arXiv subjects

Fabio Hernandez

Publications and source records attributed to Fabio Hernandez.

9 recordsLinked to original sources

arXiv2025

Data Movement Model for the Vera C. Rubin Observatory

The sky images captured nightly by the camera on the Vera C. Rubin Observatory's telescope will be processed across facilities on three continents. Data acquisition will occur at the observatory's location on Cerro Pach\'{o}n in the Andes mountains of Chile. A first copy of the raw image data set is stored at the summit and immediately transmitted via dedicated network links to the archive center within the US Data Facility at SLAC National Accelerator Laboratory in California, USA and from there to two European facilities for processing and archiving purposes. Data products resulting from periodic processing campaigns of the entire set of images collected since the beginning of the survey are made available to the scientific community in the form of data releases. In this paper we present an overall view of how we leverage the tools selected for managing the movement of data among the Rubin processing and serving facilities, including Rucio and FTS. We also present the tools we developed to integrate Rucio's data model and Rubin's Data Butler, the software abstraction layer that mediates all access to storage by pipeline tasks that implement science algorithms.

astro-ph.IM↗

arXiv2024

The Rubin Observatory's Legacy Survey of Space and Time DP0.2 processing campaign at CC-IN2P3

The Vera C. Rubin Observatory, currently in construction in Chile, will start performing the Legacy Survey of Space and Time (LSST) in 2025 for 10 years. Its 8.4-meter telescope will survey the southern sky in less than 4 nights in six optical bands, and repeatedly generate about 2 000 exposures per night, corresponding to a data volume of about 20 TiB every night. Three data facilities are preparing to contribute to the production of the annual data releases: the US Data Facility will process 35% of the raw data, the UK data facility will process 25% of the raw data and the French data facility, operated by CC-IN2P3, will locally process the remaining 40% of the raw data. In the context of the Data Preview 0.2 (DP0.2), the Data Release Production pipelines have been executed on the DC-2 simulated dataset (generated by the Dark Energy Science Collaboration, DESC). This dataset includes 20 000 simulated exposures, representing 300 square degrees of Rubin images with a typical depth of 5 years. DP0.2 ran at the Interim Data Facility (based on Google cloud), and the full exercise was independently replicated at CC-IN2P3. During this exercise, 3 PiB of data and more than 200 million files were produced. In this contribution we will present a detailed description of the system that we set up to perform this processing campaign using CC-IN2P3's computing and storage infrastructure. Several topics will be addressed: workflow generation and execution, batch job submission, memory and I/O requirements, etc. We will focus on the issues that arose during this campaign and how we addressed them and will present some perspectives after this exercise.

astro-ph.IM↗

arXiv2024

Experience deploying an analysis facility for the Rubin Observatory's Legacy Survey of Space and Time (LSST) data

The Vera C. Rubin Observatory is preparing for the execution of the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently in its final phase of construction in the Andes mountains in Chile and due to start operations in 2025 for 10 years, its 8.4-meter telescope will nightly scan the southern sky and collect images of the entire visible sky every 4 nights using a 3.2 Gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this paper, we briefly present the infrastructure deployed at the French Rubin data facility (operated by IN2P3 computing center, CC-IN2P3) to deploy the Rubin Science Platform, a set of web-based services to provide effective and convenient access to LSST data for scientific analysis. We describe the main services of the platform, the components that provide those services and our deployment model. We also present the Kubernetes-based infrastructure we are experimenting with for hosting the LSST astronomical catalog, a petabyte-scale relational database developed for the specific needs of the project.

astro-ph.IM↗

arXiv2023

Overview of the distributed image processing infrastructure to produce the Legacy Survey of Space and Time

The Vera C. Rubin Observatory is preparing to execute the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently the final phase of construction is under way in the Chilean Andes, with the Observatory's ten-year science mission scheduled to begin in 2025. Rubin's 8.4-meter telescope will nightly scan the southern hemisphere collecting imagery in the wavelength range 320-1050 nm covering the entire observable sky every 4 nights using a 3.2 gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this article we present an overview of the system currently being constructed to perform data distribution as well as the annual campaigns which reprocess the entire image dataset collected since the beginning of the survey. These processing campaigns will utilize computing and storage resources provided by three Rubin data facilities (one in the US and two in Europe). Each year a Data Release will be produced and disseminated to science collaborations for use in studies comprising four main science pillars: probing dark matter and dark energy, taking inventory of solar system objects, exploring the transient optical sky and mapping the Milky Way. Also presented is the method by which we leverage some of the common tools and best practices used for management of large-scale distributed data processing projects in the high energy physics and astronomy communities. We also demonstrate how these tools and practices are utilized within the Rubin project in order to overcome the specific challenges faced by the Observatory.

astro-ph.IM↗

arXiv2021

The LSST DESC DC2 Simulated Sky Survey

We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin's LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep (WFD) area of approximately 300 deg^2 as well as a deep drilling field (DDF) of approximately 1 deg^2. We simulate 5 years of the planned 10-year survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the dataset to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic testbed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time-domain cosmology.

astro-ph.IM↗

arXiv2021

DESC DC2 Data Release Note

In preparation for cosmological analyses of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), the LSST Dark Energy Science Collaboration (LSST DESC) has created a 300 deg$^2$ simulated survey as part of an effort called Data Challenge 2 (DC2). The DC2 simulated sky survey, in six optical bands with observations following a reference LSST observing cadence, was processed with the LSST Science Pipelines (19.0.0). In this Note, we describe the public data release of the resulting object catalogs for the coadded images of five years of simulated observations along with associated truth catalogs. We include a brief description of the major features of the available data sets. To enable convenient access to the data products, we have developed a web portal connected to Globus data services. We describe how to access the data and provide example Jupyter Notebooks in Python to aid first interactions with the data. We welcome feedback and questions about the data release via a GitHub repository.

astro-ph.CO↗

arXiv2020

Fink, a new generation of broker for the LSST community

Fink is a broker designed to enable science with large time-domain alert streams such as the one from the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). It exhibits traditional astronomy broker features such as automatised ingestion, annotation, selection and redistribution of promising alerts for transient science. It is also designed to go beyond traditional broker features by providing real-time transient classification which is continuously improved by using state-of-the-art Deep Learning and Adaptive Learning techniques. These evolving added values will enable more accurate scientific output from LSST photometric data for diverse science cases while also leading to a higher incidence of new discoveries which shall accompany the evolution of the survey. In this paper we introduce Fink, its science motivation, architecture and current status including first science verification cases using the Zwicky Transient Facility alert stream.

astro-ph.IM↗

arXiv2015

The LSST Data Management System

The Large Synoptic Survey Telescope (LSST) is a large-aperture, wide-field, ground-based survey system that will image the sky in six optical bands from 320 to 1050 nm, uniformly covering approximately $18,000$deg$^2$ of the sky over 800 times. The LSST is currently under construction on Cerro Pachón in Chile, and expected to enter operations in 2022. Once operational, the LSST will explore a wide range of astrophysical questions, from discovering "killer" asteroids to examining the nature of Dark Energy. The LSST will generate on average 15 TB of data per night, and will require a comprehensive Data Management system to reduce the raw data to scientifically useful catalogs and images with minimum human intervention. These reductions will result in a real-time alert stream, and eleven data releases over the 10-year duration of LSST operations. To enable this processing, the LSST project is developing a new, general-purpose, high-performance, scalable, well documented, open source data processing software stack for O/IR surveys. Prototypes of this stack are already capable of processing data from existing cameras (e.g., SDSS, DECam, MegaCam), and form the basis of the Hyper-Suprime Cam (HSC) Survey data reduction pipeline.

astro-ph.IM↗

arXiv2012

Status Report of the DPHEP Study Group: Towards a Global Effort for Sustainable Data Preservation in High Energy Physics

Data from high-energy physics (HEP) experiments are collected with significant financial and human effort and are mostly unique. An inter-experimental study group on HEP data preservation and long-term analysis was convened as a panel of the International Committee for Future Accelerators (ICFA). The group was formed by large collider-based experiments and investigated the technical and organisational aspects of HEP data preservation. An intermediate report was released in November 2009 addressing the general issues of data preservation in HEP. This paper includes and extends the intermediate report. It provides an analysis of the research case for data preservation and a detailed description of the various projects at experiment, laboratory and international levels. In addition, the paper provides a concrete proposal for an international organisation in charge of the data management and policies in high-energy physics.

hep-ex↗