Related papers: From Data to Software to Science with the Rubin Ob…
The exponential growth of astronomical datasets provides an unprecedented opportunity for humans to gain insight into the Universe. However, effectively analyzing this vast amount of data poses a significant challenge. Astronomers are…
Cosmology is one of the four science pillars of LSST, which promises to be transformative for our understanding of dark energy and dark matter. The LSST Dark Energy Science Collaboration (DESC) has been tasked with deriving constraints on…
We have developed an end-to-end photometric data processing pipeline to compare current photometric algorithms commonly used on ground-based imaging data. This testbed is exceedingly adaptable, and enables us to perform many research and…
As we are fast approaching the beginning of a paradigm shift in the field of science, Data driven science (the so called fourth science paradigm) is going to be the driving force in research and innovation. From medicine to biodiversity and…
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…
In the last decades, scientific software has graduated from a hidden side-product to a first-class member of the astrophysics literature. We aim to quantify the activity and impact of software development for astronomy, using a systematic…
Software plays a central role in scientific discovery. Improving how we develop and use software for research can have both broad and deep impacts on a spectrum of challenges and opportunities society faces today. The emergence of Research…
In 2021, the Coordinated Science Laboratory CSL, an Interdisciplinary Research Unit at the University of Illinois Urbana-Champaign, hosted the Future of Computing Symposium to celebrate its 70th anniversary. CSL's research covers the full…
We explore synergies between the space-based Wide-Field Infrared Survey Telescope (WFIRST) and the ground-based Rubin Observatory Legacy Survey of Space and Time (LSST). In particular, we consider a scenario where the currently envisioned…
Rucio is an open-source software framework that provides scientific collaborations with the functionality to organize, manage, and access their data at scale. The data can be distributed across heterogeneous data centers at widely…
Everybody wants to analyse their data, but only few posses the data science expertise to to this. Motivated by this observation we introduce a novel framework and system \textsc{VisualSynth} for human-machine collaboration in data science.…
The Large Synoptic Survey Telescope (LSST) project will conduct a ten year multi-band survey starting in 2022. Observing strategies for this survey are being actively investigated, and the science capabilities can be best forecasted on the…
The era of data-intensive astronomy is being ushered in with the increasing size and complexity of observational data across wavelength and time domains, the development of algorithms to extract information from this complexity, and the…
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…
Time-domain Astrophysics (TDA), a foundation of Astronomy, has become a major part of current and projected (2020s) astrophysics. While much has been derived from temporal measures of flux and color, the real physics comes from…
Extragalactic science and cosmology with Stage IV galaxy surveys will rely almost exclusively on redshift measurements derived solely from photometry, which are subject to systematic and statistical uncertainties with numerous analysis…
Astronomy produces extremely large data sets from ground-based telescopes, space missions, and simulation. The volume and complexity of these rich data sets require new approaches and advanced tools to understand the information contained…
Rosetta is a science platform for resource-intensive, interactive data analysis which runs user tasks as software containers. It is built on top of a novel architecture based on framing user tasks as microservices - independent and…
A new golden age in astronomy is upon us, dominated by data. Large astronomical surveys are broadcasting unprecedented rates of information, demanding machine learning as a critical component in modern scientific pipelines to handle the…
Reproducibility remains a central challenge in machine learning (ML), especially in collaborative eScience projects where teams iterate over data, features, and models. Current ML workflows are often dynamic yet fragmented, relying on…