  Quantum sensing is considered to be one of the most promising subfields of
quantum information to deliver practical quantum advantages in real-world
applications. However, its impressive capabilities, including high sensitivity,
are often hindered by the limited quantum resources available. Here, we
incorporate the expected information gain (EIG) and techniques such as
accelerated computation into Bayesian experimental design (BED) in order to use
quantum resources more efficiently. A simulated nitrogen-vacancy center in
diamond is used to demonstrate real-time operation of the BED. Instead of
heuristics, the EIG is used to choose optimal control parameters in real-time.
Moreover, combining the BED with accelerated computation and asynchronous
operations, we find that up to a tenfold speed-up in absolute time cost can be
achieved in sensing multiple surrounding C13 nuclear spins. Our work explores
the possibilities of applying the EIG to BED-based quantum-sensing tasks and
provides techniques useful to integrate BED into more generalized quantum
sensing systems.
