12 citations · 23 across the 7 of their papers we have counts for
8 papers
Pythia-Contrib: a modular contribution framework for the Pythia 8 event generator
Benoit Assi, Christian Bierlich, Rikab Gambhir +6
Pythia is a general-purpose Monte Carlo event generator used in particle, astroparticle, and nuclear physics, by theorists and experimentalists, to simulate particle collisions. Be…
HDSense: An efficient method for ranking observable sensitivity
Benoît Assi, Christian Bierlich, Rikab Gambhir +6
Identifying which observables most effectively constrain model parameters can be computationally prohibitive when considering full likelihoods of many correlated observables. This…
Iterative HOMER with uncertainties
Anja Butter, Ayodele Ore, Sofia Palacios Schweitzer +10
We present iHOMER, an iterative version of the HOMER method to extract Lund fragmentation functions from experimental data. Through iterations, we address the information gap betwe…
CODEX-b: Opening New Windows to the Long-Lived Particle Frontier at the LHC
Giulio Aielli, Juliette Alimena, Saul Balcarcel-Salazar +50
This document is written as a contribution to the European Strategy of Particle Physics (ESPP) update. We offer a detailed overview of current developments and future directions fo…
Post-hoc reweighting of hadron production in the Lund string model
Benoît Assi, Christan Bierlich, Philip Ilten +6
We present a method for reweighting flavor selection in the Lund string fragmentation model. This is the process of calculating and applying event weights enabling fast and exact v…
Characterizing the hadronization of parton showers using the HOMER method
Benoit Assi, Christian Bierlich, Philip Ilten +6
We update the HOMER method, a technique to solve a restricted version of the inverse problem of hadronization -- extracting the Lund string fragmentation function from data…
Describing Hadronization via Histories and Observables for Monte-Carlo Event Reweighting
Christian Bierlich, Phil Ilten, Tony Menzo +5
We introduce a novel method for extracting a fragmentation model directly from experimental data without requiring an explicit parametric form, called Histories and Observables for…
Towards a data-driven model of hadronization using normalizing flows
Christian Bierlich, Phil Ilten, Tony Menzo +5
We introduce a model of hadronization based on invertible neural networks that faithfully reproduces a simplified version of the Lund string model for meson hadronization. Addition…