The global network of gravitational-wave observatories now includes five detectors, namely LIGO Hanford, LIGO Livingston, Virgo, KAGRA, and GEO 600. These detectors collected data during their third observing run, O3, composed of three phases: O3a starting in 2019 April and lasting six months, O3b starting in 2019 November and lasting five months, and O3GK starting in 2020 April and lasting two weeks. In this paper we describe these data and various other science products that can be freely accessed through the Gravitational Wave Open Science Center at https://gwosc.org. The main data set, consisting of the gravitational-wave strain time series that contains the astrophysical signals, is released together with supporting data useful for their analysis and documentation, tutorials, as well as analysis software packages.

We use 47 gravitational wave sources from the Third LIGO–Virgo–Kamioka Gravitational Wave Detector Gravitational Wave Transient Catalog (GWTC–3) to estimate the Hubble parameter H(z), including its current value, the Hubble constant H ₀. Each gravitational wave (GW) signal provides the luminosity distance to the source, and we estimate the corresponding redshift using two methods: the redshifted masses and a galaxy catalog. Using the binary black hole (BBH) redshifted masses, we simultaneously infer the source mass distribution and H(z). The source mass distribution displays a peak around 34 M _⊙, followed by a drop-off. Assuming this mass scale does not evolve with the redshift results in a H(z) measurement, yielding H 0 = 68 − 8 + 12 km s − 1 Mpc − 1 (68% credible interval) when combined with the H ₀ measurement from GW170817 and its electromagnetic counterpart. This represents an improvement of 17% with respect to the H ₀ estimate from GWTC–1. The second method associates each GW event with its probable host galaxy in the catalog GLADE+, statistically marginalizing over the redshifts of each event’s potential hosts. Assuming a fixed BBH population, we estimate a value of H 0 = 68 − 6 + 8 km s − 1 Mpc − 1 with the galaxy catalog method, an improvement of 42% with respect to our GWTC–1 result and 20% with respect to recent H ₀ studies using GWTC–2 events. However, we show that this result is strongly impacted by assumptions about the BBH source mass distribution; the only event which is not strongly impacted by such assumptions (and is thus informative about H ₀) is the well-localized event GW190814.

Summary: 1. In this study we used species accumulation models to solve one of the most serious problems encountered when comparing species richness between different communities. The problem is how to compare data among inventories in which different methodologies or measures of sampling effort have been employed. The methods used here for bats may be applied to any other biological group. We fit two asymptotic models to species accumulation curves for bat inventories to evaluate local or within‐community diversity (alpha) and landscape diversity (gamma) in central Veracruz, Mexico. 2. Species accumulation models allow us to: (i) measure within‐inventory efficacy and completeness; (ii) obtain an estimate of species richness that is based on a standardized measure of sampling effort, which makes valid comparisons between inventories possible; and (iii) estimate the minimum sampling effort required to reach a satisfactory level of completeness. 3. The applied models fit well in all cases (r² > 0·95). The linear dependence model predicted lower asymptotes and the Clench model predicted higher asymptotes than the observed species richness. These models are useful as predictors representing the lower and upper limits between which the true species richness value should lie. 4. Alpha diversity for bats in all vegetation communities (11–18 species) was lower than the gamma diversity (20 species), suggesting that species richness and the sampling effort required are related to environmental heterogeneity. 5. We propose that 90% of the total fauna predicted by either of the models is an acceptable standardized value for comparing species richness between communities. 6. We assessed the within‐inventory completeness as the proportion of the models’ asymptote, where 90% is the desired minimum level of completeness. Except in palm stands, all bat inventories had an acceptable level of completeness, at least for the linear dependence model. 7. For conditions similar to those of our study area, the minimum effort required to obtain a satisfactory level of completeness is 5–18 nights for plant communities and 18 nights for more heterogeneous landscapes. 8. We make recommendations for improving the efficacy and completeness of bat surveys based on the application of species accumulation models.

The gravitational-wave signal GW250114 was observed by the two LIGO detectors with a network matched-filter signal-to-noise ratio of 80. The signal was emitted by the coalescence of two black holes with near-equal masses m 1 = 33.6 − 0.8 + 1.2 M ⊙ and m 2 = 32.2 − 1.3 + 0.8 M ⊙ , and small spins χ 1 , 2 ≤ 0.26 (90% credibility) and negligible eccentricity e ≤ 0.03 . Postmerger data excluding the peak region are consistent with the dominant quadrupolar ( ℓ = | m | = 2 ) mode of a Kerr black hole and its first overtone. We constrain the modes’ frequencies to ± 30 % of the Kerr spectrum, providing a test of the remnant’s Kerr nature. We also examine Hawking’s area law, also known as the second law of black hole mechanics, which states that the total area of the black hole event horizons cannot decrease with time. A range of analyses that exclude up to five of the strongest merger cycles confirm that the remnant area is larger than the sum of the initial areas to high credibility.