting massive particles (WIMPs). To mitigate this background, the XENONnT experiment is equipped with a novel gadolinium-doped water Cherenkov detector, which encloses the xenon dual-phase time projection chamber (TPC). The neutron veto (NV) can tag neutrons via their capture on gadolinium or hydrogen, which release γ -rays that are subsequently detected as Cherenkov light. In this work, we present the first results of the XENONnT NV when operated with demineralized water only, before the insertion of gadolinium. Its efficiency for detecting neutrons is ( 82 ± 1 ) % , the highest neutron detection efficiency achieved in a water Cherenkov detector. This enables a high efficiency of ( 53 ± 3 ) % for the tagging of WIMP-like neutron signals, inside a tagging time window of 250 μ s between TPC and NV, leading to a livetime loss of 1.6 % during the first science run of XENONnT.
Intrinsic backgrounds from Rn and Kr in the XENON100 experiment
In this paper, we describe the XENON100 data analyses used to assess the target-intrinsic background sources radon ([InlineMediaObject not available: see fulltext.]), thoron ([InlineMediaObject not available: see fulltext.]) and krypton ([InlineMediaObject not available: see fulltext.]). We detail the event selections of high-energy alpha particles and decay-specific delayed coincidences. We derive distributions of the individual radionuclides inside the detector and quantify their abundances during the main three science runs of the experiment over a period of ∼4years, from January 2010 to January 2014. We compare our results to external measurements of radon emanation and krypton concentrations where we find good agreement. We report an observed reduction in concentrations of radon daughters that we attribute to the plating-out of charged ions on the negatively biased cathode.
Online²²²222 Rn removal by cryogenic distillation in the XENON100 experiment
Abstract We describe the purification of xenon from traces of the radioactive noble gas radon using a cryogenic distillation column. The distillation column was integrated into the gas purification loop of the XENON100 detector for online radon removal. This enabled us to significantly reduce the constant²²²222 Rn background originating from radon emanation. After inserting an auxiliary²²²222 Rn emanation source in the gas loop, we determined a radon reduction factor ofR > 27R > 27 (95% C.L.) for the distillation column by monitoring the²²²222 Rn activity concentration inside the XENON100 detector.
The XENONnT Dark Matter Experiment
The multi-staged XENON program at INFN Laboratori Nazionali del Gran Sasso aims to detect dark matter with two-phase liquid xenon time projection chambers of increasing size and sensitivity. The XENONnT experiment is the latest detector in the program, planned to be an upgrade of its predecessor XENON1T. It features an active target of 5.9 tonnes of cryogenic liquid xenon (8.5 tonnes total mass in cryostat). The experiment is expected to extend the sensitivity to WIMP dark matter by more than an order of magnitude compared to XENON1T, thanks to the larger active mass and the significantly reduced background, improved by novel systems such as a radon removal plant and a neutron veto. This article describes the XENONnT experiment and its sub-systems in detail and reports on the detector performance during the first science run.
XENONnT WIMP Search: Signal & Background Modeling and Statistical Inference
The XENONnT experiment searches for weakly-interacting massive particle (WIMP) dark matter scattering off a xenon nucleus. In particular, XENONnT uses a dual-phase time projection chamber with a 5.9-tonne liquid xenon target, detecting both scintillation and ionization signals to reconstruct the energy, position, and type of recoil. A blind search for nuclear recoil WIMPs with an exposure of 1.1 tonne-years (4.18 t fiducial mass) yielded no signal excess over background expectations, from which competitive exclusion limits were derived on WIMP-nucleon elastic scatter cross sections, for WIMP masses ranging from 6 GeV/\\(c^2\\) up to the TeV/\\(c^2\\) scale. This work details the modeling and statistical methods employed in this search. By means of calibration data, we model the detector response, which is then used to derive background and signal models. The construction and validation of these models is discussed, alongside additional purely data-driven backgrounds. We also describe the statistical inference framework, including the definition of the likelihood function and the construction of confidence intervals.