Cover Image

The High W Challenge: Robust Neutrino Energy Estimators for LArTPCs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Thorpe, Christopher, Gramellini, Elena
Format:	Preprint
Published:	2025
Subjects:	Data Analysis, Statistics and Probability High Energy Physics - Experiment
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Uncertainty Propagation within Chained Models for Machine Learning Reconstruction of Neutrino-LAr Interactions
by: Douglas, Daniel, et al.
Published: (2024)

LArTPC hit-based topology classification with quantum machine learning and symmetry
by: Duffy, Callum, et al.
Published: (2025)

Harnessing Hardware Acceleration in High-Energy Physics through High-Level Synthesis Techniques
by: López, Pelayo Leguina, et al.
Published: (2025)

Machine Learning in High Energy Physics: A review of heavy-flavor jet tagging at the LHC
by: Mondal, Spandan, et al.
Published: (2024)

Statistical Issues on the Neutrino Mass Hierarchy with $Δχ^{2}$
by: Sawy, Fatma, et al.
Published: (2023)

Robust resonant anomaly detection with NPLM
by: Grosso, Gaia, et al.
Published: (2025)

Impact of angle-dependent recombination on neutrino energy reconstruction in LArTPCs
by: Vences, J., et al.
Published: (2025)

Machine Learning-Assisted Unfolding for Neutrino Cross-section Measurements with the OmniFold Technique
by: Huang, Roger G., et al.
Published: (2025)

Log Gaussian Cox Process Background Modeling in High Energy Physics
by: Frid, Yuval, et al.
Published: (2025)

Optimization-based Unfolding in High-Energy Physics
by: Gasperini, Simone, et al.
Published: (2026)

PhyLiNO: A Forward-Folding Likelihood-Fit Framework for Neutrino Oscillation Physics
by: Hellwig, Denise, et al.
Published: (2025)

Construction of the Global $χ^2$ Function for the Simultaneous Fitting of Correlated Energy-Dependent Cross Sections
by: Shao, Linquan, et al.
Published: (2026)

Towards Universal Unfolding of Detector Effects in High-Energy Physics using Denoising Diffusion Probabilistic Models
by: Pazos, Camila, et al.
Published: (2024)

High Level Reconstruction with Deep Learning using ILD Full Simulation
by: Suehara, Taikan, et al.
Published: (2024)

Graph Neural Network for Neutrino Physics Event Reconstruction
by: Hewes, V, et al.
Published: (2024)

The Fast Stochastic Matching Pursuit for Neutrino and Dark Matter Experiments
by: Wang, Yuyi, et al.
Published: (2024)

Stabilizing Neural Likelihood Ratio Estimation
by: Acosta, Fernando Torales, et al.
Published: (2025)

Approximate Differentiable Likelihoods for Astroparticle Physics Experiments
by: Qin, Juehang, et al.
Published: (2024)

Variational Autoencoders for At-Source Data Reduction and Anomaly Detection in High Energy Particle Detectors
by: Yue, Alexander, et al.
Published: (2024)

Statistical divergences in high-dimensional hypothesis testing and a modern technique for estimating them
by: Wilkinson, Jeremy J. H., et al.
Published: (2024)

TrackSorter: A Transformer-based sorting algorithm for track finding in High Energy Physics
by: Melkani, Yash, et al.
Published: (2024)

Bring the noise: exact inference from noisy simulations in collider physics
by: Chang, Christopher, et al.
Published: (2025)

Cross-Domain Transfer with Particle Physics Foundation Models: From Jets to Neutrino Interactions
by: Krzmanc, Gregor, et al.
Published: (2026)

GollumFit: An IceCube Open-Source Framework for Binned-Likelihood Neutrino Telescope Analyses
by: IceCube Collaboration
Published: (2025)

Gradient-descent-based reconstruction for muon tomography based on automatic differentiation in PyTorch
by: Alameddine, Jean-Marco, et al.
Published: (2025)

Uncertainty Quantification and Propagation for ACORN, a geometric deep learning tracking pipeline for HEP experiments
by: Péron, Lukas, et al.
Published: (2025)

Systematic Uncertainties in Unfolding Considering the Likelihood Formalism
by: Brenner, Lydia, et al.
Published: (2025)

Cosmic-ray tomography of shipping containers: A combination of complementary secondary particle and muon information using simulations
by: Prada, Maximilian Pérez, et al.
Published: (2025)

Wasserstein normalized autoencoder for anomaly detection
by: CMS Collaboration
Published: (2025)

A lightweight analysis farm for fundamental physics experiments
by: Brommer, Sebastian, et al.
Published: (2025)

Learning Selection Cuts With Gradients
by: Hance, Mike, et al.
Published: (2025)

MoreFit: A More Optimised, Rapid and Efficient Fit
by: Langenbruch, Christoph
Published: (2025)

Review of Machine Learning for Real-Time Analysis at the Large Hadron Collider experiments ALICE, ATLAS, CMS and LHCb
by: Boggia, Laura, et al.
Published: (2025)

Machine-Learning-Based Method for Goodness-of-Fit Test in Amplitude Analysis
by: Hou, Huoyi, et al.
Published: (2025)

Graph-based Full Event Interpretation: a graph neural network for event reconstruction in Belle II
by: Abumusabh, Merna, et al.
Published: (2025)

The Elastic Analysis Facility's (EAF's) Contribution to the Future of Analysis at Multi-Experiment Institutions and Future Colliders
by: Chavez, Elise, et al.
Published: (2025)

Unbinned Inference with Correlated Events
by: Desai, Krish, et al.
Published: (2025)

Improved Asymptotic Formulae for Statistical Interpretation Based on Likelihood Ratio Tests
by: Xia, Li-Gang, et al.
Published: (2021)

Exotic and physics-informed support vector machines for high energy physics
by: Ramirez-Morales, A., et al.
Published: (2024)

Under-coverage in high-statistics counting experiments with finite MC samples
by: Alexe, Cristina-Andreea, et al.
Published: (2024)