A machine learning approach for automated fine-tuning of semiconductor spin qubits

While spin qubits based on gate-defined quantum dots have demonstrated very favorable properties for quantum computing, one remaining hurdle is the need to tune each of them into a good operating regime by adjusting the voltages applied to electrostatic gates. The automation of these tuning procedur...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Applied physics letters 2019-04, Vol.114 (13)
Hauptverfasser:	Teske, Julian D., Humpohl, Simon Sebastian, Otten, René, Bethke, Patrick, Cerfontaine, Pascal, Dedden, Jonas, Ludwig, Arne, Wieck, Andreas D., Bluhm, Hendrik
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied physics Automation Bayesian analysis Kalman filters Machine learning Microprocessors Quantum computing Quantum dots Quantum theory Qubits (quantum computing) Tuning
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!