Passband flattened binary-tree structured add-drop multiplexers using sion waveguide technology
Bibliographic record
Abstract
When writing this introduction I saw the following press release on the Internet: “Nielsen//Netratings reports a record half billion people worldwide now have home internet access‿. The number of home users grew worldwide with 5 % over the last quarter of 2001. The growth was nearly doubled compared to Q3 2001. The growth in Europe was 4.9%, almost equal to the world growth. One in three households in Europe/Middle East and Africa have Internet access, compared with over half in the US. The Netherlands has 52 % of the households connected to the Internet and 82 % of the computers is connected to the Internet. Another press release also fromNielsen//Netratings was titled as “Broadband Usage Outpaces Narrowband for the first time.‿ 1.19 billion of the total 2.3 billion hours was spent by broadband surfers online in January 2002 in the US. The broadband time spent in January 2002 was 64 % higher than in January 2001. Nearly 21.9 million surfers (in the US) at-home accessed the Internet via broadband connection in January 2002 compared to 13.1 million in January 2001, a boost of 67% in one year time. So there is an unstoppable march towards broadband. (See www.nielsen-netratings.com) This demand can be fulfilled with the tremendous bandwidth of the optical fiber of 30 THz (1420-1670 nm). It is not possible to directly address this complete band, since the current maximum speed of the electronics and modulators is 40-100 GHZ. Wavelength division multiplexing (WDM) is used to divide the band in multiple sub bands. The spacing between the sub band channels is defined by the ITU grid. Common spacings between channels are 12.5, 25, 50, 100 and 200 GHz. The device that combines these channels onto one fiber is called a Multiplexer (Mux) and the device that does the opposite, spatial separation of frequency channels onto different fibers, is called a demultiplexer (Demux). When Mux and Demux are combined it is possible to select only one (or more) channel to be dropped or added and leaving the remaining channels undisturbed. Such a device is called an Add-drop multiplexer(ADM). Optical transmission systems 3.28 Tbit/s over a few hundred of kilometers[Nielsen 2000] or 2 Tbit/s over almost ten thousand kilometers [Yamada 2002] have already be reported.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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 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".