Why this work is in the frame
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Bibliographic record
Abstract
Parametric converters are parametric amplifiers that mix two spatially separate nondegenerate modes and are commonly used for amplifying and squeezing microwave signals in quantum computing and sensing. In Josephson parametric converters, the strong localized nonlinearity of the Josephson junction limits the amplification and squeezing, as well as the dynamic range, in current devices. In contrast, a weak distributed nonlinearity can provide higher gain and dynamic range, when implemented as a kinetic inductance (KI) nanowire of a dirty superconductor, and has additional benefits such as resilience to magnetic field, higher-temperature operation, and simplified fabrication. Here, we propose, demonstrate, and analyze the performance of a KI parametric converter that relies on the weak distributed nonlinearity of a Nb-Ti-N KI nanowire. The device utilizes three-wave mixing induced by a dc current bias. We demonstrate its operation as a nondegenerate parametric amplifier with high phase-sensitive gain, reaching two-mode amplification and deamplification of approximately 30 dB for two resonances separated by 0.8 GHz, in excellent agreement with our theory of the device. We observe a dynamic range of $\ensuremath{-}108$ dBm at 30 dB gain. Our device can significantly broaden applications of quantum-limited signal processing devices including phase-preserving amplification and two-mode squeezing.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it