Print Email Facebook Twitter Implementations of Quantum Algorithms for Solving Linear Systems Title Implementations of Quantum Algorithms for Solving Linear Systems Author Sigurđsson, Sigurdsson (TU Delft Electrical Engineering, Mathematics and Computer Science) Contributor Möller, M. (mentor) Vuik, Cornelis (mentor) Degree granting institution Delft University of TechnologyTechnical University of Berlin Programme Applied Mathematics | COSSE (Computer Simulations for Science and Engineering) Project Computer Simulations for Science and Engineering Date 2021-01-26 Abstract In this thesis, I make a comparison of two quantum algorithms for solving systems of linear equations. The two approaches are tested using both simulations of quantum processes and simulations of noisy intermediary-scale quantum computers, i.e., NISQ. Both methods are tested on the same problems to compare sensitivity and runtime efficiency, varying the tests along with different levels of condition numbers, sparsity and regularity. The first of the two methods compared is the method introduced by Harrow, Hassim, and Lloyd referred to as the HHL method, after the author's initials. The second method is by a research team at Los Alamos National Laboratory called the variational quantum linear solver, or VQLS for short. The first method, HHL, was the original discovery of solving linear systems using quantum computing methods and so has served as the backdrop and benchmark for other algorithms doing the same thing. The HHL method showed that an advantage can be had when using quantum computing to solve linear systems, in fact they show that this quantum method can have exponential speed up over the commonly used classical method. Subject Quantum algorithmsLinear SolversHHLVQLS To reference this document use: http://resolver.tudelft.nl/uuid:820157f7-5350-4908-acba-7f419f0a7ec9 Part of collection Student theses Document type master thesis Rights © 2021 Sigurdsson Sigurđsson Files PDF Sigurdsson_Thesis_MSc.pdf 2.11 MB Close viewer /islandora/object/uuid%3A820157f7-5350-4908-acba-7f419f0a7ec9/datastream/OBJ/view