12 papers
Exploring the SMEFT landscape: Bayesian Model Selection for indirect discovery
Luca Mantani
We develop a framework for indirect discovery in the Standard Model Effective Field Theory (SMEFT) based on Bayesian model selection over operator subsets. We argue that SMEFT shou…
The effect of the two-loop SMEFT RGEs at future colliders
Luca Mantani, Pablo Olgoso, Alejo N. Rossia
The search for New Physics requires ever increasing precision from experimental and theoretical efforts. Within the Standard Model Effective Field Theory (SMEFT) framework, the lat…
New Physics Reach through Precision at Future Colliders: a Multi-Pronged Approach
Tommaso Armadillo, Eugenia Celada, Jaco ter Hoeve +7
We present projections for the sensitivity of future high-energy colliders to new physics through precision measurements of the Standard Model (SM) interactions, focusing on near-t…
Proton Structure from Neural Simulation-Based Inference at the LHC
Ricardo Barrué, Lisa Benato, Ali Kaan Güven +10
The precise determination of the parton distribution functions (PDFs) of the proton is an essential ingredient for LHC analyses, including for those at the upcoming High-Luminosity…
A linear PDF model for Bayesian inference
Mark N. Costantini, Luca Mantani, James M. Moore +1
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 d…
Tailored PDFs for New Physics searches
Ella Cole, Mark N. Costantini, Elie Hammou +4
Given the non-negligible interplay between parton distribution functions (PDFs) at large x and potential New Physics (NP) effects in the high-energy tails of hadron collider observ…