arXiv subjects

Tingting Zhang

Publications and source records attributed to Tingting Zhang.

78 records · Page 5Linked to original sources

arXiv2016

Blue Phosphorene Oxide: Strain-tunable Quantum Phase Transitions and Novel 2D Emergent Fermions

Tunable quantum phase transitions and novel emergent fermions in solid state materials are fascinating subjects of research. Here, we propose a new stable two-dimensional (2D) material, the blue phosphorene oxide (BPO), which exhibits both. Based on first-principles calculations, we show that its equilibrium state is a narrow-bandgap semiconductor with three bands at low energy. Remarkably, a moderate strain can drive a semiconductor-to-semimetal quantum phase transition in BPO. At the critical transition point, the three bands cross at a single point at Fermi level, around which the quasiparticles are a novel type of 2D pseudospin-1 fermions. Going beyond the transition, the system becomes a symmetry-protected semimetal, for which the conduction and valence bands touch quadratically at a single Fermi point that is protected by symmetry, and the low-energy quasiparticles become another novel type of 2D double Weyl fermions. We construct effective models characterizing the phase transition and these novel emergent fermions, and we point out several exotic effects, including super Klein tunneling, supercollimation, and universal optical absorbance. Our result reveals BPO as an intriguing platform for the exploration of fundamental properties of quantum phase transitions and novel emergent fermions, and also suggests its great potential in nanoscale device applications.

cond-mat.mtrl-sci↗

arXiv2015

Mathematical framework for multi-frequency identification of thin insulating and small conductive inhomogeneities

We are aiming to identify the thin insulating inhomogeneities and small conductive inhomogeneities inside an electrically conducting medium by using multi-frequency electrical impedance tomography (mfEIT). The thin insulating inhomogeneities are considered in the form of tubular neighborhood of a curve and small conductive inhomogeneities are regarded as circular disks. Taking advantage of the frequency dependent behavior of insulating objects, we give a rigorous derivation of the potential along thin insulating objects at various frequencies. Asymptotic formula is given to analyze relationship between inhomogeneities and boundary potential at different frequencies. In numerical simulations, spectroscopic images are provided to visualize the reconstructed admittivity at various frequencies. For the view of both kinds of inhomogeneities, an integrated reconstructed image based on principle component analysis (PCA) is provided. Phantom experiments are performed by using Swisstom EIT-Pioneer Set.

math.AP↗

arXiv2015

Spatial Bayesian variable selection and grouping for high-dimensional scalar-on-image regression

Multi-subject functional magnetic resonance imaging (fMRI) data has been increasingly used to study the population-wide relationship between human brain activity and individual biological or behavioral traits. A common method is to regress the scalar individual response on imaging predictors, known as a scalar-on-image (SI) regression. Analysis and computation of such massive and noisy data with complex spatio-temporal correlation structure is challenging. In this article, motivated by a psychological study on human affective feelings using fMRI, we propose a joint Ising and Dirichlet Process (Ising-DP) prior within the framework of Bayesian stochastic search variable selection for selecting brain voxels in high-dimensional SI regressions. The Ising component of the prior makes use of the spatial information between voxels, and the DP component groups the coefficients of the large number of voxels to a small set of values and thus greatly reduces the posterior computational burden. To address the phase transition phenomenon of the Ising prior, we propose a new analytic approach to derive bounds for the hyperparameters, illustrated on 2- and 3-dimensional lattices. The proposed method is compared with several alternative methods via simulations, and is applied to the fMRI data collected from the KLIFF hand-holding experiment.

stat.AP↗

arXiv2014

End-to-End Reliability-aware Scheduling for Wireless Sensor Networks

Wireless Sensor Networks (WSN) are gaining popularity as a flexible and economical alternative to field-bus installations for monitoring and control applications. For mission-critical applications, communication networks must provide end-to-end reliability guarantees, posing substantial challenges for WSN. Reliability can be improved by redundancy, and is often addressed on the MAC layer by re-submission of lost packets, usually applying slotted scheduling. Recently, researchers have proposed a strategy to optimally improve the reliability of a given schedule by repeating the most rewarding slots in a schedule incrementally until a deadline. This Incrementer can be used with most scheduling algorithms but has scalability issues which narrows its usability to offline calculations of schedules, for networks that are rather static. In this paper, we introduce SchedEx, a generic heuristic scheduling algorithm extension which guarantees a user-defined end-to-end reliability. SchedEx produces competitive schedules to the existing approach, and it does that consistently more than an order of magnitude faster. The harsher the end-to-end reliability demand of the network, the better SchedEx performs compared to the Incrementer. We further show that SchedEx has a more evenly distributed improvement impact on the scheduling algorithms, whereas the Incrementer favors schedules created by certain scheduling algorithms.

cs.NI↗

arXiv2014

Electrical impedance spectroscopy-based nondestructive testing for imaging defects in concrete structures

An electrical impedance spectroscopy-based nondestructive testing (NDT) method is proposed to image both cracks and reinforcing bars in concrete structures. The method utilizes the frequency-dependent behavior of thin insulating cracks: low-frequency electrical currents are blocked by insulating cracks, whereas high-frequency currents can pass through the conducting bars without being blocked by thin cracks. Rigorous mathematical analysis relates the geometric structures of the cracks and bars to the frequency-dependent Neumann-to-Dirichlet data. Various numerical simulations support the feasibility of the proposed method.

math.AP↗

arXiv2011

Nonparametric inference of doubly stochastic Poisson process data via the kernel method

Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based inference method. We conduct a detailed study, including an asymptotic analysis, of the proposed method, and provide guidelines for its practical use, introducing a fast and stable regression method for bandwidth selection. We apply our method to real photon arrival data from recent single-molecule biophysical experiments, investigating proteins' conformational dynamics. Our result shows that conformational fluctuation is widely present in protein systems, and that the fluctuation covers a broad range of time scales, highlighting the dynamic and complex nature of proteins' structure.

stat.AP↗