Quantum approximate optimization using SWAP gates for mixing

dc.contributor.authorBorgsten, Carl
dc.contributor.departmentChalmers tekniska högskola / Institutionen för fysiksv
dc.contributor.examinerGranath, Mats
dc.contributor.supervisorGranath, Mats
dc.contributor.supervisorFitzek, David
dc.date.accessioned2021-06-23T06:48:42Z
dc.date.available2021-06-23T06:48:42Z
dc.date.issued2021sv
dc.date.submitted2020
dc.description.abstractIn recent years, with the emergence of more complex optimization problems scientists have begun to look at how quantum computers can be utilized to solve big problems. One algorithm that can be used is the quantum approximation algorithm(QAOA). QAOA applies two different types of operators to a qubit string representing an initial state. One regulates the problem to be optimized and the other mixes the states such that all possible solutions to the problem are being tested. My work investigates the possibility to use SWAP gates for mixing instead of the ordinary Pauli X operator for the traveling salesman problem. The advantage of the SWAP mixer is that it swaps the values of two qubits in the qubit string compared to the Pauli X operator that changes the value of a single qubit. My results show that the SWAP mixer works well for the traveling salesman problem and has the potential to be used in more complex problems.sv
dc.identifier.coursecodeTIFX05sv
dc.identifier.urihttps://hdl.handle.net/20.500.12380/302689
dc.language.isoengsv
dc.setspec.uppsokPhysicsChemistryMaths
dc.subjectquantumsv
dc.subjectcomputersv
dc.subjectQAOAsv
dc.subjectqubitsv
dc.subjectTSPsv
dc.subjectSWAPsv
dc.subjectalgorithmsv
dc.subjectoptimizesv
dc.subjectmixingsv
dc.subjectstatesv
dc.titleQuantum approximate optimization using SWAP gates for mixingsv
dc.type.degreeExamensarbete för masterexamensv
dc.type.uppsokH
local.programmeComplex adaptive systems (MPCAS), MSc
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