The velocity-space distribution of the solar neighborhood stars shows complex substructures (moving groups) including the well-known Hercules stream. Recently, the Gaia observation revealed their detailed structures, but their origins are still in debate. We analyzed a high-resolution N-body simulation of a Milky Way (MW)-like galaxy. To find velocity-space distributions similar to that of the solar neighborhood stars, we used Kullback-Leibler divergence (KLD), which is a metric to measure similarities between probability distributions. The KLD analysis shows the time evolution and the spatial variation of the velocity-space distribution. Velocity-space distributions with small KLDs (i.e. high similarities) are frequently but not always detected around in the simulated MW. In the velocity-map with smallest KLD, the velocity-space substructures are made from bar resonances.

In the present work, we have developed a two-dimensional gravitational model of barred galaxies to analyse the fate of escaping stars from the central barred region. For that, the model has been analysed for two different bar profiles viz. strong and weak. Here the phenomena of stellar escape from the central barred region have been studied from the perspective of an open Hamiltonian dynamical system. We observed that the escape routes correspond to the escape basins of the two index-1 saddle points. Our results show that the formation of spiral arms is encouraged for the strong bars. Also, the formation of grand design spirals is more likely for strong bars if they host central super massive black holes (SMBHs). In the absence of central SMBHs, the formation of less-prominent spiral arms is more likely. Again, for weak bars, the formation of inner disc rings is more probable.

The purpose of the present work is a detailed investigation of the dynamical evolution of Collinder 135 and UBC 7 star clusters. We present a set of dynamical numerical simulations using realistic star cluster -body modeling technique with the forward integration of the star-by-star cluster models to the present day, based on best-available 3D coordinates and velocities obtained from the latest Gaia EDR3 data release. We have established that Collinder 135 and UBC 7 are probably a binary star cluster and have common origin. We carried out a full star-by-star N-body simulation of the stellar population of both clusters using the new algorithm of Single Stellar Evolution and performed a comparison of the results obtained in the observational data (like cumulative number counts), which showed a fairly good agreement.

We summarize a series of numerical experiments of collisional dynamics in dense stellar systems such as globular clusters (GCs) and in weakly collisional plasmas using a novel simulation technique, the so-calledMulti-particle collision (MPC) method, alternative to Fokker-Planck and Monte Carlo approaches. MPC is related to particle-mesh approaches for the computation of self consistent long-range fields, ensuring that simulation time scales with N log N in the number of particles, as opposed to N2 for direct N-body. The collisional relaxation effects are modelled by computing particle interactions based on a collision operator approach that ensures rigorous conservation of energy and momenta and depends only on particles velocities and cell-based integrated quantities.

Most stars form in clumpy and sub-structured clusters. These properties also emerge in hydro-dynamical simulations of star-forming clouds, which provide a way to generate realistic initial conditions for N-body runs of young stellar clusters. However, producing large sets of initial conditions by hydro-dynamical simulations is prohibitively expensive in terms of computational time. We introduce a novel technique for generating new initial conditions from a given sample of hydro-dynamical simulations, at a tiny computational cost. In particular, we apply a hierarchical clustering algorithm to learn a tree representation of the spatial and kinematic relations between stars, where the leaves represent the single stars and the nodes describe the structure of the cluster at larger and larger scales. This procedure can be used as a basis for the random generation of new sets of stars, by simply modifying the global structure of the stellar cluster, while leaving the small-scale properties unaltered.

We trained a Neural Network that can obtain selected STARLIGHT parameters directly from S-PLUS photometry. The training set consisted of over 55 thousand galaxies with their stellar population parameters obtained from a STARLIGHT application by Cid Fernandes et al. (2005). These galaxies were crossmatched with the S-PLUS iDR 3 database, thus, recovering the photometry for the 12 band filters for 55803 objects. We also considered the spectroscopic redshift for each object which was obtained from the SDSS. Finally, we trained a fully connected Neural Network with the 12-band photometry + redshift as features, and targeted some of the STARLIGHT parameters, such as stellar mass and mean stellar age. The model performed very well for some parameters, for example, the stellar mass, with an error of 0.23 dex. In the future, we aim to apply the model to all S-PLUS galaxies, obtaining never-before-seen photometric synthesis for most objects in the catalogue.

Gaia data allows for search for extended stellar structures in phase (coordinates plus velocities) space. We describe a method of using DBSCAN clustering algorithm, which is used to group closely-packed-together data points, to a list of preliminary selected pairs of stars, with parameters expected to be found within stellar streams and comoving groups: loose structures in which stars are not gravitationally bound, but do share motion and evolutionary properties. To test our approach, we construct a model population of background stars, and use pair-constructing and clustering algorithms on it. Results show that transitioning to a list of pairs sharply reveals structures not presented in background model, which then become more apparent targets in coordinate-velocity phase space for DBSCAN algorithm thanks to now increased relative density of the extended stellar structure.

Auroral events are the prominent manifestation of solar/stellar forcing on planetary atmospheres and are closely related to the energy deposition by and evolution of planetary atmospheres. Observations of auroras are widely used to analyze the composition, structure, and chemistry of the atmosphere under study, as well as charged particle and energy fluxes that affect the atmosphere. Numerical kinetic Monte Carlo models had been developed allowing us to study the processes of precipitation of high-energy electrons, protons and hydrogen atoms into the planetary atmospheres on molecular level of description, taking into account the stochastic nature of collisional scattering at high kinetic energies. Such models are used to study auroras at both magnetized and non-magnetized planets in the Solar and extrasolar planetary systems. The current status of the kinetic model is illustrated in application to the auroral events at Mars.

Transit observations have revealed the existence of atmospheric escape in several hot Jupiters. High energy photons from the host star heat the upper atmosphere and drive the hydrodynamic escape. The escaping atmosphere can interact with the stellar wind from the host star. We run radiation hydrodynamics simulations with non-equilibrium chemistry to investigate the wind effects on the escape and the transit signature. Our simulations follow the planetary outflow driven by the photoionization heating and the wind interaction in a dynamically coupled, self-consistent manner. We show that the planetary mass-loss rate is almost independent of the wind strength, which however affects the Ly-α transit depth considerably. But the Hα transit depth is almost independent of the wind strength because it is largely caused by the lower hot layer. We argue that observations of both lines can solve the degeneracy between the EUV flux from the host and the wind strength.

We have studied the input of the exothermic photochemistry into the formation of the non-thermal escape flux in the transition H2 − H region of the extended upper atmosphere of the hot exoplanet - the sub-neptune π Men c. The formation rate and the energy spectrum of hydrogen atoms formed with an excess of kinetic energy due to the exothermic photochemistry forced by the stellar XUV radiation were calculated using a numerical kinetic Monte Carlo model of a hot planetary corona. The escape flux was estimated to be equal to 2.5×1012 cm−2s−1 for the mean level of stellar activity in the XUV radiation flux. This results in the mean estimate of the atmospheric loss rate due to the exothermic photochemistry equal to 6.7×108 g s−1. The calculated estimate is close to the observational estimates of the possible atmospheric loss rate for the exoplanet π Men c in the range less than 1.0×109 gs−1.

We describe a numerical model of hot Jupiter extended envelope that interacts with stellar wind. Our model is based on approximation of multi-component magnetic hydrodynamic. The processes of ionization, recombination, dissosiation and chemical reactions in hydrogen-helium envelope are taken into account. In particular, the ionization of neutral hydrogen atoms takes place due to processes of photo-ionization, charge-exchange and thermal collisions. Further, this model is supposed to be used for research on biomarkers’ dynamics in extended envelopes of hot Jupiters.

The detection of Earth-size exoplanets is a technological and data analysis challenge. Future progress in Earth-mass exoplanet detection is expected from the development of extreme precision radial velocity measurements. Increasing radial velocity precision requires developing a new physics-based data analysis methodology to discriminate planetary signals from host-star-related effects, taking stellar variability and instrumental uncertainties into account. In this work, we investigate and quantify stellar disturbances of the planet-hosting solar-type star HD121504 (G2V spectral type) from 3D radiative modeling obtained with the StellarBox code. The model has been used for determining statistical properties of the turbulent plasma and obtaining synthetic spectroscopic observations for several Fe I lines at different locations on the stellar disk to mimic high-resolution spectroscopic observations.

In this work we applied the previously developed self-consistent 1D model of hydrogen-helium atmosphere with suprathermal electrons to close-in hot neptune GJ 436 b. The obtained height profile of density shows the two-scale structure of the planetary atmosphere. The mass-loss rate is found to be about .

In this paper we have inferred the magnetic shielding characteristics and space weather hazards of selected potentially habitable extrasolar planets using a dynamical geophysical model from calculations of internal heat, phases of volcanism and planetary magnetic moments. The space weather hazards on the extrasolar planet Kepler-452b orbiting around a Sun-like star are found to be a minimum which enhances the habitability probability of this planet.

Accretion discs appear in many astrophysical systems. In most cases, these discs are probably not completely axisymmetric. Discs in binary systems are often found to be misaligned with respect to the binary orbit. In this case, the gravitational torque from a companion induces nodal precession in misaligned rings of gas. We first calculate whether this precession is strong enough to overcome the internal disc torques communicating angular momentum. For typical parameters, precession torque wins. To check this result, we perform numerical simulations using the Smoothed Particle Hydrodynamics code, PHANTOM, and confirm that sufficiently thin and sufficiently inclined discs can break into distinct planes that precess effectively independently. Disc tearing is widespread and severely changes the disc structure. It enhances dissipation and promotes stronger accretion onto the central object. We also perform a stability analysis on isolated warped discs to understand the physics of disc breaking and tearing observed in numerical simulations. The instability appears in the form of viscous anti-diffusion of the warp amplitude and the surface density. The discovery of disc breaking and tearing has revealed new physical processes that dramatically change the evolution of accretion discs, with obvious implications for observed systems.

The hot accretion flow around Kerr black holes is strongly magnetized. Magnetic field loops sustained by a surrounding accretion disk can close within the event horizon. We performed particle-in-cell simulations in Kerr metric to capture the dynamics of the electromagnetic field and of the ambient collisionless plasma in this coupled configuration. We find that a hybrid magnetic topology develops with a closed magnetosphere co-existing with open field lines threading the horizon reminiscent of the Blandford-Znajek solution. Further in the disk, highly inclined open magnetic field lines can launch a magnetically-driven wind. While the plasma is essentially force-free, a current sheet forms above the disk where magnetic reconnection produces macroscopic plasmoids and accelerates particles up to relativistic Lorentz factors. A highly dynamic Y-point forms on the furthest closed magnetic field line, with episodic reconnection events responsible for transient synchrotron emission and coronal heating.

Merger of binary neutron stars and black hole-neutron star binaries is the promising source of short-hard gamma-ray bursts, the most promising site for the r-process nucleosynthesis, and the source of kilonovae. To theoretically predict the merger and mass ejection processes and resulting electromagnetic emission, numerical simulation in full general relativity (numerical relativity) is the unique approach. We summarize our current understanding for the processes of neutron-star mergers and subsequent mass ejection based on the results of long-term numerical-relativity simulations. We pay particular attention to the electron fraction of the ejecta.

Based on our current high resolution direct N-body modelling of the Milky Way typical Star Cluster systems dynamical evolution we try to numerically estimate the influence of individual spin values and orientations on gravitational wave (GW) waveforms and observed time-frequency maps during multiple cycles for binary black hole (BBH) mergers. In our up to date N-body dynamical simulations we use the high order relativistic post-Newtonian corrections for the BH binary particles (3.5 post-Newtonian (PN) terms including spin-spin and spin-orbit terms). In the current work, we present the GW waveforms catalogue which covers the large parameter space in mass ratios 0.05 - 0.82 and extreme possible individual spin cases.

The load imbalance and communication overhead of parallel computing are crucial bottlenecks for galaxy simulations. A successful way to improve the scalability of astronomical simulations is a Hamiltonian splitting method, which needs to identify such regions integrated with smaller timesteps than the global timestep for integrating the entire galaxy. In the case of galaxy simulations, the regions inside supernova (SN) shells require the smallest steps. We developed the deep learning model to forecast the region affected by the SN shell’s expansion during one global step. In addition, we identified the particles with small timesteps using image processing. We can identify target particles using our method with a higher identification rate (88 % to 98 % on average) and lower “non-target”-to-“target” fraction (6.4 to 5.5 on average) compared to the analytic approach with the Sedov-Taylor solution. Our method using Hamiltonian splitting and deep learning will improve the performance of extremely high-resolution galaxy simulations.

Motivated by their role as the direct or indirect source of many of the elements in the Universe, numerical modeling of core collapse supernovae began more than five decades ago. Progress toward ascertaining the explosion mechanism(s) has been realized through increasingly sophisticated models, as physics and dimensionality have been added, as physics and numerical modeling have improved, and as the leading computational resources available to modelers have become far more capable. The past five to ten years have witnessed the emergence of a consensus across the core collapse supernova modeling community that had not existed in the four decades prior. For the majority of progenitors – i.e., slowly rotating progenitors – the efficacy of the delayed shock mechanism, where the stalled supernova shock wave is revived by neutrino heating by neutrinos emanating from the proto-neutron star, has been demonstrated by all core collapse supernova modeling groups, across progenitor mass and metallicity. With this momentum, and now with a far deeper understanding of the dynamics of these events, the path forward is clear. While much progress has been made, much work remains to be done, but at this time we have every reason to be optimistic we are on track to answer one of the most important outstanding questions in astrophysics: How do massive stars end their lives?