Experimental Investigations on Nonlinear Properties of Superconducting Nanowire Meanderline in RF and Microwave Frequencies
Bibliographic record
Abstract
We report our experimental investigations on the radio frequency (RF) and microwave nonlinear behavior of the NbN nanowire meanderline. We construct a lumped element model of the NbN nanowire meanderline, which consists of a kinetic inductance, a normal resistance, and a parasitic capacitance that is a load of a transmission line. Two complementary measurements, which are based on the one-port scattering (S)-parameter technique, are used to explore the nonlinearity in the kinetic inductance and the normal resistance of the NbN nanowire meanderline under dc current and voltage bias conditions. In the first series of experiments, the kinetic inductance has directly been measured from zero up to 99% of the critical current and to the voltage bias, where the hotspot plateau occurs. The Ginsburg-Landau (G-L) theory has been employed to justify the results. The technical procedures required to achieve our desired level of accuracy have been described in detail. In the second series of experiments, the quality factor of the NbN nanowire meanderline has been measured, providing an alternative justification to the first experimental results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".