activity
20242026
collaborators

8 papers

astro-ph.CO2026

Measurement of the Hubble constant with high-energy neutrinos

Gonzalo Herrera, Nicholas Kamp, Carlos A. Argüelles

Measuring distances in the Universe is one of the hardest problems in physics and astronomy. Almost every distance probe relies on photons, whose propagation across cosmic distance…

hep-ph2026

Astrophysical Neutrino Sources as Colliders

Carlos A. Argüelles, P. S. Bhupal Dev, Bhaskar Dutta +6

High-energy neutrinos arise from processes at large center-of-mass energies, offering a window to test physics at comparable scales or beyond those accessible in collider experimen…

physics.ins-det2026

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)

Julia Gonski, Jenni Ott, Shiva Abbaszadeh +118

The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environmen…

hep-ex2026

Lake- and Surface-Based Detectors for Forward Neutrino Physics

Nicholas W. Kamp, Carlos A. Argüelles, Albrecht Karle +2

We propose two medium-baseline, kiloton-scale neutrino experiments to study neutrinos from LHC proton-proton collisions: SINE, a surface-based scintillator panel detector observing…

hep-ex2026

Reducing Simulation Dependence in Neutrino Telescopes with Masked Point Transformers

Felix J. Yu, Nicholas Kamp, Carlos A. Argüelles

Machine learning techniques in neutrino physics have traditionally relied on simulated data, which provides access to ground-truth labels. However, the accuracy of these simulation…

physics.data-an2025

Learning Efficient Representations of Neutrino Telescope Events

Felix J. Yu, Nicholas Kamp, Carlos A. Argüelles

Neutrino telescopes detect rare interactions of particles produced in some of the most extreme environments in the Universe. This is accomplished by instrumenting a cubic-kilometer…