Quantum Algorithms

for pattern-matching in genomic sequences

Master Thesis (2018)
Author(s)

A. Sarkar (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

K.L.M. Bertels – Mentor

C.G. Almudever – Graduation committee member

Z Al-Ars – Graduation committee member

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2018 Aritra Sarkar
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 Aritra Sarkar
Graduation Date
22-06-2018
Awarding Institution
Quantum & Computer Engineering, Delft University of Technology, QuTech Advanced Research Centre
Related content

Git repository of the Project

https://gitlab.com/prince-ph0en1x/QaGs
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Fast sequencing and analysis of (microorganism, plant or human) genomes will open up new vistas in fields like personalised medication, food yield and epigenetic research. Current state-of-the-art DNA pattern matching techniques use heuristic algorithms on computing clusters of CPUs, GPUs and FPGAs. With genomic data set to eclipse social and astronomical big data streams within a decade, the alternate computing paradigm of quantum computation is explored to accelerate genome-sequence reconstruction. The inherent parallelism of quantum superposition of states is harnessed to design a quantum kernel for accelerating the search process. The project explores the merger of these two domains and identifies ways to fit these together to design a genome-sequence analysis pipeline with quantum algorithmic speedup. The design of a genome-sequence analysis pipeline with a quantum kernel is tested with a proof-of-concept demonstration using a quantum simulator.

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