Simplified time-lens based system configuration for transform-limited real-time Fourier transformation of optical pulses
Bibliographic record
Abstract
We demonstrate that a time lens (quadratic phase temporal modulator) followed by a dispersive device can be used to implement real-time Fourier transformation (RTFT) of temporal optical pulses without introducing any additional temporal phase distortion. In this so-called transform-limited RTFT operation, the time and frequency domains are fully interchanged from the input to the output of the device; in other words, the temporal waveform of the pulse at the output of the device is a replica of the input energy spectrum and at the same time, the output energy spectrum is proportional to the temporal intensity shape of the input signal. As compared with the conventional methods, the proposed configuration does not require the use of an input dispersive device preceding the time lens, thus resulting in a much simpler and more practical alternative for implementing transform-limited RTFT of optical signals. Transform-limited RTFT has enormous application in optical signal processing especially for reconfigurable, ultra-fast pulse filtering in the all-optical domain. Ultrafast optical pulse filtering enables other important optical pulse processing operations, such as all-optical temporal correlations or convolutions. We propose and analyze a novel ultra-fast optical pulse filtering design based on the above-simplified configuration for transform-limited RTFT. In this proposed filtering configuration, the time lens process is implemented using a phase electro-optic modulator driven by a RF tone. Our proposal results in a much more compact and practical design than the conventional 4-f ultra-fast optical pulse filtering system. We further carried out the analytical study of the proposed filtering system and demonstrated its simplicity and feasibility.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".