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Researcher profile

Maria Ubiali

Maria Ubiali contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
hep-phhep-exastro-ph.COastro-ph.GAMachine Learning

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Published work

8 published item(s)

preprint2026arXiv

Uncertainty in Physics and AI: Taxonomy, Quantification, and Validation

Reliable uncertainty quantification is essential for the use of machine learning in physics, where scientific discoveries depend on validated probabilistic statements. We provide a structured overview of uncertainty quantification in ML for physics, introducing a unified taxonomy of uncertainty and clarifying the interpretation of predictive and inference uncertainties across frequentist and Bayesian frameworks. We discuss principled validation tools, including coverage, calibration, bias tests, and proper scoring rules, and illustrate them with simple regression and classification examples.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

A new generation of simultaneous fits to LHC data using deep learning

We present a new methodology that is able to yield a simultaneous determination of the Parton Distribution Functions (PDFs) of the proton alongside any set of parameters that determine the theory predictions; whether within the Standard Model (SM) or beyond it. The SIMUnet methodology is based on an extension of the NNPDF4.0 neural network architecture, which allows the addition of an extra layer to simultaneously determine PDFs alongside an arbitrary number of such parameters. We illustrate its capabilities by simultaneously fitting PDFs with a subset of Wilson coefficients within the Standard Model Effective Field Theory framework and show how the methodology extends naturally to larger subsets of Wilson coefficients and to other SM precision parameters, such as the strong coupling constant or the heavy quark masses.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

The dark side of the proton

We study the sensitivity of the High-Luminosity LHC to a light baryonic dark photon B, primarily coupled to quarks, as a constituent of the proton. This is achieved by allowing for a dark photon parton distribution function (PDF) in the PDF evolution equations. Depending on the mass and coupling of the dark photon, the evolution of standard quark and gluon PDFs is distorted to varying degrees. By analysing the effect of the dark photon on the tails of Drell-Yan invariant mass distributions, we demonstrate the potential of the LHC in determining competitive bounds on dark photon parameter space.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

The Path to Proton Structure at One-Percent Accuracy

We present a new set of parton distribution functions (PDFs) based on a fully global dataset and machine learning techniques: NNPDF4.0. We expand the NNPDF3.1 determination with 44 new datasets, mostly from the LHC. We derive a novel methodology through hyperparameter optimisation, leading to an efficient fitting algorithm built upon stochastic gradient descent. We use NNLO QCD calculations and account for NLO electroweak corrections and nuclear uncertainties. Theoretical improvements in the PDF description include a systematic implementation of positivity constraints and integrability of sum rules. We validate our methodology by means of closure tests and "future tests" (i.e. tests of backward and forward data compatibility), and assess its stability, specifically upon changes of PDF parametrization basis. We study the internal compatibility of our dataset, and investigate the dependence of results both upon the choice of input dataset and of fitting methodology. We perform a first study of the phenomenological implications of NNPDF4.0 on representative LHC processes. The software framework used to produce NNPDF4.0 is made available as an open-source package together with documentation and examples.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

A fragmentation-based study of heavy quark production

Processes involving heavy quarks are a crucial component of the LHC physics program, both by themselves and as backgrounds for Higgs physics and new physics searches. In this work, we critically reconsider the validity of the widely-adopted approximation in which heavy quarks are generated at the matrix-element level, with special emphasis on the impact of the collinear logarithms associated with final-state heavy quark and gluon splittings. Our study, based on a perturbative fragmentation-function approach, explicitly shows that neglecting the resummation of collinear logarithms may yield inaccurate predictions, in particular when observables exclusive in the heavy quark degrees of freedom are considered. Our findings motivate the use of schemes which encompass the resummation of final-state collinear logarithms.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Higgs production in bottom-quark fusion: matching beyond leading order

We compute the total cross-section for Higgs boson production in bottom-quark fusion using the so-called FONLL method for the matching of a scheme in which the $b$-quark is treated as a massless parton to that in which it is treated as a massive final-state particle, and extend our previous results to the case in which the next-to-next-to-leading-log five-flavor scheme result is combined with the next-to-leading-order O(as^3) four-flavor scheme computation.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Single Top Production in PDF fits

We study the impact of recent LHC $t$-channel single top-quark and top-antiquark measurements at centre-of-mass energies of 7, 8 and 13 TeV on the parton distribution functions (PDFs) of the proton. We consider, namely, total cross sections, top-antitop cross section ratios, and differential distributions. We present a critical appraisal of the data, studying in particular how their description is affected by the theoretical details that enter the computation of the corresponding observables: QCD and electroweak higher-order corrections, the flavour scheme, and the value of the bottom-quark threshold. We perform a series of fits to the data within the NNPDF3.1 framework, whereby next-to-next-to-leading order QCD corrections are applied to single top measurements in a systematic way. We find that there exists an optimal combination of data that maximises consistency with the rest of the dataset, and efficiency in constraining the up, down and, partially, gluon PDFs.

0 citations0 reviewsNo code linkedOpen access
preprint2017arXiv

Parton distributions from high-precision collider data

We present a new set of parton distributions, NNPDF3.1, which updates NNPDF3.0, the first global set of PDFs determined using a methodology validated by a closure test. The update is motivated by recent progress in methodology and available data, and involves both. On the methodological side, we now parametrize and determine the charm PDF alongside the light quarks and gluon ones, thereby increasing from seven to eight the number of independent PDFs. On the data side, we now include the D0 electron and muon W asymmetries from the final Tevatron dataset, the complete LHCb measurements of W and Z production in the forward region at 7 and 8 TeV, and new ATLAS and CMS measurements of inclusive jet and electroweak boson production. We also include for the first time top-quark pair differential distributions and the transverse momentum of the Z bosons from ATLAS and CMS. We investigate the impact of parametrizing charm and provide evidence that the accuracy and stability of the PDFs are thereby improved. We study the impact of the new data by producing a variety of determinations based on reduced datasets. We find that both improvements have a significant impact on the PDFs, with some substantial reductions in uncertainties, but with the new PDFs generally in agreement with the previous set at the one sigma level. The most significant changes are seen in the light-quark flavor separation, and in increased precision in the determination of the gluon. We explore the implications of NNPDF3.1 for LHC phenomenology at Run II, compare with recent LHC measurements at 13 TeV, provide updated predictions for Higgs production cross-sections and discuss the strangeness and charm content of the proton in light of our improved dataset and methodology. The NNPDF3.1 PDFs are delivered for the first time both as Hessian sets, and as optimized Monte Carlo sets with a compressed number of replicas.

0 citations0 reviewsNo code linkedOpen access