Simulation of Charge Stability Diagrams for Automated Tuning Solutions (SimCATS)
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866916891296006144 |
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| author | Hader, Fabian Fleitmann, Sarah Vogelbruch, Jan Geck, Lotte van Waasen, Stefan |
| author_facet | Hader, Fabian Fleitmann, Sarah Vogelbruch, Jan Geck, Lotte van Waasen, Stefan |
| contents | Quantum dots must be tuned precisely to provide a suitable basis for quantum computation. A scalable platform for quantum computing can only be achieved by fully automating the tuning process. One crucial step is to trap the appropriate number of electrons in the quantum dots, typically accomplished by analyzing charge stability diagrams (CSDs). Training and testing automation algorithms require large amounts of data, which can be either measured and manually labeled in an experiment or simulated. This article introduces a new approach to the realistic simulation of such measurements. Our flexible framework enables the simulation of ideal CSD data complemented with appropriate sensor responses and distortions. We suggest using this simulation to benchmark published algorithms. Also, we encourage the extension by custom models and parameter sets to drive the development of robust, technology-independent algorithms. Code is available at https://github.com/f-hader/SimCATS. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_08032 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Simulation of Charge Stability Diagrams for Automated Tuning Solutions (SimCATS) Hader, Fabian Fleitmann, Sarah Vogelbruch, Jan Geck, Lotte van Waasen, Stefan Mesoscale and Nanoscale Physics Quantum Physics Quantum dots must be tuned precisely to provide a suitable basis for quantum computation. A scalable platform for quantum computing can only be achieved by fully automating the tuning process. One crucial step is to trap the appropriate number of electrons in the quantum dots, typically accomplished by analyzing charge stability diagrams (CSDs). Training and testing automation algorithms require large amounts of data, which can be either measured and manually labeled in an experiment or simulated. This article introduces a new approach to the realistic simulation of such measurements. Our flexible framework enables the simulation of ideal CSD data complemented with appropriate sensor responses and distortions. We suggest using this simulation to benchmark published algorithms. Also, we encourage the extension by custom models and parameter sets to drive the development of robust, technology-independent algorithms. Code is available at https://github.com/f-hader/SimCATS. |
| title | Simulation of Charge Stability Diagrams for Automated Tuning Solutions (SimCATS) |
| topic | Mesoscale and Nanoscale Physics Quantum Physics |
| url | https://arxiv.org/abs/2508.08032 |