Experimental Challenges in Probing Dark Energy with the Large Synoptic Survey Telescope

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The standard models of particle physics and cosmology are incomplete. The particle content does not contain a viable candidate for the dark matter in the Universe and there is no well-motivated explanation of the nature of dark energy. The fields of particle physics and cosmology are inextricably intertwined. Accelerator-based experiments, detectors in deep underground mines, and telescopes in space and on the ground are all needed and used to explore fundamental questions such as the nature of dark matter. Gravitational lensing is a cosmological probe that has the advantage of being sensitive to all matter in the Universe: baryonic and dark matter. The growth of dark matter structure is a sensitive probe of the physics of dark energy. With this award, the Stanford group will play a leadership role in a high-priority effort in observational cosmology through the proposed Large Synoptic Survey Telescope (LSST) and the LSST Dark Energy Science Collaboration. The LSST is the first ground-based telescope being designed from scratch to address the severe demands on systematic uncertainties needed to fully exploit weak gravitational lensing as a cosmological probe. The LSST will also address cosmological questions through studies of the growth of large scale structure, baryon acoustic oscillations and Type Ia supernovae. The group will study the experimental challenges to achieving the maximum sensitivity to dark energy through several observational probes, with a focus on gravitational lensing. This effort will be based on analytical and computational techniques, and on detailed simulations of the LSST system. They will contribute to the development of high fidelity simulations and, where appropriate, use existing imaging data to develop and test the understanding of systematic effects that will impact LSST. The work with LSST simulations and astronomical data provides opportunities for students and postdocs to gain skills in statistics, data analysis, and handling large data sets that are in high demand in the private and public sectors. The PI brings her strong targeted efforts in education and advising, aimed at increasing and diversifying the cohort of students who pursue degrees in physics and engineering, and broadening career paths for physicists.