hipQCD · Highest Precision QCD predictions for a new era in Higgs boson phenomenology

The discovery of the Higgs boson at the CERN Large Hadron Collider (LHC) marked the beginning of a new era for particle physics. For the first time, we may have an experimentally tested and theoretically coherent picture of fundamental interactions, valid up to very high energies. A thorough exploration of the Higgs sector, to ascertain whether or not the new particle behaves as predicted by the Standard Model is now paramount.Such an investigation is extremely challenging, and it requires absolute control over many complex Higgs signal and background processes. The goal of hipQCD is to develop innovative techniques for highest precision theoretical predictions at colliders, and to apply them for a wide range of high impact Higgs phenomenological studies at the LHC.hipQCD addresses the major Higgs production and decay channels. Its main objectives are1. to provide realistic predictions at ultimate accuracy for the main Higgs production and decay channels, by developing cutting-edge fully differential predictions at the third order in QCD perturbation theory for Higgs production in gluon and vector boson fusion and for Higgs decay to b quarks;2. to allow for precise and reliable Higgs characterization studies at very high energy scales, by developing novel techniques to tackle multi-loop amplitudes in extreme kinematics configurations;3. to significantly improve our description of Higgs production in association with other Standard Model particles, by performing groundbreaking investigations of key 2 → 3 reactions at higher orders in perturbation theory.hipQCD involves different areas of particle theory, ranging from multi-loop amplitude computations to the study of soft/collinear structures in QFT to comprehensive Higgs LHC phenomenology. Besides their crucial impact on Higgs physics, its results could also be applied to a broader range of phenomenological studies and will be essential to fully profit from existing and future collider data.