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Abstract The Tonga‐Kermadec subduction zone exhibits the fastest observed trench retreat and convergence near its northern end. However, a paradox exists: despite the rapid trench retreat, the Tonga slab maintains a relatively steep dip angle above 400 km depth. The slab turns flat around 400 km, then steepening again until encountering a stagnant segment near 670 km. Despite its significance for understanding slab dynamics, no existing numerical model has successfully demonstrated how such a distinct slab morphology can be generated under the fast convergence. Here we run subduction models that successfully reproduce the slab geometries while incorporating the observed subduction rate. We use a hybrid velocity boundary condition, imposing velocities on the arc and subducting plate while allowing the overriding plate to respond freely. This approach is crucial for achieving a good match between the modeled and observed Tonga slab. The results explain how the detailed slab structure is highly sensitive to physical parameters including the seafloor age and the mantle viscosity. Notably, a nonlinear rheology, where dislocation creep reduces upper mantle viscosity under strong mantle flow, is essential. The weakened upper mantle allows for a faster slab sinking rate, which explains the large dip angle. Our findings highlight the utilizing rheological parameters that lead to extreme viscosity variations within numerical models to achieve an accurate representation of complex subduction systems like the Tonga‐Kermadec zone. Our study opens new avenues for further study of ocean‐ocean subduction systems, advancing our understanding of their role in shaping regional and global tectonics. 

Abstract The formation of Lau Basin records an extreme event of plate tectonics, with the associated Tonga trench exhibiting the fastest retreat in the world (16 cm/yr). Yet paleogeographic reconstructions suggest that seafloor spreading in the Lau Basin only initiated around 6 Ma. This kinematics is difficult to reconcile with our present understanding of how subduction drives plate motions. Using numerical models, we propose that eastward migration of the Lau Ridge concurrent with trench retreat explains both the narrow width and thickened crust of the Lau Basin. To match the slab geometry and basin width along the Tonga‐Kermadec trench, our models suggest that fast trench retreat rate of 16 cm/yr might start ~15 Ma. Tonga slab rollback induced vigorous mantle flow underneath the South Fiji Basin which is driving the extension and thinning of the basin and contributing to its observed deeper bathymetry compared to neighboring basins. 

It is important to understand the cycle of baryons through the circumgalactic medium (CGM) in the context of galaxy formation and evolution. In this study, we forecast constraints on the feedback processes heating the CGM with current and future Sunyaev–Zeldovich (SZ) observations. To constrain these processes, we use a suite of cosmological simulations, the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS). CAMELS varies four different feedback parameters of two previously existing hydrodynamical simulations, IllustrisTNG and SIMBA. We capture the dependences of SZ radial profiles on these feedback parameters with an emulator, calculate their derivatives, and forecast future constraints on these feedback parameters from upcoming experiments. We find that for a galaxy sample similar to what would be obtained with the Dark Energy Spectroscopic Instrument at the Simons Observatory, all four feedback parameters can be constrained (some within the 10% level), indicating that future observations will be able to further restrict the parameter space for these subgrid models. Given the modeled galaxy sample and forecasted errors in this work, we find that the inner SZ profiles contribute more to the constraining power than the outer profiles. Finally, we find that, despite the wide range of parameter variation in active galactic feedback in the CAMELS simulation suite, we cannot reproduce the thermal SZ signal of galaxies selected by the Baryon Oscillation Spectroscopic Survey as measured by the Atacama Cosmology Telescope. 

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives. 

ABSTRACT Low-luminosity Type II supernovae (LL SNe II) make up the low explosion energy end of core-collapse SNe, but their study and physical understanding remain limited. We present SN 2016aqf, an LL SN II with extensive spectral and photometric coverage. We measure a V-band peak magnitude of −14.58 mag, a plateau duration of ∼100 d, and an inferred 56Ni mass of 0.008 ± 0.002 M⊙. The peak bolometric luminosity, Lbol ≈ 1041.4 erg s−1, and its spectral evolution are typical of other SNe in the class. Using our late-time spectra, we measure the [O i] λλ6300, 6364 lines, which we compare against SN II spectral synthesis models to constrain the progenitor zero-age main-sequence mass. We find this to be 12 ± 3 M⊙. Our extensive late-time spectral coverage of the [Fe ii] λ7155 and [Ni ii] λ7378 lines permits a measurement of the Ni/Fe abundance ratio, a parameter sensitive to the inner progenitor structure and explosion mechanism dynamics. We measure a constant abundance ratio evolution of $$0.081^{+0.009}_{-0.010}$$ and argue that the best epochs to measure the ratio are at ∼200–300 d after explosion. We place this measurement in the context of a large sample of SNe II and compare against various physical, light-curve, and spectral parameters, in search of trends that might allow indirect ways of constraining this ratio. We do not find correlations predicted by theoretical models; however, this may be the result of the exact choice of parameters and explosion mechanism in the models, the simplicity of them, and/or primordial contamination in the measured abundance ratio.