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Spotlight searches for continuous gravitational waves triggered on radiometer candidates in LIGO O4a data

T0 review · 1 major / 3 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read Following up 562 radiometer candidates, this search finds no continuous gravitational waves in LIGO O4a data.

desk verdict Careful O4a follow-up of 562 radiometer candidates; the null result is supported by outlier-count consistency, though the O4b validation is under-quantified. read the letter →

arxiv 2608.07312 v1 pith:Y7MGCS7Y submitted 2026-08-07 gr-qc astro-ph.IM

Alan M. Knee , Keith Riles , Ling Sun This is my paper · ORCID
classification gr-qcastro-ph.IM PACS 04.80.Nn95.55.Ym
keywords continuousgravitationalwaveshiddenMarkovmodelF-statisticradiometersearchall-skyall-frequencyLIGOO4neutronstarswavedataanalysis
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper follows up 562 sub-threshold candidates from the O4a all-sky all-frequency radiometer search, using an F-statistic matched filter with a hidden Markov model that lets the signal frequency wander between segments. Its central result is a null: 24 candidates produce outliers with false-alarm probability below 5%, three are vetoed as detector artifacts, and the remaining 21 are not recovered at comparable significance in independent O4b data. The paper concludes that no convincing continuous gravitational wave is present in these 562 frequency-sky pixels, and that all outliers are consistent with noise fluctuations. It also establishes sensitivity: 95% detection efficiency for strain amplitudes $h_0 \sim (0.63\text{--}6.3)\times10^{-25}$ for isolated neutron stars and $h_0 \sim (0.82\text{--}7.1)\times10^{-25}$ for long-period binaries across 20–1726 Hz. The search matters because it targets signals with irregular phase evolution that standard phase-coherent searches can miss.

What carries the argument

The central machinery is the F-statistic matched filter run in 24-hour coherent segments, combined with a hidden Markov model and the Viterbi algorithm to select the most probable segment-wise frequency path for each sky-position and spin-down template. The detection statistic is the normalized Viterbi log-likelihood $\bar{L}=L/N_T$. Significance is assigned by fitting an exponential tail to the distribution of detection statistics at off-target sky positions, then applying a trials-factor correction to obtain false-alarm probabilities. Three vetoes—known spectral lines, single-interferometer power imbalance, and Doppler-modulation-off consistency—filter detector artifacts, and a large injection campaign with logistic-regression fitting yields the reported 95% efficiency strain amplitudes.

What would settle it

Re-run the identical pipeline on the 21 surviving outliers using O4b data with the C01 calibration and a lower false-alarm threshold; recovery of any of them at $p_{\rm corr}^{\rm fa}<5\%$ would contradict the claim that all outliers are noise. A second check is to inject a simulated continuous wave at the quoted 95% sensitivity strain amplitude into one of the 562 O4a frequency-sky pixels and verify recovery; failure to recover it would falsify the sensitivity claim.

Watch

Extended reading notes

Core claim

The paper claims that no convincing continuous gravitational wave is detected in a directed follow-up of 562 sub-threshold candidates produced by the O4a LIGO–Virgo–KAGRA all-sky all-frequency radiometer analysis. Each candidate is a narrow $1/32$ Hz frequency band paired with a roughly $13$ deg$^2$ sky pixel. Searching O4a data from the two Advanced LIGO detectors with an F-statistic matched filter equipped with hidden Markov model frequency tracking, the paper finds 24 outliers below a trials-corrected false-alarm probability of 5%; three fail instrumental vetoes, and the 21 surviving outliers are not recovered with comparable significance when re-analyzed in O4b data. The observed outlier count (24) is consistent with the binomially expected number ($27\pm5$) at the 5% threshold, supporting the interpretation that all outliers are noise fluctuations. Injection-recovery tests place the search's 95% efficiency sensitivity at $h_0\sim(0.63\text{--}6.3)\times10^{-25}$ for isolated neutron stars and $h_0\sim(0.82\text{--}7.1)\times10^{-25}$ for neutron stars in long-period ($P_b>1$ yr) binaries.

Load-bearing premise

The false-alarm probabilities come from fitting the tail of the detection statistic to off-target sky positions, under the assumption that no real signal or unmodeled artifact contaminates those off-target positions; if that assumption fails, the outlier list and the conclusion drawn from it could change.

Editorial extensions

If this is right

  • The 562 followed-up frequency-sky pixels are effectively excluded as sites of a detectable continuous wave at the quoted strain amplitudes in O4a data.
  • Because none of the 21 surviving outliers persists in O4b data, any claimed detection at these parameters would have to explain why the signal vanished in later data; the paper's injection recovery shows a real detectable signal would persist.
  • The outlier count matches the expected noise count at the 5% false-alarm threshold, so the search behaves consistently with its stated statistical calibration.
  • The sensitivity improvement over the earlier O3 follow-up and over the ASAF upper limits sets a new reference point for radiometer-triggered continuous wave searches at O4a sensitivity.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • Editorial inference: the null result suggests, though the paper does not claim, that sub-threshold radiometer candidates in O4a are dominated by scattered noise artifacts rather than by a population of missed quasi-monochromatic sources.
  • Editorial inference: because the off-target noise model is the load-bearing premise, a natural test is to inject weak signals into off-target sky positions in O4b and measure how much the fitted exponential tail shifts; the published off-target distributions could be reused for this check.
  • Editorial inference: the search's long-period binary sensitivity is capped by the HMM's one-frequency-bin-per-segment drift limit, so a higher-order frequency-jump model could probe whether rapidly wandering sources are being missed.
  • Editorial inference: combining O4a and O4b data with a longer coherence time for the same 562 candidates would likely push the quoted strain sensitivity lower, since the paper demonstrates the pipeline can be deployed at scale but does not run this combined search.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

1 major / 3 minor

Summary. The paper presents a follow-up search for continuous gravitational waves targeting 562 sub-threshold candidates from the O4a LVK all-sky all-frequency radiometer analysis. For each candidate, the authors run an F-statistic search over a 1/32 Hz band and a ~13 sq-deg sky pixel, with a hidden Markov model to track frequency wandering. Using O4a LIGO data, they find 24 outliers with trials-corrected false-alarm probability below 5%; three are removed by detector-artifact vetoes, leaving 21. These 21 outliers are re-analyzed in independent O4b data, and none are recovered at comparable significance. The authors therefore conclude that no convincing CW signals are present. They also report extensive injection-recovery sensitivity estimates: 95% detection efficiency at h0 ~ (0.63-6.3)e-25 for isolated neutron stars and h0 ~ (0.82-7.1)e-25 for long-period binaries, plus validation against four of five pulsar hardware injections.

Significance. If the result holds, the paper demonstrates that a model-agnostic radiometer pipeline can be systematically followed up with an HMM-based coherent search over hundreds of candidates, and it places meaningful strain upper limits in the 20-1726 Hz band. The strengths of the manuscript are its large empirical injection campaign (500 injections per candidate), the use of external O4b data for an independent cross-check, validation with hardware injections, and the transparent reporting of outlier parameters and false-alarm estimates. The main null conclusion is also supported by the binomial expectation: 24 outliers from 533 clean candidates is consistent with the 27 +/- 5 expected at a 5% false-alarm threshold. The principal weakness is that the O4b validation is reported only as "the vast majority" of simulated signals being recovered, without per-candidate counts; this leaves the O4b non-recovery argument, which the paper uses to rule out real signals, under-quantified.

major comments (1)
  1. The O4b follow-up is load-bearing for the statement that the 21 O4a outliers are not consistent with astrophysical signals, but its validation is not quantified. The text says only that "the vast majority" of the 210 simulated signals (10 per candidate, injected at 110% of h95) are confidently detected in both O4a and O4b, without giving exact counts or a per-candidate breakdown. If some candidates had low O4b recovery efficiency, then an O4a outlier in one of those candidates could be a real signal that O4b is simply too insensitive to detect; the non-recovery would not be informative. In addition, the injection amplitude is fixed at 110% of the estimated 95% efficiency strain, while the amplitudes of the actual outliers are unknown and may lie below h95, where O4b detection efficiency is lower. I request that the authors report, for each of the 21 candidates, the number of injections detected in O4a and O4b, define "confidently detected" (e.g., above the O4b threshold with a specified margin), and discuss how the results would change if a few candidates had substantially lower O4b recovery. This is a local, fixable issue that does not invalidate the overall null result, especially since the outlier count is already consistent with noise, but it is necessary to fully support the O4b-based conclusion.
minor comments (3)
  1. The per-candidate h0 ranges are said to be "adjusted according to the average noise level," but the adjustment rule is not specified. Please state how the sampled strain range is chosen and confirm that h95 falls within the sampled range for all candidates, so that the logistic regression is not extrapolating.
  2. The caption contains a typo: "Cumululative density" should be "Cumulative density."
  3. The off-target false-alarm procedure assumes that no signal or unmodeled artifact exists near the off-target templates. The manuscript states this assumption, but it would help to quantify the risk: for example, by reporting how many off-target samples lie within a known spectral artifact and whether excluding those samples changes the fitted lambda_hat.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the null conclusion rests on independent O4b data and injection-recovery sensitivity, with no load-bearing step reducing to its inputs.

full rationale

The derivation chain is self-contained. The detection statistic is computed from O4a strain data, and the false-alarm probabilities are estimated from an empirical off-target noise distribution, which is used only to rank outliers rather than to define the sensitivity or the O4b result. The sensitivity estimates are obtained from a large injection-recovery campaign with a logistic fit, independent of the outlier p-values. The central null conclusion relies on the non-recovery of the 21 outliers in independent O4b data, supported by simulated signals injected at 110% of the estimated h95 values; while the manuscript reports only that 'the vast majority' of these injections were detected in both O4a and O4b without per-candidate counts, this is a quantitative-evidence gap rather than a circular reduction. Self-citations to the O3 pipeline and to ASAF analyses provide methodology and candidate inputs, but the central result is not defined in terms of those papers, and the hardware-injection recovery in Appendix C provides independent validation. No step reduces by construction to its own inputs.

Assumptions & free parameters 5 free parameters · 6 assumptions · 0 invented entities

The central null claim rests on statistical modeling of the noise distribution (exponential tail fit to off-target samples), the bounded spin-down search range derived from the 1/32 Hz bin, and the comparability of O4a/O4b data. No new physical entities are introduced.

free parameters (5)
  • Off-target exponential tail slope lambda_hat (per candidate) = Not quoted; typical lambda_hat ~ 20-25
    Estimated by MLE from off-target detection statistics (Eq. 7). It sets the false-alarm probability that defines outliers and drives the null conclusion.
  • Logistic regression coefficients a, b (per candidate) = Not quoted; posterior samples used
    Fitted to injection recovery outcomes (Eqs. 16-17) to derive h95 sensitivity. Central to the reported sensitivity but not to the null detection claim.
  • Disturbed-candidate cut threshold Ltail = 7.5 = 7.5 in normalized log-likelihood units
    Chosen as the 95th percentile of observed Ltail values across 562 candidates (Sec. V A). Excludes 29 candidates from the main result; affects outlier counting and is a data-driven selection.
  • Mismatch contour level mu* = 0.2 for sky grid step sizes = 0.2
    Chosen to define sky grid resolution (Eq. 5, Fig. 3). A design choice that trades template count versus coverage; validated by injection mismatch distribution.
  • Polarization-averaging comparison factor 2.3 = 2.3
    Empirical factor applied to ASAF upper limits to compare with polarization-averaged sensitivities (Sec. V D). Used only for the comparison figure, not for the search result.
assumptions (6)
  • domain assumption Signal model: a CW signal is a quasi-monochromatic sinusoid with slowly evolving frequency, described by the F-statistic template family (isolated or binary with Keplerian orbital motion).
    The entire search and sensitivity estimates assume this signal model (Sec. IV A). Sources with more complex phase evolution, such as strong accretion-driven wandering, may not be fully covered.
  • domain assumption Noise is stationary and Gaussian over each 24-hour coherence segment, so the F-statistic is the optimal detection statistic.
    Standard assumption inherited from LALSuite F-statistic theory (Sec. IV A, Refs. [72,83,84]). Real detector noise is nonstationary, and the off-target sampling is meant to partially correct for this.
  • domain assumption A signal that is present must stay within a single 1/32 Hz frequency bin for the duration of O4a (237 days), giving the bound |fdot| <= 1.526e-9 Hz/s.
    Used to set the spin-down search range (Sec. IV B). If a source had a larger spin-down, it would fall outside the searched grid.
  • ad hoc to paper Off-target sky positions are free of astrophysical signals, so the empirical distribution of their detection statistics equals the noise-only distribution.
    This underpins the exponential tail fit and all false-alarm probabilities (Sec. IV C, quote 'it is assumed that no signals should exist near these off-target templates'). It is plausible but not proven.
  • domain assumption O4b data provide an independent, comparably sensitive re-test of any O4a outlier; a real signal detected in O4a should be detected in O4b.
    The null conclusion follows from the lack of O4b recovery (Sec. V C). Injection recovery at 110% h95 supports this, but only for loud signals.
  • ad hoc to paper The exponential tail model with Ltail at the 96th percentile describes the noise distribution of the detection statistic.
    Used to compute p_fa via Eq. (8). The choice of Ltail at the 96th percentile is a modeling decision; the paper propagates the resulting slope uncertainty (Appendix A).

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Cite this review

Pith. "Pith review of Spotlight searches for continuous gravitational waves triggered on radiometer candidates in LIGO O4a data." pith.science (2026). https://pith.science/paper/Y7MGCS7Y

@misc{pith2026260807312,
  author       = {Pith},
  title        = {Pith review of: Spotlight searches for continuous gravitational waves triggered on radiometer candidates in LIGO O4a data},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/Y7MGCS7Y}},
  note         = {Machine review of arXiv:2608.07312}
}
abstract

We report on a follow-up search for continuous gravitational waves (CWs) targeting sub-threshold candidates from the O4a LIGO-Virgo-KAGRA (LVK) all-sky all-frequency (ASAF) directed radiometer analysis. We analyze a total of $562$ ASAF candidates using Advanced LIGO data from the first part of the fourth LVK observing run. Each candidate comprises a narrow $1/32$ Hz frequency band paired with a ${\sim}13$ deg$^2$ sky pixel, defining the search parameter space for our analysis. Our search pipeline leverages the $F$-statistic matched filter equipped with a hidden Markov model to enable tracking of a potentially frequency-wandering CW signal. Of the 562 initial candidates, we obtain $21$ outliers with false alarm probability less than $5\%$ that survive all instrumental vetoes. None of the outliers are recovered at comparable statistical significance in the second part of the fourth observing run, from which we conclude that no convincing CW signals are detected. We estimate the sensitivity of our analysis by recovering simulated signals added to real detector data. Across the $20\text{--}1726$ Hz frequency band, our search achieves $95\%$ detection efficiency for strain amplitudes in the range of $h_0\sim (0.63\text{--}6.3)\times10^{-25}$ with respect to isolated neutron stars (NSs), and $h_0\sim (0.82\text{--}7.1)\times10^{-25}$ with respect to NSs in long-period ($>1$ yr) binary systems. The large range in sensitivity is due to the strong frequency dependence of detector noise, particularly at low frequencies.

Figures

Figures reproduced from arXiv: 2608.07312 by the authors.

Figure 1
Figure 1. FIG. 1. Sky positions in equatorial coordinates and SNRs of [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2. Data availability for the LIGO Hanford (H1) and LIGO Livingston (L1) detectors during the first (O4a) and second [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 4
Figure 4. FIG. 4. Mismatch distribution based on recovering simulated [PITH_FULL_IMAGE:figures/full_fig_p005_4.png] view at source ↗
Figures from the paper (5 more)
Figure 5
Figure 5. Figure 5: FIG. 5. Binary parameter space probed by our injection re [PITH_FULL_IMAGE:figures/full_fig_p008_5.png]
Figure 6
Figure 6. Figure 6: FIG. 6. Detection statistic tail thresholds, [PITH_FULL_IMAGE:figures/full_fig_p009_6.png]
Figure 8
Figure 8. Figure 8: FIG. 8. Follow up search results for the 21 non-vetoed outliers [PITH_FULL_IMAGE:figures/full_fig_p010_8.png]
Figure 9
Figure 9. Figure 9: FIG. 9. Estimated sensitivity of our follow up analysis at [PITH_FULL_IMAGE:figures/full_fig_p012_9.png]
Figure 10
Figure 10. Figure 10: FIG. 10. Search results for five selected pulsar hardware injec [PITH_FULL_IMAGE:figures/full_fig_p013_10.png]

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Reference graph

Works this paper leans on

100 extracted references · 24 canonical work pages

  1. [1]

    Letf(t n) denote the Viterbi frequency path (including the ˙fcontribution) of the outlier, with 1≤ n≤N T

    Known lines The known lines veto discards outliers whose Viterbi frequency path contains any overlap with a known line artifact. Letf(t n) denote the Viterbi frequency path (including the ˙fcontribution) of the outlier, with 1≤ n≤N T . The outlier is vetoed if the condition 1− v⊕ c fline −f L ≤f(t n)≤ 1 +v⊕ c fline +f R ,(10) is true for anyn, wheref line...

  2. [2]

    In contrast, an astrophysical signal should be present in both detec- tors with comparable signal strength [86]

    Single interferometer The single interferometer veto tests whether one de- tector contributes a disproportionate amount of signal power, which would be indicative of a noise artifact present in one detector but not the other. In contrast, an astrophysical signal should be present in both detec- tors with comparable signal strength [86]. The single interfe...

  3. [3]

    de- tected

    DM-off The DM-off veto tests whether the signal exhibits the Doppler frequency modulations expected of an astrophys- ical signal [87]. This veto involves repeating the search using the same template as the outlier but with Doppler timing corrections disabled inside theF-statistic soft- ware. The outlier is vetoed if the DM-off search both increases the si...

  4. [4]

    The parame- ter sampling ranges are listed in Table I

    Signal injections For each ASAF candidate and source type, we draw a random population ofN inj = 500 test signals from the candidate sky pixel and frequency band. The parame- ter sampling ranges are listed in Table I. We include eccentricities up toe= 0.95 in our binary injections. We impose a constraint when sampling binary injections, namely that the Do...

  5. [5]

    notch list

    Detection efficiency fitting We quantify sensitivity in terms of the minimum strain amplitude at which 95% of signals are detected, h95% 0 (α, δ, f), which is a function of ASAF candidate fre- quency and sky position. We also report corresponding sensitivity depths, defined as D95%(α, δ, f)≡ p Sn(f) Hz h95% 0 (α, δ, f),(14) whereS n(f) is the average nois...

    arXiv 1955

  6. [6]

    Haskell and K

    B. Haskell and K. Schwenzer, Isolated Neutron Stars (2022) arXiv:2104.03137 [gr-qc]

    arXiv 2022

  7. [7]

    Aasiet al.(LIGO Scientific), Advanced LIGO, Class

    J. Aasiet al.(LIGO Scientific), Advanced LIGO, Class. Quant. Grav.32, 074001 (2015), arXiv:1411.4547 [gr-qc]

    arXiv 2015

  8. [8]

    Acerneseet al.(VIRGO), Advanced Virgo: a second- generation interferometric gravitational wave detector, Class

    F. Acerneseet al.(VIRGO), Advanced Virgo: a second- generation interferometric gravitational wave detector, Class. Quant. Grav.32, 024001 (2015), arXiv:1408.3978 [gr-qc]

    arXiv 2015

Show all 100 references
  1. [9]

    (6)), the uncertainty in the slope parameter, ˆλ, will propagate into the final estimate ofp corr fa ( ¯L)

    Becausep corr fa ( ¯L) is derived from a maximum likelihood fit to the noise distribution (see Eq. (6)), the uncertainty in the slope parameter, ˆλ, will propagate into the final estimate ofp corr fa ( ¯L). For completeness, we describe the uncertainty propagation here. In the...

  2. [10]

    Akutsuet al.(KAGRA), KAGRA: 2.5 Generation In- terferometric Gravitational Wave Detector, Nature As- tron.3, 35 (2019), arXiv:1811.08079 [gr-qc]

    T. Akutsuet al.(KAGRA), KAGRA: 2.5 Generation In- terferometric Gravitational Wave Detector, Nature As- tron.3, 35 (2019), arXiv:1811.08079 [gr-qc]

    2019

  3. [11]

    P. D. Lasky, Gravitational Waves from Neutron Stars: A Review, Publ. Astron. Soc. Austral.32, e034 (2015), arXiv:1508.06643 [astro-ph.HE]

    2015 arXiv

  4. [12]

    Sieniawska and M

    M. Sieniawska and M. Bejger, Continuous gravitational waves from neutron stars: current status and prospects, Universe5, 217 (2019), arXiv:1909.12600 [astro-ph.HE]

    2019 arXiv

  5. [13]

    Riles, Searches for continuous-wave gravitational ra- diation, Living Rev

    K. Riles, Searches for continuous-wave gravitational ra- diation, Living Rev. Rel.26, 3 (2023), arXiv:2206.06447 [astro-ph.HE]

    2023 arXiv

  6. [14]

    Wette, Searches for continuous gravitational waves from neutron stars: A twenty-year retrospective, As- tropart

    K. Wette, Searches for continuous gravitational waves from neutron stars: A twenty-year retrospective, As- tropart. Phys.153, 102880 (2023), [Erratum: As- tropart.Phys. 179, 103229 (2026)], arXiv:2305.07106 [gr- qc]

    2023

  7. [15]

    Gittins, Gravitational waves from neutron-star mountains, Class

    F. Gittins, Gravitational waves from neutron-star mountains, Class. Quant. Grav.41, 043001 (2024), arXiv:2401.01670 [gr-qc]

    2024 arXiv

  8. [16]

    Haskell, R-modes in neutron stars: Theory and ob- servations, Int

    B. Haskell, R-modes in neutron stars: Theory and ob- servations, Int. J. Mod. Phys. E24, 1541007 (2015), arXiv:1509.04370 [astro-ph.HE]

    2015 arXiv

  9. [17]

    Abbottet al.(KAGRA, LIGO Scientific, VIRGO), All-sky search for continuous gravitational waves from isolated neutron stars using Advanced LIGO and Ad- vanced Virgo O3 data, Phys

    R. Abbottet al.(KAGRA, LIGO Scientific, VIRGO), All-sky search for continuous gravitational waves from isolated neutron stars using Advanced LIGO and Ad- vanced Virgo O3 data, Phys. Rev. D106, 102008 (2022), arXiv:2201.00697 [gr-qc]

    2022 arXiv

  10. [18]

    Abbottet al.(LIGO Scientific, Virgo, VIRGO), All-sky search in early O3 LIGO data for continuous gravitational-wave signals from unknown neutron stars in binary systems, Phys

    R. Abbottet al.(LIGO Scientific, Virgo, VIRGO), All-sky search in early O3 LIGO data for continuous gravitational-wave signals from unknown neutron stars in binary systems, Phys. Rev. D103, 064017 (2021), [Erra- tum: Phys.Rev.D 108, 069901 (2023)], arXiv:2012.12128 [gr-qc]

    2021 arXiv

  11. [19]

    Steltner, M

    B. Steltner, M. A. Papa, H. B. Eggenstein, R. Prix, M. Bensch, B. Allen, and B. Machenschalk, Deep Ein- stein@Home All-sky Search for Continuous Gravitational Waves in LIGO O3 Public Data, Astrophys. J.952, 55 (2023), arXiv:2303.04109 [gr-qc]

    2023 arXiv

  12. [20]

    McGloughlin, J

    B. McGloughlin, J. Martins, B. Steltner, M. A. Papa, H.- B. Eggenstein, B. Machenschalk, R. Prix, and M. Bensch, Einstein@Home All-sky “Bucket” Search for Continuous Gravitational Waves in LIGO O3a Public Data, Astro- phys. J.997, 149 (2026), arXiv:2508.16423 [gr-qc]

    2026 arXiv

  13. [21]

    McGloughlin, B

    B. McGloughlin, B. Steltner, J. Martins, M. A. Papa, H.-B. Eggenstein, J. Ming, B. Machenschalk, R. Prix, and M. Bensch, High-frequency Continuous Gravitational Wave Search in LIGO O3 Public Data with Einstein@Home, Astrophys. J.998, 205 (2026), arXiv:2508.20073 [gr-qc]

    2026 arXiv

  14. [22]

    A. G. Abacet al.(LIGO Scientific, VIRGO, KAGRA), All-sky Searches for Continuous Gravitational Waves from Isolated Neutron Stars in the Data from the First Part of the Fourth LIGO-Virgo-KAGRA Observing Run, (2026), arXiv:2603.14168 [gr-qc]

    2026

  15. [23]

    A. G. Abacet al.(LIGO Scientific, VIRGO, KAGRA), All-sky search for continuous gravitational-wave signals from unknown neutron stars in binary systems in the first part of the fourth LIGO-Virgo-KAGRA observing run, (2025), arXiv:2511.16863 [gr-qc]

    2025

  16. [24]

    R. Abbottet al.(LIGO Scientific, VIRGO, KAGRA, Virgo), Searches for Continuous Gravitational Waves from Young Supernova Remnants in the Early Third Ob- serving Run of Advanced LIGO and Virgo, Astrophys. J. 921, 80 (2021), arXiv:2105.11641 [astro-ph.HE]

    2021

  17. [25]

    A. G. Abacet al.(KAGRA, VIRGO, LIGO Scientific), Searches for Continuous Gravitational Waves from Su- pernova Remnants in the First Part of the LIGO-Virgo- KAGRA Fourth Observing Run, Astrophys. J.1004, 204 (2026), arXiv:2603.25808 [gr-qc]

    2026 arXiv

  18. [26]

    J. Ming, M. A. Papa, H.-B. Eggenstein, B. Machenschalk, J. Martins, B. Steltner, B. McGloughlin, V. Dergachev, R. Prix, and M. Bensch, Observational Constraints on the Spin/Anisotropy of the Central Compact Objects of Cassiopeia A, Vela Jr., and G347.3–0.5 and a Single Sur- vi...

    2026 arXiv

  19. [27]

    Abbottet al.(LIGO Scientific, VIRGO, KAGRA), Searches for Gravitational Waves from Known Pulsars at Two Harmonics in the Second and Third LIGO- Virgo Observing Runs, Astrophys

    R. Abbottet al.(LIGO Scientific, VIRGO, KAGRA), Searches for Gravitational Waves from Known Pulsars at Two Harmonics in the Second and Third LIGO- Virgo Observing Runs, Astrophys. J.935, 1 (2022), arXiv:2111.13106 [astro-ph.HE]

    2022 arXiv

  20. [28]

    R. Abbottet al.(LIGO Scientific, KAGRA, VIRGO), Narrowband Searches for Continuous and Long-duration Transient Gravitational Waves from Known Pulsars in the LIGO-Virgo Third Observing Run, Astrophys. J. 932, 133 (2022), arXiv:2112.10990 [gr-qc]

    2022 arXiv

  21. [29]

    Abbottet al.(LIGO Scientific, Virgo, KAGRA), Constraints from LIGO O3 Data on Gravitational- wave Emission Due to R-modes in the Glitching Pul- sar PSR J0537–6910, Astrophys

    R. Abbottet al.(LIGO Scientific, Virgo, KAGRA), Constraints from LIGO O3 Data on Gravitational- wave Emission Due to R-modes in the Glitching Pul- sar PSR J0537–6910, Astrophys. J.922, 71 (2021), arXiv:2104.14417 [astro-ph.HE]

    2021

  22. [30]

    A. G. Abacet al.(LIGO Scientific, VIRGO, KAGRA), Search for Continuous Gravitational Waves from Known Pulsars in the First Part of the Fourth LIGO-Virgo- KAGRA Observing Run, Astrophys. J.983, 99 (2025), 15 arXiv:2501.01495 [astro-ph.HE]

    2025

  23. [31]

    A. G. Abacet al.(LIGO Scientific, VIRGO, KA- GRA), Narrowband searches for continuous gravitational waves from known pulsars in the first two parts of the fourth LIGO–Virgo–KAGRA observing run, (2026), arXiv:2603.25938 [gr-qc]

    2026 arXiv

  24. [32]

    A. G. Abacet al.(KAGRA, VIRGO, LIGO Scien- tific), Constraints on Gravitational Waves from the 2024 Vela Pulsar Glitch, Astrophys. J.1005, 12 (2026), arXiv:2512.17990 [gr-qc]

    2026 arXiv

  25. [33]

    Abbottet al.(LIGO Scientific, VIRGO, KAGRA), Search for continuous gravitational waves from 20 accret- ing millisecond x-ray pulsars in O3 LIGO data, Phys

    R. Abbottet al.(LIGO Scientific, VIRGO, KAGRA), Search for continuous gravitational waves from 20 accret- ing millisecond x-ray pulsars in O3 LIGO data, Phys. Rev. D105, 022002 (2022), arXiv:2109.09255 [astro- ph.HE]

    2022 arXiv

  26. [34]

    Middleton, P

    H. Middleton, P. Clearwater, A. Melatos, and L. Dunn, Search for gravitational waves from five low mass X-ray binaries in the second Advanced LIGO observing run with an improved hidden Markov model, Phys. Rev. D 102, 023006 (2020), arXiv:2006.06907 [astro-ph.HE]

    2020 arXiv

  27. [35]

    Abbottet al.(KAGRA, VIRGO, LIGO Scientific), Search for gravitational waves from Scorpius X-1 with a hidden Markov model in O3 LIGO data, Phys

    R. Abbottet al.(KAGRA, VIRGO, LIGO Scientific), Search for gravitational waves from Scorpius X-1 with a hidden Markov model in O3 LIGO data, Phys. Rev. D 106, 062002 (2022), arXiv:2201.10104 [gr-qc]

    2022 arXiv

  28. [36]

    Abbottet al.(LIGO Scientific, KAGRA, VIRGO), Model-based Cross-correlation Search for Gravitational Waves from the Low-mass X-Ray Binary Scorpius X-1 in LIGO O3 Data, Astrophys

    R. Abbottet al.(LIGO Scientific, KAGRA, VIRGO), Model-based Cross-correlation Search for Gravitational Waves from the Low-mass X-Ray Binary Scorpius X-1 in LIGO O3 Data, Astrophys. J. Lett.941, L30 (2022), arXiv:2209.02863 [astro-ph.HE]

    2022 arXiv

  29. [37]

    J. T. Whelanet al., Search for Gravitational Waves from Scorpius X-1 in LIGO O3 Data with Corrected Orbital Ephemeris, Astrophys. J.949, 117 (2023), arXiv:2302.10338 [astro-ph.HE]

    2023 arXiv

  30. [38]

    Abbottet al.(KAGRA, LIGO Scientific, VIRGO), Search for continuous gravitational wave emission from the Milky Way center in O3 LIGO-Virgo data, Phys

    R. Abbottet al.(KAGRA, LIGO Scientific, VIRGO), Search for continuous gravitational wave emission from the Milky Way center in O3 LIGO-Virgo data, Phys. Rev. D106, 042003 (2022), arXiv:2204.04523 [astro-ph.HE]

    2022 arXiv

  31. [39]

    L. Dunn, A. Melatos, P. Clearwater, S. Suvorova, L. Sun, W. Moran, and R. J. Evans, Search for continuous gravi- tational waves from neutron stars in five globular clusters with a phase-tracking hidden Markov model in the third LIGO observing run, Phys. Rev. D111, 083012 (2025...

    2025 arXiv

  32. [40]

    D. H. T. Cheunget al., Search for continuous gravita- tional waves from neutron stars in five globular clusters in the first part of the fourth LIGO-Virgo-KAGRA ob- serving run, (2026), arXiv:2603.04792 [gr-qc]

    2026

  33. [41]

    Abbottet al.(LIGO Scientific, Virgo, KAGRA), All- sky search for gravitational wave emission from scalar boson clouds around spinning black holes in LIGO O3 data, Phys

    R. Abbottet al.(LIGO Scientific, Virgo, KAGRA), All- sky search for gravitational wave emission from scalar boson clouds around spinning black holes in LIGO O3 data, Phys. Rev. D105, 102001 (2022), arXiv:2111.15507 [astro-ph.HE]

    2022 arXiv

  34. [42]

    A. G. Abacet al.(LIGO Scientific, VIRGO, KAGRA), Directed searches for gravitational waves from ultralight vector boson clouds around merger remnant and galac- tic black holes during the first part of the fourth LIGO- Virgo-KAGRA observing run, (2025), arXiv:2509.07352 [gr-qc]

    2025 arXiv

  35. [43]

    Hobbs, A

    G. Hobbs, A. G. Lyne, and M. Kramer, An analysis of the timing irregularities for 366 pulsars, Mon. Not. Roy. Astron. Soc.402, 1027 (2010), arXiv:0912.4537 [astro- ph.GA]

    2010 arXiv

  36. [44]

    R. M. Shannon and J. M. Cordes, Assessing the Role of Spin Noise in the Precision Timing of Millisecond Pul- sars, Astrophys. J.725, 1607 (2010), arXiv:1010.4794 [astro-ph.SR]

    2010 arXiv

  37. [45]

    Price, B

    S. Price, B. Link, S. N. Shore, and D. J. Nice, Time- correlated structure in spin fluctuations in pulsars, Mon. Not. Roy. Astron. Soc.426, 2507 (2012), arXiv:1208.0807 [astro-ph.HE]

    2012 arXiv

  38. [46]

    Parthasarathyet al., Timing of young radio pulsars – I

    A. Parthasarathyet al., Timing of young radio pulsars – I. Timing noise, periodic modulation, and proper mo- tion, Mon. Not. Roy. Astron. Soc.489, 3810 (2019), arXiv:1908.11709 [astro-ph.HE]

    2019 arXiv

  39. [47]

    M. E. Loweret al., The UTMOST pulsar timing pro- gramme – II. Timing noise across the pulsar popula- tion, Mon. Not. Roy. Astron. Soc.494, 228 (2020), arXiv:2002.12481 [astro-ph.HE]

    2020 arXiv

  40. [48]

    Mukherjee, C

    A. Mukherjee, C. Messenger, and K. Riles, Accretion- induced spin-wandering effects on the neutron star in Scorpius X-1: Implications for continuous gravita- tional wave searches, Phys. Rev. D97, 043016 (2018), arXiv:1710.06185 [gr-qc]

    2018 arXiv

  41. [49]

    A. Lyne, C. Jordan, F. Graham-Smith, C. Espinoza, B. Stappers, and P. Weltrvrede, 45 years of rotation of the Crab pulsar, Mon. Not. Roy. Astron. Soc.446, 857 (2015), arXiv:1410.0886 [astro-ph.HE]

    2015 arXiv

  42. [50]

    Keitel, G

    D. Keitel, G. Woan, M. Pitkin, C. Schumacher, B. Pearl- stone, K. Riles, A. G. Lyne, J. Palfreyman, B. Stap- pers, and P. Weltevrede, First search for long-duration transient gravitational waves after glitches in the Vela and Crab pulsars, Phys. Rev. D100, 064058 (2019), arXiv...

    2019 arXiv

  43. [51]

    C. M. Espinoza, D. Antonopoulou, R. Dodson, M. Stepanova, and A. Scherer, Small glitches and other rotational irregularities of the Vela pulsar , Astron. As- trophys.647, A25 (2021), [Erratum: Astron.Astrophys. 649, C2 (2021)], arXiv:2007.02921 [astro-ph.HE]

    2021 arXiv

  44. [52]

    J. R. Fuentes, C. M. Espinoza, A. Reisenegger, B. W. Stappers, B. Shaw, and A. G. Lyne, The glitch activity of neutron stars, Astron. Astrophys.608, A131 (2017), arXiv:1710.00952 [astro-ph.HE]

    2017 arXiv

  45. [53]

    R. N. Manchester, G. B. Hobbs, A. Teoh, and M. Hobbs, The Australia Telescope National Facility pul- sar catalogue, Astron. J.129, 1993 (2005), arXiv:astro- ph/0412641

    2005

  46. [54]

    Messenger, A semi-coherent search strategy for known continuous wave sources in binary systems, Phys

    C. Messenger, A semi-coherent search strategy for known continuous wave sources in binary systems, Phys. Rev. D 84, 083003 (2011), arXiv:1109.0501 [gr-qc]

    2011 arXiv

  47. [55]

    Leaci and R

    P. Leaci and R. Prix, Directed searches for continuous gravitational waves from binary systems: parameter- space metrics and optimal Scorpius X-1 sensitivity, Phys. Rev. D91, 102003 (2015), arXiv:1502.00914 [gr-qc]

    2015 arXiv

  48. [56]

    R. Abbottet al.(KAGRA, Virgo, LIGO Scientific), All- sky, all-frequency directional search for persistent grav- itational waves from Advanced LIGO’s and Advanced Virgo’s first three observing runs, Phys. Rev. D105, 122001 (2022), arXiv:2110.09834 [gr-qc]

    2022 arXiv

  49. [57]

    A. G. Abacet al.(LIGO Scientific, VIRGO, KAGRA), Directional Search for Persistent Gravitational Waves: Results from the First Part of LIGO-Virgo-KAGRA’s Fourth Observing Run, (2025), arXiv:2510.17487 [gr-qc]

    2025 arXiv

  50. [58]

    S. W. Ballmer, A Radiometer for stochastic gravitational waves, Class. Quant. Grav.23, S179 (2006), arXiv:gr- qc/0510096

    2006

  51. [59]

    Mitra, S

    S. Mitra, S. Dhurandhar, T. Souradeep, A. Lazzarini, V. Mandic, S. Bose, and S. Ballmer, Gravitational wave radiometry: Mapping a stochastic gravitational 16 wave background, Phys. Rev. D77, 042002 (2008), arXiv:0708.2728 [gr-qc]

    2008 arXiv

  52. [60]

    Thrane, S

    E. Thrane, S. Ballmer, J. D. Romano, S. Mitra, D. Talukder, S. Bose, and V. Mandic, Probing the anisotropies of a stochastic gravitational-wave back- ground using a network of ground-based laser interferom- eters, Phys. Rev. D80, 122002 (2009), arXiv:0910.0858 [astro-ph.IM]

    2009 arXiv

  53. [61]

    A. Ain, P. Dalvi, and S. Mitra, Fast Gravitational Wave Radiometry using Data Folding, Phys. Rev. D92, 022003 (2015), arXiv:1504.01714 [gr-qc]

    2015 arXiv

  54. [62]

    Thrane, S

    E. Thrane, S. Mitra, N. Christensen, V. Mandic, and A. Ain, All-sky, narrowband, gravitational-wave radiom- etry with folded data, Phys. Rev. D91, 124012 (2015), arXiv:1504.02158 [astro-ph.IM]

    2015 arXiv

  55. [63]

    Goncharov and E

    B. Goncharov and E. Thrane, All-sky radiometer for nar- rowband gravitational waves using folded data, Phys. Rev. D98, 064018 (2018), arXiv:1805.03761 [astro- ph.IM]

    2018 arXiv

  56. [64]

    A. Ain, J. Suresh, and S. Mitra, Very fast stochastic gravitational wave background map making using folded data, Phys. Rev. D98, 024001 (2018), arXiv:1803.08285 [gr-qc]

    2018 arXiv

  57. [65]

    Suresh, A

    J. Suresh, A. Ain, and S. Mitra, Unified mapmaking for an anisotropic stochastic gravitational wave background, Phys. Rev. D103, 083024 (2021), arXiv:2011.05969 [gr- qc]

    2021 arXiv

  58. [66]

    B. P. Abbottet al.(LIGO Scientific, Virgo), Directional Limits on Persistent Gravitational Waves from Advanced LIGO’s First Observing Run, Phys. Rev. Lett.118, 121102 (2017), arXiv:1612.02030 [gr-qc]

    2017 arXiv

  59. [67]

    B. P. Abbottet al.(LIGO Scientific, Virgo), Directional limits on persistent gravitational waves using data from Advanced LIGO’s first two observing runs, Phys. Rev. D 100, 062001 (2019), arXiv:1903.08844 [gr-qc]

    2019 arXiv

  60. [68]

    R. Abbottet al.(KAGRA, Virgo, LIGO Scientific), Search for anisotropic gravitational-wave backgrounds using data from Advanced LIGO and Advanced Virgo’s first three observing runs, Phys. Rev. D104, 022005 (2021), arXiv:2103.08520 [gr-qc]

    2021

  61. [69]

    K. M. G´ orski, E. Hivon, A. J. Banday, B. D. Wan- delt, F. K. Hansen, M. Reinecke, and M. Bartelmann, HEALPix - A Framework for high resolution discretiza- tion, and fast analysis of data distributed on the sphere, Astrophys. J.622, 759 (2005), arXiv:astro-ph/0409513

    2005 arXiv

  62. [70]

    Zonca, L

    A. Zonca, L. P. Singer, D. Lenz, M. Reinecke, C. Rosset, E. Hivon, and K. M. Gorski, healpy: equal area pixeliza- tion and spherical harmonics transforms for data on the sphere in python, Journal of Open Source Software4, 1298 (2019)

    2019

  63. [71]

    A. M. Knee, H. Du, E. Goetz, J. McIver, J. B. Carlin, L. Sun, L. Dunn, L. Strang, H. Middleton, and A. Melatos, Search for continuous gravitational waves directed at subthreshold radiometer candidates in O3 LIGO data, Phys. Rev. D109, 062008 (2024), arXiv:2311.12138 [gr-qc]

    2024 arXiv

  64. [72]

    A. F. Vargas and A. Melatos, Search for gravitational waves from Scorpius X-1 with a hidden Markov model in O3 LIGO data with a corrected orbital ephemeris, Phys. Rev. D111, 084040 (2025), arXiv:2310.19183 [gr-qc]

    2025 arXiv

  65. [73]

    A. G. Abacet al.(LIGO Scientific, VIRGO, KAGRA), Open Data from LIGO, Virgo, and KAGRA through the First Part of the Fourth Observing Run, (2025), arXiv:2508.18079 [gr-qc]

    2025 arXiv

  66. [74]

    Abacet al.(LIGO Scientific, VIRGO, KAGRA), Open Data from LIGO, Virgo, and KAGRA through the Second Part of the Fourth Observing Run, (2026), arXiv:2605.27090 [gr-qc]

    N. Abacet al.(LIGO Scientific, VIRGO, KAGRA), Open Data from LIGO, Virgo, and KAGRA through the Second Part of the Fourth Observing Run, (2026), arXiv:2605.27090 [gr-qc]

    2026 arXiv

  67. [75]

    Soniet al.(LIGO), LIGO Detector Characterization in the first half of the fourth Observing run, Class

    S. Soniet al.(LIGO), LIGO Detector Characterization in the first half of the fourth Observing run, Class. Quant. Grav.42, 085016 (2025), arXiv:2409.02831 [astro-ph.IM]

    2025

  68. [76]

    Capoteet al., Advanced LIGO detector performance in the fourth observing run, Phys

    E. Capoteet al., Advanced LIGO detector performance in the fourth observing run, Phys. Rev. D111, 062002 (2025), arXiv:2411.14607 [gr-qc]

    2025 arXiv

  69. [77]

    Allen, E

    B. Allen, E. Goetz, D. Keitel, M. Landry, G. Mendell, R. Prix, K. Riles, and K. Wette, SFT Data Format Ver- sion 2–3 Specification, LIGO Document Control Center https://dcc.ligo.org/LIGO-T040164/public (2025)

    2025

  70. [78]

    LIGO Scientific Collaboration, Virgo Collaboration, and KAGRA Collaboration, L VK Algorithm Library - LAL- Suite, Free software (GPL) (2018)

    2018

  71. [79]

    Vietset al., Reconstructing the calibrated strain signal in the Advanced LIGO detectors, Class

    A. Vietset al., Reconstructing the calibrated strain signal in the Advanced LIGO detectors, Class. Quant. Grav.35, 095015 (2018), arXiv:1710.09973 [astro-ph.IM]

    2018 arXiv

  72. [80]

    Sunet al., Characterization of systematic error in Ad- vanced LIGO calibration, Class

    L. Sunet al., Characterization of systematic error in Ad- vanced LIGO calibration, Class. Quant. Grav.37, 225008 (2020), arXiv:2005.02531 [astro-ph.IM]

    2020 arXiv

  73. [81]

    Wadeet al., Toward low-latency, high-fidelity cal- ibration of the LIGO detectors with enhanced moni- toring tools, Class

    M. Wadeet al., Toward low-latency, high-fidelity cal- ibration of the LIGO detectors with enhanced moni- toring tools, Class. Quant. Grav.42, 215016 (2025), arXiv:2508.08423 [gr-qc]

    2025

  74. [82]

    Goetz and K

    E. Goetz and K. Riles, Segments used for creating stan- dard SFTs in O4 data, LIGO Document Control Center https://dcc.ligo.org/LIGO-T2400058/public (2025)

    2025

  75. [83]

    Davis, A

    D. Davis, A. Neunzert, E. Goetz, K. Riles, K. Wette, and M. Lalleman, Self-gating of O4a h(t) for use in continuous-wave searches, LIGO Document Control Cen- ter https://dcc.ligo.org/LIGO-T2400003/public (2025)

    2025

  76. [84]

    J. C. Driggerset al.(LIGO Scientific), Improving as- trophysical parameter estimation via offline noise sub- traction for Advanced LIGO, Phys. Rev. D99, 042001 (2019), arXiv:1806.00532 [astro-ph.IM]

    2019 arXiv

  77. [85]

    Davis, T

    D. Davis, T. J. Massinger, A. P. Lundgren, J. C. Driggers, A. L. Urban, and L. K. Nuttall, Improving the Sensitiv- ity of Advanced LIGO Using Noise Subtraction, Class. Quant. Grav.36, 055011 (2019), arXiv:1809.05348 [astro- ph.IM]

    2019 arXiv

  78. [86]

    Vajente, Y

    G. Vajente, Y. Huang, M. Isi, J. C. Driggers, J. S. Kissel, M. J. Szczepanczyk, and S. Vitale, Machine-learning nonstationary noise out of gravitational-wave detectors, Phys. Rev. D101, 042003 (2020), arXiv:1911.09083 [gr- qc]

    2020 arXiv

  79. [87]

    Suvorova, L

    S. Suvorova, L. Sun, A. Melatos, W. Moran, and R. J. Evans, Hidden Markov model tracking of continuous gravitational waves from a neutron star with wandering spin, Phys. Rev. D93, 123009 (2016), arXiv:1606.02412 [astro-ph.IM]

    2016 arXiv

  80. [88]

    L. Sun, A. Melatos, S. Suvorova, W. Moran, and R. J. Evans, Hidden markov model tracking of continuous gravitational waves from young supernova remnants, Phys. Rev. D97, 043013 (2018)

    2018

  81. [89]

    Jaranowski, A

    P. Jaranowski, A. Krolak, and B. F. Schutz, Data analy- sis of gravitational - wave signals from spinning neutron stars. 1. The Signal and its detection, Phys. Rev. D58, 063001 (1998), arXiv:gr-qc/9804014

    1998 arXiv

  82. [90]

    Prix, Search for continuous gravitational waves: Metric of the multi-detector F-statistic, Phys

    R. Prix, Search for continuous gravitational waves: Metric of the multi-detector F-statistic, Phys. Rev. D 75, 023004 (2007), [Erratum: Phys.Rev.D 75, 069901 17 (2007)], arXiv:gr-qc/0606088

    2007 arXiv

  83. [91]

    E. Goetzet al.(O4 LIGO Detector), Narrow spectral artifact investigation and mitigation in LIGO data from the fourth LIGO-Virgo-KAGRA observing run, (2026), arXiv:2606.05959 [astro-ph.IM]

    2026

  84. [92]

    B. P. Abbottet al.(LIGO Scientific, VIRGO), Search for gravitational waves from Scorpius X-1 in the first Ad- vanced LIGO observing run with a hidden Markov model, Phys. Rev. D95, 122003 (2017), arXiv:1704.03719 [gr- qc]

    2017 arXiv

  85. [93]

    Jones, L

    D. Jones, L. Sun, J. Carlin, L. Dunn, M. Millhouse, H. Middleton, P. Meyers, P. Clearwater, D. Beniwal, L. Strang, A. Vargas, and A. Melatos, Validating contin- uous gravitational-wave candidates from a semicoherent search using doppler modulation and an effective point spread...

    2022

  86. [94]

    HTCondor Team, Htcondor (2024)

    2024

  87. [95]

    Pordes, D

    R. Pordes, D. Petravick, B. Kramer, D. Olson, M. Livny, A. Roy, P. Avery, K. Blackburn, T. Wenaus, F. W¨ urthwein, I. Foster, R. Gardner, M. Wilde, A. Blate- cky, J. McGee, and R. Quick, The open science grid, Jour- nal of Physics: Conference Series78, 012057 (2007)

    2007

  88. [96]

    Sfiligoi, D

    I. Sfiligoi, D. C. Bradley, B. Holzman, P. Mhashilkar, S. Padhi, and F. Wurthwein, The pilot way to grid re- sources using glideinwms, in2009 WRI World Congress on Computer Science and Information Engineering, Vol. 2 (2009) pp. 428–432

    2009

  89. [97]

    OSG, OSPool, OSG https://doi.org/10.21231/906P- 4D78 (2006)

    2006 doi

  90. [98]

    OSG, Open Science Data Federation, OSG https://doi.org/10.21231/0KVZ-VE57 (2015)

    2015 doi

  91. [99]

    Karkiet al., The Advanced LIGO Photon Calibrators, Rev

    S. Karkiet al., The Advanced LIGO Photon Calibrators, Rev. Sci. Instrum.87, 114503 (2016), arXiv:1608.05055 [astro-ph.IM]

    2016 arXiv

  92. [100]

    P. Baxi, J. Leviton, E. Morag, M. Pitkin, and K. Riles, Monitoring of continuous-wave hardware injections in LIGO interferometers during the O4 observing run, Class. Quant. Grav.43, 135019 (2026), arXiv:2601.09918 [astro-ph.IM]

    2026

Pith tools

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