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Register a new userModeling Planetary System Formation with N-Body Simulations: Role of Gas Disk and Statistics Comparing to Observations
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During the late stage of planet formation when Mars-size cores appear, interactions among planetary cores can excite their orbital eccentricities, speed their merges and thus sculpture the final architecture of planet systems. This series of work contributes to the final assembling of planet systems with N-body simulations, including the type I and II migration of planets, gas accretion of massive cores in a viscous disk. In this paper, the standard formulations of type I and II migrations are adopted to investigate the formation of planet systems around solar mass stars. Statistics on the final distributions of planetary masses, semi-major axes and eccentricities are derived, which are comparable to those of the observed systems. Our simulations predict some orbital signatures of planet systems around solar mass stars: 36% of the survival planets are giant planets (Mp>10Me). Most of the massive giant planets (Mp>30Me) locate at 1-10AU. Terrestrial planets distribute more or less evenly at <1-2 AU. Planets in inner orbits (<1 AU) may accumulate at the inner edges of either the protostellar disk (3-5 days) or its MRI dead zone (30-50 days). There is a planet desert in the mass-eccecntricity diagram, i.e., lack of planets with masses 0.005 - 0.08 MJ in highly eccentric orbits (e > 0.3 - 0.4). The average eccentricity (~ 0.15) of the giant planets (Mp>10Me) are bigger than that (~ 0.05) of the terrestrial planets (Mp< 10Me). A planet system with more planets tends to have smaller planet masses and orbital eccentricities on average.
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The population of exoplanetary systems detected by Kepler provides opportunities to refine our understanding of planet formation. Unraveling the conditions needed to produce the observed exoplanets will sallow us to make informed predictions as to where habitable worlds exist within the galaxy. In this paper, we examine using N-body simulations how the properties of planetary systems are determined during the final stages of assembly. While accretion is a chaotic process, trends in the ensemble properties of planetary systems provide a memory of the initial distribution of solid mass around a star prior to accretion. We also use EPOS, the Exoplanet Population Observation Simulator, to account for detection biases and show that different accretion scenarios can be distinguished from observations of the Kepler systems. We show that the period of the innermost planet, the ratio of orbital periods of adjacent planets, and masses of the planets are determined by the total mass and radial distribution of embryos and planetesimals at the beginning of accretion. In general, some amount of orbital damping, either via planetesimals or gas, during accretion is needed to match the whole population of exoplanets. Surprisingly, all simulated planetary systems have planets that are similar in size, showing that the peas in a pod pattern can be consistent with both a giant impact scenario and a planet migration scenario. The inclusion of material at distances larger than what Kepler observes has a profound impact on the observed planetary architectures, and thus on the formation and delivery of volatiles to possible habitable worlds.
We present a near-infrared K_n-band photometric study of edge-on galaxies with a box/peanut-shaped `bulge. The morphology of the galaxies is analysed using unsharp masking and fits to the vertical surface brightness profiles, and the results are compared to N-body simulations and orbital calculations of barred galaxies. Both theoretical approaches reproduce the main structures observed.
Terrestrial planet formation theory is at a bottleneck, with the growing realization that pairwise collisions are treated far too simply. Here, and in our companion paper (Cambioni et al. 2019) that introduces the training methodology, we demonstrate the first application of machine learning to more realistically model the late stage of planet formation by giant impacts. We present surrogate models that give fast, reliable answers for the masses and velocities of the two largest remnants of a giant impact, as a function of the colliding masses and their impact velocity and angle, with the caveat that our training data do not yet include pre-impact rotation or variable thermal conditions. We compare canonical N-body scenarios of terrestrial planet formation assuming perfect merger (Chambers 2001) with our more realistic treatment that includes inefficient accretions and hit-and-run collisions. The result is a protracted tail of final events lasting ~200 Myr, and the conversion of about half the mass of the initial population to debris. We obtain profoundly different solar system architectures, featuring a much wider range of terrestrial planet masses and enhanced compositional diversity.
We study structure formation in the presence of primordial non-Gaussianity of the local type with parameters f_NL and g_NL. We show that the distribution of dark-matter halos is naturally described by a multivariate bias scheme where the halo overdensity depends not only on the underlying matter density fluctuation delta, but also on the Gaussian part of the primordial gravitational potential phi. This corresponds to a non-local bias scheme in terms of delta only. We derive the coefficients of the bias expansion as a function of the halo mass by applying the peak-background split to common parametrizations for the halo mass function in the non-Gaussian scenario. We then compute the halo power spectrum and halo-matter cross spectrum in the framework of Eulerian perturbation theory up to third order. Comparing our results against N-body simulations, we find that our model accurately describes the numerical data for wavenumbers k < 0.1-0.3 h/Mpc depending on redshift and halo mass. In our multivariate approach, perturbations in the halo counts trace phi on large scales and this explains why the halo and matter power spectra show different asymptotic trends for k -> 0. This strongly scale-dependent bias originates from terms at leading order in our expansion. This is different from what happens using the standard univariate local bias where the scale-dependent terms come from badly behaved higher-order corrections. On the other hand, our biasing scheme reduces to the usual local bias on smaller scales where |phi| is typically much smaller than the density perturbations. We finally discuss the halo bispectrum in the context of multivariate biasing and show that, due to its strong scale and shape dependence, it is a powerful tool for the detection of primordial non-Gaussianity from future galaxy surveys.
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