The Vera C. Rubin Observatory will, over a period of 10 yr, repeatedly survey the southern sky. To ensure that images generated by Rubin meet the quality requirements for precision science, the observatory will use an active-optics system (AOS) to correct for alignment and mirror surface perturbations introduced by gravity and temperature gradients in the optical system. To accomplish this, Rubin will use out-of-focus images from sensors located at the edge of the focal plane to learn and correct for perturbations to the wave front. We have designed and integrated a deep-learning (DL) model for wave-front estimation into the AOS pipeline. In this paper, we compare the performance of this DL approach to Rubin’s baseline algorithm when applied to images from two different simulations of the Rubin optical system. We show the DL approach is faster and more accurate, achieving the atmospheric error floor both for high-quality images and low-quality images with heavy blending and vignetting. Compared to the baseline algorithm, the DL model is 40× faster, the median error 2× better under ideal conditions, 5× better in the presence of vignetting by the Rubin camera, and 14× better in the presence of blending in crowded fields. In addition, the DL model surpasses the required optical quality in simulations of the AOS closed loop. This system promises to increase the survey area useful for precision science by up to 8%. We discuss how this system might be deployed when commissioning and operating Rubin.
Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Space and Time: A Pioneering Process of Community-focused Experimental Design
Abstract Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the National Science Foundation and the U.S. Department of Energy, designed to conduct a multipurpose 10 yr optical survey of the Southern Hemisphere sky: the Legacy Survey of Space and Time. Significant flexibility in survey strategy remains within the constraints imposed by the core science goals of probing dark energy and dark matter, cataloging the solar system, exploring the transient optical sky, and mapping the Milky Way. The survey’s massive data throughput will be transformational for many other astrophysics domains and Rubin’s data access policy sets the stage for a huge community of potential users. To ensure that the survey science potential is maximized while serving as broad a community as possible, Rubin Observatory has involved the scientific community at large in the process of setting and refining the details of the observing strategy. The motivation, history, and decision-making process of this strategy optimization are detailed in this paper, giving context to the science-driven proposals and recommendations for the survey strategy included in this Focus Issue.
more »
« less
- NSF-PAR ID:
- 10333663
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Date Published:
- Journal Name:
- The Astrophysical Journal Supplement Series
- Volume:
- 258
- Issue:
- 1
- ISSN:
- 0067-0049
- Page Range / eLocation ID:
- 1
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
null (Ed.)The Legacy Survey of Space and Time, operated by the Vera C. Rubin Observatory, is a 10-year astronomical survey due to start operations in 2022 that will image half the sky every three nights. LSST will produce ~20TB of raw data per night which will be calibrated and analyzed in almost real-time. Given the volume of LSST data, the traditional subset-download-process paradigm of data reprocessing faces significant challenges. We describe here, the first steps towards a gateway for astronomical science that would enable astronomers to analyze images and catalogs at scale. In this first step, we focus on executing the Rubin LSST Science Pipelines, a collection of image and catalog processing algorithms, on Amazon Web Services (AWS). We describe our initial impressions of the performance, scalability, and cost of deploying such a system in the cloud.more » « less
-
more » « less
Abstract Lasair is the UK Community Broker for transient alerts from the Legacy Survey of Space and Time from the Vera C. Rubin Observatory. We explain the system’s capabilities, how users can achieve their scientific goals, and how Lasair is implemented. Lasair offers users a kit of parts that they can use to build filters to concentrate their desired alerts. The kit has novel light-curve features, sky context, watchlists of special sky objects and regions of the sky, dynamic cross-matching with catalogues of known astronomical sources, and classifications and annotations from other users and partner projects. These resources can be shared with other users, copied, and modified. Lasair offers real-time machine-to-machine notifications of filtered transient alerts. Even though the Rubin Observatory is not yet complete, Lasair is a mature system: it has been processing and serving data from the similarly formatted stream of the Zwicky Transient Facility alerts.
-
ABSTRACT The largest uncertainty on measurements of dark energy using type Ia supernovae (SNeIa) is presently due to systematics from photometry; specifically to the relative uncertainty on photometry as a function of wavelength in the optical spectrum. We show that a precise constraint on relative photometry between the visible and near-infrared can be achieved at upcoming survey telescopes, such as at the Vera C. Rubin Observatory, via a laser source tuned to the 342.78 nm vacuum excitation wavelength of neutral sodium atoms. Using a high-power laser, this excitation will produce an artificial star, which we term a ‘laser photometric ratio star’ (LPRS) of de-excitation light in the mesosphere at wavelengths in vacuum of 589.16, 589.76, 818.55, and 819.70 nm, with the sum of the numbers of 589.16 and 589.76 nm photons produced by this process equal to the sum of the numbers of 818.55 and 819.70 nm photons, establishing a precise calibration ratio between, for example, the r and $z$ filters of the LSST camera at the Rubin Observatory. This technique can thus provide a novel mechanism for establishing a spectrophotometric calibration ratio of unprecedented precision for upcoming telescopic observations across astronomy and atmospheric physics; thus greatly improving the performance of upcoming measurements of dark energy parameters using type SNeIa. The second paper of this pair describes an alternative technique to achieve a similar, but brighter, LPRS than the technique described in this paper, by using two lasers near resonances at 589.16 and 819.71 nm, rather than the single 342.78 nm on-resonance laser technique described in this paper.more » « less
-
Abstract The Vera C. Rubin Observatory is expected to start the Legacy Survey of Space and Time (LSST) in early to mid-2025. This multiband wide-field synoptic survey will transform our view of the solar system, with the discovery and monitoring of over five million small bodies. The final survey strategy chosen for LSST has direct implications on the discoverability and characterization of solar system minor planets and passing interstellar objects. Creating an inventory of the solar system is one of the four main LSST science drivers. The LSST observing cadence is a complex optimization problem that must balance the priorities and needs of all the key LSST science areas. To design the best LSST survey strategy, a series of operation simulations using the Rubin Observatory scheduler have been generated to explore the various options for tuning observing parameters and prioritizations. We explore the impact of the various simulated LSST observing strategies on studying the solar system’s small body reservoirs. We examine what are the best observing scenarios and review what are the important considerations for maximizing LSST solar system science. In general, most of the LSST cadence simulations produce ±5% or less variations in our chosen key metrics, but a subset of the simulations significantly hinder science returns with much larger losses in the discovery and light-curve metrics.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3847/1538-4365/ac3e72
