What would it take for APDs/SPADs to be viable in photonic quantum computing? Architecture redesign vs. device-level breakthroughs!!

I’ve been looking at the detector landscape for photonic quantum computing, and the momentum difference between SPADs/APDs and Superconducting Nanowire Single-Photon Detectors (SNSPDs) is striking. High-performance optical quantum computer setups overwhelmingly rely on SNSPDs due to near-unity PDE (>98%), negligible dark count rates, and sub-10 ps jitter. However, their sub-Kelvin cryogenic overhead is a massive bottleneck for deployment and scalability outside of specialised lab facilities. On the other hand, room-temperature or TE-cooled APDs/SPADs offer CMOS integration and compact footprints, but they carry severe trade-offs (after pulsing, lower PDE, higher DCR, and silicon's bandgap blind spot at telecom C/O-bands). For folks working on hardware, device physics, or quantum architectures: Do we need to rethink the whole system architecture? Can device-level improvements ever bridge the gap to meet strict fault-tolerance thresholds, or would adopting SPADs require fundamentally redesigning the quantum pipeline (e.g., higher-overhead QEC codes, hybrid dual-rail encoding, or frequency upconversion)? Where is the primary device bottleneck? Is the ceiling set by fundamental material physics (bandgap, impact ionisation noise, carrier lifetime), or are there solvable bottlenecks in waveguide integration, specialised doping profiles, and quench circuit topologies? Is device-level TCAD simulation still an open, high-impact frontier? Between 3D-stacked BSI, Ge-on-Si, and integrated waveguide designs, how much room is left to innovate at the device structure level versus standardising around mature foundry PDKs? I currently work on detector readout electronics and am evaluating whether pivoting toward device-level APD/SPAD TCAD simulation is a high-impact research direction for quantum hardware. Would love to hear your insights.Where do you think the biggest unsolved problems are? submitted by /u/amythetics [link] [comments]