Leibniz MMS Days 2024 - Abstract

Geng, Alexander

Quantum computing in image processing - promises and the reality of the NISQ era

The size of images and these data that we process daily has been increasing enormously in recent years. Quantum computing promises to process this data more efficiently. Experiments on quantum computer simulators have proven the paradigms on which this promise is built to be correct. However, currently, running the same algorithms on a real quantum computer is often too error-prone to be of any practical use. We explore the current possibilities for image processing on real quantum computers. We have redesigned a commonly used quantum image encoding technique to reduce its susceptibility to errors. Our experimental results demonstrate that the current size limit for images to be encoded on a quantum computer and retrieved with an error of at most 5?s 2 × 2 pixels. We will show, how to overcome these limitations and make use of the current NISQ hardware by combining classical and quantum computing to solve image processing tasks like edge detection and classification of images.