Arushi Nath

Toronto, Canada


Arushi Nath

Toronto, Canada


Arushi Nath

Toronto, Canada


Planetary Defense Conference (PDC) 2023 Poster Presentation

Developing Algorithms for Characterisation of Near Earth Asteroids and Measure the Impact of the DART Mission
The Planetary Defense Conference  (PDC) is held bi-annually bringing together the world’s experts to discuss the threats asteroid  and comet may  present to the Earth, and the measures that can be taken to defend Earth against approaching objects.

The 8th PDC conference is happening at the Vienna International Centre and the Austrian Academy of Sciences, in cooperation with ESA, the Commission for Geosciences of the Austrian Academy of Sciences and UNOOSA from 3 - 7 April 2023.

I am presenting my citizen science work on planetary defense using robotic telescopes and open data, in particular on characterisation of Near-Earth Objects (NEOs) and measuring the impact of the NASA Double Asteroids Redirection Test (DART) Mission.

Lunar and Planetary Science Conference (LPSC) 2023 Poster Presentation

(My Research Poster in 20 threaded tweets)
Strengthening Planetary Defense: Developing Algorithms to Determine the Physical Properties of Asteroids using Robotic Telescopes and Applying them to Measure the Impact of NASA’s DART Asteroid Deflection Mission

The pace of discovery of near-earth asteroids outpaces current abilities to analyze them. Knowledge of an asteroid's physical properties is essential to deflect them. I developed open-source algorithms that combine images from robotic telescopes and open data to determine asteroids' size, rotation, and strength. I took observations of the Didymos binary asteroid, and my algorithm determined it to be 850m wide, with a 2.26-hour rotation period and rubble pile strength. I measured a 35-minute decrease in the mutual orbital period after impact by the 2022 NASA DART Mission. External sources validated the findings. Every citizen scientist is now a planetary defender.

Publication: Finding Unknown Asteroids to Strengthen Planetary Defence

Arushi Nath. Journal of the Royal Astronomical Society of Canada. Volume 117.  February 2023.

 The success of the NASA Double Asteroid Redirection Test (DART) Mission in slamming a kinetic impactor on moonlet Dimorphos of asteroid Didymos on 2022 September 26 and changing its orbit has put the planetary defence on world news. The challenge of planetary defence intrigues me. Roughly 66 million years ago, an asteroid at least 10–kilometres wide may have led to the extinction of dinosaurs. If humans do not want to suffer the same fate, then we need to be well-informed and prepared to handle any threats of an asteroid colliding with Earth. Webinar: Asteroid Science with Remote Telescope with a focus on DART Mission

Citizen science and robotic telescopes have brought astronomy to everyone, from school kids to backyard astronomers and those staying in rural areas with dark skies to city dwellers living under a light cloud. For the past two years, Arushi Nath, age 13, has been using robotic telescopes, open datasets, python algorithms, and middle school maths to undertake research on near-earth asteroids. Astrometry-related observations helped her identify asteroids, provide information about their celestial location, and predict their future locations. Photometry involved taking images of the asteroid to find its magnitude. Longer observations yield a change in magnitude, which makes it possible to find the rotational period. For binary asteroids, she uses light curves to find the moonlet’s orbital period. As with all her research, she makes her datasets and methodology open source to reach out to other youths and citizen scientists.

Strengthening Planetary Defense: Detecting Unknown Asteroids using Open Data, Math, and Python

I took images from 4 telescopes located at different latitudes to get full sky coverage. I wrote Python algorithms to query European Space Agency’s GAIA and NASA’s Horizon sky catalogues to find all known stars and asteroids. Mean, standard deviation, and histograms created masks to remove known objects. The remaining objects were classified as possible asteroid candidates.
I detected 3 ‘preliminary’ asteroids. Using the telescope's focal length and celestial location, my algorithm’s plate-solving ability determined its Right Ascension and Declination. I reported this information by creating a Minor Planet Center report for my images. I have made my code and methodology open-source to crowdsource planetary defense.

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