  State preparation and measurement errors are commonly regarded as
indistinguishable. The problem of distinguishing state preparation (SPAM)
errors from measurement errors is important to the field of characterizing
quantum processors. In this work, we propose a method to separately
characterize SPAM errors using a novel type of algorithmic cooling protocol
called measurement-based algorithmic cooling (MBAC). MBAC assumes the ability
to perform (potentially imperfect) projective measurements on individual
qubits, which is available on many modern quantum processors. We demonstrate
that MBAC can significantly reduce state preparation error under realistic
assumptions, with a small overhead that can be upper bounded by measurable
quantities. Thus, MBAC can be a valuable tool not only for benchmarking
near-term quantum processors, but also for improving the performance of quantum
processors in an algorithmic manner.
