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Asymptotic Theory of Dual Generalized Order Statistics from Heterogeneous Population

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Journal of the Indian Society for Probability and Statistics 2018年第2期19卷 359-377页

作者： Elsawah, A.M. Essawe, Fatma Zhao, Hui Department of Mathematics Faculty of Science Zagazig University Zagazig 44519 Egypt Division of Science and Technology BNU-HKBU United International College Zhuhai 519085 China Faculty of Mathematics and Statistics Central China Normal University Wuhan 430079 China Department of Statistics and Computer Faculty of Applied Science Read Sea University Port Sudan Sudan

The outcomes of several real-life experiments arise in descending order. Dual generalized order statistics (DGOS) have been introduced as a unification of several models of descendingly ordered random variables like reversed ordered order statistics, lower k-records and lower Pfeifer records. The asymptotic theory (AT) proceeds by assuming that it is possible (in principle) to keep collecting additional data, so that the sample size grows infinitely. Under this assumption, many results can be obtained that are unavailable for samples of finite size. The AT is widely used in various statistical approaches, such as ordered random variables, time series models, estimation, testing hypotheses and so on. While the AT of DGOS from homogeneous population, i.e., all of the data points come from the same distribution, has been soundly investigated, no research has been devoted to this problem for heterogeneous population, i.e., the data points come from more than one distribution. This paper gives a closer look at the AT of DGOS based on data from a finite mixture of distributions normalized by the same continuous strictly monotonic sequence or a mixture of continuous strictly monotonic sequences. © 2018, The Indian Society for Probability and Statistics (ISPS).

关键词： Asymptotic theory Dual generalized order statistics Heterogeneous population Homogeneous population Normalization

Nonreciprocal transport in a bilayer of MnBi2Te4 and Pt

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arXiv 2022年

作者： Ye, Chen Xie, Xiangnan Lv, Wenxing Huang, Ke Yang, Allen Jian Jiang, Sicong Liu, Xue Zhu, Dapeng Qiu, Xuepeng Tong, Mingyu Zhou, Tong Hsu, Chuang-Han Chang, Guoqing Lin, Hsin Li, Peisen Yang, Kesong Wang, Zhenyu Jiang, Tian Wang, Xiao Renshaw Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link 637371 Singapore State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Physics Laboratory Industrial Training Center Shenzhen Polytechnic Guangdong Shenzhen518055 China Department of NanoEngineering Program of Chemical Engineering University of California La Jolla San DiegoCA92093-0448 United States Program of Materials Science and Engineering University of California La Jolla San DiegoCA92093-0418 United States Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Fert Beijing Institute MIIT Key Laboratory of Spintronics School of Integrated Circuit Science and Engineering Beihang University Beijing100191 China Beihang-Goertek Joint Microelectronics Institute Qingdao Research Institute Beihang University Qingdao266000 China Shanghai Key Laboratory of Special Artificial Microstructure Materials and Technology School of Physics Science and Engineering Tongji University Shanghai200092 China College of Advanced Interdisciplinary Studies National University of Defense Technology Changsha410073 China Insitute of Physics Academia Sinica Taipei115229 Taiwan College of Intelligence Science and Technology National University of Defense Technology Changsha410073 China National Innovation Institute of Defense Technology Academy of Military Sciences PLA China Beijing100010 China Beijing Academy of Quantum Information Sciences Beijing100084 China Beijing Institute for Advanced Study National University of Defense Technology Changsha410073 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Ave 639798 Singapore

MnBi2Te4 (MBT) is the first intrinsic magnetic topological insulator with the interaction of spin-momentum locked surface electrons and intrinsic magnetism, and it exhibits novel magnetic and topological phenomena. Recent studies suggested that the interaction of electrons and magnetism can be affected by the Mn-doped Bi2Te3 phase at the surface due to inevitable structural defects. Here we report an observation of nonreciprocal transport, i.e. current-direction-dependent resistance, in a bilayer composed of antiferromagnetic MBT and nonmagnetic Pt. The emergence of the nonreciprocal response below the Néel temperature confirms a correlation between nonreciprocity and intrinsic magnetism in the surface state of MBT. The angular dependence of the nonreciprocal transport indicates that nonreciprocal response originates from the asymmetry scattering of electrons at the surface of MBT mediated by magnon. Our work provides an insight into nonreciprocity arising from the correlation between magnetism and Dirac surface electrons in intrinsic magnetic topological insulators. © 2022, CC BY.

关键词： Magnetism

A new family of tractable ising models

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arXiv 2019年

作者： Likhosherstov, Valerii Maximov, Yury Chertkov, Michael Skolkovo Institute of Science and Technology Moscow Russia Theoretical Division and Center for Nonlinear Studies Los Alamos National Laboratory Los AlamosNM United States Graduate Program in Applied Mathematics University of Arizona TucsonAZ United States

We present a new family of zero-field Ising models over N binary variables/spins obtained by consecutive "gluing" of planar and O(1)-sized components along with subsets of at most three vertices into a tree. The polynomial time algorithm of the dynamic programming type for solving exact inference (partition function computation) and sampling consists of a sequential application of an efficient (for planar) or brute-force (for O(1)-sized) inference and sampling to the components as a black box. To illustrate utility of the new family of tractable graphical models, we first build an O(N 32 ) algorithm for inference and sampling of the K5-minor-free zero-field Ising models-an extension of the planar zero-field Ising models-which is neither genus- nor treewidth-bounded. Second, we demonstrate empirically an improvement in the approximation quality of the NP-hard problem of the square-grid Ising model (with non-zero field) inference. Copyright © 2019, The Authors. All rights reserved.

关键词： Ising model

Improving interim decisions in randomized trials by exploiting information on short-term outcomes and prognostic baseline covariates

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arXiv 2019年

作者： Van Lancker, Kelly Vandebosch, An Vansteelandt, Stijn Department of Applied Mathematics Computer Science and Statistics Ghent University Ghent Belgium Janssen R and D A Division of Janssen Pharmaceutica Nv Beerse Belgium Department of Medical Statistics London School of Hygiene and Tropical Medicine London United Kingdom

Conditional power calculations are frequently used to guide the decision whether or not to stop a trial for futility or to modify planned sample size. These ignore the information in short-term endpoints and baseline covariates, and thereby do not make fully efficient use of the information in the data. We therefore propose an interim decision procedure based on the conditional power approach which exploits the information contained in baseline covariates and short-term outcomes. We will realise this by considering the estimation of the treatment effect at the interim analysis as a missing data problem. This problem is addressed by employing specific prediction models for the long-term endpoint which enable the incorporation of baseline covariates and multiple short-term endpoints. We show that the proposed procedure leads to an efficiency gain and a reduced sample size, without compromising the Type I error rate of the procedure, even when the adopted prediction models are misspecified. In particular, implementing our proposal in the conditional power approach allows earlier decisions relative to standard approaches, whilst controlling the probability of an incorrect decision. This time gain results in a lower expected number of recruited patients in case of stopping for futility, such that fewer patients receive the futile regimen. We explain how these methods can be used in adaptive designs with unblinded sample size reassessment based on the inverse normal p-value combination method to control type I error. We support the proposal by Monte Carlo simulations based on data from a real clinical trial. Copyright © 2019, The Authors. All rights reserved.

关键词： Monte Carlo methods

Two-dimensional charge order stabilized in clean polytype heterostructures

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arXiv 2021年

作者： Sung, Suk Hyun Schnitzer, Noah Novakov, Steve El Baggari, Ismail Luo, Xiangpeng Gim, Jiseok Vu, Nguyen M. Li, Zidong Brintlinger, Todd H. Liu, Yu Lu, Wenjian Sun, Yuping Deotare, Parag B. Sun, Kai Zhao, Liuyan Kourkoutis, Lena F. Heron, John T. Hovden, Robert Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Department of Materials Science and Engineering Cornell University IthacaNY14853 United States Kavli Institute at Cornell for Nanoscale Science IthacaNY14853 United States Department of Physics University of Michigan Ann ArborMI48109 United States Department of Physics Cornell University IthacaNY14853 United States Rowland Institute at Harvard CambridgeMA02142 United States Electrical and Computer Engineering Department University of Michigan Ann ArborMI48109 United States Materials Science and Technology Division U.S. Naval Research Laboratory WashingtonDC20375 United States Key Laboratory of Materials Physics Institute of Solid State Physics Chinese Academy of Sciences Hefei230031 China High Magnetic Field Laboratory Chinese Academy of Sciences Hefei230031 China Collaborative Innovation Centre of Advanced Microstructures Nanjing University Nanjing210093 China Applied Physics Program University of Michigan Ann ArborMI48109 United States School of Applied and Engineering Physics Cornell University IthacaNY14853 United States

Compelling evidence suggests distinct correlated electron behavior may exist only in clean 2D materials such as 1T-TaS2. Unfortunately, experiment and theory suggest that extrinsic disorder in free standing 2D layers disrupts correlation-driven quantum behavior. Here we demonstrate a route to realizing fragile 2D quantum states through endotaxial polytype engineering of van der Waals materials. The true isolation of 2D charge density waves (CDWs) between metallic layers stabilizes commensurate long-range order and lifts the coupling between neighboring CDW layers to restore mirror symmetries via interlayer CDW twinning. The twinned-commensurate charge density wave (tC-CDW) reported herein has a single metal–insulator phase transition at ~350 K as measured structurally and electronically. Fast in-situ transmission electron microscopy and scanned nanobeam diffraction map the formation of tC-CDWs. This work introduces endotaxial polytype engineering of van der Waals materials to access latent 2D ground states distinct from conventional 2D fabrication. © 2021, CC BY.

关键词： Charge density waves

Randomized compiling for scalable quantum computing on a noisy superconducting quantum processor

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arXiv 2020年

作者： Hashim, Akel Naik, Ravi K. Morvan, Alexis Ville, Jean-Loup Mitchell, Bradley Kreikebaum, John Mark Davis, Marc Smith, Ethan Iancu, Costin O'Brien, Kevin P. Hincks, Ian Wallman, Joel J. Emerson, Joseph Siddiqi, Irfan Quantum Nanoelectronics Laboratory Department of Physics University of California at Berkeley BerkeleyCA94720 United States Graduate Group in Applied Science and Technology University of California at Berkeley BerkeleyCA94720 United States Computational Research Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Materials Sciences Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Quantum Benchmark Inc. KitchenerONN2H 5G5 Canada Institute for Quantum Computing and Department of Applied Mathematics University of Waterloo WaterlooONN2L 3G1 Canada

The successful implementation of algorithms on quantum processors relies on the accurate control of quantum bits (qubits) to perform logic gate operations. In this era of noisy intermediate-scale quantum (NISQ) computing, systematic miscalibrations, drift, and crosstalk in the control of qubits can lead to a coherent form of error which has no classical analog. Coherent errors severely limit the performance of quantum algorithms in an unpredictable manner, and mitigating their impact is necessary for realizing reliable quantum computations. Moreover, the average error rates measured by randomized benchmarking and related protocols are not sensitive to the full impact of coherent errors, and therefore do not reliably predict the global performance of quantum algorithms, leaving us unprepared to validate the accuracy of future large-scale quantum computations. Randomized compiling is a protocol designed to overcome these performance limitations by converting coherent errors into stochastic noise, dramatically reducing unpredictable errors in quantum algorithms and enabling accurate predictions of algorithmic performance from error rates measured via cycle benchmarking. In this work, we demonstrate significant performance gains under randomized compiling for the four-qubit quantum Fourier transform algorithm and for random circuits of variable depth on a superconducting quantum processor. Additionally, we accurately predict algorithm performance using experimentally-measured error rates. Our results demonstrate that randomized compiling can be utilized to leverage and predict the capabilities of modern-day noisy quantum processors, paving the way forward for scalable quantum computing. Copyright © 2020, The Authors. All rights reserved.

关键词： Benchmarking

Machine Learning in Nuclear Physics

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arXiv 2021年

作者： Boehnlein, Amber Diefenthaler, Markus Sato, Nobuo Schram, Malachi Ziegler, Veronique Fanelli, Cristiano Hjorth-Jensen, Morten Horn, Tanja Kuchera, Michelle P. Lee, Dean Nazarewicz, Witold Ostroumov, Peter Orginos, Kostas Poon, Alan Wang, Xin-Nian Scheinker, Alexander Smith, Michael S. Pang, Long-Gang Thomas Jefferson National Accelerator Facility 12000 Jefferson Avenue Newport NewsVA United States Laboratory for Nuclear Science Massachusetts Institute of Technology CambridgeMA02139 United States The NSF AI Institute for Artificial Intelligence and Fundamental Interactions United States Facility for Rare Isotope Beams Department of Physics and Astronomy Michigan State University MI48824 United States Department of Physics Center for Computing in Science Education University of Oslo OsloN-0316 Norway Department of Physics The Catholic University of America N. E. Washington DC20064 United States Department of Physics Department of Mathematics & Computer Science Davidson College NC28035 United States Department of Physics William & Mary WilliamsburgVA United States Nuclear Science Division Lawrence Berkeley National Laboratory 1 Cyclotron Road BerkeleyCA94720 United States Accelerator Operations and Technology Division Applied Electrodynamics Group Los Alamos National Laboratory Los AlamosNM87544 United States Physics Division Oak Ridge National Laboratory Oak RidgeTN37831-6354 United States Key Laboratory of Quark and Lepton Physics Institute of Particle Physics Central China Normal University Wuhan430079 China

Advances in machine learning methods provide tools that have broad applicability in scientific research. These techniques are being applied across the diversity of nuclear physics research topics, leading to advances that will facilitate scientific discoveries and societal applications. This Colloquium provides a snapshot of nuclear physics research which has been transformed by machine learning techniques. © 2021, CC BY.

关键词： Machine learning

Plane-wave analysis of a hyperbolic system of equations with relaxation in Rd

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arXiv 2018年

作者： de Hoop, Maarten V. Liu, Jian-Guo Markowich, Peter A. Ussembayev, Nail S. Department of Computational and Applied Mathematics Rice University HoustonTX77005 United States Department of Mathematics Department of Physics Duke University DurhamNC27708 United States Applied Mathematics and Computer Science Program CEMSE Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Faculty of Mathematics University of Vienna ViennaA-1090 Austria Applied Mathematics and Computer Science Program CEMSE Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

We consider a multi-dimensional scalar wave equation with memory corresponding to the viscoelastic material described by a generalized Zener model. We deduce that this relaxation system is an example of a non-strictly hyperbolic system satisfying Majda's block structure condition. Well-posedness of the associated Cauchy problem is established by showing that the symbol of the spatial derivatives is uniformly diagonalizable with real eigenvalues. A long-time stability result is obtained by plane-wave analysis when the memory term allows for dissipation of energy.35L40 (Primary) 74D05, 35B35 (Secondary) Copyright © 2018, The Authors. All rights reserved.

关键词： Viscoelasticity

EMPRESS. X. Spatially resolved mass-metallicity relation in extremely metal-poor galaxies: Evidence of episodic star-formation fueled by a metal-poor gas infall

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arXiv 2024年

作者： Nakajima, Kimihiko Ouchi, Masami Isobe, Yuki Xu, Yi Ozaki, Shinobu Nagao, Tohru Inoue, Akio K. Rauch, Michael Kusakabe, Haruka Onodera, Masato Nishigaki, Moka Ono, Yoshiaki Sugahara, Yuma Hattori, Takashi Hirai, Yutaka Hashimoto, Takuya Kim, Ji Hoon Moriya, Takashi J. Yanagisawa, Hiroto Aoyama, Shohei Fujimoto, Seiji Fukushima, Hajime Fukushima, Keita Harikane, Yuichi Hatano, Shun Hayashi, Kohei Ishigaki, Tsuyoshi Kawasaki, Masahiro Kojima, Takashi Komiyama, Yutaka Koyama, Shuhei Koyama, Yusei Lee, Chien-Hsiu Matsumoto, Akinori Mawatari, Ken Motohara, Kentaro Murai, Kai Nagamine, Kentaro Nakane, Minami Saito, Tomoki Sasaki, Rin Shibuya, Takatoshi Suzuki, Akihiro Takeuchi, Tsutomu T. Umeda, Hiroya Umemura, Masayuki Watanabe, Kuria Yabe, Kiyoto Yajima, Hidenobu Zhang, Yechi National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwanoha Chiba Kashiwa277-8582 Japan Osawa 2-21-1 Mitaka Tokyo181-8588 Japan University of Tokyo Chiba Kashiwa277-8583 Japan Kavli Institute for Cosmology University of Cambridge Madingley Road CambridgeCB3 0HA United Kingdom Cavendish Laboratory University of Cambridge 19 JJ Thomson Avenue CambridgeCB3 0HE United Kingdom Waseda Research Institute for Science and Engineering Faculty of Science and Engineering Waseda University 3-4-1 Okubo Shinjuku Tokyo169-8555 Japan Department of Physics Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Research Center for Space and Cosmic Evolution Ehime University Bunkyo-cho 2-5 Ehime Matsuyama790-8577 Japan Department of Physics School of Advanced Science and Engineering Faculty of Science and Engineering Waseda University 3-4-1 Okubo Shinjuku Tokyo169-8555 Japan Observatories of the Carnegie Institution for Science 813 Santa Barbara St. PasadenaCA91101 United States Observatoire de Genève Université de Genève 51 Chemin de Pégase Versoix1290 Switzerland 650 North Aohoku Place HiloHI96720 United States Department of Physics and Astronomy University of Notre Dame 225 Nieuwland Science Hall Notre DameIN46556 United States Astronomical Institute Tohoku University 6-3 Aoba Aramaki Aoba-ku Miyagi Sendai980-8578 Japan Division of Physics Faculty of Pure and Applied Sciences University of Tsukuba Ibaraki Tsukuba305-8571 Japan Faculty of Pure and Applied Sciences University of Tsukuba Ibaraki Tsukuba305-8571 Japan Astronomy Program Department of Physics and Astronomy Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of SNU Astronomy Research Cent

Using the Subaru/FOCAS IFU capability, we examine the spatially resolved relationships between gas-phase metallicity, stellar mass, and star-formation rate surface densities (Σ★ and ΣSFR, respectively) in extremely metal-poor galaxies (EMPGs) in the local universe. Our analysis includes 24 EMPGs, comprising 9,177 spaxels, which span a unique parameter space of local metallicity (12 + log(O/H) 6.9 to 7.9) and stellar mass surface density (Σ★ ∼ 105 to 107 Mo kpc−2), extending beyond the range of existing large integral-field spectroscopic surveys. Through spatially resolved emission line diagnostics based on the [N ii] BPT-diagram, we verify the absence of evolved active galactic nuclei in these EMPGs. Our findings reveal that, while the resolved mass-metallicity relation exhibits significant scatter in the low-mass regime, this scatter is closely correlated with local star-formation surface density. Specifically, metallicity decreases as ΣSFR increases for a given Σ★. Notably, half of the EMPGs show a distinct metal-poor horizontal branch on the resolved mass-metallicity relation. This feature typically appears at the peak clump with the highest Σ★ and ΣSFR and is surrounded by a relatively metal-enriched ambient region. These findings support a scenario in which metal-poor gas infall fuels episodic star formation in EMPGs, consistent with the kinematic properties observed in these systems. In addition, we identify four EMPGs with exceptionally low central metallicities (12 + log(O/H) 7.2), which display only a metal-poor clump without a surrounding metal-rich region. This suggests that such ultra-low metallicity EMPGs, at less than a few percent of the solar metallicity, may serve as valuable analogs for galaxies in the early stages of galaxy evolution. Copyright © 2024, The Authors. All rights reserved.

关键词： Spectroscopic analysis