Cover Image

Using Machine Learning to Improve PDF Uncertainties

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gombas, Jason P., Schwienhorst, Reinhard, Dong, Binbin, Fein, Jarrett
Format:	Preprint
Published:	2024
Subjects:	High Energy Physics - Phenomenology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Search for a Heavy-philic W' Boson using Proton-Proton Collisions at Center-of-Mass Energy of 13 TeV Using the ATLAS Detector
by: Gombas, Jason Peter
Published: (2025)

Quantitative Understanding of PDF Fits and their Uncertainties
by: Chiefa, Amedeo, et al.
Published: (2025)

Higgs Signal Strength Estimation with Machine Learning under Systematic Uncertainties
by: He, Minxuan, et al.
Published: (2025)

Improving Neutrino Energy Reconstruction with Machine Learning
by: Kopp, Joachim, et al.
Published: (2024)

Alien operators for PDF evolution
by: Van Thurenhout, S., et al.
Published: (2025)

Further Reduction of the PDF Uncertainty in the High-Mass Drell-Yan Spectrum Utilizing Neutral and Charged Current Inputs
by: Fu, Yao, et al.
Published: (2025)

Deep Inelastic Scattering Cross Section Uncertainties in Tau Neutrino Appearance Measurements
by: Kozynets, Tetiana, et al.
Published: (2024)

A linear PDF model for Bayesian inference
by: Costantini, Mark N., et al.
Published: (2025)

Improving the Direct Determination of $|V_{ts}|$ using Deep Learning
by: Heo, Jeewon, et al.
Published: (2025)

Precision phenomenology of the PDF-BSM interplay
by: Alvarado, Manuel Morales
Published: (2025)

The impact of inclusive electron ion collider data on the strong coupling determination in a global PDF fit
by: Harland-Lang, L. A., et al.
Published: (2025)

A study of systematic uncertainties within the MSHT PDF Framework
by: Reader, Matthew
Published: (2024)

Testing a 95 GeV Scalar at the CEPC with Machine Learning
by: Dong, Yabo, et al.
Published: (2025)

QED-enhanced PDF implications for the Higgs sector
by: Cooper-Sarkar, Amanda M., et al.
Published: (2025)

PDF at small $x$ in the non-perturbative region
by: Nekrasov, M. L.
Published: (2026)

First Nucleon Gluon PDF from Large Momentum Effective Theory
by: Good, William, et al.
Published: (2025)

A Determination of the Top Mass from a Global PDF Analysis
by: Ball, Richard D., et al.
Published: (2026)

On the dependence of the Landau gauge ghost-gluon-vertex on the number of flavors
by: Zierler, Fabian, et al.
Published: (2023)

Global Analyses of Generalized Parton Distributions with Diverse PDF Inputs
by: The MMGPDs Collaboration, et al.
Published: (2026)

Resummation phenomenology and PDF determination for precision QCD at the LHC
by: Silvetti, Federico
Published: (2024)

On the impact of the mixed $Z/ γ$ PDF at muon colliders
by: Marzocca, David, et al.
Published: (2024)

Parametrization sampling and the pion PDF in a phenomenological analysis
by: Courtoy, Aurore
Published: (2024)

Evaluating the faithfulness of PDF uncertainties in the presence of inconsistent data
by: Barontini, Andrea, et al.
Published: (2025)

Low-energy theory of jet processes and PDF factorization
by: Becher, Thomas, et al.
Published: (2025)

Renormalon effect of quasi-PDF in gradient flow formalism
by: Zhang, Jia-lu
Published: (2025)

Extractions of the strong coupling from collider data without PDF refitting are biased
by: Forte, Stefano, et al.
Published: (2025)

The impact of LHC precision measurements of inclusive jet and dijet production on the CTEQ-TEA global PDF fit
by: Ablat, Alim, et al.
Published: (2024)

Exact NNLO corrections vs K-factors in PDF fits
by: Sharma, Tanishq
Published: (2024)

Determination of proton PDF uncertainties with Markov chain Monte Carlo
by: Risse, Peter, et al.
Published: (2025)

Colibri: A new tool for fast-flying PDF fits
by: Costantini, Mark N., et al.
Published: (2025)

Top-philic Machine Learning
by: Barman, Rahool Kumar, et al.
Published: (2024)

Machine Learning Electroweakino Production
by: Masełek, Rafał, et al.
Published: (2024)

Machine Learning in the 2HDM2S model for Dark Matter
by: Boto, Rafael, et al.
Published: (2025)

NeoPDF: A fast interpolation library for collinear and transverse momentum-dependent parton distributions
by: Rabemananjara, Tanjona R.
Published: (2025)

A parton shower consistent with parton densities at LO and NLO: PDF2ISR
by: Jung, H., et al.
Published: (2025)

Machine Learning Techniques for Intermediate Mass Gap Lepton Partner Searches at the Large Hadron Collider
by: Dutta, Bhaskar, et al.
Published: (2023)

A Markov Chain Monte Carlo determination of Proton PDF uncertainties at NNLO
by: Risse, Peter, et al.
Published: (2024)

A reassessment of the role of high $x$ data on the MSHT global PDF fit
by: Harland-Lang, L. A., et al.
Published: (2025)

Analysis of HERA data with a PDF parametrization inspired by quantum statistical mechanics
by: Bonvini, Marco, et al.
Published: (2023)

Unraveling Dirac Magnetic Monopoles with Muon Beams at TeV Energies Using Machine Learning
by: Javaid, M. Tayyab, et al.
Published: (2026)