arXiv subjects

Ying Yang

Publications and source records attributed to Ying Yang.

116 records · Page 7Linked to original sources

arXiv2017

A Two-grid Method for Linearizing and Symmetrizing the Steady-state Poisson-Nernst-Planck Equations

In this paper, a two-grid method is proposed to linearize and symmetrize the steady-state Poisson-Nernst-Planck equations. The computational system is decoupled to linearize and symmetrize equations by using this method, which can improve the computational efficiency compared with the finite element method. Error estimates are derived for the proposed method. The numerical results show that the two-grid method is effective.

math.NA↗

arXiv2016

Cross Section and Higgs Mass Measurement with Higgsstrahlung at the CEPC

The Circular Electron Positron Collider (CEPC) is a future Higgs factory proposed by the Chinese high energy physics community. It will operate at a center-of-mass energy of 240-250 GeV. The CEPC will accumulate an integrated luminosity of 5 ab$^{\rm{-1}}$ in ten years' operation, producing one million Higgs bosons via the Higgsstrahlung and vector boson fusion processes. This sample allows a percent or even sub-percent level determination of the Higgs boson couplings. With GEANT4-based full simulation and dedicated fast simulation tool, we evaluated the statistical precisions of the Higgstrahlung cross section $σ_{ZH}$ and the Higgs mass $m_{H}$ measurement at the CEPC in the $Z\rightarrowμ^+μ^-$ channel. The statistical precision of $σ_{ZH}$ ($m_{H}$) measurement could reach 0.97\% (6.9 MeV) in the model-independent analysis which uses only the information of Z boson decay. For the standard model Higgs boson, the $m_{H}$ precision could be improved to 5.4 MeV by including the information of Higgs decays. Impact of the TPC size to these measurements is investigated. In addition, we studied the prospect of measuring the Higgs boson decaying into invisible final states at the CEPC. With the standard model $ZH$ production rate, the upper limit of ${\cal B}(H\rightarrow \rm{inv.})$ could reach 1.2\% at 95\% confidence level.

hep-ex↗

arXiv2016

A Decoupling Two-Grid Method for the Steady-State Poisson-Nernst-Planck Equations

Poisson-Nernst-Planck equations are widely used to describe the electrodiffusion of ions in a solvated biomolecular system. Two kinds of two-grid finite element algorithms are proposed to decouple the steady-state Poisson-Nernst-Planck equations by coarse grid finite element approximations. Both theoretical analysis and numerical experiments show the efficiency and effectiveness of the two-grid algorithms for solving Poisson-Nernst-Planck equations.

math.NA↗

arXiv2016

Mimir: Bringing CTables into Practice

The present state of the art in analytics requires high upfront investment of human effort and computational resources to curate datasets, even before the first query is posed. So-called pay-as-you-go data curation techniques allow these high costs to be spread out, first by enabling queries over uncertain and incomplete data, and then by assessing the quality of the query results. We describe the design of a system, called Mimir, around a recently introduced class of probabilistic pay-as-you-go data cleaning operators called Lenses. Mimir wraps around any deterministic database engine using JDBC, extending it with support for probabilistic query processing. Queries processed through Mimir produce uncertainty-annotated result cursors that allow client applications to quickly assess result quality and provenance. We also present a GUI that provides analysts with an interactive tool for exploring the uncertainty exposed by the system. Finally, we present optimizations that make Lenses scalable, and validate this claim through experimental evidence.

cs.DB↗

arXiv2015

Estimating Learning Effects: A Short-Time Fourier Transform Regression Model for MEG Source Localization

Magnetoencephalography (MEG) has a high temporal resolution well-suited for studying perceptual learning. However, to identify where learning happens in the brain, one needs to ap- ply source localization techniques to project MEG sensor data into brain space. Previous source localization methods, such as the short-time Fourier transform (STFT) method by Gramfort et al.([Gramfort et al., 2013]) produced intriguing results, but they were not designed to incor- porate trial-by-trial learning effects. Here we modify the approach in [Gramfort et al., 2013] to produce an STFT-based source localization method (STFT-R) that includes an additional regression of the STFT components on covariates such as the behavioral learning curve. We also exploit a hierarchical L 21 penalty to induce structured sparsity of STFT components and to emphasize signals from regions of interest (ROIs) that are selected according to prior knowl- edge. In reconstructing the ROI source signals from simulated data, STFT-R achieved smaller errors than a two-step method using the popular minimum-norm estimate (MNE), and in a real-world human learning experiment, STFT-R yielded more interpretable results about what time-frequency components of the ROI signals were correlated with learning.

stat.AP↗

arXiv2014

Binocular parallax stereo imaging based on correlation matching algorithm

The intensity fluctuation correlation of pseudo-thermal light can be utilized to realize binocular parallax stereo imaging (BPSI). With the help of correlation matching algorithm, the matching precision of feature points can reach one pixel authentically. The implementations of the proposed BPSI system with real objects were demonstrated in detail. And the experimental results indicated that the proposed system performs better when the object's superficial characteristics are not obvious, for example its surface reflectivity is constant.

physics.optics↗

arXiv2014

Epidemic-like Proximity-based Traffic Offloading

Cellular networks are overloaded due to the mobile traffic surge, and mobile social network (MSNets) carrying information flow can help reduce cellular traffic load. If geographically-nearby users directly adopt WiFi or Bluetooth technology (i.e., leveraging proximity-based communication) for information spreading in MSNets, a portion of mobile traffic can be offloaded from cellular networks. For many delay-tolerant applications, it is beneficial for traffic offloading to pick some seed users as information sources, which help further spread the information to others in an epidemic-like manner using proximity-based communication. In this paper, we develop a theoretical framework to study the issue of choosing only k seed users so as to maximize the mobile traffic offloaded from cellular networks via proximity-based communication. We introduce a gossip-style social cascade (GSC) model to model the information diffusion process, which captures the epidemic-like nature of proximity-based communication and characterizes users' social participation as well. For static networks as a special-case study and mobile networks, we establish an equivalent view and a temporal mapping of the information diffusion process, respectively, leveraging virtual coupon collectors. We further prove the submodularity in the information diffusion and propose a greedy algorithm to choose the seed users for proximity-based traffic offloading, yielding a solution within about 63% of the optimal value to the traffic offloading maximization (TOM) problem. Experiments are carried out to study the offloading performance of our approach, illustrating that proximity-based communication can offload cellular traffic by over 60% with a small number of seed users and the greedy algorithm significantly outperforms the heuristic and random algorithms.

cs.IT↗

arXiv2013

Low complexity resource allocation for load minimization in OFDMA wireless networks

To cope with the ever increasing demand for bandwidth, future wireless networks will be designed with reuse distance equal to one. This scenario requires the implementation of techniques able to manage the strong multiple access interference each cell generates towards its neighbor cells. In particular, low complexity and reduced feedback are important requirements for practical algorithms. In this paper we study an allocation problem for OFDMA networks formulated with the objective of minimizing the load of each cell in the system subject to the constraint that each user meets its target rate. We decompose resource allocation into two sub-problems: channel allocation under deterministic power assignment and continuous power assignment optimization. Channel allocation is formulated as the problem of finding the maximum weighted independent set (MWIS) in graph theory. In addition, we propose a minimal weighted-degree greedy (MWDG) algorithm of which the approximation factor is analyzed. For power allocation, an iterative power reassignment algorithm (DPRA) is proposed. The control information requested to perform the allocation is limited and the computational burden is shared between the base station and the user equipments. Simulations have been carried out under constant bit rate traffic model and the results have been compared with other allocation schemes of similar complexity. MWDG has excellent performance and outperforms all other techniques.

cs.IT↗