arXiv subjects

Jin Li

Publications and source records attributed to Jin Li.

At least 271 records · Page 15Linked to original sources

arXiv2019

Stone-Wales graphene: A Two Dimensional Carbon Semi-Metal with Magic Stability

A two-dimensional carbon allotrope, Stone-Wales graphene, is identified in stochastic group and graph constrained searches and systematically investigated by first-principles calculations. Stone-Wales graphene consists of well-arranged Stone-Wales defects, and it can be constructed through a 90$^\circ$ bond-rotation in a $\sqrt{8}$$\times$$\sqrt{8}$ super-cell of graphene. Its calculated energy relative to graphene, +149 meV/atom, makes it more stable than the most competitive previously suggested graphene allotropes. We find that Stone-Wales graphene based on a $\sqrt{8}$ super-cell is more stable than those based on $\sqrt{9} \times \sqrt{9}$, $\sqrt{12} \times \sqrt{12}$ and $\sqrt{13} \times \sqrt{13}$ super-cells, and is a "magic size" that can be further understood through a simple "energy splitting and inversion" model. The calculated vibrational properties and molecular dynamics of SW-graphene confirm that it is dynamically stable. The electronic structure shows SW-graphene is a semimetal with distorted, strongly anisotropic Dirac cones.

cond-mat.mtrl-sci↗

arXiv2018

Double Adaptive Stochastic Gradient Optimization

Adaptive moment methods have been remarkably successful in deep learning optimization, particularly in the presence of noisy and/or sparse gradients. We further the advantages of adaptive moment techniques by proposing a family of double adaptive stochastic gradient methods~\textsc{DASGrad}. They leverage the complementary ideas of the adaptive moment algorithms widely used by deep learning community, and recent advances in adaptive probabilistic algorithms.We analyze the theoretical convergence improvements of our approach in a stochastic convex optimization setting, and provide empirical validation of our findings with convex and non convex objectives. We observe that the benefits of~\textsc{DASGrad} increase with the model complexity and variability of the gradients, and we explore the resulting utility in extensions of distribution-matching multitask learning.

stat.ML↗

arXiv2018

Directional fast neutron detection using a time projection chamber and plastic scintillation detectors

A new method for directional fast neutron detection is proposed based on a neutron time projection chamber (TPC) and position-sensitive plastic scintillation detectors. The detection system can efficiently locate the approximate location of a hot spot with 4π field-of-view using only the neutron TPC. Then, the system generates a high-resolution image of the hot spot using selected coincidence events in the TPC and the scintillation detectors. A prototype was built and tested using a Cf-252 source. An efficiency of 7.1x10-3 was achieved for fast searching. The angular resolution was 7.8° (full width at half maximum, FWHM) for high-resolution imaging using the simple back projection method.

physics.ins-det↗

arXiv2018

Security Matters: A Survey on Adversarial Machine Learning

Adversarial machine learning is a fast growing research area, which considers the scenarios when machine learning systems may face potential adversarial attackers, who intentionally synthesize input data to make a well-trained model to make mistake. It always involves a defending side, usually a classifier, and an attacking side that aims to cause incorrect output. The earliest studies on the adversarial examples for machine learning algorithms start from the information security area, which considers a much wider varieties of attacking methods. But recent research focus that popularized by the deep learning community places strong emphasis on how the "imperceivable" perturbations on the normal inputs may cause dramatic mistakes by the deep learning with supposed super-human accuracy. This paper serves to give a comprehensive introduction to a range of aspects of the adversarial deep learning topic, including its foundations, typical attacking and defending strategies, and some extended studies.

cs.LG↗

arXiv2018

Complex low energy tetrahedral polymorphs of group IV elements from first-principles

The energy landscape of carbon is exceedingly complex, hosting diverse and important metastable phases, including diamond, fullerenes, nanotubes and graphene. Searching for structures, especially those with large unit cells, in this landscape is challenging. Here we use a combined stochastic search strategy employing two algorithms (AIRSS and RG2) to apply connectivity constraints to unit cells containing up to 100 carbon atoms. We uncover three low energy carbon polymorphs (Pbam-32, P6/mmm and I-43d) with new topologies, containing 32, 36 and 94 atoms in their primitive cells, respectively. Their energies relative to diamond are 96 meV/atom, 131 meV/atom and 112 meV/atom, respectively, which suggests potential metastability. These three carbon allotropes are mechanically and dynamically stable, insulating carbon crystals with superhard mechanical properties. The I43d structure possesses a direct band gap of 7.25 eV, which is the widest gap in the carbon allotrope family. Silicon, germanium and tin versions of Pbam-32, P6/mmm and I-43d also show energetic, dynamical and mechanical stability. The computed electronic properties show that they are potential materials for semiconductor and photovoltaic applications.

cond-mat.mtrl-sci↗

arXiv2018

A Real-time Robotic Grasp Approach with Oriented Anchor Box

Grasp is an essential skill for robots to interact with humans and the environment. In this paper, we build a vision-based, robust and real-time robotic grasp approach with fully convolutional neural network. The main component of our approach is a grasp detection network with oriented anchor boxes as detection priors. Because the orientation of detected grasps is significant, which determines the rotation angle configuration of the gripper, we propose the Orientation Anchor Box Mechanism to regress grasp angle based on predefined assumption instead of classification or regression without any priors. With oriented anchor boxes, the grasps can be predicted more accurately and efficiently. Besides, to accelerate the network training and further improve the performance of angle regression, Angle Matching is proposed during training instead of Jaccard Index Matching. Five-fold cross validation results demonstrate that our proposed algorithm achieves an accuracy of 98.8% and 97.8% in image-wise split and object-wise split respectively, and the speed of our detection algorithm is 67 FPS with GTX 1080Ti, outperforming all the current state-of-the-art grasp detection algorithms on Cornell Dataset both in speed and accuracy. Robotic experiments demonstrate the robustness and generalization ability in unseen objects and real-world environment, with the average success rate of 90.0% and 84.2% of familiar things and unseen things respectively on Baxter robot platform.

cs.RO↗

arXiv2018

An SOA Based Design of JUNO DAQ Online Software

The Online Software, manager of the JUNO data acquisition (DAQ) system, is composed of many distributed components working coordinately. It takes the responsibility of configuring, processes management, controlling and information sharing etc. The design of service-oriented architecture (SOA) which represents the modern tendency in the distributed system makes the online software lightweight, loosely coupled, reusable, modular, self-contained and easy to be extended. All the services in the SOA distributed online software system will send messages each to another directly without a traditional broker in the middle, which means that services could operate harmoniously and independently. ZeroMQ is chosen but not the only technical choice as the low-level communication middle-ware because of its high performance and convenient communication model while using Google Protocol Buffers as a marshaling library to unify the pattern of message contents. Considering the general requirement of JUNO, the concept of partition and segment are defined to ensure multiple small-scaled DAQs could run simultaneous and easy to join or leave. All running data except the raw physics events will be transmitted, processed and recorded to the database. High availability (HA) is also taken into account to solve the inevitable single point of failure (SPOF) in the distribution system. This paper will introduce all the core services' functionality and techniques in detail.

cs.SE↗

arXiv2018

Reversible Codes and Its Application to Reversible DNA Codes over $F_{4^k}$

Coterm polynomials are introduced by Oztas et al. [a novel approach for constructing reversible codes and applications to DNA codes over the ring $F_2[u]/(u^{2k}-1)$, Finite Fields and Their Applications 46 (2017).pp. 217-234.], which generate reversible codes. In this paper, we generalize the coterm polynomials and construct some reversible codes which are optimal codes by using $m$-quasi-reciprocal polynomials. Moreover, we give a map from DNA $k$-bases to the elements of $F_{4^k}$, and construct reversible DNA codes over $F_{4^k}$ by DNA-$m$-quasi-reciprocal polynomials.

cs.IT↗

arXiv2018

A Model on Heat Signal of Crystal Detector at Low Temperature

We present a model to calculate heat signal shapes from low temperature bolometer attached to a crystal. This model is based on the elementary acoustic wave theory at low temperature, and has been developed using modern Monte Carlo techniques. Physical processes in phonon propagation, such as transmission, scattering and reflection are considered. Using our model, the calculated time dependence of signal agrees with real experimental data. This model has applications in low temperature rare event particle detectors for dark matter and neutrinos.

physics.ins-det↗

arXiv2018

Testing the anisotropy of the universe using the simulated gravitational wave events from advanced LIGO and Virgo

The detection of gravitational waves (GWs) provides a powerful tool to constrain the cosmological parameters. In this paper, we investigate the possibility of using GWs as standard sirens in testing the anisotropy of the universe. We consider the GW signals produced by the coalescence of binary black hole systems and simulate hundreds of GW events from the advanced Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo. It is found that the anisotropy of the universe can be tightly constrained if the redshift of the GW source is precisely known. The anisotropic amplitude can be constrained with an accuracy comparable to the Union2.1 complication of type-Ia supernovae if $\gtrsim 400$ GW events are observed. As for the preferred direction, $\gtrsim 800$ GW events are needed in order to achieve the accuracy of Union2.1. With 800 GW events, the probability of pseudo anisotropic signals with an amplitude comparable to Union2.1 is negligible. These results show that GWs can provide a complementary tool to supernovae in testing the anisotropy of the universe.

astro-ph.CO↗

arXiv2018

The Flash ADC system and PMT waveform reconstruction for the Daya Bay Experiment

To better understand the energy response of the Antineutrino Detector (AD), the Daya Bay Reactor Neutrino Experiment installed a full Flash ADC readout system on one AD that allowed for simultaneous data taking with the current readout system. This paper presents the design, data acquisition, and simulation of the Flash ADC system, and focuses on the PMT waveform reconstruction algorithms. For liquid scintillator calorimetry, the most critical requirement to waveform reconstruction is linearity. Several common reconstruction methods were tested but the linearity performance was not satisfactory. A new method based on the deconvolution technique was developed with 1% residual non-linearity, which fulfills the requirement. The performance was validated with both data and Monte Carlo (MC) simulations, and 1% consistency between them has been achieved.

physics.ins-det↗

arXiv2018

$L_p$ Minkowski Valuations on polytopes

For $1 \leq p < \infty$, Ludwig, Haberl and Parapatits classified $L_p$ Minkowski valuations intertwining the special linear group with additional conditions such as homogeneity and continuity. In this paper,a complete classification of $L_p$ Minkowski valuations intertwining the special linear group on polytopes without any additional conditions is established for $p \geq 1$ including $p = \infty$. For $n=3$ and $p=1$, there exist valuations not mentioned before.

math.MG↗

arXiv2018

Laplace transforms and valuations

It is proved that the classical Laplace transform is a continuous valuation which is positively GL$(n)$ covariant and logarithmic translation covariant. Conversely, these properties turn out to be sufficient to characterize this transform.

math.MG↗

arXiv2018

$L_p$-Blaschke Valuations

In this article, a classification of continuous, linearly intertwining, symmetric $L_p$-Blaschke ($p>1$) valuations is established as an extension of Haberl's work on Blaschke valuations. More precisely, we show that for dimensions $n\geq 3$, the only continuous, linearly intertwining, normalized symmetric $L_p$-Blaschke valuation is the normalized $L_p$-curvature image operator, while for dimension $n = 2 $, a rotated normalized $L_p$-curvature image operator is an only additional one. One of the advantages of our approach is that we deal with normalized symmetric $L_p$-Blaschke valuations, which makes it possible to handle the case $p=n$. The cases where $p \not =n$ are also discussed by studying the relations between symmetric $L_p$-Blaschke valuations and normalized ones.

math.MG↗

arXiv2018

The China Jinping Underground Laboratory and its Early Science

The China Jinping Underground Laboratory, inaugurated in 2010, is an underground research facility with the deepest rock overburden and largest space by volume in the world. The first-generation science programs include dark matter searches conducted by the CDEX and PandaX experiments. These activities are complemented by measurements of ambient radioactivity and installation of low-background counting systems. Phase II of the facility is being constructed, and its potential research projects are being formulated. In this review, we discuss the history, key features, results, and status of this facility and its experimental programs, as well as their future evolution and plans.

hep-ex↗

arXiv2017

Very high frequency gravitational waves from magnetars and gamma-ray burst

Extremely powerful astrophysical electromagnetic (EM) system could be possible source of high-frequency gravitational waves (HFGWs). Here based on properties of magnetars and gamma-ray bursts (GRBs), we address "Gamma-HFGWs" (with very high-frequency around 10^{20}Hz) caused by ultra-strong EM radiations (in the radiation-dominated phase of GRBs fireball) interacting with super-high magnetar surface magnetic fields (around 10^{11}Tesla). By certain parameters of distance and power, the Gamma-HFGWs would have far field energy density around 10^{-6}, and they would cause perturbed signal EM waves of around 10^{-20}Watt/m^2 in planned HFGW detection system based on EM response to GWs. Specially, Gamma-HFGWs would possess distinctive envelopes with characteristic shapes depending on the particular structures of surface magnetic fields of magnetars, which could be exclusive features helpful to distinguish them from background noise. Results obtained suggest that magnetars could involve in possible astrophysical EM sources of GWs in very high-frequency band, and Gamma-HFGWs would be potential targets for observations in the future.

gr-qc↗

arXiv2017

Graphdiyne Nanoribbons with Open Hexagonal Rings: Existence of Topological Unprotected Edge States

Using first principles calculations, we studied a new class of graphdiyne nanoribbons (GDYNR) with open hexagonal rings on the edges.To avoid the effects from dangling bond, hydrogen or oxygen atoms were absorbed on the edges. There are two kinds of GDYNR depending on the edge structures, armchair and zigzag. The electronic structures show that all of them are semiconductors. The band gap can be tuned by the width of GDYNR. As the width of nanoribbons increases, the energy gap decreases firstly and then increases, and reaches a minimum gap for both kinds. To understand the intriguing phenomenon, we constructed a tight-binding model for GDYNR and found that the existence of the minimum of the energy gap is due to the competition between the interaction within the two edges and the coupling in between. Furthermore, topological unprotected edge states are found in the band structure of a semi-infinite system by calculating surface Green's function. If GDYNR could be synthesized in experiments, it would be useful for the nanodevices in the future.

cond-mat.mtrl-sci↗

arXiv2017

Zero-Shot Learning by Generating Pseudo Feature Representations

Zero-shot learning (ZSL) is a challenging task aiming at recognizing novel classes without any training instances. In this paper we present a simple but high-performance ZSL approach by generating pseudo feature representations (GPFR). Given the dataset of seen classes and side information of unseen classes (e.g. attributes), we synthesize feature-level pseudo representations for novel concepts, which allows us access to the formulation of unseen class predictor. Firstly we design a Joint Attribute Feature Extractor (JAFE) to acquire understandings about attributes, then construct a cognitive repository of attributes filtered by confidence margins, and finally generate pseudo feature representations using a probability based sampling strategy to facilitate subsequent training process of class predictor. We demonstrate the effectiveness in ZSL settings and the extensibility in supervised recognition scenario of our method on a synthetic colored MNIST dataset (C-MNIST). For several popular ZSL benchmark datasets, our approach also shows compelling results on zero-shot recognition task, especially leading to tremendous improvement to state-of-the-art mAP on zero-shot retrieval task.

cs.CV↗