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Support Vector Machines on Noisy Intermediate-Scale Quantum Computers
KTH, School of Electrical Engineering and Computer Science (EECS).
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Support vector machine algorithms are considered essential for the implementationof automation in a radio access network. Specifically, they are critical inthe prediction of the quality of user experience for video streaming based ondevice and network-level metrics. Quantum support vector machine (QSVM)is the quantum analogue of the classical support vector machine algorithm,which utilizes the properties of quantum computers to exponentially speed upthe algorithm. This thesis provides an implementation of the QSVMclassificationsystem and its fundamental components, the quantum Fourier transform(QFT) and the Harrow-Hassidim-Lloyd (HHL) algorithms, using the opensourcequantum computing software development kits (SDKs), IBM’s Qiskitand Rigetti’s pyQuil, and real quantum computers that can be accessed by publiccloud service. Moreover, the QSVM classification system is implementedon a superconducting quantum computer, IBMQX2, showing the potential ofthis quantum algorithm to be executed on the Noisy Intermediate-Scale Quantum(NISQ) computers.

Abstract [sv]

Supportvektormaskinalgoritmer anses nödvändiga för implementering av automatiseringi radionätet. De är kritiska när det gäller att säkerställa den upplevdaanvändarkvaliteten för strömmad video (quality of user experience) baseradpå enhets- och nätverksnivåmätningar. Kvantsupportvektormaskinsalgoritmen(QSVM) är en kvantanaloga version av den klassiska supportvektormaskinalgoritmen,som använder egenskaperna hos kvantdatorer för att exponentielltsnabba upp algoritmen. Denna avhandling tillhandahåller en implementeringav den QSVM klassificeringssystemet och dess grundläggande komponenter,kvant-Fourier-transform (QFT) och Harrow-Hassidim-Lloyd (HHL) -algoritmerna, med hjälp av open-source kvantmjukvara (SDK), IBMs Qiskitoch Rigettis pyQuil och riktiga kvantdatorer som kan nås via en offentlig molntjänst.Dessutom implementeras QSVM-klassificeringssystemet på en supraledandekvantdator, IBMQX2, som visar potentialen för denna kvantalgoritmatt kunna exekveras på den brusiga medelstora kvantdatorer (NISQ).

Place, publisher, year, edition, pages
2019. , p. 64
Series
TRITA-EECS-EX ; 2019:644
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-266112OAI: oai:DiVA.org:kth-266112DiVA, id: diva2:1381355
External cooperation
Ericsson
Educational program
Master of Science - Information and Network Engineering
Supervisors
Examiners
Available from: 2019-12-20 Created: 2019-12-20 Last updated: 2019-12-20Bibliographically approved

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