Probing the interlayer excitation dynamics in WS2/WSe2 heterostructures with broadly tunable pump and probe energies.

van der Waals heterostructures based on transition metal dichalcogenides (TMDs) provide a fascinating platform for exploring new physical phenomena and novel optoelectronic functionalities. Revealing the energy-dependence of photocarrier population dynamics in heterostructures is key for developing optoelectronic or valleytronic devices. Here, the broadband transient dynamics of interlayer excitation of a nearly-aligned WS2/WSe2 heterostructure is investigated by using energy-dependent pump-probe spectroscopy at cryogenic temperatures. Interestingly, WS2/WSe2 interlayer excitation, herein comprising a mixture of intra- and inter-layer excitons, exhibits largely constant lifetimes of a few hundred picoseconds across a broad energy range, in stark contrast to the salient energy-dependent dynamics of intralayer excitons in monolayer WSe2. While the PL emission of the WS2/WSe2 heterostructure is found to be strongly affected by electrostatic doping, the lifetimes of interlayer excitation show negligible changes. Our work elaborates the signatures of ultrafast dynamics introduced by intra- and interlayer co-existing excitonic species and enriches the understanding of interlayer couplings in van der Waals heterostructures.

A Resilient Method for Visual-Inertial Fusion Based on Covariance Tuning.

To improve localization and pose precision of visual-inertial simultaneous localization and mapping (viSLAM) in complex scenarios, it is necessary to tune the weights of the visual and inertial inputs during sensor fusion. To this end, we propose a resilient viSLAM algorithm based on covariance tuning. During back-end optimization of the viSLAM process, the unit-weight root-mean-square error (RMSE) of the visual reprojection and IMU preintegration in each optimization is computed to construct a covariance tuning function, producing a new covariance matrix. This is used to perform another round of nonlinear optimization, effectively improving pose and localization precision without closed-loop detection. In the validation experiment, our algorithm outperformed the OKVIS, R-VIO, and VINS-Mono open-source viSLAM frameworks in pose and localization precision on the EuRoc dataset, at all difficulty levels.