arXiv subjects

Hao Gao

Publications and source records attributed to Hao Gao.

78 records · Page 5Linked to original sources

arXiv2017

Topological Dirac line nodes and superconductivity coexist in SnSe at high pressure

Due to fundamental interest and potential applications in quantum computation, tremendous efforts have been invested to study topological superconductivity. However, bulk topological superconductivity seems to be difficult to realize and its mechanism is still elusive. Several possible routes to induce topological superconductivity have been proposed, including proximity efforts, doping or pressurizing a topological insulator or semimetal. Among them, the pressurizing is considered to be a clean way to tune the electronic structures. Here we report the discovery of a pressure-induced topological and superconducting phase of SnSe, a material which is highly focused recently due to its superior thermoelectric properties. In situ high-pressure electrical transport and synchrotron X-ray diffraction measurements show that the superconductivity emerges along with the formation of a CsCl-type structural symmetry of SnSe above around 27 GPa, with a maximum critical temperature of 3.2 K at 39 GPa. Based on ab initio calculations, this CsCl-type SnSe is predicted to be a Dirac line nodes (DLN) semimetal in the absence of spin-orbit coupling, whose DLN states are protected by the coexistence of time-reversal and inversion symmetries. These results make CsCl-type SnSe an interesting model platform with simple crystal symmetry to study the interplay of topological physics and superconductivity.

cond-mat.mtrl-sci↗

arXiv2016

Fused Analytical and Iterative Reconstruction (AIR) via modified proximal forward-backward splitting: a FDK-based iterative image reconstruction example for CBCT

This work is to develop a general framework, namely analytical iterative reconstruction (AIR) method, to incorporate analytical reconstruction (AR) method into iterative reconstruction (IR) method, for enhanced CT image quality and reconstruction efficiency. Specifically, AIR is established based on the modified proximal forward-backward splitting (PFBS) algorithm, and its connection to the filtered data fidelity with sparsity regularization is discussed. As a result, AIR decouples data fidelity and image regularization with a two-step iterative scheme, during which an AR-projection step updates the filtered data fidelity term, while a denoising solver updates the sparsity regularization term. During the AR-projection step, the image is projected to the data domain to form the data residual, and then reconstructed by certain AR to a residual image which is then weighted together with previous image iterate to form next image iterate. Intuitively since the eigenvalues of AR-projection operator are close to the unity, PFBS based AIR has a fast convergence. Such an advantage is rigorously established through convergence analysis and numerical computation of convergence rate. The proposed AIR method is validated in the setting of circular cone-beam CT with AR being FDK and total-variation sparsity regularization, and has improved image quality from both AR and IR. For example, AIR has improved visual assessment and quantitative measurement in terms of both contrast and resolution, and reduced axial and half-fan artifacts.

physics.med-ph↗

arXiv2016

Origin of the superconductivity of WTe2 under pressure

Tungsten ditelluride (WTe2) has attracted significant attention due to its interesting electronic properties, such as the unsaturated magnetoresistance and superconductivity. Recently, it has been proposed to be a new type of Weyl semimetal, which is distinguished from other transition metal dichalcogenides (TMDs) from a topological prospective. Here, we study the structure of WTe2 under pressure with a crystal structure prediction and ab initio calculations combined with high pressure synchrotron X-ray diffraction and Raman spectroscopy measurements. We find that the ambient orthorhombic structure (Td) transforms into a monoclinic structure (1T') at around 4-5 GPa. As the transition pressure is very close to the critical point in recent high-pressure electrical transport measurements, the emergence of superconductivity in WTe2 under pressure is attributed to the Td-1T' structure phase transition, which associates with a sliding mechanism of the TMD layers and results in a shorter Te-Te interlayer distance compared to the intralayer ones. These results highlight the critical role of the interlayer stacking and chalcogen interactions on the electronic and superconducting properties of multilayered TMDs under hydrostatic strain environments.

cond-mat.mtrl-sci↗

arXiv2013

AIR: fused Analytical and Iterative Reconstruction method for computed tomography

Purpose: CT image reconstruction techniques have two major categories: analytical reconstruction (AR) method and iterative reconstruction (IR) method. AR reconstructs images through analytical formulas, such as filtered backprojection (FBP) in 2D and Feldkamp-Davis-Kress (FDK) method in 3D, which can be either mathematically exact or approximate. On the other hand, IR is often based on the discrete forward model of X-ray transform and formulated as a minimization problem with some appropriate image regularization method, so that the reconstructed image corresponds to the minimizer of the optimization problem. This work is to investigate the fused analytical and iterative reconstruction (AIR) method. Methods: Based on IR with L1-type image regularization, AIR is formulated with a AR-specific preconditioner in the data fidelity term, which results in the minimal change of the solution algorithm that replaces the adjoint X-ray transform by the filtered X-ray transform. As a proof-of-concept 2D example of AIR, FBP is incorporated into tensor framelet (TF) regularization based IR, and the formulated AIR minimization problem is then solved through split Bregman method with GPU-accelerated X-ray transform and filtered adjoint X-ray transform. Conclusion: AIR, the fused Analytical and Iterative Reconstruction method, is proposed with a proof-of-concept 2D example to synergize FBP and TF-regularized IR, with improved image resolution and contrast for experimental data. The potential impact of AIR is that it offers a general framework to develop various AR enhanced IR methods, when neither AR nor IR alone is sufficient.

physics.med-ph↗

arXiv2012

Cine cone beam CT reconstruction using low-rank matrix factorization: algorithm and a proof-of-princple study

Respiration-correlated CBCT, commonly called 4DCBCT, provide respiratory phase-resolved CBCT images. In many clinical applications, it is more preferable to reconstruct true 4DCBCT with the 4th dimension being time, i.e., each CBCT image is reconstructed based on the corresponding instantaneous projection. We propose in this work a novel algorithm for the reconstruction of this truly time-resolved CBCT, called cine-CBCT, by effectively utilizing the underlying temporal coherence, such as periodicity or repetition, in those cine-CBCT images. Assuming each column of the matrix $\bm{U}$ represents a CBCT image to be reconstructed and the total number of columns is the same as the number of projections, the central idea of our algorithm is that the rank of $\bm{U}$ is much smaller than the number of projections and we can use a matrix factorization form $\bm{U}=\bm{L}\bm{R}$ for $\bm{U}$. The number of columns for the matrix $\bm{L}$ constraints the rank of $\bm{U}$ and hence implicitly imposing a temporal coherence condition among all the images in cine-CBCT. The desired image properties in $\bm{L}$ and the periodicity of the breathing pattern are achieved by penalizing the sparsity of the tight wavelet frame transform of $\bm{L}$ and that of the Fourier transform of $\bm{R}$, respectively. A split Bregman method is used to solve the problem. In this paper we focus on presenting this new algorithm and showing the proof of principle using simulation studies on an NCAT phantom.

physics.med-ph↗

arXiv2011

Omni-tomography/Multi-tomography -- Integrating Multiple Modalities for Simultaneous Imaging

Current tomographic imaging systems need major improvements, especially when multi-dimensional, multi-scale, multi-temporal and multi-parametric phenomena are under investigation. Both preclinical and clinical imaging now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities to define morphologic details, delineate interval changes due to disease or interventions, and study physiological functions that have interconnected aspects. Over the past decade, fusion of multimodality images has emerged with two different approaches: post-hoc image registration and combined acquisition on PET-CT, PET-MRI and other hybrid scanners. There are intrinsic limitations for both the post-hoc image analysis and dual/triple modality approaches defined by registration errors and physical constraints in the acquisition chain. We envision that tomography will evolve beyond current modality fusion and towards grand fusion, a large scale fusion of all or many imaging modalities, which may be referred to as omni-tomography or multi-tomography. Unlike modality fusion, grand fusion is here proposed for truly simultaneous but often localized reconstruction in terms of all or many relevant imaging mechanisms such as CT, MRI, PET, SPECT, US, optical, and possibly more. In this paper, the technical basis for omni-tomography is introduced and illustrated with a top-level design of a next generation scanner, interior tomographic reconstructions of representative modalities, and anticipated applications of omni-tomography.

physics.med-ph↗