Particle theory

Abstract:

We present a calculation of the bosonic contribution to the two-loop mixed QCD-electroweak scattering amplitudes for Z-boson production in association with one hard jet at hadron colliders. We employ a method to calculate amplitudes in the ’t Hooft-Veltman scheme that reduces the amount of spurious non-physical information needed at intermediate stages of the computation, to keep the complexity of the calculation under control. We compute all the relevant Feynman integrals numerically using the Auxiliary Mass Flow method. We evaluate the two-loop scattering amplitudes on a two-dimensional grid in the rapidity and transverse momentum of the Z boson, which has been designed to yield a reliable numerical sampling of the boosted-Z region. This result provides an important building block for improving the theoretical modelling of a key background for monojet searches at the LHC.

Abstract:

The IceCube Neutrino Observatory relies on an array of photomultiplier tubes to detect Cherenkov light produced by charged particles in the South Pole ice. IceCube data analyses depend on an in-depth characterization of the glacial ice, and on novel approaches in event reconstruction that utilize fast approximations of photoelectron yields. Here, a more accurate model is derived for event reconstruction that better captures our current knowledge of ice optical properties. When evaluated on a Monte Carlo simulation set, the median angular resolution for in-ice particle showers improves by over a factor of three compared to a reconstruction based on a simplified model of the ice. The most substantial improvement is obtained when including effects of birefringence due to the polycrystalline structure of the ice. When evaluated on data classified as particle showers in the high-energy starting events sample, a significantly improved description of the events is observed.

Abstract:

Name that Neutrino is a citizen science project where volunteers aid in classification of events for the IceCube Neutrino Observatory, an immense particle detector at the geographic South Pole. From March 2023 to September 2023, volunteers did classifications of videos produced from simulated data of both neutrino signal and background interactions. Name that Neutrino obtained more than 128,000 classifications by over 1800 registered volunteers that were compared to results obtained by a deep neural network machine-learning algorithm. Possible improvements for both Name that Neutrino and the deep neural network are discussed.

Abstract:

We determine several classes of smooth complex projective surfaces on which Zariski decomposition can be combined with vanishing theorems to yield cohomology formulae for all line bundles. The obtained formulae express cohomologies in terms of divisor class intersections, and are adapted to the decomposition of the effective cone into Zariski chambers. In particular, we show this occurs on generalised del Pezzo surfaces, toric surfaces, and K3 surfaces. In the second part we use these surface results to derive formulae for all line bundle cohomology on a simple class of elliptically fibered Calabi–Yau three-folds. Computing such quantities is a crucial step in deriving the massless spectrum in string compactifications.