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We develop and use a novel mixed-precision weighted essentially non-oscillatory (WENO) method for solving the Teukolsky equation, which arises when modeling perturbations of Kerr black holes. We show that WENO methods outperform higher-order finite-difference methods, standard in the discretization of the Teukolsky equation, due to the need to add dissipation for stability purposes in the latter. In particular, as the WENO scheme uses no additional dissipation it is well-suited for scenarios requiring long-time evolution such as the study of Price tails and gravitational wave emission from extreme mass ratio binaries. In the mixed-precision approach, the expensive computation of the WENO weights is performed in reduced floating-point precision that results in a significant speedup factor of 3.3. In addition, we use state-of-the-art Nvidia general-purpose graphics processing units and cluster parallelism to further accelerate the WENO computations. Our optimized WENO solver can be used to quickly generate accurate results of significance in the field of black hole and gravitational wave physics. We apply our solver to study the behavior of the Aretakis charge -- a conserved quantity, that if detected by a gravitational wave observatory like LIGO/Virgo would prove the existence of extremal black holes.
It has recently been suggested that the presence of a plenitude of light axions, an Axiverse, is evidence for the extra dimensions of string theory. We discuss the observational consequences of these axions on astrophysical black holes through the Penrose superradiance process. When an axion Compton wavelength is comparable to the size of a black hole, the axion binds to the black hole nucleus forming a gravitational atom in the sky. The occupation number of superradiant atomic levels, fed by the energy and angular momentum of the black hole, grows exponentially. The black hole spins down and an axion Bose-Einstein condensate cloud forms around it. When the attractive axion self-interactions become stronger than the gravitational binding energy, the axion cloud collapses, a phenomenon known in condensed matter physics as Bosenova. The existence of axions is first diagnosed by gaps in the mass vs spin plot of astrophysical black holes. For young black holes the allowed values of spin are quantized, giving rise to Regge trajectories inside the gap region. The axion cloud can also be observed directly either through precision mapping of the near horizon geometry or through gravitational waves coming from the Bosenova explosion, as well as axion transitions and annihilations in the gravitational atom. Our estimates suggest that these signals are detectable in upcoming experiments, such as Advanced LIGO, AGIS, and LISA. Current black hole spin measurements imply an upper bound on the QCD axion decay constant of 2 x 10^17 GeV, while Advanced LIGO can detect signals from a QCD axion cloud with a decay constant as low as the GUT scale. We finally discuss the possibility of observing the gamma-rays associated with the Bosenova explosion and, perhaps, the radio waves from axion-to-photon conversion for the QCD axion.
We consider several methods for generating initial guesses when iteratively solving sequences of linear systems, showing that they can be implemented efficiently in GPU-accelerated PDE solvers, specifically solvers for incompressible flow. We propose new initial guess methods based on stabilized polynomial extrapolation and compare them to the projection method of Fischer [15], showing that they are generally competitive with projection schemes despite requiring only half the storage and performing considerably less data movement and communication. Our implementations of these algorithms are freely available as part of the libParanumal collection of GPU-accelerated flow solvers.
Gravitational-wave astronomy has the potential to substantially advance our knowledge of the cosmos, from the most powerful astrophysical engines to the initial stages of our universe. Gravitational waves also carry information about the nature of black holes. Here we investigate the potential of gravitational-wave detectors to test a proposal by Bekenstein and Mukhanov that the area of black hole horizons is quantized in units of the Planck area. Our results indicate that this quantization could have a potentially observable effect on the classical gravitational wave signals received by detectors. In particular, we find distorted gravitational-wave echoes in the post-merger waveform describing the inspiral and merger of two black holes. These echoes have a specific frequency content that is characteristic of black hole horizon area quantization.
In this paper, we study an adaptive planewave method for multiple eigenvalues of second-order elliptic partial equations. Inspired by the technique for the adaptive finite element analysis, we prove that the adaptive planewave method has the linear convergence rate and optimal complexity.
In this work we consider a mixed precision approach to accelerate the implemetation of multi-stage methods. We show that Runge-Kutta methods can be designed so that certain costly intermediate computations can be performed as a lower-precision computation without adversely impacting the accuracy of the overall solution. In particular, a properly designed Runge-Kutta method will damp out the errors committed in the initial stages. This is of particular interest when we consider implicit Runge-Kutta methods. In such cases, the implicit computation of the stage values can be considerably faster if the solution can be of lower precision (or, equivalently, have a lower tolerance). We provide a general theoretical additive framework for designing mixed precision Runge-Kutta methods, and use this framework to derive order conditions for such methods. Next, we show how using this approach allows us to leverage low precision computation of the implicit solver while retaining high precision in the overall method. We present the behavior of some mixed-precision implicit Runge-Kutta methods through numerical studies, and demonstrate how the numerical results match with the theoretical framework. This novel mixed-precision implicit Runge-Kutta framework opens the door to the design of many such methods.