KetGPT -- Dataset Augmentation of Quantum Circuits using Transformers

arXiv:2402.13352v1 Announce Type: cross
Abstract: Quantum algorithms, represented as quantum circuits, can be used as benchmarks for assessing the performance of quantum systems. Existing datasets, widely utilized in the field, suffer from limitations in size and versatility, leading researchers to employ randomly generated circuits. Random circuits are, however, not representative benchmarks as they lack the inherent properties of real quantum algorithms for which the quantum systems are manufactured. This shortage of `useful' quantum benchmarks poses a challenge to advancing the …

abstract algorithms arxiv augmentation benchmarks cs.ai cs.et cs.lg dataset datasets generated limitations performance quant-ph quantum random researchers systems transformers type