Improved modeling of in-ice particle showers for IceCube event reconstruction

Journal of Instrumentation IOP Publishing 19:06 (2024) P06026

Authors:

R Abbasi, M Ackermann, J Adams, SK Agarwalla, JA Aguilar, M Ahlers, JM Alameddine, NM Amin, K Andeen, G Anton, C Argüelles, Y Ashida, S Athanasiadou, L Ausborm, SN Axani, X Bai, A Balagopal V., M Baricevic, SW Barwick, S Bash, V Basu, R Bay, JJ Beatty, J Becker Tjus

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.

Citizen science for IceCube: Name that Neutrino

European Physical Journal Plus Springer 139:6 (2024) 533

Authors:

R Abbasi, M Ackermann, J Adams, SK Agarwalla, JA Aguilar, M Ahlers, JM Alameddine, NM Amin, K Andeen, G Anton, C Argüelles, Y Ashida, S Athanasiadou, L Ausborm, SN Axani, X Bai, A Balagopal V., M Baricevic, SW Barwick, V Basu, R Bay, JJ Beatty, J Becker Tjus, J Beise

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.

Cohomology Chambers on Complex Surfaces and Elliptically Fibered Calabi–Yau Three-Folds

Communications in Mathematical Physics Springer 405:7 (2024) 151

Authors:

Callum R Brodie, Andrei Constantin

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.

Percolating Cosmic String Networks from Kination

ArXiv 2406.12637 (2024)

Authors:

Joseph P Conlon, Edmund J Copeland, Edward Hardy, Noelia Sánchez González

Electroweak phase transition with a double well done doubly well

Journal of High Energy Physics Springer 2024:6 (2024) 89

Authors:

Prateek Agrawal, Simone Blasi, Alberto Mariotti, Michael Nee

Abstract:

We revisit the electroweak phase transition in the scalar singlet extension of the standard model with a ℤ2 symmetry. In significant parts of the parameter space the phase transition occurs in two steps — including canonical benchmarks used in experimental projections for gravitational waves. Domain walls produced in the first step of the transition seed the final step to the electroweak vacuum, an effect which is typically neglected but leads to an exponentially enhanced tunnelling rate. We improve previous results obtained for the seeded transition, which made use of the thin-wall or high temperature approximations, by using the mountain pass algorithm that was recently proposed as a useful tool for seeded processes. We then determine the predictions of the seeded transition for the latent heat, bubble size and characteristic time scale of the transition. Differences compared to homogeneous transitions are most pronounced when there are relatively few domain walls per hubble patch, potentially leading to an enhanced gravitational wave signal. We also provide a derivation of the percolation criteria for a generic seeded transition, which applies to the domain wall seeds we consider as well as to strings and monopoles.