Exploring Citizen Science Use Cases with the Lasair transient alert broker

Lead Research Organisation: Queen's University Belfast
Department Name: Sch of Mathematics and Physics

Abstract

Astronomy will enter the petabyte era with the first light of the 8.2-m Large Synoptic Survey Telescope (LSST). Equipped with a wide-field camera covering an area 40 times the size of the full Moon, LSST will effectively make the largest movie of the night sky. Every three nights LSST will survey the entire visible night sky. This enables an unprecedented study of cosmic and Solar System transients: variable stars, moving Solar System objects, Solar System bodies exhibiting cometary activity, supernovae, and other astrophysical explosions. LSST will identify ten million transient/variable sources per night Using present day LSST precursor datasets, we will explore how we can maximise LSST transient science by combining citizen science/crowd-sourcing and automated routines to better search for the astronomical needle in a haystack. In particular, we will focus on how the Lasair alert stream broker concept can be leveraged with the Zooniverse platform, which hosts the largest collection of people-powered projects in the world, to efficiently and effectively sift through the LSST alert stream in real time to identify transient sources worthy of rapid follow-up with other ground-based and space-based telescopes.

Technical Summary

The 2020s will see time domain astronomy enter a new era with the first light of the Large Synoptic Survey Telescope (LSST). LSST is wide-field 8.2-m optical telescope under construction in Chile. Starting in 2022, LSST will generate 15 terabytes of images nightly, approximately 40 times larger than present-day wide-field astronomical surveys produce today. LSST will radically transform our view of the transient and variable sky. Each night, LSST is expected to produce up to ten million identifications of transient sources per night, identifying large numbers of novae, supernovae, gravitational lensing, rare astrophysical explosions, Solar System moving objects, and variable stars. LSST will also provide an unprecedented window into time-domain transient Solar System science. Surveying the sky every 3 nights, LSST will monitor millions of asteroids and tens of thousands of distant Solar System bodies, producing the largest sample of comets and other active small bodies exhibiting comet-like behavior. With such a data deluge, Lasair, the UK LSST alert stream broker concept, is being built to in real time filter and classify future LSST transient detections to enable rapid follow-up observations of unique and interesting sources. We propose to explore citizen science uses cases for exploiting LSST time domain science and in particular how the Lasair alert stream broker can be leveraged with the Zooniverse platform to provide unique transient science when paired with citizen science assessment and machine learning techniques.

Planned Impact

We propose to explore citizen science uses cases for exploiting LSST time domain science and in particular how the Lasair alert stream broker can be leveraged with the Zooniverse platform to provide unique transient science when paired with citizen science assessment and machine learning techniques.

The proposed work will contribute to the Digital Economy, through content creation and consumption. We are exploring new pathways for citizen science to contribute to astronomical time domain and building new tools which link future surveys with the Zooniverse platform. The open source software we build will be made publicly available, enabling all groups proposing and developing LSST community alert stream brokers and present-day LSST precursor surveys to connect their broker to the Zooniverse platform, providing further citizen science opportunities in time domain astronomy. This will extend the functionality and capability of the Zooniverse and the types of citizen science projects that can be developed by researchers utilising the platform. This will directly enhance the Zoonvierse platform's value as a laboratory for the understanding of how a diverse community collaborates in order to cocreate value through data analysis.

Citizen science builds unique and authentic research experiences for the public that directly engage individuals with little or no scientific training or background. Platforms like the Zooniverse, lower the barrier for the public to contribute directly to scientific investigations. Our proposed pilot study has the potential to influence and enhance the types of citizen science projects that can be generated for transient astronomy and will enhance the capabilities of the Zooniverse platform to ingest data from time domain surveys and transient alert brokers. Through these efforts, we will also contribute towards public engagement and outreach.

Publications

10 25 50
 
Description Public engagement - see the other parts of this submission
First Year Of Impact 2020
Sector Education
Impact Types Cultural,Societal

 
Title Lasair-Zooniverse Integration 
Description This repository demonstrates integration of lasair, the LSST:UK broker concept for astronomers studying transient and variable astrophysical sources and the Zooniverse citizen science platform. The code here was used to prepare daily data uploads based on new alerts from lasair for a demonstration citizen science project hosted on the Zooniverse Project Builder platform. 
Type Of Technology Webtool/Application 
Year Produced 2020 
Open Source License? Yes  
Impact This software enables researchers to develop their own citizen science project powered by Lasair alerts. This open source repository serves as an example that can be adapted to also allow other Legacy Survey of Space and Time alert stream brokers to create unique citizen science projects with their processed alert streams. 
URL https://github.com/rafia17/Zooniverse_SLSN
 
Description Citizen Science Project Volunteer Beta Test 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact We beta tested the demo citizen science project developed from the ZTF Lasair broker. The project was developed from the Belfast meeting to test the Lasair to Zooniverse open source software and test the concept of using citizen science/human pattern recognition to identify superluminous supernovae. The light curves of superluminous supernovae typically show a significant rise in brightness over a long period (usually more than 25 days) followed by a slow decline in brightness that can last more than 200 days. Volunteers were asked to review light curves from ZTF Lasair transients not already identified as shorter rise supernovae. The results from the project demonstrate that this concept works well as a citizen science project and that the Lasair alert stream-Zooniverse connection software developed on this grant.
Year(s) Of Engagement Activity 2020
URL https://www.zooniverse.org/projects/mrniaboc/superluminous-supernovae
 
Description LSST:UK Blog Post 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Blog post summarising the funded work and describing the activities of the first planned meeting in Belfast.
Year(s) Of Engagement Activity 2020
URL https://www.lsst.ac.uk/news/2020/lsstuk-and-citizen-science-20-02-14