Photon-level single-pixel 3D tomography with masked attention network.

Tomography plays an important role in characterizing the three-dimensional structure of samples within specialized scenarios. In the paper, a masked attention network is presented to eliminate interference from different layers of the sample, substantially enhancing the resolution for photon-level single-pixel tomographic imaging. The simulation and experimental results have demonstrated that the axial resolution and lateral resolution of the imaging system can be improved by about 3 and 2 times respectively, with a sampling rate of 3.0 %. The scheme is expected to be seamlessly integrated into various tomography systems, which is conducive to promoting the tomographic imaging for biology, medicine, and materials science.

Bayesian-Based Hybrid Method for Rapid Optimization of NV Center Sensors.

NV centers are among the most promising platforms in the field of quantum sensing. Magnetometry based on NV centers, especially, has achieved concrete development in areas of biomedicine and medical diagnostics. Improving the sensitivity of NV center sensors under wide inhomogeneous broadening and fieldamplitude drift is a crucial issue of continuous concern that relies on the coherent control of NV centers with high average fidelity. Quantum optimal control (QOC) methods provide access to this target; nevertheless, the high time consumption of current methods due to the large number of needful sample points as well as the complexity of the parameter space has hindered their usability. In this paper, we propose the Bayesian estimation phase-modulated (B-PM) method to tackle this problem. In the case of the state transforming of an NV center ensemble, the B-PM method reduced the time consumption by more than 90% compared with the conventional standard Fourier basis (SFB) method while increasing the average fidelity from 0.894 to 0.905. In the AC magnetometry scenario, the optimized control pulse obtained with the B-PM method achieved an eight-fold extension of coherence time T2 compared with the rectangular π pulse. Similar application can be made in other sensing situations. As a general algorithm, the B-PM method can be further extended to the open- and closed-loop optimization of complex systems based on a variety of quantum platforms.

Pulsed Quantum-State Reconstruction of Dark Systems.

We propose a novel strategy to reconstruct the quantum state of dark systems, i.e., degrees of freedom that are not directly accessible for measurement or control. Our scheme relies on the quantum control of a two-level probe that exerts a state-dependent potential on the dark system. Using a sequence of control pulses applied to the probe makes it possible to tailor the information one can obtain and, for example, allows us to reconstruct the density operator of a dark spin as well as the Wigner characteristic function of a harmonic oscillator. Because of the symmetry of the applied pulse sequence, this scheme is robust against slow noise on the probe. The proof-of-principle experiments are readily feasible in solid-state spins and trapped ions.