collaborators

7 papers

astro-ph.HE2026

Constraining gamma-ray burst parameters with the first ultra-high energy neutrino event KM3-230213A

KM3NeT Collaboration, O. Adriani, A. Albert +278

Context: The detection of the highest energy neutrino observed to date by KM3NeT, with an estimated energy of 220 PeV, opens up new possibilities for the study and identification o…

astro-ph.HE2026

Discovery of 30 Repeating Fast Radio Burst Sources and Uniform Population Statistics of 80 Repeating Sources from CHIME/FRB

Amanda M. Cook, Kaitlyn Shin, Ziggy Pleunis +44

We present 30 newly discovered repeating fast radio burst (FRB) sources from the second catalog of bursts detected by the FRB backend on the Canadian Hydrogen Intensity Mapping Exp…

physics.optics2026

Linking extended vector wave fields with momentum space topology

A. Neuhaus, P. Gessler, P. Dreher +10

Topology describes properties of physical systems that remain constant under continuous deformations. For infinite vector waves, global topological invariants in position space are…

math.OC2026

Handling Overtime Constraints in Mixed Integer Linear Programming for Surgical Scheduling: A Comparison of Neural Network and Classical Linearization Techniques

Cindy Pistorius, J. Theresia van Essen

Uncertainty in surgery durations continues to be difficult to account for in operating room scheduling. In particular, it remains complex to accurately incorporate uncertainty in s…

astro-ph.HE2026

Optimizing the potential of KM3NeT in detecting core-collapse supernovae

KM3NeT Collaboration, O. Adriani, A. Albert +285

Core-collapse supernovae mark the end of life of massive stars. However, despite their importance in astrophysics, their underlying mechanisms remain unclear. Neutrinos that emerge…

q-fin.CP2025

Controllable Generation of Implied Volatility Surfaces with Variational Autoencoders

Jing Wang, Shuaiqiang Liu, Cornelis Vuik

This paper presents a deep generative modeling framework for controllably synthesizing implied volatility surfaces (IVSs) using a variational autoencoder (VAE). Unlike conventional…