Journal Article

A tau lepton identification algorithm, DeepTau, based on convolutional neural network techniques, has been developed in the CMS experiment to discriminate reconstructed hadronic decays of tau leptons ($τ_\mathrm{h}$) from quark or gluon jets and electrons and muons that are misreconstructed as $τ_\mathrm{h}$ candidates. The latest version of this algorithm, v2.5, includes domain adaptation by backpropagation, a technique that reduces discrepancies between collision data and simulation in the region with the highest purity of genuine $τ_\mathrm{h}$ candidates. [...]

Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies. Low-energy interactions are needed to reconstruct the energies of astrophysical neutrinos from supernovae bursts and search for new physics using increasingly precise measurement of coherent elastic neutrino scattering. [...]

The ATLAS experiment at the Large Hadron Collider explores the use of modern neural networks for a multi-dimensional calibration of its calorimeter signal defined by clusters of topologically connected cells (topo-clusters). The Bayesian neural network (BNN) approach not only yields a continuous and smooth calibration function that improves performance relative to the standard calibration but also provides uncertainties on the calibrated energies for each topo-cluster. [...]

The Swampland cobordism conjecture [.] predicts various new objects in a theory with dynamical gravity. Applying this idea to the Standard Model of particle physics, a string object is predicted. [...]

Domain wall (DW) networks may have formed in the early Universe following the spontaneous breaking of a discrete symmetry. Notably, several particle physics models predict the existence of current-carrying DWs, which can capture and store particles as zero modes on it. [...]

Cosmological phase transitionscan give rise to intriguing phenomena, such as baryogenesis or a stochastic gravitational wave background, due to nucleation and percolation of vacuum bubbles in the primordial plasma. A key parameter for predicting these relics is the bubble wall velocity, whose computation relies onsolving the Boltzmann equations of the various speciesalong the bubble profile. [...]

We compute the non-Gaussian corrections to the energy density and anisotropies ofgravitational waves induced during the radiation era after an ultra-slow-roll phase of inflationby using a diagrammatic approach, and present the corresponding Feynman rules. Our two-loopcalculation includes both the intrinsic non-Gaussianity of the inflaton perturbation δϕ and the non-Gaussianity arising from the nonlinear relation between the latter and the curvatureperturbation ℛ, which we find to be subdominant with respect to the former. [...]

The induced conservative tidal response of self-gravitating objects in general relativity is parametrized in terms of a set of coefficients, which are commonly referred to as Love numbers. For asymptotically-flat black holes in four spacetime dimensions, the Love numbers are famously zero in the static regime. [...]

Axion-like particles, which we call axions, can compose the missing dark matter and mayform substructures such as miniclusters and axion stars. We obtain the mass distributions ofaxion stars derived from their host miniclusters in our galaxy and find a significant number ofaxion stars reaching the decay mass, the critical mass set by the axion-photon coupling.Axion stars that have reached the decay mass can accrete surrounding axions either via or directlyfrom their host miniclusters, subsequently converting them into radio photons through parametricresonance. [...]