THE DISCOVERY OF PERIODIC MODULATIONS IN THE OPTICAL SPECTRA OF GALAXIES, POSSIBLY DUE TO ULTRARAPID LIGHT BURSTS FROM THEIR MASSIVE CENTRAL BLACK HOLES
Bibliographic record
Abstract
A Fourier transform analysis of 2.5 million spectra in the SDSS survey was carried out to detect periodic modulations contained in the intensity versus frequency spectrum. A statistically significant signal was found for 223 galaxies, while the spectra of 0.9 million galaxies were observed. A plot of the periods as a function of redshift clearly shows that the effect is real without any doubt, because the modulations are quantized at two base periods that increase with redshift in two very tight parallel linear relations. We suggest that this result could be caused by light bursts separated by times on the order of 10 −13 s, but other causes may be possible. We investigate the hypothesis that the modulation is generated by the Fourier transform of spectral lines, but conclude that this hypothesis is not valid. Although the light burst suggestion implies absurdly high temperatures, it is supported by the fact that the Crab pulsar also has extremely short unresolved pulses (<0.5 ns) that imply similarly high temperatures. Furthermore, the radio spectrum of the Crab pulsar also has spectral bands similar to those that have been detected. Finally, decreasing the signal-to-noise threshold of detection gives results consistent with beamed signals having a small beam divergence, as expected from non-thermal sources that send a jet, like those seen in pulsars. Considering that galaxy centers contain massive black holes, exotic black hole physics may be responsible for the spectral modulation. However, at this stage, this idea is only a hypothesis to be confirmed with further work.
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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 | 0.001 | 0.001 |
| 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 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".