Quantum image processing and recognition

Purpose and goal:

The core idea of this project is to design, manufacture and test a novel image processor that uses quantum resources to encode a digital image into a diffraction pattern and is able to classify previously unseen images. Expected results and effects:

By using diffraction patterns to classify images, we reduce the amount of data storage and increase the ML processing performance. At the same time, by using quantum transmitters and receivers we ensure that we use the minimum amount of energy per information bit. Approach and implementation:

The project is structured around the four main deliverables to reduce complexity and overhead. The main deliverables of the project are: D1. Database design and implementation. D2. ML model training and evaluation. D3. Chipset design and simulation. D4. Chipset manufacturing and testing.