coincidence_delay — ONED `matched` op

• Data kinds: signal × signal → table

• Call: import fullseye as fs; fs.ledger.coincidence_delay(snr_a, snr_b, rate: 'float' = 4096.0, *, max_delay_s: 'float' = 0.01) -> 'dict' (to call the implementation directly, import gwsearch; gwsearch.coincidence_delay(snr_a, snr_b, rate: 'float' = 4096.0, *, max_delay_s: 'float' = 0.01) -> 'dict'; from the registry, ops1d.get("coincidence_delay"))

Usage

Time difference (b − a) between the peaks of two SNR time series, to sub-sample precision.

> The detailed description below is the original text — the summary and the headings are translated.

Parameters

snr_a, snr_b : array_like

matched_filter_snr の返り(同じ長さ・同じ標本化)。

rate : float

標本化周波数 [Hz]。

max_delay_s : float

a の山から b の山を探す窓(±)[s]。LIGO H1–L1 は光の走行時間 10 ms。

Returns

dict

delay_s(副標本、放物線)、delay_samples(整数)、peak_a / peak_b(山の高さ)、

index_a / index_b、network_snr = √(peak_a² + peak_b²)、window_samples

(探した窓の片側の標本数 = round(max_delay_s·rate))。

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• poc_gw_detector_pseudo_simulation — py -3.11 examples/poc_gw_detector_pseudo_simulation.py

Ops the type connects to (they accept `table` as input)

—

Same category (`matched`)

psd_welch · whiten_by_psd · chirp_newtonian · chirp_mass_from_track · matched_filter_snr · optimal_snr

*Provenance: gwsearch.py — ONED operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

coincidence_delay — ONED matched op