52,760 research outputs found
A Fractal and Scale-free Model of Complex Networks with Hub Attraction Behaviors
It is widely believed that fractality of complex networks origins from hub
repulsion behaviors (anticorrelation or disassortativity), which means large
degree nodes tend to connect with small degree nodes. This hypothesis was
demonstrated by a dynamical growth model, which evolves as the inverse
renormalization procedure proposed by Song et al. Now we find that the
dynamical growth model is based on the assumption that all the cross-boxes
links has the same probability e to link to the most connected nodes inside
each box. Therefore, we modify the growth model by adopting the flexible
probability e, which makes hubs have higher probability to connect with hubs
than non-hubs. With this model, we find some fractal and scale-free networks
have hub attraction behaviors (correlation or assortativity). The results are
the counter-examples of former beliefs.Comment: 9 pages, 5 figure
Efficient Network Construction through Structural Plasticity
Deep Neural Networks (DNNs) on hardware is facing excessive computation cost
due to the massive number of parameters. A typical training pipeline to
mitigate over-parameterization is to pre-define a DNN structure first with
redundant learning units (filters and neurons) under the goal of high accuracy,
then to prune redundant learning units after training with the purpose of
efficient inference. We argue that it is sub-optimal to introduce redundancy
into training for the purpose of reducing redundancy later in inference.
Moreover, the fixed network structure further results in poor adaption to
dynamic tasks, such as lifelong learning. In contrast, structural plasticity
plays an indispensable role in mammalian brains to achieve compact and accurate
learning. Throughout the lifetime, active connections are continuously created
while those no longer important are degenerated. Inspired by such observation,
we propose a training scheme, namely Continuous Growth and Pruning (CGaP),
where we start the training from a small network seed, then literally execute
continuous growth by adding important learning units and finally prune
secondary ones for efficient inference. The inference model generated from CGaP
is sparse in the structure, largely decreasing the inference power and latency
when deployed on hardware platforms. With popular DNN structures on
representative datasets, the efficacy of CGaP is benchmarked by both algorithm
simulation and architectural modeling on Field-programmable Gate Arrays (FPGA).
For example, CGaP decreases the FLOPs, model size, DRAM access energy and
inference latency by 63.3%, 64.0%, 11.8% and 40.2%, respectively, for
ResNet-110 on CIFAR-10
Rigorous proof for the non-local correlation functions in the antiferromagnetic seamed transverse Ising ring
An unusual correlation function is conjectured by M. Campostrini et al.
(Phys. Rev. E 91, 042123 (2015)) for the ground state of a transverse Ising
chain with geometrical frustration in one of the translationally invariant
cases. Later, we demonstrated the correlation function and showed its non-local
nature in the thermodynamic limit based on the rigorous evaluation of a
Toeplitz determinant (J. Stat. Mech. 113102 (2016)). In this paper, we prove
rigorously that all the states that forming the lowest gapless spectrum
(including the ground state) in the kink phase exhibit the same asymptotic
correlation function. So, in a point of view of cannonical ensemble, the
thermal correlation function is inert to temperature within the energy range of
the lowest gapless spectrum.Comment: 8 pages, 0 figure
Ultra-small phase estimation via weak measurement technique with postselection
Weak measurement is a novel technique for parameter estimation with higher
precision. In this paper we develop a general theory for the parameter
estimation based on weak measurement technique with arbitrary postselection.
The previous weak value amplification model and the joint weak measurement
model are two special cases in our theory. Applying the developed theory, the
time-delay estimation is investigated in both theory and experiment.
Experimental results shows that when the time-delay is ultra small, the joint
weak measurement scheme outperforms the weak value amplification scheme, and is
robust against not only the misalignment errors but also the
wavelength-dependence of the optical components. These results are consistent
with the theoretical predictions that has not been verified by any experiment
before.Comment: 8 pages with 8 figure
Code Attention: Translating Code to Comments by Exploiting Domain Features
Appropriate comments of code snippets provide insight for code functionality,
which are helpful for program comprehension. However, due to the great cost of
authoring with the comments, many code projects do not contain adequate
comments. Automatic comment generation techniques have been proposed to
generate comments from pieces of code in order to alleviate the human efforts
in annotating the code. Most existing approaches attempt to exploit certain
correlations (usually manually given) between code and generated comments,
which could be easily violated if the coding patterns change and hence the
performance of comment generation declines. In this paper, we first build
C2CGit, a large dataset from open projects in GitHub, which is more than
20 larger than existing datasets. Then we propose a new attention
module called Code Attention to translate code to comments, which is able to
utilize the domain features of code snippets, such as symbols and identifiers.
We make ablation studies to determine effects of different parts in Code
Attention. Experimental results demonstrate that the proposed module has better
performance over existing approaches in both BLEU and METEOR
ARABIS: an Asynchronous Acoustic Indoor Positioning System for Mobile Devices
Acoustic ranging based indoor positioning solutions have the advantage of
higher ranging accuracy and better compatibility with commercial-off-the-self
consumer devices. However, similar to other time-domain based approaches using
Time-of-Arrival and Time-Difference-of-Arrival, they suffer from performance
degradation in presence of multi-path propagation and low received
signal-to-noise ratio (SNR) in indoor environments. In this paper, we improve
upon our previous work on asynchronous acoustic indoor positioning and develop
ARABIS, a robust and low-cost acoustic positioning system (IPS) for mobile
devices. We develop a low-cost acoustic board custom-designed to support large
operational ranges and extensibility. To mitigate the effects of low SNR and
multi-path propagation, we devise a robust algorithm that iteratively removes
possible outliers by taking advantage of redundant TDoA estimates. Experiments
have been carried in two testbeds of sizes 10.67m*7.76m and 15m*15m, one in an
academic building and one in a convention center. The proposed system achieves
average and 95% quantile localization errors of 7.4cm and 16.0cm in the first
testbed with 8 anchor nodes and average and 95% quantile localization errors of
20.4cm and 40.0cm in the second testbed with 4 anchor nodes only.Comment: 8 pages, 13 figure
Constraints on Dark Energy from New Observations including Pan-STARRS
In this paper, we set the new limits on the equation of state parameter (EoS)
of dark energy with the observations of cosmic microwave background radiation
(CMB) from Planck satellite, the type Ia supernovae from Pan-STARRS and the
baryon acoustic oscillation (BAO). We consider two parametrization forms of
EoS: a constant and time evolving . The results show
that with a constant EoS, (), which is
consistent with CDM at about confidence level. For a time
evolving model, we get (),
(), and in this case CDM can
be comparable with our observational data at confidence level. In
order to do the parametrization independent analysis, additionally we adopt the
so called principal component analysis (PCA) method, in which we divide
redshift range into several bins and assume as a constant in each redshift
bin (bin-w). In such bin-w scenario, we find that for most of the bins
cosmological constant can be comparable with the data, however, there exists
few bins which give deviating from CDM at more than
confidence level, which shows a weak hint for the time evolving behavior of
dark energy. To further confirm this hint, we need more data with higher
precision.Comment: 9 pages, 8 figures, 1 tabl
Research on two-dimensional traffic flow model based on psychological field theory
In this paper, the influence of fan-shaped buffer zone on the performance of
the toll plaza is researched. A two-dimensional traffic flow model and a
comprehensive evaluation model based on mechanical model and psychological
field are established. The traffic flow model is simulated by creating
coordinate system.
We first establish queue theory model to analyze vehicles when entering toll
plaza. Then, a two-dimensional steadily car-following model is established
based on psychological field for the analysis of vehicles when leaving toll
plaza. According to psychological field theory, we analyze the force condition
of each vehicle. The force of each vehicle is contributed by the vehicles in
its observation area and obstacles. By projecting these vehicles and obstacles
via the equipotential line in the psychological field, the influence on the
value and direction acceleration of following vehicles is obtained.
Consequently, the changes of each vehicle's speed and position are obtained as
well. Next, we establish simulation based on the states of vehicles and make
the rules of vehicle state-changing. By simulating the system, we obtain the
throughput of the toll plaza's input and output. Then we obtained the bearing
pressure on the road by the max throughput and the demand of the roads. Using
the number of cars in per unit area as the safety factor. Then a comprehensive
evaluation model is established based on bearing pressure on the road, cost and
safety factor.Comment: 22 page
Two-photon Interference with Non-identical Photons
The indistinguishability of non-identical photons is dependent on detection
system in quantum physics. If two photons with different wavelengths are
indistinguishable for a detection system, there can be two-photon interference
when these two photons are incident to two input ports of a Hong-Ou-Mandel
interferometer, respectively. The reason why two-photon interference phenomena
are different for classical and nonclassical light is not due to interference,
but due to the properties of light and detection system. These conclusions are
helpful to understand the physics and applications of two-photon interference.Comment: 5 pages, 3 figures. Comments are welcom
One-sided Measurement-Device-Independent Quantum Key Distribution
Measurement-device-independent quantum key distribution (MDI-QKD) protocol
was proposed to remove all the detector side channel attacks, while its
security relies on the trusted encoding systems. Here we propose a one-sided
MDI-QKD (1SMDI-QKD) protocol, which enjoys detection loophole-free advantage,
and at the same time weakens the state preparation assumption in MDI-QKD. The
1SMDI-QKD can be regarded as a modified MDI-QKD, in which Bob's encoding system
is trusted, while Alice's is uncharacterized. For the practical implementation,
we also provide a scheme by utilizing coherent light source with an analytical
two decoy state estimation method. Simulation with realistic experimental
parameters shows that the protocol has a promising performance, and thus can be
applied to practical QKD applications
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