Design and Analysis of a Low-Power Readout Circuit for CdZnTe Detectors in 0.13-$\mu \text{m}$ CMOS
Bibliographic record
Abstract
In this paper, the design of a low-power low-noise readout circuit for cadmium zinc telluride (CdZnTe or CZT) detectors is presented. Such sensors are used in a variety of applications, including medical imaging, security, and astrophysics. The readout circuit includes a charge-sensitive amplifier (CSA), a reset network to accommodate the leakage current of the detector, and a first-order pulse shaper with a pole-zero cancellation circuit. The CSA has two gain settings for 0-5and 5-45-fC injected charge, and the pulse shaper is designed to provide four different shaping times. The discharge time constant of the CSA can also be adjusted to accommodate various event rates. Furthermore, a comprehensive noise analysis of the readout system is presented. To facilitate the noise analysis, the equivalent noise charge (ENC) equations are derived analytically. The optimization of the noise performance of the front-end circuit is also discussed. The application-specific integrated circuit is fabricated in a 0.13-μm CMOS process. For a detector capacitance of 250 fF, the measured ENC varies from 66 to 101 e̅-rms depending on the peaking time. The measured power consumption of the readout circuit is just under 1 mW 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".