hoppet v2 release note
The European Physical Journal C SpringerOpen 86:2 (2026) 157-157
Abstract:
We document the three main new features in the v2 release series of the hoppet parton distribution function evolution code, specifically support for N 3 LO QCD evolution in the variable flavour number scheme, for the determination of hadronic structure functions for massless quarks up to N 3 LO, and for QED evolution to an accuracy phenomenologically equivalent to NNLO QCD. Additionally we describe a new Python interface, CMake build option, functionality to save a hoppet table as an LHAPDF grid and update our performance benchmarks, including optimisations in interpolating PDF tables.Probing neutrino emission at GeV energies from compact binary mergers with the IceCube Neutrino Observatory
Physical Review D American Physical Society (APS) 113:4 (2026) 042003
Abstract:
The advent of multimessenger astronomy has allowed for new types of source searches by neutrino detectors. We present the results of the search for 0.5–100 GeV astrophysical neutrinos detected with IceCube and emitted from compact binary mergers detected by the LIGO, Virgo, and KAGRA interferometers from their first run of observation (O1) to the end of the first part of the fourth (O4a). An innovative approach is used to lower the energy threshold to 0.5 GeV and to search for an excess of GeV neutrinos in time coincidence with astrophysical transient events. Furthermore, we use a statistical combination of all observations, a binomial test, to search for a subpopulation of neutrino emitters. No significant excess was found from the studied mergers, with a best post-trial p-value of 40%, and there is currently no hint of a population of GeV neutrino emitters found in the IceCube data (post-trial p-value=81%).Reproducing Standard Model fermion masses and mixing in string theory: A heterotic line bundle study
Physical Review D American Physical Society (APS) 113:4 (2026) 046005
Abstract:
Deriving the Yukawa couplings and the resulting fermion masses and mixing angles of the Standard Model (SM) from a more fundamental theory remains one of the central outstanding problems in theoretical high-energy physics. It has long been recognized that string theory provides a framework within which this question can, at least in principle, be addressed. While substantial progress has been made in studying flavor physics in string compactifications over the past few decades, a concrete string construction that reproduces the full set of observed SM flavor parameters remains unknown. Here, we take a significant step in this direction by identifying two explicit heterotic string models compactified on a Calabi-Yau threefold with Abelian, holomorphic, and polystable vector bundles with minimal supersymmetric (MS) SM spectrum. Subject to reasonable assumptions about the moduli, we show that these models reproduce the correct values of the quark and charged lepton masses, as well as the quark mixing parameters, at some point in their moduli spaces. The resulting four-dimensional theories are supersymmetric, contain no exotic fields, and realize a -term suppressed to the electroweak scale. While the issues of moduli stabilization and supersymmetry breaking are not addressed here; our main result constitutes a proof of principle: There exist choices of topology and moduli within heterotic string compactifications which allow for an MSSM spectrum with the correct flavor parameters.Fast low energy reconstruction using Convolutional Neural Networks
Journal of Instrumentation IOP Publishing 21:02 (2026) P02020
Abstract:
IceCube is a Cherenkov detector instrumenting over a cubic kilometer of glacial ice deep under the surface of the South Pole. The DeepCore sub-detector lowers the detection energy threshold to a few GeV, enabling the precise measurements of neutrino oscillation parameters with atmospheric neutrinos. The reconstruction of neutrino interactions inside the detector is essential in studying neutrino oscillations. It is particularly challenging to reconstruct sub-100 GeV events with the IceCube detectors due to the relatively sparse detection units and detection medium. Convolutional neural networks (CNNs) are broadly used in physics experiments for both classification and regression purposes. This paper discusses the CNNs developed and employed for the latest IceCube-DeepCore oscillation measurements [1]. These CNNs estimate various properties of the detected neutrinos, such as their energy, direction of arrival, interaction vertex position, flavor-related signature, and are also used for background classification.Development of Superfluid Helium-3 Bolometry Using Nanowire Resonators with SQUID Readout for the QUEST-DMC Experiment
Journal of Low Temperature Physics Springer 222:2 (2026) 39