Fast and high-yield fabrication of axially symmetric ion-trap needle electrodes via two step electrochemical etching
Bibliographic record
Abstract
Despite the progress in building sophisticated microfabricated ion traps, Paul traps employing needle electrodes retain their significance due to the simplicity of fabrication while producing high-quality systems suitable for quantum information processing, atomic clocks, etc. For low noise operations such as minimizing "excess micromotion," needles should be geometrically straight and aligned precisely with respect to each other. Self-terminated electrochemical etching, previously employed for fabricating ion-trap needle electrodes, employs a sensitive and time-consuming technique, resulting in a low success rate of usable electrodes. Here, we demonstrate an etching technique for the quick fabrication of straight and symmetric needles with a high success rate and a simple apparatus with reduced sensitivity to alignment imperfections. The novelty of our technique comes from using a two-step approach employing turbulent etching for fast shaping and slow etching/polishing for subsequent surface finish and tip cleaning. Using this technique, needle electrodes for an ion trap can be fabricated within a day, significantly reducing the setup time for a new apparatus. The needles fabricated via this technique have been used in our ion trap to achieve trapping lifetimes of several months.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".