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The formation of a series of isostructural three-component co-crystals between 1,2,4,5-tetrachloro-3-iodobenzene and each of three isosteric bipyridines is reported.

 

Abstract Neutrinos are one of the most promising messengers for signals of new physics Beyond the Standard Model (BSM). On the theoretical side, their elusive nature, combined with their unknown mass mechanism, seems to indicate that the neutrino sector is indeed opening a window to new physics. On the experimental side, several long-standing anomalies have been reported in the past decades, providing a strong motivation to thoroughly test the standard three-neutrino oscillation paradigm. In this Snowmass21 white paper, we explore the potential of current and future neutrino experiments to explore BSM effects on neutrino flavor during the next decade. 

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.

Published by the American Physical Society2024 

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.

Published by the American Physical Society2024 

We present a first search for dark-trident scattering in a neutrino beam using a dataset corresponding to$7.2\times {10}^{20}$protons on target taken with the MicroBooNE detector at Fermilab. Proton interactions in the neutrino target at the main injector produce${\pi }^0$and$\eta$mesons, which could decay into dark-matter (DM) particles mediated via a dark photon$A^{\prime }$. A convolutional neural network is trained to identify interactions of the DM particles in the liquid-argon time projection chamber (LArTPC) exploiting its imagelike reconstruction capability. In the absence of a DM signal, we provide limits at the 90% confidence level on the squared kinematic mixing parameter${ϵ}^2$as a function of the dark-photon mass in the range$10\le M_{A^{\prime }}\le 400\mathrm{MeV}$. The limits cover previously unconstrained parameter space for the production of fermion or scalar DM particles$\chi$for two benchmark models with mass ratios$M_{\chi }/M_{A^{\prime }}=0.6$and 2 and for dark fine-structure constants$0.1\le {\alpha }_D\le 1$.

Published by the American Physical Society2024