Low-Noise, High-Gain Transimpedance Amplifier Integrated With SiAPD for Low-Intensity Near-Infrared Light Detection
Bibliographic record
Abstract
A fully integrated near-infrared spectroscopy photoreceiver including two new silicon avalanche photodiodes (SiAPDs) and a new transimpedance amplifier (TIA) is proposed in this paper. SiAPDs are designed in p+/n-well structure with guard-rings realized in different shapes. The TIA front-end has been designed using distributed-gain concept combined with resistive-feedback and common-gate topology to reach low-noise, low-power consumption, high gain-bandwidth product characteristics and it is robust against power-supply variation (1-3 V). This circuit is developed using 0.35 μm CMOS technology and the measurement results are compared with other results from the literature. The designed rectangular and octagonal SiAPDs have the avalanche gain of 100 and 45 with the breakdown voltage of 9 and 6 V and the photon absorption efficiency of 45% and 25% at 800 nm. Fabricated TIA offers high-transimpedance gain (up to 250 MV/A), tunable BW (1 kHz-1 GHz), extremely low input and output noises (100 fA/√Hz, 1.8 μV/√Hz), and low-power consumption (0.8 mW). The impact and effects of on-chip integration of SiAPD and TIA front-end have been also measured and evaluated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".