arXiv subjects

Yi Jiang

Publications and source records attributed to Yi Jiang.

At least 217 records · Page 12Linked to original sources

arXiv2020

Maximization and Minimization of Interfacial Thermal Conductance by Modulating the Mass Distribution of Interlayer

Tuning interfacial thermal conductance has been a key task for the thermal management of nanoelectronic devices. Here, it is studied how the interfacial thermal conductance is great influenced by modulating the mass distribution of the interlayer of one-dimensional atomic chain. By nonequilibrium Green's function and machine learning algorithm, the maximum/minimum value of thermal conductance and its corresponding mass distribution are calculated. Interestingly, the mass distribution corresponding to the maximum thermal conductance is not a simple function, such as linear and exponential distribution predicted in previous works, it is similar to a sinusoidal curve around linear distribution for larger thickness interlayer. Further, the mechanism of the abnormal results is explained by analyzing the phonon transmission spectra and density of states. The work provides deep insight into optimizing and designing interfacial thermal conductance by modulating mass distribution of interlayer atoms.

cond-mat.mtrl-sci↗

arXiv2020

Involution on pseudoisotopy spaces and the space of nonnegatively curved metrics

We prove that certain involutions defined by Vogell and Burghelea-Fiedorowicz on the rational algebraic $K$-theory of spaces coincide. This gives a way to compute the positive and negative eigenspaces of the involution on rational homotopy groups of pseudoisotopy spaces from the involution on rational $S^{1}$-equivariant homology group of the free loop space of a simply-connected manifold. As an application, we give explicit dimensions of the open manifolds $V$ that appear in Belegradek-Farrell-Kapovitch's work for which the spaces of complete nonnegatively curved metrics on $V$ have nontrivial rational homotopy groups.

math.GT↗

arXiv2020

Same data may bring conflict results: a caution to use the disruptive index

In the last two decades, scholars have designed various types of bibliographic related indicators to identify breakthrough-class academic achievements. In this study, we take a further step to look at properties of the promising disruptive index, thus deepening our understanding of this index and further facilitating its wise use in bibliometrics. Using publication records for Nobel laureates between 1900 and 2016, we calculate the DI of Nobel Prize-winning articles and its benchmark articles in each year and use the median DI to denote the central tendency in each year, and compare results between Medicine, Chemistry, and Physics. We find that conclusions based on DI depend on the length of their citation time window, and different citation time windows may cause different, even controversial, results. Also, discipline and time play a role on the length of citation window when using DI to measure the innovativeness of a scientific work. Finally, not all articles with DI equals to 1 were the breakthrough-class achievements. In other words, the DI stands up theoretically, but we should not neglect that the DI was only shaped by the number of citing articles and times the references have been cited, these data may vary from database to database.

cs.DL↗

arXiv2020

Worm-algorithm-type Simulation of Quantum Transverse-Field Ising Model

We apply a worm algorithm to simulate the quantum transverse-field Ising model in a path-integral representation of which the expansion basis is taken as the spin component along the external-field direction. In such a representation, a configuration can be regarded as a set of non-intersecting loops constructed by "kinks" for pairwise interactions and spin-down (or -up) imaginary-time segments. The wrapping probability for spin-down loops, a dimensionless quantity characterizing the loop topology on a torus, is observed to exhibit small finite-size corrections and yields a high-precision critical point in two dimensions (2D) as $h_c \! =\! 3.044\, 330(6)$, significantly improving over the existing results and nearly excluding the best one $h_c \! =\! 3.044\, 38 (2)$. At criticality, the fractal dimensions of the loops are estimated as $d_{\ell \downarrow} (1{\rm D}) \! = \! 1.37(1) \! \approx \! 11/8 $ and $d_{\ell \downarrow} (2{\rm D}) \! = \! 1.75 (3)$, consistent with those for the classical 2D and 3D O(1) loop model, respectively. An interesting feature is that in one dimension (1D), both the spin-down and -up loops display the critical behavior in the whole disordered phase ($ 0 \! \leq \! h \! < \! h_c$), having a fractal dimension $d_{\ell} \! = \! 1.750 (7)$ that is consistent with the hull dimension $d_{\rm H} \! = \! 7/4$ for critical 2D percolation clusters. The current worm algorithm can be applied to simulate other quantum systems like hard-core boson models with pairing interactions.

cond-mat.stat-mech↗

arXiv2020

Measuring the linear and nonlinear elastic properties of brain tissue with shear waves and inverse analysis

We use supersonic shear wave imaging (SSI) technique to measure not only the linear but also the nonlinear elastic properties of brain matter. Here, we tested six porcine brains ex vivo and measured the velocities of the plane shear waves induced by acoustic radiation force at different states of pre-deformation when the ultrasonic probe is pushed into the soft tissue. We relied on an inverse method based on the theory governing the propagation of small-amplitude acoustic waves in deformed solids to interpret the experimental data. We found that, depending on the subjects, the resulting initial shear modulus mu0 varies from 1.8 to 3.2 kPa, the stiffening parameter b of the hyperelastic Demiray-Fung model from 0.13 to 0.73, and the third- (A) and fourth-order (D) constants of weakly nonlinear elasticity from -1.3 to -20.6 kPa and from 3.1 to 8.7 kPa, respectively. Paired t-test performed on the experimental results of the left and right lobes of the brain shows no significant difference. These values are in line with those reported in the literature on brain tissue, indicating that the SSI method, combined to the inverse analysis, is an efficient and powerful tool for the mechanical characterization of brain tissue, which is of great importance for computer simulation of traumatic brain injury and virtual neurosurgery.

cond-mat.soft↗

arXiv2020

Deep Learning Methods for Lung Cancer Segmentation in Whole-slide Histopathology Images -- the ACDC@LungHP Challenge 2019

Accurate segmentation of lung cancer in pathology slides is a critical step in improving patient care. We proposed the ACDC@LungHP (Automatic Cancer Detection and Classification in Whole-slide Lung Histopathology) challenge for evaluating different computer-aided diagnosis (CADs) methods on the automatic diagnosis of lung cancer. The ACDC@LungHP 2019 focused on segmentation (pixel-wise detection) of cancer tissue in whole slide imaging (WSI), using an annotated dataset of 150 training images and 50 test images from 200 patients. This paper reviews this challenge and summarizes the top 10 submitted methods for lung cancer segmentation. All methods were evaluated using the false positive rate, false negative rate, and DICE coefficient (DC). The DC ranged from 0.7354$\pm$0.1149 to 0.8372$\pm$0.0858. The DC of the best method was close to the inter-observer agreement (0.8398$\pm$0.0890). All methods were based on deep learning and categorized into two groups: multi-model method and single model method. In general, multi-model methods were significantly better ($\textit{p}$<$0.01$) than single model methods, with mean DC of 0.7966 and 0.7544, respectively. Deep learning based methods could potentially help pathologists find suspicious regions for further analysis of lung cancer in WSI.

eess.IV↗

arXiv2020

QCD Corrections to $e^+e^- \rightarrow H^{\pm}W^{\mp}$ in Type-I THDM at Electron Positron Colliders

We investigate in detail the charged Higgs production associated with a $W$ boson at electron-positron colliders within the framework of the Type-I two-Higgs-doublet model (THDM). We calculate the integrated cross section at the LO and analyze the dependence of the cross section on the THDM parameters and the colliding energy in a benchmark scenario of the input parameters of Higgs sector. The numerical results show that the integrated cross section is sensitive to the charged Higgs mass, especially in the vicinity of $m_{H^{\pm}} \simeq 184~ {\rm GeV}$ at a $500~ {\rm GeV}$ $e^+e^-$ collider, and decreases consistently as the increment of $\tanβ$ in the low $\tanβ$ region. The peak in the colliding energy distribution of the cross section arises from the resonance of loop integrals and its position moves towards low colliding energy as the increment of $m_{H^{\pm}}$. We also study the two-loop NLO QCD corrections to both the integrated cross section and the angular distribution of the charged Higgs boson, and find that the QCD relative correction is also sensitive to the charged Higgs mass and strongly depends on the final-state phase space. For $\tanβ= 2$, the QCD relative correction at a $500~ {\rm GeV}$ $e^+e^-$ collider varies in the range of $[-10\%,\, 11\%]$ as $m_{H^{\pm}}$ increases from $150$ to $400~ {\rm GeV}$.

hep-ph↗

arXiv2020

$WWγ$ production at hadron colliders with NLO QCD+EW corrections and parton shower effects

$W^+W^-γ$ production in proton-proton collision provides a window to the mechanism of electroweak symmetry breaking and a direct accessment to triple and quartic gauge couplings. Precision study of gauge boson self-interactions may also provide evidence of existence of new physics beyond the Standard Model. In this paper, we study the $W^+W^-γ$ production at the LHC and future higher energy proton-proton colliders at the QCD+EW NLO including parton shower effects. We find that the contributions from the photon-induced (i.e., $qγ$- and $γγ$-initiated) channels are non-negligible since the photon luminosity can be enhanced significantly with the increment of colliding energy, and the large real jet emission QCD and EW corrections can be depressed sufficiently by applying the jet veto event selection scheme. Moreover, we also investigate the theoretical errors arising from the PDF uncertainty and the factorization/renormalization scale dependence.

hep-ph↗

arXiv2020

Dynamic Compressed Sensing for Real-Time Tomographic Reconstruction

Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) theory exploits the inherent sparse signal structure to efficiently reconstruct three-dimensional (3D) volumes at the nanoscale from undersampled measurements. However, the process bottlenecks 3D reconstruction with computation times that run from hours to days. Here we demonstrate a framework for dynamic compressed sensing that produces a 3D specimen structure that updates in real-time as new specimen projections are collected. Researchers can begin interpreting 3D specimens as data is collected to facilitate high-throughput and interactive analysis. Using scanning transmission electron microscopy (STEM), we show that dynamic compressed sensing accelerates the convergence speed by 3-fold while also reducing its error by 27% for an Au/SrTiO3 nanoparticle specimen. Before a tomography experiment is completed, the 3D tomogram has interpretable structure within 33% of completion and fine details are visible as early as 66%. Upon completion of an experiment, a high-fidelity 3D visualization is produced without further delay. Additionally, reconstruction parameters that tune data fidelity can be manipulated throughout the computation without rerunning the entire process.

physics.comp-ph↗

arXiv2020

Learning to Segment the Tail

Real-world visual recognition requires handling the extreme sample imbalance in large-scale long-tailed data. We propose a "divide&conquer" strategy for the challenging LVIS task: divide the whole data into balanced parts and then apply incremental learning to conquer each one. This derives a novel learning paradigm: class-incremental few-shot learning, which is especially effective for the challenge evolving over time: 1) the class imbalance among the old-class knowledge review and 2) the few-shot data in new-class learning. We call our approach Learning to Segment the Tail (LST). In particular, we design an instance-level balanced replay scheme, which is a memory-efficient approximation to balance the instance-level samples from the old-class images. We also propose to use a meta-module for new-class learning, where the module parameters are shared across incremental phases, gaining the learning-to-learn knowledge incrementally, from the data-rich head to the data-poor tail. We empirically show that: at the expense of a little sacrifice of head-class forgetting, we can gain a significant 8.3% AP improvement for the tail classes with less than 10 instances, achieving an overall 2.0% AP boost for the whole 1,230 classes.

cs.CV↗

arXiv2020

Discontinuity-resolving shock-capturing schemes on unstructured grids

Solving compressible flows containing discontinuities remains a major challenge for numerical methods especially on unstructured grids. Thus in this work, we make contributions to shock capturing schemes on unstructured grids with aim of resolving discontinuities with low numerical dissipation. Different from conventional shock capturing schemes which only use polynomials as interpolation functions on unstructured grids, the proposed scheme employs the linear polynomial as well as non-polynomial as reconstruction candidates. For linear polynomial, the second order MUSCL scheme with the MLP (Multi-dimensional Limiting Process) slope limiter is adopted. The multi-dimensional THINC (Tangent of Hyperbola for INterface Capturing) function with quadratic surface representation and Gaussian quadrature, so-called THINC/QQ, is used as the non-polynomial reconstruction candidate. With these reconstruction candidates, a multi-stage boundary variation diminishing (BVD) algorithm which aims to minimize numerical dissipation is designed on unstructured grids to select the final reconstruction function. The resulted shock capturing scheme is named as MUSCL-THINC/QQ-BVD. The performance of the proposed scheme is demonstrated through solving compressible single-phase and multi-phase problems where the discontinuity is the typical flow structure. The numerical results show that the proposed scheme is capable of capturing sharp discontinuous profiles without numerical oscillations as well as resolving vortices associated with Kelvin-Helmholtz instabilities along shear layers and material interfaces. In comparison with schemes only replying on high order polynomials, the proposed scheme shows significant improvement of resolution across discontinuities. Thus, this work provides an accurate and robust shock-capturing scheme to resolve discontinuities in compressible flows.

physics.comp-ph↗

arXiv2019

Physics of Electrostatic Projection Revealed by High-Speed Video Imaging

Processes based on electrostatic projection are used extensively in industry, e.g. for mineral separations, electrophotography or manufacturing of coated abrasives, such as sandpaper. Despite decades of engineering practice, there are still unanswered questions. In this paper, we present a comprehensive experimental study of projection process of more than 1500 individual spherical alumina particles with a nominal size of 500 $μ$m, captured by high-speed video imaging and digital image analysis. Based on flight trajectories of approximately 1100 projected particles, we determined the acquired charge and dynamics as a function of relative humidity (RH) and electric field intensity and compared the results with classical theories. For RH levels of 50\% and above, more than 85\% of disposed particles were projected, even when the electric field intensity was at its minimum level. This suggests that, beyond a critical value of electric field intensity, relative humidity plays a more critical role in the projection process. We also observed that the charging time is reduced dramatically for RH levels of 50\% and above, possibly due to the build-up of thin water films around the particles which can facilitate charge transfer. In contrast, projected particles at 30\% RH level exhibited an excessive amount of electric charge, between two to four times than that of saturation value, which might be attributed to triboelectric charging effects. Finally, the physics of electrostatic projection is compared and contrasted with those of induced-charge electrokinetic phenomena, which share similar field-square scaling, as the applied field acts on its own induced charge to cause particle motion.

cond-mat.soft↗

arXiv2019

Precision study of $W^-W^+H$ production including parton shower effects at the CERN Large Hadron Collider

The precision study of $W^-W^+H$ production with subsequent $W^{\pm} \rightarrow l^{\pm} \overset{ _{(-)}}{ν_{l}}$ and $H \rightarrow b\bar{b}$ decays at the LHC can help us to study the Higgs gauge couplings and to search for new physics beyond the SM. In this paper, we calculate the shower-matched NLO QCD correction and the EW corrections from the $q\bar{q}$ annihilation and photon-induced channels to the $W^-W^+H$ production at the $14~ {\rm TeV}$ LHC, and deal with the subsequent decays of Higgs and $W^{\pm}$ bosons by adopting the {\sc MadSpin} method. Both the integrated cross section and some kinematic distributions of $W^{\pm}$, $H$ and their decay products are provided. We find that the QCD correction enhances the LO differential cross section significantly, while the EW correction from the $q\bar{q}$ annihilation channel obviously suppresses the LO differential cross section, especially in the high energy phase-space region due to the Sudakov effect. The $qγ$- and $γγ$-induced relative corrections are positive, and insensitive to the transverse momenta of $W^{\pm}$, $H$ and their decay products. These photon-induced corrections compensate the negative $q\bar{q}$-initiated EW correction, and become the dominant EW contribution as the increment of the $pp$ colliding energy. The parton shower (PS) effects on the kinematic distributions are nonnegligible. The PS relative correction to the $b$-jet transverse momentum distribution can exceed $100\%$ in the high $p_{T, b}$ region. We also investigate the scale and PDF uncertainties, and find that the theoretical error of the ${\rm QCD}+{\rm EW}+qγ+γγ$ corrected integrated cross section mainly comes from the renormalization scale dependence of the QCD correction.

hep-ph↗

arXiv2019

Negatively curved bundles in the Igusa stable range

We use classical results in smoothing theory to extract information about the rational homotopy groups of the space of negatively curved metrics on a high dimensional manifold. It is also shown that smooth M-bundles over spheres equipped with fiberwise negatively curved metrics, represent elements of finite order in the homotopy groups of the classifying space for smooth M-bundles, provided the dimension of M is large enough.

math.GT↗

arXiv2019

Sampling Limits for Electron Tomography with Sparsity-exploiting Reconstructions

Electron tomography (ET) has become a standard technique for 3D characterization of materials at the nano-scale. Traditional reconstruction algorithms such as weighted back projection suffer from disruptive artifacts with insufficient projections. Popularized by compressed sensing, sparsity-exploiting algorithms have been applied to experimental ET data and show promise for improving reconstruction quality or reducing the total beam dose applied to a specimen. Nevertheless, theoretical bounds for these methods have been less explored in the context of ET applications. Here, we perform numerical simulations to investigate performance of l_1-norm and total-variation (TV) minimization under various imaging conditions. From 36,100 different simulated structures, our results show specimens with more complex structures generally require more projections for exact reconstruction. However, once sufficient data is acquired, dividing the beam dose over more projections provides no improvements - analogous to the traditional dose-fraction theorem. Moreover, a limited tilt range of +-75 or less can result in distorting artifacts in sparsity-exploiting reconstructions. The influence of optimization parameters on reconstructions is also discussed.

cs.CV↗

arXiv2019

SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition

Object detection and instance recognition play a central role in many AI applications like autonomous driving, video surveillance and medical image analysis. However, training object detection models on large scale datasets remains computationally expensive and time consuming. This paper presents an efficient and open source object detection framework called SimpleDet which enables the training of state-of-the-art detection models on consumer grade hardware at large scale. SimpleDet supports up-to-date detection models with best practice. SimpleDet also supports distributed training with near linear scaling out of box. Codes, examples and documents of SimpleDet can be found at https://github.com/tusimple/simpledet .

cs.CV↗

arXiv2019

Removing Stripes, Scratches, and Curtaining with Non-Recoverable Compressed Sensing

Highly-directional image artifacts such as ion mill curtaining, mechanical scratches, or image striping from beam instability degrade the interpretability of micrographs. These unwanted, aperiodic features extend the image along a primary direction and occupy a small wedge of information in Fourier space. Deleting this wedge of data replaces stripes, scratches, or curtaining, with more complex streaking and blurring artifacts-known within the tomography community as missing wedge artifacts. Here, we overcome this problem by recovering the missing region using total variation minimization, which leverages image sparsity based reconstruction techniques-colloquially referred to as compressed sensing-to reliably restore images corrupted by stripe like features. Our approach removes beam instability, ion mill curtaining, mechanical scratches, or any stripe features and remains robust at low signal-to-noise. The success of this approach is achieved by exploiting compressed sensings inability to recover directional structures that are highly localized and missing in Fourier Space.

cs.CV↗

arXiv2018

$H_5^{\pm\pm}h^0$ production via vector-boson fusion in Georgi-Machacek model at hadron colliders

The Georgi-Machacek (GM) model is a distinctive TeV-scale extension of the Standard Model (SM) due to the introduction of two (one real and one complex) scalar triplets to the Higgs sector. It predicts the existence of doubly charged Higgs bosons $H_5^{\pm\pm}$ and the vacuum expectation value of Higgs triplets $v_Δ$ can reach a few tens of GeV. In this paper, we perform a parameter scan of the GM model within the H5plane benchmark scenario and investigate in detail the single production of a doubly charged Higgs boson in association with a SM-like Higgs boson via vector-boson fusion at the $14~ {\rm TeV}$ LHC and $70~ {\rm TeV}$ Super Proton-Proton Collider. Both integrated cross section and differential distributions with respect to some kinematic variables for $pp \rightarrow W^{\pm}W^{\pm} \rightarrow H_5^{\pm\pm} h^0 + 2\, {\rm jets}$ are provided up to the QCD next-to-leading order. In the signal-background analysis we employ the {\sc madspin} method to take into account the spin correlation and finite width effects of the intermediate Higgs and $W$ bosons and present some kinematic distributions of final leptons. The numerical results show that the SM background can be suppressed remarkably and the $H_5^{\pm\pm} h^0$ vector-boson fusion signal can be directly detected at future high-luminosity, high-energy hadron colliders by imposing a proper cut on the transverse mass $M_{T, \ell_1 \ell_2}$.

hep-ph↗