4 citations · 5 across the 6 of their papers we have counts for
5 papers · 1 filter
Adaptive Spectroscopy of Fast Two-Level-System Dynamics in Superconducting Qubits
Fabrizio Berritta, David Pahl, Lukas Pahl +15
Parasitic two-level-system (TLS) defects are a major source of energy relaxation and temporal instability in superconducting quantum processors. Our sub-second adaptive spectroscop…
Evidence of Quantum Machine Learning Advantage with Tens of Noisy Qubits
Onur Danaci, Yash J. Patel, Riccardo Molteni +3
Learning problems involving quantum data are natural candidates for demonstrating an advantage in quantum machine learning. Recent results indicate that, for certain tasks and unde…
Operating a bistable qubit
Fabrizio Berritta, Jan A. Krzywda, Tom Dvir +4
Parasitic two-level-system (TLS) defects limit the stability and performance of solid-state quantum processors. Their interaction with a qubit can cause discrete, stochastic shifts…
Real-time adaptive tracking of fluctuating relaxation rates in superconducting qubits
Fabrizio Berritta, Jacob Benestad, Jan A. Krzywda +17
The fidelity of operations on a solid-state quantum processor is fundamentally bounded by environmental decoherence. Characterizing environmental fluctuations is challenging becaus…
Efficient Qubit Calibration by Binary-Search Hamiltonian Tracking
Fabrizio Berritta, Jacob Benestad, Lukas Pahl +14
We present and experimentally implement a real-time protocol for calibrating the frequency of a resonantly driven qubit, achieving exponential scaling in calibration precision with…