Searcharxiv⌕ Search

arXiv subjects

Ping Guo

Publications and source records attributed to Ping Guo.

62 records · Page 4Linked to original sources

Systematic study of $α$ decay for odd-$A$ nuclei within a two-potential approach

$α$ decay is usually associated with both ground and low-lying isomeric states of heavy and superheavy nuclei, and the unpaired nucleon plays a key role on $α$ decay. In this work, we systematically studied the $α$ decay half-lives of odd-$A$ nuclei, including both favored and unfavored $α$ decay within the two-potential approach based on the isospin dependent nuclear potential. The $α$ preformation probabilities are estimated by using an analytic formula taking into account the shell structure and proton-neutron correlation, and the parameters are obtained through the $α$ decay half-lives data. The results indicate that in general the $α$ preformation probabilities of even-$Z$, odd-$N$ nuclei are slightly smaller than the odd-$Z$, even-$N$ ones. We found that the odd-even staggering effect may play a more important role on spontaneous fission than $α$ decay. The calculated half-lives can well reproduce the experimental data.

nucl-th↗

Pulsar Candidate Selection Using Ensemble Networks for FAST Drift-Scan Survey

The Commensal Radio Astronomy Five-hundred-meter Aperture Spherical radio Telescope (FAST) Survey (CRAFTS) utilizes the novel drift-scan commensal survey mode of FAST and can generate billions of pulsar candidate signals. The human experts are not likely to thoroughly examine these signals, and various machine sorting methods are used to aid the classification of the FAST candidates. In this study, we propose a new ensemble classification system for pulsar candidates. This system denotes the further development of the pulsar image-based classification system (PICS), which was used in the Arecibo Telescope pulsar survey, and has been retrained and customized for the FAST drift-scan survey. In this study, we designed a residual network model comprising 15 layers to replace the convolutional neural networks (CNNs) in PICS. The results of this study demonstrate that the new model can sort >96% of real pulsars to belong the top 1% of all candidates and classify >1.6 million candidates per day using a dual--GPU and 24--core computer. This increased speed and efficiency can help to facilitate real-time or quasi-real-time processing of the pulsar-search data stream obtained from CRAFTS. In addition, we have published the labeled FAST data used in this study online, which can aid in the development of new deep learning techniques for performing pulsar searches.

astro-ph.IM↗

A VEST of the Pseudoinverse Learning Algorithm

In this paper, we briefly review the basic scheme of the pseudoinverse learning (PIL) algorithm and present some discussions on the PIL, as well as its variants. The PIL algorithm, first presented in 1995, is a non-gradient descent and non-iterative learning algorithm for multi-layer neural networks and has several advantages compared with gradient descent based algorithms. Some new viewpoints to PIL algorithm are presented, and several common pitfalls in practical implementation of the neural network learning task are also addressed. In addition, we show that so called extreme learning machine is a Variant crEated by Simple name alTernation (VEST) of the PIL algorithm for single hidden layer feedforward neural networks.

cs.LG↗

Systematic study of favored α-decay half-lives of closed shell odd-A and doubly-odd nuclei related to ground and isomeric states

In this work, we systematically investigate the favored $α$-decay half-lives and $α$ preformation probabilities of both odd-$A$ and doubly-odd nuclei related to ground and isomeric states around the doubly magic cores at $Z=82$, $N=82$ and at $Z=82$, $N=126$, respectively, within a two-potential approach from the view of the valence nucleon (or hole). The results show that the $α$ preformation probability is linear related to $N_\text{p}N_\text{n}$ or $N_\text{p}N_\text{n}I$, where $N_\text{p}$, $N_\text{n}$, and $I$ are the number of valence protons (or holes), the number of valence neutrons (or holes), and the isospin of the parent nucleus, respectively. Fitting the $α$ preformation probabilities data extracted from the differences between experimental data and calculated half-lives without a shell correction, we give two analytic formulas of the $α$ preformation probabilities and the values of corresponding parameters. Using those formulas and the parameters, we calculate the $α$-decay half-lives for those nuclei. The calculated results can well reproduce the experimental data.

nucl-th↗

A Machine Learning Based Forwarding Algorithm Over Cognitive Radios in Wireless Mesh Networks

Wireless Mesh Networks improve their capacities by equipping mesh nodes with multi-radios tuned to non-overlapping channels. Hence the data forwarding between two nodes has multiple selections of links and the bandwidth between the pair of nodes varies dynamically. Under this condition, a mesh node adopts machine learning mechanisms to choose the possible best next hop which has maximum bandwidth when it intends to forward data. In this paper, we present a machine learning based forwarding algorithm to let a forwarding node dynamically select the next hop with highest potential bandwidth capacity to resume communication based on learning algorithm. Key to this strategy is that a node only maintains three past status, and then it is able to learn and predict the potential bandwidth capacities of its links. Then, the node selects the next hop with potential maximal link bandwidth. Moreover, a geometrical based algorithm is developed to let the source node figure out the forwarding region in order to avoid flooding. Simulations demonstrate that our approach significantly speeds up the transmission and outperforms other peer algorithms.

cs.NI↗

Systematic study of $α$ decay half-lives for even-even nuclei within a two-potential approach

$α$ decay is a common and important process for natural radioactivity of heavy and superheavy nuclei. The $α$ decay half-lives for even-even nuclei from Z=62 to Z=118 are systematically researched based on the two-potential approach with a quasi-stationary state approximation. To describe the deviations between experimental half-lives and calculated results due to the nuclear shell structure, a hindrance factor related with $α$ particle preformation probability is introduced. Our results can well reproduce the experimental data equally to the density-dependent cluster model and the generalized liquid drop model. We also study the isospin effect of nuclear potential in this work. Considering the isospin effect the calculated results improved about 7.3$\%$.

nucl-th↗

Combined Descriptors in Spatial Pyramid Domain for Image Classification

Recently spatial pyramid matching (SPM) with scale invariant feature transform (SIFT) descriptor has been successfully used in image classification. Unfortunately, the codebook generation and feature quantization procedures using SIFT feature have the high complexity both in time and space. To address this problem, in this paper, we propose an approach which combines local binary patterns (LBP) and three-patch local binary patterns (TPLBP) in spatial pyramid domain. The proposed method does not need to learn the codebook and feature quantization processing, hence it becomes very efficient. Experiments on two popular benchmark datasets demonstrate that the proposed method always significantly outperforms the very popular SPM based SIFT descriptor method both in time and classification accuracy.

cs.CV↗