We report on the design, fabrication, and characterization of a Silicon Nitride (SiN)-based integrated photonic chip in which the dielectric waveguides are coupled to photodetectors integrated homogeneously into the Silicon substrate. The photonic-electronic coupling was realized by a 3D inverse tapering of SiN waveguides. The novelty of our approach consists in tapering the waveguide in the vertical direction by means of an engineered wet chemical etching. This allows for a smooth transition from a full-height to an arbitrarily thin waveguide thickness at the detector location, expanding adiabatically the optical mode towards the latter. The measured chips showed a responsivity $R\approx 109~\mu$A/mW and a corresponding quantum efficiency of 16% at an excitation wavelength of 850 nm. Our technological solution offers a versatile method for a top-down monolithic integration of lightwave circuitries with substrate-located photon sensing devices.

Photonic Integrated Chips (PICs) are an up-and-coming solution for base building blocks of quantum computers. The ready accessibility of photonics integrated systems and the fact that they allow for direct monolithic integration with electronics in a compact architecture have pushed the academic community to inspect their capabilities further. Still, at this stage, their characterization, control, and fine-tuning is an open issue for which this work aims to provide a viable solution. In this paper we present a method for an easy setup and an efficient architecture to simultaneously optimize multiple outputs of a PIC. The proposed solution can be embedded in an automation tool for tuning and verifying output on- and off-chip detectors. We fabricated a Silicon Oxynitride (SiON)-based PIC featuring a network of Mach-Zehnder interferometers (MZI) arranged in Clements architecture driven by Titanium-Titanium Nitride (TiTiN) thermistors. We interfaced the chip electronically through commercial driver modules and optically through optical guides and controlled it through a Python optimization algorithm. Finally, we retrieved the feedback of the control both by sensing it through integrated silicon photodetectors and by an image processing algorithm capable of inspecting the light intensity scattered by the waveguides in a custom region.