Abstract: RADES (Relic Axion Detector Exploratory Setup) is a project with the goal of directly searching for axion dark matter above the 30 μeV scale employing custom-made microwave filters in magnetic dipole fields. Currently RADES is taking data at the LHC dipole of the CAST experiment. In the long term, the RADES cavities are envisioned to take data in the BabyIAXO magnet. In this article we report on the modelling, building and characterisation of an optimised microwave-filter design with alternating irises that exploits maximal coupling to axions while being scalable in length without suffering from mode-mixing. We develop the mathematical formalism and theoretical study which justifies the performance of the chosen design. We also point towards the applicability of this formalism to optimise the MADMAX dielectric haloscopes.

Abstract: A search for dark matter is conducted in final states containing a photon and missing transverse momentum in proton-proton collisions at root s = 13 TeV. The data, collected during 2015-2018 by the ATLAS experiment at the CERN LHC, correspond to an integrated luminosity of 139 fb(-1). No deviations from the predictions of the Standard Model are observed and 95% confidence-level upper limits between 2.45 fb and 0.5 fb are set on the visible cross section for contributions from physics beyond the Standard Model, in different ranges of the missing transverse momentum. The results are interpreted as 95% confidence-level limits in models where weakly interacting dark-matter candidates are pair-produced via an s-channel axial-vector or vector mediator. Dark-matter candidates with masses up to 415 (580) GeV are excluded for axial-vector (vector) mediators, while the maximum excluded mass of the mediator is 1460 (1470) GeV. In addition, the results are expressed in terms of 95% confidence-level limits on the parameters of a model with an axion-like particle produced in association with a photon, and are used to constrain the coupling g(aZ gamma) of an axion-like particle to the electroweak gauge bosons.

Abstract: Next-generation neutrinoless double beta decay experiments aim for half-life sensitivities of similar to 10(27) yr, requiring suppressing backgrounds to < 1 count/tonne/yr. For this, any extra background rejection handle, beyond excellent energy resolution and the use of extremely radiopure materials, is of utmost importance. The NEXT experiment exploits differences in the spatial ionization patterns of double beta decay and single-electron events to discriminate signal from background. While the former display two Bragg peak dense ionization regions at the opposite ends of the track, the latter typically have only one such feature. Thus, comparing the energies at the track extremes provides an additional rejection tool. The unique combination of the topology-based background discrimination and excellent energy resolution (1% FWHM at the Q-value of the decay) is the distinguishing feature of NEXT. Previous studies demonstrated a topological background rejection factor of <similar to> 5 when reconstructing electron-positron pairs in the Tl-208 1.6 MeV double escape peak (with Compton events as background), recorded in the NEXT-White demonstrator at the Laboratorio Subterraneo de Canfranc, with 72% signal efficiency. This was recently improved through the use of a deep convolutional neural network to yield a background rejection factor of similar to 10 with 65% signal efficiency. Here, we present a new reconstruction method, based on the Richardson-Lucy deconvolution algorithm, which allows reversing the blurring induced by electron diffusion and electroluminescence light production in the NEXT TPC. The new method yields highly refined 3D images of reconstructed events, and, as a result, significantly improves the topological background discrimination. When applied to real-data 1.6 MeV e(-)e(+) pairs, it leads to a background rejection factor of 27 at 57% signal efficiency.