# Posts Tagged lsst

## Recent Postings from lsst

### Porting the LSST Data Management Pipeline Software to Python 3

The LSST data management science pipelines software consists of more than 100,000 lines of Python 2 code. LSST operations will begin after support for Python 2 has been dropped by the Python community in 2020, and we must therefore plan to migrate the codebase to Python 3. During the transition period we must also support our community of active Python 2 users and this complicates the porting significantly. We have decided to use the Python future package as the basis for our port to enable support for Python 2 and Python 3 simultaneously, whilst developing with a mindset more suited to Python 3. In this paper we report on the current status of the port and the difficulties that have been encountered.

### Maximizing Science in the Era of LSST: A Community-Based Study of Needed US Capabilities

The Large Synoptic Survey Telescope (LSST) will be a discovery machine for the astronomy and physics communities, revealing astrophysical phenomena from the Solar System to the outer reaches of the observable Universe. While many discoveries will be made using LSST data alone, taking full scientific advantage of LSST will require ground-based optical-infrared (OIR) supporting capabilities, e.g., observing time on telescopes, instrumentation, computing resources, and other infrastructure. This community-based study identifies, from a science-driven perspective, capabilities that are needed to maximize LSST science. Expanding on the initial steps taken in the 2015 OIR System Report, the study takes a detailed, quantitative look at the capabilities needed to accomplish six representative LSST-enabled science programs that connect closely with scientific priorities from the 2010 decadal surveys. The study prioritizes the resources needed to accomplish the science programs and highlights ways that existing, planned, and future resources could be positioned to accomplish the science goals.

### New views of the distant stellar halo

Currently only a small number of Milky Way (MW) stars are known to exist beyond 100 kpc from the Galactic center. Though the distribution of these stars in the outer halo is believed to be sparse, they can provide evidence of more recent accretion events than in the inner halo and help map out the MW's dark matter halo to its virial radius. We have re-examined the outermost regions of 11 existing stellar halo models with two synthetic surveys: one mimicking present-day searches for distant M giants and another mimicking RR Lyrae (RRLe) projections for LSST. Our models suggest that color and proper motion cuts currently used to select M giant candidates for follow-up successfully remove nearly all halo dwarf self-contamination and are useful for focusing observations on distant M giants, of which there are thousands to tens of thousands beyond 100 kpc in our models. We likewise expect that LSST will identify comparable numbers of RRLe at these distances. We demonstrate that several observable properties of both tracers, such as proximity of neighboring stars, proper motions, and distances (for RRLe) could help us separate different accreted structures from one another. We also discuss prospects for using ratios of M giants to RRLe as a proxy for accretion time, which in the future could provide new constraints on the recent accretion history of our Galaxy.

### Looking through the same lens: shear calibration for LSST, Euclid & WFIRST with stage 4 CMB lensing

The next generation weak lensing surveys (i.e., LSST, Euclid and WFIRST) will require exquisite control over systematic effects. In this paper, we address shear calibration and present the most realistic forecast to date for LSST/Euclid/WFIRST and CMB lensing from a stage 4 CMB experiment (CMB S4). We use the CosmoLike code to simulate a joint analysis of all the two-point functions of galaxy density, galaxy shear and CMB lensing convergence. We include the full Gaussian and non-Gaussian covariances and explore the resulting joint likelihood with Monte Carlo Markov Chains. We constrain shear calibration biases while simultaneously varying cosmological parameters, galaxy biases and photometric redshift uncertainties. We find that CMB lensing from CMB S4 enables the calibration of the shear biases down to 0.2% - 3% in 10 tomographic bins for LSST (below the ~0.5% requirements in most tomographic bins), down to 0.4% - 2.4% in 10 bins for Euclid and 0.6% - 3.2% in 10 bins for WFIRST. For a given lensing survey, the method works best at high redshift where shear calibration is otherwise most challenging. This self-calibration is robust to Gaussian photometric redshift uncertainties and to a reasonable level of intrinsic alignment. It is also robust to changes in the beam and the effectiveness of the component separation of the CMB experiment, and slowly dependent on its depth, making it possible with third generation CMB experiments such as AdvACT and SPT-3G, as well as the Simons Observatory.

### Testing LSST Dither Strategies for Survey Uniformity and Large-Scale Structure Systematics

The Large Synoptic Survey Telescope (LSST) will survey the southern sky from 2022-2032 with unprecedented detail. Given that survey observational strategy can lead to artifacts in the observed data, we investigate the effects of telescope-pointing offsets (called dithers) on the $r$-band coadded 5$\sigma$ depth yielded after the 10-year survey. We analyze this survey depth for several geometric patterns of dithers (e.g., random, hexagonal lattice, spiral) with amplitude as large as the radius of the LSST field-of-view, implemented on different timescales (per season, per night, per visit). Our results illustrate that per night and per visit dither assignments are more effective than per season. Also, we find that some dither geometries (e.g. hexagonal lattice) are particularly sensitive to the timescale on which the dithers are implemented, while others like random dithers perform well on all timescales. We then model the propagation of depth variations to artificial fluctuations in galaxy counts, which are a systematic for large-scale structure studies. We calculate the bias in galaxy counts induced due to the observing strategy, accounting for photometric calibration uncertainties, dust extinction, and magnitude cuts; uncertainties in this bias limit our ability to account for structure induced by the survey strategy. We find that after 10 years of the LSST survey, the best observing strategies lead to uncertainties in the bias smaller than the minimum statistical floor for a galaxy catalog as deep as $r$$<27.5; of these, a few bring the uncertainties close to the floor for r$$<$25.7 after only one year of survey.

### Cosmic Visions Dark Energy: Science

Cosmic surveys provide crucial information about high energy physics including strong evidence for dark energy, dark matter, and inflation. Ongoing and upcoming surveys will start to identify the underlying physics of these new phenomena, including tight constraints on the equation of state of dark energy, the viability of modified gravity, the existence of extra light species, the masses of the neutrinos, and the potential of the field that drove inflation. Even after the Stage IV experiments, DESI and LSST, complete their surveys, there will still be much information left in the sky. This additional information will enable us to understand the physics underlying the dark universe at an even deeper level and, in case Stage IV surveys find hints for physics beyond the current Standard Model of Cosmology, to revolutionize our current view of the universe. There are many ideas for how best to supplement and aid DESI and LSST in order to access some of this remaining information and how surveys beyond Stage IV can fully exploit this regime. These ideas flow to potential projects that could start construction in the 2020's.

### Optical selection of quasars: SDSS and LSST

Over the last decade, quasar sample sizes have increased from several thousand to several hundred thousand, thanks mostly to SDSS imaging and spectroscopic surveys. LSST, the next-generation optical imaging survey, will provide hundreds of detections per object for a sample of more than ten million quasars with redshifts of up to about seven. We briefly review optical quasar selection techniques, with emphasis on methods based on colors, variability properties and astrometric behavior.

### Cosmic shear without shape noise

We describe a new method for reducing the shape noise in weak lensing measurements by an order of magnitude. Our method relies on spectroscopic measurements of disk galaxy rotation and makes use of the Tully-Fisher (TF) relation in order to control for the intrinsic orientations of galaxy disks. For this new proposed experiment, the shape noise ceases to be an important source of statistical error. Using CosmoLike, a new cosmological analysis software package, we simulate likelihood analyses for two spectroscopic weak lensing survey concepts (roughly similar in scale to Dark Energy Survey Task Force Stage III and Stage IV missions) and compare their constraining power to a cosmic shear survey from the Large Synoptic Survey Telescope (LSST). Our forecasts in seven-dimensional cosmological parameter space include statistical uncertainties resulting from shape noise, cosmic variance, halo sample variance, and higher-order moments of the density field. We marginalize over systematic uncertainties arising from photometric redshift errors and shear calibration biases considering both optimistic and conservative assumptions about LSST systematic errors. We find that even the TF-Stage III is highly competitive with the optimistic LSST scenario, while evading the most important sources of theoretical and observational systematic error inherent in traditional weak lensing techniques. Furthermore, the TF technique enables a narrow-bin cosmic shear tomography approach to tightly constrain time-dependent signatures in the dark energy phenomenon.

### Strong Lens Time Delay Challenge: I. Experimental Design

The time delays between point-like images in gravitational lens systems can be used to measure cosmological parameters as well as probe the dark matter (sub-)structure within the lens galaxy. The number of lenses with measured time delays is growing rapidly as a result of some dedicated efforts; the upcoming Large Synoptic Survey Telescope (LSST) will monitor ~1000 lens systems consisting of a foreground elliptical galaxy producing multiple images of a background quasar. In an effort to assess the present capabilities of the community to accurately measure the time delays in strong gravitational lens systems, and to provide input to dedicated monitoring campaigns and future LSST cosmology feasibility studies, we invite the community to take part in a "Time Delay Challenge" (TDC). The challenge is organized as a set of "ladders", each containing a group of simulated datasets to be analyzed blindly by participating independent analysis teams. Each rung on a ladder consists of a set of realistic mock observed lensed quasar light curves, with the rungs' datasets increasing in complexity and realism to incorporate a variety of anticipated physical and experimental effects. The initial challenge described here has two ladders, TDC0 and TDC1. TDC0 has a small number of datasets, and is designed to be used as a practice set by the participating teams as they set up their analysis pipelines. The (non-mandatory) deadline for completion of TDC0 will be the TDC1 launch date, December 1, 2013. TDC1 will consist of some 1000 light curves, a sample designed to provide the statistical power to make meaningful statements about the sub-percent accuracy that will be required to provide competitive Dark Energy constraints in the LSST era.