Abstract

Parton distribution functions (PDFs) quantify probabilities to find partons (quarks and gluons) in a hadron as a function of the fraction x of the hadron’s momentum carried by the parton at a given energy scale. PDFs play a critical role in precision tests of the Standard Model in Higgs boson production and other electroweak processes at the Large Hadron Collider (LHC), and in searches for physics beyond the Standard Model. PDFs are obtained by the global QCD analysis, which fits theoretical predictions to experimental measurements. PDF fitting and post-analysis are computationally intensive. This dissertation discusses fast statistical methods for the global QCD analysis. To compute theoretical cross sections, I developed an original Monte Carlo integration method based on Boosted Decision Trees. To understand the properties of high-dimensional probability distributions in the PDF parameter space, I developed an L2 sensitivity method, explored its mathematical properties, and applied it to elucidate the role of various experiments, such as deep-inelastic scattering on deuteron, in the global fits. These results facilitate obtaining accurate PDFs for precision measurements at the CERN LHC and BNL Electron-Ion Collider.

Degree Date

Fall 12-18-2021

Document Type

Dissertation

Degree Name

Ph.D.

Department

Department of Physics

Advisor

Dr. Pavel Nadolsky

Second Advisor

Dr. Allison McCarn Deiana

Third Advisor

Dr. Fredrick I. Olness

Fourth Advisor

Dr. Alberto Accardi

Subject Area

Physics

Number of Pages

145

Format

.pdf

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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