Nonreciprocal phase shifts in a nonlinear periodic waveguide
Bibliographic record
Abstract
We explore nonreciprocal vibration transmission in a nonlinear periodic waveguide. Nonlinearity and asymmetry, the two necessary requirements for nonreciprocity, are both introduced within the unit cell of the periodic waveguide. We focus primarily on the contribution of phase to the nonreciprocal steady-state response of the system. To highlight the phase effects, which are rarely discussed in the literature, we investigate response regimes in which nonreciprocity is solely due to nonreciprocal phase shifts: when the locations of the source and receiver are interchanged, the amplitude of transmitted vibrations remains unchanged but the transmitted phases are not equal. We present a computational analysis of this state of phase nonreciprocity in the weakly nonlinear frequency-preserving response regime, where we characterize the response using its nonreciprocal phase shift. This allows us to systematically find a set of system parameters (including two symmetry-breaking parameters) that lead to reciprocal nonlinear response in a system with broken mirror symmetry. In other words, we show that breaking the mirror symmetry of a passive nonlinear waveguide is a necessary but insufficient condition for nonreciprocal dynamics to exist. Our findings highlight the important role of phase in nonlinear nonreciprocity and showcase the potential of asymmetry to serve as an additional design parameter.
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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 | 0.001 |
| 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".