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Neutron-induced nuclear reactions play an important role in the Big Bang Nucleosynthesis. Their excitation functions are, from an experimental point of view, usually difficult to measure. Nevertheless, in the last decades, big efforts have led to a better understanding of their role in the primordial nucleosynthesis network. In this work, we apply the Trojan Horse Method to extract the cross section at astrophysical energies for the³He(n,p)³H reaction after a detailed study of the²H(³He,pt)H three-body process. Data extracted from the present measurement are compared with other published sets. The reaction rate is also calculated, and the impact on the Big Bang nucleosynthesis is examined in detail.

This paper details the first application of a software tagging algorithm to reduce radon-induced backgrounds in liquid noble element time projection chambers, such as XENON1T and XENONnT. The convection velocity field in XENON1T was mapped out using${}^{222}\mathrm{Rn}$and${}^{218}\mathrm{Po}$events, and the rms convection speed was measured to be$0.30\pm 0.01\mathrm{cm}/\mathrm{s}$. Given this velocity field,${}^{214}\mathrm{Pb}$background events can be tagged when they are followed by${}^{214}\mathrm{Bi}$and${}^{214}\mathrm{Po}$decays, or preceded by${}^{218}\mathrm{Po}$decays. This was achieved by evolving a point cloud in the direction of a measured convection velocity field, and searching for${}^{214}\mathrm{Bi}$and${}^{214}\mathrm{Po}$decays or${}^{218}\mathrm{Po}$decays within a volume defined by the point cloud. In XENON1T, this tagging system achieved a${}^{214}\mathrm{Pb}$background reduction of${6.2}_{-0.9}^{+0.4}\%$with an exposure loss of$1.8\pm 0.2\%$, despite the timescales of convection being smaller than the relevant decay times. We show that the performance can be improved in XENONnT, and that the performance of such a software-tagging approach can be expected to be further improved in a diffusion-limited scenario. Finally, a similar method might be useful to tag the cosmogenic${}^{137}\mathrm{Xe}$background, which is relevant to the search for neutrinoless double-beta decay.

In this work, we expand on the XENON1T nuclear recoil searches to study the individual signals of dark matter interactions from operators up to dimension eight in a chiral effective field theory (ChEFT) and a model of inelastic dark matter (iDM). We analyze data from two science runs of the XENON1T detector totaling$1\mathrm{t}\times \mathrm{yr}$exposure. For these analyses, we extended the region of interest from$[4.9,40.9]{\mathrm{keV}}_{\mathrm{NR}}$to$[4.9,54.4]{\mathrm{keV}}_{\mathrm{NR}}$to enhance our sensitivity for signals that peak at nonzero energies. We show that the data are consistent with the background-only hypothesis, with a small background overfluctuation observed peaking between 20 and$50{\mathrm{keV}}_{\mathrm{NR}}$, resulting in a maximum local discovery significance of$1.7\sigma$for the$\mathrm{Vector}\otimes {\text{Vector}}_{\text{strange}}$ChEFT channel for a dark matter particle of$70\mathrm{GeV}/c^2$and$1.8\sigma$for an iDM particle of$50\mathrm{GeV}/c^2$with a mass splitting of$100\mathrm{keV}/c^2$. For each model, we report 90% confidence level upper limits. We also report upper limits on three benchmark models of dark matter interaction using ChEFT where we investigate the effect of isospin-breaking interactions. We observe rate-driven cancellations in regions of the isospin-breaking couplings, leading to up to 6 orders of magnitude weaker upper limits with respect to the isospin-conserving case.

The QCD axion is a particle postulated to exist since the 1970s to explain the strong-CP problem in particle physics. It could also account for all of the observed dark matter in the Universe. The axion resonant interaction detection experiment (ARIADNE) intends to detect the QCD axion by sensing the fictitious ‘magnetic field’ created by its coupling to spin. Short-range axion-mediated interactions can occur between a sample of laser-polarized³He nuclear spins and an unpolarized source-mass sprocket. The experiment must be sensitive to magnetic fields below the 10⁻¹⁹T level to achieve its design sensitivity, necessitating tight control of the experiment’s magnetic environment. We describe a method for controlling three aspects of that environment which would otherwise limit the experimental sensitivity. Firstly, a system of superconducting magnetic shielding is described to screen ordinary magnetic noise from the sample volume at the 10⁸level, which should be sufficient to reduce the contribution of Johnson noise in the sprocket-shaped source mass, expected to be at the 10⁻¹²T$/\sqrt{\mathrm{H}\mathrm{z}}$level, to below the threshold for signal detection. Secondly, a method for reducing magnetic field gradients within the sample up to 10²times is described, using a simple and cost-effective design geometry. Thirdly, a novel coil design is introduced which allows the generation of fields similar to those produced by Helmholtz coils in regions directly abutting superconducting boundaries. This method allows the nuclear Larmor frequency of the sample to be tuned to match the axion field modulation frequency set by the sprocket rotation. Finally, we experimentally investigate the magnetic shielding factor of sputtered thin-film superconducting niobium on quartz substrates for various geometries and film thicknesses relevant for the ARIADNE axion experiment using SQUID magnetometry. The methods may be generally useful for magnetic field control near superconducting boundaries in other experiments where similar considerations apply.

Methods commonly used to estimate net primary production (NPP) from satellite observations are now being applied to biogeochemical (BGC) profiling float observations. Insights can be gained from regional differences in float and satellite NPP estimates that reveal gaps in our understanding and guide future NPP model development. We use 7 years of BGC profiling float data from the Northeast Pacific Ocean to quantify discrepancies between float and satellite NPP estimates and decompose them into contributions associated with the platform sensing method and depth resolution of observations. We find small, systematic seasonal discrepancies in the depth‐integrated NPP (iNPP) but much larger (>±100%) discrepancies in depth‐resolved NPP. Annual iNPP estimates from the two platforms are significantly, positively correlated, suggesting that they similarly track interannual variability in the study region. Using the long‐term satellite iNPP record, we identify elevated annual iNPP during two recent marine heatwaves and gain insights about ecosystem functionality.