Opening a Window of Discovery on the Dynamic Universe

Understanding Data and Simulations

Welcome to the possibilities of LSST’s data and simulation. 

Explore how LSST’s data will be structured, 
how to model LSST from sky to detector with the simulation framework, 
and find out how you can access and process LSST data and simulations.

What will LSST data look like?

LSST will deliver calibrated images and data products on a daily and annual basis. The project will also host some related data products generated by the community.

Prompt data products:
  • Source catalogs from difference imaging (available 24 hours after acquisition)
  • Images (available 24 hours after acquisition)
  • Within 60 seconds of readout: alerts about sources that changed relative to a reference image, including moving objects
Data releases (yearly):
  • a global and uniform processing of all the data taken from the start of the survey until a given date (typically 6 months before the release).
  • calibrated images
  • source catalogs with positions, flux, shapes, etc…
  • light curves

Read more about the planned data products.

Modelling LSST from sky to detector: the simulation framework

Highly sophisticated and open-source tools exist for you to simulate everything from how LSST could make its observations over time, how light passes through the telescope system and spreads out on the detector, and what alerts and catalogues of astronomical sources will be created.

Catalogs
Images
Survey Strategy

CatSim: the catalog simulator simulates the properties and distributions of stars, galaxies, and asteroids that LSST expects to observe.

ImSim: is an open source software package used to drive simulations of the LSST telescope and survey.  imSim is used both for small scale studies in the Dark Energy Science Collaboration and LSST, and also for large scale data challenges.

OpSim: the operations simulator generates sequences of LSST observations based on one or more science programs and the historical weather, accounting  for the expected performance of the telescope and site.

 

PhoSim: the photon simulator generates representative images of the sky as LSST would observe it by raytracing photons through an atmosphere, telescope, and camera.

MAF: the metrics analysis framework is an application used to analyse the outputs of the Operations Simulator to evaluate the science and technical performance of the LSST survey strategy


Read more about the LSST simulation ecosystem.

How can I access and process LSST data and simulations?

Data

The whole LSST data (raw and calibrated images, yearly data releases) will be archived in its entirety in two facilities on different continents: NCSA in the US and CC-IN2P3 in France. Users with data rights will access the survey releases and data products through tools provided by the Project, from a Data Access Center (DAC). Currently planned DACs are at NCSA, at CC-IN2P3, and in Chile; additional DACs are under consideration in other participating countries.

Database queries for catalogs

Many users will only desire the output catalogues provided in each data release.

DACs will provide access via QServ, which allows efficient querying of the petabyte-size catalogs.
http://slac.stanford.edu/exp/lsst/qserv/ 
https://ieeexplore.ieee.org/document/6114487/

Accessing raw or calibrated images

The recommended way to access images is with LSST’s applications layer of the data processing software, which is entirely open-source. It has two components for users, together called the “DM stack”: a pipeline for data reduction, and tools for interacting with calibrated images and catalogues.  It has two components for users, together called the “DM stack”: a pipeline for data reduction, and tools for interacting with calibrated images and catalogues. More information on DM stack

As part of the data releases, the reduction pipeline will be run by LSST Project to create the data products, and users will only have to run it if they need more specific raw data processing. You can use the pipeline to process simulated images or observed images (e.g. from Subaru HSC) into catalogues: see the tutorial.

For interacting with calibrated data, the DM stack tools provide a Python-interface environment for further processing of data products and visualising data: [link to tutorial for interacting with released data products, to be created].

Working group specific tools

Among the science collaborations [link], many working groups are developing software tailored to their specific needs. For example, see the Solar System collaboration for discussion of LSST’s moving-object detections, or the Core Cosmology Library developed by DESC. More information on Science Collaborations

Simulations

The LSST Project regularly simulates LSST strategies through OpSim. The OpSim products are all available for download (as sql databases).

The DESC SC generates “mock universes” for the purpose of creating and testing LSST pipelines. The software used to generate these simulations is generally public on the DESC github repository.

Financial support for LSST comes from the National Science Foundation (NSF) through Cooperative Agreement No. 1258333, the Department of Energy (DOE) Office of Science under Contract No. DE-AC02-76SF00515, and private funding raised by the LSST Corporation. The NSF-funded LSST Project Office for construction was established as an operating center under management of the Association of Universities for Research in Astronomy (AURA).  The DOE-funded effort to build the LSST camera is managed by the SLAC National Accelerator Laboratory (SLAC).
The National Science Foundation (NSF) is an independent federal agency created by Congress in 1950 to promote the progress of science. NSF supports basic research and people to create knowledge that transforms the future.
NSF and DOE will continue to support LSST in its Operations phase. They will also provide support for scientific research with LSST data.   




Contact   |   We are Hiring   |   Business with LSST

Admin Login

Back to Top