Robust optical physical unclonable function using disordered photonic integrated circuits
Bibliographic record
Abstract
Abstract Physical unclonable function (PUF) has emerged as a promising and important security primitive for use in modern systems and devices, due to their increasingly embedded, distributed, unsupervised, and physically exposed nature. However, optical PUFs based on speckle patterns, chaos, or ‘strong’ disorder are so far notoriously sensitive to probing and/or environmental variations. Here we report an optical PUF designed for robustness against fluctuations in optical angular/spatial alignment, polarization, and temperature. This is achieved using an integrated quasicrystal interferometer (QCI) which sensitively probes disorder while: (1) ensuring all modes are engineered to exhibit approximately the same confinement factor in the predominant thermo‐optic medium (e. g. silicon), and (2) constraining the transverse spatial‐mode and polarization degrees of freedom. This demonstration unveils a new means for amplifying and harnessing the effects of ‘weak’ disorder in photonics and is an important and enabling step toward new generations of optics‐enabled hardware and information security devices.
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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 | 0.001 | 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".