Insertable system for fast turnaround time microwave experiments in a dilution refrigerator
Bibliographic record
Abstract
Microwave experiments in dilution refrigerators are a central tool in the field of superconducting quantum circuits and other research areas. This type of experiments relied so far on attaching a device to the mixing chamber of a dilution refrigerator. The minimum turnaround time in this case is a few days as required by cooling down and warming up the entire refrigerator. We developed a new approach, in which a suitable sample holder is attached to a cold-insertable probe and brought in contact with transmission lines permanently mounted inside the cryostat. The total turnaround time is 8 h if the target temperature is 80 mK. The lowest attainable temperature is 30 mK. Our system can accommodate up to six transmission lines, with a measurement bandwidth tested from zero frequency to 12 GHz. This bandwidth is limited by low-pass components in the setup; we expect the intrinsic bandwidth to be at least 18 GHz. We present our setup, discuss the experimental procedure, and give examples of experiments enabled by this system. This new measurement method will have a major impact on systematic ultra-low temperature studies using microwave signals, including those requiring quantum coherence.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".