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arxiv: 2604.15500 · v1 · submitted 2026-04-16 · 🌌 astro-ph.HE

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Joint Detection and Characterization of the Standing Accretion Shock Instability for Core-Collapse Supernovae with cWB XP

Claudia Moreno, Javier M. Antelis, Marek J. Szczepa\'nczyk, Michelle Zanolin, Vicente Sierra, Zidu Lin

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Pith reviewed 2026-05-10 09:48 UTC · model grok-4.3

classification 🌌 astro-ph.HE
keywords standing accretion shock instabilitycore-collapse supernovaegravitational wavesneutrino signalsLIGO O3 O4 datacoherent WaveBurstmultimessenger detectionSASI identification probability
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The pith

An enhanced coherent WaveBurst XP algorithm applied to real LIGO O3 and O4 data delivers the highest sensitivity to date for detecting the standing accretion shock instability in core-collapse supernovae via gravitational waves and neutrino

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

This paper shows that an updated version of the coherent WaveBurst software called XP can quantitatively identify the standing accretion shock instability in core-collapse supernovae by analyzing real gravitational-wave data from LIGO's O3 and O4 runs together with neutrino signals. It reports improved estimates of signal parameters such as central frequency and duration while presenting identification probabilities through receiver operating characteristic curves. The combined multimessenger approach yields higher detection rates than earlier work for O3 data, and the gravitational-wave channel alone reaches near-perfect identification scores for O4 data even at 10 kiloparsecs. A sympathetic reader would care because this instability is thought to play a key role in how massive stars explode as supernovae, and reliable detection in actual detector data brings multimessenger observations closer to probing that mechanism directly. The focus remains on separating genuine SASI signatures from real instrumental noise without relying solely on simulated data.

Core claim

The paper presents the most sensitive to-date multimessenger detection of the standing accretion shock instability in real interferometric data, which quantitatively identifies the presence of the SASI in core-collapse supernovae using neutrino and gravitational-wave signals. In the GW channel, the coherent WaveBurst software on its version XP is implemented with real LIGO data from the O3 and O4 observing runs, obtaining more accurate estimation of parameters such as the central frequency and signal duration. The SASI identification probability versus false alarm rates is presented in the form of ROC curves. For O3, the combined GW and neutrino detection shows identification probabilities (

What carries the argument

coherent WaveBurst XP (cWB XP) algorithm, which processes real LIGO gravitational-wave data to estimate SASI parameters and compute identification probabilities against false alarm rates in a multimessenger framework with neutrino signals

If this is right

  • For O3 data the combined gravitational-wave and neutrino channel achieves SASI identification probabilities of 1.0 at 1 kpc, 0.90 at 5 kpc and 0.37 at 10 kpc for a false identification probability of 0.10, improving on earlier results.
  • For O4 data the gravitational-wave channel alone reaches identification probabilities of 1.0 at 1 kpc, 0.99 at 5 kpc and 0.97 at 10 kpc for a false identification probability of 0.01.
  • Parameter estimates for central frequency and signal duration become more accurate when cWB XP is applied to the real LIGO observing runs.
  • Receiver operating characteristic curves quantify the trade-off between SASI identification probability and false alarm rate in actual interferometric data.
  • The gravitational-wave channel alone becomes sufficient for high-confidence SASI detection at distances up to 10 kpc in the O4 data set.

Where Pith is reading between the lines

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

  • Future LIGO runs could incorporate real-time cWB XP triggers to flag potential SASI events for rapid multimessenger follow-up.
  • If a nearby supernova produces signals matching the reported probabilities, it would provide direct evidence that the standing accretion shock instability operates during the explosion.
  • The same pipeline might be tested on data from other gravitational-wave detectors to cross-check identification rates independent of LIGO-specific noise.
  • Extending the joint neutrino plus gravitational-wave analysis to include electromagnetic observations could further reduce false positives in supernova searches.

Load-bearing premise

The cWB XP implementation on real LIGO O3 and O4 data can reliably separate SASI signals from detector noise and other sources without introducing significant biases in the reported identification probabilities or parameter estimates.

What would settle it

A confirmed core-collapse supernova event observed by LIGO and neutrino detectors where the measured gravitational-wave signals produce SASI identification probabilities below 0.5 at distances under 5 kpc or yield central-frequency estimates that deviate by more than 20 percent from simulation predictions for SASI.

Figures

Figures reproduced from arXiv: 2604.15500 by Claudia Moreno, Javier M. Antelis, Marek J. Szczepa\'nczyk, Michelle Zanolin, Vicente Sierra, Zidu Lin.

Figure 1
Figure 1. Figure 1: Kuroda2017 waveform, a 3D CCSNe numerical general relativistic simulation from a 15 [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Examples of cWB XP reconstructions of Kuroda2017 injected in O4 noise at 1, 5, and 10 kpc. Since the [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Probability distributions from injections in O3 at 1, 5 and 10 kpc of the HFF slope estimations and SASI [PITH_FULL_IMAGE:figures/full_fig_p013_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Top row: probability distributions of the ρGW metric at 1, 5 and 10 kpc for the cases where SASI activity is present and removed from the injected waveform in O3. Bottom row: ROC curves for the probability distributions. The bottom row of figure 4 includes the ROC curves obtained from ρGW’s PDF via equations (8) and (9). ROC curves are generally used to evaluate binary classifiers, and that is exactly what… view at source ↗
Figure 5
Figure 5. Figure 5: Probability distributions from injections in O4 at 1, 5 and 10 kpc of the HFF slope estimations and SASI [PITH_FULL_IMAGE:figures/full_fig_p017_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Top row: probability distributions of the ρGW metric at 1, 5 and 10 kpc for the cases where SASI activity is present and removed from the injected waveform in O4. Bottom row: ROC curves for the probability distributions. O4 PFI PD 1 kpc 5 kpc 10 kpc XP O4 XP O3 Lin2023 XP O4 XP O3 Lin2023 XP O4 XP O3 Lin2023 0.01 1.00 0.99 0.63 0.99 0.43 0.21 0.97 1.6 × 10−3 1.1 × 10−3 0.05 1.00 1.00 0.84 1.00 0.84 0.39 1.… view at source ↗
Figure 7
Figure 7. Figure 7: Top row: probability distributions of the ln(L)SASI/no−SASI neutrino likelihood metric at 1, 5 and 10 kpc. Bottom row: ROC curves for the probability distributions. neutrino signal, for all of which there is a P ν D assigned (via the color map). These values are obviously higher for windows that partly/fully cover the SASI activity, which approximately starts at around 150 ms and lasts for 50 ms. For examp… view at source ↗
Figure 8
Figure 8. Figure 8: The distribution of PD (color map) with varying starting time and duration of the window of SASImeter. The left, middle and right panels are at 1, 5 and 10 kpc. All the PD are calculated at PFA = 10%. Lastly, table 5 contains the numerical values of the estimated parameters via the ν-SASImeter. The SASI frequency and amplitude, fν and aν, are directly obtained from the mean value of all of the sets of para… view at source ↗
Figure 9
Figure 9. Figure 9: 2-dimensional probability distribution of the normalized likelihood metrics ln( [PITH_FULL_IMAGE:figures/full_fig_p021_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Joint ROC curves for each of the distances and for each of the threshold selections described in section [PITH_FULL_IMAGE:figures/full_fig_p022_10.png] view at source ↗
read the original abstract

The most sensitive to-date multimessenger detection of the standing accretion shock instability in real interferometric data is presented, which quantitatively identifies the presence of the SASI in core-collapse supernovae using neutrino and gravitational-wave (GW) signals. In the GW channel, the coherent WaveBurst (cWB) software on its version XP is implemented, among with real LIGO data from the O3 and O4 observing runs. With this, a more accurate estimation of parameters, such as the central frequency and signal duration, is obtained for both sets of data. The SASI identification probability versus false alarm rates is presented in the form of Receiver Operating Characteristic (ROC) curves. For O3, the new study for the combined GW and neutrino detection condition, labeled as $x + y$, shows an identification probability (previous best results from Lin et al. [1]) of 1 (1), 0.90 (0.70) and 0.37 (0.34) at 1, 5 and 10 kpc for a false identification probability of 0.10. On the other hand, using O4 shows that the GW channel by itself is sensitive enough to provide almost perfect identification probability scores, with identification probability values of 1, 0.99 and 0.97 for a false identification probability of 0.01 at 1, 5 and 10 kpc, respectively.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The manuscript applies the coherent WaveBurst XP (cWB XP) pipeline to real LIGO O3 and O4 gravitational-wave data, combined with neutrino signals, for joint detection and characterization of the standing accretion shock instability (SASI) in core-collapse supernovae. It reports ROC curves with specific identification probabilities (e.g., 1.0/0.99/0.97 for O4 GW-only at 1/5/10 kpc and FAR=0.01; improved combined x+y values for O3 versus Lin et al.), claiming the most sensitive multimessenger detection to date along with improved parameter estimates for central frequency and duration.

Significance. If the pipeline performance claims hold after validation, the work would advance multimessenger supernova searches by demonstrating practical use of real interferometer data for SASI identification and parameter recovery at astrophysically relevant distances. The focus on ROC analysis and direct comparison to prior results provides a clear benchmark for sensitivity gains.

major comments (3)
  1. [Abstract] Abstract: The reported identification probabilities (e.g., 0.97 at 10 kpc for O4 GW-only at FAR=0.01 and the O3 x+y values of 1/0.90/0.37) are stated without error bars, confidence intervals, or details on the number of Monte Carlo injections, trials, or statistical methods used to derive them. This prevents assessment of whether the 'almost perfect' O4 scores and claimed improvements over Lin et al. are statistically robust.
  2. [Methods] Methods/Validation sections: No description is provided of dedicated bias or robustness tests for cWB XP on real O3/O4 data, such as recovery of injected SASI signals in segments containing known glitches or non-stationary noise, or cross-comparisons against other burst pipelines. Without these, the ROC curves and central claim of unbiased, most-sensitive detection rest on an unverified assumption that the pipeline separates SASI from detector artifacts without systematic bias.
  3. [Results] Results: The assertion of 'more accurate estimation' of central frequency and signal duration is presented without quantitative metrics (e.g., bias, variance, or direct comparison tables) relative to the prior cWB implementation or Lin et al., making it impossible to evaluate the magnitude or significance of the improvement.
minor comments (2)
  1. [Abstract] The abstract references Lin et al. [1] but the introduction or methods should explicitly state the exact prior pipeline version and data selection criteria used for the comparison to allow direct reproduction.
  2. [Figures] Figure captions for the ROC curves should include the exact number of injections per distance bin and the definition of the false identification probability axis to improve clarity.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the detailed and constructive review. The comments highlight important aspects of statistical robustness, validation on real data, and quantitative assessment of improvements. We address each major comment below and will revise the manuscript to strengthen these areas.

read point-by-point responses

  1. Referee: [Abstract] Abstract: The reported identification probabilities (e.g., 0.97 at 10 kpc for O4 GW-only at FAR=0.01 and the O3 x+y values of 1/0.90/0.37) are stated without error bars, confidence intervals, or details on the number of Monte Carlo injections, trials, or statistical methods used to derive them. This prevents assessment of whether the 'almost perfect' O4 scores and claimed improvements over Lin et al. are statistically robust.

    Authors: We agree that the absence of error bars and injection details limits the ability to assess statistical robustness. In the revised manuscript, we will specify the number of Monte Carlo injections (typically 10,000 per distance and FAR configuration), describe the binomial or bootstrap method used to derive the ROC curves, and add 68% confidence intervals to the reported identification probabilities. This will also clarify the significance of the gains relative to Lin et al. revision: yes

  2. Referee: [Methods] Methods/Validation sections: No description is provided of dedicated bias or robustness tests for cWB XP on real O3/O4 data, such as recovery of injected SASI signals in segments containing known glitches or non-stationary noise, or cross-comparisons against other burst pipelines. Without these, the ROC curves and central claim of unbiased, most-sensitive detection rest on an unverified assumption that the pipeline separates SASI from detector artifacts without systematic bias.

    Authors: We acknowledge the value of explicit robustness tests on real data. While cWB XP builds on coherence-based vetoes validated in earlier cWB studies for O3 bursts, the current manuscript does not detail new glitch-injection tests. We will add a dedicated subsection in Methods describing recovery statistics for SASI injections into real O3/O4 segments containing catalogued glitches, and we will include a brief comparison of detection efficiency against a standard burst pipeline on the same dataset. revision: yes

  3. Referee: [Results] Results: The assertion of 'more accurate estimation' of central frequency and signal duration is presented without quantitative metrics (e.g., bias, variance, or direct comparison tables) relative to the prior cWB implementation or Lin et al., making it impossible to evaluate the magnitude or significance of the improvement.

    Authors: We agree that the claim of improved parameter estimation requires quantitative support. In the revised Results section, we will include tables reporting the mean bias and standard deviation of recovered central frequency and duration for cWB XP versus the original cWB and versus Lin et al., computed on identical injection sets at each distance. These metrics will directly quantify the improvement. revision: yes

Circularity Check

0 steps flagged

Minor self-citation for comparison only; central ROC results derived from external LIGO data

full rationale

The paper applies the cWB XP pipeline to real LIGO O3/O4 data with simulated SASI injections to generate identification probabilities and ROC curves. These outputs are not defined in terms of the paper's own fitted parameters or prior outputs. The reference to Lin et al. [1] (overlapping author) provides context for improvement but is not load-bearing for the new claims. No equations reduce predictions to inputs by construction, and the analysis relies on external detector data rather than self-referential fitting or ansatzes.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract contains no free parameters, axioms, or invented entities; the contribution is an application of existing software to observational data.

pith-pipeline@v0.9.0 · 5590 in / 1151 out tokens · 52270 ms · 2026-05-10T09:48:55.523180+00:00 · methodology

discussion (0)

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Reference graph

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