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When revisiting our fits in order to expand the above work, errors in the implementation of analytical expressions of the observables have been encountered. One of these errors affects the branching ratio of B → K + − at low q 2 in the presence of chirality-flipped operators. Carefully checking our results, we also found that systematic uncertainties of the lattice results of the B → K ( * ) form factors had been incorrectly neglected.After correcting these errors, we replace Tables 2 ("Postdiction" rows only), 3, 6, 4, and 5, as well as Figs. 2, 3, and 4. We also replace selected parts of Sect. 4 that are not given in the tables.While our main conclusions stay as they are, some details are adjusted. Our revised conclusions are given at the end of this erratum. Result Statistical approachFor the "selection" data set, we erroneously included the observables P i at high q 2 . Hence there are now N = 20 experimental inputs, two theory constraints, and dim ν = 24. (4.7)Our corrected result for the deviation in the (C 7 -C 9 ) from the SM expectation is 2.5σ , and solution A is favored over solution B with R A :R B = 82 %:18 %. Solution A is described by the 1D marginalized 68 % credibility regions For the data set "selection", the credibility regions in Fig. 2 are larger now as the observables P i at high q 2 are no longer part of it. Fit in the extended SM+SM basisWe now find that, of all four solutions, A and D dominate over B and C in terms of the posterior mass: R A :R B :R C :R D = 37 %:14 %:15 %:34 %. 123

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We present GALARIO, a computational library that exploits the power of modern graphical processing units (GPUs) to accelerate the analysis of observations from radio interferometers like ALMA or the VLA. GALARIO speeds up the computation of synthetic visibilities from a generic 2D model image or a radial brightness profile (for axisymmetric sources). On a GPU, GALARIO is 150 faster than standard Python and 10 times faster than serial C++ code on a CPU. Highly modular, easy to use and to adopt in existing code, GALARIO comes as two compiled libraries, one for Nvidia GPUs and one for multicore CPUs, where both have the same functions with identical interfaces. GALARIO comes with Python bindings but can also be directly used in C or C++. The versatility and the speed of GALARIO open new analysis pathways that otherwise would be prohibitively time consuming, e.g. fitting high resolution observations of large number of objects, or entire spectral cubes of molecular gas emission. It is a general tool that can be applied to any field that uses radio interferometer observations. The source code is available online at http://github.com/mtazzari/galario under the open source GNU Lesser General Public License v3.Comparing a model image computed on a regular grid to observed visibilities that are scattered across the Fourier plane involves a series of 1D and 2D array operations such as Fourier transforms, transpositions, and interpolations . The size of the arrays used to properly model the visibilities are set by the prop-