LSST CD-1 Review SLAC, Menlo Park, CA November 1 - 3, 2011 Analysis Overview Bhuv Jain and Jeff Newman

Planning the dark energy analysis for LSST: guiding principles Identify a set of systematics that could dominate the error budget for dark energy unless advances are made by the LSST team. –Two categories: 1. systematics that will need to be controlled significantly better than for Stage III surveys, 2. those that Stage III surveys have not addressed at all. –Develop a science risk reduction plan focused on likely sources of error: LSST camera/telescope, photometric and photo-z calibration, observing strategy, astrophysical uncertainties, and analysis algorithms themselves. Identify simulation and computational needs (ImSim and cosmological) to include relevant physics, test measurement algorithms and develop methodology for controlling systematics. Stage III surveys aim to make order of magnitude advances on the techniques LSST will use. So develop a plan of work that is synergistic and of interactions with precursor surveys that are mutually beneficial.

Planning the dark energy analysis for LSST: The Starting Point To develop the high-level analysis plan and to identify the key systematics it is useful to schematically break down the dark energy analysis into the following steps. –Observing field/band/seeing selection and cadence issues –The reduction of raw images –The production of catalogs from the processed images –Measurement of statistical quantities such as power spectra –Cosmological analysis leading to dark energy constraints. Note that the first three steps relate to Level 1 and 2 software, so the role of a dark energy collaboration is to be figured out in consultation with the project. Two critical elements linked to the above steps:

Planning the dark energy analysis for LSST: Stage III surveys and global simulation resources –Stage III surveys: what do we expect to learn in the next 5 years? What outcomes of our work would interest these projects? How do we handle the proprietary (initial) aspects of these collaborations? What aspects of their data will be useful to us for testing analysis schemes? What is our access to the data? –Spectroscopic surveys: what are the needs for calibration of LSST photo-z’s? –EUCLID: what are the synergies with LSST? –CMB and other cosmological probes: what are the expected (direct and indirect) connections to dark energy in the LSST era? –GREAT lensing challenges and other such simulation efforts: how should the LSST DESC interact with them?

Dark Energy Planning Example: Analysis Steps for WL Weak Lensing pipeline: raw images to shear catalog Object detection (threshold systematic, forced photometry, seeing subsamples) Star-Galaxy Separation, Deblending PSF measurement: Analytic model based or pixel based PSF correction: StackFit, MultiFit, or both? PSF interpolation: PCA algorithm Shear measurement: Key challenge: shape estimation (Bayesian, neural net..). Key advantage: large number of exposures in several useful bands, dithered and rotated.

Dark Energy Planning Example: Analysis Steps for WL Lensing statistics Estimators and software for measurements of ~10 distinct lensing statistics. Starting with 2-point correlations, compare different estimators with regard to E/B mode separation and sensitivity to systematics. Error bars/covariances: non-Gaussian (off-diagonal) terms; covariances between different statistics and with LSS/Clusters. Tomography and cross-correlations: galaxy-shear, magnification and CMB lensing (all measure the galaxy-mass cross power). Cluster mass function: scope out in connection with Cluster group. Cosmological analysis and parameter estimation Emulators: interpolation scheme to provide predictions desired parameter value Develop a complete set of "nuisance parameters” Methods to marginalize over the nuisance parameters Incorporate WL magnification Parameterization of modified gravity and unconventional dark energy models

How should we generate a task list? In the first phase of work, we are not aiming to be comprehensive. A carefully chosen set of ~10 tasks across all science areas will need to be chosen. Criteria: A task should be critical to the success of the program and need to be tackled several years before first light We should be equipped to make progress on it Simulations with relevant physics should be available Synergistic connections to precursor surveys are a plus The work involved should be “interesting”! At this meeting, we will follow a mixed approach: high level + bottom up: develop “example” tasks in some detail, and flesh out connections between science analysis and computing/simulation/software.

Example Tasks: Weak Lensing Investigate deblending: also impacts LSS and Strong Lensing –Use ImSim to characterize distribution of nearby objects as function of m in realistic LSST run. –Use GalSim to systematically test shear measurement errors as fn of separation/mag for a simple algorithm like aperture clipping. –Try more sophisticated deblending algorithms? –Characterize how sharply would need to throw out blends to keep systematics under control –What does this do to Neff?

Example Tasks: Large Scale Structure

Example Tasks: Galaxy Clusters and Theory Mass calibration and cluster finding: – Identify required multi-wavelength mass proxies and strategy for acquiring them. – Determine key mass-observable scaling relations from current data (informing overall strategy and priors/nuisance parameters for modeling). – Determine optimal strategies for finding clusters with LSST alone and in combination with external data (e.g. X-ray, SZ). Cosmological parameter degeneracy breaking –Cross correlation of spectropscopic survey peculiar velocity spectra, CMB ISW and lensing with LSST WL and LSS. –CMB lensing as complementary probe of P(k) –X-ray and SZ cluster survey scaling relations

Connections to Computation, Simulation & Software Next up!