Quantum Algorithms for Combinatorial Optimization

Kliesch, Alexander

Alexander Kliesch

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Original title:: Quantum Algorithms for Combinatorial Optimization
Translated title:: Quantenalgorithmen für kombinatorische Optimierung
Author:: Kliesch, Alexander
Year:: 2023
Document type:: Dissertation
Faculty/School:: TUM School of Computation, Information and Technology
Advisor:: König, Robert (Prof. Dr.)
Referee:: König, Robert (Prof. Dr.); Kueng, Richard (Prof. Dr.)
Language:: en
Subject group:: MAT Mathematik
TUM classification:: PHY 011; MAT 022
Abstract:: This thesis studies the "Quantum Approximate Optimization Algorithm" (QAOA) applied to approximately solve NP-complete combinatorial optimization problems such as the Max-Cut problem. In particular, we prove performance limitations of QAOA. We furthermore propose two new algorithms derived from QAOA ("recursive QAOA" and "twisted QAOA") which aim at bypassing these limitations.
Translated abstract:: Diese Dissertation untersucht den "Quantum Approximate Optimization Algorithm" (QAOA), welcher zur approximativen Lösung von NP-vollständigen kombinatorischen Optimierungsproblemen wie dem Max-Cut-Problem verwendet wird. Insbesondere beweisen wir Leistungsgrenzen von QAOA. Darüber hinaus schlagen wir zwei neue, von QAOA abgeleitete Algorithmen vor ("recursive QAOA" und "twisted QAOA"), welche darauf abzielen, diese Beschränkungen zu umgehen.
WWW:: https://mediatum.ub.tum.de/?id=1692178
Date of submission:: 25.11.2022
Oral examination:: 19.07.2023
File size:: 5627545 bytes
Pages:: 136
Urn (citeable URL):: https://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:91-diss-20230719-1692178-1-4
Last change:: 11.08.2023
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