Multifrequential periodogram analysis of earthquake occurrence: An alternative approach to the Schuster spectrum, with two examples in central California
Bibliographic record
Abstract
Abstract Periodic earthquake occurrences may reflect links with semidiurnal to multiyear tides, seasonal hydrological loads, and ~14 month pole tide forcing. The Schuster spectrum is a recent extension of Schuster's traditional test for periodicity analysis in seismology. We present an alternative approach: the multifrequential periodogram analysis (MFPA), performed on time series of monthly earthquake numbers. We explore if seismicity in two central California regions, the Central San Andreas Fault near Parkfield (CSAF‐PKD) and the Sierra Nevada‐Eastern California Shear Zone (SN‐ECSZ), exhibits periodic behavior at periods of 2 months to several years. Original and declustered catalogs spanning up to 26 years were analyzed with both methods. For CSAF‐PKD, the MFPA resolves ~1 year periodicities, with additional statistically significant periods of ~6 and ~4 months; for SN‐ECSZ, it finds a strong ~14 month periodic component. Unlike the Schuster spectrum, the MFPA has an exact modified statistic at non‐Fourier frequencies. Informed by the MFPA period estimates, trigonometric models with periods of 12, 6, and 4 months (Model 1) and 14.24 and 12 months (Model 2) were fitted to time series of earthquake numbers. For CSAF‐PKD, Model 1 shows a peak annual earthquake occurrence during August‐November and a secondary peak in April. Similar peaks, or troughs, are found in annual and semiannual components of pole tide and tide‐induced stress model time series and fault normal‐stress reduction from seasonal hydrological unloading. For SN‐ECSZ, the dominant ~14 month periodicity prevents regular annual peaking, and Model 2 provides a better fit (Δ : 2.4%). This new MFPA application resolves several periodicities in earthquake catalogs that reveal external periodic forcing.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".