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Acoustic compressional and shear wave velocities (VP, VS) of anhydrous (AHRG) and hydrous rhyolitic glasses (HRG) containing 3.28 wt% (HRG-3) and 5.90 wt% (HRG-6) total water concentra- tion (H2Ot) have been measured using Brillouin light scattering (BLS) spectroscopy up to 3 GPa in a diamond-anvil cell at ambient temperature. In addition, Fourier-transform infrared (FTIR) spectroscopy was used to measure the speciation of H2O in the glasses up to 3 GPa. At ambient pressure, HRG-3 contains 1.58 (6) wt% hydroxyl groups (OH–) and 1.70 (7) wt% molecular water (H2Om) while HRG-6 contains 1.67 (10) wt% OH– and 4.23 (17) wt% H2Om where the numbers in parentheses are ±1σ. With increasing pressure, very little H2Om, if any, converts to OH– within uncertainties in hydrous rhyolitic glasses such that HRG-6 contains much more H2Om than HRG-3 at all experimental pressures. We observe a nonlinear relationship between high-pressure sound velocities and H2Ot, which is attributed to the distinct effects of each water species on acoustic velocities and elastic moduli of hydrous glasses. Near ambient pressure, depolymerization due to OH– reduces VS and G more than VP and KS. VP and KS in both anhydrous and hydrous glasses decrease with increasing pressure up to ~1–2 GPa before increasing with pressure. Above ~1–2 GPa, VP and KS in both hydrous glasses converge with those in AHRG. In particular, VP in HRG-6 crosses over and becomes higher than VP in AHRG. HRG-6 displays lower VS and G than HRG-3 near ambient pressure, but VS and G in these glasses converge above ~2 GPa. Our results show that hydrous rhyolitic glasses with ~2–4 wt% H2Om can be as incompressible as their anhydrous counterpart above ~1.5 GPa. The nonlinear effects of hydration on high-pressure acoustic velocities and elastic moduli of rhyolitic glasses observed here may provide some insight into the behavior of hydrous silicate melts in felsic magma chambers at depth. 

Following rapid decompression in the conduit of a volcano, magma breaks into ash- to block-sized fragments, powering explosive sub-Plinian and Plinian eruptions that may generate destructive pyroclastic falls and flows. It is thus crucial to assess how magma breaks up into fragments. This task is difficult, however, because of the subterranean nature of the entire process and because the original size of pristine fragments is modified by secondary fragmentation and expansion. New textural observations of sub-Plinian and Plinian pumice lapilli reveal that some primary products of magma fragmentation survive by sintering together within seconds of magma break-up. Their size distributions reflect the energetics of fragmentation, consistent with products of rapid decompression experiments. Pumice aggregates thus offer a unique window into the previously inaccessible primary fragmentation process and could be used to determine the potential energy of fragmentation. 

Silicic volcanic activity has long been framed as either violently explosive or gently effusive. However, recent ob- servations demonstrate that explosive and effusive behavior can occur simultaneously. Here, we propose that rhyolitic magma feeding subaerial eruptions generally fragments during ascent through the upper crust and that effusive eruptions result from conduit blockage and sintering of the pyroclastic products of deeper cryptic frag- mentation. Our proposal is supported by (i) rhyolitic lavas are volatile depleted; (ii) textural evidence supports a pyroclastic origin for effusive products; (iii) numerical models show that small ash particles !10−5 m can diffusive- ly degas, stick, and sinter to low porosity, in the time available between fragmentation and the surface; and (iv) inferred ascent rates from both explosive and apparently effusive eruptions can overlap. Our model reconciles previously paradoxical observations and offers a new framework in which to evaluate physical, numerical, and geochemical models of Earth’s most violent volcanic eruptions. 

The di!usion of water through silicate melts is a key process in volcanic systems. Di!usion controls the growth of the bub- bles that drive volcanic eruptions and determines the evolution of the spatial distribution of dissolved water during and after magma mingling, crystal growth, fracturing and fragmentation, and welding of pyroclasts. Accurate models for water di!u- sion are therefore essential for forward modelling of eruptive behaviour, and for inverse modelling to reconstruct eruptive and post-eruptive history from the spatial distribution of water in eruptive products. Existing models do not include the kinetics of the homogeneous species reaction that interconverts molecular (H2Om) and hydroxyl (OH) water; reaction kinetics are impor- tant because final species distribution depends on cooling history. Here we develop a flexible 1D numerical model for di!usion and speciation of water in silicate melts. We validate the model against FTIR transects of the spatial distribution of molecular, hydroxyl, and total water across di!usion-couple experiments of haplogranite composition, run at 800–1200 C and 5 kbar. We adopt a stepwise approach to analysing and modelling the data. First, we use the analytical Sauer-Freise method to deter- mine the e!ective di!usivity of total water DH2Ot as a function of dissolved water concentration CH2Ot and temperature T for each experiment and find that the dependence of DH2 Ot on CH2 Ot is linear for CH2 Ot K 1:8 wt.% and exponential for CH2 Ot J 1:8 wt.%. Second, we develop a 1D numerical forward model, using the method of lines, to determine a piece-wise function for DH2 Ot !CH2 Ot ; T " that is globally-minimized against the entire experimental dataset. Third, we extend this numerical model to account for speciation of water and determine globally-minimized functions for di!usivity of molecular water DH2 Om !CH2 Ot ; T " and the equilibrium constant K for the speciation reaction. Our approach includes three key novelties: (1) functions for dif- fusivities of H2Ot and H2Om, and the speciation reaction, are minimized simultaneously against a large experimental dataset, covering a wide range of water concentration (0:25 CH2 Ot 7 wt.%) and temperature (800  C T 1200  C), such that the resulting functions are both mutually-consistent and broadly applicable; (2) the minimization allows rigorous and robust analysis of uncertainties such that the accuracy of the functions is quantified; (3) the model can be straightforwardly used to determine functions for di!usivity and speciation for other melt compositions pending suitable di!usion-couple experiments. The modelling approach is suitable for both forward and inverse modelling of di!usion processes in silicate melts; the model is available as a MATLAB script from the electronic supplementary material. 

One of the most compelling features of Gaussian process (GP) regression is its ability to provide well-calibrated posterior distributions. Recent advances in inducing point methods have sped up GP marginal likelihood and posterior mean computations, leaving posterior covariance estimation and sampling as the remaining computational bottlenecks. In this paper we address these shortcomings by using the Lanczos algorithm to rapidly approximate the predictive covariance matrix. Our approach, which we refer to as LOVE (LanczOs Variance Estimates), substantially improves time and space complexity. In our experiments, LOVE computes covariances up to 2,000 times faster and draws samples 18,000 times faster than existing methods, all without sacrificing accuracy. 

Abstract The Gravitational-Wave Transient Catalog (GWTC) is a collection of short-duration (transient) gravitational-wave signals identified by the LIGO–Virgo–KAGRA Collaboration in gravitational-wave data produced by the eponymous detectors. The catalog provides information about the identified candidates, such as the arrival time and amplitude of the signal and properties of the signal’s source as inferred from the observational data. GWTC is the data release of this dataset, and version 4.0 extends the catalog to include observations made during the first part of the fourth LIGO–Virgo–KAGRA observing run up until 2024 January 31. This Letter marks an introduction to a collection of articles related to this version of the catalog, GWTC-4.0. The collection of articles accompanying the catalog provides documentation of the methods used to analyze the data, summaries of the catalog of events, observational measurements drawn from the population, and detailed discussions of selected candidates. 

Recent work shows that inference for Gaussian processes can be performed efficiently using iterative methods that rely only on matrix-vector multiplications (MVMs). Structured Kernel Interpolation (SKI) exploits these techniques by deriving approximate kernels with very fast MVMs. Unfortunately, such strategies suffer badly from the curse of dimensionality. We develop a new technique for MVM based learning that exploits product kernel structure. We demonstrate that this technique is broadly applicable, resulting in linear rather than exponential runtime with dimension for SKI, as well as state-of-the-art asymptotic complexity for multi-task GPs. 

Abstract We report the observation of gravitational waves from two binary black hole coalescences during the fourth observing run of the LIGO–Virgo–KAGRA detector network, GW241011 and GW241110. The sources of these two signals are characterized by rapid and precisely measured primary spins, nonnegligible spin–orbit misalignment, and unequal mass ratios between their constituent black holes. These properties are characteristic of binaries in which the more massive object was itself formed from a previous binary black hole merger and suggest that the sources of GW241011 and GW241110 may have formed in dense stellar environments in which repeated mergers can take place. As the third-loudest gravitational-wave event published to date, with a median network signal-to-noise ratio of 36.0, GW241011 furthermore yields stringent constraints on the Kerr nature of black holes, the multipolar structure of gravitational-wave generation, and the existence of ultralight bosons within the mass range 10⁻¹³–10⁻¹²eV. 

Abstract On 2023 November 23, the two LIGO observatories both detected GW231123, a gravitational-wave signal consistent with the merger of two black holes with masses $137_{-18}^{+23}{M}_{\odot }$and $101_{-50}^{+22}{M}_{\odot }$(90% credible intervals), at a luminosity distance of 0.7–4.1 Gpc, a redshift of $0.40_{-0.25}^{+0.27}$, and with a network signal-to-noise ratio of ∼20.7. Both black holes exhibit high spins— $0.90_{-0.19}^{+0.10}$and $0.80_{-0.52}^{+0.20}$, respectively. A massive black hole remnant is supported by an independent ringdown analysis. Some properties of GW231123 are subject to large systematic uncertainties, as indicated by differences in the inferred parameters between signal models. The primary black hole lies within or above the theorized mass gap where black holes between 60–130M_⊙should be rare, due to pair-instability mechanisms, while the secondary spans the gap. The observation of GW231123 therefore suggests the formation of black holes from channels beyond standard stellar collapse and that intermediate-mass black holes of mass ∼200M_⊙form through gravitational-wave-driven mergers.