The goal of this work is to adopt an existing data compression algorithm so that it can be run on a quantum computer. Afterwards, the student should have a solid understanding of data compression, the basics of quantum computing, and…
Disclaimer: No background in quantum computing or data compression is needed when you start. Learning is part of the process.
Background: Data Compression plays a major role in today’s communication infrastructure. Whenever you are listening to a song on Spotify or watching a video on Youtube, the data that is being exchanged has been compressed to reduce the amount of storage space it requires and increase the speed at which it can be transmitted. The underlying compression algorithms exploit redundancies within the data to reduce the amount of bits needed to store the same amount of information. Lossless compression algorithms in particular do so in a way that allows you to fully recover the information from before it has been compressed. The process as a whole is completely reversible! No information is lost.
With billions in funding and major companies like Google or IBM active in the field, Quantum Computing is a technology that often makes the headlines due to its potential to solve otherwise untraceable problems. In contrast to our every day computers, quantum computers work fundamentally different. They can manipulate multiple states at once, seem to reverse the order of cause and effect, and pose a significant threat to internet security. They are not, however, an all powerful machine. Due to the laws of quantum physics, every operation performed on a quantum computer has to be reversible.
If every action on a quantum computer has to be reversible and lossless data compression algorithms have to be reversible by definition, the conclusion suggests itself that compression algorithms lend themselves well to quantum computing. The goal of this thesis is to explore this potential.
Goal of the Thesis: The goal of this work is to adopt an existing data compression algorithm so that it can be run on a quantum computer. At the end of the work, the student should have a solid understanding of data compression, understand the basics of quantum computing, and be able to evaluate the potential of quantum computing for real-world computational challenges.
Tasks:
- Literature research on the state of the art in quantum computing for data compression.
- Evaluation of existing data compression algorithms and selection of an algorithm well suited for quantum computer-ification.
- Prototypical implementation of a corresponding quantum algorithm.
- Evaluation of the proposed quantum algorithm on either existing quantum simulators or actual quantum hardware.
If you are interested in the presented work or have alternative ideas for topics in the field of quantum computing, reach out to Christoph Stein, Stefan Klikovits, or Manuel Wimmer.