We present a novel AI approach for high-resolution high-dynamic range synthesis imaging by radio interferometry (RI) in astronomy. R2D2, standing for ``{R}esidual-to-{R}esidual {D}NN series for high-{D}ynamic range imaging'', is a model-based data-driven approach relying on hybrid deep neural networks (DNNs) and data-consistency updates. Its reconstruction is built as a series of residual images estimated as the outputs of DNNs, each taking the residual dirty image of the previous iteration as an input. The approach can be interpreted as a learned version of a matching pursuit approach, whereby model components are iteratively identified from residual dirty images, and of which CLEAN is a well-known example. We propose two variants of the R2D2 model, built upon two distinctive DNN architectures: a standard U-Net, and a novel unrolled architecture. We demonstrate their use for monochromatic intensity imaging on highly-sensitive observations of the radio galaxy Cygnus A at S band, from the Very Large Array (VLA). R2D2 is validated against CLEAN and the recent RI algorithms AIRI and uSARA, which respectively inject a learned implicit regularization and an advanced handcrafted sparsity-based regularization into the RI data. With only few terms in its series, the R2D2 model is able to deliver high-precision imaging, superseding the resolution of CLEAN, and matching the precision of AIRI and uSARA. In terms of computational efficiency, R2D2 runs at a fraction of the cost of AIRI and uSARA, and is also faster than CLEAN, opening the door to near real-time precision imaging in RI.

The Earth's core is growing lopsided, scientists have discovered, but it is unclear why. The solid-iron core in the middle of the planet has been growing faster under Indonesia's Banda Sea, seismologists at the University of California in Berkeley found. The growth on one side of the molten metal is the product of iron crystals that form as the molten iron cools, but something in the Earth's outer core or mantle under the south Asian country is removing heat at a faster rate than on the opposite side, under Brazil. The faster the cooling, the faster that iron crystallisation occurs – and the faster the growth increases. Such a disparity has significant implications for the Earth's magnetic field, and the convection currents in the core that generate the field are what protects us from dangerous solar particles.