Superconducting Coupler with Exponentially Large On:Off Ratio
Bibliographic record
Abstract
Tunable two-qubit couplers offer an avenue to mitigate errors in multiqubit superconducting quantum processors. However, most couplers operate in a narrow frequency band and target specific couplings, such as the spurious $ZZ$ interaction. We introduce a superconducting coupler that alleviates these limitations by suppressing all two-qubit interactions with an exponentially large on-off ratio and without the need for fine-tuning. Our approach is based on a bus mode supplemented by an ancillary nonlinear resonator mode. Driving the ancillary mode leads to a coupler-state-dependent field displacement in the resonator which, in turn, results in an exponential suppression of real and virtual two-qubit interactions with respect to the drive power. A superconducting circuit implementation supporting the proposed mechanism is presented.
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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 | 0.001 |
| 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".