arXiv subjects

Shuang Li

Publications and source records attributed to Shuang Li.

260 records · Page 15Linked to original sources

arXiv2016

Extended relativistic configuration interaction and many-body perturbation calculations of spectroscopic data for the $n \leq 6$ configurationsin ne-like ions between Cr XV and Kr XXVII

Level energies, wavelengths, electric dipole, magnetic dipole, electric quadrupole, and magnetic quadrupole transition rates, oscillator strengths, and line strengths from combined relativistic configuration interaction and many-body perturbation calculations are reported for the 201 fine-structure states of the $2s^2 2p^6$, $2s^2 2p^5 3l$, $2s 2p^6 3l$, $2s^2 2p^5 4l$, $2s 2p^6 4l$, $2s^2 2p^5 5l$, and $2s^2 2p^5 6l$ configurations in all Ne-like ions between Cr XV and Kr XXVII. Calculated level energies and transition data are compared with experiments from the NIST and CHIANTI databases, and other recent benchmark calculations. The mean energy difference with the NIST experiments is only 0.05%. The present calculations significantly increase the amount of accurate spectroscopic data for the $n >3$ states in a number of Ne-like ions of astrophysics interest. A complete dataset should be helpful in analyzing new observations from the solar and other astrophysical sources, and is also likely to be useful for modeling and diagnosing a variety of plasmas including astronomical and fusion plasma.

physics.atom-ph↗

arXiv2016

COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution

Information diffusion in online social networks is affected by the underlying network topology, but it also has the power to change it. Online users are constantly creating new links when exposed to new information sources, and in turn these links are alternating the way information spreads. However, these two highly intertwined stochastic processes, information diffusion and network evolution, have been predominantly studied separately, ignoring their co-evolutionary dynamics. We propose a temporal point process model, COEVOLVE, for such joint dynamics, allowing the intensity of one process to be modulated by that of the other. This model allows us to efficiently simulate interleaved diffusion and network events, and generate traces obeying common diffusion and network patterns observed in real-world networks. Furthermore, we also develop a convex optimization framework to learn the parameters of the model from historical diffusion and network evolution traces. We experimented with both synthetic data and data gathered from Twitter, and show that our model provides a good fit to the data as well as more accurate predictions than alternatives.

cs.SI↗

arXiv2014

Measurements of the heavy-flavour nuclear modification factor in p--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV with ALICE at the LHC

The heavy-flavour nuclear modification factor $R_{\rm pPb}$ has been measured with the ALICE detector in p--Pb collisions at the nucleon--nucleon center of mass energy $\sqrt{s_{\rm NN}}$ = 5.02 TeV at the CERN LHC in a wide rapidity and transverse momentum range, as well as in several decay channels. $R_{\rm pPb}$ is consistent with unity within uncertainties at mid-rapidity and forward rapidity. In the backward region a slight enhancement of the yield of heavy-flavour decay muons is found in the region $2<p_{\rm T}<4$ GeV/$c$. The results are described within uncertainties by theoretical calculations that include initial-state effects. The measurements add experimental evidence that the suppression of heavy-flavour production observed at high $p_{\rm T}$ in central Pb--Pb collisions with respect to pp collisions is due to a medium effect induced by the interaction of heavy quarks with the partonic matter.

hep-ex↗

arXiv2013

Stone-Wales Defects in Silicene: Formation, Stability and Reactivity of Defect Sites

During the synthesis of ultra-thin materials with hexagonal lattice structure Stone-Wales (SW) type of defects are quite likely to be formed and the existence of such topological defects in the graphene-like structures results in dramatical changes of their electronic and mechanical properties. Here we investigate the formation and reactivity of such SW defects in silicene. We report the energy barrier for the formation of SW defects in freestanding (~2.4 eV) and Ag(111)-supported (~2.8 eV) silicene and found it to be significantly lower than in graphene (~9.2 eV). Moreover, the buckled nature of silicene provides a large energy barrier for the healing of the SW defect and therefore defective silicene is stable even at high temperatures. Silicene with SW defects is semiconducting with a direct bandgap of 0.02 eV and this value depends on the concentration of defects. Furthermore, nitrogen substitution in SW defected silicene shows that the defect lattice sites are the least preferable substitution locations for the N atoms. Our findings show the easy formation of SW defects in silicene and also provide a guideline for bandgap engineering in silicene-based materials through such defects.

cond-mat.mtrl-sci↗

arXiv2013

Bootstrap inference for network construction with an application to a breast cancer microarray study

Gaussian Graphical Models (GGMs) have been used to construct genetic regulatory networks where regularization techniques are widely used since the network inference usually falls into a high-dimension-low-sample-size scenario. Yet, finding the right amount of regularization can be challenging, especially in an unsupervised setting where traditional methods such as BIC or cross-validation often do not work well. In this paper, we propose a new method - Bootstrap Inference for Network COnstruction (BINCO) - to infer networks by directly controlling the false discovery rates (FDRs) of the selected edges. This method fits a mixture model for the distribution of edge selection frequencies to estimate the FDRs, where the selection frequencies are calculated via model aggregation. This method is applicable to a wide range of applications beyond network construction. When we applied our proposed method to building a gene regulatory network with microarray expression breast cancer data, we were able to identify high-confidence edges and well-connected hub genes that could potentially play important roles in understanding the underlying biological processes of breast cancer.

stat.ME↗

arXiv2012

Maximizing System Throughput Using Cooperative Sensing in Multi-Channel Cognitive Radio Networks

In Cognitive Radio Networks (CRNs), unlicensed users are allowed to access the licensed spectrum when it is not currently being used by primary users (PUs). In this paper, we study the throughput maximization problem for a multi-channel CRN where each SU can only sense a limited number of channels. We show that this problem is strongly NP-hard, and propose an approximation algorithm with a factor at least $1/2μ$ where $μ\in [1,2]$ is a system parameter reflecting the sensing capability of SUs across channels and their sensing budgets. This performance guarantee is achieved by exploiting a nice structural property of the objective function and constructing a particular matching. Our numerical results demonstrate the advantage of our algorithm compared with both a random and a greedy sensing assignment algorithm.

cs.NI↗

arXiv2012

Maximizing Social Welfare in Operator-based Cognitive Radio Networks under Spectrum Uncertainty and Sensing Inaccuracy

In Cognitive Radio Networks (CRNs), secondary users (SUs) are allowed to opportunistically access the unused/under-utilized channels of primary users (PUs). To utilize spectrum resources efficiently, an auction scheme is often applied where an operator serves as an auctioneer and accepts spectrum requests from SUs. Most existing works on spectrum auctions assume that the operator has perfect knowledge of PU activities. In practice, however, it is more likely that the operator only has statistical information of the PU traffic when it is trading a spectrum hole, and it is acquiring more accurate information in real time. In this paper, we distinguish PU channels that are under the control of the operator, where accurate channel states are revealed in real-time, and channels that the operator acquires from PUs out of its control, where a sense-before-use paradigm has to be followed. Considering both spectrum uncertainty and sensing inaccuracy, we study the social welfare maximization problem for serving SUs with various levels of delay tolerance. We first model the problem as a finite horizon Markov decision process when the operator knows all spectrum requests in advance, and propose an optimal dynamic programming based algorithm. We then investigate the case when spectrum requests are submitted online, and propose a greedy algorithm that is 1/2-competitive for homogeneous channels and is comparable to the offline algorithm for more general settings. We further show that the online algorithm together with a payment scheme achieves incentive compatibility for the SUs while guaranteeing a non-negative revenue for the operator.

cs.NI↗

arXiv2011

Maximizing System Throughput by Cooperative Sensing in Cognitive Radio Networks

Cognitive Radio Networks allow unlicensed users to opportunistically access the licensed spectrum without causing disruptive interference to the primary users (PUs). One of the main challenges in CRNs is the ability to detect PU transmissions. Recent works have suggested the use of secondary user (SU) cooperation over individual sensing to improve sensing accuracy. In this paper, we consider a CRN consisting of a single PU and multiple SUs to study the problem of maximizing the total expected system throughput. We propose a Bayesian decision rule based algorithm to solve the problem optimally with a constant time complexity. To prioritize PU transmissions, we re-formulate the throughput maximization problem by adding a constraint on the PU throughput. The constrained optimization problem is shown to be NP-hard and solved via a greedy algorithm with pseudo-polynomial time complexity that achieves strictly greater than 1/2 of the optimal solution. We also investigate the case for which a constraint is put on the sensing time overhead, which limits the number of SUs that can participate in cooperative sensing. We reveal that the system throughput is monotonic over the number of SUs chosen for sensing. We illustrate the efficacy of the performance of our algorithms via a numerical investigation.

cs.NI↗