The Digital Press

The LSST survey at the Vera C. Rubin Observatory will vastly increase discoveries of solar system objects, but interpreting its data requires accounting for complex detection biases. Sorcha, a new open-source Python simulator, is designed to model these biases at LSST’s unprecedented scale, enabling accurate population comparisons.

Why it matters: Sorcha helps astronomers correct for detection biases in LSST’s huge solar system object dataset.

The big picture: LSST will discover about 5 million new solar system objects over ten years, demanding new simulation tools.

Stunning stat: Sorcha can simulate billions of objects, supporting analysis on local machines and high-performance clusters.

Quick takeaway: Sorcha’s modular design makes it adaptable to various surveys beyond LSST, broadening its utility.