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Analysis of cosmic shear is an integral part of understanding structure growth across cosmic time, which in-turn provides us with information about the nature of dark energy. Conventional methods generate \emph{shear maps} from which we can infer the matter distribution in the universe. Current methods (e.g., Kaiser-Squires inversion) for generating these maps, however, are tricky to implement and can introduce bias. Recent alternatives construct a spatial process prior for the lensing potential, which allows for inference of the convergence and shear parameters given lensing shear measurements. Realizing these spatial processes, however, scales cubically in the number of observations - an unacceptable expense as near-term surveys expect billions of correlated measurements. Therefore, we present a linearly-scaling shear map construction alternative using a scalable Gaussian Process (GP) prior called MuyGPs. MuyGPs avoids cubic scaling by conditioning interpolation on only nearest-neighbors and fits hyperparameters using batched leave-one-out cross validation. We use a suite of ray-tracing results from N-body simulations to demonstrate that our method can accurately interpolate shear maps, as well as recover the two-point and higher order correlations. We also show that we can perform these operations at the scale of billions of galaxies on high performance computing platforms., Comment: 12 Pages, 5 Figures

Upcoming wide field surveys will have many overlapping epochs of the same region of sky. The conventional wisdom is that in order to reduce the errors sufficiently for systematics-limited measurements, like weak lensing, we must do simultaneous fitting of all the epochs. Using current algorithms this will require a significant amount of computing time and effort. In this paper, we revisit the potential of using coadds for shear measurements. We show on a set of image simulations that the multiplicative shear bias can be constrained below the 0.1% level on coadds, which is sufficient for future lensing surveys. We see no significant differences between simultaneous fitting and coadded approaches for two independent shear codes: Metacalibration and BFD. One caveat of our approach is the assumption of a principled coadd, i.e. the PSF is mathematically well-defined for all the input images. This requires us to reject CCD images that do not fully cover the coadd region. We estimate that the number of epochs that must be rejected for a survey like LSST is on the order of 20%, resulting in a small loss in depth of less than 0.1 magnitudes. We also put forward a cell-based coaddition scheme that meets the above requirements for unbiased weak lensing shear estimation in the context of LSST.

We demonstrate a sapphire machining process integrated with intermediate-scale quantum processors. The process allows through-substrate electrical connections, necessary for low-frequency mode-mitigation, as well as signal-routing, which are vital as quantum computers scale in qubit number, and thus dimension. High-coherence qubits are required to build fault-tolerant quantum computers and so material choices are an important consideration when developing a qubit technology platform. Sapphire, as a low-loss dielectric substrate, has shown to support high-coherence qubits. In addition, recent advances in material choices such as tantalum and titanium-nitride, both deposited on a sapphire substrate, have demonstrated qubit lifetimes exceeding 0.3 ms. However, the lack of any process equivalent of deep-silicon etching to create through-substrate-vias in sapphire, or to inductively shunt large dies, has limited sapphire to small-scale processors, or necessitates the use of chiplet architecture. Here, we present a sapphire machining process that is compatible with high-coherence qubits. This technique immediately provides a means to scale QPUs with integrated mode-mitigation, and provides a route toward the development of through-sapphire-vias, both of which allow the advantages of sapphire to be leveraged as well as facilitating the use of sapphire-compatible materials for large-scale QPUs., Comment: 9 pages, 6 figures

Superconducting qubits are a promising route to achieving large-scale quantum computers. A key challenge in realising large-scale superconducting quantum processors involves mitigating frequency collisions. In this paper, we present an approach to tuning fixed-frequency qubits with the use of an electron beam to locally anneal the Josephson junction. We demonstrate the ability to both increase and decrease the junction barrier resistance. The technique shows an improvement in wafer scale frequency targetting by assessing the frequency collisions in our qubit architecture. Coherence measurements are also done to evaluate the performance before and after tuning. The tuning process utilises a standard electron beam lithography system, ensuring reproducibility and implementation by any group capable of fabricating these Josephson junctions. This technique has the potential to significantly improve the performance of large-scale quantum computing systems, thereby paving the way for the future of quantum computing., Comment: 12 pages, 8 figures