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作者： Zhou, Hao Zhu, Hengliang Cui, Tao Pan, David Z. Zhou, Dian Zeng, Xuan State Key Laboratory of ASIC and Systems Department of Microelectronics Fudan University Shanghai200433 China State Key Laboratory of Scientific and Engineering Computing National Center for Mathematics and Interdisciplinary Sciences Institute of Computational Mathematics Academy of Mathematics and System Sciences Chinese Academy of Sciences Beijing100190 China Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Department of Electrical Engineering University of Texas at Dallas RichardsonTX75080 United States

Thermomechanical stress is one of the most important issues in performance and reliability analysis of through silicon via-based 3-D integrated circuits (3-D ICs), where an accurate numerical approach is generally needed to produce stress models and identify weak points in the structure. In this paper, we propose a knowledge-oriented nonuniform (KONU) refinement strategy for 3-D IC stress simulation under the framework of a parallel adaptive finite element method (FEM), and apply it in 3-D IC stress and reliability analysis. Parallel adaptive FEM is promising for solving large-scale problems due to its high accuracy and parallel efficiency. It produces refined meshes based on the a posteriori error analysis, which has the quasi-optimal convergence rate for solving the problem. It has high parallel efficiency, which makes it suitable for handling large and complex structures in 3-D ICs. The KONU refinement strategy developed in this paper can efficiently reduce the number of refinement iterations in parallel adaptive FEM for 3-D IC thermomechanical stress simulation and improves the computational efficiency. It is demonstrated in this paper through several examples that parallel adaptive FEM for thermomechanical stress evaluation can be widely applied in 3-D IC reliability analysis, where accurate stress simulation and modeling is exceptionally important to produce accurate results. © 2018 IEEE.

关键词： Reliability analysis

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Altering Chain Flexibility of Aliphatic Polyesters for Yellow-Green Clusteroluminescence in 38 % Quantum Yield

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Angewandte Chemie 2021年第6期134卷

作者： Bo Chu Prof. Haoke Zhang Dr. Lanfang Hu Prof. Bin Liu Prof. Chengjian Zhang Prof. Xinghong Zhang Prof. Ben Zhong Tang MOE Key Laboratory of Macromolecular Synthesis and Functionalization Department of Polymer Science and Engineering Zhejiang University Hangzhou 310027 China ZJU-Hangzhou Global Scientific and Technological Innovation Center Hangzhou 311215 China Guangdong Provincial Key Laboratory of Luminescence from Molecular Aggregates South China University of Technology Guangzhou 510640 China School of Energy and Power Engineering North University of China Taiyuan 03005 China Shenzhen Institute of Aggregate Science and Technology School of Science and Engineering The Chinese University of Hong Kong Shenzhen 518172 China The Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong China

Preparation of non-conjugated polymers with long-wavelength emission and high quantum yield (QY) is still a huge challenge. Herein, we report the first example of linear non-conjugated polyester exhibiting yellow–green clusteroluminescence (CL) and a high QY of 38 %. We discovered that the polyester P3 with balanced flexibility and rigidity showed the longest CL wavelength and highest QY. Systematically photophysical characterization unravel the key role of ester cluster in the CL and the cluster formation via the aggregate of ester units was visualized. Moreover, P3 was demonstrated to be a highly selective, quick-responsive (ca. 1.2 min) and sensitive detector (detection limit is 0.78 μM) for irons owing to the fast disassociation of clusters by irons. This work not only gains further mechanistic insight into CL but also provides a new strategy to design high-efficiency and long-wavelength CL, meanwhile, enlightens the glorious application prospect of luminescent polyester.

关键词： aliphatic polyesters chain flexibility clusteroluminescence

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Vulnerability of quantum classification to adversarial perturbations

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Physical Review A 2020年第6期101卷 062331-062331页

作者： Nana Liu Peter Wittek Institute of Natural Sciences Shanghai Jiao Tong University Shanghai 200240 China Ministry of Education Key Laboratory in Scientific and Engineering Computing Shanghai Jiao Tong University Shanghai 200240 China University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai 200240 China Rotman School of Management University of Toronto Toronto Canada M5S 3E6 Creative Destruction Lab Toronto Canada M5S 3E6 Vector Institute for Artificial Intelligence Toronto Canada M5G 1M1 Perimeter Institute for Theoretical Physics Waterloo Canada N2L 2Y5

High-dimensional quantum systems are vital for quantum technologies and are essential in demonstrating practical quantum advantage in quantum computing, simulation, and sensing. Since dimensionality grows exponentially with the number of qubits, the potential power of noisy intermediate-scale quantum devices over classical resources also stems from entangled states in high dimensions. An important family of quantum protocols that can take advantage of high-dimensional Hilbert space is classification tasks. These include quantum machine learning algorithms, witnesses in quantum information processing, and certain decision problems. However, due to counterintuitive geometrical properties emergent in high dimensions, classification problems are vulnerable to adversarial attacks. We demonstrate that the amount of perturbation needed for an adversary to induce a misclassification scales inversely with dimensionality. This is shown to be a fundamental feature independent of the details of the classification protocol. Furthermore, this leads to a tradeoff between the security of the classification algorithm against adversarial attacks and quantum advantages that we expect for high-dimensional problems. In fact, protection against these adversarial attacks requires extra resources that can even scale polynomially with the Hilbert space dimension of the system, which can erase any significant quantum advantage that we might expect from a quantum protocol. This has wide-ranging implications in the use of both near-term and future quantum technologies for classification.

关键词： Machine learning Quantum algorithms Quantum information processing Quantum protocols

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Naphthodithiophene Diimide Based Chiral π-Conjugated Nanopillar Molecules

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Angewandte Chemie 2021年第46期133卷

作者： Li Zhang Guilan Zhang Hang Qu Yogesh Todarwal Yun Wang Prof. Dr. Patrick Norman Dr. Mathieu Linares Dr. Mathieu Surin Dr. Hui-Jun Zhang Dr. Jianbin Lin Prof. Dr. Yun-Bao Jiang Department of Chemistry College of Chemistry and Chemical Engineering MOE Key Laboratory of Spectrochemical Analysis and Instrumentation Xiamen University Xiamen 361005 China Department of Theoretical Chemistry and Biology School of Engineering Sciences in Chemistry Biotechnology and Health KTH Royal Institute of Technology 10691 Stockholm Sweden Laboratory of Organic Electronics and Scientific Visualization Group ITN Campus Norrköping Swedish e-Science Research Centre (SeRC) Linköping University 58183 Linköping Sweden Laboratory for Chemistry of Novel Materials Centre of Innovation and Research in Materials and Polymers (CIRMAP) University of Mons—UMONS 20 Place du Parc 7000 Mons Belgium

The synthesis, structures, and properties of [4]cyclonaphthodithiophene diimides ([4]C-NDTIs) are described. NDTIs as important n-type building blocks were catenated in the α-positions of thiophene rings via an unusual electrochemical-oxidation-promoted macrocyclization route. The thiophene–thiophene junction in [4]C-NDTIs results in an ideal pillar shape. This interesting topology, along with appealing electronic and optical properties inherited from the NDTI units, endows the [4]C-NDTIs with both near-infrared (NIR) light absorptions, strong excitonic coupling, and tight encapsulation of C 60 . Stable orientations of the NDTI units in the nanopillars lead to stable inherent chirality, which enables detailed circular dichroism studies on the impact of isomeric structures on π-conjugation. Remarkably, the [4]C-NDTIs maintain the strong π–π stacking abilities of NDTI units and thus adopt two-dimensional (2D) lattice arrays at the molecular level. These nanopillar molecules have great potential to mimic natural photosynthetic systems for the development of multifunctional organic materials.

关键词： conjugation cycloparaphenylenes macrocycles nanopillar molecules naphthodithiophene diimide

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Structural stability of the transonic shock problem in a divergent three-dimensional axi-symmetric perturbed nozzle

arXiv

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arXiv 2019年

作者： Weng, Shangkun Xie, Chunjing Xin, Zhouping School OfMathematics and Statistics Wuhan University Wuhan Hubei Province430072 China School of Mathematical Sciences Institute of Natural Sciences Ministry of Education Key Laboratory of Scientific and Engineering Computing Shanghai Jiao Tong University Shanghai200240 China Institute of Mathematical Sciences Chinese University of Hong Kong Shatin NT Hong Kong

In this paper, we investigate the structural stability of the transonic shock problem in an axisymmetric perturbed nozzle. The axisymmetric perturbation of supersonic incoming flow including the swirl velocity is also considered. We obtain the existence and uniqueness of the piecewise smooth transonic shock solution in a general 3D axisymmetric De Laval nozzle. Due to the singularity on the axis, a key issue is to find an invertible Lagrange transformation to straighten the stream line. Copyright © 2019, The Authors. All rights reserved.

关键词： Lagrange multipliers

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Back Cover: Naphthodithiophene Diimide Based Chiral π-Conjugated Nanopillar Molecules (Angew. Chem. Int. Ed. 46/2021)

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Angewandte Chemie International Edition 2021年第46期60卷

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Rücktitelbild: Naphthodithiophene Diimide Based Chiral π-Conjugated Nanopillar Molecules (Angew. Chem. 46/2021)

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Angewandte Chemie 2021年第46期133卷

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High Order Mass-Lumping Finite Elements on Simplexes

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高等学校计算数学学报（英文版） 2017年第2期10卷 331-350页

作者： Tao Cui Wei Leng Deng Lin Shichao Ma Linbo Zhang State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of SciencesNo.55 East Zhongguancun Road Beijing 100190 China State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of SciencesNo.55 East Zhongguancun Road Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049 China

This paper is concerned with the construction of high order mass-lumping finite elements on simplexes and a program for computing mass-lumping finite elements on triangles and *** polynomial spaces for mass-lumping finite elements,as proposed in the literature,are presented and *** particular,the unisolvence problem of symmetric point-sets for the polynomial spaces used in mass-lumping elements is addressed,and an interesting property of the unisolvent symmetric point-sets is observed and *** its theoretical proof is still lacking,this property seems to be true in general,and it can greatly reduce the number of cases to consider in the computations of mass-lumping elements.A program for computing mass-lumping finite elements on triangles and tetrahedra,derived from the code for computing numerical quadrature rules presented in [7],is *** mass-lumping finite elements on triangles found using this program with higher orders,namely 7,8 and 9,than those available in the literature are reported.

关键词： Finite element mass-lumping simplex numerical quadrature multivariate polynomial interpolation unisolvence

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Parallelizable algorithms for optimization problems with orthogonality constraints

arXiv

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arXiv 2018年

作者： Gao, Bin Liu, Xin Yuan, Ya-Xiang State Key Laboratory of Scientific and Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences University of Chinese Academy of Sciences China

To construct a parallel approach for solving optimization problems with orthogonality constraints is usually regarded as an extremely difficult mission, due to the low scalability of the orthonormalization procedure. However, such demand is particularly huge in some application areas such as materials computation. In this paper, we propose a proximal linearized augmented Lagrangian algorithm (PLAM) for solving optimization problems with orthogonality constraints. Unlike the classical augmented Lagrangian methods, in our algorithm, the prime variables are updated by minimizing a proximal linearized approximation of the augmented Lagrangian function, meanwhile the dual variables are updated by a closed-form expression which holds at any first-order stationary point. The orthonormalization procedure is only invoked once at the last step of the above mentioned algorithm if high-precision feasibility is needed. Consequently, the main parts of the proposed algorithm can be parallelized naturally. We establish global subsequence convergence, worst-case complexity and local convergence rate for PLAM under some mild assumptions. To reduce the sensitivity of the penalty parameter, we put forward a modification of PLAM, which is called parallelizable column-wise block minimization of PLAM (PCAL). Numerical experiments in serial illustrate that the novel updating rule for the Lagrangian multipliers significantly accelerates the convergence of PLAM and makes it comparable with the existent feasible solvers for optimization problems with orthogonality constraints, and the performance of PCAL does not highly rely on the choice of the penalty parameter. Numerical experiments under parallel environment demonstrate that PCAL attains good performance and high scalability in solving discretized Kohn-Sham total energy minimization *** Codes 15A18, 65F15, 65K05, 90C06 Copyright © 2018, The Authors. All rights reserved.

关键词： Linearization

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Τ-FPL: Tolerance-constrained learning in linear time 32

Τ-FPL: Tolerance-constrained learning in linear time

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32nd AAAI Conference on Artificial Intelligence, AAAI 2018

作者： Zhang, Ao Li, Nan Pu, Jian Wang, Jun Yan, Junchi Zha, Hongyuan Shanghai Key Laboratory of Trustworthy Computing MOE International Joint Lab of Trustworthy Software School of Computer Science and Software Engineering East China Normal University Shanghai China Institute of Data Science and Technologies Alibaba Group Hangzhou China IBM Research China Georgia Institute of Technology Atlante United States

ISBN: (纸本)9781577358008

In many real-world applications, learning a classifier with false-positive rate under a specified tolerance is appealing. Existing approaches either introduce prior knowledge dependent label cost or tune parameters based on traditional classifiers, which are of limitation in methodology since they do not directly incorporate the false-positive rate tolerance. In this paper, we propose a novel scoring-thresholding approach, τ-False Positive Learning (τ-FPL) to address this problem. We show that 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 τ-FPL over the existing approaches. Copyright © 2018, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Mathematical transformations

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