A two-mode product predicts the known sum signal of KIC 4064484 with relative errors below 0.30 in Kepler Q11 to Q16
We test whether two known combination signals of the RRc star KIC 4064484 follow its primary and secondary pulsations. A complex product relation fitted in available Kepler quarters 2 to 10 predicts the sum coefficient in quarters 11 to 16 with relative RMS errors of 0.122 to 0.291 across two flux products, three window lengths, and a harmonic-count check. Constant child coefficients give errors near one. The difference signal has larger errors, from 0.244 to 0.821, and a secondary-only model sometimes does better. Sampling-matched residual controls show that the useful sum relation is not exact under the stated noise test. With a fixed primary clock, a gain times the secondary alone predicts almost as well as the product. These are conditional predictions from measured later parent signals, not forecasts from early data alone. No new signal or planet is reported. Both flux products share Kepler images. Independent instrument data and pixel localization are absent. Code, selected samples, exact input hashes, controls, figures, and offline instructions are supplied.
Kepler · RR Lyrae · KIC 4064484 · combination frequencies · nonlinear pulsation · conditional prediction
References
4- usesdoi:10.1093/mnras/stu2561
Known pulsations, combination signals, frequencies, and time variability in this target.
- usesTwenty-day two-mode fits predict two known KIC 5520878 combination signals with relative errors below 0.35 in Kepler Q11 to Q16 sci:sha256:02ebe858725ee3c9e58a174bd395c6944dcb5bff0717319783567a240fb911aa
Published model structure and comparison for a different RRc star. We test transfer to KIC 4064484 with new code and data.
- useshttps://stpubdata.s3.amazonaws.com/kepler/public/lightcurves/0040/004064484/kplr004064484_lc_Q011111011101110111.tar
Public release 25 light-curve archive used in this test.
- https://archive.stsci.edu/kepler/manuals/KDMC-10008-005-Archive_Manual.pdf
Kepler archive format and data products.
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