检索结果-内蒙古大学图书馆

Journal of Computational Science 2025年 90卷

作者： Nassira Madani Zakia Hammouch EL-Houssine Azroul Sidi Mohamed Ben Abdellah University Faculty of Sciences Dhar el Mahraz Laboratory of Modeling Applied Mathematics and Intelligent Systems (L2MASI) Fez Morocco Interdisciplinary Laboratory for Modeling Simulation and Scientific Innovation (LIMSIS) École Normale Supérieure Moulay Ismail University of Meknès Meknès 50000 Morocco Department of Mathematics and Applied Mathematics School of Science and Technology Sefako Makgatho Health Sciences University Ga-Rankuwa South Africa Department of Medical Research China Medical University Hospital Taichung Taiwan Department of Mathematics Kyung Hee University 26 Kyungheedae-ro Dongdaemun-gu Seoul 02447 South Korea Laboratory of Intelligent Systems Energy and Sustainable Development Private University of Fez (UPF) Lot. Quaraouiyine Route Ain Chkef Fez Morocco

The goal of this study is to introduce a new model to better understand the spread of HIV/AIDS, with a particular focus on individuals who are unaware of their infection status. We propose and analyze a new Caputo–Fabrizio fractional model, examining its local stability around the equilibrium point using the abdicate method tailored for Caputo–Fabrizio derivatives. To assess global stability, we employ linear matrix inequalities (LMI). Furthermore, we formulate a fractional optimal control problem to identify effective strategies for controlling the disease. Numerical simulations are conducted to confirm the stability of the equilibrium and to demonstrate the behavior of the proposed solutions.

关键词： Basic reproduction number Caputo–Fabrizio derivative HIV/AIDS Sensitivity analysis Stability analysis

Cloaking the underlying long-range order of randomly perturbed lattices

学校读者我要写书评

暂无评论

Physical Review E 2020年第3期101卷 032118-032118页

作者： Michael A. Klatt Jaeuk Kim Salvatore Torquato Department of Physics Princeton University Princeton New Jersey 08544 USA Department of Chemistry Princeton Institute for the Science and Technology of Materials and Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

Random, uncorrelated displacements of particles on a lattice preserve the hyperuniformity of the original lattice, that is, normalized density fluctuations vanish in the limit of infinite wavelengths. In addition to a diffuse contribution, the scattering intensity from the the resulting point pattern typically inherits the Bragg peaks (long-range order) of the original lattice. Here we demonstrate how these Bragg peaks can be hidden in the effective diffraction pattern of independent and identically distributed perturbations. All Bragg peaks vanish if and only if the sum of all probability densities of the positions of the shifted lattice points is a constant at all positions. The underlying long-range order is then “cloaked” in the sense that it cannot be reconstructed from the pair correlation function alone. On the one hand, density fluctuations increase monotonically with the strength of perturbations a, as measured by the hyperuniformity order metric Λ¯. On the other hand, the disappearance and reemergence of long-range order, depending on whether the system is cloaked as the perturbation strength increases, is manifestly captured by the τ order metric. Therefore, while the perturbation strength a may seem to be a natural choice for an order metric of perturbed lattices, the τ order metric is a superior choice. It is noteworthy that cloaked perturbed lattices allow one to easily simulate very large samples (with at least 106 particles) of disordered hyperuniform point patterns without Bragg peaks.

关键词： Classical statistical mechanics

Effects of Coulomb and isospin symmetry breaking interactions on neutron-skin thickness

学校读者我要写书评

暂无评论

Physical Review C 2023年第6期107卷 064302-064302页

作者： Tomoya Naito (内藤智也) Gianluca Colò Haozhao Liang (梁豪兆) Xavier Roca-Maza Hiroyuki Sagawa (佐川弘幸) RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS) Wako 351-0198 Japan Department of Physics Graduate School of Science The University of Tokyo Tokyo 113-0033 Japan Yukawa Institute for Theoretical Physics Kyoto University Kyoto 606-8502 Japan Dipartimento di Fisica Università degli Studi di Milano Via Celoria 16 20133 Milano Italy INFN Sezione di Milano Via Celoria 16 20133 Milano Italy Center for Mathematics and Physics University of Aizu Aizu-Wakamatsu 965-8560 Japan RIKEN Nishina Center Wako 351-0198 Japan

Both the Coulomb interaction and isospin symmetry breaking (ISB) parts of the nuclear interaction break the isospin symmetry in atomic nuclei. Effects of these two kinds of interaction on properties of atomic nuclei, especially the mass difference of mirror nuclei and the neutron-skin thickness of N=Z and N≠Z nuclei, are discussed. It is found that corrections to the Hartree-Fock-Slater approximation for the Coulomb interaction negligibly affect the neutron-skin thickness, while the charge-symmetry breaking term originating from the strong interaction might affect it non-negligibly. According to our calculations, the ISB terms other than the Coulomb interaction affect the estimation of the density dependence of the symmetry energy, L, by about 0–12MeV using the correlation with the neutron-skin thickness.

关键词： Equations of state of nuclear matter Nuclear forces Nuclear structure & decays Discrete symmetries Nuclear density functional theory

Achieving the depairing limit along the c axis in Fe1+yTe1−xSex single crystals

学校读者我要写书评

暂无评论

Physical Review B 2020年第13期101卷 134516-134516页

作者： Yue Sun Haruka Ohnuma Shin-ya Ayukawa Takashi Noji Yoji Koike Tsuyoshi Tamegai Haruhisa Kitano Department of Physics and Mathematics Aoyama Gakuin University Sagamihara 252-5258 Japan Research Institute for Interdisciplinary Science Okayama University Okayama 700-8530 Japan Department of Applied Physics Tohoku University Sendai 980-8579 Japan Department of Applied Physics The University of Tokyo Tokyo 113-8656 Japan

We report achievement of a depairing current limit along the c axis in Fe1+yTe1−xSex single crystals. A series of crystals with Tc ranging from 8.6 K to 13.7 K (different amounts of excess Fe, y) were fabricated into c-axis bridges with a square-micrometer cross-section. The critical current density, Jc, was directly estimated from the transport current-voltage measurements. The transport Jc reaches a very large value, which is about one order of magnitude larger than the depinning Jc, but comparable to the calculated depairing Jc∼2×106 A/cm2 at 0 K, based on the Ginzburg-Landau (GL) theory. The temperature dependence of the depairing Jc follows the GL theory [∝(1-T/Tc)3/2] down to ∼0.83Tc, then increases with a reduced slope at low temperatures, which can be qualitatively described by the Kupriyanov-Lukichev theory. Our study provides a route to understand the behavior of depairing Jc in iron-based superconductors in a wide temperature range.

关键词： Superconductivity Iron-based superconductors Type-II superconductors Unconventional superconductors Focused ion beam Resistivity measurements

On the approximability of random-hypergraph MAX-3-XORSAT problems with quantum algorithms

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Kapit, Eliot Barton, Brandon A. Feeney, Sean Grattan, George Patnaik, Pratik Sagal, Jacob Carr, Lincoln D. Oganesyan, Vadim Department of Physics Colorado School of Mines 1523 Illinois St GoldenCO80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines 1500 Illinois St GoldenCO80401 United States Quantum Engineering Program Colorado School of Mines 1523 Illinois St GoldenCO80401 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

A canonical feature of the constraint satisfaction problems in NP is approximation hardness, where in the worst case, finding sufficient-quality approximate solutions is exponentially hard for all known methods. Fundamentally, the lack of any guided local minimum escape method ensures both exact and approximate classical approximation hardness, but the equivalent mechanism(s) for quantum algorithms are poorly understood. For algorithms based on Hamiltonian time evolution, we explore this question through the prototypically hard MAX-3-XORSAT problem class. We conclude that the mechanisms for quantum exact and approximation hardness are fundamentally distinct. We review known results from the literature, and identify mechanisms that make conventional quantum methods (such as Adiabatic Quantum Computing) weak approximation algorithms in the worst case. We construct a family of "spectrally filtered" quantum algorithms that escape these issues, and develop analytical theories for their performance. We show that, for random hypergraphs in the approximation-hard regime, if we define the energy to be E = Nunsat - Nsat, spectrally filtered quantum optimization will return states with E ≤ qmEGS (where EGS is the ground state energy) in sub-quadratic time, where conservatively, qm 0.59. This is in contrast to qm → 0 for the hardest instances with classical searches. We test all of these claims with extensive numerical simulations. We do not claim that this approximation guarantee holds for all possible hypergraphs, though our algorithm’s mechanism can likely generalize widely. These results suggest that quantum computers are more powerful for approximate optimization than had been previously assumed. © 2023, CC BY.

关键词： Constraint satisfaction problems

Modelling the behavior of human crowds as coupled active-passive dynamics of interacting particle systems

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Thieu, Thoa Melnik, Roderick M3AI Laboratory MS2Discovery Interdisciplinary Research Institute Wilfrid Laurier University 75 University Ave W WaterlooONN2L 3C5 Canada Department of Mathematics Indiana University 831 East 3rd St. BloomingtonIN47405 United States Bcam - Basque Center for Applied Mathematics Bilbao Spain

The modelling of human crowd behaviors offers many challenging questions to science in general. Specifically, the social human behavior consists of many physiological and psychological processes which are still largely unknown. To model reliably such human crowd systems with complex social interactions, stochastic tools play an important role for the setting of mathematical formulations of the problems. In this work, using the description based on an exclusion principle, we study a statistical-mechanics-based lattice gas model for active-passive population dynamics with an application to human crowd behaviors. We provide representative numerical examples for the evacuation dynamics of human crowds, where the main focus in our considerations is given to an interacting particle system of active and passive human groups. Furthermore, our numerical results show that the communication between active and passive humans strongly influences the evacuation time of the whole population even when the "faster-is-slower" phenomenon is taken into account. To provide an additional inside into the problem, a stationary state of our model is analyzed via current representations and heat map techniques. Finally, future extensions of the proposed models are discussed in the context of coupled data-driven modelling of human crowds and traffic flows, vital for the design strategies in developing intelligent transportation systems. Copyright © 2021, The Authors. All rights reserved.

关键词： Dynamics

A new covariant formalism for kinetic plasma simulations in curved spacetimes

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Trent, Tyler Christian, Pierre Chan, Chi-Kwan Psaltis, Dimitrios Özel, Feryal School of Physics Georgia Institute of Technology 837 State St NW AtlantaGA30332 United States Departments of Astronomy and Physics University of Arizona 933 N. Cherry Ave. TucsonAZ85721 United States Physics Department Fairfield University 1073 N Benson Rd FairfieldCT06824 United States Data Science Institute and Program in Applied Mathematics University of Arizona 1230 N. Cherry Ave. TucsonAZ85721 United States

Low density plasmas are characterized by a large scale separation between the gyromotion of particles around local magnetic fields and the macroscopic scales of the system, often making global kinetic simulations computationally intractable. The guiding center formalism has been proposed as a powerful tool to bridge the gap between these scales. Despite its usefulness, the guiding center approach has been formulated successfully only in flat spacetimes, limiting its applicability in astrophysical settings. Here, we present a new covariant formalism that leads to kinetic equations in the guiding center limit that are valid in arbitrary spacetimes. Through a variety of experiments, we demonstrate that our equations capture all known gyro-center drifts while overcoming one severe limitation imposed on numerical algorithms by the fast timescales of the particle gyromotion. This formalism will enable explorations of a variety of global plasma kinetic phenomena in the curved spacetimes around black holes and neutron stars. © 2023, CC BY.

关键词： Integral equations

Model of virus therapy and chemotherapy for cancer 3

学校读者我要写书评

暂无评论

Model of virus therapy and chemotherapy for cancer

3rd International Conference on Natural and Environmental Sciences 2019, ICONES 2019

作者： Safitri, E. Tarmizi, T. Ramli, M. Wahyuni, S. Ikhwan, M. Mathematics Graduate Study Program Universitas Syiah Kuala Banda Aceh23111 Indonesia Department of Mathematics Universitas Syiah Kuala Banda Aceh23111 Indonesia Graduate School of Mathematics and Applied Science Universitas Syiah Kuala Banda Aceh23111 Indonesia

This article discusses the mathematical model of changes in the number of cancer cells as a result of the intervention. Here the effect of combination treatment, in the form of virus injection and chemotherapy on tumor cells, is presented in detail. There are two different tumor cells, uninfected tumor cells and infected tumor cells. Model simulations with different parameters were performed for 700 d. The initial values for the population of virus-infected tumor cells are divided into two categories. The number of tumor cells injected with the virus is 1/2 (half) and all tumor cells that are not infected. Based on the simulation results, it was concluded that the more the number of tumor cells injected with the virus, the faster the decrease in the number of tumor cell populations. It was also concluded that the reduced population of tumor cells reduces the amount of chemotherapy concentration used. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Viruses

Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Papamarkou, Theodore Skoularidou, Maria Palla, Konstantina Aitchison, Laurence Arbel, Julyan Dunson, David Filippone, Maurizio Fortuin, Vincent Hennig, Philipp Hernández-Lobato, José Miguel Hubin, Aliaksandr Immer, Alexander Karaletsos, Theofanis Khan, Mohammad Emtiyaz Kristiadi, Agustinus Li, Yingzhen Mandt, Stephan Nemeth, Christopher Osborne, Michael A. Rudner, Tim G.J. Rügamer, David Teh, Yee Whye Welling, Max Wilson, Andrew Gordon Zhang, Ruqi Department of Mathematics The University of Manchester Manchester United Kingdom Eric and Wendy Schmidt Center Broad Institute of MIT and Harvard Cambridge United States Spotify London United Kingdom Computational Neuroscience Unit University of Bristol Bristol United Kingdom Centre Inria de l'Université Grenoble Alpes Grenoble France Department of Statistical Science Duke University United States Statistics Program KAUST Saudi Arabia Helmholtz AI Munich Germany Department of Computer Science Technical University of Munich Munich Germany Munich Center for Machine Learning Munich Germany Tübingen AI Center University of Tübingen Tübingen Germany Department of Engineering University of Cambridge Cambridge United Kingdom Department of Mathematics University of Oslo Oslo Norway Bioinformatics and Applied Statistics Norwegian University of Life Sciences Ås Norway Department of Computer Science ETH Zurich Switzerland Chan Zuckerberg Initiative CA United States Center for Advanced Intelligence Project RIKEN Tokyo Japan Vector Institute Toronto Canada Department of Computing Imperial College London London United Kingdom Department of Computer Science UC Irvine Irvine United States Department of Mathematics and Statistics Lancaster University Lancaster United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Center for Data Science New York University New York United States Department of Statistics LMU Munich Munich Germany DeepMind London United Kingdom Department of Statistics University of Oxford Oxford United Kingdom Informatics Institute University of Amsterdam Amsterdam Netherlands Courant Institute of Mathematical Sciences Center for Data Science Computer Science Department New York University New York United States Department of Computer Science Purdue University West Lafayette United States

In the current landscape of deep learning research, there is a predominant emphasis on achieving high predictive accuracy in supervised tasks involving large image and language datasets. However, a broader perspective reveals a multitude of overlooked metrics, tasks, and data types, such as uncertainty, active and continual learning, and scientific data, that demand attention. Bayesian deep learning (BDL) constitutes a promising avenue, offering advantages across these diverse settings. This paper posits that BDL can elevate the capabilities of deep learning. It revisits the strengths of BDL, acknowledges existing challenges, and highlights some exciting research avenues aimed at addressing these obstacles. Looking ahead, the discussion focuses on possible ways to combine large-scale foundation models with BDL to unlock their full potential. © 2024, CC BY-NC-ND.

关键词： Large datasets

Iterative quantum optimization of spin glass problems with rapidly oscillating transverse fields

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Barton, Brandon Sagal, Jacob Feeney, Sean Grattan, George Patnaik, Pratik Oganesyan, Vadim Carr, Lincoln D. Kapit, Eliot Quantum Engineering Program Colorado School of Mines 1523 Illinois St GoldenCO80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines 1500 Illinois St GoldenCO80401 United States Center for Computational Quantum Physics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Department of Physics Colorado School of Mines 1523 Illinois St GoldenCO80401 United States Department of Computer Science Colorado School of Mines 1500 Illinois St GoldenCO80401 United States Department of Physics and Astronomy College of Staten Island City University of New York Staten IslandNY10314 United States Physics program and Initiative for the Theoretical Sciences The Graduate Center City University of New York New YorkNY10016 United States

In this work, we introduce a new iterative quantum algorithm, called Iterative Symphonic Tunneling for Satisfiability problems (IST-SAT), which solves quantum spin glass optimization problems using high-frequency oscillating transverse fields. IST-SAT operates as a sequence of iterations, in which bitstrings returned from one iteration are used to set spin-dependent phases in oscillating transverse fields in the next iteration. Over several iterations, the novel mechanism of the algorithm steers the system toward the problem ground state. We benchmark IST-SAT on sets of hard MAX-3-XORSAT problem instances with exact state vector simulation, and report polynomial speedups over trotterized adiabatic quantum computation (TAQC) and the best known semi-greedy classical algorithm. When IST-SAT is seeded with a sufficiently good initial approximation, the algorithm converges to exact solution(s) in a polynomial number of iterations. Our numerical results identify a critial Hamming radius(CHR), or quality of initial approximation, where the time-to-solution crosses from exponential to polynomial scaling in problem size. By combining IST-SAT with future classical or quantum approximation algorithms, larger gains may be achieved. The mechanism we present in this work thus presents a new path toward achieving quantum advantage in optimization. © 2024, CC BY.

关键词： Combinatorial optimization