Parallel computing solutions to the Balitsky-Kovchegov equation

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dc.contributor.advisorWeigert, Weigert, Heriberten_ZA
dc.contributor.authorHillebrand-Viljoen, Charlotte Stephanieen_ZA
dc.date.accessioned2016-07-25T07:14:55Z
dc.date.available2016-07-25T07:14:55Z
dc.date.issued2016en_ZA
dc.description.abstractThe JIMWLK (Jalilian-Marian, Iancu, McLerran,Weigert, Leonodiv and Kovner; pronounced "gym walk") equation describes the energy evolution of observables in the colour glass condensate (CGC) state of matter, which is particularly relevant to collider physics. Currently there are many implementations of JIMWLK evolution in the spirit of the factorised Balitsky-Kovchegov (BK) equation for the total cross section, including a number of efforts to consistently implement evolution at next-to-leading-order[1-5]. Aside from NLO there is a growing interest in studying new, more exclusive, observables, such as single transverse spin asymmetries and transverse momentum distributions[6-8]. These require the inclusion of new degrees of freedom, which can be done systematically by extending the Gaussian truncation of the JIMWLK equation[9][10]. This necessarily increases the computational demands, both in terms of floating point operations and of storage requirements. After a discussion of the theoretical context, we address the first computational step and introduce new, parallelised methods in code that evolves the BK equation. Parallelisation of BK evolution using NVIDIA CUDA with implementation on a commercially available graphical processing unit (GPU) results in performance improvements of roughly an order of magnitude over comparable serial programmes. This also allows us to implement test cases which are often neglected. The code presented here covers only the total cross section case, but it is written with extension to more interesting cases in mind and we discuss some such potential applications.en_ZA
dc.identifier.apacitationHillebrand-Viljoen, C. S. (2016). <i>Parallel computing solutions to the Balitsky-Kovchegov equation</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Physics. Retrieved from http://hdl.handle.net/11427/20656en_ZA
dc.identifier.chicagocitationHillebrand-Viljoen, Charlotte Stephanie. <i>"Parallel computing solutions to the Balitsky-Kovchegov equation."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Physics, 2016. http://hdl.handle.net/11427/20656en_ZA
dc.identifier.citationHillebrand-Viljoen, C. 2016. Parallel computing solutions to the Balitsky-Kovchegov equation. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Hillebrand-Viljoen, Charlotte Stephanie AB - The JIMWLK (Jalilian-Marian, Iancu, McLerran,Weigert, Leonodiv and Kovner; pronounced "gym walk") equation describes the energy evolution of observables in the colour glass condensate (CGC) state of matter, which is particularly relevant to collider physics. Currently there are many implementations of JIMWLK evolution in the spirit of the factorised Balitsky-Kovchegov (BK) equation for the total cross section, including a number of efforts to consistently implement evolution at next-to-leading-order[1-5]. Aside from NLO there is a growing interest in studying new, more exclusive, observables, such as single transverse spin asymmetries and transverse momentum distributions[6-8]. These require the inclusion of new degrees of freedom, which can be done systematically by extending the Gaussian truncation of the JIMWLK equation[9][10]. This necessarily increases the computational demands, both in terms of floating point operations and of storage requirements. After a discussion of the theoretical context, we address the first computational step and introduce new, parallelised methods in code that evolves the BK equation. Parallelisation of BK evolution using NVIDIA CUDA with implementation on a commercially available graphical processing unit (GPU) results in performance improvements of roughly an order of magnitude over comparable serial programmes. This also allows us to implement test cases which are often neglected. The code presented here covers only the total cross section case, but it is written with extension to more interesting cases in mind and we discuss some such potential applications. DA - 2016 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2016 T1 - Parallel computing solutions to the Balitsky-Kovchegov equation TI - Parallel computing solutions to the Balitsky-Kovchegov equation UR - http://hdl.handle.net/11427/20656 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/20656
dc.identifier.vancouvercitationHillebrand-Viljoen CS. Parallel computing solutions to the Balitsky-Kovchegov equation. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Physics, 2016 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/20656en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Physicsen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherPhysicsen_ZA
dc.titleParallel computing solutions to the Balitsky-Kovchegov equationen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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