Constraints on jet formation mechanisms with the most energetic giant outbursts in MS 0735+7421

Giant X-ray cavities lie in some active galactic nuclei (AGNs) locating in central galaxies of clusters, most of these cavities are thought to be inflated by jets of AGNs. The jets can be either powered by rotating black holes or the accretion disks surrounding black holes, or both. In this work, we choose the most energetic cavity, MS 0735+7421, with stored energy ~ 10^62 erg, to constrain the jet formation mechanisms and the evolution of the central massive black hole in this source. The bolometric luminosity of the AGN in this cavity is ~ 10^(-5) L_Edd, however, the mean power of the jet required to inflate the cavity is estimated as ~ 0.02 L_Edd, which implies that the source has experienced strong outbursts previously. During outbursts, the jet power and the mass accretion rate should be significantly higher than its present values. We construct an accretion disk model, in which the angular momentum and energy carried away by jets is properly included, to calculate the spin and mass evolution of the massive black hole. In our calculations, different jet formation mechanisms are employed, and we find that the jets generated with the Blandford-Znajek (BZ) mechanism are unable to produce the giant cavity with ~ 10^62 erg in this source. Only the jets accelerated with the combination of the Blandford-Payne (BP) and BZ mechanisms can successfully inflate such a giant cavity, if the magnetic pressure is close to equipartition with the total (radiation+gas) pressure of the accretion disk. For dynamo generated magnetic field in the disk, such an energetic giant cavity can be inflated by the magnetically driven jets only if the initial black hole spin parameter a_0 > 0.95. Our calculations show that the final spin parameter a of the black hole is always ~ 0:9 - 0.998 for all the computational examples which can provide sufficient energy for the cavity of MS 0735+7421.Comment: 25 pages, 8 figures, accepted by Ap

A strong negative correlation between radio loudness RUVR_{\rm UV} and optical-to-X-ray spectral index αox\alpha_{\rm ox} in low-luminosity AGNs

It has been argued for years that the accretion mode changes from bright active galactic nuclei (AGNs) to low-luminosity AGNs (LLAGNs) at a rough dividing point of bolometric Eddington ratio $\lambda \sim 10^{-2}$. In this work, we strengthen this scenario through investigation of the relationship between the radio loudness $R_{\rm UV}$ and the optical-to-X-ray spectral index $\alpha_{\rm ox}$ in LLAGNs with $10^{-6} \lesssim \lambda \lesssim 10^{-3}$. We compile from literature a sample of 32 LLAGNs, consisting 18 LINERs and 14 low Eddington ratio Seyfert galaxies, and observe a strong negative $R_{\rm UV}$--$\alpha_{\rm ox}$ relationship, with large scatter in both $R_{\rm UV}$ and $\alpha_{\rm ox}$. We further demonstrate that this negative correlation, and the additional two negative relationships reported in literature ($R_{\rm UV}$--$\lambda$ and $\alpha_{\rm ox}$--$\lambda$ correlations), can be understood consistently and comprehensively under the truncated accretion--jet model, the model that has been applied successfully applied to LLAGNs. We argue that the scatter in the observations are (mainly) due to the spread in the viscosity parameter $\alpha$ of a hot accretion flow, a parameter that potentially can serve as a diagnose of the strength and/or configuration of magnetic fields in accretion flows.Comment: 8 pages, 3 figures, 2 tables. Accepted by MNRA

Stochastic pole expansion method

In this paper, we propose a new analytic continuation method to extract real frequency spectral functions from imaginary frequency Green's functions of quantum many-body systems. This method is based on the pole representation of Matsubara Green's function and a stochastic sampling procedure is utilized to optimize the amplitudes and locations of poles. In order to capture narrow peaks and sharp band edges in the spectral functions, a constrained sampling algorithm and a self-adaptive sampling algorithm are developed. To demonstrate the usefulness and performance of the new method, we at first apply it to study the spectral functions of representative fermionic and bosonic correlators. Then we employ this method to tackle the analytic continuation problems of matrix-valued Green's functions. The synthetic Green's functions, as well as realistic correlation functions from finite temperature quantum many-body calculations, are used as input. The benchmark results demonstrate that this method is capable of reproducing most of the key characteristics in the spectral functions. The sharp, smooth, and multi-peak features in both low-frequency and high-frequency regions of spectral functions could be accurately resolved, which overcomes one of the main limitations of the traditional maximum entropy method. More importantly, it exhibits excellent robustness with respect to noisy and incomplete input data. The causality of spectral function is always satisfied even in the presence of sizable noises. As a byproduct, this method could derive a fitting formula for the Matsubara data, which provides a compact approximation to the many-body Green's functions. Hence, we expect that this new method could become a pivotal workhorse for numerically analytic continuation and be broadly useful in many applications.Comment: 26 pages, 20 figure

Reconstructing lattice QCD spectral functions with stochastic pole expansion and Nevanlinna analytic continuation

The reconstruction of spectral functions from Euclidean correlation functions is a well-known, yet ill-posed inverse problem in the fields of many-body and high-energy physics. In this paper, we present a comprehensive investigation of two recently developed analytic continuation methods, namely stochastic pole expansion and Nevanlinna analytic continuation, for extracting spectral functions from mock lattice QCD data. We examine a range of Euclidean correlation functions generated by representative models, including the Breit-Wigner model, the Gaussian mixture model, the resonance-continuum model, and the bottomonium model. Our findings demonstrate that the stochastic pole expansion method, when combined with the constrained sampling algorithm and the self-adaptive sampling algorithm, successfully recovers the essential features of the spectral functions and exhibits excellent resilience to noise of input data. In contrast, the Nevanlinna analytic continuation method suffers from numerical instability, often resulting in the emergence of spurious peaks and significant oscillations in the high-energy regions of the spectral functions, even with the application of the Hardy basis function optimization algorithm.Comment: 14 pages, 8 figure