GWTC-4 Gravitational-Wave Event Catalog

• GWTC-4 is a comprehensive gravitational-wave event catalog detailing 218 compact binary coalescence candidates, including new events from the O4a run.
• It employs advanced matched-filter searches and Bayesian parameter estimation with multiple waveform models to accurately infer source properties.
• The catalog supports precision cosmological inference with spectral and dark siren methods, enhancing population studies and tests of gravity.

The Gravitational-Wave Transient Catalog, version 4.0 (GWTC-4), is a comprehensive compilation of short-duration gravitational-wave signals identified by the LIGO–Virgo–KAGRA (LVK) Collaboration. GWTC-4 represents a major expansion and refinement over previous editions by incorporating data from the first part of the fourth observing run (O4a), spanning 2023 May 24 through 2024 January 16, and includes advanced analyses of compact binary coalescences such as binary black holes (BBHs), neutron star–black hole (NSBH) systems, and binary neutron stars (BNSs). This version also supports robust population studies, cosmological inference via “spectral siren” and “dark siren” methods, and tests of modified gravitational-wave propagation.

1. Catalog Content and Scope

GWTC-4.0 contains strain data and associated metadata from the advanced LIGO, Virgo, and KAGRA detectors, covering the O4a run and preceding engineering time. The catalog features:

• 218 compact binary coalescence candidates not vetoed for instrumental or environmental reasons and having a probability of astrophysical origin $p_{\rm astro} \geq 0.5$ (Collaboration et al., 25 Aug 2025).
• Among these, 128 new candidates are added from O4a, with 86 passing a false alarm rate (FAR) threshold of $< 1\,\mathrm{yr}^{-1}$ for full Bayesian parameter estimation.
• Event types include BBH mergers, NSBH systems (notably GW230518_125908 and GW230529_181500 where neutron star origin is likely from $m < 3\,M_\odot$), and some candidates in the putative lower mass gap ($3$–$5\,M_\odot$).

Notable events include GW230814_061920 (network $\mathrm{SNR} \approx 42$), and GW231123_135430, inferred to represent the most massive BBH observed to date, with $M_{\rm tot} \approx 236^{+29}_{-48}\,M_\odot$.

2. Methodologies of Detection and Characterization

Candidate identification and characterization in GWTC-4.0 employ an array of signal modeling and search pipelines (Collaboration et al., 25 Aug 2025):

• Signal Modeling: Utilizes inspiral–merger–ringdown (IMR) waveform families, with IMRPhenom, SEOBNR, and NRSur models. Gravitational-wave strain $h(t; \theta)$ is expressed as a function of intrinsic and extrinsic parameters, incorporating antenna response.
• Matched-filter Searches: Pipelines such as PyCBC, GstLAL, and cWB cross-correlate data with template banks:

$$\rho^2 = \frac{\langle d | h(\theta) \rangle^2}{\langle h(\theta)|h(\theta)\rangle}$$

where

$$\langle a | b \rangle = 4\,{\rm Re} \int_0^\infty \frac{\tilde a(f) \tilde b^*(f)}{S_n(f)} df$$

• Unmodeled Burst Search: cWB targets short-duration excess power, relying on time–frequency coherent analysis.
• Data Quality: Rigorous vetoing of non-astrophysical transients, employing auxiliary channel flags and statistical consistency tests ($\chi^2$).
• Bayesian Parameter Estimation: Source parameters $\theta$ are inferred using nested sampling and MCMC methods under likelihood

$$\mathcal{L}(d|\theta) \propto \exp\left[-\frac{1}{2} \sum_{\rm det} \int \frac{|\tilde d(f) - \tilde h(f;\theta)|^2}{S_n(f)} df\right]$$

and

$p(\theta|d) \propto \mathcal{L}(d|\theta)p(\theta)$

Consistent measurement of key source parameters—chirp mass $(\mathcal{M}_c)$, mass ratio $(q)$, effective inspiral spin $(\chi_{\rm eff})$, luminosity distance $(D_L)$—is facilitated by cross-validation across pipelines and waveform families.

3. Catalog Expansion and Astrophysical Trends

The inclusion of O4a candidates provides a substantial increase in sample size and diversity, enabling precision population and formation channel studies:

• Mass spectrum: BBH component masses now span $5.79\,M_\odot$ to $137\,M_\odot$ (for GW231123_135430), with population features at $10\,M_\odot$, $20\,M_\odot$, and $35\,M_\odot$ (Collaboration et al., 25 Aug 2025).
• Spin Distribution: 90% of BBHs have $\chi < 0.57$, and spins are preferentially aligned with the orbital plane, indicating formation through isolated binary evolution. However, 24–42% of binaries show negative $\chi_{\rm eff}$, consistent with dynamical assembly in gas-free environments.
• Mass Ratio: Peak near $q=0.74^{+0.13}_{-0.13}$ for $m_1 \sim 10\,M_\odot$ BBHs. The dominant population mode favors nearly equal-mass systems, with a break mass $m_\text{break} \approx 36\,M_\odot$ and broken-power-law index $\alpha_1 \approx 1.7$, $\alpha_2 \approx 4.6$.

Multimodal posteriors can arise, especially at high-mass or high-spin, due to noise artifacts, modeling differences, or incomplete signal content (Collaboration et al., 25 Aug 2025). Glitch mitigation employs Bayesian modeling (BAYESWAVE) and frequency cutoffs.

4. Population Inference and Hierarchical Bayesian Analyses

Population properties are extracted via hierarchical Bayesian methodologies (Collaboration et al., 25 Aug 2025, Hernandez et al., 3 Sep 2025, Collaboration et al., 4 Sep 2025):

• Parameterized Mass and Spin Models: The BBH primary mass function is fit by broken-power-law with distinct “modes” corresponding to different formation scenarios. The probability distribution may be summarized as

$$P(m_1) \propto \begin{cases} m_1^{- \alpha_1}, & m_\text{min} \leq m_1 < m_\text{break} \ m_1^{- \alpha_2}, & m_\text{break} \leq m_1 \leq m_\text{max} \end{cases}$$

with $m_\text{break} \approx 36\,M_\odot$, $\alpha_1 \approx 1.7$, $\alpha_2 \approx 4.6$.

• Merger Rates: Median inferred BBH merger rates are $\sim$16 Gpc$^{-3}$ yr$^{-1}$ (with spread of $+6/-5$).
• Spin–Mass Ratio Correlations: Evidence for correlation between $\chi_\text{eff}$ and $q$ is reported, though the mode vs. width contributions are not conclusively disentangled.

Two distinct population modes suggest formation via isolated binaries (aligned spins, equal masses) and dynamical channels (misaligned, negative spins).

5. Cosmological Inference: Standard, Spectral, and Dark Sirens

GWTC-4 candidates support cosmological inference—including measurement of the Hubble constant ($H_0$) and tests of gravitational-wave propagation—without direct electromagnetic (EM) counterparts (Hernandez et al., 3 Sep 2025, Collaboration et al., 4 Sep 2025):

• Spectral Siren Cosmology: Leverages features in the BBH mass spectrum (e.g., peaks at $10\,M_\odot$, $35\,M_\odot$, a shoulder at $45\,M_\odot$) to statistically infer source redshifts. The transformation $m_{1,2}^{\rm det} = m_{1,2} (1+z)$, with $z$ estimated via features in $p(m_{1,2}|z, \Lambda_c)$, breaks the mass–redshift degeneracy.
• Bayesian Hierarchical Inference: Joint posterior over population and cosmological parameters is constructed; e.g.,

$$p(\Lambda_p, \Lambda_c| \{d_i\}) \propto \prod_{i=1}^{N_\text{det}} p(d_i | \Lambda_p, \Lambda_c)$$

• Models for Mass Distribution: Powerlaw + Peak, Broken Powerlaw + 2 Peaks (parametric), and flexibly data-driven non-parametric Gaussian process approaches; the latter achieves the tightest constraints.
• Hubble Constant Estimates:
  • Gaussian process model yields $H_0=69^{+7}_{-6}$ km s$^{-1}$ Mpc$^{-1}$ (10% fractional uncertainty) when combined with GW170817 EM counterpart (Hernandez et al., 3 Sep 2025).
  • FullPop model applied to the GWTC-4 sample reports $H_0=76.6^{+13.0}_{-9.5}$ km s$^{-1}$ Mpc$^{-1}$ (68% interval), consistent with other GW-inferred and EM-based constraints (Collaboration et al., 4 Sep 2025).
• Dark Siren Method: Involves host galaxy catalog (GLADE+) based photometric redshift priors, extracting additional redshift information for BBH candidates.
• Modified Propagation and Gravity Tests: Quantified through the magnitude parameter $\Xi_0$:

$$D_L^{\rm GW} = D_L^{\rm EM}\left[\Xi_0 + \frac{1 - \Xi_0}{(1+z)^n}\right]$$

with derived constraint $\Xi_0 = 1.2^{+0.8}_{-0.4}$ (68% credible interval), consistent with general relativity.

6. Data Products, Systematics, and Future Prospects

GWTC-4 provides comprehensive data products via GWOSC, including strain data, posterior distributions, search sensitivities, and glitch subtraction models (Collaboration et al., 25 Aug 2025). Advanced systematics studies compare multiple waveform families and investigate multimodal posteriors, with differences in parameter inference across models highlighted for extreme-mass and spin events.

Sensitivity studies benchmark the time–volume (VT) product, and sky localization accuracy is variable due to network configuration—two-detector operation yields hundreds of square degrees uncertainty for some events.

Future O4 and projected O5 runs will further extend the candidate sample, likely improving cosmological parameter constraints, enabling stricter tests of gravitational-wave propagation, and allowing refined population models via deeper and more complete galaxy catalogs. Additional bright siren events (EM counterparts) would add further calibration for cosmological inference.

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In total, GWTC-4.0 establishes an expanded, rigorously analyzed gravitational-wave event catalog, underpinning both fundamental astrophysical measurements and complementary cosmological studies. Its integration of advanced signal processing, hierarchical Bayesian population modeling, and emerging cosmological methodology serves as a state-of-the-art reference for gravitational-wave physics.