  The performance of a quantum processor depends on the characteristics of the
device and the quality of the control pulses. Characterizing cloud-based
quantum computers and calibrating the pulses that control them is necessary for
high-fidelity operations. However, this time intensive task eats into the
availability of the device. Here, we show restless measurements with a dynamic
repetition rate that speed-up calibration and characterization tasks.
Randomized benchmarking is performed 5.3 times faster on the quantum device
than when an active reset is used and without discarding any data. In addition,
we calibrate a qubit with parameter scans and error-amplifying gate sequences
and show speed-ups of up to a factor of forty on the quantum device over active
reset. Finally, we present a methodology to perform restless quantum process
tomography that mitigates restless state preparation errors. These results
reduce the footprint of characterization and calibration tasks. Quantum
computers can thus either spend more time running applications or run
calibrations more often to maintain gate fidelity.
