In the era of large astronomical surveys that are grappling with unsolved methodological and data challenges, transforming Data into Science is a huge, and exciting, problem. With surveys and instruments such as Planck, Pan-STARRS1, DES, VST KiDS, LSST, Gaia, EUCLID, JPAS, SKA, wide-field spectroscopic surveys and the large and interconnected databases of archival material coming online, a special scientific focus on cosmological inference is of great interest. Without this focus there is no guarantee that the best possible Science will be the outcome of this data-flood. But transforming data into knowledge is still a largely unsolved problem; a problem, that must be tackled by cross-disciplinary efforts.
The scientific promise of weak gravitational lensing (WL) has inspired a number of very ambitious observational programs starting in 2012/2013 (KIDS, Pan-STARRS, HSC, DES), and several more to begin in about a decade from now (LSST, Euclid). These surveys will cover an order of magnitude more sky area than most existing ones (thousands of square degrees of sky rather than hundreds), and due to the greater statistical power, better control of systematic errors is also required. The WL community therefore must learn as much as possible from existing data in order to focus its efforts for the next generation surveys, both to reduce the main sources of systematic error and to develop more sophisticated ways of handling outstanding theoretical issues.
In the past few years, there has been extensive development in WL theory, observations, and numerical simulations. The field of WL now reaches such a maturity and level of complexity that future surveys will benefit considerably from tighter connections between the different areas. We envision a workshop that will establish strong and durable connection between observers who focused on the previous generation of lensing surveys, those working on the next generation, and theorists. The ultimate goal is to guide the efforts of those working on the next generation surveys, which will include thorough discussion of ways to minimize and characterize systematic errors (through hardware, software, and careful survey design) that plagued previous surveys, and development of theoretical techniques to get the most information from the data while minimizing sensitivity to any residual systematics. Among the observational systematics under discussion will be robust measurement of galaxy shapes under realistic imaging conditions; and estimation of photometric redshifts (line-of-sight distances to galaxies using broad-band photometry) to get redshift estimates for all galaxies, and the use of spectroscopic surveys for calibration purposes. Another equally important aspect is data reduction of very large data sets and data mining, more specifically what future surveys can learn from computer science techniques and high energy physics to deal with the ever increasing data flow. Among the theoretical topics of discussion are intrinsic alignments of galaxy shapes (due to, e.g. local tidal fields – which can mimic a lensing signal); optimal ways to distinguish between dark energy and modifications of the theory of gravity; and minimization of theoretical uncertainties in the observables, e.g. due to the (currently) poorly known effects of baryons (luminous matter). Regarding numerical simulations, the topics of discussion will include the important question of small-scale modeling of the dark matter power spectrum and its sensitivity to baryonic physics such as AGN, supernovae winds and other feedback mechanisms. The workshop will allow a significant amount of time for informal discussions and the development of new research collaborations.
Click here to link to the workshop’s website.