(P1.060) Enzo Services via NESSSI
Richard Wagner (University of California, San Diego)
Michael Norman (University of California, San Diego)
Roy Williams (California Institute Of Technology, CACR)
We will describe the design of the Enzo Data Analysis Services, which allow users to perform predefined analysis operations on data generated by the AMR cosmology code Enzo. These services are a continuation of our work in building the LCA Theory SkyNode, which contains a catalog of simulated galaxy clusters from the Simulated Cluster Archive (SCA). The design of the Data Analysis Services is intended to mimic the object identification and analysis paradigm used for observational data as much as possible. Using the SkyNode, users can identify clusters by properties such as mass, redshift, or virial radius, and retrieve the corresponding object IDs. The object IDs are in turn passed to the analysis service, which handles the data. This way, users are only aware of the object IDs, analysis parameters, and results, and are not required to download software or deal with the simulation data.
The Enzo Data Analysis Services have been deployed using the NVO Extensible, Scalable, Secure Service Infrastructure (NESSSI) and are accessible using a scriptable Python client, or a simple web form. Two services are will be available: a projection tool; and a radial profiler. These services are stepping stones to future services, and, it is hoped, will serve as models for other providers of theory data.