Science Spotlight

LSST will drive research across all areas of astronomy and will require technological advances to meet its ambitious goals. On this page we highlight some of the scientific and technical contributions that UK researchers are making to LSST.

A New Era for Interstellar Objects with LSST

LSST will usher in a new era for the study of interstellar objects, revealing new insights into how planets are constructed in our Galaxy. 

A trailer for LSST's view of the Universe

LSST will provide our most comprehensive view yet of the large-scale structure of the Universe, as traced by the clustering of galaxies. Astronomers are making preparations for that by applying to precursor datasets the analysis tools they are sharpening in readiness for LSST. 

Citizen Science with LSST

The Zooniverse citizen science platform will be used for LSST. 

Deep Learning for RAPID classification of the transient Universe

To deal with the large data volumes of modern time-domain astronomy, deep neural networks are being applied to the problem of classifying astronomical transient phenomena in survey data streams, in preparation for LSST. 

Fishing for galaxy clusters with neural nets

Galaxy clusters are some of the most massive structures in the cosmos, but despite being millions of lightyears across, they can still be hard to spot, so artificial intelligence will be used to find them in LSST's vast sky survey atlas.

LSST software is helping other astronomy projects

Astronomers operating the Gravitational-wave Optical Transient Observer (GOTO) are using LSST's open source software in their hunt for the optical counterparts of gravitational wave events. 

LSST will allow us to understand how and when the Milky Way's bulge formed

The centre of the Milky Way shows a prominent bulge which extends above the disc. LSST will permit us to map the age distribution of stars in the bulge to high fidelity to test models for the formation and evolution of the Milky Way bulge.

Simulating the distribution of galaxy redshifts

Sophisticated statistical techniques are being used to work out how best to estimate the distances to galaxies detected by LSST. 

Understanding how galaxy mergers shape the observable Universe

Mergers between galaxies, caused by the attractive force of gravity pulling objects together, are thought to be the principal process that governs the evolution of the observable Universe. The deep images that LSST will produce will reveal subtle features around galaxies that trace their merger history and that have been hidden from view hitherto.