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100 records · Page 6

The Distribution and Annihilation of Dark Matter Around Black Holes

We use a Monte Carlo code to calculate the geodesic orbits of test particles around Kerr black holes, generating a distribution function of both bound and unbound populations of dark matter (DM) particles. From this distribution function, we calculate annihilation rates and observable gamma-ray spectra for a few simple DM models. The features of these spectra are sensitive to the black hole spin, observer inclination, and detailed properties of the DM annihilation cross-section and density profile. Confirming earlier analytic work, we find that for rapidly spinning black holes, the collisional Penrose process can reach efficiencies exceeding 600%, leading to a high-energy tail in the annihilation spectrum. The high particle density and large proper volume of the region immediately surrounding the horizon ensures that the observed flux from these extreme events is non-negligible.

astroparticle physics↗

Electromagnetic Chirps from Neutron Star-Black Hole Mergers

We calculate the electromagnetic signal of a gamma-ray flare coming from the surface of a neutron star shortly before merger with a black hole companion. Using a new version of the Monte Carlo radiation transport code Pandurata that incorporates dynamic spacetimes, we integrate photon geodesics from the neutron star surface until they reach a distant observer or are captured by the black hole. The gamma-ray light curve is modulated by a number of relativistic effects, including Doppler beaming and gravitational lensing. Because the photons originate from the inspiraling neutron star, the light curve closely resembles the corresponding gravitational waveform: a chirp signal characterized by a steadily increasing frequency and amplitude. We propose to search for these electromagnetic chirps using matched filtering algorithms similar to those used in LIGO data analysis.

gamma-ray burst↗

On the Maximum Stellar Rotation to Form a Black Hole without an Accompanying Luminous Transient

The collapse of a massive star with low angular momentum content is commonly argued to result in the formation of a black hole without an accompanying bright transient. Our goal in this Letter is to understand the flow in and around a newly-formed black hole, involving accretion and rotation, via general relativistic hydrodynamics simulations aimed at studying the conditions under which infalling material can accrete without forming a centrifugally supported structure and, as a result, generate no effective feedback. If the feedback from the black hole is, on the other hand, significant, the collapse would be halted and we suggest that the event is likely to be followed by a bright transient. We find that feedback is only efficient if the specific angular momentum of the infalling material at the innermost stable circular orbit exceeds that of geodesic circular flow at that radius by at least≈20%. We use the results of our simulations to constrain the maximal stellar rotation rates of the disappearing massive progenitors PHL293B-LBV and N6946-BH1, and to provide an estimate of the overall rate of disappearing massive stars. We find that about a few percent of single O-type stars with measured rotational velocities are expected to spin below the critical value before collapse and are thus predicted to vanish without a trace.

Scott C Noble↗

Transient Resonances in EMRIs: A Scalar Toy Model

We present calculations of the scalar self-force for a scalar point-charge following different $r\theta$-resonant geodesics in Kerr spacetime. Using this scalar model, we present two methods for constructing the self-force for resonant sources using two different phase parameterizations of the point-particle motion. We relate these two methods via a simple shifting relation that holds for both the scalar and gravitational self-forces. We discuss how this shifting relation allows us to compare self-force results both at and away from resonances. Finally, we provide new evidence that conservative scalar perturbations can drive the leading-order evolution of the orbital dynamics during resonances (i.e., the orbit-averaged rate of change of the Carter constant depends on contributions from the conservative self-force). This evidence conflicts with a commonly assumed conjecture that these integrated conservative contributions should vanish during both resonant and non-resonant motion.

Zachary Nasipak↗

Geometric Acoustics for Aircraft Noise Scattering

This paper discusses aircraft noise scattering by geometric acoustics, which consists of the basic features of sound propagation and reflection in rays or ray tubes, diffraction by smooth geometry in terms of surface creeping waves, and diffraction by abrupt geometry features such as the wing trailing edges. Based on the classic theories of these features, prediction methodologies can be constructed for aircraft noise scattering. The methodologies, however, require important modifications and extensions to account for unique features in aircraft noise applications, for both current conventional aircraft and future unconventional designs. These modifications and extensions include the derivation of a general reflection coefficient that contains the effects of surface geometry curvature, surface impedance, and mean flow. Corrections to the basic formulation of diffraction, both smooth geometry and sharp edges, are formulated to account for the finite dimensions of practical applications. For smooth geometry diffraction, a second order correction is used to continuously transition from insolified to shadow zones and an approach is presented to compute the properties of the geodesic path of surface wave propagation. A model is developed to make use of the ray propagation formulation for incoherent and partially coherent propagation and scattering, which is an important phenomenon in aircraft noise. Mean flow effect is also included in the methodology for low Mach number flows. Examples of calculations based on these theoretical developments are presented to illustrate the unique features in aircraft noise applications.

Yueping Guo↗

Adiabatic Evolution Due to the Conservative Scalar Self-force During Orbital Resonances

We calculate the scalar self-force experienced by a scalar point-charge orbiting a Kerr black holealongrθ-resonant geodesics. We use the self-force to calculate the averaged rate of change of thecharge’s orbital energy⟨ ̇E⟩, angular momentum⟨ ̇Lz⟩, and Carter constant⟨ ̇Q⟩, which togethercapture the leading-order adiabatic, secular evolution of the point-charge. Away from resonances,only the dissipative (time antisymmetric) components of the self-force contribute to⟨ ̇E⟩,⟨ ̇Lz⟩, and⟨ ̇Q⟩. We demonstrate, using a new numerical code, that duringrθresonances conservative (timesymmetric) scalar perturbations also contribute to⟨ ̇Q⟩and, thus, help drive the adiabatic evolutionof the orbit. Furthermore, we observe that the relative impact of these conservative contributionsto⟨ ̇Q⟩is particularly strong for eccentric 2:3 resonances. These results provide the first conclusivenumerical evidence that conservative scalar perturbations of Kerr spacetime are nonintegrable duringrθresonances.

Zachary Nasipak↗

Nano-Newton Electrostatic Force Actuators for Femto-Newton-Sensitive Measurements: System Performance Test in the LISA Pathfinder Mission

Electrostatic force actuation is a key component of the system of geodesic reference test masses (TM) for the LISA orbiting gravitational wave observatory and in particular for performance at low frequencies, below 1 mHz, where the observatory sensitivity is limited by stray force noise. The system needs to apply forces of order 10 −9 N while limiting fluctuations in the measurement band to levels approaching 10 −15 N=Hz 1/2 . We present here the LISA actuation system design, based on audio-frequency voltage carrier signals, and results of its in-flight performance test with the LISA Pathfinder test mission. In LISA, TM force actuation is used to align the otherwise free-falling TM to the spacecraft-mounted optical metrology system, without any forcing along the critical gravitational wave-sensitive interferometry axes. In LISA Pathfinder, on the other hand, the actuation was used also to stabilize the TM along the critical x axis joining the two TM, with the commanded actuation force entering directly into the mission’s main differential acceleration science observable. The mission allowed demonstration of the full compatibility of the electrostatic actuation system with the LISA observatory requirements, including dedicated measurement campaigns to amplify, isolate, and quantify the two main force noise contributions from the actuation system, from actuator gain noise and from low frequency “in band” voltage fluctuations. These campaigns have shown actuation force noise to be a relevant, but not dominant, noise source in LISA Pathfinder and have allowed performance projections for the conditions expected in the LISA mission.

M. Armanos↗

Effective structural impact detection and localization using convolutional neural network and Bayesian information fusion with limited sensors

Due to their unpredictable nature, many impact events (e.g., overheight vehicles striking on bridges) go unnoticed or get reported many hours later. However, they can induce structural failures or hidden damage that accelerates the structure’s long-term degradation. Therefore, prompt impact detection and localization strategies are essential for early warning of impact events and rapid maintenance of structures. Most existing impact detection strategies are developed for aircraft composite panels utilizing high-rate synchronized measurement from densely deployed sensors. Limited efforts have been made for infrastructure or human habitats which generally require large-scale but low-rate measurement. In particular, due to harsh environments (e.g., deep space habitats under meteoroids), structural impact localization must be robust to limited sensors (e.g., sensor damage during impacts) and multi-source errors (e.g., measurement errors). In this study, an effective impact detection and localization strategy is proposed using a limited number of vibration measurements, especially in harsh environments (e.g. in deep space). Convolutional neural networks are trained for each sensor node and are fused using Bayesian theory to improve the accuracy of impact localization. Special considerations are paid to evaluate the effect of both measurement error and modeling error in the analysis. The proposed strategy is illustrated using 1D structure, and further validated in 3D geodesic dome structure numerically. The results demonstrate that it can detect and localize impact events accurately and robustly on structures.

Yuguang Fu↗

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Chengjia Han↗