Cover Image

Gradient-descent-based reconstruction for muon tomography based on automatic differentiation in PyTorch

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Alameddine, Jean-Marco, Sattler, Felix, Stephan, Maurice, Barnes, Sarah
Format:	Preprint
Published:	2025
Subjects:	High Energy Physics - Experiment Data Analysis, Statistics and Probability
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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)

B2G4: A synthetic data pipeline for the integration of Blender models in Geant4 simulation toolkit
by: Rodriguez, Angel Bueno, et al.
Published: (2023)

Pty-Chi: A PyTorch-based modern ptychographic data analysis package
by: Du, Ming, et al.
Published: (2025)

Efficient factored gradient descent algorithm for quantum state tomography
by: Wang, Yong, et al.
Published: (2022)

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

Harnessing the potential of PyStoch: detecting continuous gravitational waves from interesting supernova remnant targets
by: Salvadore, Claudio, et al.
Published: (2025)

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

Multi-stage tomography based on eigenanalysis for high-dimensional dense unitary processes in gate-based quantum computers
by: Deville, Yannick, et al.
Published: (2024)

Photon Classification with Gradient Boosted Trees at CLAS12
by: Matousek, Gregory, et al.
Published: (2024)

A unified machine learning approach for reconstructing hadronically decaying tau leptons
by: Tani, Laurits, et al.
Published: (2024)

An implementation of neural simulation-based inference for parameter estimation in ATLAS
by: ATLAS Collaboration
Published: (2024)

Machine learning approaches for automatic cleaning of investigative drilling data
by: Huang, Fei, et al.
Published: (2025)

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

SwdFold:A Reweighting and Unfolding method based on Optimal Transport Theory
by: Pan, Chu-Cheng, et al.
Published: (2024)

Elephant random walks with graph based shared memory: First and second order asymptotics
by: Das, Deborshi
Published: (2024)

Clustering in atom probe tomography data: coordination number metric, percolation-based parameter scaling, and size effects
by: Lazarev, Mykola, et al.
Published: (2026)

Lepton energy scale and resolution corrections based on the minimization of an analytical likelihood: IJazZ2.0
by: Couderc, F., et al.
Published: (2026)

Sparse flow reconstruction methods to reduce the costs of analyzing large unsteady datasets
by: Stahl, Spencer L., et al.
Published: (2024)

Manifold-based transformation of probability distributions: application to the inverse problem of reconstructing distributions from experimental data
by: Oroguchi, Tomotaka, et al.
Published: (2024)

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

Physics-based linear regression for high-dimensional forward uncertainty quantification
by: Wang, Ziqi
Published: (2024)

Copula-based analytical results of horizontal visibility graphs for correlated time series
by: Lee, Jeong-Min, et al.
Published: (2025)

Model-based and empirical analyses of stochastic fluctuations in economy and finance
by: Zadourian, Rubina
Published: (2024)

Two measurement bases are asymptotically informationally complete for any pure state tomography
by: Feng, Tianfeng, et al.
Published: (2025)

A skeletonization based image segmentation algorithm to isolate slender regions in 3D microstructures
by: Deshpande, Vinit Vijay, et al.
Published: (2025)

High-dimensional maximum-entropy phase space tomography
by: Hoover, Austin
Published: (2025)

Texture tomography with high angular resolution utilizing sparsity
by: Carlsen, Mads, et al.
Published: (2024)

Exact closed-form recurrence probabilities for biased random walks at any step number
by: Mookerjee, Debendro, et al.
Published: (2024)

Closed-form survival probabilities for biased random walks at arbitrary step number
by: Mookerjee, Debendro, et al.
Published: (2025)

N-dimensional maximum-entropy tomography via particle sampling
by: Hoover, Austin
Published: (2024)

Comparative study of machine learning and statistical methods for automatic identification and quantification in γ-ray spectrometry
by: Phan, Dinh Triem, et al.
Published: (2025)

Graph Neural Network-based Tracking as a Service
by: Zhao, Haoran, et al.
Published: (2024)

Learning to bin: differentiable and Bayesian optimization for multi-dimensional discriminants in high-energy physics
by: Erdmann, Johannes, et al.
Published: (2026)

Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter
by: Aamir, M., et al.
Published: (2024)

Critical density for network reconstruction
by: Gabrielli, Andrea, et al.
Published: (2023)

CNN on `Top': In Search of Scalable & Lightweight Image-based Jet Taggers
by: Baruah, Rajneil, et al.
Published: (2025)

Classifier Surrogates: Sharing AI-based Searches with the World
by: Bieringer, Sebastian, et al.
Published: (2024)

Least Squares as Random Walks
by: Kostinski, Alexander, et al.
Published: (2025)

3D deep learning for enhanced atom probe tomography analysis of nanoscale microstructures
by: Yu, Jiwei, et al.
Published: (2024)

The Interplay of Machine Learning--based Resonant Anomaly Detection Methods
by: Golling, Tobias, et al.
Published: (2023)