LHC Theory Initiative

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This award funds the LHC Theory Initiative, a competitive national fellowship program supporting the training of postdoctoral fellows in theoretical particle physics.The ultimate goal of particle physics is to identify the fundamental principles that govern matter, energy, space and time. The Standard Model (SM) provides a well tested quantitative description of the known particles and forces. A body of evidence suggests that the SM is not complete, and that it is the low-energy limit of a more fundamental theory.The CERN Large Hadron Collider (LHC) began physics operations in 2010, and on July 4, 2012, the ATLAS and CMS collaborations announced discovery of a new resonance with a mass near 125 GeV. Subsequent running has confirmed that the new particle looks like the long-sought Higgs boson. CERN is in the process of doubling the LHC's energy and significantly increasing its luminosity. Physics goals include precision measurements of Higgs properties, as well as direct searches for new particles, especially dark matter. Accurate theoretical predictions are needed for the LHC to realize its full potential. For example, because of the LHC's high luminosity, it can be difficult to separate signals from backgrounds. The lowest-order predictions for such processes exhibit significant uncertainties that can be reduced by including higher orders in perturbation theory. Also, it is essential to explore signatures and strategies in depth to make the most of the new discoveries and to fully exploit the physics potential of this powerful experimental facility. This fellowship program will help ensure that the United States has the young theorists it needs to gain full benefit from the investment it has made in the LHC experimental facility.The activities proposed here are to provide calculational tools and theoretical results necessary to fully extract physics results from the LHC. Proposed activities include calculations of higher-order QCD and electroweak corrections in the SM and beyond-the-SM models, as well as the development of new, improved, shower algorithms. Also important is the development of robust and well-tested Monte Carlo tools to confront the data with theoretical models. Much remains to be done in these areas.