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Vector resonant relaxation (VRR) is known to be the fastest gravitational process that shapes the geometry of stellar orbits in nuclear star clusters. This leads to the realignment of the orbital planes on the corresponding VRR time scale $t_{\rm VRR}$ of a few million years, while the eccentricity $e$ and semimajor axis $a$ of the individual orbits are approximately conserved. The distribution of orbital inclinations reaches an internal equilibrium characterised by two conserved quantities, the total potential energy among stellar orbits, $E_{\rm tot}$, and the total angular momentum, $L_{\rm tot}$. On timescales longer than $t_\mathrm{VRR}$, the eccentricities and semimajor axes change slowly and the distribution of orbital inclinations are expected to evolve through a series of VRR equilibria. Using a Monte Carlo Markov Chain method, we determine the equilibrium distribution of orbital inclinations in the microcanonical ensemble with fixed $E_{\rm tot}$ and $L_{\rm tot}$ for isolated nuclear star clusters with a power-law distribution of $a$, $e$, and $m$, where $m$ is the stellar mass. We explore the possible equilibria for $9$ representative $E_{\rm tot}$--$L_{\rm tot}$ pairs that cover the possible parameter space. For all cases, the equilibria show anisotropic mass segregation where the distribution of more massive objects is more flattened than that for lighter objects. Given that stellar black holes are more massive than the average main sequence stars, these findings suggest that black holes reside in disc-like structures within nuclear star clusters for a wide range of initial conditions., Comment: 11 pages, 7 figures, submitted to MNRAS

It is challenging, yet important, to measure the - ever-changing - cold electron density in the plasmasphere. The cold electron density inside and outside of the plasmapause is a key parameter for radiation belt dynamics. One indirect measurement is through finding the velocity dispersion relation exhibited by lightning induced whistlers. The main difficulty of the method comes from low signal-to-noise ratios for most of the ground-based whistler components. To provide accurate electron density and L-shell measurements, whistler components need to be detectable in the noisy background, and their characteristics need to be reliably determined. For this reason precise segmentation is needed on a spectrogram image. Here we present a fully automated way to perform such an image segmentation by leveraging the power of convolutional neural networks, a state-of-the-art method for computer vision tasks. Testing the proposed method against a manually, and semi-manually segmented whistler dataset achieved <10% relative electron density prediction error for 80% of the segmented whistler traces, while for the L-shell, the relative error is <5% for 90% of the cases. By segmenting more than 1 million additional real whistler traces from Rothera station Antarctica, logged over 9 years, seasonal changes in the average electron density were found. The variations match previously published findings, and confirm the capabilities of the image segmentation technique.

Vector resonant relaxation (VRR) is known to be the fastest gravitational process that shapes the geometry of stellar orbits in nuclear star clusters. This leads to the realignment of the orbital planes on the corresponding VRR time scale $t_{\rm VRR}$ of a few million years, while the eccentricity $e$ and semimajor axis $a$ of the individual orbits are approximately conserved. The distribution of orbital inclinations reaches an internal equilibrium characterised by two conserved quantities, the total potential energy among stellar orbits, $E_{\rm tot}$, and the total angular momentum, $L_{\rm tot}$. On timescales longer than $t_\mathrm{VRR}$, the eccentricities and semimajor axes change slowly and the distribution of orbital inclinations are expected to evolve through a series of VRR equilibria. Using a Monte Carlo Markov Chain method, we determine the equilibrium distribution of orbital inclinations in the microcanonical ensemble with fixed $E_{\rm tot}$ and $L_{\rm tot}$ for isolated nuclear star clusters with a power-law distribution of $a$, $e$, and $m$, where $m$ is the stellar mass. We explore the possible equilibria for $9$ representative $E_{\rm tot}$--$L_{\rm tot}$ pairs that cover the possible parameter space. For all cases, the equilibria show anisotropic mass segregation where the distribution of more massive objects is more flattened than that for lighter objects. Given that stellar black holes are more massive than the average main sequence stars, these findings suggest that black holes reside in disc-like structures within nuclear star clusters for a wide range of initial conditions., Comment: Version accepted for publication in MNRAS

It is challenging, yet important, to measure the - ever-changing - cold electron density in the plasmasphere. The cold electron density inside and outside of the plasmapause is a key parameter for radiation belt dynamics. One indirect measurement is through finding the velocity dispersion relation exhibited by lightning induced whistlers. The main difficulty of the method comes from low signal-to-noise ratios for most of the ground-based whistler components. To provide accurate electron density and L-shell measurements, whistler components need to be detectable in the noisy background, and their characteristics need to be reliably determined. For this reason precise segmentation is needed on a spectrogram image. Here we present a fully automated way to perform such an image segmentation by leveraging the power of convolutional neural networks, a state-of-the-art method for computer vision tasks. Testing the proposed method against a manually, and semi-manually segmented whistler dataset achieved <10% relative electron density prediction error for 80% of the segmented whistler traces, while for the L-shell, the relative error is <5% for 90% of the cases. By segmenting more than 1 million additional real whistler traces from Rothera station Antarctica, logged over 9 years, seasonal changes in the average electron density were found. The variations match previously published findings, and confirm the capabilities of the image segmentation technique.

We investigate the dynamical evolution of an intermediate-mass black hole (IMBH) in a nuclear star cluster hosting a supermassive black hole (SMBH) and both a spherical and a flattened disk-like distribution of stellar-mass objects. We use a direct N-body (phiGPU) and an orbit-averaged (N-ring) numerical integrator to simulate the orbital evolution of stars and the IMBH. We find that the IMBH's orbit gradually aligns with the stellar disk if their mutual initial inclination is less than 90 degree. If it is larger than 90 degree, i.e. counterrotating, the IMBH does not align. Initially, the rate of orbital reorientation increases linearly with the ratio of the mass of the IMBH over the SMBH mass and it is orders of magnitude faster than ordinary (i.e. Chandrasekhar) dynamical friction, particularly for high SMBH masses. The semimajor axes of the IMBH and the stars are approximately conserved. This suggests that the alignment is predominantly driven by orbit-averaged gravitational torques of the stars, a process which may be called resonant dynamical friction. The stellar disk is warped by the IMBH, and ultimately increases its thickness. This process may offer a test for the viability of IMBH candidates in the Galactic Center. Resonant dynamical friction is not limited to IMBHs; any object much more massive than disk particles may ultimately align with the disk. This may have implications for the formation and evolution of black hole disks in dense stellar systems and gravitational wave source populations for LIGO, VIRGO, KAGRA, and LISA., Comment: 19 pages, 14 figures, 1 video, accepted by ApJ