Complementarity of direct detection experiments in search of light Dark Matter

Dark Matter experiments searching for Weakly interacting massive particles (WIMPs) primarily use nuclear recoils (NRs) in their attempt to detect WIMPs. Migdal-induced electronic recoils (ERs) provide additional sensitivity to light Dark Matter with $\mathcal{O}(\text{GeV}/c^2)$ masses. In this work, we use Bayesian inference to find the parameter space where future detectors like XENONnT and SuperCDMS SNOLAB will be able to detect WIMP Dark Matter through NRs, Migdal-induced ERs or a combination thereof. We identify regions where each detector is best at constraining the Dark Matter mass and spin independent cross-section and infer where two or more detection configurations are complementary to constraining these Dark Matter parameters through a combined analysis.Comment: 19 pages, 7 figure

Solar neutrino detection sensitivity in DARWIN via electron scattering

We detail the sensitivity of the proposed liquid xenon DARWIN observatory to solar neutrinos via elastic electron scattering. We find that DARWIN will have the potential to measure the fluxes of five solar neutrino components: pp, 7Be, 13N, 15O and pep. The precision of the13N, 15O and pep components is hindered by the doublebeta decay of 136Xe and, thus, would benefit from a depleted target. A high-statistics observation of pp neutrinos would allow us to infer the values of the electroweak mixing angle,sin2 θw, and the electron-type neutrino survival probability, Pee, in the electron recoil energy region from a few keV up to 200keV for the first time, with relative precision of 5% and 4%, respectively, with 10 live years of data and a 30 tonne fiducial volume. An observation of pp and 7Be neutrinos would constrain the neutrino-inferred solar luminosity down to 0.2%. A combination of all flux measurements would distinguish between the high- (GS98) and low-metallicity (AGS09) solar models with 2.1–2.5σ significance, independent of external measurements from other experiments or a measurement of8B neutrinos through coherent elastic neutrino-nucleus scattering in DARWIN. Finally, we demonstrate that with a depleted target DARWIN may be sensitive to the neutrino capture process of 131Xe

Data-Driven Decision Support Tool Co-Development with a Primary Health Care Practice Based Learning Network

Background: The Alliance for Healthier Communities is a learning health system that supports Community Health Centres (CHCs) across Ontario, Canada to provide team-based primary health care to people who otherwise experience barriers to care. This case study describes the ongoing process and lessons learned from the first Alliance for Healthier Communities’ Practice Based Learning Network (PBLN) data-driven decision support tool co-development project. Methods: We employ an iterative approach to problem identification and methods development for the decision support tool, moving between discussion sessions and case studies with CHC electronic health record (EHR) data. We summarize our work to date in terms of six stages: population-level descriptive-exploratory study, PBLN team engagement, decision support tool problem selection, sandbox case study 1: individual-level risk predictions, sandbox case study 2: population-level planning predictions, project recap and next steps decision. Results: The population-level study provided an initial point of engagement to consider how clients are (not) represented in EHR data and to inform problem selection and methodological decisions thereafter. We identified three meaningful types of decision support, with initial target application areas: risk prediction/screening, triaging specialized program referrals, and identifying care access needs. Based on feasibility and expected impact, we started with the goal to support earlier identification of mental health decline after diabetes diagnosis. As discussions deepened around clinical use cases associated with example prediction task set ups, the target problem evolved towards supporting the upstream task of organizational planning and advocacy for adequate mental health care service capacity to meet incoming needs. Conclusions: This case study contributes towards a tool to support diabetes and mental health care, as well as lays groundwork for future CHC decision support tool initiatives. We share lessons learned and reflections from our process that other primary health care organizations may use to inform their own co-development initiatives

A precision experiment to investigate long-lived radioactive decays

Radioactivity is understood to be described by a Poisson process, yet some measurements of nuclear decays appear to exhibit unexpected variations. Generally, the isotopes reporting these variations have long half lives, which are plagued by large measurement uncertainties. In addition to these inherent problems, there are some reports of time-dependent decay rates and even claims of exotic neutrino-induced variations. We present a dedicated experiment for the stable long-term measurement of gamma emissions resulting from β decays, which will provide high-quality data and allow for the identification of potential systematic influences. Radioactive isotopes are monitored redundantly by thirty-two 76 mm × 76 mm NaI(Tl) detectors in four separate temperature-controlled setups across three continents. In each setup, the monitoring of environmental and operational conditions facilitates correlation studies. The deadtime-free performance of the data acquisition system is monitored by LED pulsers. Digitized photomultiplier waveforms of all events are recorded individually, enabling a study of time-dependent effects spanning microseconds to years, using both time-binned and unbinned analyses. We characterize the experiment's stability and show that the relevant systematics are accounted for, enabling precise measurements of effects at levels well below \order{-4}

Design and performance of the field cage for the XENONnT experiment

The precision in reconstructing events detected in a dual-phase time projection chamber depends on an homogeneous and well understood electric field within the liquid target. In the XENONnT TPC the field homogeneity is achieved through a double-array field cage, consisting of two nested arrays of field shaping rings connected by an easily accessible resistor chain. Rather than being connected to the gate electrode, the topmost field shaping ring is independently biased, adding a degree of freedom to tune the electric field during operation. Two-dimensional finite element simulations were used to optimize the field cage, as well as its operation. Simulation results were compared to 83mKr calibration data. This comparison indicates an accumulation of charge on the panels of the TPC which is constant over time, as no evolution of the reconstructed position distribution of events is observed. The simulated electric field was then used to correct the charge signal for the field dependence of the charge yield. This correction resolves the inconsistent measurement of the drift electron lifetime when using different calibrations sources and different field cage tuning voltages