Coloma, P., Hernandez, P., & Urrea, S. (2022). New bounds on axion-like particles from MicroBooNE. J. High Energy Phys., 08(8), 025–25pp.
Abstract: Neutrino experiments lie at the edge of the intensity frontier and therefore can be exploited to search for new light particles weakly coupled to the visible sector. In this work we derive new constraints on axion-like particles (ALPs) using data from the MicroBooNE experiment, from a search for e(+)e(-) pairs pointing in the direction of the NuMI absorber. In particular, we consider the addition of higher-dimensional effective operators coupling the ALP to the electroweak gauge bosons. These would induce K -> pi a from kaon decay at rest in the NuMI absorber, as well as ALP decays into pairs of leptons or photons. We discuss in detail and compare various results obtained for the decay width K -> pi a in previous literature. For the operator involving the Higgs, MicroBooNE already sets competitive bounds (comparable to those of NA62) for ALP masses between 100 and 200 MeV. We also compute the expected sensitivities from the full NuMI dataset recorded at MicroBooNE. Our results show that a search for a -> gamma gamma signal may be able to improve over current constraints from beam-dump experiments on the operator involving the ALP coupling to the W.
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ATLAS Collaboration(Aad, G. et al), Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Cabrera Urban, S., Cardillo, F., et al. (2022). A search for an unexpected asymmetry in the production of e(+)mu(-) and e(-)mu(+) pairs in proton-proton collisions recorded by the ATLAS detector at root s=13 TeV. Phys. Lett. B, 830, 137106–22pp.
Abstract: This search, a type not previously performed at ATLAS, uses a comparison of the production cross sections for e(+)mu(-) and e(-)mu(+) pairs to constrain physics processes beyond the Standard Model. It uses 139 fb(-1) of proton-proton collision data recorded at root s = 13 TeV at the LHC. Targeting sources of new physics which prefer final states containing e(+)mu(-) and e(-)mu(+), the search contains two broad signal regions which are used to provide model-independent constraints on the ratio of cross sections at the 2% level. The search also has two special selections targeting supersymmetric models and leptoquark signatures. Observations using one of these selections are able to exclude, at 95% confidence level, singly produced smuons with masses up to 640 GeV in a model in which the only other light sparticle is a neutralino when the R-parity-violating coupling lambda(23)(1)' is close to unity. Observations using the other selection exclude scalar leptoquarks with masses below 1880 GeV when g(1R)(eu) = g(1R)(mu c) = 1, at 95% confidence level. The limit on the coupling reduces to g(1R)(eu) = g(1R)(mu c) = 0.46 for a mass of 1420 GeV.
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Villanueva-Domingo, P., Villaescusa-Navarro, F., Angles-Alcazar, D., Genel, S., Marinacci, F., Spergel, D. N., et al. (2022). Inferring Halo Masses with Graph Neural Networks. Astrophys. J., 935(1), 30–15pp.
Abstract: Understanding the halo-galaxy connection is fundamental in order to improve our knowledge on the nature and properties of dark matter. In this work, we build a model that infers the mass of a halo given the positions, velocities, stellar masses, and radii of the galaxies it hosts. In order to capture information from correlations among galaxy properties and their phase space, we use Graph Neural Networks (GNNs), which are designed to work with irregular and sparse data. We train our models on galaxies from more than 2000 state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations project. Our model, which accounts for cosmological and astrophysical uncertainties, is able to constrain the masses of the halos with a similar to 0.2 dex accuracy. Furthermore, a GNN trained on a suite of simulations is able to preserve part of its accuracy when tested on simulations run with a different code that utilizes a distinct subgrid physics model, showing the robustness of our method. The PyTorch Geometric implementation of the GNN is publicly available on GitHub (https://github.com/PabloVD/HaloGraphNet).
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MoEDAL Collaboration(Acharya, B. et al), Musumeci, E., Mitsou, V. A., Papavassiliou, J., Ruiz de Austri, R., Santra, A., et al. (2022). Search for highly-ionizing particles in pp collisions at the LHC's Run-1 using the prototype MoEDAL detector. Eur. Phys. J. C, 82(8), 694–16pp.
Abstract: A search for highly electrically charged objects (HECOs) and magnetic monopoles is presented using 2.2 fb(-1) of p – p collision data taken at a centre of mass energy (E-CM) of 8 TeV by the MoEDAL detector during LHC's Run-1. The data were collected using MoEDAL's prototype Nuclear Track Detectord array and the Trapping Detector array. The results are interpreted in terms of Drell-Yan pair production of stable HECO and monopole pairs with three spin hypotheses (0, 1/2 and 1). The search provides constraints on the direct production of magnetic monopoles carrying one to four Dirac magnetic charges and with mass limits ranging from 590 GeV/c(2) to 1 TeV/c(2). Additionally, mass limits are placed on HECOs with charge in the range 10e to 180e, where e is the charge of an electron, for masses between 30 GeV/c(2) and 1 TeV/c(2).
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Baru, V., Dong, X. K., Du, M. L., Filin, A., Guo, F. K., Hanhart, C., et al. (2022). Effective range expansion for narrow near-threshold resonances. Phys. Lett. B, 833, 137290–7pp.
Abstract: We discuss some general features of the effective range expansion, the content of its parameters with respect to the nature of the pertinent near-threshold states and the necessary modifications in the presence of coupled channels, isospin violations and unstable constituents. As illustrative examples, we analyse the properties of the chi(c1)(3872) and T-cc(+) states supporting the claim that these exotic states have a predominantly molecular nature.
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