arXiv subjects

Fabrice Jammes

Publications and source records attributed to Fabrice Jammes.

4 recordsLinked to original sources

arXiv2025

Enabling Early Transient Discovery in LSST via Difference Imaging with DECam

We present SLIDE, a pipeline that enables transient discovery in data from the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST), using archival images from the Dark Energy Camera (DECam) as templates for difference imaging. We apply this pipeline to the recently released Data Preview 1 (DP1; the first public release of Rubin commissioning data) and search for transients in the resulting difference images. The image subtraction, photometry extraction, and transient detection are all performed on the Rubin Science Platform. We demonstrate that SLIDE effectively extracts clean photometry by circumventing poor or missing LSST templates. We identified 29 previously unreported transients, 12 of which would not have been detected based on the DP1 DiaObject catalog. SLIDE will be especially useful for transient analysis in the early years of LSST, when template coverage will be largely incomplete or when templates may be contaminated by transients present at the time of acquisition. We present multiband light curves for a sample of known transients, along with new transient candidates identified through our search. Finally, we discuss the prospects of applying this pipeline during the main LSST survey. Our pipeline is broadly applicable and will support studies of all transients with slowly evolving phases.

astro-ph.HE↗

arXiv2025

Variability-finding in Rubin Data Preview 1 with LSDB

The Vera C. Rubin Observatory recently released Data Preview 1 (DP1) in advance of the upcoming Legacy Survey of Space and Time (LSST), which will enable boundless discoveries in time-domain astronomy over the next ten years. DP1 provides an ideal sandbox for validating innovative data analysis approaches for the LSST mission, whose scale challenges established software infrastructure paradigms. This note presents a pair of such pipelines for variability-finding using powerful software infrastructure suited to LSST data, namely the HATS (Hierarchical Adaptive Tiling Scheme) format and the LSDB framework, developed by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) Frameworks team. This article presents a pair of variability-finding pipelines built on LSDB, the HATS catalog of DP1 data, and preliminary results of detected variable objects, two of which are novel discoveries.

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↗

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↗