Neptune’s external mean-motion resonances play an important role in sculpting the observed population of trans-Neptunian objects (TNOs). The population of scattering TNOs is known to “stick” to Neptune's resonances while evolving in semimajor axis (a), though simulations show that resonance sticking is less prevalent at a ≳ 200–250 au. Here we present an extensive numerical exploration of the strengths of Neptune's resonances for scattering TNOs with perihelion distances q = 33 au. We show that the drop-off in resonance sticking for the large a scattering TNOs is not a generic feature of scattering dynamics but can instead be attributed to the specific configuration of Neptune and Uranus in our solar system. In simulations with just Uranus removed from the giant planet system, Neptune's resonances are strong in the scattering population out to at least ∼300 au. Uranus and Neptune are near a 2:1 period ratio, and the variations in Neptune's orbit resulting from this near-resonance are responsible for destabilizing Neptune's resonances for high-e TNO orbits beyond the ∼20:1 resonance at a ≈ 220 au. Direct interactions between Uranus and the scattering population are responsible for slightly weakening Neptune's closer-in resonances. In simulations where Neptune and Uranus are placed in their mutual 2:1 resonance, we see almost no stable libration of scattering particles in Neptune's external resonances. Our results have important implications for how the strengths of Neptune's distant resonances varied during the epoch of planet migration when the Neptune–Uranus period ratio was evolving. These strength variations likely affected the distant scattering, resonant, and detached TNO populations.
海王星的外部平均运动共振在形成观测到的跨海王星天体(TNOs)群方面起着重要作用。众所周知,在半长轴(a)的演化过程中,散射的 TNO 物体群会 "粘附 "在海王星的共振上,不过模拟结果表明,共振粘附在 ≳ 200-250 au 时并不那么普遍。在这里,我们对近日点距离 q = 33 au 的散射 TNO 的海王星共振强度进行了广泛的数值探索。我们的研究表明,大a散射TNOs共振粘性的下降并不是散射动力学的一般特征,而是由于海王星和天王星在太阳系中的特殊构造造成的。在只将天王星从巨行星系统中移除的模拟中,海王星的共振在至少 ∼300 au 范围内的散射群体中是很强的。天王星和海王星的周期比接近 2:1,这种近共振导致海王星轨道的变化,从而破坏了海王星在 ≈ 220 au 处的∼20:1 共振之外的高 e TNO 轨道共振的稳定性。天王星和散射群之间的直接相互作用会稍微削弱海王星的近距离共振。在海王星和天王星处于2:1共振的模拟中,我们发现海王星外部共振中几乎没有稳定的散射粒子天平动。我们的研究结果对海王星-天王星周期比演变的行星迁移时代海王星遥远共振的强度如何变化具有重要意义。这些强度变化很可能会影响到遥远的散射、共振和分离的尘埃粒子群。
{"title":"Uranus’s Influence on Neptune’s Exterior Mean-motion Resonances","authors":"Severance Graham, Kathryn Volk","doi":"10.3847/psj/ad4707","DOIUrl":"https://doi.org/10.3847/psj/ad4707","url":null,"abstract":"Neptune’s external mean-motion resonances play an important role in sculpting the observed population of trans-Neptunian objects (TNOs). The population of scattering TNOs is known to “stick” to Neptune's resonances while evolving in semimajor axis (<italic toggle=\"yes\">a</italic>), though simulations show that resonance sticking is less prevalent at <italic toggle=\"yes\">a</italic> ≳ 200–250 au. Here we present an extensive numerical exploration of the strengths of Neptune's resonances for scattering TNOs with perihelion distances <italic toggle=\"yes\">q</italic> = 33 au. We show that the drop-off in resonance sticking for the large <italic toggle=\"yes\">a</italic> scattering TNOs is not a generic feature of scattering dynamics but can instead be attributed to the specific configuration of Neptune and Uranus in our solar system. In simulations with just Uranus removed from the giant planet system, Neptune's resonances are strong in the scattering population out to at least ∼300 au. Uranus and Neptune are near a 2:1 period ratio, and the variations in Neptune's orbit resulting from this near-resonance are responsible for destabilizing Neptune's resonances for high-<italic toggle=\"yes\">e</italic> TNO orbits beyond the ∼20:1 resonance at <italic toggle=\"yes\">a</italic> ≈ 220 au. Direct interactions between Uranus and the scattering population are responsible for slightly weakening Neptune's closer-in resonances. In simulations where Neptune and Uranus are placed in their mutual 2:1 resonance, we see almost no stable libration of scattering particles in Neptune's external resonances. Our results have important implications for how the strengths of Neptune's distant resonances varied during the epoch of planet migration when the Neptune–Uranus period ratio was evolving. These strength variations likely affected the distant scattering, resonant, and detached TNO populations.","PeriodicalId":34524,"journal":{"name":"The Planetary Science Journal","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Proton auroras are widely observed on the dayside of Mars, identified as a significant intensity enhancement in the hydrogen Lyα (121.6 nm) emission at altitudes of ∼110 and 150 km. Solar wind protons penetrating as energetic neutral atoms into Mars’ thermosphere are thought to be primarily responsible for these auroras. Recent observations of spatially localized “patchy” proton auroras suggest a possible direct deposition of protons into Mars’ atmosphere during unstable solar wind conditions. Improving our understanding of proton auroras is therefore important for characterizing the interaction of the solar wind with Mars’ atmosphere. Here, we develop a first purely data-driven model of proton auroras using Mars Atmosphere and Volatile Evolution (MAVEN) in situ observations and limb scans of Lyα emissions between 2014 and 2022. We train an artificial neural network that reproduces individual Lyα intensities and relative Lyα peak intensity enhancements with Pearson correlations of ∼94% and ∼60% respectively for the test data, along with a faithful reconstruction of the shape of the observed altitude profiles of Lyα emission. By performing a Shapley Additive Explanations (SHAP) analysis, we find that solar zenith angle, solar longitude, CO2 atmosphere variability, solar wind speed, and temperature are the most important features for the modeled Lyα peak intensity enhancements. Additionally, we find that the modeled peak intensity enhancements are high for early local-time hours, particularly near polar latitudes, and the induced magnetic fields are weaker. Through SHAP analysis, we also identify the influence of biases in the training data and interdependences between the measurements used for the modeling, and an improvement of those aspects can significantly improve the performance and applicability of the ANN model.
{"title":"An Explainable Deep-learning Model of Proton Auroras on Mars","authors":"Dattaraj B. Dhuri, Dimitra Atri, Ahmed AlHantoobi","doi":"10.3847/psj/ad45ff","DOIUrl":"https://doi.org/10.3847/psj/ad45ff","url":null,"abstract":"Proton auroras are widely observed on the dayside of Mars, identified as a significant intensity enhancement in the hydrogen Ly<italic toggle=\"yes\">α</italic> (121.6 nm) emission at altitudes of ∼110 and 150 km. Solar wind protons penetrating as energetic neutral atoms into Mars’ thermosphere are thought to be primarily responsible for these auroras. Recent observations of spatially localized “patchy” proton auroras suggest a possible direct deposition of protons into Mars’ atmosphere during unstable solar wind conditions. Improving our understanding of proton auroras is therefore important for characterizing the interaction of the solar wind with Mars’ atmosphere. Here, we develop a first purely data-driven model of proton auroras using Mars Atmosphere and Volatile Evolution (MAVEN) in situ observations and limb scans of Ly<italic toggle=\"yes\">α</italic> emissions between 2014 and 2022. We train an artificial neural network that reproduces individual Ly<italic toggle=\"yes\">α</italic> intensities and relative Ly<italic toggle=\"yes\">α</italic> peak intensity enhancements with Pearson correlations of ∼94% and ∼60% respectively for the test data, along with a faithful reconstruction of the shape of the observed altitude profiles of Ly<italic toggle=\"yes\">α</italic> emission. By performing a Shapley Additive Explanations (SHAP) analysis, we find that solar zenith angle, solar longitude, CO<sub>2</sub> atmosphere variability, solar wind speed, and temperature are the most important features for the modeled Ly<italic toggle=\"yes\">α</italic> peak intensity enhancements. Additionally, we find that the modeled peak intensity enhancements are high for early local-time hours, particularly near polar latitudes, and the induced magnetic fields are weaker. Through SHAP analysis, we also identify the influence of biases in the training data and interdependences between the measurements used for the modeling, and an improvement of those aspects can significantly improve the performance and applicability of the ANN model.","PeriodicalId":34524,"journal":{"name":"The Planetary Science Journal","volume":"96 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141504697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Juan A. Sanchez, Vishnu Reddy, Audrey Thirouin, William F. Bottke, Theodore Kareta, Mario De Florio, Benjamin N. L. Sharkey, Adam Battle, David C. Cantillo, Neil Pearson
The study of small (<300 m) near-Earth objects (NEOs) is important because they are more closely related than larger objects to the precursors of meteorites that fall on Earth. Collisions of these bodies with Earth are also more frequent. Although such collisions cannot produce massive extinction events, they can still produce significant local damage. Here we present the results of a photometric and spectroscopic survey of small NEOs that include near-infrared spectra of 84 objects with a mean diameter of 126 m and photometric data of 59 objects with a mean diameter of 87 m. We found that S-complex asteroids are the most abundant among the NEOs, comprising ∼66% of the sample. Most asteroids in the S-complex were found to have compositions consistent with LL-chondrites. Our study revealed the existence of NEOs with spectral characteristics similar to those in the S-complex but that could be hidden within the C- or X-complex due to their weak absorption bands. We suggest that the presence of metal or shock darkening could be responsible for the attenuation of the absorption bands. These objects have been grouped into a new subclass within the S-complex called Sx-types. The dynamical modeling showed that 83% of the NEOs escaped from the ν