Prediction of Molecular Single-Photon Emitters: A Materials-Modelling Approach
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866910047781519360 |
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| author | Öhman, Erik Karlsson Wang, Daqing Geilhufe, R. Matthias Schäfer, Christian |
| author_facet | Öhman, Erik Karlsson Wang, Daqing Geilhufe, R. Matthias Schäfer, Christian |
| contents | Interfacing light with quantum systems is an integral part of quantum technology, with the most essential building block being single-photon emitters. Although various platforms exist, each with its individual strengths, molecular emitters boast a unique advantage -- namely the flexibility to tailor their design to fit the requirements of a specific task. However, the characteristics of the vast space of possible molecular configurations are challenging to understand and explore. Here, we present a theoretical and computational framework to initiate exploration of this vast potential by integrating database analysis with microscopic predictions. Using a model system of dibenzoterrylene in an anthracene host as benchmark, our approach identifies promising new candidates, among them a chiral molecular emitter. Future extensions of our approach integrated with machine learning routines hold the promise of ultimately unlocking the full potential of molecular quantum light-matter interfaces. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_06407 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Prediction of Molecular Single-Photon Emitters: A Materials-Modelling Approach Öhman, Erik Karlsson Wang, Daqing Geilhufe, R. Matthias Schäfer, Christian Quantum Physics Materials Science Applied Physics Computational Physics Optics Interfacing light with quantum systems is an integral part of quantum technology, with the most essential building block being single-photon emitters. Although various platforms exist, each with its individual strengths, molecular emitters boast a unique advantage -- namely the flexibility to tailor their design to fit the requirements of a specific task. However, the characteristics of the vast space of possible molecular configurations are challenging to understand and explore. Here, we present a theoretical and computational framework to initiate exploration of this vast potential by integrating database analysis with microscopic predictions. Using a model system of dibenzoterrylene in an anthracene host as benchmark, our approach identifies promising new candidates, among them a chiral molecular emitter. Future extensions of our approach integrated with machine learning routines hold the promise of ultimately unlocking the full potential of molecular quantum light-matter interfaces. |
| title | Prediction of Molecular Single-Photon Emitters: A Materials-Modelling Approach |
| topic | Quantum Physics Materials Science Applied Physics Computational Physics Optics |
| url | https://arxiv.org/abs/2510.06407 |