Neural Simulation-Based Inference Workflow demonstration

The notebooks presented here aim to serve as a scaled-down and simplified tutorial for the workflow building related to the NSBI analysis recently published by ATLAS:

• An implementation of neural simulation-based inference for parameter estimation in ATLAS (https://arxiv.org/pdf/2412.01600)

• Measurement of off-shell Higgs boson production in the $H\to ZZ\to 4\ell$ decay channel using a neural simulation-based inference technique in 13 TeV p-p collisions with the ATLAS detector (https://arxiv.org/pdf/2412.01548)

The aim is to demonstrate the workflow associated with a full-scale LHC analysis. The physics results presented in the notebooks only serve as examples of the workflow. The code in this tutorial is partially derived from the original ATLAS analysis code written by Jay Sandesara [git], R.D. Schaffer [git] and Arnaud Maury [git].

Note: The tutorial is a scaled down version of the original workflow.

The workflow currently uses the ttbar open data released by CMS, more open datasets will be added in the future. A more complete version with systematic uncertainties and ensemble training will also be added.

Building a general toolkit for NSBI at the LHC (Work in Progress)

Workflow bluprint (tentative):

Acknowledgements

This work is being supported by the U.S. National Science Foundation (NSF) cooperative agreements OAC-1836650 and PHY-2323298 (IRIS-HEP).