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REVIEW 4 major objections 5 minor 54 references

Pulsar Cyclic Spectroscopy in the Partial-Deconvolution Regime: Benefits & Limitations

T0 review · 4 major / 5 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read Cyclic spectroscopy remains useful when full deconvolution is impossible: partial phase retrieval still recovers the scintillation pattern and enables scattering-delay measurements.

desk verdict Worth engaging: the empirical partial-deconvolution demonstration is useful, but cyclic merit 2.0 is a calibrated fit rather than an independent predictor, and the phase-retrieval claim needs simulation support before it is trusted. read the letter →

arxiv 2505.13832 v3 pith:TPWEEOLN submitted 2025-05-20 astro-ph.HE

Jacob E. Turner , Timothy Dolch , Paul B. Demorest , Ryan S. Lynch , Daniel R. Stinebring , Cody Jessup , Nathaniel Jones , Christopher Scheithauer This is my paper · ORCID
classification astro-ph.HE
keywords cyclicspectroscopypulsartimingarraysinterstellarmediumscintillationdynamicwavefieldscatteringdelaymeritradioastronomymethods
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

Cyclic spectroscopy is usually judged by whether it can fully deconvolve the interstellar-medium transfer function from a pulsar's pulse. This paper argues that even when full deconvolution is out of reach, the technique still beats conventional spectroscopy: the dynamic wavefield power recovers the complete scintillation pattern, partial phase information appears in the wavefield, and fine frequency resolution makes scattering-delay and scintillation-bandwidth measurements possible for highly scattered pulsars. The authors demonstrate this on baseband observations of three millisecond pulsars, quantify how recovered phase improves as observing frequency approaches the full-deconvolution boundary, and show that useful signal can be extracted before complete phase retrieval is achieved. They also introduce a revised figure of merit, cyclic merit 2.0, which ranks pulsars by per-scintle signal-to-noise rather than observing bandwidth, and calibrate a threshold for expecting deconvolution success. If correct, pulsar timing arrays can obtain interstellar-medium and timing information from observations that fall short of complete phase recovery.

What carries the argument

The load-bearing object is the cyclic spectrum $S_E(\nu,\alpha_k)=\langle E(\nu+\alpha_k/2)E^*(\nu-\alpha_k/2)\rangle$, through which the periodic pulsar signal is resampled at harmonics $\alpha_k=k/P$ of the pulse period, bypassing the usual time-frequency (Gabor) resolution limit. In the interstellar-medium case the cyclic spectrum factors into the intrinsic pulse transform times a bilinear product of the transfer function $H$, so the transfer function, and hence the dynamic wavefield $H(\nu,t)$, can be recovered by iterative deconvolution. Full deconvolution requires the scintillation bandwidth to satisfy $\Delta\nu_d\lesssim 1/W_{10}$, where $W_{10}$ is the pulse width at 10% of maximum. In the partial-deconvolution regime the same machinery still produces a dynamic wavefield whose squared modulus is the dynamic wavefield power and whose 2D Fourier transform is the secondary wavefield. The paper's new diagnostic, cyclic merit 2.0, replaces observing bandwidth with scintillation bandwidth in the signal-to-noise estimate, which changes which pulsars appear promising.

What would settle it

Compute cyclic merit 2.0 for a large sample and observe the predicted-best and predicted-worst pulsars with sensitive telescopes; if deconvolution success rates do not separate according to the 0.05 threshold, the calibration is falsified. Alternatively, on a single partial-deconvolution observation, compare the dynamic wavefield power pixel-by-pixel with the simultaneously measured dynamic spectrum: if some scintles appear in one data product and not the other, the paper's 'complete signal recovery' claim for the wavefield power would be falsified.

Watch

Extended reading notes

Core claim

The paper's central claim is that complete phase retrieval is not the dividing line for the usefulness of cyclic spectroscopy. Using observations of three millisecond pulsars in both the full- and partial-deconvolution regimes, it shows that the squared modulus of a partially recovered dynamic wavefield, $|H(\nu,t)|^2$, reproduces the same scintillation pattern as the dynamic spectrum and yields nearly identical scintillation-bandwidth power-law fits, despite the wavefield phase being only partly recovered. Phase retrieval is found to be continuous: closer to the full-deconvolution boundary, more of the wavefield phase survives as signal structure rather than noise. The paper therefore concludes that partial-deconvolution data should be treated as incomplete rather than incorrect, and that cyclic processing is preferable to Fourier spectroscopy in all regimes when baseband data or a cyclic backend are available. It further claims that a modest cyclic merit can coexist with no observable deconvolution for low-flux, highly scattered pulsars, motivating a new predictor, cyclic merit 2.0, in which signal-to-noise is evaluated over a single scintillation bandwidth rather than the observing band; a power-law calibration maps the old threshold $m_{\rm cyc}\gg 1$ to $m_{\rm cyc,2.0}\gg 0.05$.

Load-bearing premise

The prediction of which pulsars will benefit rests on a power-law calibration between the old and new cyclic merits computed from one pulsar sample; if that mapping does not transfer to other telescopes, observing bands, or sources, the headline threshold of 0.05 and the source rankings would not hold.

Editorial extensions

If this is right

  • Pulsar timing arrays can measure scattering delays for highly scattered pulsars even when full cyclic deconvolution fails, improving noise models and gravitational-wave sensitivity.
  • Scintillation-bandwidth power-law studies of the interstellar medium can be done from dynamic wavefield power instead of dynamic spectra, with nearly identical measurements and extra harmonic information.
  • Observing strategies should favor lower frequencies and highly scattered pulsars with narrow scintles, because phase recovery improves continuously toward the full-deconvolution boundary.
  • Cyclic merit 2.0, once calibrated, lets observers rank pulsars by per-scintle signal-to-noise, exposing sources whose apparent merit is inflated by large scattering delay but whose faint flux per scintle makes deconvolution impractical.
  • The upcoming availability of a cyclic spectroscopy backend would let observers obtain these benefits without retaining baseband data.

Reading between the lines

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

  • The claim that dynamic wavefield power fully mirrors the dynamic spectrum in the partial regime could be quantified with a pixel-by-pixel residual statistic; testing this across many epochs would delimit exactly how complete the 'complete signal recovery' actually is.
  • A natural prospective test is to pre-select pulsars predicted above the cyclic merit 2.0 threshold of 0.05, observe them, and compare deconvolution success rates against the old merit; this would validate or refute the transferability of the power-law calibration.
  • The partial-recovery results suggest a hybrid pipeline the paper advocates but does not test: use cyclic spectroscopy to anchor the wavefield amplitude, and apply the $\theta-\theta$ transform only where its single-screen, anisotropic-scattering assumption holds, reserving cyclic partial phase for multi-screen lines of sight.
  • Because the full-deconvolution boundary fluctuates with scintillation bandwidth from epoch to epoch, scheduling decisions could treat cyclic merit as a live observing metric rather than a static catalog value.
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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

4 major / 5 minor

Summary. This paper investigates whether cyclic spectroscopy retains benefits for pulsar observations outside the full-deconvolution regime, where the scintillation bandwidth exceeds the inverse pulse width and complete recovery of the ISM transfer function is not possible. The authors analyze baseband observations of PSR B1937+21 (Arecibo ASP and PUPPI; GBT VEGAS), PSR J1643−1224, and PSR J1903+0327 (GBT), compute the cyclic figure of merit mcyc (Eq. 5) and full-deconvolution regime boundaries (Eq. 3), and extend these estimates to the NANOGrav 12.5-year pulsar sample under GBT and DSA-2000 sensitivities (Figs. 2–4). Comparing data products across regimes, they report that the partial-deconvolution dynamic wavefield contains coherent structure indicative of incomplete but genuine phase retrieval (Figs. 6–7); that dynamic wavefield power recovers the scintillation pattern and yields scintillation-bandwidth power-law fits nearly identical to those from the dynamic spectrum (Figs. 8–9); and that partial recovery of the secondary wavefield is possible, with the θ−θ transform discussed as a complementary approach (Figs. 10–11). Motivated by the null result for PSR J1903+0327—in the full-deconvolution regime yet with no discernible phase recovery—the paper introduces 'cyclic merit 2.0', based on scintillation rather than observing bandwidth, and uses a power-law fit (Fig. 18) to translate the original mcyc ≫ 1 threshold into mcyc,2.0 ≫ 0.05.

Significance. The central claim—that partial cyclic deconvolution still yields useful phase information and that dynamic wavefield power recovers the scintillation pattern in the partial-deconvolution regime—is practically important, since most NANOGrav pulsars are observed outside the full-deconvolution regime. If it holds, pulsar timing arrays could justify adopting cyclic processing for essentially all observations, with real gains in scattering-delay estimation and ISM studies. The survey-style merit and regime-boundary calculations for the full NANOGrav sample, with explicitly stated receiver and sky-temperature assumptions, are a genuinely useful planning resource for the GBT and DSA-2000. The paper's strengths include its detailed data products, its willingness to report the J1903+0327 null result, its explicit acknowledgment that part of the phase-imaginary resemblance is a small-angle effect, and its fair treatment of the θ−θ transform's limitations. The significance is currently capped by the absence of ground-truth or simulated validation of the partial-phase-retrieval claim, and by the under-specified, self-calibrated definition of cyclic merit 2.0.

major comments (4)
  1. [Section 5, definition of cyclic merit 2.0] Cyclic merit 2.0 is never defined by an equation. The text states that it 'behaves identical to the original cyclic merit' but 'relies on scintillation bandwidth rather than observing bandwidth' and that 'S/N now relies on flux density over a single scintle rather than the width of the observing band.' Since the original mcyc in Eq. (5) inherits its S/N from the bandwidth-dependent estimate of Eq. (8), the definition of mcyc,2.0 is ambiguous as written: exactly which bandwidth (full observing band, PFB channel, or scintillation bandwidth) enters the S/N term, and is the effective-pulse-width factor unchanged? Without an explicit formula, the values in Figs. 16–18 and the headline threshold are not reproducible. Please provide the full formula for mcyc,2.0 and state all assumptions used to compute it.
  2. [Section 5, Fig. 18] The decision threshold mcyc,2.0 ≫ 0.05 is obtained from a power-law fit between mcyc,2.0 and mcyc computed on the same NANOGrav sample with the same S/N model (Eq. 8) used to rank those same pulsars in Figs. 16 and 17. Because mcyc,2.0 is constructed from the same underlying quantities (scattering delay, S/N, pulse widths) as mcyc, the fit in Fig. 18 largely demonstrates self-correlation; it does not establish that mcyc,2.0 predicts deconvolution success on any independent outcome. No known-outcome test (e.g., the observations in Table 2 or a held-out set) is reported. The fit parameters, scatter, and residuals for Fig. 18 are not given, and the criterion as stated ('≫ 0.05') is non-operational: the paper does not state the mcyc,2.0 value corresponding to its own suggestion that mcyc ≳ 10 is sufficient. Given that the metric is motivated by the single J1903+0327 failure case, the 0.05 threshold should either be validated on independent outcomes or explicitly presented as a provisional calibration.
  3. [Section 4.2, Figs. 6–8] The central claim that genuine partial phase retrieval occurs rests on visual inspection of the recovered wavefields. In the partial-deconvolution regime the true H(ν,t) is unknown, so the coherent patches in Fig. 6 and the banded phase structure in Fig. 7 cannot be distinguished from regions of high S/N in which the iterative pycyc deconvolution converges to a stable but arbitrary phase. The paper itself notes in Section 4.2 that the phase and imaginary components resemble each other mainly because many recovered phases are near zero, which weakens the claim that non-trivial phase information is being recovered, and Section 4.3 reports non-physical power at negative delays in the partial-regime secondary wavefield. Moreover, the trend of more complete phase retrieval near the full-deconvolution regime (Fig. 7) is degenerate: observing frequency, S/N per scintle, and scattering delay vary together across the sub-bands, so the same trend would be expected even if the recovered phase were S/N-weighted noise. No simulation with an injected phase screen or quantitative phase-error measurement against the full-deconvolution control observation is provided. An end-to-end simulation with a known transfer function is needed to support the headline claim of partial phase retrieval, or the claim should be substantially softened.
  4. [Section 4.2, Fig. 9] The claim that the dynamic wavefield power shows 'complete signal recovery' in the partial-deconvolution regime is supported only by visual similarity to the dynamic spectrum (Fig. 8) and by the power-law fits of scintillation bandwidth versus frequency in Fig. 9. Such fits aggregate many scintles and are insensitive to pixel-level errors such as normalization offsets, smearing, or S/N-dependent bias, so they establish similar aggregate scintillation statistics but not faithful image recovery. Please either temper the 'complete signal recovery' wording or add a quantitative fidelity check, such as a cross-correlation or residual statistics between the dynamic spectrum and the wavefield power over the same time-frequency region.
minor comments (5)
  1. [Table 2] The 'a' note to the PSR J1903+0327 Δνd entry says the value was 'estimated from pulse broadening-inferred scattering delay'; please state explicitly how the conversion was made (presumably via Eq. 6 with C1 = 0.957) so the reader can propagate the uncertainty correctly.
  2. [Section 3.2] The pycyc iterative deconvolution is treated as a black box; a sentence on the update rule, initialization, number of iterations, and stopping criterion would materially aid reproducibility, particularly since the partial-regime results are interpreted as genuine phase recovery.
  3. [Section 3.4.1, Eq. (7)] The approximation Σk k² a_k ≈ (P/We)^{3/2} is stated without derivation; please cite the derivation in Turner et al. (2023) or give a brief justification of the step.
  4. [Fig. 8] The full- and partial-regime panels use different color scales (2–10 versus 1–6 in arbitrary units); a shared normalization or an explicit statement of the scales would make the claimed 'complete signal recovery' easier for the reader to judge.
  5. [Section 4.1.2, Figs. 2–4] The NANOGrav survey calculations depend on several assumed constants (C1 = 0.957, filling factor 0.2, and S/N bandwidths of 5/50/100 MHz); a brief sensitivity check of the merit rankings over the stated allowed ranges (e.g., C1 ∈ [0.6, 1.5]) would clarify how robust the conclusions in Figs. 2–4 are.

Circularity Check

1 steps flagged · score 6.0 of 10

Cyclic merit 2.0 threshold is fitted on the same NANOGrav sample it then labels, while the core partial-phase-retrieval analysis is independent.

  1. fitted input called prediction [Sec. 5 (Cyclic Merit 2.0) and Fig. 18; expectation labels in Figs. 16–17 captions.]
    "To determine how cyclic merit 2.0 can be used to estimate the likelihood of successful cyclic deconvolution, we compared how a given pulsar’s calculated cyclic merit 1.0 differed from its corresponding cyclic merit 2.0 at a given observing frequency, with the results shown in Figure 18. By examining this behavior in log space, we can see that the resulting trend can be described quite well by a simple power law fit. When performing such an analysis in aggregate, our fit indicates that the original cyclic deconvolution threshold of mcyc≫ 1 translates to mcyc,2.0≫ 0.05."

    Threshold 0.05 is obtained by a power-law fit to mcyc vs mcyc,2.0 computed for the same NANOGrav pulsars and same S/N model (Eq. 8) that are then ranked in Figs. 16–17, whose captions assert 'We would expect full cyclic deconvolution for sources with mcyc,2.0 ≫ 0.05.' The expectation is therefore a restatement of the fit, not an independent test against known deconvolution outcomes. The only external anchor, PSR J1903+0327's lack of results, is the same case that motivated the new metric, so its low 'assuringly' ranking is by construction. The metric is calibrated and then the calibrated values are used as evidence for the metric's usefulness. The independent partial-phase-retrieval demonstration is unaffected.

full rationale

The main load-bearing empirical claim—that partial-deconvolution cyclic spectroscopy recovers useful phase information and a useful dynamic wavefield power—is supported by direct comparisons of full- and partial-regime wavefields (Figs. 5–8) and by power-law fits of scintillation bandwidth from dynamic spectra versus dynamic wavefield power (Fig. 9). Those comparisons are not circular: the data products are constructed independently from the same baseband data, and no parameter is fitted from one product to force the other. The paper's reliance on prior work by the same authors (Dolch et al. 2021; Turner et al. 2023) is also not circular, because the cyclic merit formula and radical approximation are stated explicitly and applied rather than imported as an unexamined uniqueness theorem. The one genuine circularity is the calibration of the new cyclic merit 2.0 threshold: mcyc,2.0 ≫ 0.05 is obtained by a power-law fit between mcyc and mcyc,2.0 computed on the same NANOGrav pulsars and same S/N estimates that are then ranked and labeled 'expect full cyclic deconvolution' in Figs. 16–17. This is a self-calibration presented as a predictive threshold, and the only external failure case (PSR J1903+0327) is the same case used to motivate the metric. That makes the source-ranking and threshold component partially circular, even though the partial-phase-retrieval result stands independently. Score 6 reflects that the central demonstration is independent but one 'prediction' (the mcyc,2.0 expectation threshold) reduces to its own fit.

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

The central demonstration relies on standard cyclic-spectroscopy models rather than invented entities. The forward-looking metric, however, depends on several hand-picked scaling laws, an assumed radiometer S/N model, and a fitted calibration threshold.

free parameters (5)
  • C1 conversion constant = 0.957
    Chosen conversion constant in Eq. 6 assuming thin-screen Kolmogorov turbulence; the paper notes C1 can range 0.6-1.5, so this choice affects all scattering delays and cyclic merits.
  • Assumed S/N bandwidths for NANOGrav survey = 5 MHz at 350 MHz, 50 MHz at 820 MHz, 100 MHz at 1500 MHz
    Used in Eq. 8 as the bandwidth over which scintles are assumed not to evolve; a hand-picked modeling choice that strongly affects estimated cyclic merits for the full NANOGrav sample.
  • Filling factors for scintle count = eta_nu = eta_t = 0.2
    Used in Eq. 4 to estimate the uncertainty in scintillation bandwidth; standard Cordes 1986 values but are chosen, not measured.
  • Scintillation scaling indices = nu^4.4 for bandwidth, nu^1.2 for timescale
    Used in Sec. 3.4.2 to scale parameters between observing frequencies for all NANOGrav pulsars; an assumed model, not individually fitted.
  • Cyclic merit 2.0 decision threshold = 0.05 (mcyc,2.0 much greater than 0.05)
    Derived from a power-law fit between old and new cyclic merits on the same NANOGrav sample (Sec. 5, Fig. 18); a fitted calibration, not an independently derived threshold.
assumptions (6)
  • domain assumption The observed cyclic spectrum factorizes as SE(nu, alpha_k) = <H(nu+alpha_k/2)H*(nu-alpha_k/2)> Sx(nu, alpha_k) (Eq. 2), separating the ISM transfer function from the intrinsic pulse.
    Invoked in Sec. 1 and used for all wavefield reconstructions; assumes stationary cyclostationarity over the scintillation timescale.
  • domain assumption Full cyclic deconvolution is possible when Delta_nu_d is less than or about 1/W10 (Eq. 3).
    Used in Sec. 3.4.1 to classify observations as full or partial; taken from cyclic spectroscopy sensitivity limits.
  • domain assumption Scattering delay can be estimated from scintillation bandwidth by Delta_nu_d = C1/(2 pi tau_d) with C1 = 0.957 (Eq. 6).
    Used in Sec. 3.4.1 to convert Delta_nu_d to tau_d for the cyclic merit; assumes thin-screen Kolmogorov scattering.
  • domain assumption The radiometer equation (Eq. 8) with assumed telescope gain, system temperature, and bandwidth gives a valid S/N estimate for each NANOGrav pulsar.
    Used in Sec. 3.4.2 to compute cyclic merits for the NANOGrav sample; the assumed bandwidths (5/50/100 MHz) are choices, not measurements.
  • domain assumption Scintillation bandwidth and timescale scale as nu^4.4 and nu^1.2 across observing frequencies.
    Used to extrapolate NANOGrav measurements to 350/820/1500 MHz in Sec. 3.4.2; standard scaling but not valid for all lines of sight.
  • domain assumption The theta-theta transform requires a single anisotropic phase screen to recover the secondary wavefield.
    Invoked in Sec. 4.3 when explaining the shortcomings of the theta-theta transform for complex lines of sight; standard assumption of that method.

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Pith. "Pith review of Pulsar Cyclic Spectroscopy in the Partial-Deconvolution Regime: Benefits & Limitations." pith.science (2026). https://pith.science/paper/TPWEEOLN

@misc{pith2026250513832,
  author       = {Pith},
  title        = {Pith review of: Pulsar Cyclic Spectroscopy in the Partial-Deconvolution Regime: Benefits & Limitations},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/TPWEEOLN}},
  note         = {Machine review of arXiv:2505.13832}
}
abstract

We explore possible advantages of cyclic spectroscopy for observations of pulsars in instances where full cyclic deconvolution is not feasible. We compute cyclic merits and full-deconvolution regime boundaries for pulsars observed by NANOGrav and discuss which sources stand to benefit the most from using cyclic spectroscopy when observed with the Green Bank Telescope and DSA-2000 in a given frequency range. We compare data products, namely the wavefield, in both full-deconvolution and partial-deconvolution regimes to demonstrate what can be accomplished with incomplete phase retrieval. Additionally, we show how some phase retrieval can still be achieved in the partial-deconvolution regime and how this allows for additional information in scintillation-based data products, like the dynamic wavefield power, compared to what can be found in traditional dynamic spectra. An examination of dynamic wavefield phase as a function of observing frequency reveals more complete phase retrieval is achieved the closer one gets to the full deconvolution regime, agreeing with the expectations of cyclic merit. While we demonstrate that fragmentary recovery of the secondary wavefield can be accomplished in the partial-deconvolution regime, we advocate for a synergistic approach with phase retrieval methods like the $\theta-\theta$ transform, although we also provide discussion about shortcomings of this strategy. Finally, we use the combination of modest cyclic merit and lack of discernible results for PSR J1903$+$0327 to motivate the creation of an updated "cyclic merit 2.0", which relies on scintillation bandwidth instead of observing bandwidth.

Figures

Figures reproduced from arXiv: 2505.13832 by the authors.

Figure 1
Figure 1. Cyclic merit over observing frequency for PSR B1937+21 on MJD 60581. This metric decreases as a source is observed further from the full-deconvolution regime. 4.1.2. NANOGrav Observations Cyclic merit estimations for NANOGrav pulsars when ob￾served with the GBT or DSA-2000 can be seen in Figures 2 and 3, respectively, while estimations of each pulsar’s thresh￾old to the full deconvolution regime are shown in [PITH_… view at source ↗
Figure 2
Figure 2. Estimated cyclic merits for pulsars in the NANOGrav 12.5-year data set at observing frequencies of 350 (red diamonds), 820 (orange crosses), and 1500 (blue circles) MHz assuming data were taken with the GBT. We would expect full cyclic deconvolution for sources with mcyc ≫ 1 [PITH_FULL_IMAGE:figures/full_fig_p008_2.png] view at source ↗
Figure 3
Figure 3. Estimated cyclic merits for pulsars in the NANOGrav 12.5-year data set at observing frequencies of 820 (orange crosses) and 1500 (blue circles) MHz assuming data were taken with DSA-2000. We would expect full cyclic deconvolution for sources with mcyc ≫ 1 [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figures from the paper (15 more)
Figure 4
Figure 4. Figure 4: Estimated maximum observing frequency for pulsars in the NANOGrav 12.5-year data set to be observed in the full deconvolution regime [PITH_FULL_IMAGE:figures/full_fig_p010_4.png]
Figure 5
Figure 5. Figure 5: Imaginary (top left), real (top right), and phase components of the dynamic wavefield for a PSR B1937+21 observation in the full￾deconvolution regime. The prevalence of structure throughout all three images indicates this observation has complete phase retrieval. 1 for…
Figure 6
Figure 6. Figure 6: Imaginary (top left), real (top right), and phase components of the dynamic wavefield for a PSR B1937+21 observation in the partial￾deconvolution regime. The inconsistency of structure throughout all three images indicates this observation has incomplete phase retrieva…
Figure 7
Figure 7. Figure 7: Example dynamic wavefield phase retrieval over frequency for an observation of PSR B1937+21 in the partial deconvolution regime. As indicated by the continuity of cyclic merit, the closer to the full deconvolution regime one observes, the higher the cyclic merit and th…
Figure 8
Figure 8. Figure 8: Dynamic wavefield powers from PSR B1937+21 observations with full (left) and partial (right) phase retrieval. As indicated by the full reconstruction of the scintillation pattern, the dynamic wavefield power with incomplete phase retrieval still recovers the frequency …
Figure 9
Figure 9. Figure 9: Scintillation bandwidth power law fits using both dy￾namic spectra (DS; blue circles) and dynamic wavefield power (WF; orange triangles) from an observation of PSR B1937+21. Any dif￾ferences in measurements between the two trends can primarily be attributed to the diff…
Figure 10
Figure 10. Figure 10: Secondary wavefields (left) and secondary spectra (right) from PSR B1937+21 observations in the full (top) and partial (bottom) deconvolution regimes. The limited degree to which scattered images are recovered, along with the presence of images at non-physical delays …
Figure 11
Figure 11. Figure 11: Attempted recovered phase (left) and secondary wavefield (right) using the θ − θ implementation found in SCINTOOLS (Reardon et al. 2020; Sprenger et al. 2021; Baker et al. 2022) of the partial-deconvolution regime observation of PSR B1937+21 shown in earlier figures. …
Figure 12
Figure 12. Figure 12: Recovered dynamic spectrum (left) and intensity pulse profile (right) of PSR J1643–1224 from an observation processed with cyclic spectroscopy. The periodic black bands indicate gaps between polyphase filterbank channels. array sensitivities (Agazie et al. 2023b), we …
Figure 13
Figure 13. Figure 13: Example dynamic (left) and secondary (right) spectra for PSR J1643–1224 across a single PFB channel. Significant, detailed scintillation structure is visible in the dynamic spectrum and a scintillation arc is visibile in the secondary spectrum [PITH_FULL_IMAGE:figure…
Figure 14
Figure 14. Figure 14: Scintillation bandwidth power law fit for an observation of PSR J1643−1224. The narrow scintles allow for precise estima￾tions and many measurements across the observing band, resulting in highly constrained scaling indices. this technique, both from a cyclic deconvol…
Figure 15
Figure 15. Figure 15: Cyclic merit over multiples of the scintillation timescale at different observing frequencies with 33 (left) and 100 (right) MHz of bandwidth for PSR J1903+0327. The low cyclic merit even after long integration times suggests significantly more sensitive instruments w…
Figure 16
Figure 16. Figure 16: Estimated cyclic merit 2.0 for pulsars in the NANOGrav 12.5-year data set at observing frequencies of 350 (red diamonds), 820 (orange crosses), and 1500 (blue circles) MHz assuming data were taken with the GBT. We would expect full cyclic deconvolution for sources wit…
Figure 17
Figure 17. Figure 17: Estimated cyclic merits 2.0 for pulsars in the NANOGrav 12.5-year data set at observing frequencies of 820 (orange crosses) and 1500 (blue circles) MHz assuming data were taken with DSA-2000. We would expect full cyclic deconvolution for sources with mcyc,2.0 ≫ 0.05 …
Figure 18
Figure 18. Figure 18: Cyclic merit 1.0 (x-axis) and 2.0 (y-axis) at 350 (red squares), 820 (orange crosses), and 1500 (blue circles) MHz for all pulsars in NANOGrav’s 12.5-year data set. A simple power law fit indicates that the original mcyc ≫ 1 threshold corresponds approx￾imately to mcy…

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  1. [1]

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  2. [2]

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  3. [3]

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  4. [4]

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  8. [8]

    F., Anumarlapudi, A., et al

    Agazie, G., Alam, M. F., Anumarlapudi, A., et al. 2023 a , The Astrophysical Journal Letters, 951, L9, 10.3847/2041-8213/acda9a

    doi:10.3847/2041-8213/acda9a 2023

Show all 54 references
  1. [9]

    M., et al

    Agazie, G., Anumarlapudi, A., Archibald, A. M., et al. 2023 b , ApJL, 951, L10, 10.3847/2041-8213/acda88

    2023 doi

  2. [10]

    F., Arzoumanian, Z., Baker, P

    Alam, M. F., Arzoumanian, Z., Baker, P. T., et al. 2020, The Astrophysical Journal Supplement Series, 252, 4, 10.3847/1538-4365/abc6a0

    2020 doi

  3. [11]

    P., Tollerud , E

    Astropy Collaboration , Robitaille , T. P., Tollerud , E. J., et al. 2013, , 558, A33, 10.1051/0004-6361/201322068

    2013 doi

  4. [12]

    H., et al

    Baker , D., Brisken , W., van Kerkwijk , M. H., et al. 2022, , 510, 4573, 10.1093/mnras/stab3599

    2022 doi

  5. [13]

    H., van Lieshout, R., & Pen, U.-L

    Baker, D., Brisken, W., van Kerkwijk, M. H., van Lieshout, R., & Pen, U.-L. 2023, Monthly Notices of the Royal Astronomical Society, 525, 211, 10.1093/mnras/stad2318

    2023 doi

  6. [14]

    D., et al

    Burgay , M., Bailes , M., Bates , S. D., et al. 2013, , 433, 259, 10.1093/mnras/stt721

    2013 doi

  7. [15]

    Cordes, J. M. 1986, ApJ, 311, 183, 10.1086/164764

    1986 doi

  8. [16]

    M., & Lazio, T

    Cordes, J. M., & Lazio, T. J. W. 2002, NE2001.I. A New Model for the Galactic Distribution of Free Electrons and its Fluctuations

    2002

  9. [17]

    M., & Rickett, B

    Cordes, J. M., & Rickett, B. J. 1998, ApJ, 507, 846, 10.1086/306358

    1998 doi

  10. [18]

    M., Weisberg , J

    Cordes , J. M., Weisberg , J. M., & Boriakoff , V. 1985, , 288, 221, 10.1086/162784

    1985 doi

  11. [21]

    S., McLaughlin , M., Olszanski , T

    Deneva , J. S., McLaughlin , M., Olszanski , T. E. E., et al. 2024, , 271, 23, 10.3847/1538-4365/ad19da

    2024 doi

  12. [22]

    R., Jones, G., et al

    Dolch, T., Stinebring, D. R., Jones, G., et al. 2021, ApJ, 913, 98, 10.3847/1538-4357/abf48b

    2021 doi

  13. [23]

    B., Schinzel , F

    Dowell , J., Taylor , G. B., Schinzel , F. K., Kassim , N. E., & Stovall , K. 2017, , 469, 4537, 10.1093/mnras/stx1136

    2017 doi

  14. [24]

    M., Lam, M

    Geiger, A., Cordes, J. M., Lam, M. T., et al. 2025, The Astrophysical Journal, 986, 191, 10.3847/1538-4357/add0b6

    2025 doi

  15. [25]

    J., & Gaensler, B

    Harvey-Smith, L., Madsen, G. J., & Gaensler, B. M. 2011, The Astrophysical Journal, 736, 83, 10.1088/0004-637X/736/2/83

    2011 doi

  16. [26]

    Hunter, J. D. 2007, CSE, 9, 90, 10.1109/MCSE.2007.55

    2007 doi

  17. [27]

    A., Bailes, M., Ord, S

    Jacoby, B. A., Bailes, M., Ord, S. M., Knight, H. S., & Hotan, A. W. 2007, The Astrophysical Journal, 656, 408, 10.1086/509312

    2007 doi

  18. [28]

    Lam , M. T. 2017, PyPulse: PSRFITS handler . 1706.011

    2017

  19. [29]

    T., McLaughlin, M

    Lam, M. T., McLaughlin, M. A., Arzoumanian, Z., et al. 2019, ApJ, 872, 193, 10.3847/1538-4357/ab01cd

    2019 doi

  20. [30]

    A., Jones, G., et al

    Levin, L., McLaughlin, M. A., Jones, G., et al. 2016, ApJ, 818, 166. http://stacks.iop.org/0004-637X/818/i=2/a=166

    2016

  21. [31]

    Liu , Y., Verbiest , J. P. W., Main , R. A., et al. 2022, , 664, A116, 10.1051/0004-6361/202142552

    2022 doi

  22. [32]

    Mahajan, N., & van Kerkwijk, M. H. 2023, The Astrophysical Journal, 955, 33, 10.3847/1538-4357/acec3a

    2023 doi

  23. [33]

    A., Antoniadis, J., Chen, S., et al

    Main, R. A., Antoniadis, J., Chen, S., et al. 2023, Monthly Notices of the Royal Astronomical Society, 525, 1079, 10.1093/mnras/stad1980

    2023 doi

  24. [34]

    A., Antoniadis, J., et al

    Mall, G., Main, R. A., Antoniadis, J., et al. 2022, Monthly Notices of the Royal Astronomical Society, 511, 1104, 10.1093/mnras/stac096

    2022 doi

  25. [35]

    E., Spiewak , R., Swiggum , J

    McEwen , A. E., Spiewak , R., Swiggum , J. K., et al. 2020, , 892, 76, 10.3847/1538-4357/ab75e2

    2020 doi

  26. [36]

    K., Cordes, J

    Ocker, S. K., Cordes, J. M., & Chatterjee, S. 2020, The Astrophysical Journal, 897, 124, 10.3847/1538-4357/ab98f9

    2020 doi

  27. [37]

    K., Cordes, J

    Ocker, S. K., Cordes, J. M., Chatterjee, S., et al. 2023, Monthly Notices of the Royal Astronomical Society, 527, 7568, 10.1093/mnras/stad3683

    2023 doi

  28. [38]

    Price , D. C. 2016, PyGDSM: Python interface to Global Diffuse Sky Models , Astrophysics Source Code Library, record ascl:1603.013

    2016

  29. [39]

    J., Coles , W

    Reardon , D. J., Coles , W. A., Bailes , M., et al. 2020, , 904, 104, 10.3847/1538-4357/abbd40

    2020 doi

  30. [40]

    J., Bigot-Sazy , M

    Remazeilles , M., Dickinson , C., Banday , A. J., Bigot-Sazy , M. A., & Ghosh , T. 2015, , 451, 4311, 10.1093/mnras/stv1274

    2015 doi

  31. [41]

    2021, , 500, 1114, 10.1093/mnras/staa3353

    Sprenger , T., Wucknitz , O., Main , R., Baker , D., & Brisken , W. 2021, , 500, 1114, 10.1093/mnras/staa3353

    2021 doi

  32. [42]

    H., Thorsett , S

    Stairs , I. H., Thorsett , S. E., & Camilo , F. 1999, , 123, 627, 10.1086/313245

    1999 doi

  33. [43]

    R., McLaughlin , M

    Stinebring , D. R., McLaughlin , M. A., Cordes , J. M., et al. 2001, , 549, L97, 10.1086/319133

    2001 doi

  34. [44]

    E., Stinebring , D

    Turner , J. E., Stinebring , D. R., McLaughlin , M. A., et al. 2023, , 944, 191, 10.3847/1538-4357/acb6fd

    2023 doi

  35. [45]

    E., McLaughlin , M

    Turner , J. E., McLaughlin , M. A., Cordes , J. M., et al. 2021, , 917, 10, 10.3847/1538-4357/abfafe

    2021 doi

  36. [46]

    E., Dolch, T., Cordes, J

    Turner, J. E., Dolch, T., Cordes, J. M., et al. 2024, The Astrophysical Journal, 972, 16, 10.3847/1538-4357/ad5af9

    2024 doi

  37. [47]

    C., & Varoquaux , G

    van der Walt , S., Colbert , S. C., & Varoquaux , G. 2011, CSE, 13, 22

    2011

  38. [48]

    2011, , 28, 1, 10.1071/AS10021

    van Straten , W., & Bailes , M. 2011, , 28, 1, 10.1071/AS10021

    2011 doi

  39. [49]

    A., Demorest, P

    Walker, M. A., Demorest, P. B., & van Straten, W. 2013, The Astrophysical Journal, 779, 99, 10.1088/0004-637X/779/2/99

    2013 doi

  40. [50]

    A., Koopmans, L

    Walker, M. A., Koopmans, L. V. E., Stinebring, D. R., & Van Straten, W. 2008, Monthly Notices of the Royal Astronomical Society, 388, 1214, 10.1111/j.1365-2966.2008.13452.x

    2008

  41. [51]

    A., & Stinebring , D

    Walker , M. A., & Stinebring , D. R. 2005, , 362, 1279, 10.1111/j.1365-2966.2005.09396.x

    2005

  42. [52]

    F., Han , J

    Wang , P. F., Han , J. L., Xu , J., et al. 2023, Research in Astronomy and Astrophysics, 23, 104002, 10.1088/1674-4527/acea1f

    2023 doi

  43. [53]

    2024, , 961, 48, 10.3847/1538-4357/ad0724

    Wang , X.-W., Yan , Z., Shen , Z.-Q., et al. 2024, , 961, 48, 10.3847/1538-4357/ad0724

    2024 doi

  44. [54]

    M., Manchester , R

    Yan , W. M., Manchester , R. N., van Straten , W., et al. 2011, , 414, 2087, 10.1111/j.1365-2966.2011.18522.x

    2011

  45. [55]

    Young, O., & Lam, M. T. 2024, The Astrophysical Journal, 962, 131, 10.3847/1538-4357/ad1ce7

    2024 doi

  46. [56]

    S., et al

    Zheng , H., Tegmark , M., Dillon , J. S., et al. 2017, , 464, 3486, 10.1093/mnras/stw2525

    2017 doi

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