Details
| Original language | English |
|---|---|
| Title of host publication | 2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (electronic) | 9798350345995 |
| ISBN (print) | 979-8-3503-4600-8 |
| Publication status | Published - 2023 |
| Event | 2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023 - Munich, Germany Duration: 26 Jun 2023 → 30 Jun 2023 |
Publication series
| Name | Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC |
|---|---|
| ISSN (Print) | 2639-5452 |
| ISSN (electronic) | 2833-1052 |
Abstract
Quantum generative learning is a promising candidate to demonstrate practical quantum advantage on state-of-the-art quantum information processing devices in the near future. In particular, photonic quantum frequency coprocessors (QFPs) [1] leverage quantum-correlated light sources, a high degree of mode scalability, robustness to decoherence and integration with preexisting telecom infrastructure. As was demonstrated experimentally in previous work [2], phase control and deterministic frequency mixing allow to manipulate individual frequency modes and provide coherent control of tens of frequency modes for two photons.
ASJC Scopus subject areas
- Materials Science(all)
- Electronic, Optical and Magnetic Materials
- Physics and Astronomy(all)
- Instrumentation
- Physics and Astronomy(all)
- Atomic and Molecular Physics, and Optics
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2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023. Institute of Electrical and Electronics Engineers Inc., 2023. ( Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Generative Adversarial Learning boosted by a Photonic Quantum Frequency Coprocessor
AU - Rübeling, Philip
AU - Baekkegaard, Thomas
AU - Zinner, Nikolaj Thomas
AU - Kues, Michael
N1 - Funding Information: 1 Lukens, Joseph M., and Pavel Lougovski., "Frequency-encoded photonic qubits for quantum information processing." Optica (2017) 2 Kues, M., Reimer, C., et al., Quantum optical microcombs. Nature Photonics 13, 170–179 (2019). 3 Lloyd, Seth, and Christian Weedbrook. "Quantum generative adversarial learning." Physical review letters (2018) [4] Abbas, Amira, et al. "The power of quantum neural networks." Nature Computational Science (2021) *This work received funding from the European Research Council (ERC) under grant agreement No. 947603 (QFreC project) and from the German Federal Ministry of Education and Research, Quantum Futur Program (PQuMAL)
PY - 2023
Y1 - 2023
N2 - Quantum generative learning is a promising candidate to demonstrate practical quantum advantage on state-of-the-art quantum information processing devices in the near future. In particular, photonic quantum frequency coprocessors (QFPs) [1] leverage quantum-correlated light sources, a high degree of mode scalability, robustness to decoherence and integration with preexisting telecom infrastructure. As was demonstrated experimentally in previous work [2], phase control and deterministic frequency mixing allow to manipulate individual frequency modes and provide coherent control of tens of frequency modes for two photons.
AB - Quantum generative learning is a promising candidate to demonstrate practical quantum advantage on state-of-the-art quantum information processing devices in the near future. In particular, photonic quantum frequency coprocessors (QFPs) [1] leverage quantum-correlated light sources, a high degree of mode scalability, robustness to decoherence and integration with preexisting telecom infrastructure. As was demonstrated experimentally in previous work [2], phase control and deterministic frequency mixing allow to manipulate individual frequency modes and provide coherent control of tens of frequency modes for two photons.
UR - http://www.scopus.com/inward/record.url?scp=85175706033&partnerID=8YFLogxK
U2 - 10.1109/CLEO/EUROPE-EQEC57999.2023.10231993
DO - 10.1109/CLEO/EUROPE-EQEC57999.2023.10231993
M3 - Conference contribution
AN - SCOPUS:85175706033
SN - 979-8-3503-4600-8
T3 - Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC
BT - 2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023
Y2 - 26 June 2023 through 30 June 2023
ER -