i-flow: High-dimensional Integration and Sampling with Normalizing Flows

In high-energy physics (HEP) experiments, a thorough understanding of the properties of known physics forms the basis of any searches that look for new effects. This can only be achieved by an accurate simulation, which in many cases boils down to performing an integral and sampling from it. Often high-dimensional phase space integrals with nontrivial correlations between dimensions are required in important theory calculations. Monte-Carlo (MC) methods still remain as the most important techniques for solving high-dimensional problems across many fields, including for instance: biology [1, 2], chemistry [3], astronomy [4], medical physics [5], finance [6] and image rendering [7]. In high-energy physics, all analyses at the Large Hadron Collider (LHC) rely strongly on multipurpose Monte Carlo event generators [8, 9] for signal or background prediction.