  Quantum computing uses quantum resources provided by the underlying quantum
nature of matter to enhance classical computation. However, the current Noisy
Intermediate-Scale Quantum (NISQ) era in quantum computing is characterized by
the use of quantum processors comprising from a few tens to, at most, a few
hundreds of physical qubits without implementing quantum error correction
techniques. This limits the scalability in the implementation of quantum
algorithms. Digital-analog quantum computing (DAQC) has been proposed as a more
resilient alternative quantum computing paradigm to outperform digital quantum
computation within the NISQ era framework. It arises from adding the
flexibility provided by fast single-qubit gates to the robustness of analog
quantum simulations. Here, we perform a careful comparison between the digital
and digital-analog paradigms under the presence of noise sources. The
comparison is illustrated by comparing the performance of the quantum Fourier
transform and quantum phase estimation algorithms under a wide range of single-
and two-qubit noise sources. Indeed, we obtain that when the different noise
channels usually present in superconducting quantum processors are considered,
the fidelity of these algorithms for the digital-analog paradigm outperforms
the one obtained for the digital approach. Additionally, this difference grows
when the size of the processor scales up, making DAQC a sensible alternative
paradigm in the NISQ era. Finally, we show how to adapt the DAQC paradigm to
quantum error mitigation techniques for canceling different noise sources,
including the bang error.
