Bibliographic record
Abstract
Summary form only given. An all-optical logic NOT gate is a basic building block for implementation of all-optical shift registers, packet header processing, bit-error monitoring etc. A passive NOT gate based on spectral phase-only linear optical filtering of an input return to zero on-off-keying (RZ-OOK) data signal was first proposed and demonstrated in [1]. This gate requires no energy for switching and it is compatible with ultrafast speed processing. In [1], a commercial waveshaper was used to implement the needed spectral phase-only filter. However, commercial waveshapers are bulky, expensive and offer a limited frequency resolution (> 10 GHz), which in turn imposes a severe constraint on the minimum bit rate of the data signals (typically above 640 Gb/s for random data). To this end, we propose a fibre Bragg grating (FBG) design to achieve narrow spectral phase filters for NOT gate operation of RZ-OOK data. In the design reported here, we assume an incoming data signal at 80 Gbps with a PRBS of 27-1 bits and 5-ps FWHM Gaussian pulses. As discussed in [1], a passive NOT gate can be realized by simply π phase shifting the clock frequency components of the RZ-OOK data signal. The target reflective intensity spectral response is bandlimited, and it follows an 8-order super-Gaussian function with a peak reflectivity of 90 % and a 3-dB bandwidth (BW) of 300 GHz, the associated phase response consists of three Gaussian components, each with peak amplitude of π rad and a 3-dB BW of 0.5 GHz, separated by an FSR of 80 GHz (equal to the bit rate). An inverse layer peeling algorithm is used to extract the complex coupling coefficient profile for this target spectral response. The resulting grating apodization profile is shown in Fig. 1-(a). The inset shows the zoomed-in central portion of the profile. As can be inferred from the profile, a large dynamic range in apodization is required to achieve such a complex spectral response, which is difficult to realize using conventional amplitude apodization schemes [2]. However, this complex coupling coefficient profile can be physically realized by locally modulating the grating period using a phase-only modulation apodization technique [3]. In this technique, the local apodization is achieved by adding a slow periodic modulation function along the phase function of the grating. Compared to traditional amplitude apodization, this method is highly robust to fabrication errors as the refractive index variation remains constant along the grating length. i.e. 5×10-3is considered in our design. Fig. 1-(b) shows the local chirp (grating period variation relative to the central grating period) around the centre of the FBG of total length 21 cm. Fig. 1-(c) shows the amplitude spectral response (left) and phase response (right) of the designed FBG. Linear phase variation is cancelled out for better representation of the phase profiles. The simulated input and output temporal waveforms are shown in Fig. 1-(d). The results clearly show inversion of the input data signal.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".