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Data-driven learning of non-Markovian quantum dynamics
Samuel Goodwin, Brian K. McFarland, Manuel H. Muñoz-Arias +6
Fault-tolerant quantum computing requires extremely precise knowledge and control of qubit dynamics during the application of a gate. We develop a data-driven learning protocol for…
Realization and Calibration of Continuously Parameterized Two-Qubit Gates on a Trapped-Ion Quantum Processor
Christopher G. Yale, Ashlyn D. Burch, Matthew N. H. Chow +5
Continuously parameterized two-qubit gates are a key feature of state-of-the-art trapped-ion quantum processors as they have favorable error scalings and show distinct improvements…
Noise-Aware Circuit Compilations for a Continuously Parameterized Two-Qubit Gateset
Christopher G. Yale, Rich Rines, Victory Omole +9
State-of-the-art noisy-intermediate-scale quantum (NISQ) processors are currently implemented across a variety of hardware platforms, each with their own distinct gatesets. As such…
Frequency-robust Mølmer-Sørensen gates via balanced contributions of multiple motional modes
Brandon P. Ruzic, Matthew N. H. Chow, Ashlyn D. Burch +5
In this work, we design and implement frequency-robust Molmer-Sorensen gates on a linear chain of trapped ions, using Gaussian amplitude modulation and a constant laser frequency.…
Detecting and tracking drift in quantum information processors
Timothy Proctor, Melissa Revelle, Erik Nielsen +5
If quantum information processors are to fulfill their potential, the diverse errors that affect them must be understood and suppressed. But errors typically fluctuate over time, a…