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$\times$ 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 $w$ and time evolving $w(a)=w_0+w_a(1-a)$. The results show that with a constant EoS, $w=-1.141\pm{0.075}$ ($68\%~C.L.$), which is consistent with $\Lambda$CDM at about $2\sigma$ confidence level. For a time evolving $w(a)$ model, we get $w_0=-1.09^{+0.16}_{-0.18}$ ($1\sigma~C.L.$), $w_a=-0.34^{+0.87}_{-0.51}$ ($1\sigma~C.L.$), and in this case $\Lambda$CDM can be comparable with our observational data at $1\sigma$ 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 $w$ 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 $w$ deviating from $\Lambda$CDM at more than $2\sigma$ 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