IRN Terascale @ IJCLab Orsay

Session

Methods and Tools

21 avr. 2026, 14:40

Auditorium Pierre Lehmann (IJCLab)

3. SMEFT NLO correction to Higgs decaying to fermion pairs implementation Sherpa

Shakeel Ur Rahaman (IPPP, Durham University)

21/04/2026 14:40

Methods and Tools

Leveraging the Large Hadron Collider (LHC) data and the SMEFT framework, study the properties of Higgs boson is now an active research program. However, the robust analysis hinges on the inclusion of higher order (NLO) Electroweak (EW) and QCD corrections arising from dimension-6 SMEFT operators for a more accurate picture. While significant progress has been made in calculating NLO QCD...

4. Study of Neutral-Current Drell-Yan process with POWHEG: Impact of NLO EW effects and sin2thetaW

Mohamed Berkat (CEA Saclay)

21/04/2026 15:00

Methods and Tools

The NCDY process is sensitive to NLO EW effects and to the value of sin2thetaW, which manifest themselves differently on the Z peak and at high invariant mass. In this, we present a practical and physics-oriented study based on POWHEG-BOX-V2 (Z_ew-BMNNPV), with emphasis on how to configure and validate NLO electroweak simulations. We discuss a reproducible workflow to control the relevant...

8. Information Theory meets QCD

Ben Assi (University of Cincinnati)

21/04/2026 15:20

Methods and Tools

We begin by reviewing how NLL accuracy is achieved in modern parton showers, highlighting the recent Sherpa implementation, and then introduce our new information-theoretic matching framework to achieve beyond NLL accuracy. By minimizing a Kullback–Leibler functional under constraints set by precision QCD input observables (including theory uncertainties), we embed high-order predictions into...

1. Exploring the BSM parameter space with Simulation-Based Inference method

Arpita Mondal (Laboratory of Subatomic Physics & Cosmology)

21/04/2026 15:40

Methods and Tools

Sampling parameter spaces of beyond-the-Standard-Model (BSM) scenarios is computationally challenging due to high dimensionality, complex likelihoods, and stringent experimental constraints. We explore likelihood-free, neural network-based Simulation-Based Inference (SBI) methods to address this problem, focusing on three amortized approaches: Neural Posterior Estimation (NPE), Neural...

15. How to Explain Parton Distribution Functions with Shapley Values

Raphael BONNET GUERRINI

21/04/2026 16:30

Methods and Tools

This talk presents preliminary results obtained with an adapted explainable AI method, Shapley values, to study parton distribution functions (PDFs), with the goal of quantifying the impact of individual PDFs on the global fit, on specific datasets, and across particular x-regions.

21. Bayesian Neural Networks for Robust Uncertainty Quantification in Parton Distribution Functions

Dakshansh Chawda (University of Milan)

21/04/2026 16:50

Methods and Tools

Parton Distribution Functions (PDFs) are a cornerstone of modern collider phenomenology, encoding the non-perturbative structure of the proton and entering virtually every theoretical prediction at hadron colliders. Their precise determination is essential across broad physics program: from accurate predictions of Standard Model benchmark processes such as Higgs, W and Z boson production, to...

30. Scaling laws for amplitude surrogates

Joaquín Iturriza Ramirez (Lpnhe)

21/04/2026 17:10

Methods and Tools

Fast and precise evaluations of scattering amplitudes even in the case of precision calculations is essential for event generation tools at the HL-LHC. We explore the scaling behavior of the achievable precision of neural networks in this regression problem for multiple architectures, including a Lorentz symmetry aware multilayer perceptron and a fully Lorentz equivariant transformer using...