RESUMO
Semiconductor quantum dot molecules are considered promising candidates for quantum technological applications due to their wide tunability of optical properties and coverage of different energy scales associated with charge and spin physics. While previous works have studied the tunnel-coupling of the different excitonic charge complexes shared by the two quantum dots by conventional optical spectroscopy, we here report on the first demonstration of a coherently controlled interdot tunnel-coupling focusing on the quantum coherence of the optically active trion transitions. We employ ultrafast four-wave mixing spectroscopy to resonantly generate a quantum coherence in one trion complex, transfer it to and probe it in another trion configuration. With the help of theoretical modeling on different levels of complexity, we give an instructive explanation of the underlying coupling mechanism and dynamical processes.
RESUMO
We discuss the coupling efficiency of single-photon sources into single-mode fibers using 3D printed micro-optical lens designs. Using the wave propagation method, we optimize lens systems for two different quantum light sources and assess the results in terms of maximum coupling efficiencies, misalignment effects, and thermo-optical influences. Thereby, we compare singlet lens designs with one lens printed onto the fiber with doublet lens designs with an additional lens printed onto the semiconductor substrate. The single-photon sources are quantum dots based on microlenses and circular Bragg grating cavities at 930 nm and 1550 nm, respectively.
RESUMO
We perform extended numerical studies to maximize the overall photon coupling efficiency of fiber-coupled quantum dot single-photon sources emitting in the near-infrared and O-band and C-band. Using the finite element method, we optimize the photon extraction and fiber-coupling efficiency of quantum dot single-photon sources based on micromesas, microlenses, circular Bragg grating cavities and micropillars. The numerical simulations which consider the entire system consisting of the quantum dot source itself, the coupling lens, and the single-mode fiber, yield overall photon coupling efficiencies of up to 83%. Our work provides objectified comparability of different fiber-coupled single-photon sources and proposes optimized geometries for the realization of practical and highly efficient quantum dot single-photon sources.
RESUMO
We report on the deterministic fabrication of quantum devices aided by machine-learning-based image processing. The goal of the work is to demonstrate that pattern recognition based on specifically trained machine learning (ML) algorithms and applying it to luminescence maps can strongly enhance the capabilities of modern fabrication technologies that rely on a precise determination of the positions of quantum emitters like, for instance, in situ lithography techniques. In the present case, we apply in situ electron beam lithography (EBL) to deterministically integrate single InGaAs quantum dots (QDs) into circular Bragg grating resonators with increased photon extraction efficiency (PEE). In this nanotechnology platform, suitable QDs are selected by 2D cathodoluminescence maps before EBL of the nanoresonators aligned to the selected emitters is performed. Varying the electron beam dose of cathodoluminescence (CL) mapping, we intentionally change the signal-to-noise ratio of the CL maps to mimic different brightness of the emitters and to train the ML algorithm. ML-based image processing is then used to denoise the images for reliable and accurate QD position retrieval. This way, we achieve a significant enhancement in the PEE and position accuracy, leading to more than one order increase of sensitivity in ML-enhanced in situ EBL. Overall, this demonstrates the high potential of ML-based image processing in deterministic nanofabrication which can be very attractive for the fabrication of bright quantum light sources based on emitters with low luminescence yield in the future.
