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001034092 037__ $$aFZJ-2024-06913
001034092 1001_ $$0P:(DE-Juel1)170099$$aHader, Fabian$$b0
001034092 245__ $$aAutomated Charge Transition Detection in Quantum Dot Charge Stability Diagrams
001034092 260__ $$c2024
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001034092 520__ $$aGate-defined semiconductor quantum dots require an appropriate number of electrons to function as qubits. The number of electrons is usually tuned by analyzing charge stability diagrams, in which charge transitions manifest as edges. Therefore, to fully automate qubit tuning, it is necessary to recognize these edges automatically and reliably. This paper investigates possible detection methods, describes their training with simulated data from the SimCATS framework, and performs a quantitative comparison with a future hardware implementation in mind. Furthermore, we investigated the quality of the optimized approaches on experimentally measured data from a GaAs and a SiGe qubit sample.
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001034092 7001_ $$0P:(DE-Juel1)176540$$aFuchs, Fabian$$b1
001034092 7001_ $$0P:(DE-Juel1)173094$$aFleitmann, Sarah$$b2$$ufzj
001034092 7001_ $$0P:(DE-Juel1)201385$$aHavemann, Karin$$b3$$ufzj
001034092 7001_ $$0P:(DE-Juel1)173093$$aScherer, Benedikt$$b4$$ufzj
001034092 7001_ $$0P:(DE-Juel1)133952$$aVogelbruch, Jan$$b5$$ufzj
001034092 7001_ $$0P:(DE-Juel1)169123$$aGeck, Lotte$$b6$$ufzj
001034092 7001_ $$0P:(DE-Juel1)142562$$aWaasen, Stefan Van$$b7$$ufzj
001034092 773__ $$a10.36227/techrxiv.172963185.53119182/v1
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001034092 9141_ $$y2024
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