Pseudo-planar Ge-on-Si Single-photon Avalanche Diode Detector with Record Low Noise-equivalent Power

Autor: Millar, Ross W., Kirdoda, Jaroslaw, Thorburn, Fiona, Yi, Xin, Greener, Zoë M., Huddleston, Laura, Benakaprasad, Bhavana, Watson, Scott, Coughlan, Conor, Buller, Gerald S., Paul, Douglas J.
Jazyk: angličtina
Rok vydání: 2021
ISSN: 0277-786X
Popis: Single-photon avalanche diode (SPAD) detectors are of significant interest for numerous applications, including light detection and ranging (LIDAR), and quantum technologies such as quantum-key distribution and quantum information processing. Here we present a record low noise-equivalent-power (NEP) for Ge-on-Si SPADs using a pseudo-planar design, showing high detection efficiency in the short-wave infrared; a spectral region which is key for quantum technologies and hugely beneficial for LIDAR. These devices can leverage the benefits of Si avalanche layers, with lower afterpulsing compared to InGaAs/InP, and reduced cost due to Si foundry compatibility. By scaling the SPAD pixels down to 26μm diameter, a step change in performance has been demonstrated, with significantly reduced dark count rates (DCRs), and low jitter (134ps). Ge-on-Si SPADs were fabricated using photolithography techniques and characterised using time-correlated single-photon counting. The DCR reaches as low as kilocount/s at 100K for excess bias up to ~5%. This reduction in DCR enables higher temperature operation; e.g. the DCR of a 26μm diameter pixel at 150 K is approximately equivalent to a 100 μm diameter pixel at 77 K (100s of kilocounts/s). These low values of DCR, coupled with the relatively temperature independent single photon detection efficiencies (SPDE) of ~29% (at 1310nm wavelength) leads to a record low NEP of 7.7×10−17WHz−1/2. This is approximately 2 orders of magnitude lower than previous similarly sized mesa-geometry Ge-on-Si SPADs. This technology can potentially offer a lowcost, Si foundry compatible SPAD operating at short-wave infrared wavelengths, with potential applications in quantum technologies and autonomous vehicle LIDAR.
Databáze: OpenAIRE