SMuK 2023 – wissenschaftliches Programm
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T: Fachverband Teilchenphysik
T 128: AI Topical Day – New Methods (joint session AKPIK/T)
T 128.3: Vortrag
Donnerstag, 23. März 2023, 18:00–18:15, HSZ/0004
Quantum Angle Generator for Image Generation — •Florian Rehm1,2, Sofia Vallecorsa1, Michele Grossi1, Kerstin Borras2,3, Dirk Krücker2, Simon Schnake2,3, Alexis-Harilao Verney-Provatas2,3, and Valle Varo3 — 1CERN, Switzerland — 2RWTH Aachen University, Germany — 3DESY, Germany
The Quantum Angle Generator (QAG) is a new generative model for quantum computers. It consists of a parameterized quantum circuit trained with an objective function. The QAG model utilizes angle encoding for the conversion between the generated quantum data and classical data. Therefore, it requires one qubit per feature or pixel, while the output resolution is adjusted by the number of shots performing the image generation. This approach allows the generation of highly precise images on recent quantum computers. In this paper, the model is optimised for a High Energy Physics (HEP) use case generating simplified one-dimensional images measured by a specific particle detector, a calorimeter. With a reasonable number of shots, the QAG model achieves an elevated level of accuracy. The advantages of the QAG model are lined out - such as simple and stable training, a reasonable amount of qubits, circuit calls, circuit size and computation time compared to other quantum generative models, e.g. quantum GANs (qGANs) and Quantum Circuit Born Machines.