Pith. sign in

REVIEW 2 major objections 4 minor 65 references

The Indian Pulsar Timing Array Data Release 2: III. Search for a Stochastic Gravitational Wave Background

T0 review · 2 major / 4 minor · reviewed 2026-08-15 · deepseek-v4-flash

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗ Review JSON

Pith's one-line read This paper reports no statistically significant common red-noise process in the Indian Pulsar Timing Array's second data release and places a 95% upper limit on any gravitational-wave background amplitude.

desk verdict Solid, honest null result from InPTA DR2 with a genuinely useful dual-band chromatic diagnostic; the 'averages out' claim is the only soft spot and is addressable. read the letter →

arxiv 2608.02808 v1 pith:KDC7DTB3 submitted 2026-08-03 astro-ph.HE

Hemanga Tahbildar , Kunjal Vara , Mayuresh Surnis , Churchil Dwivedi , Bhal Chandra Joshi , Sharika Dhakappa , Aman Srivastava , Shantanu Desai
show 23 more authors
Abhimanyu Susobhanan Adya Shukla Himanshu Grover P. Arumugam Manjari Bagchi Neelam Dhanda Batra Manoneeta Chakraborty Shaswata Chowdhury Debabrata Deb A. Gopakumar Sushovan Mondal Kuldeep Meena K Nobleson Avinash Kumar Paladi Arul Pandian B Kaustubh Rai Prerna Rana Shubhit Sardana Vidit Singh Jaikhomba Singha Keitaro Takahashi Pratik Tarafdar Zenia Zuraiq
This is my paper · ORCID
classification astro-ph.HE
keywords stochasticgravitationalwavebackgroundpulsartimingarraycommonuncorrelatedrednoiseHellings-DownscorrelationupperlimitmillisecondpulsarsInPTADR2chromatic
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 reports the first independent search for an isotropic stochastic gravitational-wave background using the second data release of the Indian Pulsar Timing Array, 27 millisecond pulsars observed with the upgraded GMRT over up to 7.2 years. It concludes that the data show no statistically significant common red-noise process in any of four diagnostics, and that the Hellings-Downs quadrupolar correlation expected from a gravitational-wave background is absent. The headline result is a 95% upper limit on the background amplitude of $A_{\rm GWB} < 3.4\times10^{-14}$ at the supermassive-black-hole-binary spectral index $\gamma=13/3$, stable across solar-wind exclusion cuts. The work matters because it adds an independent, dual-frequency dataset to the global pulsar timing array effort and directly demonstrates that residual chromatic noise can masquerade as common-process support in the most precisely timed pulsars.

What carries the argument

The central object is the common uncorrelated red-noise (CURN) process, a common power-law spectrum with independent phase realizations per pulsar, described by amplitude $A_{\rm CURN}$ and spectral index $\gamma_{\rm CURN}$. The argument runs through four diagnostics built on it: the Bayesian CURN posterior with a Savage-Dickey Bayes factor; per-pulsar dropout factors that let each pulsar's participation in the common process switch on or off; importance reweighting of the CURN chain to the Hellings-Downs-correlated model; and the noise-marginalized optimal statistic, which averages the optimal statistic over the posterior of the noise parameters. The Hellings-Downs overlap reduction function $\Gamma_{\rm HD}(\zeta_{ab})$ supplies the spatial-correlation template that must be matched for a gravitational-wave interpretation. The machinery also includes the fixed spectral index $\gamma=13/3$ from the idealized supermassive-black-hole-binary population model, used to convert the non-detection into a prior-dependent 95% upper limit via importance reweighting from a log-uniform to a linear-in-amplitude prior.

What would settle it

Recompute the fiducial 95% upper limit after dropping the three pulsars whose Band 3 dropout factors are inflated (PSRs J1744-1134, J1909-3744, J1600-3053), or after replacing their chromatic noise models with more flexible ones; if the limit moves by more than about 0.05 in $\log_{10} A_{\rm GWB}$, the claim that per-pulsar contamination averages out is not supported.

Watch

Extended reading notes

Core claim

Using a Bayesian common-spectrum search and a noise-marginalized optimal statistic, the paper finds no evidence for a common uncorrelated red-noise process or for Hellings-Downs correlations in InPTA DR2. The free-spectral-index posterior is broad, $\log_{10} A_{\rm CURN} = -13.71^{+1.06}_{-3.28}$ with $\gamma_{\rm CURN}=2.98^{+3.62}_{-2.70}$, and the Savage-Dickey Bayes factor for a common process over noise alone is 2.5, which the paper describes as at most a bare mention on the Jeffreys scale. The optimal-statistic signal-to-noise ratios for monopole, dipole, and Hellings-Downs correlations all peak near zero. Fixing $\gamma=13/3$, the paper places a 95% upper limit $\log_{10} A_{\rm GWB} < -13.47$ ($A_{\rm GWB} < 3.4\times10^{-14}$), robust across solar-elongation cuts of $10^\circ$, $20^\circ$, and $30^\circ$ and consistent between the full dual-band data and Band 5-only data. The paper also shows that several of the most precisely timed pulsars have dropout factors well above unity in the full data that collapse to unity when Band 3 is removed, which it interprets as residual dispersion-measure and scattering power leaking into the common process; it argues this contamination averages out in the array-level amplitude posterior. Simulations with injected signals at $\log_{10} A_{\rm inj}=-14$ indicate that a baseline of at least 10 years is needed before the common red process starts to be recovered.

Load-bearing premise

The analysis assumes that the single-pulsar noise models from the companion analysis fully capture each pulsar's chromatic noise, so that any remaining dispersion-measure or scattering power does not bias the common-process amplitude; the paper itself shows this assumption fails for PSRs J1744-1134, J1909-3744, and J1600-3053, and it argues without a quantitative proof that the contamination averages out at the array level.

Editorial extensions

If this is right

  • The non-detection is consistent with the amplitudes reported by longer-baseline pulsar timing arrays; the paper attributes the difference to the shorter observing span, since the signal-to-noise of a $\gamma=13/3$ background grows steeply with baseline.
  • The reported upper limit is stable under solar-elongation cuts, indicating that unmodelled solar-wind power does not bias the array-level constraint.
  • Dual-band data expose chromatic contamination that single-band arrays cannot resolve: the same pulsars whose dropout factors are inflated by Band 3 would otherwise appear to support a common signal.
  • Simulated extensions of the InPTA data show that extending the observing baseline alone, with 27 pulsars fixed, recovers an injected signal at $\log_{10} A_{\rm inj}=-14$ by roughly 15 years, with a biased high amplitude at 10 years in the full configuration.
  • Because the simulated results hold the pulsar count fixed, adding pulsars remains a complementary route to sensitivity that this forecast does not quantify.

Reading between the lines

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

  • A natural extension is to apply the same Band 3 versus Band 5 dropout comparison to other multi-band pulsar datasets to flag pulsars whose apparent common-process support is chromatic in origin.
  • The claim that per-pulsar chromatic contamination averages out in the array-level posterior is asserted without a quantitative proof; a direct calculation of the array posterior with and without the three affected pulsars would test whether the upper limit remains stable to the stated 0.03-0.05 in $\log_{10} A$.
  • A testable prediction of the paper's interpretation is that the elevated dropout factors for PSRs J1744-1134, J1909-3744, and J1600-3053 will disappear entirely once their chromatic noise models are improved, not merely when Band 3 data are removed.
  • The forecast implies that a 10-year InPTA baseline should show the common-process posterior beginning to concentrate near the injected amplitude; if it instead remains prior-dominated, the chromatic inflation seen at 7.2 years may persist longer than modeled.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 4 minor

Summary. The manuscript reports the first independent pulsar-timing-array search for an isotropic stochastic gravitational-wave background using InPTA DR2: 27 millisecond pulsars with up to 7.2 years of uGMRT dual-band (Band 3 and Band 5) timing data. It applies a Bayesian common-uncorrelated-red-noise (CURN) analysis with per-pulsar dropout factors, a Savage-Dickey Bayes factor, noise-marginalized optimal statistics, and importance reweighting from CURN to Hellings-Downs correlations. The paper finds no statistically significant common red process (Bayes factor 2.5; monopole, dipole, and HD signal-to-noise ratios consistent with zero) and sets a fiducial 95% upper limit of log10 A_GWB < -13.47 (A_GWB < 3.4e-14) at spectral index gamma = 13/3. It also presents injection-recovery simulations projecting how the common-process posterior evolves for 10- and 15-year baselines, concluding that about 10 years are needed to begin recovering an injected signal at log10 A = -14.

Significance. If the results hold, this is a valuable and appropriate contribution: it is the first standalone SGWB constraint from InPTA, exploits the array's simultaneous dual-band capability to expose residual chromatic noise, and ships reproducible code. The analysis follows established enterprise-based PTA methodology and includes multiple cross-checks: dropout factors, solar-wind elongation cuts, Band 3 removal, CURN-to-HD reweighting, and importance reweighting with Kish effective sample sizes. The non-detection is consistent with the array's relatively short baseline and does not conflict with the evidence reported by longer-baseline arrays. The main caveat, the unsupported claim that chromatic contamination 'averages out' at the array level, does not threaten the HD-correlation non-detection but does affect how securely the numerical upper limit can be interpreted.

major comments (2)
  1. [VB4 and VIF] The statement in Section VB4 that residual chromatic power 'averages out in the array-marginalized amplitude posterior' and therefore 'does not bias the array-level amplitude limit' is not quantitatively established. Because the CURN covariance in Eq. (2) is block-diagonal, per-pulsar chromatic leakage enters that pulsar's common-process term additively, and the paper provides no explicit cancellation mechanism at the array level. The only quantitative evidence offered, the 0.05 difference between the full DR2 and Band 5-only limits, compares two configurations and does not show that either is unbiased. More importantly, the paper's own Section VIF and Table II report a short-baseline high-amplitude bias in the full DR2 configuration (log10 A recovered as -13.80 for an injected -14 signal at 7.2 yr) and describe this as 'the same chromatic-inflation signature seen in the real-data full DR2 upper limit.' This appears to contradict the 'does not bias' claim. Please either demonstrate by injection-recovery that the reported 95% upper limit has the stated coverage under the real noise model, or revise the text to state that the limit may be conservatively biased by residual chromatic power.
  2. [VIE-VIF] The forecasting claim that 'it will take at least a 10 year baseline to start recovering the common red noise signal' is drawn from what appears to be a single realization per configuration: the text refers to 'all realizations' but does not state how many independent realizations were generated or averaged. With a single realization, the recovered posteriors in Table II do not carry ensemble error bars, so the 10-year values (log10 A = -13.56 with injected -14 for full DR2; gamma = 3.44 with injected 13/3) do not by themselves establish the onset of recovery. Please either add multiple realizations and report the spread of recovered medians, or soften the language to describe the 10-year posteriors as showing convergence toward the injected values rather than a demonstrated recovery.
minor comments (4)
  1. [Section IVG, Eq. (11)] Please define the tilde notation and the matrices P_I and S_IJ explicitly before first use, since Eq. (11) uses P^{-1}_I \tilde S_IJ P^{-1}_J without defining \tilde S_IJ or the index ranges beyond the surrounding text.
  2. [Section I] The introductory sentence stating that current datasets 'do not yet support a statistically significant detection [8-11]' is in tension with Section VII, which describes [8-11] as having reported evidence in 2023; please harmonize the wording to avoid an apparent contradiction.
  3. [Figure 4 caption] The caption phrase 'sorted by the InPTA-DR2 full DR2 value' is redundant; it should be simplified to 'sorted by the full DR2 dropout factor,' and the figure should explicitly state that the blue points are the Band 5-only configuration.
  4. [Table I and Section VB5] The log-uniform reference quantile varies by 0.04 in log10 A across the elongation cuts (-13.55 to -13.59), while the text's 'stable to within 0.03' statement applies only to the LinearExp column; please specify which quantity the stability claim refers to.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the SGWB search, upper limit, and forecasts are derived from independent inputs and external methods, not from the target result.

full rationale

The derivation chain is self-contained. The single-pulsar noise parameters from the companion analysis [36] are fitted to per-pulsar residuals only; the common-process amplitude and Hellings-Downs correlation are not included in that fit, so the target quantity A_GWB is a genuinely new parameter constrained by the array likelihood (Eqs. 1-4). The spectral index gamma=13/3 used for the headline upper limit is taken from the external idealized SMBHB model (Phinney 2001), not fitted from InPTA data. The injection-recovery forecasts inject a chosen amplitude log10 A_inj=-14 and compare the recovered posteriors against it, which is a falsifiable pipeline check rather than a fit renamed as a prediction. The CURN-to-HD reweighting (Eq. 10) and the noise-marginalized optimal statistic follow established external methodology [45,49]. The paper's repeated assertion that residual chromatic contamination 'averages out' at the array level is an under-demonstrated robustness claim, not a circular step: the full-DR2 versus Band-5-only comparison is an empirical consistency check, and the upper limit is not constructed from the dropout factors. The self-citation to [36] is load-bearing but independent, since that work contains no common-process or HD search and its assumptions do not include the target result. The paper also explicitly flags the 7.2-year simulation validation as a weak test (Sec. VIE), an acknowledged limitation rather than a circular argument. No step reduces by construction to its own input.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

The paper does not introduce free parameters fitted to the target data in a way that biases the central claim. The spectral index gamma = 13/3 is fixed from the standard SMBHB model, not fitted. The simulation injected amplitude log10 A_inj = -14 is chosen as an input and is not fitted to the real data. The analysis relies on standard Gaussian-process PTA likelihood machinery and on noise parameter estimates from the companion SPNA paper [36]; the latter are inputs from prior analysis, not free parameters introduced here. The central result remains a non-detection with an upper limit, so no invented entities are needed.

assumptions (3)
  • domain assumption The timing residuals are realizations of a stationary Gaussian process with the covariance structure in Eq. (1).
    Standard assumption in PTA analyses, stated in Sec. IV A. It is well-established in the field and not particular to this paper.
  • domain assumption The noise parameters from the companion single-pulsar noise analysis [36] are correct and adequate for all 27 pulsars.
    The paper relies on these parameters throughout and itself reports evidence that residual chromatic power is not fully captured (dropout factors rising above unity in full DR2 and falling to unity when Band 3 is removed, Sec. VB2).
  • domain assumption The SMBHB spectral index gamma = 13/3 is the appropriate value for the upper limit.
    This is the standard idealized circular-orbit, GW-only evolution model (Sec. IVB7, Eq. 5), widely used in PTA analyses. It does not affect the free-spectral-index non-detection claim.

how reviews work

0 comments
Cite this review

Pith. "Pith review of The Indian Pulsar Timing Array Data Release 2: III. Search for a Stochastic Gravitational Wave Background." pith.science (2026). https://pith.science/paper/KDC7DTB3

@misc{pith2026260802808,
  author       = {Pith},
  title        = {Pith review of: The Indian Pulsar Timing Array Data Release 2: III. Search for a Stochastic Gravitational Wave Background},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KDC7DTB3}},
  note         = {Machine review of arXiv:2608.02808}
}
abstract

We present the first independent search for an isotropic stochastic gravitational wave background in the second data release of the Indian Pulsar Timing Array, comprising of 27 millisecond pulsars monitored simultaneously in two frequency bands with the upgraded Giant Metrewave Radio Telescope over a maximum 7.2 year baseline. Building on a comprehensive single pulsar noise analysis, we search for a common uncorrelated red noise process within a Bayesian inference framework and with the noise-marginalized optimal statistics, and we test the robustness of the result through per-pulsar dropout analyses and solar-wind exclusion cuts. Leaving the spectral index free, we recover a broad amplitude posterior, $\log_{10} A_{\rm CURN} = -13.71^{+1.06}_{-3.28}$, with an unconstrained spectral index $\gamma_{\rm CURN} = 2.98^{+3.62}_{-2.70}$ and a Savage-Dickey Bayes factor of $2.5$ for a common red process over the no signal model. The optimal-statistic signal to noise ratios for the monopole, dipole, and Hellings-Downs correlations are all consistent with zero. Fixing the spectral index to $\gamma = 13/3$, the value predicted by an idealized toy model in which the background is sourced by a population of supermassive black hole binaries in circular orbits evolving purely under leading-order gravitational radiation reaction, we place a $95\%$ upper limit on the common-process amplitude of $A_{\rm GWB} < 3.4\times10^{-14}$, stable across solar elongation cuts of $10^\circ$, $20^\circ$, and $30^\circ$. This limit lies approximately an order of magnitude above the amplitudes reported by other, longer-running pulsar timing array experiments. We also demonstrate through simulated datasets with the addition of simple chromatic and achromatic noise components that it will take at least a 10 year baseline to start recovering the common red noise signal.

Figures

Figures reproduced from arXiv: 2608.02808 by the authors.

Figure 1
Figure 1. FIG. 1. Per-pulsar dropout factors for the common process [PITH_FULL_IMAGE:figures/full_fig_p007_1.png] view at source ↗
Figure 2
Figure 2. FIG. 2. Marginal posterior on [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. FIG. 3. Joint posterior on the common-process amplitude [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: FIG. 4. Per-pulsar dropout factors for the common process, sorted by the InPTA-DR2 full DR2 value, for InPTA-DR2 full [PITH_FULL_IMAGE:figures/full_fig_p009_4.png]
Figure 5
Figure 5. Figure 5: FIG. 5. Noise marginalized distributions of the optimal [PITH_FULL_IMAGE:figures/full_fig_p009_5.png]
Figure 6
Figure 6. Figure 6: FIG. 6. Marginal posterior distributions for [PITH_FULL_IMAGE:figures/full_fig_p010_6.png]
Figure 7
Figure 7. Figure 7: FIG. 7. Recovered posterior distributions for the common-process amplitude, [PITH_FULL_IMAGE:figures/full_fig_p012_7.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

65 extracted references · 29 canonical work pages

  1. [1]

    White Noise White noise captures fluctuations that are statistically independent from one observation to the next. Three pa- rameters are used to describe it for each backend/receiver combination: EFAC, which rescales the nominal ToA un- certainty; EQUAD, which adds an additional uncertainty term in quadrature; and ECORR, which accounts for noise correlat...

    work page

  2. [2]

    We represent it as a stationary Gaussian process in the Fourier domain, with a power-law spectrum set by an amplitudeA arn (nor- malized atf 1yr) and a spectral indexγarn

    Achromatic Red Noise Achromatic red noise (ARN), sometimes referred to as spin noise, reflects long timescale, frequency independent variability in the pulsar’s rotation. We represent it as a stationary Gaussian process in the Fourier domain, with a power-law spectrum set by an amplitudeA arn (nor- malized atf 1yr) and a spectral indexγarn. The spectral d...

    work page

  3. [3]

    Dispersion Measure Noise Time variable free electron content along the pulsar’s line of sight produces frequency dependent delays scaling asν −2, referred to as dispersion measure noise (DMN). As with ARN, this is captured by a power-law Gaussian process in the Fourier domain, here with an additional frequency scaling term evaluated relative to a fiducial...

    work page

  4. [4]

    (8)-(9) of [36]), we allow the chromatic indexχfcn to vary freely, resulting in the free chromatic noise (FCN) model

    Free Chromatic Noise Rather than assuming the fixedν−4 scaling of a stan- dard scattering noise model (defined in Eqs. (8)-(9) of [36]), we allow the chromatic indexχfcn to vary freely, resulting in the free chromatic noise (FCN) model. This added flexibility accommodates pulsar-to-pulsar differ- ences in the chromatic power spectrum that a fixed thin scr...

    work page

  5. [5]

    Solar Wind Noise Ionized plasma flowing radially outward from the Sun modifies the total electron content along the line of sight within the Solar system, inducing a frequency dependent delay that varies with both the pulsar’s DM and its solar elongation as they change over the course of a year. We model this effect in a deterministic way by expanding the...

    work page

  6. [6]

    Common Uncorrelated Red Noise As an intermediate step, we first search for a com- mon spectrum process affecting all pulsars with identi- cal power spectral density but independent phase real- izations. This common uncorrelated red noise model has covariance: CCURN =block-diag(C CURN 1 ,C CURN 2 ,...,C CURN M ),(2) where each block has the same functional...

    work page

  7. [7]

    Hellings-Downs Correlations ThetrueSGWBsignatureisdistinguishedfromCURN by the presence of inter-pulsar correlations following the Hellings-Downs curve [25]. For a stochastic background 5 of gravitational waves with an isotropic and unpolar- ized distribution, the expected correlation between tim- ing residuals from pulsarsaandbseparated by angleζ is: ΓHD...

    work page

  8. [8]

    An- toniadis, P

    EPTA Collaboration, InPTA Collaboration, J. An- toniadis, P. Arumugam, S. Arumugam, S. Babak, M. Bagchi, A. S. Bak Nielsen, C. G. Bassa, A. Bathula, A. Berthereau, M. Bonetti, E. Bortolas, P. R. Brook, M. Burgay, R. N. Caballero, A. Chalumeau, D. J. Cham- pion, S. Chanlaridis, S. Chen, I. Cognard, S. Danda- pat, D. Deb, S. Desai, G. Desvignes, N. Dhanda-B...

    arXiv 2023

Show all 65 references
  1. [9]

    Common-process posterior and Bayes factor We first search for a CURN process across the ar- ray using the Bayesian framework of Section IV, with the spectral index left as a free parameter. The re- covered marginal posterior on the amplitude is broad, withlog 10ACURN =−13.71 +...

  2. [10]

    Dropout factors To test whether the common-process is supported by the array as a whole rather than driven by a few pul- sars, we compute the per-pulsar dropout factors of Sec- tion IVC for two configurations (Figure 4). For the fidu- cial combined full DR2 data, the dropout f...

  3. [11]

    Optimal Statistic As an independent hybrid frequentist check, we ap- ply the NMOS (Section IVG), computing the S/N for three overlap-reduction functions (Figure 5). The noise marginalized S/N distributions peak near zero for the monopole (−0.34), dipole (−0.42), and HD correla...

  4. [12]

    We compute the limit for both dataset configurations, the combined full DR2 and the Band 5 only data, with the results shown in Figure 6

    Upper limit on the common-process amplitude Given the absence of a common-process detection, we place an upper limit on the common-spectrum amplitude following the procedure of Section IVE, with the spec- tral index fixed at the SMBHB value expected from a population of inspir...

  5. [13]

    Robustness to Solar-wind contamination As a final robustness check, we assess the sensitivity of the constraint to residual Solar-wind contamination by recomputing the95%upper limit after excluding all TOAs within solar elongations of10◦,20 ◦, and30◦. As in Section IVE, the sp...

    2023

  6. [14]

    Einstein, Sitzungsberichte der Königlich Preussischen Akademie der Wissenschaften , 688 (1916)

    A. Einstein, Sitzungsberichte der Königlich Preussischen Akademie der Wissenschaften , 688 (1916)

    1916

  7. [15]

    R. A. Hulse and J. H. Taylor, ApJ195, L51 (1975)

    1975

  8. [16]

    B. P. Abbott, R. Abbott, T. D. Abbott, and et al., Phys. Rev. Lett.116, 061102 (2016), arXiv:1602.03837 [gr-qc]

    2016 arXiv

  9. [17]

    LIGO Scientific Collaboration, J. Aasi, J. Abadie, and et al., Classical and Quantum Gravity32, 074001 (2015), arXiv:1411.4547 [gr-qc]

    2015 arXiv

  10. [18]

    Amaro-Seoane, H

    P. Amaro-Seoane, H. Audley, S. Babak, and et al., arXiv e-prints , arXiv:1702.00786 (2017), arXiv:1702.00786 [astro-ph.GA]

    2017 arXiv

  11. [19]

    M. V. Sazhin, Soviet Ast.22, 36 (1978)

    1978

  12. [20]

    R. S. Foster and D. C. Backer, ApJ361, 300 (1990)

    1990

  13. [21]

    L. Bian, J. s. Shu, B. Wang, Q. Yuan, and J. Zong, Phys. Rev. D106, L101301 (2022), arXiv:2205.07293 [astro-ph.CO]

    2022 arXiv

  14. [22]

    Agazie, A

    G. Agazie, A. Anumarlapudi, A. M. Archibald, Z. Ar- zoumanian, P. T. Baker, B. Bécsy, L. Blecha, A. Brazier, P. R. Brook, S. Burke-Spolaor, R. Burnette, R. Case, M. Charisi, S. Chatterjee, K. Chatziioannou, B. D. Cheeseboro, S. Chen, T. Cohen, J. M. Cordes, N. J. Cornish, F. C...

    2023 arXiv

  15. [23]

    D. J. Reardon, A. Zic, R. M. Shannon, and et al., ApJ 951, L6 (2023), arXiv:2306.16215 [astro-ph.HE]

    2023 arXiv

  16. [24]

    H. Xu, S. Chen, Y. X. Guo, and et al., Research in Astronomy and Astrophysics23, 075024 (2023), arXiv:2306.16216 [astro-ph.HE]

    2023 arXiv

  17. [25]

    Hewish, S

    A. Hewish, S. J. Bell, J. D. H. Pilkington, P. F. Scott, and R. A. Collins, Nature217, 709 (1968)

    1968

  18. [26]

    D. C. Backer, S. R. Kulkarni, C. Heiles, M. M. Davis, and W. M. Goss, Nature300, 615 (1982)

    1982

  19. [27]

    Hobbs, L

    G. Hobbs, L. Guo, R. N. Caballero, W. Coles, K. J. Lee, R. N. Manchester, D. J. Reardon, D. Matsakis, M. L. Tong, Z. Arzoumanian, M. Bailes, C. G. Bassa, N. D. R. Bhat, A. Brazier, S. Burke-Spolaor, D. J. Champion, S.Chatterjee, I.Cognard, S.Dai, G.Desvignes, T.Dolch, R. D. Fe...

    2020 arXiv

  20. [28]

    Detweiler, ApJ234, 1100 (1979)

    S. Detweiler, ApJ234, 1100 (1979)

    1979

  21. [29]

    Agazie, A

    G. Agazie, A. Anumarlapudi, A. M. Archibald, Z. Ar- zoumanian, P. T. Baker, B. Bécsy, L. Blecha, A. Brazier, P. R. Brook, S. Burke-Spolaor, M. Charisi, S. Chatter- jee, T. Cohen, J. M. Cordes, N. J. Cornish, F. Crawford, H. T. Cromartie, K. Crowter, M. E. Decesar, P. B. De- mo...

    2023 arXiv

  22. [30]

    R.T.Edwards, G.B.Hobbs, andR.N.Manchester,MN- RAS372, 1549 (2006), arXiv:astro-ph/0607664 [astro- ph]

    2006 arXiv

  23. [31]

    Lentati, S

    L. Lentati, S. R. Taylor, C. M. F. Mingarelli, and et al., MNRAS453, 2576 (2015), arXiv:1504.03692 [astro-ph.HE]

    2015 arXiv

  24. [32]

    E. S. Phinney, arXiv e-prints , astro-ph/0108028 (2001), arXiv:astro-ph/0108028 [astro-ph]

    2001 arXiv

  25. [34]

    Antoniadis, S

    J. Antoniadis, S. Babak, A. S. Bak Nielsen, and et al., A&A678, A48 (2023), arXiv:2306.16224 [astro-ph.HE]

    2023 arXiv

  26. [35]

    Madge, E

    E. Madge, E. Morgante, C. Puchades-Ibáñez, N. Ram- berg, W. Ratzinger, S. Schenk, and P. Schwaller, Journal of High Energy Physics2023, 171 (2023), arXiv:2306.14856 [hep-ph]

    2023 arXiv

  27. [36]

    Burke-Spolaor, S

    S. Burke-Spolaor, S. R. Taylor, M. Charisi, T. Dolch, J. S. Hazboun, A. M. Holgado, L. Z. Kelley, T. J. W. Lazio, D. R. Madison, N. McMann, C. M. F. Mingarelli, A. Rasskazov, X. Siemens, J. J. Simon, and T. L. Smith, The Astronomy and Astrophysics Review27, 5 (2019), arXiv:181...

    2019 arXiv

  28. [37]

    Di Marco, A

    V. Di Marco, A. Zic, R. M. Shannon, and E. Thrane, MNRAS532, 4026 (2024), arXiv:2401.07471 [astro- ph.HE]

    2024

  29. [38]

    R. W. Hellings and G. S. Downs, ApJ265, L39 (1983)

    1983

  30. [39]

    F. A. Jenet, G. B. Hobbs, W. van Straten, R. N. Manch- ester, M. Bailes, J. P. W. Verbiest, R. T. Edwards, A. W. Hotan, J. M. Sarkissian, and S. M. Ord, ApJ653, 1571 (2006), arXiv:astro-ph/0609013 [astro-ph]

    2006 arXiv

  31. [40]

    J. R. Gair, J. D. Romano, and S. R. Taylor, Phys. Rev. D 92, 102003 (2015), arXiv:1506.08668 [gr-qc]

    2015 arXiv

  32. [41]

    C. M. F. Mingarelli, T. Sidery, I. Mandel, and A. Vec- chio, Phys. Rev. D88, 062005 (2013), arXiv:1306.5394 [astro-ph.HE]

    2013 arXiv

  33. [42]

    B. C. Joshi, P. Arumugasamy, M. Bagchi, D. Bandy- opadhyay, A. Basu, N. Dhanda Batra, S. Bethapudi, A. Choudhary, K. De, L. Dey, A. Gopakumar, Y. Gupta, M. A. Krishnakumar, Y. Maan, P. K. Manoharan, A. Naidu, R. Nandi, D. Pathak, M. Surnis, and A. Su- sobhanan, Journal of Astr...

    2018

  34. [43]

    B. C. Joshi, A. Gopakumar, A. Pandian, T. Prabu, L. Dey, M. Bagchi, S. Desai, P. Tarafdar, P. Rana, Y. Maan, N. D. Batra, R. Girgaonkar, N. Agarwal, P. Arumugam, A. Basu, A. Bathula, S. Dandapat, Y. Gupta, S. Hisano, R. Kato, D. Kharbanda, T. Kiku- naga, N. Kolhe, M. A. Krishn...

    2022

  35. [44]

    The95%upper limit is then the0.95weighted quantile of the marginal amplitude posterior

    confirming a stable reweighted posterior in each case. The95%upper limit is then the0.95weighted quantile of the marginal amplitude posterior. F. Likelihood Reweighting from CURN to HD A full HD search requires evaluating the cross- correlation terms of the array covariance ma...

  36. [45]

    Swarup, S

    G. Swarup, S. Ananthakrishnan, V. K. Kapahi, A. P. Rao, C. R. Subrahmanya, and V. K. Kulkarni, Current Science60, 95 (1991)

    1991

  37. [46]

    Gupta, B

    Y. Gupta, B. Ajithkumar, H. S. Kale, S. Nayak, S. Sab- hapathy, S. Sureshkumar, R. V. Swami, J. N. Chen- galur, S. K. Ghosh, C. H. Ishwara-Chandra, B. C. Joshi, N. Kanekar, D. V. Lal, and S. Roy, Current Science113, 707 (2017)

    2017

  38. [47]

    Tarafdar, K

    P. Tarafdar, K. Nobleson, P. Rana, J. Singha, M. A. Kr- ishnakumar, B. C. Joshi, A. K. Paladi, N. Kolhe, N. D. Batra, N. Agarwal, A. Bathula, S. Dandapat, S. Desai, L. Dey, S. Hisano, P. Ingale, R. Kato, D. Kharbanda, T. Kikunaga, P. Marmat, B. A. Pandian, T. Prabu, A. Srivast...

    2022 arXiv

  39. [48]

    P. Rana, P. Tarafdar, K. Nobleson, C. Dwivedi, B. Chan- dra Joshi, D. Deb, S. Mondal, M. A. Krishnakumar, A. Shukla, J. Singha, H. Grover, H. Tahbildar, A. Susob- hanan, M. Surnis, S. Desai, N. D. Batra, A. Srivastava, V. Bharambe, J. Jose, V. Vyasraj, S. Jose Jacob, Amar- nat...

    2025 arXiv

  40. [49]

    Nobleson, C

    K. Nobleson, C. Dwivedi, S. Desai, B. C. Joshi, H. Grover, D. Deb, V. Vyasraj, K. Vara, H. Tahbildar, A. Susobhanan, M. Surnis, A. Srivastava, S. Sardana, K. Takahashi, Amarnath, P. Arumugam, M. Bagchi, N. D. Batra, M. Chakraborty, S. Chowdhury, S. J. Ja- cob, J. Jose, S. Kala...

    2026

  41. [50]

    Srivastava, S

    A. Srivastava, S. Desai, N. Kolhe, M. Surnis, B. C. Joshi, A. Susobhanan, A. Chalumeau, S. Hisano, K. Noble- son, S. Arumugam, D. Kharbanda, J. Singha, P. Taraf- dar, P. Arumugam, M. Bagchi, A. Bathula, S. Danda- pat, L. Dey, C. Dwivedi, R. Girgaonkar, A. Gopakumar, Y. Gupta, ...

    2023 arXiv

  42. [51]

    van Haasteren, Y

    R. van Haasteren, Y. Levin, P. McDonald, and T. Lu, MNRAS395, 1005 (2009), arXiv:0809.0791 [astro-ph]

    2009 arXiv

  43. [52]

    S. R. Taylor, M. Vallisneri, J. A. Ellis, and et al., ApJ 821, 13 (2016), arXiv:1511.05564 [astro-ph.HE]

    2016 arXiv

  44. [53]

    enterprise: Enhanced Numerical Toolbox Enabling Ro- bust Estimates of Pulsar Inherent Signals, enterprise Software,

    J. A. Ellis, S. J. Vigeland, M. A. McLaughlin, and et al., “enterprise: Enhanced Numerical Toolbox Enabling Ro- bust Estimates of Pulsar Inherent Signals, enterprise Software,” Astrophysics Source Code Library, record ascl:2004.007 (2020), ascl:2004.007

    2020

  45. [54]

    van Haasteren and M

    R. van Haasteren and M. Vallisneri, Phys. Rev. D88, 044024 (2013), arXiv:1210.0584 [gr-qc]

    2013 arXiv

  46. [55]

    Arzoumanian, P

    Z. Arzoumanian, P. T. Baker, H. Blumer, B. Bécsy, A. Brazier, P. R. Brook, S. Burke-Spolaor, S. Chatter- jee, S. Chen, J. M. Cordes, N. J. Cornish, F. Craw- ford, H. T. Cromartie, M. E. Decesar, P. B. Demorest, T. Dolch, J. A. Ellis, E. C. Ferrara, W. Fiore, E. Fon- seca, N. G...

    2020 arXiv

  47. [56]

    J. M. Dickey, The Annals of Mathematical Statistics42, 204 (1971)

    1971

  48. [57]

    Kish,Survey Sampling(Wiley & Sons, 1995)

    L. Kish,Survey Sampling(Wiley & Sons, 1995)

    1995

  49. [58]

    Hourihane, P

    S. Hourihane, P. Meyers, S. Vigeland, S. R. Taylor, J. A. Ellis, J. S. Hazboun, C. M. F. Mingarelli, and M. Val- lisneri, ApJ958, L37 (2023), arXiv:2212.06276 [gr-qc]

    2023 arXiv

  50. [59]

    Anholm, S

    M. Anholm, S. Ballmer, J. D. E. Creighton, and et al., Phys. Rev. D79, 084030 (2009), arXiv:0809.0701 [gr-qc]

    2009 arXiv

  51. [60]

    P. B. Demorest, R. D. Ferdman, M. E. Gonzalez, and et al., ApJ762, 94 (2013), arXiv:1201.6641 [astro- ph.HE]

    2013 arXiv

  52. [61]

    S. J. Chamberlin, J. D. E. Creighton, P. B. Demor- est, and et al., Phys. Rev. D91, 044048 (2015), arXiv:1410.8256 [gr-qc]

    2015 arXiv

  53. [62]

    S. J. Vigeland, K. Islo, S. Burke-Spolaor, and et al., Phys. Rev. D98, 044003 (2018), arXiv:1805.12188 [gr- qc]

    2018 arXiv

  54. [63]

    N. Pol, S. Taylor, S. Vigeland, L. Kelley, J. Simon, S. Chen, and Nanograv Collaboration, inAmerican As- tronomical Society Meeting Abstracts #237, American Astronomical Society Meeting Abstracts, Vol. 237 (2021) p. 433.01

    2021

  55. [64]

    Trotta, Contemporary Physics49, 71 (2008), arXiv:0803.4089 [astro-ph]

    R. Trotta, Contemporary Physics49, 71 (2008), arXiv:0803.4089 [astro-ph]

    2008 arXiv

  56. [65]

    libstempo: Python wrapper for Tempo2,

    M. Vallisneri, “libstempo: Python wrapper for Tempo2,” Astrophysics Source Code Library, record ascl:2002.017 (2020), ascl:2002.017

    2020

  57. [66]

    Siemens, J

    X. Siemens, J. Ellis, F. Jenet, and J. D. Romano, Classical and Quantum Gravity30, 224015 (2013), arXiv:1305.3196 [astro-ph.IM]

    2013 arXiv

Pith tools

Reviewed August 15, 2026 · model on record in the stance chip above.