Uploaded July 2022 | Updated September 2026, 1 hour ago
"Models of small-body mass distribution in the solar system are based on limited ground truth, currently 14 asteroids have a measured mass. Using the laser interferometers onboard the LISA spacecraft, LISA will detect a near-Earth asteroid (NEA) when both local test masses are perturbed by the gravitational encounter. For NEA with a known orbit, the mass can then be derived.
The signal shape of a NEA encounter depends upon the NEA’s mass, velocity and impact parameter, and is distinctively different from glitches recorded by LISA Pathfinder as the test masses are displaced towards the NEA before and after the encounter. Typically, both test masses are displaced by different amounts along the axis of their respective lasers, resulting in a dual signal pattern different from single interferometer glitches and gravitational wave bursts.
Using LISA Consortium software, NEA encounters are modelled using LISA Glitch, simulated using LISA Instrument and time-delay interferometry (TDI) combinations calculated using PyTDI. Different machine learning algorithms are assessed by their relative success in detecting the NEA signal patterns. Early results of this ongoing investigation are presented.
With approximately 2 measurable NEA encounters expected per year, automated detection is required. This capability potentially extends the data analysis pipelines planned for LISA. It could also be adapted to a predictive tool as part of LISA's orbit planning to reduce the risk of NEA encounters during operational runs."
Author and Presenter: Stephen Mead
"Models of small-body mass distribution in the solar system are based on limited ground truth, currently 14 asteroids have a measured mass. Using the laser interferometers onboard the LISA spacecraft, LISA will detect a near-Earth asteroid (NEA) when both local test masses are perturbed by the gravitational encounter. For NEA with a known orbit, the mass can then be derived.
The signal shape of a NEA encounter depends upon the NEA’s mass, velocity and impact parameter, and is distinctively different from glitches recorded by LISA Pathfinder as the test masses are displaced towards the NEA before and after the encounter. Typically, both test masses are displaced by different amounts along the axis of their respective lasers, resulting in a dual signal pattern different from single interferometer glitches and gravitational wave bursts.
Using LISA Consortium software, NEA encounters are modelled using LISA Glitch, simulated using LISA Instrument and time-delay interferometry (TDI) combinations calculated using PyTDI. Different machine learning algorithms are assessed by their relative success in detecting the NEA signal patterns. Early results of this ongoing investigation are presented.
With approximately 2 measurable NEA encounters expected per year, automated detection is required. This capability potentially extends the data analysis pipelines planned for LISA. It could also be adapted to a predictive tool as part of LISA's orbit planning to reduce the risk of NEA encounters during operational runs."
Author and Presenter: Stephen Mead
