arXiv subjects

Bocheng Zhu

Publications and source records attributed to Bocheng Zhu.

22 records · Page 2Linked to original sources

arXiv2020

Gas flows in an Active galactic nuclei. I. Two-phase gas inflow

We perform two-dimensional hydrodynamic simulations to study the non-rotating gas flow in the region from 1-1000 parsec. This region connects the galaxy scale and the accretion disk scale. The gas is irradiated by the photons generated by the accretion disk system near the central black hole with $10^8$ solar mass. We assume that the luminosity of the central accretion system is constant and equals to $0.3$ Eddington luminosity. Gas with density higher than $10^{-24} {\rm g \ cm^{-3}}$ is found to be thermally unstable. Two phase, cold and hot, gas flow will form due to thermal instability. We calculated the ratio of cold gas accretion rate to hot gas accretion rate. This ratio is a function of gas density and generally increases with the increase of gas density. The maximum value of this ratio is $16$, when gas density is $10^{-21} {\rm g \ cm^{-3}} $. Gas with density lower than $10^{-24} {\rm g \ cm^{-3}}$ is found to be thermally stable and the gas flow is one-phase. The applications of the results are briefly discussed.

astro-ph.HE↗

arXiv2019

On the Role of Hot Feedback Mode in Active Galactic Nuclei Feedback in an Elliptical Galaxy

Depending on the value of the accretion rate, black hole accretion is divided into cold and hot modes. The two modes have distinctly different physics and correspond to two feedback modes. Most previous feedback works either focus only on one mode, or the accretion physics is not always properly adopted. Here, by performing hydrodynamical numerical simulations of AGN feedback in an elliptical galaxy, we show that including both is important, and gives different results from including just one or the other. We specifically focus on the wind and radiation (but neglecting the jet) feedback in the hot mode, to explore whether this particular mode of feedback can play any important feedback role. For this aim, we have run two test models. In one model, we always adopt the cold mode no matter what value the accretion rate is; in another model, we turn off the AGN once it enters into the hot mode. We have calculated the AGN light curves, black hole growth, star formation, and AGN energy duty-cycle; and compared the results with the model in which the two modes are correctly included. Important differences are found. For example, if we were to adopt only the cold mode, the total mass of newly formed stars would become two orders of magnitude smaller, and the fraction of energy ejected within the high accretion regime (i.e., $L_{\rm BH} > 2\% L_{\rm Edd}$) would be too small to be consistent with observations. We have also investigated the respective roles of wind and radiation in the hot mode.

astro-ph.HE↗

arXiv2016

Wireless Physical-Layer Identification: Modeling and Validation

The wireless physical-layer identification (WPLI) techniques utilize the unique features of the physical waveforms of wireless signals to identify and classify authorized devices. As the inherent physical layer features are difficult to forge, WPLI is deemed as a promising technique for wireless security solutions. However, as of today it still remains unclear whether existing WPLI techniques can be applied under real-world requirements and constraints. In this paper, through both theoretical modeling and experiment validation, the reliability and differentiability of WPLI techniques are rigorously evaluated, especially under the constraints of state-of-art wireless devices, real operation environments, as well as wireless protocols and regulations. Specifically, a theoretical model is first established to systematically describe the complete procedure of WPLI. More importantly, the proposed model is then implemented to thoroughly characterize various WPLI techniques that utilize the spectrum features coming from the non-linear RF-front-end, under the influences from different transmitters, receivers, and wireless channels. Subsequently, the limitations of existing WPLI techniques are revealed and evaluated in details using both the developed theoretical model and in-lab experiments. The real-world requirements and constraints are characterized along each step in WPLI, including i) the signal processing at the transmitter (device to be identified), ii) the various physical layer features that originate from circuits, antenna, and environments, iii) the signal propagation in various wireless channels, iv) the signal reception and processing at the receiver (the identifier), and v) the fingerprint extraction and classification at the receiver.

cs.CR↗

arXiv2016

User Capacity of Wireless Physical-layer Identification: An Information-theoretic Perspective

Wireless Physical Layer Identification (WPLI) system aims at identifying or classifying authorized devices based on the unique Radio Frequency Fingerprints (RFFs) extracted from their radio frequency signals at the physical layer. Current works of WPLI focus on demonstrating system feasibility based on experimental error performance of WPLI with a fixed number of users. While an important question remains to be answered: what's the user number that WPLI can accommodate using different RFFs and receiving equipment. The user capacity of the WPLI can be a major concern for practical system designers and can also be a key metric to evaluate the classification performance of WPLI. In this work, we establish a theoretical understanding on user capacity of WPLI in an information-theoretic perspective. We apply information-theoretic modeling on RFF features of WPLI. An information-theoretic approach is consequently proposed based on mutual information between RFF and user identity to characterize the user capacity of WPLI. Based on this theoretical tool, the achievable user capacity of WPLI is characterized under practical constrains of off-the-shelf receiving devices. Field experiments on classification error performance are conducted for the validation of the information-theoretic user capacity characterization.

cs.CR↗