Legacy Survey of Space and Time (LSST)

• LSST is a comprehensive 10-year astronomical survey employing deep, wide-field imaging to study cosmic phenomena from faint galaxies to solar system bodies.
• The survey uses innovative data processing techniques to manage 20 terabytes of nightly data, enabling real-time analysis and precise stellar and galaxy models.
• LSST’s high-precision measurements advance our understanding of galaxy evolution, stellar content, and the dynamics of near-Earth and trans-Neptunian objects.

The Legacy Survey of Space and Time (LSST), conducted by the Vera C. Rubin Observatory, represents a monumental endeavor in astronomical surveys. Scheduled to span a ten-year period, LSST aims to revolutionize our understanding of various astronomical phenomena, utilizing its unparalleled depth, breadth, and technological innovation.

Imaging Depth and Field of View

LSST features deep and wide imaging capabilities, designed to probe vast regions of the southern hemisphere sky with unprecedented sensitivity. The survey can achieve a 10-year depth of approximately $r \approx 27.5$ AB magnitude, with a surface brightness limit exceeding 32 mag arcsec$^{-2}$, enabling the detection of faint astronomical phenomena. A substantial field of view, roughly $9.6$ deg$^2$, combined with an etendue of $319 \text{ m}^2 \text{ deg}^2$, grants it the statistical power to uncover rare low surface brightness features, profoundly impacting galaxy evolution studies (Brough et al., 2020).

Studies of Low Surface Brightness Phenomena

The LSST's depth is integral to exploring low surface brightness astronomy, allowing detailed examination of phenomena such as faint shells, tidal tails, and stellar streams around galaxies—key indicators of galaxy interactions and mergers. This capacity for deep imaging is expected to reveal new populations of LSB galaxies and provide significant insights into the intracluster light (ICL), offering a historic first in detailed ICL measurements across varying cluster masses and redshifts (Brough et al., 2020).

White Dwarfs and Stellar Content

In the field of stellar astronomy, LSST stands to dramatically increase our knowledge base, particularly concerning white dwarfs (WDs). Over the survey's duration, LSST is predicted to detect more than 150 million WDs. Utilizing its precise parallax and proper motion data, LSST will allow for improved WD population models, facilitating a better understanding of stellar evolution pathways, including ZZ Ceti stars and those with debris disks (Fantin et al., 2020).

LSST's stellar content simulation, employing the TRILEGAL code, predicts detailed mappings of variable stars such as Cepheids and eclipsing binaries. This will help refine our models of stellar populations and the structure of our galaxy, the Milky Way, and the Magellanic Clouds (Tio et al., 2022).

Solar System Science

A significant application of the LSST is in mapping the solar system's small bodies. LSST is expected to yield an extensive catalog of approximately 100,000 near-Earth objects and millions of main belt asteroids and trans-Neptunian objects. This dataset will enable critical advancements in understanding planetary formation and the dynamics of small body populations, providing robust data for identifying potential hazardous objects (Collaboration et al., 2020).

Furthermore, LSST's ability to measure asteroid masses through the observation of mutual gravitational encounters between asteroids will allow more precise determination of the physical properties of these bodies, significantly enhancing solar system sciences (Bernstein et al., 1 Apr 2025).

Data Processing and Infrastructure

To manage the vast data output—approximately 20 terabytes of nightly data—a sophisticated distributed image processing infrastructure has been deployed. Key facilities in the US, the UK, and France will handle data processing and storage. Utilization of cloud-based services such as AWS for scaling the LSST Science Pipelines exemplifies how modern computing infrastructure can effectively manage high-frequency, large-volume data workloads (Hernandez et al., 2023).

These cloud-based strategies highlight innovations such as automated data abstraction and dynamic resource allocation, crucial for maintaining efficient, cost-effective processing and real-time analysis capabilities (Bektesevic et al., 2020).

Management and Collaboration

LSST’s operational strategy has been shaped through extensive community collaboration. Initiatives like the Metric Analysis Framework (MAF) and Operational Simulator (OpSim) enable continuous refinement of observing strategies to optimize scientific outputs across diverse astrophysical fields (Bianco et al., 2021).

This approach also underpins LSST's capability to accommodate future scientific prospects through adaptive survey strategies and potential upgrades, ensuring that the Rubin Observatory remains an essential resource for the astronomical community even beyond its initial 10-year mission (Blum et al., 2022).

In conclusion, the LSST is set to provide an unprecedented view of the universe, from unraveling cosmological mysteries and mapping the structure of the Milky Way, to reforming our understanding of solar system dynamics and stellar evolution. Its legacy will be a trove of high-quality data accelerating discovery across multiple domains in astrophysics.