3 papers
cs.NE2026
Quantization Effects of Artificial Neural Networks for Embedded Edge-Computing Applications
Alperen Aksoy, Ilja Bekman, Vesselin Dimitrov +7
This paper examines the use of Quantized Neural Networks (QNNs) for two resource-constrained scientific applications: automated calibration of semi- conductor quantum bits (qubits)…
cond-mat.mes-hall2025
Automated Charge Transition Detection in Quantum Dot Charge Stability Diagrams
Fabian Hader, Fabian Fuchs, Sarah Fleitmann +5
Gate-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 dia…
cond-mat.mes-hall2025
Simulation of Charge Stability Diagrams for Automated Tuning Solutions (SimCATS)
Fabian Hader, Sarah Fleitmann, Jan Vogelbruch +2
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 tun…