A robust uncertainty estimate in global analyses of Parton Distribution Functions (PDFs) is essential at the Large Hadron Collider (LHC), especially in view of the high-precision data anticipated by experimentalists in the High-Luminosity phase of the LHC. A Bayesian framework to determine PDFs provides a rigorous treatment of uncertainties and full control on the prior, though its practical implementation can be computationally demanding. To address these challenges, we introduce a novel approach to PDF determination tailored for Bayesian inference, based on the use of linear models. Unlike traditional parametrisations, our method represents PDFs as vectors in a functional space spanned by specially chosen bases, derived from the dimensional reduction of a neural network functional space, providing a compact yet versatile representation of PDFs. The low-dimensionality of the preferred models allows for particularly fast inference. The size of the bases can be systematically adjusted, allowing for transparent control over underfitting and overfitting, and facilitating principled model selection through Bayesian workflows. In this work, the methodology is applied to a fit of Deep Inelastic Scattering synthetic data, and thoroughly tested via multi-closure tests, thus paving the way to its application to global PDF fits.

United Kingdom

Mark Costantini

Spain

Luca Mantani

James Moore

Maria Ubiali

A linear PDF model for Bayesian inference

We present a systematic comparison of theoretical predictions and various high-precision experimental measurements, specifically of differential cross sections performed by the LHC run II for Drell-Yan gauge boson, top-quark pair, single-inclusive jet and di-jet production, and by HERA for single-inclusive jet and di-jet production. Theoretical predictions are computed at next-to-next-to-leading order (NNLO) accuracy in perturbative Quantum Chromodynamics. The most widely employed sets of Parton Distribution Functions (PDFs) are used, and PDF, strong coupling, and missing higher order uncertainties are taken into account. We quantitatively assess the predictive power of each PDF set and the contribution of the different sources of experimental and theoretical uncertainty to the agreement between data and predictions. We show that control over all of these aspects is crucial to precision physics studies, such as the determination of Standard Model parameters at the LHC.

Amedeo Chiefa

Switzerland

Juan Cruz-Martinez

Italy

Emanuele Nocera

Netherlands

Tanjona Rabemananjara

Juan Rojo

Tanishq Sharma

Roy Stegeman

Parton distributions confront LHC Run II data: a quantitative appraisal

We present a detailed mathematical study of the Monte Carlo replica method as applied in the global fitting literature from the high-energy physics theory community. For the first time, we provide a rigorous derivation of the parameter distributions implied by the method, and show that, whilst they agree with Bayesian posteriors for linear models, they disagree otherwise. We proceed to numerically quantify the disagreement between the Monte Carlo replica method and the Bayesian method in the context of two phenomenologically relevant scenarios: fits of the SMEFT Wilson coefficients, and fits of PDFs (albeit in a toy scenario). In both scenarios, we find that uncertainty estimates of the quantities of interest are discrepant between the two approaches when non-linearity is relevant. Our findings motivate future investigation of Bayesian methodologies for global PDF fits, especially in the context of simultaneous determination of PDFs and SMEFT Wilson coefficients.

Germany

Maeve Madigan

A critical study of the Monte Carlo replica method

We present the open-source SIMUnet code, designed to fit Standard Model Effective Field Theory (SMEFT) Wilson coefficient alongside Parton Distribution Functions (PDFs) of the proton. SIMUnet can perform SMEFT global fits, as well as simultaneous fits of the PDFs and of an arbitrarily large number of SMEFT degrees of freedom, by including both PDF-dependent and PDF-independent observables. SIMUnet can also be used to determine whether the effects of any New Physics models can be fitted away in a global fit of PDFs. SIMUnet is built upon the open-source NNPDF code and is released together with documentation, and tutorials. To illustrate the functionalities of the new tool, we present a new global analysis of the SMEFT Wilson coefficients accounting for their interplay with the PDFs. We increment our previous analysis of the LHC Run II top quark data with both (i) the Higgs production and decay rates data from the LHC, and (ii) the precision electroweak and diboson measurements from LEP and the LHC.

Elie Hammou

Zahari Kassabov

Manuel Morales-Alvarado

SIMUnet: an open-source tool for simultaneous global fits of EFT Wilson coefficients and PDFs

With an explicit example, we show that Jordan frame and the conformally transformed Einstein frames clearly lead to different physics for a non-minimally coupled theory of gravity, namely Brans–Dicke theory, at least at the quantum level. The example taken up is the spatially flat Friedmann cosmology in Brans–Dicke theory.