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arXiv 2020年

作者： Torquato, Salvatore Kim, Jaeuk Klatt, Michael A. Department of Physics Princeton University PrincetonNJ08544 United States Department of Chemistry Princeton Institute for the Science and Technology of Materials Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

The local number variance σ2(R) associated with a spherical sampling window of radius R enables a classification of many-particle systems in d-dimensional Euclidean space Rd according to the degree to which large-scale density fluctuations are suppressed, resulting in a demarcation between hyperuniform and nonhyperuniform phyla. To more completely characterize density fluctuations, we carry out an extensive study of higher-order moments or cumulants, including the skewness γ1(R), excess kurtosis γ2(R) and the corresponding probability distribution function P[N(R)] of a large family of models across the first three space dimensions, including both hyperuniform and nonhyperuniform systems with varying degrees of short- and long-range order. To carry out this comprehensive program, we derive new theoretical results that apply to general point processes and conduct high-precision numerical studies. Specifically, we derive explicit closed-form integral expressions for γ1(R) and γ2(R) that encode structural information up to three-body and four-body correlation functions, respectively. We also derive rigorous bounds on γ1(R), γ2(R) and P[N(R)] for general point processes and corresponding exact results for general packings of identical spheres. High-quality simulation data for γ1(R), γ2(R) and P[N(R)] are generated for each model. We also ascertain the proximity of P[N(R)] to the normal distribution via a novel Gaussian "distance" metric l2(R). Among all models, the convergence to a central limit theorem (CLT) is generally fastest for the disordered hyperuniform processes such that γ1(R) ∼ l2(R) ∼ R-(d+1)/2 and γ2(R) ∼ R-(d+1) for large R. The convergence to a CLT is slower for standard nonhyperuniform models and slowest for the "antihyperuniform" model studied here. We prove that one-dimensional hyperuniform systems of class I or any d-dimensional lattice cannot obey a CLT. Remarkably, we discovered that the gamma distribution provides a good approximation to P[N(R)] for

关键词： Higher order statistics

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Magnetized and quadratic convection based thermal transport in ternary radiative bio-nanofluid via intelligent neural networks: Two hidden layers mechanism

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Results in Physics 2024年 65卷

作者： Ayub, Assad Darvesh, Adil Shah, Syed Zahir Hussain Junjua, Moin-ud-Din Santos, Elizaldo Domingues dos Ahmad, Shabbir Hendy, Ahmed S. Ragab, Adham E. Department of Mathematics & Statistics Hazara University Manshera Pakistan School of Mathematical Sciences Zhejiang Normal University Zhejiang Jinhua 321004 China Programa de Pós-Graduação em Modelagem Computacional/LMCE Escola de Engenharia Universidade Federal do Rio Grande – FURG RS Rio Grande 96203900 Brazil FURG Escola de Engenharia RS Rio Grande Brazil Department of Basic Sciences and Humanities Muhammad Nawaz Sharif University of Engineering and Technology Multan 60000 Pakistan Department of Computational Mathematics and Computer Science Institute of Natural Sciences and Mathematics Ural Federal University 19 Mira St. Yekaterinburg 620002 Russian Federation Department of Industrial Engineering College of Engineering King Saud University P.O. Box 800 Riyadh 11421 Saudi Arabia Department of Mathematics Ghazi University Dera Ghazi Khan 32200 Pakistan Graduate Program of Ocean Engineering School of Engineering Universidade Federal do Rio Grande Italia Avenue km 8 96201-900 Rio Grande Brazil Department of Mechanics and Mathematics Western Caspian University Baku 1001 Azerbaijan

Significance: The thermal analysis of nanofluid in a vertical cylinder (artery) in a magnetized environment holds significant implications in physiological and thermal regulation networks. This research is significant in biomedical engineering with applications like medical diagnostics and treatment strategies. Motive: This study investigates the thermal behavior of a magnetized blood-based ternary Carreau nanofluid flowing through a vertically bounded artery with quadratic convection. Velocity and heat transfer analysis is conducted within the artery, utilizing thermal radiation and quadratic convection in a magnetized setting. The base fluid consists of blood, augmented with three nanoparticles: CuO, Al₂O₃, and TiO₂. The investigation centers on examining the properties of blood nanofluid, arterial geometry, and thermal dynamics. Methodology: The physical model generates a set of partial differential equations (PDEs) and similarities mechanism is utilized to fetch its non dimensional form in terms of ordinary differential equations (ODEs). Furthermore, numerical outcomes are obtained with Matlab function bvp4c and obtained data set is trained through robust scheme Levenberg-Marquardt neural network (LMNN) procedure to predict the solution. Findings: Velocity of blood is reduced with increased values of wiessenberg number, magnetic parameter and mixed convection parameter and velocity increases for Second-order convection parameter. Temperature profile decreases with curvature parameter, mixed convection parameter and permeability parameter. © 2024

关键词： Blood fluid Intelligent neural network Magnetized environment Ternary nanoparticles Thermal scrutiny

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Overview of the Head and Neck Tumor Segmentation for Magnetic Resonance Guided Applications (HNTS-MRG) 2024 Challenge 1st

Overview of the Head and Neck Tumor Segmentation for Magneti...

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1st Challenge on Head and Neck Tumor Segmentation for MRI-Guided Applications, HNTS-MRG 2024, Held in Conjunction with 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024

作者： Wahid, Kareem A. Dede, Cem El-Habashy, Dina M. Kamel, Serageldin Rooney, Michael K. Khamis, Yomna Abdelaal, Moamen R. A. Ahmed, Sara Corrigan, Kelsey L. Chang, Enoch Dudzinski, Stephanie O. Salzillo, Travis C. McDonald, Brigid A. Mulder, Samuel L. McCullum, Lucas Alakayleh, Qusai Sjogreen, Carlos He, Renjie Mohamed, Abdallah S. R. Lai, Stephen Y. Christodouleas, John P. Schaefer, Andrew J. Naser, Mohamed A. Fuller, Clifton D. Department of Radiation Oncology The University of Texas MD Anderson Cancer HoustonTX United States Department of Imaging Physics The University of Texas MD Anderson Cancer HoustonTX United States Transitional Year Program Corewell Health Wiliam Beaumont Royal OakMI United States Department of Radiation Oncology University of Maryland School of Medicine BaltimoreMD United States Department of Clinical Oncology and Nuclear Medicine Faculty of Medicine Alexandria University Alexandria Egypt UT MD Anderson Cancer CenterUTHealth Houston Graduate School of Biomedical Sciences Houston United States Department of Radiation Oncology Baylor College of Medicine HoustonTX United States Department of Head and Neck Surgery The University of Texas MD Anderson Cancer HoustonTX United States Elekta AtlantaGA United States Department of Computational Applied Mathematics and Operations Research Rice University HoustonTX United States

ISBN: (纸本)9783031832734

Magnetic resonance (MR)-guided radiation therapy (RT) is enhanc- ing head and neck cancer (HNC) treatment through superior soft tissue con- trast and longitudinal imaging capabilities. However, manual tumor segmentation remains a significant challenge, spurring interest in artificial intelligence (AI)- driven automation. To accelerate innovation in this field, we present the Head and Neck Tumor Segmentation for MR-Guided Applications (HNTS-MRG) 2024 Challenge, a satellite event of the 27th International Conference on Medical Image Computing and Computer Assisted Intervention. This challenge addresses the scarcity of large, publicly available AI-ready adaptive RT datasets in HNC and explores the potential of incorporating multi-timepoint data to enhance RT auto- segmentation performance. Participants tackled two HNC segmentation tasks: automatic delineation of primary gross tumor volume (GTVp) and gross metastatic regional lymph nodes (GTVn) on pre-RT (Task 1) and mid-RT (Task 2) T2- weighted scans. The challenge provided 150 HNC cases for training and 50 for final testing hosted on *** using a Docker submission framework. In total, 19 independent teams from across the world qualified by submitting both their algorithms and corresponding papers, resulting in 18 submissions for Task 1 and 15 submissions for Task 2. Evaluation using the mean aggregated Dice Simi- larity Coefficient showed top-performing AI methods achieved scores of 0.825 in Task 1 and 0.733 in Task 2. These results surpassed clinician interobserver vari- ability benchmarks, marking significant strides in automated tumor segmentation for MR-guided RT applications in HNC. © The Author(s) 2025.

关键词： Deep learning

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Publisher's Note: “A dominant dimensionless number and theoretical model for the evolution of multiphase Richtmyer–Meshkov instability” [Phys. Fluids 36(1), 013314 (2024)]

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Physics of Fluids 2024年第2期36卷

作者： Yingming Si (司英明) Shuai Li (李帅) Baoqing Meng (孟宝清) Chun Wang (王春) Baolin Tian (田保林) State Key Laboratory of High Temperature Gas Dynamics Institute of Mechanics Chinese Academic of Sciences Beijing 100190 China School of Engineering Science University of Chinese Academy of Sciences Beijing 100049 China Graduate School Chinese Academy of Engineering Physics Beijing 100088 China Institute of Applied Physics and Computational Mathematics Beijing 100094 China HEDPS Center for Applied Physics and Technology and College of Engineering Peking University Beijing 100871 China

Initiated by all authors, it is proposed to change the affiliation of the author Baolin Tian. Since the affiliation of Baolin Tian in the previous manuscript1 w

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Manifestations of metastable criticality in the long-range structure of model water glasses

arXiv

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arXiv 2021年

作者： Gartner, Thomas E. Torquato, Salvatore Car, Roberto Debenedetti, Pablo G. Department of Chemistry Princeton University PrincetonNJ United States Department of Physics Princeton University PrincetonNJ United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ United States Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ United States Department of Chemical and Biological Engineering Princeton University PrincetonNJ United States

Much attention has been devoted to water’s metastable phase behavior, including polyamorphism (multiple amorphous solid phases), and the hypothesized liquid-liquid transition and associated critical point. However, the possible relationship between these phenomena remains incompletely understood. Using molecular dynamics simulations of the realistic TIP4P/2005 model, we found a striking signature of the liquid-liquid critical point in the structure of water glasses, manifested as a pronounced increase in long-range density fluctuations at pressures proximate to the critical pressure. By contrast, these signatures were absent in glasses of two model systems that lack a critical point. We also characterized the departure from equilibrium upon vitrification via the non-equilibrium index;water-like systems exhibited a strong pressure dependence in this metric, whereas simple liquids did not. These results reflect a surprising relationship between the metastable equilibrium phenomenon of liquid-liquid criticality and the non-equilibrium structure of glassy water, with implications for our understanding of water phase behavior and glass physics. Our calculations suggest a possible experimental route to probing the existence of the liquid-liquid transition in water and other fluids. © 2021, CC BY.

关键词： Criticality (nuclear fission)

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Characterization of a microsecond pulsed non-equilibrium atmospheric pressure Ar plasma using laser scattering and optical emission spectroscopy

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Plasma science and Technology 2020年第6期22卷 120-127页

作者： Fengdong JIA Yong WU Qi MIN Maogen SU Keigo TAKEDA Kenji ISHIKAWA Hiroki KONDO Makoto SEKINE Masaru HORI Zhiping ZHONG School of Physical Sciences University of Chinese Academy of SciencesBeijing 100049People's Republic of China Institute of Applied Physics and Computational Mathematics Beijing 100088People's Republic of China Key Laboratory of Atomic and Molecular Physics&Functional Material of Gansu Province College of Physics and Electronic EngineeringNorthwest Normal UniversityLanzhou 730070People's Republic of China Department of Electrical and Electronic Engineering Faculty of Science and TechnologyMeijo UniversityNagoya 468-8502Japan Graduate School of Engineering Nagoya UniversityNagoya 464-8603Japan CAS Center for Excellence in Topological Quantum Computation University of Chinese Academy of SciencesBeijing 100190People's Republic of China

A non-equilibrium atmospheric pressure argon(Ar)plasma excited by microsecond pulse is studied experimentally by laser scattering and optical emission spectroscopy(OES),and theoretically by collisional-radiative(CR)*** specifically,the electron temperature and electron density of plasma are obtained directly by the laser Thomson scattering,the gas temperature is measured by laser Raman scattering,the optical emissions of excited Ar states of plasma are measured by *** laser scattering results show that the electron temperature is about 1 eV which is similar to that excited by 60 Hz AC power,but the gas temperature is as low as 300 K compared to about 700 K excited by 60 Hz AC *** is shown that the microsecond pulsed power supply,rather than nanosecond ones,is short enough to reduce the gas temperature of atmospheric pressure plasma to near room *** electron temperature and electron density are also obtained by CR model based on OES,and find that the intensities of the optical emission intensity lines of 727.41,811.73,841.08,842.83,852.44 and 912.86 nm of Ar can be used to characterize the behavior of electron density and electron temperature,it is very useful to quickly estimate the activity of the atmospheric pressure Ar plasma in many applications.

关键词： plasma diagnosis laser Thomson scattering atmospheric pressure plasma

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Exponential acceleration of macroscopic quantum tunneling in a Floquet Ising model

arXiv

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arXiv 2023年

作者： Grattan, George Barton, Brandon A. Feeney, Sean Mossi, Gianni Patnaik, Pratik Sagal, Jacob C. Carr, Lincoln D. Oganesyan, Vadim Kapit, Eliot Quantum Engineering Program Colorado School of Mines 1523 Illinois St CO Golden80401 United States Department of Computer Science Colorado School of Mines 1500 Illinois St CO Golden80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines 1500 Illinois St CO Golden80401 United States Department of Physics Colorado School of Mines 1523 Illinois St CO Golden80401 United States KBR Inc. 601 Jefferson St. HoustonTX77002 United States NASA Ames Research Center Moffett FieldCA94035 United States Department of Physics and Astronomy College of Staten Island CUNY Staten IslandNY10314 United States Physics program and Initiative for the Theoretical Sciences The Graduate Center CUNY New YorkNY10016 United States Center for Computational Quantum Physics Flatiron Institute 162 5th Avenue New YorkNY10010 United States

The exponential suppression of macroscopic quantum tunneling (MQT) in the number of elements to be reconfigured is an essential element of broken symmetry phases. Slow MQT is also a core bottleneck in quantum algorithms, such as traversing an energy landscape in optimization, and adiabatic state preparation more generally. In this work, we demonstrate the possibility to accelerate MQT through Floquet engineering with the application of a uniform, high frequency transverse drive field. Using the ferromagnetic phase of the transverse field Ising model in one and two dimensions as a prototypical example, we identify three qualitatively distinct regimes as a function of drive strength: (i) for weak drive, the system exhibits exponentially slow MQT alongside robust magnetic order, as expected;(ii) at intermediate drive strength, we find polynomial decay of rates alongside vanishing magnetic order consistent with critical or paramagnetic state;(iii) at very strong drive strengths both the tunnelling rate and time-averaged magnetic order remain finite with increasing system size. We support these claims with extensive full wavefunction and matrix-product state numerical simulations, and theoretical analysis. An experimental test of these results presents a technologically important and novel scientific question accessible on NISQ-era quantum computers. © 2023, CC BY.

关键词： Ising model

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Hyperuniformity order metric of Barlow packings

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Physical Review E 2019年第2期99卷 022111-022111页

作者： T. M. Middlemas F. H. Stillinger S. Torquato Department of Chemistry Department of Physics Princeton Institute for the Science and Technology of Materials and Program in Applied and Computational Mathematics Princeton University New Jersey 08544 USA

The concept of hyperuniformity has been a useful tool in the study of density fluctuations at large length scales in systems ranging across the natural and mathematical sciences. One can rank a large class of hyperuniform systems by their ability to suppress long-range density fluctuations through the use of a hyperuniformity order metric Λ¯. We apply this order metric to the Barlow packings, which are the infinitely degenerate densest packings of identical rigid spheres that are distinguished by their stacking geometries and include the commonly known fcc lattice and hcp crystal. The “stealthy stacking” theorem implies that these packings are all stealthy hyperuniform, a strong type of hyperuniformity, which involves the suppression of scattering up to a wave vector K. We describe the geometry of three classes of Barlow packings, two disordered classes and small-period packings. In addition, we compute a lower bound on K for all Barlow packings. We compute Λ¯ for the aforementioned three classes of Barlow packings and find that, to a very good approximation, it is linear in the fraction of fcc-like clusters, taking values between those of least-ordered hcp and most-ordered fcc. This implies that the value of Λ¯ of all Barlow packings is primarily controlled by the local cluster geometry. These results highlight the special nature of anisotropic stacking disorder, which provides impetus for future research on the development of anisotropic order metrics and hyperuniformity properties.

关键词： Classical statistical mechanics

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Edge states of Floquet-Dirac semimetal in a laser-driven semiconductor quantum-well

arXiv

引用

arXiv 2020年

作者： Zhang, Boyuan Maeshima, Nobuya Hino, Ken-Ichi Doctoral Program in Materials Science Graduate School of Pure and Applied Sciences University of Tsukuba Tsukuba Ibaraki305-8573 Japan Center for Computational Sciences University of Tsukuba Tsukuba305-8577 Japan Division of Materials Science Faculty of Pure and Applied Sciences University of Tsukuba Tsukuba305-8573 Japan

Band crossings observed in a wide range of condensed matter systems are recognized as a key to understand low-energy fermionic excitations that behave as massless Dirac particles. Despite rapid progress in this field, the exploration of non-equilibrium topological states remains scarce and it has potential ability of providing a new platform to create unexpected massless Dirac states. Here we show that in a cw-laser driven semiconductor quantum-well, the optical Stark effect conducts bulk-band crossing, and the resulting Floquet-Dirac semimetallic phase supports an unconventional edge state in the projected one-dimensional Brillouin zone. Further, we reveal that this edge state mediates a transition between topological and non-topological edge states that is caused by tuning the laser intensity. The existence of the respective edge states and the related topological numbers are understood in a unified manner in terms of the laser-induced polarization reflecting parity hybridization in the bulk Brillouin zone. Copyright © 2020, The Authors. All rights reserved.

关键词： Semiconductor quantum wells

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International Workshop on Applications of Probability and Statistics to Biology,July 11-13,2019--In Honor of Professor Minping Qian’s 80th Birthday

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Quantitative Biology 2020年第2期8卷 177-186页

作者： Minghua Deng Jianfeng Feng Hong Qian Lin Wan Fengzhu Sun Center for Quantitative Biology Peking UniversityBeijing 100871China LMAM Center for Statistical ScienceSchool of Mathematical SciencesPeking UniversityBeijing 100871China Institute of Science and Technology for Brain-inspired Intelligence Fudan UniversityShanghai 200433China School of Mathematical Sciences Fudan UniversityShanghai 200433China Centre for Computational Systems Biology Fudan UniversityShanghai 200433China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence at Fudan University Ministry of EducationShanghai 200433China Department of Computer Science University of WarwickCoventryCV47ALUnited Kingdom Department of Applied Mathematics University of WashingtonSeattleWA 98195USA NCMIS Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China Quantitative and Computational Biology Program University of Southern CaliforniaLos AngelesCA 90089USA

The International Workshop on Applications of Probability and Statistics to Biology(APSB)was successfully held in Shanghai,China,July 11-13,*** workshop was hosted by the Institute of science and Technology for Brain-inspired Intelligence(ISTBI)at Fudan University,and in honor of the 80th birthday of *** Qian of Peking *** of the twenty eight speakers were former students or close collaborators of ***;and there were over eighty participants from all over China and United States.

关键词： Probability speakers ping

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