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Particle colliders have evolved from a less prominent area of physics in the 1960s to a central focus of high-energy research today. Machines like the Large Hadron Collider (LHC) provide high center-of-mass energies, enabling scientists to test the predictions of the Standard Model and explore new physics.
Developed in the 1970s, Quantum Chromodynamics (QCD) has become a cornerstone of the Standard Model, describing how quarks and gluons interact and bind to form hadrons like protons and neutrons. As colliders like the LHC achieve higher energies, the complexity of QCD calculations increases, highlighting the need for precise theoretical predictions to compare with experimental results. A solid understanding of QCD processes is essential for advancing our knowledge of strong interactions and for uncovering signals of new physics beyond the Standard Model.
Our investigation is structured into three main topics. First, we conduct a comprehensive numerical evaluation of the Next-to-Next-to-Leading Order (NNLO) leadingcolor amplitude for the process Z/γ → g +g +q +q. This subprocess is important for obtaining precise measurements of αs, which can be compared with future collider experiments.
Second, we focus on calculating three families of two-loop six-point massless integrals in dimensional regularization. The results are expressed as one-fold integrals over classical polylogarithms. This constitutes the first analytic computation of twoloop master integrals with eight scales. Achieving Next-to-Next-to-Leading Order (NNLO) accuracy for processes involving four or more jets remains a significant challenge due to the inherent complexity of these two-loop calculations, highlighting the importance of our work in enhancing precise predictions for collider physics.
Finally, we present a novel Integration by Parts (IBP) reduction tool, NeatIBP+Kira, designed to optimize the reduction of integrals in high-precision calculations for collider physics. By employing advanced methods such as syzygy and spanning-cuts, our tool improves memory efficiency and reduces computational runtime, representing a significant advancement in computational techniques for multiloop calculations.