Abstract A giant-impact origin for the Moon is generally accepted, but many aspects of lunar formation remain poorly understood and debated. Ćuk et al. proposed that an impact that left the Earth–Moon system with high obliquity and angular momentum could explain the Moon’s orbital inclination and isotopic similarity to Earth. In this scenario, instability during the Laplace Plane transition, when the Moon’s orbit transitions from the gravitational influence of Earth’s figure to that of the Sun, would both lower the system’s angular momentum to its present-day value and generate the Moon’s orbital inclination. Recently, Tian & Wisdom discovered new dynamical constraints on the Laplace Plane transition and concluded that the Earth–Moon system could not have evolved from an initial state with high obliquity. Here we demonstrate that the Earth–Moon system with an initially high obliquity can evolve into the present state, and we identify a spin–orbit secular resonance as a key dynamical mechanism in the later stages of the Laplace Plane transition. Some of the simulations by Tian & Wisdom did not encounter this late secular resonance, as their model suppressed obliquity tides and the resulting inclination damping. Our results demonstrate that a giant impact that left Earth with high angular momentum and high obliquity (θ> 61°) is a promising scenario for explaining many properties of the Earth–Moon system, including its angular momentum and obliquity, the geochemistry of Earth and the Moon, and the lunar inclination.
more »
« less
Tidal dissipation with 3-D finite element deformation code CitcomSVE v2.1: comparisons with the semi-analytical approach, in the context of the Lunar tidal deformations
- Award ID(s):
- 2222115
- PAR ID:
- 10618578
- Publisher / Repository:
- Springer
- Date Published:
- Journal Name:
- Celestial Mechanics and Dynamical Astronomy
- Volume:
- 136
- Issue:
- 5
- ISSN:
- 0923-2958
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract We present an expansion of FLEET, a machine-learning algorithm optimized to select transients that are most likely tidal disruption events (TDEs). FLEET is based on a random forest algorithm trained on both the light curves and host galaxy information of 4779 spectroscopically classified transients. We find that for transients with a probability of being a TDE,P(TDE) > 0.5, we can successfully recover TDEs with ≈40% completeness and ≈30% purity when using their first 20 days of photometry or a similar completeness and ≈50% purity when including 40 days of photometry, an improvement of almost 2 orders of magnitude compared to random selection. Alternatively, we can recover TDEs with a maximum purity of ≈80% and a completeness of ≈30% when considering only transients withP(TDE) > 0.8. We explore the use of FLEET for future time-domain surveys such as the Legacy Survey of Space and Time on the Vera C. Rubin Observatory (Rubin) and the Nancy Grace Roman Space Telescope (Roman). We estimate that ∼104well-observed TDEs could be discovered every year by Rubin and ∼200 TDEs by Roman. Finally, we run FLEET on the TDEs from our Rubin survey simulation and find that we can recover ∼30% of them at redshiftz< 0.5 withP(TDE) > 0.5, or ∼3000 TDEs yr–1that FLEET could uncover from the Rubin stream. We have demonstrated that we will be able to run FLEET on Rubin photometry as soon as this survey begins. FLEET is provided as an open source package on GitHub: https://github.com/gmzsebastian/FLEET.more » « less
An official website of the United States government

