47 research outputs found
Modeling of GERDA Phase II data
The GERmanium Detector Array (GERDA) experiment at the Gran Sasso underground
laboratory (LNGS) of INFN is searching for neutrinoless double-beta
() decay of Ge. The technological challenge of GERDA is
to operate in a "background-free" regime in the region of interest (ROI) after
analysis cuts for the full 100kgyr target exposure of the
experiment. A careful modeling and decomposition of the full-range energy
spectrum is essential to predict the shape and composition of events in the ROI
around for the search, to extract a precise
measurement of the half-life of the double-beta decay mode with neutrinos
() and in order to identify the location of residual
impurities. The latter will permit future experiments to build strategies in
order to further lower the background and achieve even better sensitivities. In
this article the background decomposition prior to analysis cuts is presented
for GERDA Phase II. The background model fit yields a flat spectrum in the ROI
with a background index (BI) of cts/(kgkeVyr) for the enriched BEGe data set and
cts/(kgkeVyr) for the
enriched coaxial data set. These values are similar to the one of Gerda Phase I
despite a much larger number of detectors and hence radioactive hardware
components
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Modeling of GERDA Phase II data
The GERmanium Detector Array (Gerda) experiment at the Gran Sasso underground laboratory (LNGS) of INFN is searching for neutrinoless double-beta (0νββ) decay of 76Ge. The technological challenge of Gerda is to operate in a “background-free” regime in the region of interest (ROI) after analysis cuts for the full 100 kg·yr target exposure of the experiment. A careful modeling and decomposition of the full-range energy spectrum is essential to predict the shape and composition of events in the ROI around Qββ for the 0νββ search, to extract a precise measurement of the half-life of the double-beta decay mode with neutrinos (2νββ) and in order to identify the location of residual impurities. The latter will permit future experiments to build strategies in order to further lower the background and achieve even better sensitivities. In this article the background decomposition prior to analysis cuts is presented for Gerda Phase II. The background model fit yields a flat spectrum in the ROI with a background index (BI) of 16.04+0.78−0.85⋅10−3 cts/(keV·kg·yr) for the enriched BEGe data set and 14.68+0.47−0.52⋅10−3 cts/(keV·kg·yr) for the enriched coaxial data set. These values are similar to the one of Phase I despite a much larger number of detectors and hence radioactive hardware components
Conflict Causes and Prevention Strategies at the Society-Science Nexus in Transdisciplinary Collaborative Research Settings
Collaboration between researchers and society is essential when addressing challenging 21st Century questions. Such collaboration often comprises international, inter- and trans-disciplinary teams, as well as temporal constraints, resulting in inherently complex research projects. Although practitioners increasingly appreciate the value of bottom-up approaches, operational details are often overlooked. Further knowledge is necessary, especially about what might endanger project success. Using a food security project, this paper analyzes conflict experiences and prevention strategies between project members and local stakeholders through personal interviews and focus group discussions. Data for this case study was collected in four Tanzanian villages. This paper identifies multiple conflict drivers, including missing information transfers; diverging expectations; overlaps of field activities with seasonal farming activities; and obscure participant selection. Identified conflict prevention strategies include developing trust, reducing language barriers, and involving locals. Research practitioners, institutes, and hegemonic actors are responsible for ensuring that projects will not worsen the entered situation and negatively affect the community, adhering to the “do no harm” principle; therefore, it is vital to be aware and seek to improve international and collaborative research projects that actively involve local stakeholders. This paper supports the understanding of interacting with local communities in a food security context to support the development of innovative collaboration approaches and methods. Through collaboration, it is possible to find sustainable solutions to pressing issues.Peer Reviewe