A low-power low-noise CMOS charge-sensitive amplifier for capacitive detectors
Bibliographic record
Abstract
In this paper, the design of a new low-power low-noise charge-sensitive amplifier (CSA) is presented. The proposed CSA is intended for capacitive sensor readout circuits such as interface circuits for solid-state detectors used in medical imaging and X-ray spectroscopy. A comprehensive noise analysis of readout systems that consist of a CSA followed by an RC-CR pulse shaper is presented. To facilitate predicting the noise behaviour of the system, the equivalent noise charge (ENC) equations are derived analytically. The readout circuit is designed and laid out in a 0.13-μm CMOS process. Post-layout simulations show that the conversion gain of the CSA with a 20 fF feedback capacitor is 37.5 mV/fC. The estimated ENC of the readout system is 38 e̅-rms at a 1 μs peaking time with a detector capacitance of 0.5 pF and a leakage current of 50 pA. The integral nonlinearity of the CSA is less than 0.74% for 0.5-3 ke̅. The open-loop gain of the amplifier is ~ 80 dB and the gain-bandwidth product is about 345 MHz. The CSA occupies 0.0021 mm2and consumes 37.5 μW from a 1.2 V supply.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".