Image de couverture de livre

MoreFit: A More Optimised, Rapid and Efficient Fit

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Langenbruch, Christoph
Format:	Preprint
Publié:	2025
Sujets:	Data Analysis, Statistics and Probability High Energy Physics - Experiment
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

VecAmpFit: vectorized amplitude-analysis fitting library
par: Chilikin, K.
Publié: (2026)

Machine-Learning-Based Method for Goodness-of-Fit Test in Amplitude Analysis
par: Hou, Huoyi, et autres
Publié: (2025)

Construction of the Global $χ^2$ Function for the Simultaneous Fitting of Correlated Energy-Dependent Cross Sections
par: Shao, Linquan, et autres
Publié: (2026)

Jet Tagging with More-Interaction Particle Transformer
par: Wu, Yifan, et autres
Publié: (2024)

SymbolFit: Automatic Parametric Modeling with Symbolic Regression
par: Tsoi, Ho Fung, et autres
Publié: (2024)

A General Track Fit based on Triplets
par: Schöning, Andre
Publié: (2024)

PhyLiNO: A Forward-Folding Likelihood-Fit Framework for Neutrino Oscillation Physics
par: Hellwig, Denise, et autres
Publié: (2025)

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

Large-Scale Pretraining and Finetuning for Efficient Jet Classification in Particle Physics
par: Zhao, Zihan, et autres
Publié: (2024)

Global Optimisation of Black-Box Functions with Generative Models in the Wasserstein Space
par: Ramazyan, Tigran, et autres
Publié: (2024)

A lightweight analysis farm for fundamental physics experiments
par: Brommer, Sebastian, et autres
Publié: (2025)

A simple tool for weighted averaging of inconsistent data sets
par: Trassinelli, Martino, et autres
Publié: (2024)

SwdFold:A Reweighting and Unfolding method based on Optimal Transport Theory
par: Pan, Chu-Cheng, et autres
Publié: (2024)

A unified machine learning approach for reconstructing hadronically decaying tau leptons
par: Tani, Laurits, et autres
Publié: (2024)

A Statistical Method for Improving Momentum Measurement of Photon Conversions Reconstructed from Single Electrons
par: Bingül, Ahmet, et autres
Publié: (2024)

FunTuple: A new N-tuple component for offline data processing at the LHCb experiment
par: Mathad, Abhijit, et autres
Publié: (2023)

Machine Learning in High Energy Physics: A review of heavy-flavor jet tagging at the LHC
par: Mondal, Spandan, et autres
Publié: (2024)

Monte Carlo method for constructing confidence intervals with unconstrained and constrained nuisance parameters in the NOvA experiment
par: Acero, M. A., et autres
Publié: (2022)

Cosmic-ray tomography of shipping containers: A combination of complementary secondary particle and muon information using simulations
par: Prada, Maximilian Pérez, et autres
Publié: (2025)

Gradient-descent-based reconstruction for muon tomography based on automatic differentiation in PyTorch
par: Alameddine, Jean-Marco, et autres
Publié: (2025)

Uncertainty Quantification and Propagation for ACORN, a geometric deep learning tracking pipeline for HEP experiments
par: Péron, Lukas, et autres
Publié: (2025)

Systematic Uncertainties in Unfolding Considering the Likelihood Formalism
par: Brenner, Lydia, et autres
Publié: (2025)

Wasserstein normalized autoencoder for anomaly detection
par: CMS Collaboration
Publié: (2025)

Learning Selection Cuts With Gradients
par: Hance, Mike, et autres
Publié: (2025)

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

Harnessing Hardware Acceleration in High-Energy Physics through High-Level Synthesis Techniques
par: López, Pelayo Leguina, et autres
Publié: (2025)

Robust resonant anomaly detection with NPLM
par: Grosso, Gaia, et autres
Publié: (2025)

Graph-based Full Event Interpretation: a graph neural network for event reconstruction in Belle II
par: Abumusabh, Merna, et autres
Publié: (2025)

The Elastic Analysis Facility's (EAF's) Contribution to the Future of Analysis at Multi-Experiment Institutions and Future Colliders
par: Chavez, Elise, et autres
Publié: (2025)

Unbinned Inference with Correlated Events
par: Desai, Krish, et autres
Publié: (2025)

The High W Challenge: Robust Neutrino Energy Estimators for LArTPCs
par: Thorpe, Christopher, et autres
Publié: (2025)

Improved Asymptotic Formulae for Statistical Interpretation Based on Likelihood Ratio Tests
par: Xia, Li-Gang, et autres
Publié: (2021)

Exotic and physics-informed support vector machines for high energy physics
par: Ramirez-Morales, A., et autres
Publié: (2024)

Under-coverage in high-statistics counting experiments with finite MC samples
par: Alexe, Cristina-Andreea, et autres
Publié: (2024)

Learning the Standard Model Manifold: Bayesian Latent Diffusion for Collider Anomaly Detection
par: Patel, Jigar, et autres
Publié: (2026)

Normalizing Flows for Domain Adaptation when Identifying $Λ$ Hyperon Events
par: Kelleher, Rowan, et autres
Publié: (2024)

Run 3 performance and advances in heavy-flavor jet tagging in CMS
par: Sarkar, Uttiya
Publié: (2024)

RootInteractive tool for multidimensional statistical analysis, machine learning and analytical model validation
par: Ivanov, Marian, et autres
Publié: (2024)

Deep Probabilistic Direction Prediction in 3D with Applications to Directional Dark Matter Detectors
par: Ghrear, Majd, et autres
Publié: (2024)

Fast Posterior Probability Sampling with Normalizing Flows and Its Applicability in Bayesian analysis in Particle Physics
par: Baz, Mathias El, et autres
Publié: (2023)