41 research outputs found
Deep Neural Networks for Energy and Position Reconstruction in EXO-200
We apply deep neural networks (DNN) to data from the EXO-200 experiment. In
the studied cases, the DNN is able to reconstruct the relevant parameters -
total energy and position - directly from raw digitized waveforms, with minimal
exceptions. For the first time, the developed algorithms are evaluated on real
detector calibration data. The accuracy of reconstruction either reaches or
exceeds what was achieved by the conventional approaches developed by EXO-200
over the course of the experiment. Most existing DNN approaches to event
reconstruction and classification in particle physics are trained on Monte
Carlo simulated events. Such algorithms are inherently limited by the accuracy
of the simulation. We describe a unique approach that, in an experiment such as
EXO-200, allows to successfully perform certain reconstruction and analysis
tasks by training the network on waveforms from experimental data, either
reducing or eliminating the reliance on the Monte Carlo.Comment: Accepted version. 33 pages, 28 figure
Sensitivity and discovery potential of the proposed nEXO experiment to neutrinoless double beta decay
The next-generation Enriched Xenon Observatory (nEXO) is a proposed
experiment to search for neutrinoless double beta () decay in
Xe with a target half-life sensitivity of approximately years
using kg of isotopically enriched liquid-xenon in a time
projection chamber. This improvement of two orders of magnitude in sensitivity
over current limits is obtained by a significant increase of the Xe
mass, the monolithic and homogeneous configuration of the active medium, and
the multi-parameter measurements of the interactions enabled by the time
projection chamber. The detector concept and anticipated performance are
presented based upon demonstrated realizable background rates.Comment: v2 as publishe
Characterization of an Ionization Readout Tile for nEXO
A new design for the anode of a time projection chamber, consisting of a
charge-detecting "tile", is investigated for use in large scale liquid xenon
detectors. The tile is produced by depositing 60 orthogonal metal
charge-collecting strips, 3~mm wide, on a 10~\si{\cm} 10~\si{\cm}
fused-silica wafer. These charge tiles may be employed by large detectors, such
as the proposed tonne-scale nEXO experiment to search for neutrinoless
double-beta decay. Modular by design, an array of tiles can cover a sizable
area. The width of each strip is small compared to the size of the tile, so a
Frisch grid is not required. A grid-less, tiled anode design is beneficial for
an experiment such as nEXO, where a wire tensioning support structure and
Frisch grid might contribute radioactive backgrounds and would have to be
designed to accommodate cycling to cryogenic temperatures. The segmented anode
also reduces some degeneracies in signal reconstruction that arise in
large-area crossed-wire time projection chambers. A prototype tile was tested
in a cell containing liquid xenon. Very good agreement is achieved between the
measured ionization spectrum of a Bi source and simulations that
include the microphysics of recombination in xenon and a detailed modeling of
the electrostatic field of the detector. An energy resolution =5.5\%
is observed at 570~\si{keV}, comparable to the best intrinsic ionization-only
resolution reported in literature for liquid xenon at 936~V/\si{cm}.Comment: 18 pages, 13 figures, as publishe
An integrated online radioassay data storage and analytics tool for nEXO
Large-scale low-background detectors are increasingly used in rare-event
searches as experimental collaborations push for enhanced sensitivity. However,
building such detectors, in practice, creates an abundance of radioassay data
especially during the conceptual phase of an experiment when hundreds of
materials are screened for radiopurity. A tool is needed to manage and make use
of the radioassay screening data to quantitatively assess detector design
options. We have developed a Materials Database Application for the nEXO
experiment to serve this purpose. This paper describes this database, explains
how it functions, and discusses how it streamlines the design of the
experiment