The chopped random basis (CRAB) ansatz for quantum optimal control has been proven to be a versatile tool to enable quantum technology applications such as quantum computing, quantum simulation, quantum sensing, and quantum communication. Its capability to encompass experimental constraints—while maintaining an access to the usually trap-free control landscape—and to switch from open-loop to closed-loop optimization (including with remote access—or RedCRAB) is contributing to the development of quantum technology on many different physical platforms. In this review article we present the development, the theoretical basis and the toolbox for this optimization algorithm, as well as an overview of the broad range of different theoretical and experimental applications that exploit this powerful technique.

We propose a protocol to estimate magnetic fields using a single nitrogen-vacancy (N-V) center in diamond, where the estimate precision scales inversely with time, $\delta${}B~1/T, rather than the square-root of time, $\delta${}B~1/T. The method is based on converting the task of magnetometry into phase estimation, performing quantum phase estimation on a single N-V nuclear spin using either adaptive or nonadaptive feedback control, and the recently demonstrated capability to perform single-shot readout within the N-V [P. Neumann et al., Science 329, 542 (2010)]. We present numerical simulations to show that our method provides an estimate whose precision scales close to ~1/T (T~ the total estimation time), and moreover will give an unambiguous estimate of the static magnetic field experienced by the N-V. By combining this protocol with recent proposals for scanning magnetometry using an N-V, our protocol will provide a significant decrease in signal acquisition time while providing an unambiguous spatial map of the magnetic field.

We apply the concept of quantum speed limit (QSL)—the minimal time needed to perform a driven evolution—to complex interacting many-body systems where the effects of interactions have to be taken into account. We introduce a general strategy to eliminate the detrimental effects of the interparticle repulsion and drive the system at the QSL by applying a compensating control pulse (CCP). To prove the principles we consider a prototypical many-body system, a bosonic Josephson junction, and investigate a transfer of atoms from the ground state of one well to the ground state of the neighboring well, at increasing levels of complexity—from a textbook two-level approximation to full many-body treatment. By tracing the efficiency of the CCP protocol we show that the driven dynamics does follow the geodetic pathway and, therefore, it is optimal. The CCP strategy, applicable for a general interacting quantum many-body system with strong driving, can be of a practical relevance for the experimental implementation of quantum technology protocols, as quantum simulations or matter-wave metrology.

Fully autonomous precise control of qubits is crucial for quantum information processing, quantum communication, and quantum sensing applications. It requires minimal human intervention on the ability to model, to predict, and to anticipate the quantum dynamics, as well as to precisely control and calibrate single qubit operations. Here, we demonstrate single qubit autonomous calibrations via closed-loop optimisations of electron spin quantum operations in diamond. The operations are examined by quantum state and process tomographic measurements at room temperature, and their performances against systematic errors are iteratively rectified by an optimal pulse engineering algorithm. We achieve an autonomous calibrated fidelity up to 1.00 on a time scale of minutes for a spin population inversion and up to 0.98 on a time scale of hours for a single qubit $$\frac{\pi }{2}$$π 2 -rotation within the experimental error of 2%. These results manifest a full potential for versatile quantum technologies.