Differential rotation in neutron stars allows for significantly larger masses than rigid rotation. Some of those hypermassive objects are, however, unstable and collapse to a black hole immediately after formation. Yet, the exact threshold of dynamical stability is still unknown.

In our work we explore the limits on masses of neutron stars with various degrees of differential rotation which could be stable against a prompt collapse to a black hole by using turning-point (j-constant) criterion. We considered both spheroidal and quasi-toroidal differentially rotating neutron stars described by the polytropic equation of state. We find that massive configurations could be temporarily stabilized by differential rotation. Such objects are important sources of gravitational waves. Our results are a starting point for more detailed studies of stability using hydrodynamical codes.

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.

The Radio Neutrino Observatory Greenland (RNO-G) is currently being deployed and it is currently gathering data. As a precursor and complementary detector to the future radio array of IceCube-Gen2 in Antarctica, it will explore mainly the Northern sky via in-ice radio detection technique. The total array configuration includes 35 radio stations and will be fully completed within three years from now. The antennas will register the radio signals produced by the Askaryan effect in cascades generated in ice by neutrinos. RNO-G’s scientific purpose is to detect UHE neutrinos at energies above 10 PeV. Due to the attenuation length of radio waves in ice (order of 1 km) the radio detection allows to address neutrino energies above several PeV. The detector will reach unprecedented sensitivity in the scale from tens of PeV up to EeV. Models predict GRBs induced by binary neutron star mergers as likely transient sources of such highly energetic neutrinos. The current study of NS-NS mergers will therefore possibly be complemented by future RNO-G detections through multimessenger temporal and spatial coincidence, including an alert system. In this presentation, we will describe the instrument capabilities and explore the possibility of detection of such sources with RNO-G.

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 this paper I present a method to enhance the search sensitivity for long transient Gravitational Waves produced by Neutron Star instabilities. This method consists in a selective image filter, called Triangular Filter, to be applied to data spectrograms. It is shown that thanks to this implementation a ∼20% gain in sensitivity is achievable.

The binary neutron star merger gravitational-wave event GW170817 and observations of the subsequent electromagnetic signals at different wavelengths have helped better understand the outflows that follow these mergers. In particular, the off-axis afterglow of the jetted ejecta has allowed to probe the lateral structure of such jets, especially thanks to VLBI imagery of the source. In this work, we model this afterglow including a decelerating jet with lateral structure, while synchrotron emission and synchrotron self-Compton scatterings power the jet radiation. In particular, we extend our analysis to very high energies and predict the light curve in the energy range of H.E.S.S. and the CTA. We finally discuss how future detections of afterglows by these observatories can help break the degeneracies in some key physical parameter measurements, and allow to probe efficiently a sub-population of fast-merging binaries.

During the late stages of a neutron star binary inspiral finite-size effects come into play, with the tidal deformability of the supranuclear density matter leaving an imprint on the gravitational-wave signal. As demonstrated in the case of GW170817—the first direct detection of gravitational waves from a neutron star binary—this can lead to strong constraints on the neutron star equation of state. As detectors become more sensitive, effects which may have a smaller influence on the neutron star tidal deformability need to be taken into consideration. Dynamical effects, such as oscillation mode resonances triggered by the orbital motion, have been shown to contribute to the tidal deformability, especially close to the neutron star coalesence. We calculate the contribution of the various stellar oscillation modes to the tidal deformability and demonstrate the (anticipated) dominance of the fundamental mode, showing what the impact of the matter composition is on the tidal deformability.

The magnetar SGR J1830–0645 was discovered in outburst in October 2020. We studied its X-ray properties during the first month of the outburst using XMM–Newton, NuSTAR and Swift observations. The shape and amplitude of the pulse profile varied significantly with energy. The broadband spectrum was well described using two absorbed blackbody components plus a faint power law component at high energies. Phase-resolved spectral analysis of the data suggests that the emission could be attributed to thermal photons from a single heated region with a complex shape on the star surface undergoing resonant Compton scattering on charged particles located in the magnetosphere. Modelling the evolutionary path of the magnetar with our magneto-thermal evolutionary codes indicates that SGR J1830 was born ≈23 kyr ago with a dipolar magnetic field of ∼1015 G, slightly larger than the current value.

The Bisous model is a tool that uses stochastic methods to detect the network of galactic filaments. This model is explicitly developed to detect the structure from observational data, using only galaxy positions as input. This paper shows that the Bisous model gives reliable results and including photometric data improves the resulting filamentary network. We used MultiDark-Galaxies catalogue to create a mock with photometric redshifts and samples with different galaxy number densities. We found that the filaments detected with the Bisous model are reliable; 85% of the detected filaments are unchanged compared to results with more complete input data. Adding photometric data improves the fraction of galaxies in filaments. Using the confusion matrix technique, we found the false discovery rate to always be below 5% when using photometric data.

The convection-enhanced neutrino-driven supernova engine’s success in explaining a myriad of supernova properties has set it as the standard engine behind supernova. However, due to the success of rotationally-powered engines in explaining astrophysical transients like gamma-ray bursts, these engines have been revived as possible drivers of normal supernovae, competing with this standard engine. In this paper, these competing engines, and the constraints placed by compact remnant observations on these engines, are reviewed. We find that, with these constraints, such rotationally-powered engines can explain less than 1% of the current supernova remnants. In addition, we find that the remnant mass distribution can be used to constrain properties of the convection-enhanced neutrino-driven engine, helping astronomers understand the nature of convection in this engine.

One of the models explaining the high luminosity of pulsing ultra-luminous X-ray sources (pULXs) was suggested by Mushtukov et al. (2015). They showed that the accretion columns on the surfaces of highly magnetized neutron stars can be very luminous due to opacity reduction in the high magnetic field. However, a strong magnetic field leads also to amplification of the electron-positron pairs creation. Therefore, increasing of the electron and positron number densities compensates the cross-section reduction, and the electron scattering opacity does not decrease with the magnetic field magnification. As a result, the maximum possible luminosity of the accretion column does not increase with the magnetic field. It ranges between 1040 − 1041 erg s−1 depending only slightly on the magnetic field strength.

We argue that measurements of X-ray polarization using the recently launched Imaging X-ray Polarimetry Explorer will answer many open questions about magnetars in particular the physical state of their surfaces, whether vacuum birefringence exists, and the nature of the hard X-ray emission from these objects. We outline the capabilities of the instrument, specific models and the results of simulations for the magnetar 4U 0142+61.

We present Ekster, a new method for simulating the formation and dynamics of individual stars in a relatively low-resolution gas background. Here, we use Ekster to simulate star cluster formation in two different regions from each of two galaxy models with different spiral potentials. We simulate these regions for 3 Myr to study where and how star clusters form. We find that massive GMC regions form more massive clusters than sections of spiral arms. Additionally we find that clusters form both by accreting gas and by merging with other proto-clusters, the latter happening more frequently in the denser GMC regions.

There are indications that the magnetic field evolution in galaxies might be massively shaped by tidal interactions and mergers between galaxies. The details of the connection between the evolution of magnetic fields and that of their host galaxies is still a field of research.

We use a combined approach of magnetohydrodynamics for the baryons and an N-body scheme for the dark matter to investigate magnetic field amplification and evolution in interacting galaxies.

We find that, for two colliding equal-mass galaxies and for varying initial relative spatial orientations, magnetic fields are amplified during interactions, yet cannot be sustained. Furthermore, we find clues for an active mean-field dynamo.

In recent years, an increasing amount of attention is being paid to the gravitational few-body problem and its applications to astrophysical scenarios. Among the main reasons for this renewed interest there is large number of newly discovered exoplanets and the detection of gravitational waves. Here, we present two numerical codes to model three- and few-body systems, called tsunami and okinami. The tsunami code is a direct few-body code with algorithmic regularization, tidal forces and post-Newtonian corrections. okinami is a secular, double-averaged code for stable hierarchical triples. We describe the main methods implemented in our codes, and review our recent results and applications to gravitational-wave astronomy, planetary science and statistical escape theories.

The LIGO-Virgo gravitational wave detectors have confidently observed 4 events involving neutron stars: two binary neutron star (BNS) mergers (GW170817 and GW190425), and two neutron star-black hole mergers (GW200105 and GW200115). However, our theoretical understanding of the remnant properties of such systems is incomplete due to the complexities related to the modeling of matter effects and the very high computational cost of corresponding numerical relativity simulations. An important such property is the recoil velocity, which is imparted onto the remnant due to the anisotropic emission of gravitational radiation and the dynamical ejection of matter in the kilonova. In this work, we combine gravitational radiation as well as dynamical ejecta distributions, computed by the Computational Relativity numerical simulations, to get accurate estimates for BNS remnant recoil velocities. We find that recoils due to ejection of matter dominate those caused by gravitational wave emission. Knowledge of BNS remnant recoil velocities is important in determining if the remnant is retained by its environment for future hierarchical mergers which, in turn, can form binaries with black holes in the so-called lower mass gap of ∼ 3 – 5M⊙.

Einstein Telescope (ET), a the future third generation gravitational wave detector will be sensitive to gravitational wave signal down to 1 Hz. We present an algorithm to estimate the parameters of the low mass merging compact binary systems such as localisation, chirp mass, redshift, mass ratios and total mass of the source which are crucial in order to estimate the capability of ET to study various compact binary populations. We analysed the compact binary populations of (i) Pop I and Pop II, (ii) Pop III, and (iii) globular clusters, with single ET.

T Tauri Stars (TTSs) offer a unique chance to study the physics of non-relativistic accretion engines. In this invited talk, the current status of the field is presented with special emphasis on the predictive power of the numerical simulation of magnetospheric accretion and close binary systems and its impact on astronomical observations.

Computational fluid dynamics is a crucial tool to theoretically explore the cosmos. In the last decade, we have seen a substantial methodological diversification with a number of cross-fertilizations between originally different methods. Here we focus on recent developments related to the Smoothed Particle Hydrodynamics (SPH) method. We briefly summarize recent technical improvements in the SPH-approach itself, including smoothing kernels, gradient calculations and dissipation steering. These elements have been implemented in the Newtonian high-accuracy SPH code MAGMA2 and we demonstrate its performance in a number of challenging benchmark tests. Taking it one step further, we have used these new ingredients also in the first particle-based, general-relativistic fluid dynamics code that solves the full set of Einstein equations, SPHINCS_BSSN. We present the basic ideas and equations and demonstrate the code performance at examples of relativistic neutron stars that are evolved self-consistently together with the spacetime.

We present a new algorithm to solve the equations of radiation hydrodynamics (RHD) in a frequency-integrated, two-moment formulation. Novel features of the algorithm include i) the adoption of a non-local Variable Eddington Tensor (VET) closure for the radiation moment equations, computed with a ray-tracing method, ii) support for adaptive mesh refinement (AMR), iii) use of a time-implicit Godunov method for the hyperbolic transport of radiation, and iv) a fixed-point Picard iteration scheme to accurately handle the stiff nonlinear gas-radiation energy exchange. Tests demonstrate that our scheme works correctly, yields accurate rates of energy and momentum transfer between gas and radiation, and obtains the correct radiation field distribution even in situations where more commonly used – but less accurate – closure relations like the Flux-limited Diffusion and Moment-1 approximations fail. Our scheme presents an important step towards performing RHD simulations with increasing spatial and directional accuracy, effectively improving their predictive capabilities.