Artificial intelligence helps to predict likelihood of life on other worlds
European Week of Astronomy and Space Science press release
RAS PR 18/16 (EWASS 12)
3 April 2018
Developments in artificial intelligence may help us to predict the probability of life on other planets, according to new work by a team based at Plymouth University. The study uses artificial neural networks (ANNs) to classify planets into five types, estimating a probability of life in each case, which could be used in future interstellar exploration missions. The work is presented at the European Week of Astronomy and Space Science (EWASS) in Liverpool on 4 April by Mr Christopher Bishop.
Artificial neural networks are systems that attempt to replicate the way the human brain learns. They are one of the main tools used in machine learning, and are particularly good at identifying patterns that are too complex for a biological brain to process.
The team, based at the Centre for Robotics and Neural Systems at Plymouth University, have trained their network to classify planets into five different types, based on whether they are most like the present-day Earth, the early Earth, Mars, Venus or Saturn’s moon Titan. All five of these objects are rocky bodies known to have atmospheres, and are among the most potentially habitable objects in our Solar System.
Composite image showing an infrared view of Saturn's moon Titan, taken from NASA's Cassini spacecraft. Some measures suggest that Titan has the highest habitability rating of any world other than Earth, based on factors such as availability of energy, and various surface and atmosphere characteristics. Credit: NASA / JPL / University of Arizona / University of Idaho. Click for a larger image
Mr Bishop comments, “We’re currently interested in these ANNs for prioritising exploration for a hypothetical, intelligent, interstellar spacecraft scanning an exoplanet system at range.”
He adds, “We're also looking at the use of large area, deployable, planar Fresnel antennas to get data back to Earth from an interstellar probe at large distances. This would be needed if the technology is used in robotic spacecraft in the future.”
Atmospheric observations – known as spectra – of the five Solar System bodies are presented as inputs to the network, which is then asked to classify them in terms of the planetary type. As life is currently known only to exist on Earth, the classification uses a ‘probability of life’ metric which is based on the relatively well-understood atmospheric and orbital properties of the five target types.
Bishop has trained the network with over a hundred different spectral profiles, each with several hundred parameters that contribute to habitability. So far, the network performs well when presented with a test spectral profile that it hasn’t seen before.
Schematic diagram of a neural network. The inputs represent values from a spectrum of a test planet’s atmosphere. The output layer contains a ‘probability of life’, which is based on a measurement of the input’s similarity to the five Solar System targets. The inputs pass through a series of hidden layers in the network, which are interconnected and enable the network to ‘learn’ which patterns of spectral lines correspond to a specific planet type. Credit: C. Bishop / Plymouth University. Click for a larger image
“Given the results so far, this method may prove to be extremely useful for categorising different types of exoplanets using results from ground–based and near Earth observatories” says Dr Angelo Cangelosi, the supervisor of the project.
The technique may also be ideally suited to selecting targets for future observations, given the increase in spectral detail expected from upcoming space missions such ESA’s Ariel Space Mission and NASA’s James Webb Space Telescope.
Media contacts
Dr Robert Massey
Royal Astronomical Society
Mob: +44 (0)7802 877 699
This email address is being protected from spambots. You need JavaScript enabled to view it.
Ms Anita Heward
Royal Astronomical Society
Mob: +44 (0)7756 034 243
This email address is being protected from spambots. You need JavaScript enabled to view it.
Dr Morgan Hollis
Royal Astronomical Society
Mob: +44 (0)7802 877 700
This email address is being protected from spambots. You need JavaScript enabled to view it.
Dr Helen Klus
Royal Astronomical Society
This email address is being protected from spambots. You need JavaScript enabled to view it.
Ms Marieke Baan
European Astronomical Society
This email address is being protected from spambots. You need JavaScript enabled to view it.
Science contacts
Mr Christopher Bishop
Centre for Robotics and Neural Systems
Plymouth University
christopher.bishop@plymouth.
Dr Angelo Cangelosi
Centre for Robotics and Neural Systems
Plymouth University
This email address is being protected from spambots. You need JavaScript enabled to view it.
Images and captions
Composite image showing an infrared view of Saturn's moon Titan, taken from NASA's Cassini spacecraft. Some measures suggest that Titan has the highest habitability rating of any world other than Earth, based on factors such as availability of energy, and various surface and atmosphere characteristics.
Credit: NASA / JPL / University of Arizona / University of Idaho
Schematic diagram of a neural network. The inputs represent values from a spectrum of a test planet’s atmosphere. The output layer contains a ‘probability of life’, which is based on a measurement of the input’s similarity to the five Solar System targets. The inputs pass through a series of hidden layers in the network, which are interconnected and enable the network to ‘learn’ which patterns of spectral lines correspond to a specific planet type.
Credit: C. Bishop / Plymouth University
Notes for editors
The European Week of Astronomy and Space Science (EWASS 2018) will take place at the Arena and Conference Centre (ACC) in Liverpool from 3 - 6 April 2018. Bringing together around 1500 astronomers and space scientists, the conference is the largest professional astronomy and space science event in the UK for a decade and will see leading researchers from around the world presenting their latest work.
EWASS 2018 is a joint meeting of the European Astronomical Society and the Royal Astronomical Society. It incorporates the RAS National Astronomy Meeting (NAM), and includes the annual meeting of the UK Solar Physics (UKSP) group. The conference is principally sponsored by the Royal Astronomical Society (RAS), the Science and Technology Facilities Council (STFC) and Liverpool John Moores University (LJMU).
Liverpool John Moores University (LJMU) is one of the largest, most dynamic and forward-thinking universities in the UK, with a vibrant community of 25,000 students from over 100 countries world-wide, 2,500 staff and 250 degree courses. LJMU celebrated its 25th anniversary of becoming a university in 2017 and has launched a new five-year vision built around four key ‘pillars’ to deliver excellence in education; impactful research and scholarship; enhanced civic and global engagement; and an outstanding student experience.
The Royal Astronomical Society (RAS), founded in 1820, encourages and promotes the study of astronomy, solar-system science, geophysics and closely related branches of science. The RAS organizes scientific meetings, publishes international research and review journals, recognizes outstanding achievements by the award of medals and prizes, maintains an extensive library, supports education through grants and outreach activities and represents UK astronomy nationally and internationally. Its more than 4000 members (Fellows), a third based overseas, include scientific researchers in universities, observatories and laboratories as well as historians of astronomy and others.
The RAS accepts papers for its journals based on the principle of peer review, in which fellow experts on the editorial boards accept the paper as worth considering. The Society issues press releases based on a similar principle, but the organisations and scientists concerned have overall responsibility for their content.
Follow the RAS on Twitter, Facebook and Instagram
The European Astronomical Society (EAS) promotes and advances astronomy in Europe. As an independent body, the EAS is able to act on matters that need to be handled at a European level on behalf of the European astronomical community. In its endeavours the EAS collaborates with affiliated national astronomical societies and also with pan-European research organisations and networks. Founded in 1990, the EAS is a society of individual members. All astronomers may join the society, irrespective of their field of research, or their country of work or origin. In addition, corporations, publishers and non-profit organisations can become organizational members of the EAS. The EAS, together with one of its affiliated societies, organises the annual European Week of Astronomy & Space Science (formerly known as JENAM) to enhance its links with national communities, to broaden connections between individual members and to promote European networks.
The Science and Technology Facilities Council (STFC) is keeping the UK at the forefront of international science and has a broad science portfolio and works with the academic and industrial communities to share its expertise in materials science, space and ground-based astronomy technologies, laser science, microelectronics, wafer scale manufacturing, particle and nuclear physics, alternative energy production, radio communications and radar.
STFC's Astronomy and Space Science programme provides support for a wide range of facilities, research groups and individuals in order to investigate some of the highest priority questions in astrophysics, cosmology and solar system science. STFC's astronomy and space science programme is delivered through grant funding for research activities, and also through support of technical activities at STFC's UK Astronomy Technology Centre and RAL Space at the Rutherford Appleton Laboratory. STFC also supports UK astronomy through the international European Southern Observatory.
Follow STFC on Twitter
STFC is part of UK Research and Innovation
