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REVIEW 2 major objections 5 minor 64 references

Twenty-two years of Super-Kamiokande solar 8B neutrino data show no lasting short-period or solar-cycle flux modulations once detector systematics are isolated.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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T0 review · grok-4.5

2026-07-31 21:29 UTC pith:YMHLSKAY

load-bearing objection Solid multi-method reanalysis of the public 22-yr SK ⁸B series that retires the early ~38.8 d candidate as transient and supplies a usable <0.2% solar-cycle amplitude bound; novelty is comparative hygiene, not a new detection. the 2 major comments →

arxiv 2607.27979 v1 pith:YMHLSKAY submitted 2026-07-30 astro-ph.HE hep-ph

Comparative Periodogram Analysis of 22 Years of Super-Kamiokande Solar ⁸B Neutrino Data: Classical, Phase-Based, and Information Theoretic Methods

Liangliang Ren , Ze-Lin Zhang , Bing Xu , Tian-Cheng Huang , Ran Wang , Jia-Xin Dong , Yan-Ping Wang This is my paper
classification astro-ph.HE hep-ph
keywords solar neutrinosSuper-KamiokandeperiodogramGeneralized Lomb-ScargleBayesian model selectionsolar cycledetector systematics8B flux
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

Solar 8B neutrinos can in principle carry imprints of core rotation, magnetic fields, or a neutrino magnetic moment, so a careful search for periodic flux variations is a direct probe of the solar interior and of particle properties. This paper re-analyzes the full 22-year Super-Kamiokande data set with nine different periodogram methods and splits the time series by detector era so that hardware changes can be separated from genuine solar signals. The only candidate that survives multiple algorithms is a ~38.8-day modulation confined to the early, lower-statistics years; it disappears completely in the highest-quality later data and is only weakly favored by Bayesian model comparison. A ~24-day feature and any ~11-year solar-cycle modulation are decisively rejected, the latter with an amplitude upper limit below 0.2 percent of the mean flux. The work therefore supplies both a concrete null result on solar and neutrino physics and a practical multi-metric checklist that future high-statistics experiments can use to avoid mistaking detector artifacts for astrophysics.

Core claim

After hierarchical segmentation of the 22-year Super-Kamiokande 8B flux, seven algorithms give only weak Bayesian evidence (ln B > 0) for a ~38.8-day periodicity in the pre-2001/SK-I era; that signal is entirely absent in the highest-statistics SK-IV modified-flux data, where the Bayes factor decisively favors the null (ln B ≪ −5). A ~24.3-day peak seen in post-2001 raw flux is likewise rejected and vanishes after Earth–Sun distance correction. No ~11-year solar-cycle modulation is found, yielding an amplitude upper limit <0.2 % of the mean flux. Frequentist false-alarm probabilities alone are shown to be insufficient; Bayesian model selection is required to decide whether low-amplitude peak

What carries the argument

Hierarchical temporal segmentation (full baseline, pre/post-2001, SK-I–IV) combined with nine periodogram algorithms and a Bayesian sinusoid-versus-null comparison that reports the logarithmic Bayes factor ln B via the BIC approximation.

Load-bearing premise

The BIC approximation to the Bayes factor, together with the chosen priors and block-bootstrap procedure, is treated as a reliable enough criterion to declare that low-amplitude periodogram peaks are non-astrophysical.

What would settle it

A continuous, high-statistics data set (for example from Hyper-Kamiokande) in which the same ~38.8-day signal reappears with ln B > 5 after identical distance correction and multi-method analysis would falsify the claim that the feature is merely a transient of the early low-statistics era.

Watch this falsifier — get emailed when new claim-graph text bears on it.

If this is right

  • Next-generation analyses of Hyper-Kamiokande and JUNO solar data should report both frequentist FAPs and Bayesian ln B rather than FAPs alone.
  • The <0.2 % amplitude bound already rules out large solar-cycle core-temperature swings and many simple resonant spin-flavor precession scenarios at current sensitivity.
  • Detector-phase splits must be performed before any short-period claim is advanced, because hardware transitions can inject spurious ~20–40 day aliases.
  • Non-detections by box-fitting and information-theoretic methods already limit non-sinusoidal transit-like flux dips to ≲2 % of the mean.
  • Open release of the multi-method pipeline supplies a ready benchmark for cross-experiment comparison in the 2030s.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the early ~38.8-day feature is truly solar-cycle-dependent rather than purely instrumental, a future detector that spans a full solar maximum with uniform hardware could still recover a weak, amplitude-modulated signal even if SK-IV alone does not.
  • The same multi-metric stack can be applied without modification to the emerging CEνNS 8B “neutrino fog” data sets from liquid-xenon dark-matter detectors, providing an independent systematic cross-check.
  • The decisive Bayesian rejection of the ~24-day raw-flux peak suggests that residual seasonal water-transparency or veto-duty-cycle effects remain the dominant background for any sub-percent solar-rotation search.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

2 major / 5 minor

Summary. The manuscript presents a systematic comparison of nine periodogram algorithms (classical/generalized LS, BLS, phase-dispersion, and information-theoretic) applied to the public 22-year Super-Kamiokande 8B solar-neutrino flux time series, with hierarchical segmentation (full baseline, pre/post-July 2001, and SK-I–IV) and Bayesian MCMC sinusoidal validation. It reports that GLS is the most robust frequentist detector under heteroscedastic errors; that a ~38.8 d feature appears with only weak Bayesian support (ln B > 0) in pre-2001/SK-I and is absent in SK-IV modified flux (ln B ≪ −5); that a ~24.3 d raw-flux peak is Bayesian-rejected and vanishes after D² correction; and that no ~11 yr solar-cycle modulation is found, with an amplitude upper limit <0.2% of the mean flux. The work frames a multi-metric (FAP + ln B) best-practice pipeline for next-generation detectors.

Significance. If the empirical re-evaluation holds, the paper usefully closes or demotes long-standing short-period claims in the SK 8B record and supplies a concrete, reproducible methodological blueprint (open pipeline, multi-algorithm cross-checks, phase segmentation, asymmetric-likelihood MCMC) for Hyper-Kamiokande and JUNO. Strengths include use of an external public dataset, independent method definitions, model-independent D² correction, and explicit frequentist–Bayesian contrast in a low-SNR regime. The GLS-versus-classical-LS demonstration and the phase-dependent disappearance of candidate peaks are of lasting practical value even if some Bayesian language is softened.

major comments (2)
  1. [Abstract; §4.3; §4.5; Appendix Table 3] Abstract and §§4.3–4.5 / 4.5 summary: the claim that “seven algorithms provide weak evidence (ln B > 0)” for the ~38.8 d signal overstates independence. Appendix Table 3 shows essentially identical ln B values across LS/GLS/BLS/LKSL/PDM1/MHAOV/QMICS/QMIEU because a single shared MCMC sinusoid pipeline (same nested models, same BIC approximation) is applied to coincident periodogram peaks. Cross-recovery of the period by GLS/MHAOV/PDM1 is genuine and important; the Bayesian evidence itself is not seven independent model comparisons. Please rephrase to separate periodogram consensus from the single MCMC/BIC evidence stream.
  2. [§3.6; Abstract; §4; §6] §3.6 Eqs. (3.25)–(3.27) and Jeffreys-scale language used throughout §4: ln B is obtained from the BIC difference for a five-parameter sinusoid versus a two-parameter (constant+linear) null, with uniform priors and no full marginal-likelihood computation. In this low-SNR nested setting the BIC approximation and the labels “decisive/strong evidence for the null” (ln B ≪ −5) are stronger than the calculation strictly warrants. The structural conclusions (SK-IV absence; D² disappearance of ~24.3 d) do not require those labels, but the abstract and conclusions should caveat the approximation and avoid over-interpreting Jeffreys thresholds as full Bayesian evidence.
minor comments (5)
  1. [§5.2] §5.2: the ~11 yr amplitude upper limit (<0.2% of mean flux) is constructed from SK-IV RMS scatter rather than a dedicated periodogram or MCMC amplitude posterior at P ≈ 11 yr. Label it clearly as a semi-quantitative bound and, if feasible, add a one-line GLS/MCMC amplitude constraint at that period for consistency with the rest of the analysis.
  2. [Title page] ArXiv ePrint placeholder “1234.56789” on the title page should be replaced by 2607.27979 (or removed).
  3. [Figure 9; Appendix Figures 11–17] Figure 9 caption states QME/QMICS are omitted for clarity, yet the legend still lists them in places; align caption and legend. Several appendix periodogram panels are dense; consider marking the 95% GEV/bootstrap threshold on each panel for readability.
  4. [§2.3; §3.6] §2.3: symmetrization σ = (σ− + σ+)/2 is adopted for periodograms while the MCMC uses the full asymmetric likelihood—state explicitly that periodogram FAPs therefore do not propagate asymmetry, to avoid reader confusion.
  5. [Front matter; §2.1] Minor typos/consistency: “Y ears” in the running title; occasional spacing in 8B; ensure live-day totals in §2.1 match Tables 1–2 captions throughout.

Circularity Check

0 steps flagged

No significant circularity: external public data analyzed with independently defined periodogram and nested-model methods; results are not forced by construction.

full rationale

The paper applies nine standard periodogram algorithms (LS, GLS, BLS, LKSL, PDM1, MHAOV, QME, QMICS, QMIEU) and a Bayesian nested comparison (sinusoid vs constant+linear drift via BIC-approximated ln B) to the publicly released Super-Kamiokande 22-year 8B flux series, with hierarchical temporal segmentation and a model-independent D² Earth–Sun distance correction. Candidate frequencies are taken from periodogram peaks and then re-fit; that is ordinary two-stage inference on the same external time series, not a fitted parameter renamed as an independent prediction, nor a quantity defined in terms of itself. Cross-method recovery of ~0.106 yr in pre-2001/SK-I, its absence in SK-IV modified flux, and the vanishing of the ~24.3 d raw-flux peak after D² correction are empirical outcomes of the data and segmentation, not identities forced by normalization or by a self-citation uniqueness theorem. Citations are to Super-K data releases, Pasumarti & Desai’s compilation, and the standard periodogram literature; there is no load-bearing self-citation chain or smuggled ansatz that makes the central claims true by definition. Methodological caveats (BIC approximation, Jeffreys-scale language, RMS-based 11 yr amplitude cap) affect strength of wording, not circularity of the derivation.

Axiom & Free-Parameter Ledger

6 free parameters · 6 axioms · 0 invented entities

The central negative and weak-evidence claims rest on standard time-series statistics, the public SK flux series and its published uncertainties, and several analysis choices (segmentation boundaries, BIC-as-Bayes-factor, bootstrap design, sinusoidal model family) that are conventional but not forced by first principles.

free parameters (6)
  • Frequency grid (0.01–20 yr⁻¹, Δf = 1/(T·N_samp), N_samp=5) = 0.01–20 yr⁻¹, 5 samples per peak
    Defines the search space and look-elsewhere burden for all periodograms.
  • BLS fixed dip duration and phase bins = 10 days, m=100 bins, 1000 trial periods
    Controls sensitivity to box-shaped signals; fixed rather than profiled.
  • Block-bootstrap length and N_boot = 30-day blocks, N_boot=100
    Sets empirical FAP and GEV tail for non-LS methods.
  • QMI/QME kernel bandwidths = h_f=0.5·std(F)·N^{-1/6}, h_φ=1
    h_f via weighted Silverman rule and h_φ=1 enter all information-theoretic scores.
  • MCMC prior bounds and BIC parameter count k=5 = A,B~U(±5σ_F), f~U(0.6–1.4 f_init), etc.; k=5
    Uniform priors on A,B,f,c,s and the BIC penalty directly set ln B and Jeffreys-scale calls.
  • 11-year amplitude upper-limit construction = RMS≈0.015×10^6 cm^{-2}s^{-1} → <0.004×10^6 (~0.2%)
    Uses SK-IV modified-flux RMS and baseline to quote <0.2% (95% C.L.).
axioms (6)
  • domain assumption Bin-averaged sinusoidal model with piecewise asymmetric Gaussian likelihood matches the SK flux extraction (Eqs. 3.20–3.23).
    Inherited from Super-Kamiokande collaboration formalism; required for MCMC validation.
  • ad hoc to paper BIC difference approximates the Bayes factor for nested sinusoid vs constant+linear models (Eq. 3.27) and Jeffreys’ scale applies to ln B.
    Standard large-N approximation used as the decisive model-selection metric throughout Section 4.
  • domain assumption Earth–Sun D(t)² correction removes orbital modulation without erasing genuine solar periodicities of interest.
    Preprocessing step (Eq. 2.1) used to classify residual peaks as non-orbital.
  • domain assumption Heteroscedastic inverse-variance weighting and floating mean (GLS) are the correct second-order model for these bins.
    Underpins the claim that GLS is statistically preferred over classical LS.
  • ad hoc to paper Hierarchical July-2001 and SK-I–IV splits separate instrumental from astrophysical effects.
    Segmentation strategy is a design choice that drives the transient-vs-persistent interpretation.
  • standard math Standard periodogram and ANOVA sampling distributions / bootstrap exchangeability under the null.
    Baluev FAP, F-tests for PDM/MHAOV, and block bootstrap FAPs.

pith-pipeline@v1.2.0-daily-grok45 · 57391 in / 3848 out tokens · 68375 ms · 2026-07-31T21:29:51.384119+00:00 · methodology

0 comments
read the original abstract

Solar $^8\mathrm{B}$ neutrinos offer a unique probe of solar interior dynamics and neutrino electromagnetic properties. We present a systematic, multi-method periodogram analysis of the 22-year Super-Kamiokande solar neutrino dataset (1996--2018), comparing nine algorithms. Through hierarchical temporal segmentation, we disentangle astrophysical signals from detector systematics. The Generalized Lomb-Scargle (GLS) method provides the most statistically robust detections by correctly handling heteroscedastic uncertainties, whereas classical Lomb-Scargle systematically underestimates significance. The Lafler--Kinman method generally fails, whereas independent algorithms like MHAOV and PDM1 recover consistent periodicities, providing vital cross-validation. In pre-2001 and SK-I data, seven algorithms provide \textit{weak evidence} ($\ln B > 0$) for a $\sim 38.8$ d periodicity. However, this signal is entirely absent in the highest-statistics SK-IV modified flux data, where the Bayes factor decisively favors the null model ($\ln B \ll -5$), indicating it is a transient feature of the early low-statistics era. Conversely, a $\sim 24.3$ d signal in post-2001 raw flux is decisively rejected by the Bayesian framework and vanishes in modified flux, confirming its seasonal systematic origin. Furthermore, no evidence is found for an $\sim 11$-year solar cycle modulation, yielding a stringent amplitude upper limit of $<0.2\%$ of the mean flux. By highlighting the stark contrast between frequentist significance and Bayesian model selection ($\ln B$) in low signal-to-noise regimes, we establish a rigorous, multi-metric best-practice framework for periodicity searches. This work provides a direct methodological blueprint for next-generation observatories like Hyper-Kamiokande and JUNO.

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Reference graph

Works this paper leans on

64 extracted references · 44 linked inside Pith

  1. [2]

    Adelberger et al.,Solar fusion cross sections II: the pp chain and CNO cycles,Rev

    E.G. Adelberger et al.,Solar fusion cross sections II: the pp chain and CNO cycles,Rev. Mod. Phys.83(2011) 195 [1004.2318]

    Pith/arXiv arXiv 2011

  2. [3]

    Suliga, S

    A.M. Suliga, S. Shalgar and G.M. Fuller,A closer look at the pp-chain reaction in the Sun: constraining the coupling of light mediators to protons, J. Cosmology Astropart. Phys.2021 (2021) 042 [2012.11620]

    Pith/arXiv arXiv 2021

  3. [4]

    Bahcall and M.H

    J.N. Bahcall and M.H. Pinsonneault,Solar models with helium and heavy element diffusion, Rev. Mod. Phys.67(1995) 781 [hep-ph/9505425]

    Pith/arXiv arXiv 1995

  4. [5]

    Bahcall, P.I

    J.N. Bahcall, P.I. Krastev and A.Y. Smirnov,Where do we stand with solar neutrino oscillations?,Phys. Rev. D58(1998) 096016 [hep-ph/9807216]

    Pith/arXiv arXiv 1998

  5. [6]

    Bahcall, A.M

    J.N. Bahcall, A.M. Serenelli and S. Basu,New solar opacities, abundances, helioseismology, and neutrino fluxes,Astrophys. J. Lett.621(2005) L85 [astro-ph/0412440]. [7]Super-Kamiokandecollaboration,Measurements of the solar neutrino flux from Super-Kamiokande’s first 300 days,Phys. Rev. Lett.81(1998) 1158 [hep-ex/9805021]. [8]Borexinocollaboration,Measurem...

    Pith/arXiv arXiv 2005

  6. [10]

    Akhmedov,Resonant Amplification of Neutrino Spin Rotation in Matter and the Solar Neutrino Problem,Phys

    E.K. Akhmedov,Resonant Amplification of Neutrino Spin Rotation in Matter and the Solar Neutrino Problem,Phys. Lett. B213(1988) 64

    1988

  7. [11]

    Lim and W.J

    C.-S. Lim and W.J. Marciano,Resonant Spin - Flavor Precession of Solar and Supernova Neutrinos,Phys. Rev. D37(1988) 1368

    1988

  8. [12]

    C.S. Lim, M. Mori, Y. Oyama and A. Suzuki,Correlation between solar neutrino flux and solar magnetic activity for Majorana neutrinos,Physics Letters B243(1990) 389

    1990

  9. [13]

    Ando and K

    S. Ando and K. Sato,Three-generation study of neutrino spin-flavor conversion in supernovae and implication for the neutrino magnetic moment, Phys. Rev. D67(2003) 023004 [hep-ph/0211053]

    Pith/arXiv arXiv 2003

  10. [14]

    Joshi and S.R

    S. Joshi and S.R. Jain,Neutrino spin-flavor oscillations in solar environment,Research in Astronomy and Astrophysics20(2020) 123 [1906.09475]

    Pith/arXiv arXiv 2020

  11. [15]

    Delepine and A

    D. Delepine and A. Yebra,Distinguishing Dirac and Majorana neutrinos: Resonant spin-flavor precession of GeV-scale astrophysical transients,Phys. Rev. D114(2026) 015012

    2026

  12. [16]

    Delepine and A

    D. Delepine and A. Yebra,Solar Flares as a Probe of Neutrino Nature: Distinguishing Dirac and Majorana via Resonant Spin-Flavor Precession,arXiv e-prints(2026) arXiv:2602.05149 [2602.05149]

    arXiv 2026

  13. [17]

    Aharmim, S.N

    B. Aharmim, S.N. Ahmed, A.E. Anthony, N. Barros, E.W. Beier, A. Bellerive et al.,Searches for High-frequency Variations in the8B Solar Neutrino Flux at the Sudbury Neutrino Observatory, ApJ710(2010) 540 [0910.2433]

    Pith/arXiv arXiv 2010

  14. [18]

    Baldwin, L.J

    M.P. Baldwin, L.J. Gray, T.J. Dunkerton, K. Hamilton, P.H. Haynes, W.J. Randel et al.,The quasi-biennial oscillation,Reviews of Geophysics39(2001) 179

    2001

  15. [19]

    Simoniello, K

    R. Simoniello, K. Jain, S.C. Tripathy, S. Turck-Chieze, C. Baldner, W. Finsterle et al.,The quasi-biennial periodicity as a window on the solar magnetic dynamo configuration,Astrophys. J.765(2013) 100 [1210.6796]. – 39 –

    Pith/arXiv arXiv 2013

  16. [20]

    Sturrock,Neutrino-Flux Variability, Nuclear-Decay Variability, and Their Apparent Relationship,Space Sci

    P.A. Sturrock,Neutrino-Flux Variability, Nuclear-Decay Variability, and Their Apparent Relationship,Space Sci. Rev.218(2022) 23 [2203.05069]

    Pith/arXiv arXiv 2022

  17. [21]

    Vasil, D

    G.M. Vasil, D. Lecoanet, K. Augustson, K.J. Burns, J.S. Oishi, B.P. Brown et al.,The solar dynamo begins near the surface, Nature629(2024) 769 [2404.07740]

    Pith/arXiv arXiv 2024

  18. [22]

    Hatta, Y

    Y. Hatta, Y. Nakano, S. Sugama, M. Kunitomo, H. Ito and T. Sekii,Solar Neutrino Flux Fluctuations Caused by Solar Gravity Modes,arXiv e-prints(2026) arXiv:2604.06535 [2604.06535]

    Pith/arXiv arXiv 2026

  19. [23]

    Turck-Chièze and S

    S. Turck-Chièze and S. Couvidat,Solar neutrinos, helioseismology and the solar internal dynamics,Reports on Progress in Physics74(2011) 086901 [1009.0852]

    Pith/arXiv arXiv 2011

  20. [24]

    Zavatarelli, on behalf of theBOREXINO Collaboration, M

    S. Zavatarelli, on behalf of theBOREXINO Collaboration, M. Agostini, K. Altenmüller, S. Appel, V. Atroshchenko et al.,The study of solar neutrinos and of non-standard neutrino interactions with borexino,Journal of Physics: Conference Series1468(2020) 012192

    2020

  21. [25]

    K. Abe, Y. Hayato, T. Iida, M. Ikeda, C. Ishihara, K. Iyogi et al.,Solar neutrino results in Super-Kamiokande-III, Phys. Rev. D83(2011) 052010 [1010.0118]. [26]Super-Kamiokandecollaboration,Search for Periodic Time Variations of the Solar B8 Neutrino Flux between 1996 and 2018 in Super-Kamiokande,Phys. Rev. Lett.132(2024) 241803 [2311.01159]

    Pith/arXiv arXiv 2011

  22. [27]

    Kumaran, L

    S. Kumaran, L. Ludhova, Ö. Penek and G. Settanta,Borexino Results on Neutrinos from the Sun and Earth,Universe7(2021) 231 [2105.13858]. [28]BOREXINOcollaboration,Independent determination of the Earth’s orbital parameters with solar neutrinos in Borexino,Astropart. Phys.145(2023) 102778 [2204.07029]

    Pith/arXiv arXiv 2021

  23. [29]

    Basilico, G

    D. Basilico, G. Bellini, J. Benziger, R. Biondi, B. Caccianiga, F. Calaprice et al.,Final results of Borexino on CNO solar neutrinos, Phys. Rev. D108(2023) 102005 [2307.14636]

    Pith/arXiv arXiv 2023

  24. [30]

    W. Ma, A. Abdukerim, C. Cheng, Z. Bo, W. Chen, X. Chen et al.,Search for Solar B 8 Neutrinos in the PandaX-4T Experiment Using Neutrino-Nucleus Coherent Scattering, Phys. Rev. Lett.130(2023) 021802 [2207.04883]

    Pith/arXiv arXiv 2023

  25. [31]

    Z. Bo, W. Chen, X. Chen, Y. Chen, Z. Cheng, X. Cui et al.,First Indication of Solar B8 Neutrinos through Coherent Elastic Neutrino-Nucleus Scattering in PandaX-4T, Phys. Rev. Lett.133(2024) 191001 [2407.10892]

    Pith/arXiv arXiv 2024

  26. [32]

    De Romeri, D.K

    V. De Romeri, D.K. Papoulias, G. Sanchez Garcia, C.A. Ternes and M. Tórtola,Neutrino electromagnetic properties and sterile dipole portal in light of the first solar CEνNS data, J. Cosmology Astropart. Phys.2025(2025) 080 [2412.14991]

    Pith/arXiv arXiv 2025

  27. [33]

    De Romeri, A

    V. De Romeri, A. Majumdar, D.K. Papoulias and R. Srivastava,New light mediators and the neutrino fog: Implications from XENONnT nuclear recoil data, J. Cosmology Astropart. Phys. 2026(2026) 093 [2512.08853]

    Pith/arXiv arXiv 2026

  28. [34]

    Zhuang, L.E

    Y. Zhuang, L.E. Strigari, L. Jin and S. Sinha,Prospects for measuring the time variation of astrophysical neutrino sources at dark matter detectors, Phys. Rev. D110(2024) 043037 [2402.18454]

    Pith/arXiv arXiv 2024

  29. [35]

    Lomb,Least-Squares Frequency Analysis of Unequally Spaced Data, Ap&SS39(1976) 447

    N.R. Lomb,Least-Squares Frequency Analysis of Unequally Spaced Data, Ap&SS39(1976) 447

    1976

  30. [36]

    Scargle,Studies in astronomical time series analysis

    J.D. Scargle,Studies in astronomical time series analysis. II. Statistical aspects of spectral analysis of unevenly spaced data., ApJ263(1982) 835. [37]Super-Kamiokandecollaboration,Solar neutrino measurements in super-Kamiokande-I, Phys. Rev. D73(2006) 112001 [hep-ex/0508053]. [38]Super-Kamiokandecollaboration,Solar neutrino measurements in Super-Kamioka...

    Pith/arXiv arXiv 1982

  31. [41]

    Haubold and A.M

    H.J. Haubold and A.M. Mathai,Does SuperKamiokande Observe Levy Flights of Solar Neutrinos?,arXiv e-prints(2024) arXiv:2405.11057 [2405.11057]

    arXiv 2024

  32. [42]

    Aharmim, S.N

    B. Aharmim, S.N. Ahmed, A.E. Anthony, E.W. Beier, A. Bellerive, M. Bergevin et al.,Search for periodicities in the8B solar neutrino flux measured by the Sudbury Neutrino Observatory, Phys. Rev. D72(2005) 052010 [hep-ex/0507079]

    Pith/arXiv arXiv 2005

  33. [43]

    Pasumarti and S

    V. Pasumarti and S. Desai,Generalized Lomb–Scargle analysis of 22 years of super-Kamiokande solar 8B neutrino data,Eur. Phys. J. C84(2024) 487 [2402.11258]

    Pith/arXiv arXiv 2024

  34. [44]

    Zechmeister and M

    M. Zechmeister and M. Kürster,The generalised Lomb-Scargle periodogram. A new formalism for the floating-mean and Keplerian periodograms, A&A496(2009) 577 [0901.2573]

    Pith/arXiv arXiv 2009

  35. [45]

    Kovács, S

    G. Kovács, S. Zucker and T. Mazeh,A box-fitting algorithm in the search for periodic transits, A&A391(2002) 369 [astro-ph/0206099]

    Pith/arXiv arXiv 2002

  36. [46]

    L. Ren, C. Li, B. Ma, S. Cheng, S.-J. Huang, B. Tang et al.,A Systematic Search for Short-period Close White Dwarf Binary Candidates Based on Gaia EDR3 Catalog and Zwicky Transient Facility Data, ApJS264(2023) 39 [2302.02802]

    Pith/arXiv arXiv 2023

  37. [47]

    Clarke,String/Rope length methods using the Lafler-Kinman statistic, A&A386(2002) 763

    D. Clarke,String/Rope length methods using the Lafler-Kinman statistic, A&A386(2002) 763

    2002

  38. [48]

    Stellingwerf,Period determination using phase dispersion minimization., ApJ224(1978) 953

    R.F. Stellingwerf,Period determination using phase dispersion minimization., ApJ224(1978) 953

    1978

  39. [49]

    Schwarzenberg-Czerny,Fast and Statistically Optimal Period Search in Uneven Sampled Observations, ApJ460(1996) L107

    A. Schwarzenberg-Czerny,Fast and Statistically Optimal Period Search in Uneven Sampled Observations, ApJ460(1996) L107

    1996

  40. [50]

    Mondrik, J.P

    N. Mondrik, J.P. Long and J.L. Marshall,A Multiband Generalization of the Multiharmonic Analysis of Variance Period Estimation Algorithm and the Effect of Inter-band Observing Cadence on Period Recovery Rate, ApJ811(2015) L34 [1508.04772]

    Pith/arXiv arXiv 2015

  41. [51]

    Graham, A.J

    M.J. Graham, A.J. Drake, S.G. Djorgovski, A.A. Mahabal, C. Donalek, V. Duan et al.,A comparison of period finding algorithms, MNRAS434(2013) 3423 [1307.2209]

    Pith/arXiv arXiv 2013

  42. [52]

    Huijse, P.A

    P. Huijse, P.A. Estevez, P. Protopapas, J.C. Principe and P. Zegers,Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases,IEEE Computational Intelligence Magazine9(2014) 27 [1509.07823]

    Pith/arXiv arXiv 2014

  43. [53]

    Huijse, P.A

    P. Huijse, P.A. Estévez, F. Förster, S.F. Daniel, A.J. Connolly, P. Protopapas et al.,Robust Period Estimation Using Mutual Information for Multiband Light Curves in the Synoptic Survey Era, ApJS236(2018) 12 [1709.03541]. [54]Hyper-Kamiokandecollaboration,Hyper-Kamiokande Design Report,1805.04163

    Pith/arXiv arXiv 2018

  44. [55]

    B. Abi, R. Acciarri, M.A. Acero, G. Adamov, D. Adams, M. Adinolfi et al.,Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume II: DUNE Physics,arXiv e-prints(2020) arXiv:2002.03005 [2002.03005]

    arXiv 2020

  45. [56]

    Abusleme, T

    A. Abusleme, T. Adam, S. Ahmad, R. Ahmed, S. Aiello, M. Akram et al.,Sub-percent precision measurement of neutrino oscillation parameters with JUNO,Chinese Physics C46(2022) 123001 [2204.13249]. [57]Matthias Raphael Stock, JUNOcollaboration,Status and prospects of the JUNO experiment,SciPost Phys. Proc.17(2025) 020 [2405.07321]

    arXiv 2022

  46. [58]

    Walter,The Super-Kamiokande Experiment,World Scientific Publishing Co

    C.W. Walter,The Super-Kamiokande Experiment,World Scientific Publishing Co. Pte. Ltd. (2008) 19 [0802.1041]. – 41 –

    Pith/arXiv arXiv 2008

  47. [59]

    Leroy,Fast calculation of the Lomb-Scargle periodogram using nonequispaced fast Fourier transforms, A&A545(2012) A50

    B. Leroy,Fast calculation of the Lomb-Scargle periodogram using nonequispaced fast Fourier transforms, A&A545(2012) A50

    2012

  48. [60]

    VanderPlas and Ž

    J.T. VanderPlas and Ž. Ivezić,Periodograms for Multiband Astronomical Time Series, ApJ 812(2015) 18 [1502.01344]

    Pith/arXiv arXiv 2015

  49. [61]

    VanderPlas,Understanding the Lomb-Scargle Periodogram, ApJS236(2018) 16 [1703.09824]

    J.T. VanderPlas,Understanding the Lomb-Scargle Periodogram, ApJS236(2018) 16 [1703.09824]

    Pith/arXiv arXiv 2018

  50. [62]

    Hartman and G.Á

    J.D. Hartman and G.Á. Bakos,VARTOOLS: A program for analyzing astronomical time-series data,Astronomy and Computing17(2016) 1 [1605.06811]

    Pith/arXiv arXiv 2016

  51. [63]

    Baluev,Assessing the statistical significance of periodogram peaks, MNRAS385(2008) 1279 [0711.0330]

    R.V. Baluev,Assessing the statistical significance of periodogram peaks, MNRAS385(2008) 1279 [0711.0330]

    Pith/arXiv arXiv 2008

  52. [64]

    Baluev,Detecting non-sinusoidal periodicities in observational data using multiharmonic periodograms, MNRAS395(2009) 1541 [0811.0907]

    R.V. Baluev,Detecting non-sinusoidal periodicities in observational data using multiharmonic periodograms, MNRAS395(2009) 1541 [0811.0907]

    Pith/arXiv arXiv 2009

  53. [65]

    Foreman-Mackey, D.W

    D. Foreman-Mackey, D.W. Hogg, D. Lang and J. Goodman,emcee: The MCMC Hammer, PASP125(2013) 306 [1202.3665]

    Pith/arXiv arXiv 2013

  54. [66]

    Andrae, T

    R. Andrae, T. Schulze-Hartung and P. Melchior,Dos and don’ts of reduced chi-squared,arXiv e-prints(2010) arXiv:1012.3754 [1012.3754]. [67]Bayesian information criteria, inInformation Criteria and Statistical Modeling, (New York, NY), pp. 211–237, Springer New York (2008), DOI

    Pith/arXiv arXiv 2010

  55. [68]

    Speagle,DYNESTY: a dynamic nested sampling package for estimating Bayesian posteriors and evidences, MNRAS493(2020) 3132 [1904.02180]

    J.S. Speagle,DYNESTY: a dynamic nested sampling package for estimating Bayesian posteriors and evidences, MNRAS493(2020) 3132 [1904.02180]

    Pith/arXiv arXiv 2020

  56. [69]

    Faulkenberry,Computing Bayes factors to measure evidence from experiments: An extension of the BIC approximation,arXiv e-prints(2018) arXiv:1803.00360 [1803.00360]

    T.J. Faulkenberry,Computing Bayes factors to measure evidence from experiments: An extension of the BIC approximation,arXiv e-prints(2018) arXiv:1803.00360 [1803.00360]

    Pith/arXiv arXiv 2018

  57. [70]

    Jeffreys,Theory of Probability,Oxford University Press Oxford(1961)

    H. Jeffreys,Theory of Probability,Oxford University Press Oxford(1961)

    1961

  58. [71]

    Alfradique, R

    V. Alfradique, R. da Mata, J.C. Rodríguez-Ramírez and C.R. Bom,Multi-wavelength analysis of the progenitor of GRB 230307A via Bayesian model comparison,arXiv e-prints(2025) arXiv:2510.14879 [2510.14879]

    arXiv 2025

  59. [72]

    Robitaille, E.J

    Astropy Collaboration, T.P. Robitaille, E.J. Tollerud, P. Greenfield, M. Droettboom and E.e.a. Bray,Astropy: A community Python package for astronomy, A&A558(2013) A33 [1307.6212]

    Pith/arXiv arXiv 2013

  60. [73]

    Price-Whelan, P.L

    Astropy Collaboration, A.M. Price-Whelan, P.L. Lim and N.e.a. Earl,The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package, ApJ935(2022) 167 [2206.14220]

    Pith/arXiv arXiv 2022

  61. [74]

    Price-Whelan, B.M

    Astropy Collaboration, A.M. Price-Whelan, B.M. Sipőcz, H.M. Günther, P.L. Lim and S.M.e.a. Crawford,The Astropy Project: Building an Open-science Project and Status of the v2.0 Core Package, AJ156(2018) 123 [1801.02634]

    Pith/arXiv arXiv 2018

  62. [75]

    Harris, K.J

    C.R. Harris, K.J. Millman, S.J. van der Walt, R. Gommers, P. Virtanen and D.C. et al.,Array programming with NumPy,Nature585(2020) 357

    2020

  63. [76]

    Virtanen, R

    P. Virtanen, R. Gommers, T.E. Oliphant, M. Haberland, T. Reddy and D.e.a. Cournapeau, SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,Nature Methods17 (2020) 261

    2020

  64. [77]

    Hunter,Matplotlib: A 2d graphics environment,Computing in Science & Engineering9 (2007) 90

    J.D. Hunter,Matplotlib: A 2d graphics environment,Computing in Science & Engineering9 (2007) 90. – 42 – -15 -10 -5 0 5 10 15 lnB (Bayes Factor) Full_22yr - LS Full_22yr - GLS Full_22yr - BLS Full_22yr - LKSL Full_22yr - PDM1 Full_22yr - MHAOV Full_22yr - QME Full_22yr - QMICS Full_22yr - QMIEU Pre_July2001 - LS Pre_July2001 - GLS Pre_July2001 - BLS Pre_Ju...

    2007