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Low-density plasmas are characterized by a large-scale separation between the gyromotion of particles around local magnetic fields and the macroscopic scales of the system, often making global kinetic simulations computationally intractable. The guiding center formalism has been proposed as a powerful tool to bridge the gap between these scales. Despite its usefulness, the guiding center approach has been formulated successfully only in flat spacetimes, limiting its applicability in astrophysical settings. Here, we present a new covariant formalism that leads to kinetic equations in the guiding center limit that are valid in arbitrary spacetimes. Through a variety of experiments, we demonstrate that our equations capture all known gyrocenter drifts while overcoming one severe limitation imposed on numerical algorithms by the fast timescales of the particle gyromotion. This formalism will enable explorations of a variety of global plasma kinetic phenomena in the curved spacetimes around black holes and neutron stars.

 

In the collisionless plasmas of radiatively inefficient accretion flows, heating and acceleration of ions and electrons are not well understood. Recent studies in the gyrokinetic limit revealed the importance of incorporating both the compressive and Alfvénic cascades when calculating the partition of dissipated energy between the plasma species. In this paper, we use a covariant analytic model of the accretion flow to explore the impact of compressive and Alfvénic heating, Coulomb collisions, compressional heating, and radiative cooling on the radial temperature profiles of ions and electrons. We show that, independent of the partition of heat between the plasma species, even a small fraction of turbulent energy dissipated to the electrons makes their temperature scale with a virial profile and the ion-to-electron temperature ratio smaller than in the case of pure Coulomb heating. In contrast, the presence of compressive cascades makes this ratio larger because compressive turbulent energy is channeled primarily into the ions. We calculate the ion-to-electron temperature in the inner accretion flow for a broad range of plasma properties, mass accretion rates, and black hole spins and show that it ranges between 5 ≲T_i/T_e≲ 40. We provide a physically motivated expression for this ratio that can be used to calculate observables from simulations of black hole accretion flows for a wide range of conditions.

 

Observations of the S stars, the cluster of young stars in the inner 0.1 pc of the Galactic center, have been crucial in providing conclusive evidence for a supermassive black hole at the center of our galaxy. Since some of the stars have orbits less than that of a typical human lifetime, it is possible to observe multiple orbits and test the weak-field regime of general relativity. Current calculations of orbits require relatively slow and expensive computations in order to perform numerical integrations for the position and momentum of each star at each observing time. In this paper, we present a computationally efficient, first-order post-Newtonian model for the astrometric and spectroscopic data gathered for the S stars. We find that future, 30 m class telescopes—and potentially even current large telescopes with very high spectroscopic resolution—may be able to detect the Shapiro effect for an S star in the next decade or so.

 

We present a new reconstruction of the Event Horizon Telescope (EHT) image of the M87 black hole from the 2017 data set. We usePRIMO, a novel dictionary-learning-based algorithm that uses high-fidelity simulations of accreting black holes as a training set. By learning the correlations between the different regions of the space of interferometric data, this approach allows us to recover high-fidelity images even in the presence of sparse coverage and reach the nominal resolution of the EHT array. The black hole image comprises a thin bright ring with a diameter of 41.5 ± 0.6μas and a fractional width that is at least a factor of 2 smaller than previously reported. This improvement has important implications for measuring the mass of the central black hole in M87 based on the EHT images.

 

The sparse interferometric coverage of the Event Horizon Telescope (EHT) poses a significant challenge for both reconstruction and model fitting of black hole images.PRIMOis a new principal components analysis-based algorithm for image reconstruction that uses the results of high-fidelity general relativistic, magnetohydrodynamic simulations of low-luminosity accretion flows as a training set. This allows the reconstruction of images that are consistent with the interferometric data and that live in the space of images that is spanned by the simulations.PRIMOfollows Monte Carlo Markov Chains to fit a linear combination of principal components derived from an ensemble of simulated images to interferometric data. We show thatPRIMOcan efficiently and accurately reconstruct synthetic EHT data sets for several simulated images, even when the simulation parameters are significantly different from those of the image ensemble that was used to generate the principal components. The resulting reconstructions achieve resolution that is consistent with the performance of the array and do not introduce significant biases in image features such as the diameter of the ring of emission.

 

The horizon-scale images of black holes obtained with the Event Horizon Telescope have provided new probes of their metrics and tests of general relativity. The images are characterized by a bright, near-circular ring from the gravitationally lensed emission from the hot plasma and a deep central depression cast by the black hole. The metric tests rely on the fact that the bright ring closely traces the boundary of the black hole shadow with a small displacement that has been quantified using simulations. In this paper we develop a self-consistent covariant analytic model of the accretion flow that spans a broad range of plasma conditions and black hole properties to explore the general validity of this result. We show that, for any physical model of the accretion flow, the ring always encompasses the outline of the shadow and is not displaced by it by more than half the ring width. This result is a consequence of conservation laws and basic thermodynamic considerations and does not depend on the microphysics of the plasma or the details of the numerical simulations. We also present a quantitative measurement of the bias between the bright ring and the shadow radius based on the analytical models.

 

The Event Horizon Telescope recently captured images of the supermassive black hole in the center of the M87 galaxy, which shows a ring-like emission structure with the south side only slightly brighter than the north side. This relatively weak asymmetry in the brightness profile along the ring has been interpreted as a consequence of the low inclination of the observer (around 17° for M87), which suppresses the Doppler beaming and boosting effects that might otherwise be expected due to the nearly relativistic velocities of the orbiting plasma. In this work, we use a large suite of general relativistic magnetohydrodynamic simulations to reassess the validity of this argument. By constructing explicit counterexamples, we show that low inclination is a sufficient but not necessary condition for images to have low brightness asymmetry. Accretion flow models with high accumulated magnetic flux close to the black hole horizon (the so-called magnetically arrested disks) and low black hole spins have angular velocities that are substantially smaller than the orbital velocities of test particles at the same location. As a result, such models can produce images with low brightness asymmetry even when viewed edge on.

 

Abstract We introduce a new Markov Chain Monte Carlo (MCMC) algorithm with parallel tempering for fitting theoretical models of horizon-scale images of black holes to the interferometric data from the Event Horizon Telescope (EHT). The algorithm implements forms of the noise distribution in the data that are accurate for all signal-to-noise ratios. In addition to being trivially parallelizable, the algorithm is optimized for high performance, achieving 1 million MCMC chain steps in under 20 s on a single processor. We use synthetic data for the 2017 EHT coverage of M87 that are generated based on analytic as well as General Relativistic Magnetohydrodynamic (GRMHD) model images to explore several potential sources of biases in fitting models to sparse interferometric data. We demonstrate that a very small number of data points that lie near salient features of the interferometric data exert disproportionate influence on the inferred model parameters. We also show that the preferred orientations of the EHT baselines introduce significant biases in the inference of the orientation of the model images. Finally, we discuss strategies that help identify the presence and severity of such biases in realistic applications.