Artash Nath, Grade 8 Student. I was thrilled to be offered a slot to speak at the TRANSFORM 2020 Virtual Conference. Transform 2020 is a week-long celebration of digital geoscience, […]
Artash Nath, Grade 8 Student.
I was thrilled to be offered a slot to speak at the TRANSFORM 2020 Virtual Conference. Transform 2020 is a week-long celebration of digital geoscience, with hackathons, tutorials, lightning talks, and group discussions, organized by the Software Underground.
Software Underground is a grass-roots community of subsurface professionals — academic and applied geologists, geophysicists, resource engineers, and others — who write code and use computers in their work. In short, it is an exciting place for scientists that like rocks and computers to learn from each other and share their project findings.
I had a lot of fun participating in the Conference and the Hackathon and learned a lot about geological modeling and seismology in a very friendly and encouraging environment. The virtualization of conferences due to the #COVID19 lockdown has lowered the entry barriers to learning for many. And especially for those who are unable to attend the events physically because of costs, visa issues, have jobs, or attend schools.
For the past week, I attended many of the talks, tutorials, and exchanged messages and ideas with many people over the Slack. It was interesting to learn about Python Libraries (such as GemPy, ObsPy) being used by the community for Geologic Image processing, seismic modeling, and visualization. I was able to create several models, play with data from different sources such as Incorporated Research Institutions for Seismology (IRIS), Canadian National Seismograph Network (CNSN) and RaspberryPi Shake.
Machine Learning for Space Applications
On 12 June 2020, I gave a talk on how Machine Learning could be used to analyze big datasets from Outer Space to Subsurface. I have been working on big datasets on exoplanets and asteroids downloaded from NASA and the European Space Agency for the last 2 years. I have been applying machine learning to identify patterns and draw new results from them.
See my Space Data and Machine Learning projects:
- Hybrid Machine Learning Model to Remove Noise from Exoplanet Data from the ARIEL Space Telescope (presented at the ARIEL Science, Mission & Community 2020 Conference)
- Using Machine Learning to Predict Risk Index of Asteroid Collision (presented at the 2019 Planetary Defence Conference, Maryland)
Knowledge about seismology and understanding and interpreting seismology data is very useful for space-related data analysis. In some projects, seismic vibrations are noises that need to be isolated to focus on more sensitive data. And in other cases, gathering and studying seismic vibrations are themselves the goal to understand more about planetary formation.
Space to Surface: LIGO and Seismic Vibrations
For example, on 14 September 2015, the Laser Interferometer Gravitational-Wave Observatory (LIGO) observed its first Gravitational Wave (GW150914) from two colliding black holes of around 36 and 29 solar masses that happened 1.3 billion years ago. The gravitational waves detected by LIGO range in frequency from tens of hertz to a few hundred hertz. This overlaps with the frequency of seismic vibration caused by ocean waves, earthquakes, tides, weather patterns, and traffic.
To isolate from Seismic vibrations, advanced LIGO suspends its heavy mirrors (test mass) on Quadruple Pendulum. This makes them 10 to the power of 9 times quieter than the ground. The suspended mirrors act as Free Masses that can be displaced by Gravitational Waves.
See the experiment I did on isolating seismic vibrations using a homemade quadruple pendulum
This experiment won me the Silver Medal at the 2019 Toronto Science Fair. Watch the video of the presentation on LIGO and Seismic Vibrations, I gave at the meeting of the Royal Astronomical Society of Canada at the Ontario Science Centre.
Space to Sub Surface: Mars, NASA InSight, and Seismic Vibrations
The NASA’s Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) lander has been on the surface of Mars since November 2018 at a location known as Elysium Planitia. InSight’s two-year mission will be to study the deep interior of Mars to learn how all celestial bodies with rocky surfaces, including Earth and the Moon, formed.
It is equipped with a seismometer, SEIS, or the Seismic Experiment for Interior Structure. Its main job is to measure the pulse of Mars by studying waves created by marsquakes, thumps of meteorite impacts, and even surface vibrations generated by activity in Mars’ atmosphere and by weather phenomena such as dust storms.
Seismic Vibrations and COVID19
I continue to build up my knowledge on seismology, seismic instruments, data sources, data structures, and Python libraries. As a part of the TRANSFORM 2020 Hackathon, I am working to understand the impact of the COVID19 lockdown and the slowdown of economic activities and transport use on seismic vibrations.
This will allow me to pool the knowledge I gained from the Conference and apply it to a very interesting project.
I thank the TRANSFORM 2020 Conference Organisers for creating a welcoming, inclusive, active and enthusiastic community around sub surface, geology and seismology related topics.