Automated tuning and characterization of single-electron and single-hole transistor charge sensors
Bibliographic record
Abstract
We present an automated protocol for tuning single-electron transistors (SETs) and single-hole transistors (SHTs) to operate as high-sensitivity DC charge sensors. The protocol initializes a previously unmeasured device after cooldown, identifies a working point in barrier-gate space, and selects and ranks charge-sensing operating points. It further automates the acquisition and analysis of Coulomb diamonds to extract sensor-relevant parameters, including lever arm, charging energy, gate and source/drain capacitances, and estimated dot radius. We demonstrate the protocol on accumulation-mode silicon MOS SET and SHT devices operated at 1.5 K and $\approx 50$ mK, respectively, establishing ambipolar applicability across a wide temperature range. Operation at 1.5 K indicates that charge sensing in compact MOS devices is feasible in the 1-2 K regime, supporting higher-temperature readout relevant to scalable spin-qubit architectures. Compared to manual tuning, automation reduces operator overhead and provides consistent device characterization, with clear pathways for further speedups and improved robustness via faster electronics and feedback-based stabilization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".