821 research outputs found
Merging of a CO WD and a He-rich white dwarf to produce a type Ia supernovae
Context: Although type Ia supernovae (SNe Ia) play a key role in
astrophysics, the companions of the exploding carbon-oxygen white dwarfs (CO
WDs) are still not completely identified. It has been suggested recently that a
He-rich WD (a He WD or a hybrid HeCO WD) merges with a CO WD may produce an SN
Ia. This theory was based on the double-detonation model, in which the shock
compression in the CO core caused by the surface explosion of the He-rich shell
might lead to the explosion of the whole CO WD. However, so far, very few
binary population synthesis (BPS) studies have been made on the merger scenario
of a CO WD and a He-rich WD in the context of SNe Ia. Aims: We aim to
systematically study the Galactic birthrates and delay-time distributions of
SNe Ia based on the merger scenario of a CO WD and a He-rich WD. Methods: We
performed a series of Monte Carlo BPS simulations to investigate the properties
of SNe Ia from the merging of a CO WD and a He-rich WD based on the Hurley
rapid binary evolution code. We also considered the influence of different
metallicities on the final results. Results: From our simulations, we found
that no more than 15% of all SNe Ia stem from the merger scenario of a CO WD
and a He-rich WD, and their delay times range from ~110 Myr to the Hubble time.
This scenario mainly contributes to SN Ia explosions with intermediate and long
delay times. The present work indicates that the merger scenario of a CO WD and
a He-rich WD can roughly reproduce the birthrates of SN 1991bg-like events, and
cover the range of their delay times. We also found that SN Ia birthrates from
this scenario would be higher for the cases with low metallicities.Comment: 8 pages, 8 figures, accepted for publication in A&
User-Centric Interference Nulling in Downlink Multi-Antenna Heterogeneous Networks
In heterogeneous networks (HetNets), strong interference due to spectrum
reuse affects each user's signal-to-interference ratio (SIR), and hence is one
limiting factor of network performance. In this paper, we propose a
user-centric interference nulling (IN) scheme in a downlink large-scale HetNet
to improve coverage/outage probability by improving each user's SIR. This IN
scheme utilizes at most maximum IN degree of freedom (DoF) at each macro-BS to
avoid interference to uniformly selected macro (pico) users with
signal-to-individual-interference ratio (SIIR) below a macro (pico) IN
threshold, where the maximum IN DoF and the two IN thresholds are three design
parameters. Using tools from stochastic geometry, we first obtain a tractable
expression of the coverage (equivalently outage) probability. Then, we analyze
the asymptotic coverage/outage probability in the low and high SIR threshold
regimes. The analytical results indicate that the maximum IN DoF can affect the
order gain of the outage probability in the low SIR threshold regime, but
cannot affect the order gain of the coverage probability in the high SIR
threshold regime. Moreover, we characterize the optimal maximum IN DoF which
optimizes the asymptotic coverage/outage probability. The optimization results
reveal that the IN scheme can linearly improve the outage probability in the
low SIR threshold regime, but cannot improve the coverage probability in the
high SIR threshold regime. Finally, numerical results show that the proposed
scheme can achieve good gains in coverage/outage probability over a maximum
ratio beamforming scheme and a user-centric almost blank subframes (ABS)
scheme.Comment: Transactions on Wireless Communications (under revision). arXiv admin
note: text overlap with arXiv:1504.0528
A natural language processing-based approach: mapping human perception by understanding deep semantic features in street view images
In the past decade, using Street View images and machine learning to measure
human perception has become a mainstream research approach in urban science.
However, this approach using only image-shallow information makes it difficult
to comprehensively understand the deep semantic features of human perception of
a scene. In this study, we proposed a new framework based on a pre-train
natural language model to understand the relationship between human perception
and the sense of a scene. Firstly, Place Pulse 2.0 was used as our base
dataset, which contains a variety of human-perceived labels, namely, beautiful,
safe, wealthy, depressing, boring, and lively. An image captioning network was
used to extract the description information of each street view image.
Secondly, a pre-trained BERT model was finetuning and added a regression
function for six human perceptual dimensions. Furthermore, we compared the
performance of five traditional regression methods with our approach and
conducted a migration experiment in Hong Kong. Our results show that human
perception scoring by deep semantic features performed better than previous
studies by machine learning methods with shallow features. The use of deep
scene semantic features provides new ideas for subsequent human perception
research, as well as better explanatory power in the face of spatial
heterogeneity.Comment: 11 pages, 8 figure
A super-Eddington wind scenario for the progenitors of type Ia supernovae: binary population synthesis calculations
The super-Eddington wind scenario has been proposed as an alternative way for
producing type Ia supernovae (SNe Ia). The super-Eddington wind can naturally
prevent the carbon--oxygen white dwarfs (CO WDs) with high mass-accretion rates
from becoming red-giant-like stars. Furthermore, it works in low-metallicity
environments, which may explain SNe Ia observed at high redshifts. In this
article, we systematically investigated the most prominent single-degenerate
WD+MS channel based on the super-Eddington wind scenario. We combined the
Eggleton stellar evolution code with a rapid binary population synthesis (BPS)
approach to predict SN Ia birthrates for the WD+MS channel by adopting the
super-Eddington wind scenario and detailed mass-accumulation efficiencies of
H-shell flashes on the WDs. Our BPS calculations found that the estimated SN Ia
birthrates for the WD+MS channel are ~0.009-0.315*10^{-3}{yr}^{-1} if we adopt
the Eddington accretion rate as the critical accretion rate, which are much
lower than that of the observations (<10% of the observed SN Ia birthrates).
This indicates that the WD+MS channel only contributes a small proportion of
all SNe Ia. The birthrates in this simulation are lower than previous studies,
the main reason of which is that new mass-accumulation efficiencies of H-shell
flashes are adopted. We also found that the critical mass-accretion rate has a
significant influence on the birthrates of SNe Ia. Meanwhile, the results of
our BPS calculations are sensitive to the values of the common-envelope
ejection efficiency.Comment: 14 pages, 9 figures, 1 table, accepted for publication in Astronomy
and Astrophysic
Precise Localization and Formation Control of Swarm Robots via Wireless Sensor Networks
Precise localization and formation control are one of the key technologies to achieve coordination and control of swarm robots, which is also currently a bottleneck for practical applications of swarm robotic systems. Aiming at overcoming the limited individual perception and the difficulty of achieving precise localization and formation, a localization approach combining dead reckoning (DR) with wireless sensor network- (WSN-) based methods is proposed in this paper. Two kinds of WSN localization technologies are adopted in this paper, that is, ZigBee-based RSSI (received signal strength indication) global localization and electronic tag floors for calibration of local positioning. First, the DR localization information is combined with the ZigBee-based RSSI position information using the Kalman filter method to achieve precise global localization and maintain the robot formation. Then the electronic tag floors provide the robots with their precise coordinates in some local areas and enable the robot swarm to calibrate its formation by reducing the accumulated position errors. Hence, the overall performance of localization and formation control of the swarm robotic system is improved. Both of the simulation results and the experimental results on a real schematic system are given to demonstrate the success of the proposed approach
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