Shear Calibration for Next-Generation Weak Lensing Surveys Using CMB Lensing
The paper addresses the critical challenge of shear calibration in next-generation weak lensing surveys, specifically focusing on LSST (Legacy Survey of Space and Time), Euclid, and WFIRST. These surveys aim to probe the growth of cosmic structures and the geometry of the Universe, thereby offering insights into dark energy, modifications to general relativity, and the sum of neutrino masses. A significant hurdle for these surveys is the control of systematic errors, among which shear calibration biases pose a substantial challenge.
The authors propose a methodology for calibrating shear biases using CMB (Cosmic Microwave Background) lensing from a stage 4 CMB experiment, labeled as "CMB S4". This is achieved through a joint analysis involving all two-point functions of galaxy density, galaxy shear, and CMB lensing convergence. The paper utilizes the CosmoLike code to simulate such an analysis, incorporating full Gaussian and non-Gaussian covariances and leveraging Monte Carlo Markov Chains to explore the resultant joint likelihoods.
Key numerical findings demonstrate that CMB lensing from CMB S4 can calibrate shear biases to a precision ranging between 0.2% and 3% across 10 tomographic bins for LSST, achieving better than the required ~0.5% accuracy in most bins. Similar calibrations are noted for Euclid and WFIRST, with precisions of 0.4%-2.4% and 0.6%-3.2%, respectively. The method, although most effective at high redshift where shear calibration is traditionally challenging, remains robust under Gaussian photometric redshift uncertainties and intrinsic galaxy alignments. Additionally, it shows resilience to variations in the beam and the component separation efficacy of the CMB experiment, as well as moderate dependence on its depth, indicating its feasibility with third-generation CMB experiments like AdvACT, SPT-3G, and the Simons Observatory.
The paper's analysis revisits the requirements for shear calibration in the context of LSST, showing that self-calibration based solely on LSST data can significantly reduce the dependence on external priors. A detailed exploration is presented, quantifying how specific priors on shear biases affect cosmological parameter constraints and demonstrating the powerful self-calibration capability of LSST when shear, galaxy-galaxy lensing, and clustering data are combined.
Moreover, through an examination of shear self-calibration using CMB S4 lensing, the paper offers insights into the dependency of shear bias constraints on various survey parameters, intrinsic alignments, and photometric redshift uncertainties. This thorough analysis shows that even when these potential systematic issues are considered, the methodology outlined still achieves shear bias constraints within acceptable margins, thus providing a robust measure of redundancy and cross-verification for major cosmic surveys.
The implications of this work are profound, offering a method not solely reliant on image simulations for shear calibration, but one that robustly utilizes data from diverse background sources, embedding an intrinsic system of cross-validation among major astronomical surveys. The adaptability and robustness of the presented method suggest that as CMB experiments and wide-field surveys evolve, their integrated analysis could provide an unprecedented precision in cosmological parameter estimation.
Moving forward, the practical integration of this calibration method into upcoming survey frameworks could significantly enhance the reliability of cosmic shear measurements, paving the way for more accurate and comprehensive cosmological models. This paper therefore underscores the importance of interdisciplinary synergy in the ambit of cosmological surveys and lays groundwork for future enhancements to shear calibration techniques in large-scale structure studies.