5 papers · 1 filter
Many Wrongs Make a Right: Leveraging Biased Simulations Towards Unbiased Parameter Inference
Ezequiel Alvarez, Sean Benevedes, Manuel Szewc +1
In particle physics, as in many areas of science, parameter inference relies on simulations to bridge the gap between theory and experiment. Recent developments in simulation-based…
Di-Higgs to 4b with Bayesian inference: improving simulation estimates
Ezequiel Alvarez, Leandro Da Rold, Manuel Szewc +3
Measuring di-Higgs production in the four-bottom channel is challenged by overwhelming QCD backgrounds and imperfect simulations. We develop a Bayesian mixture model that simultane…
Inferring correlated distributions: boosted top jets
Ezequiel Alvarez, Manuel Szewc, Alejandro Szynkman +2
Improving the understanding of signal and background distributions in signal-region is a valuable key to enhance any analysis in collider physics. This is usually a difficult task…
Improvement and generalization of ABCD method with Bayesian inference
Ezequiel Alvarez, Leandro Da Rold, Manuel Szewc +3
To find New Physics or to refine our knowledge of the Standard Model at the LHC is an enterprise that involves many factors. We focus on taking advantage of available information a…
Inferring flavor mixtures in multijet events
Ezequiel Alvarez, Yuling Yao
Multijet events with heavy-flavors are of central importance at the LHC since many relevant processes -- such as , , and others -- have a preferred branchi…