arXiv subjects

Nan Li

Publications and source records attributed to Nan Li.

At least 325 records · Page 18Linked to original sources

arXiv2018

Mason's theorem with a difference radical

Differential calculus is not a unique way to observe polynomial equations such as $a+b=c$. We propose a way of applying difference calculus to estimate multiplicities of the roots of the polynomials $a$, $b$ and $c$ satisfying the equation above. Then a difference $abc$ theorem for polynomials is proved using a new notion of a radical of a polynomial. Two results on the non-existence of polynomial solutions to difference Fermat type functional equations are given as applications. We also introduce a truncated second main theorem for differences, and use it to consider difference Fermat type equations with transcendental entire solutions.

math.CV↗

arXiv2018

Advancing Tabu and Restart in Local Search for Maximum Weight Cliques

The tabu and restart are two fundamental strategies for local search. In this paper, we improve the local search algorithms for solving the Maximum Weight Clique (MWC) problem by introducing new tabu and restart strategies. Both the tabu and restart strategies proposed are based on the notion of a local search scenario, which involves not only a candidate solution but also the tabu status and unlocking relationship. Compared to the strategy of configuration checking, our tabu mechanism discourages forming a cycle of unlocking operations. Our new restart strategy is based on the re-occurrence of a local search scenario instead of that of a candidate solution. Experimental results show that the resulting MWC solver outperforms several state-of-the-art solvers on the DIMACS, BHOSLIB, and two benchmarks from practical applications.

cs.AI↗

arXiv2018

Graph-based Hypothesis Generation for Parallax-tolerant Image Stitching

The seam-driven approach has been proven fairly effective for parallax-tolerant image stitching, whose strategy is to search for an invisible seam from finite representative hypotheses of local alignment. In this paper, we propose a graph-based hypothesis generation and a seam-guided local alignment for improving the effectiveness and the efficiency of the seam-driven approach. The experiment demonstrates the significant reduction of number of hypotheses and the improved quality of naturalness of final stitching results, comparing to the state-of-the-art method SEAGULL.

cs.CV↗

arXiv2018

Quasi-homography warps in image stitching

The naturalness of warps is gaining extensive attentions in image stitching. Recent warps such as SPHP and AANAP, use global similarity warps to mitigate projective distortion (which enlarges regions), however, they necessarily bring in perspective distortion (which generates inconsistencies). In this paper, we propose a novel quasi-homography warp, which effectively balances the perspective distortion against the projective distortion in the non-overlapping region to create a more natural-looking panorama. Our approach formulates the warp as the solution of a bivariate system, where perspective distortion and projective distortion are characterized as slope preservation and scale linearization respectively. Because our proposed warp only relies on a global homography, thus it is totally parameter-free. A comprehensive experiment shows that a quasi-homography warp outperforms some state-of-the-art warps in urban scenes, including homography, AutoStitch and SPHP. A user study demonstrates that it wins most users' favor, comparing to homography and SPHP.

cs.CV↗

arXiv2018

Single-Perspective Warps in Natural Image Stitching

Results of image stitching can be perceptually divided into single-perspective and multiple-perspective. Compared to the multiple-perspective result, the single-perspective result excels in perspective consistency but suffers from projective distortion. In this paper, we propose two single-perspective warps for natural image stitching. The first one is a parametric warp, which is a combination of the as-projective-as-possible warp and the quasi-homography warp via dual-feature. The second one is a mesh-based warp, which is determined by optimizing a total energy function that simultaneously emphasizes different characteristics of the single-perspective warp, including alignment, naturalness, distortion and saliency. A comprehensive evaluation demonstrates that the proposed warp outperforms some state-of-the-art warps, including homography, APAP, AutoStitch, SPHP and GSP.

cs.CV↗

arXiv2018

A polymer based phononic crystal

A versatile system to construct polymeric phononic crystals by using ultrasound is described. In order to fabricate this material a customised cavity device fitted with a 2 MHz acoustic transducer and an acoustic reflector is employed for standing wave creation in the device chamber. The polymer crystal is formed when the standing waves are created during the polymerisation process. The resulting crystals are reproduced in the shape of the tunable cavity device, and add unique periodic features. Their separation is related to the applied acoustic wave frequency during the fabrication process and their composition was found to be made up to two material phases. To assess the acoustic properties of the polymer crystals their average acoustic velocity is measured relative to monomer solutions of different concentrations. It is demonstrated that one of the signature characteristics of phononic crystal, the slow wave effect, was expressed by the polymer. Furthermore the thickness of a unit cell is analysed from images obtained from an optical microscope. By knowing the thickness the average acoustic velocity is calculated to be 1538 m/s when the monomer/cross-linker concentration is 1.5 M. This numerical calculation closely agrees with the predicted value for this monomer/crosslinker concentration of 1536 m/s. This work provides a methodology for accessing a new type of adaptable phononic crystal based on flexible polymers.

physics.app-ph↗

arXiv2018

tau-FPL: Tolerance-Constrained Learning in Linear Time

Learning a classifier with control on the false-positive rate plays a critical role in many machine learning applications. Existing approaches either introduce prior knowledge dependent label cost or tune parameters based on traditional classifiers, which lack consistency in methodology because they do not strictly adhere to the false-positive rate constraint. In this paper, we propose a novel scoring-thresholding approach, tau-False Positive Learning (tau-FPL) to address this problem. We show the scoring problem which takes the false-positive rate tolerance into accounts can be efficiently solved in linear time, also an out-of-bootstrap thresholding method can transform the learned ranking function into a low false-positive classifier. Both theoretical analysis and experimental results show superior performance of the proposed tau-FPL over existing approaches.

cs.LG↗

arXiv2018

Launch and capture of a single particle in a pulse-laser-assisted dual-beam fiber-optic trap

The rapid loading and manipulation of microspheres in optical trap is important for its applications in optomechanics and precision force sensing. We investigate the microsphere behavior under coaction of a dual-beam fiber-optic trap and a pulse laser beam, which reveals a launched microsphere can be effectively captured in a spatial region. A suitable order of pulse duration for launch is derived according to the calculated detachment energy threshold of pulse laser. Furthermore, we illustrate the effect of structural parameters on the launching process, including the spot size of pulse laser, the vertical displacement of beam waist and the initial position of microsphere. Our result will be instructive in the optimal design of the pulse-laser-assisted optical tweezers for controllable loading mechanism of optical trap.

physics.app-ph↗

arXiv2018

A study of the new hemispherical 9-inch PMT

The new hemispherical photomultiplier tubes (PMTs) with 9 inch diameter from Hainan Zhanchuang Photonics Technology Co.,Ltd (HZC) have been studied. Narrow transit time spread (FWHM=2.35 ns) accompanied by small nonlinearity (750 photoelectrons at 5%) and high gain (1E7 ) with good single photoelectron (PE) resolution have been observed. 11 PMTs of this type are deployed and studied in the prototype detector for JUNO at IHEP, China.

physics.ins-det↗

arXiv2017

Galaxy-galaxy weak-lensing measurement from SDSS: II. host halo properties of galaxy groups

As the second paper of a series on studying galaxy-galaxy lensing signals using the Sloan Digital Sky Survey Data Release 7 (SDSS DR7), we present our measurement and modelling of the lensing signals around groups of galaxies. We divide the groups into four halo mass bins, and measure the signals around four different halo-center tracers: brightest central galaxy (BCG), luminosity-weighted center, number-weighted center and X-ray peak position. For X-ray and SDSS DR7 cross identified groups, we further split the groups into low and high X-ray emission subsamples, both of which are assigned with two halo-center tracers, BCGs and X-ray peak positions. The galaxy-galaxy lensing signals show that BCGs, among the four candidates, are the best halo-center tracers. We model the lensing signals using a combination of four contributions: off-centered NFW host halo profile, sub-halo contribution, stellar contribution, and projected 2-halo term. We sample the posterior of 5 parameters i.e., halo mass, concentration, off-centering distance, sub halo mass, and fraction of subhalos via a MCMC package using the galaxy-galaxy lensing signals. After taking into account the sampling effects (e.g. Eddington bias), we found the best fit halo masses obtained from lensing signals are quite consistent with those obtained in the group catalog based on an abundance matching method, except in the lowest mass bin. Subject headings: (cosmology:) gravitational lensing, galaxies: clusters: general

astro-ph.CO↗

arXiv2017

Mapping the world population one building at a time

High resolution datasets of population density which accurately map sparsely-distributed human populations do not exist at a global scale. Typically, population data is obtained using censuses and statistical modeling. More recently, methods using remotely-sensed data have emerged, capable of effectively identifying urbanized areas. Obtaining high accuracy in estimation of population distribution in rural areas remains a very challenging task due to the simultaneous requirements of sufficient sensitivity and resolution to detect very sparse populations through remote sensing as well as reliable performance at a global scale. Here, we present a computer vision method based on machine learning to create population maps from satellite imagery at a global scale, with a spatial sensitivity corresponding to individual buildings and suitable for global deployment. By combining this settlement data with census data, we create population maps with ~30 meter resolution for 18 countries. We validate our method, and find that the building identification has an average precision and recall of 0.95 and 0.91, respectively and that the population estimates have a standard error of a factor ~2 or less. Based on our data, we analyze 29 percent of the world population, and show that 99 percent lives within 36 km of the nearest urban cluster. The resulting high-resolution population datasets have applications in infrastructure planning, vaccination campaign planning, disaster response efforts and risk analysis such as high accuracy flood risk analysis.

cs.CV↗

arXiv2017

Epitaxial thin films of pyrochlore iridate Bi_{2+x}Ir_{2-y}O_{7-delta}: structure, defects and transport properties

While pyrochlore iridate thin films are theoretically predicted to possess a variety of emergent topological properties, experimental verification of these predictions can be obstructed by the challenge in thin film growth. Here we report on the pulsed laser deposition and characterization of thin films of a representative pyrochlore compound Bi2Ir2O7. The films were epitaxially grown on yttria-stabilized zirconia substrates and have lattice constants that are a few percent larger than that of the bulk single crystals. The film composition shows a strong dependence on the oxygen partial pressure. Density-functional-theory calculations indicate the existence of Bi_Ir antisite defects, qualitatively consistent with the high Bi: Ir ratio found in the films. Both Ir and Bi have oxidation states that are lower than their nominal values, suggesting the existence of oxygen deficiency. The iridate thin films show a variety of intriguing transport characteristics, including multiple charge carriers, logarithmic dependence of resistance on temperature, antilocalization corrections to conductance due to spin-orbit interactions, and linear positive magnetoresistance.

cond-mat.mtrl-sci↗

arXiv2017

A robust mass estimator for dark matter subhalo perturbations in strong gravitational lenses

A few dark matter substructures have recently been detected in strong gravitational lenses though their perturbations of highly magnified images. We derive a characteristic scale for lensing perturbations and show that this is significantly larger than the perturber's Einstein radius. We show that the perturber's projected mass enclosed within this radius, scaled by the log-slope of the host galaxy's density profile, can be robustly inferred even if the inferred density profile and tidal radius of the perturber are biased. We demonstrate the validity of our analytic derivation by using several gravitational lens simulations where the tidal radii and the inner log-slopes of the density profile of the perturbing subhalo are allowed to vary. By modeling these simulated data we find that our mass estimator, which we call the effective subhalo lensing mass, is accurate to within about 10\% or smaller in each case, whereas the inferred total subhalo mass can potentially be biased by nearly an order of magnitude. We therefore recommend that the effective subhalo lensing mass be reported in future lensing reconstructions, as this will allow for a more accurate comparison with the results of dark matter simulations.

astro-ph.GA↗

arXiv2017

Open-Category Classification by Adversarial Sample Generation

In real-world classification tasks, it is difficult to collect training samples from all possible categories of the environment. Therefore, when an instance of an unseen class appears in the prediction stage, a robust classifier should be able to tell that it is from an unseen class, instead of classifying it to be any known category. In this paper, adopting the idea of adversarial learning, we propose the ASG framework for open-category classification. ASG generates positive and negative samples of seen categories in the unsupervised manner via an adversarial learning strategy. With the generated samples, ASG then learns to tell seen from unseen in the supervised manner. Experiments performed on several datasets show the effectiveness of ASG.

cs.LG↗

arXiv2017

Computing Simple Multiple Zeros of Polynomial Systems

Given a polynomial system f associated with a simple multiple zero x of multiplicity μ, we give a computable lower bound on the minimal distance between the simple multiple zero x and other zeros of f. If x is only given with limited accuracy, we propose a numerical criterion that f is certified to have μ zeros (counting multiplicities) in a small ball around x. Furthermore, for simple double zeros and simple triple zeros whose Jacobian is of normalized form, we define modified Newton iterations and prove the quantified quadratic convergence when the starting point is close to the exact simple multiple zero. For simple multiple zeros of arbitrary multiplicity whose Jacobian matrix may not have a normalized form, we perform unitary transformations and modified Newton iterations, and prove its non-quantified quadratic convergence and its quantified convergence for simple triple zeros.

math.NA↗

arXiv2017

CMU DeepLens: Deep Learning For Automatic Image-based Galaxy-Galaxy Strong Lens Finding

Galaxy-scale strong gravitational lensing is not only a valuable probe of the dark matter distribution of massive galaxies, but can also provide valuable cosmological constraints, either by studying the population of strong lenses or by measuring time delays in lensed quasars. Due to the rarity of galaxy-scale strongly lensed systems, fast and reliable automated lens finding methods will be essential in the era of large surveys such as LSST, Euclid, and WFIRST. To tackle this challenge, we introduce CMU DeepLens, a new fully automated galaxy-galaxy lens finding method based on Deep Learning. This supervised machine learning approach does not require any tuning after the training step which only requires realistic image simulations of strongly lensed systems. We train and validate our model on a set of 20,000 LSST-like mock observations including a range of lensed systems of various sizes and signal-to-noise ratios (S/N). We find on our simulated data set that for a rejection rate of non-lenses of 99%, a completeness of 90% can be achieved for lenses with Einstein radii larger than 1.4" and S/N larger than 20 on individual $g$-band LSST exposures. Finally, we emphasize the importance of realistically complex simulations for training such machine learning methods by demonstrating that the performance of models of significantly different complexities cannot be distinguished on simpler simulations. We make our code publicly available at https://github.com/McWilliamsCenter/CMUDeepLens .

astro-ph.IM↗

arXiv2017

Searching for initial stage of massive star formation around the H II region G18.2-0.3

Sometimes the early star formation can be found in cold and dense molecular clouds, such as infrared dark cloud (IRDC). Considering star formation often occurs in clustered condition, HII regions may be triggering a new generation of star formation, so we can search for initial stage of massive star formation around HII regions. Based on that above, this work is to introduce one method of how to search for initial stage of massive star formation around HII regions. Towards one sample of the HII region G18.2-0.3, multiwavelength observations are carried out to investigate its physical condition. In contrast and analysis, we find three potential initial stages of massive star formation, suggesting that it is feasible to search for initial stage of massive star formation around HII regions.

astro-ph.GA↗

arXiv2017

Perception-based energy functions in seam-cutting

Image stitching is challenging in consumer-level photography, due to alignment difficulties in unconstrained shooting environment. Recent studies show that seam-cutting approaches can effectively relieve artifacts generated by local misalignment. Normally, seam-cutting is described in terms of energy minimization, however, few of existing methods consider human perception in their energy functions, which sometimes causes that a seam with minimum energy is not most invisible in the overlapping region. In this paper, we propose a novel perception-based energy function in the seam-cutting framework, which considers the nonlinearity and the nonuniformity of human perception in energy minimization. Our perception-based approach adopts a sigmoid metric to characterize the perception of color discrimination, and a saliency weight to simulate that human eyes incline to pay more attention to salient objects. In addition, our seam-cutting composition can be easily implemented into other stitching pipelines. Experiments show that our method outperforms the seam-cutting method of the normal energy function, and a user study demonstrates that our composed results are more consistent with human perception.

cs.CV↗