Noisy NEAs

"Noise" from LISA Mission Gives Scientists a Way to Study Mass, Population of Near-Earth Asteroids

Binary stars, like the ones depicted in this artist’s drawing, will lose their orbital energy by generating gravity waves, according to Einstein’s theory of General Relativity. The NASA/ESA LISA satellites are designed to detect these waves. Planetary scientists will also be able to use LISA data to gather useful information about near-Earth asteroids.
Credit: NASA/courtesy of

Planetary scientists will get some unexpected help from the NASA/ESA LISA satellites thanks to a clever way of turning “noise” from that mission’s data into useful information about near-Earth asteroids, according to a paper by Pasquale Tricarico, a scientist at the Tucson-based Planetary Science Institute.

LISA is on a mission to detect gravitational waves – a warping of the space/time continuum that scientists hope to see directly for the first time.

LISA, slated for launch no earlier than 2018, will include three satellites connected by laser beams. The distance between the satellites should change as a gravitational wave passes. But it’s a small effect, causing the distance to change by less than an atom’s width.

Einstein’s General Theory of Relativity predicts that gravitational waves from exploding stars or colliding black holes ripple across the universe, causing other bodies to wobble like driftwood in a motorboat’s wake.

The LISA mission is primarily designed to help observe gravitational waves – a phenomenon predicted by Einstein’s General Theory of Relativity.
Credit: Einstein archives

In 2006, planetary scientists realized that Near Earth Asteroids (NEAs) also would make the spacecraft wobble as they passed nearby, creating a distinct signature in the data being collected.

Tricarico expanded on that work to predict the number of asteroid encounters LISA can expect and how those encounters can be used to determine the mass of passing asteroids.

Tricarico’s paper, which will be published in the “Classical and Quantum Gravity” journal, predicts that LISA can expect to see one or two known near-Earth asteroids a year, and a total of around ten during the expected mission lifetime. To see the paper online, go to:

When an encounter with a known asteroid shows up in the data, scientists will already know its trajectory. “So from the signal, we can indirectly measure the asteroid’s mass because that’s the only uncertainty in the equation,” Tricarico said.

These mass measurements are important because “we only know the mass of asteroids that have been visited by spacecraft or the mass of a few binary asteroids observed from Earth,” he added. “We always wonder about the porosity, the density, and this will give us measurements from additional asteroids.” Mass measurements can also help astrobiologists determine the potential affects such asteroids could have if they were to impact the Earth in the future.

The Laser Interferometer Space Antenna (LISA) mission’s primary objective is to search for gravitational waves, but the mission will also help astrobiologists study near-Earth asteroids (NEAs).
Credit: NASA

If a known asteroid passes one of the satellites and doesn’t leave a signature, “that allows us to put an upper limit on the mass of that asteroid,” Tricarico added.

Tricarico also has predicted the number of potential encounters with smaller, unknown NEAs.

“We don’t have good constraints on the size distribution for small asteroids because they have to come very close to Earth for us to observe them using ground-based telescopes,” he said. If LISA starts detecting five asteroids a year instead of two or three, this could modify theories concerning the distribution of sizes in the NEA population.

Asteroids may have played a role in the origin of life by delivering important precursor molecules to our planet. Because of this, obtaining a more accurate estimate of the numbers of NEAs is important for astrobiologists trying to understand the amount of material delivered to Earth in the past – as well as the present day.

Tricarico’s work in this area was supported by NASA’s Applied Information Research Program.