About Lasair

The Rubin Observatory will provide unprecedented temporal resolution, depth and uniform photometry over an entire hemisphere, along with a real-time stream of alerts from the ever changing sky. To extract the scientific potential from that stream, the community needs brokers that offer the ability to filter, query, and manipulate the alerts, and combine them with external data sources. There are several “community brokers” for the LSST survey, listed here. The LSST:UK consortium has been building a broker called Lasair, alongside an International Data Access Centre (IDAC), building on its strengths and heritage in leading astronomical surveys, data processing and analysis. The hope is that Lasair will be of value to the worldwide community, not just to the the UK consortium.

Please see and cite our paper: R.D.Williams et. al., Enabling science from the Rubin alert stream with Lasair, RAS Techniques and Instruments, 3,1, 362 (2024).

How is Lasair Different?

Suppose you want to filter out pictures of cats from a stream of millions of pictures of animals.

One way to do it is to use humans to make a training set of cat pictures, then train a machine-learning system, and it will filter from the stream all the pictures that resemble the cats in the training set. This is what the other Rubin brokers do.

Another way is to build “features” from the pictures, then filter by the features. This is what Lasair does. Features might be number of legs, detection of whiskers, shape of ears, shape of eyes and irises, mobility of tail, nature of the background context, and so on. Other features can be the classifications made by other brokers. It is up to the user to combine the features as they wish to make a filter.

The machine-learning approach can suffer from confirmation bias: all the cats that are found look like the cats in the training set, which may not include exotic cats. The hope of the features-based approach is that (1) exotic cats are discovered that are definitely cats, but different from those in the training set; and (2) different sub-species are distinguished that were lumped together into one by the machine learning.

The Lasair approach

Lasair is a platform for scientists to make science; it does not try to make the science itself. Every Rubin broker aims to filter the stream, but Lasair does this differently. Lasair offers direct access with a staged approach: scientists can start with a simple, immediate mechanism using familiar SQL-like languages. These SQL-like queries can be custom made or users can choose and modify one of our pre-built and tested queries. These queries return an initial selection of objects, based on our rich value-added data content, and users can then run their own local code on the results. Users can build up to running their own code on both the stream and the database with their own resources. SQL filters and code can be made public, shared with a group of colleagues, duplicated, and edited. SQL filters can be escalated from static (run on command) to active (streaming) filters, that run in near real time as new alerts arrive.

How Lasair Works

Lasair is built to process transient alerts rapidly and make the key decision: is this an object I want to follow up? LSST alerts will come at very high rate, and Lasair takes advantage of the design of the distribution system: “Events are sent in rich alert packets to enable standalone classification” (slide 48). Thus alerts are judged based only on that rich alert packet, without database interaction, leading to a very fast processing rate.

The “rich data packet” means a year of past data about each object (or a month for the ZTF prototype). Note that Lasair has the full light curves – available through the object web page or API – but queries and filters are based on these shorter light curves.

See this page for a more complete description of how Lasair works.

Scientific goals of Lasair

Lasair extracts many types of astrophysical phenomena from the alert streams of ZTF/LSST: extragalactic transients, kilonovae and gravitational wave sources, massive samples of supernovae, active galactic nuclei, tidal disruption events, Milky Way and Local Group stellar transients. However, Lasair does not handle Solar System bodies.

See this page for a more complete description of science goals.