Marcos López-Caniego


Sessions

11-06
10:15
30min
EXPLORING THE DARK SIDE OF THE UNIVERSE: THE EUCLID SCIENTIFIC ARCHIVE SYSTEM
Sara Nieto, Marcos López-Caniego

Euclid is the ESA mission to explore the dark universe in the next decade. Launched on the 1st of July this year, Euclid is orbiting around the Lagrange L2 point and will map the 3D distribution of billions of galaxies and dark matter associated with them. It will hence measure the large-scale structures of the Universe across 10 billion light years, revealing the history of its expansion and the growth of structures during the last three-quarters of its history. The Euclid Consortium (EC) is in charge of processing all the Euclid data, of which only the most scientifically valuable data will be released through the Euclid Science Archive System (ESAS) during 6 years of mission lifetime: images, various types of catalogues and spectra.

Regarding data release contents, it is planned to combine Euclid observations with ground-based images obtained from several telescopes, and a huge pixel data collection, catalogues and spectra. At the end of 2023, the first science ready data products of the Early Release Observations (EROs) shall be published in ESAS. At the same time, the first data of the EC pipeline will be made available in ESAS too but only to EC members. The first public release, Q1 is planned by the end of 2024.
In the meantime, the science archive already hosts simulated images, catalogues and spectra that were used to excercise the scientific exploitation. Thus, in order to demonstrate how to explore, visualize and analyze the first public data, within the next Focus Demo, we will show the latest functionalities of the archive and the tools available for the users, such as the ESA Euclid Astroquery and ESA Datalabs Science Platform among others.

Science with data archives: challenges in multi-wavelength and time domain data analysis
Focus Demos
11-09
15:15
30min
Navigating ESA HST and JWST Science Archives through Automated Jupyter Notebooks
Javier Espinosa Aranda, Marcos López-Caniego, Maria Arevalo Sanchez

Efficient data access and analysis are crucial in the ever-expanding realm of astrophysical research. This demonstration aims to showcase a comprehensive workflow for initiating and conducting research using the European Space Agency's (ESA) Hubble Space Telescope (HST) and James Webb Space Telescope (JWST) Science Archives. Guidance will be provided from the User Interfaces to advanced scripting, supporting researchers when navigating the vast repositories of observations and data.

Starting from scratch, participants will learn how to execute simple searches using the available User Interfaces (https://hst.esac.esa.int/ehst, https://jwst.esac.esa.int/archive). These user-friendly applications will help users to identify the desired observations and check the associated files in the quick-look viewers for images, cubes and even their footprints, using an embedded version of ESASky. The objective of this step is to construct complex queries that target specific celestial objects, time periods, and data types, among many other filters.

A step-by-step walkthrough will highlight the direct integration of these queries into automated Jupyter Notebooks generated on-the-fly in the User Interfaces, removing the need for manual data extraction. These notebooks will be readily equipped with essential code snippets for data retrieval, pre-processing, and initial analysis. Participants will gain insights into effectively handling and visualizing data directly within the notebooks.

The automated notebooks serve as a foundation for attendees to embark on scientific exploration immediately, facilitating faster insights and reducing the barrier to entry for researchers new to the archives. This approach not only empowers researchers but also encourages collaborative and reproducible research practices within the astrophysical community (e.g. integrating these Notebooks into ESA Datalabs).

Science with data archives: challenges in multi-wavelength and time domain data analysis
Focus Demos