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Adaptive energy reference for machine-learning models of the electronic density of states

Physical Review Materials 2025年第1期9卷 013802-013802页

作者： Wei Bin How Sanggyu Chong Federico Grasselli Kevin K. Huguenin-Dumittan Laboratory of Computational Science and Modeling IMX École Polytechnique Fédérale de Lausanne Lausanne 1015 Switzerland

The electronic density of states (DOS) provides information regarding the distribution of electronic energy levels in a material, and can be used to approximate its optical and electronic properties and therefore guide computational materials design. Given its usefulness and relative simplicity, it has been one of the first electronic properties used as a target for machine-learning approaches going beyond interatomic potentials. A subtle but important point, well appreciated in the condensed matter community but usually overlooked in the construction of data-driven models, is that for bulk configurations the absolute energy reference of single-particle energy levels is ill-defined. Only energy differences matter, and quantities derived from the DOS are typically independent of the absolute alignment. We introduce an adaptive scheme that optimizes the energy reference of each structure as part of the training process and show that it consistently improves the quality of machine-learning models compared to traditional choices of energy reference for different classes of materials and different model architectures. On a practical level, we trace the improved performance to the ability of this self-aligning scheme to match the most prominent features in the DOS. More broadly, we believe that this paper highlights the importance of incorporating insights on the nature of the physical target into the definition of the architecture and of the appropriate figures of merit for machine-learning models, translating into better transferability and overall performance.

关键词： Electronic density of states

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Convolution Type of Metaplectic Cohen's Distribution Time-Frequency Analysis Theory, Method and Technology

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IEEE Transactions on Information Theory 2025年第3期71卷 2292-2314页

作者： Cui, Manjun Zhang, Zhichao Han, Jie Chen, Yunjie Cao, Chunzheng Nanjing University of Information Science and Technology School of Mathematics and Statistics Center for Applied Mathematics of Jiangsu Province Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing210044 China Nanjing University of Information Science and Technology School of Mathematics and Statistics Nanjing210044 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Hainan Normal University Key Laboratory of Computational Science and Application of Hainan Province Haikou571158 China Nanjing University of Information Science and Technology School of Remote Sensing and Geomatics Engineering Nanjing210044 China

The conventional Cohen's distribution can't meet the requirement of additive noises jamming signals high-performance denoising under the condition of low signal-to-noise ratio, it is necessary to integrate the metaplectic transform for non-stationary signal fractional domain time-frequency analysis. In this paper, we embark on blending time-frequency operators and coordinate operator fractionizations to formulate the definition of the joint fractionizations metaplectic Wigner distribution (JFMWD), based on which we integrate the generalized metaplectic convolution to address the unified representation issue of the convolution type of metaplectic Cohen's distribution (CMCD), whose special cases and essential properties are also derived. We blend Wiener filter principle and fractional domain filter mechanism of the metaplectic transform to design the least-squares adaptive filter method in the JFMWD domain, giving birth to the least-squares adaptive filter-based CMCD whose kernel function can be adjusted with the input signal automatically to achieve the minimum mean-square error (MSE) denoising in Wigner distribution domain. We discuss the optimal symplectic matrices selection strategy of the proposed adaptive CMCD through the minimum MSE minimization modeling and solving. Some examples are also carried out to demonstrate that the proposed filtering method outperforms some state-of-the-arts including the classical Gaussian filter, the Cohen's distribution filtering methods with fixed kernel functions, the classical Wiener filter, the adaptive generalized linear canonical convolution-based filtering method, the adaptive Cohen's distribution filtering method, the adaptive JFMWD-based Cohen's distribution filtering method, and the adaptive generalized metaplectic convolution-based Cohen's distribution filtering method in noise suppression. © 1963-2012 IEEE.

关键词： Adaptive filtering

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PET-MAD, a universal interatomic potential for advanced materials modeling

arXiv

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arXiv 2025年

作者： Mazitov, Arslan Bigi, Filippo Kellner, Matthias Pegolo, Paolo Tisi, Davide Fraux, Guillaume Pozdnyakov, Sergey Loche, Philip Ceriotti, Michele Laboratory of Computational Science and Modeling Institut des Matériaux École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland

Machine-learning interatomic potentials (MLIPs) have greatly extended the reach of atomic-scale simulations, offering the accuracy of first-principles calculations at a fraction of the effort. Leveraging large quantum mechanical databases and expressive architectures, recent "universal" models deliver qualitative accuracy across the periodic table but are often biased toward low-energy configurations. We introduce PET-MAD, a generally applicable MLIP trained on a dataset combining stable inorganic and organic solids, systematically modified to enhance atomic diversity. Using a moderate but highly-consistent level of electronic-structure theory, we assess PET-MAD’s accuracy on established benchmarks and advanced simulations of six materials. PET-MAD rivals state-of-the-art MLIPs for inorganic solids, while also being reliable for molecules, organic materials, and surfaces. It is stable and fast, enabling, out-of-the-box, the near-quantitative study of thermal and quantum mechanical fluctuations, functional properties, and phase transitions. It can be efficiently fine-tuned to deliver full quantum mechanical accuracy with a minimal number of targeted calculations. Copyright © 2025, The Authors. All rights reserved.

关键词： Benchmarking

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Theoretical insight into stabilities and optoelectronic properties of RbZnX3 (X=Cl, Br) halide perovskites for energy conversion applications

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Optical and Quantum Electronics 2025年第1期57卷 1-21页

作者： Khan, Naimat Ullah Ghani, Usman khan, Arshad Khan, Asif Nawaz Ullah, Khadim Ali, Roshan Fadhali, Mohammed M. Department of Physics Materials Modeling and Simulation Lab University of Science & Technology Bannu Khyber Pakhtunkhwa Bannu28100 Pakistan Department of Physics University of Science & Technology Bannu Khyber Pakhtunkhwa Bannu28100 Pakistan Theoretical Condensed Matter Physics and Computational Materials Physics Laboratory College of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China Department of Physical Sciences Physics Division College of Science Jazan University P.O. Box. 114 Jazan45142 Saudi Arabia

Owing to the interesting physical characteristics of perovskites, herein, we investigate RbZnX3 (X = Cl, Br) halide perovskites for sustainable green energy applications. All the given structures were made relaxed and minimum energy was attained by employing Birch-Muranghan equation of state. The electronic band structure of the under study materials were calculated through modified-Beck-Johnson potential. Our results showed that all the investigated RbZnX3 (X = Cl, Br) perovskites are semiconductors with band gaps of 1.34, and 0.12 eV, respectively. The calculated tolerance factors, formation energies, Born-Hung criteria, phonon spectra and ab initio molecular dynamic (AIMD) simulations demonstrated that the given compounds exhibit geometrical, thermodynamic, mechanical, dynamic and thermal stabilities. Findings of elastic investigation revealed an elastic, anisotropic, and ductile nature of our predicted compounds. Moreover, all the studied materials revealed strong absorption – 104 cm−1 in the visible and ultraviolet spectrum and the device absorption efficiency (%) was found comparable to other known reported materials. Overall, this study demonstrates that our simulated perovskites are suitable candidates for photovoltaic and optoelectronic applications. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Bromine compounds

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Impact of Intraspecific Competition of Predator on Coexistence of a Predator-Prey Model with Additive Predation on Prey

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SIAM Journal on Applied Dynamical Systems 2025年第2期24卷 1191-1230页

作者： Bai, Dingyong Xie, Mingming Wu, Jianhong Zheng, Bo Yu, Jianshe Kang, Yun School of Mathematics and Information Science Guangzhou University Guangzhou510006 China Guangzhou Center for Applied Mathematics Guangzhou University Guangzhou510006 China Laboratory for Industrial and Applied Mathematics York University TorontoONM3J 1P3 Canada Science and Mathematics Faculty College of Integrate Sciences and Arts Arizona State University MesaAZ85212 United States Simon A. Levin Mathematical Computational and Modeling Sciences Center Arizona State University TempeAZ85281 United States

We consider a predator-prey model incorporating intraspecific competition in the predator and additive predation on the prey. The additive predation can elicit strong/weak Allee effects in prey, leading to complex dynamics in the model. Our goal is to examine how predator competition affects the species' coexistence. Analyzing the model with the predator competition coefficient as the bifurcation parameter, we reveal the existence and stability of equilibria, and various bifurcation phenomena such as Hopf, saddle-node, and Bogdanov-Takens bifurcations, as well as heteroclinic and homoclinic bifurcations. These bifurcations identify critical thresholds in the competition coefficient, indicating behavioral transitions. Our findings indicate that the strong Allee effect heightens the extinction risk for both species, but predator intraspecific competition reduces this risk and promotes coexistence. Especially when the ratio of the predator's mortality to conversion rate is low, there are competition thresholds that trigger a range of initial values conducive to coexistence, which widens as competition intensifies. Additionally, our analysis shows that reducing the predation pressure on the prey from other potential predators can foster coexistence by inducing a weak Allee effect or eliminating the Allee effect altogether. © 2025 Society for Industrial and Applied Mathematics.

关键词： Abiotic

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A general formalism for machine-learning models based on multipolar-spherical harmonics

arXiv

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arXiv 2025年

作者： Domina, Michelangelo Sanvito, Stefano School of Physics AMBER and CRANN Institute Trinity College Dublin 2 Ireland Laboratory of Computational Science and Modeling Institut des Matériaux École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland

The formulation of descriptors of the local chemical environment, enabling the construction of machine-learning models, is usually obtained by studying the properties of the expansion coefficients of a neighborhood density. In this work, we show that all the transformation properties of the descriptors and their behaviour under rotation, inversion and complex conjugation, are derived from the choice of the basis over which the density is expanded. Furthermore, crucially they are independent from the explicit mathematical form of the neighborhood density. In particular, we show that all the descriptors investigated, can be obtained by an expansion in multipolar spherical harmonics, which constitutes the core of this work, and which is introduced and analysed in great detail. By exploiting the orthogonality and the transformation rules of the multipolar spherical harmonics, we show that several formulations are simplified, such as the one needed to obtain the λ−SOAP kernel and its properties. We close this work by applying our framework to several multi-body descriptors available in literature, providing an in-depth analysis of their main properties, as made clear from the vantage viewpoint of a basis-centered approach. © 2025, CC BY.

关键词： Adversarial machine learning

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Matrix Factorization for Inferring Associations and Missing Links

arXiv

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arXiv 2025年

作者： Barron, Ryan Eren, Maksim E. Truong, Duc P. Matuszek, Cynthia Wendelberger, James Dorn, Mary F. Alexandrov, Boian Theoretical Division Los Alamos National Laboratory United States Information Systems and Modeling Los Alamos National Laboratory United States Department of Computer Science and Electrical Engineering University of Maryland Baltimore County United States Computer Computational and Statistical Sciences Los Alamos National Laboratory United States

Missing link prediction is a method for network analysis, with applications in recommender systems, biology, social sciences, cybersecurity, information retrieval, and Artificial Intelligence (AI) reasoning in Knowledge Graphs. Missing link prediction identifies unseen but potentially existing connections in a network by analyzing the observed patterns and relationships. In proliferation detection, this supports efforts to identify and characterize attempts by state and non-state actors to acquire nuclear weapons or associated technology - a notoriously challenging but vital mission for global security. Dimensionality reduction techniques like Non-Negative Matrix Factorization (NMF) and Logistic Matrix Factorization (LMF) are effective but require selection of the matrix rank parameter, that is, of the number of hidden features, k, to avoid over/under-fitting. We introduce novel Weighted (WNMFk), Boolean (BNMFk), and Recommender (RNMFk) matrix factorization methods, along with ensemble variants incorporating logistic factorization, for link prediction. Our methods integrate automatic model determination for rank estimation by evaluating stability and accuracy using a modified bootstrap methodology and uncertainty quantification (UQ), assessing prediction reliability under random perturbations. Additionally, we incorporate Otsu threshold selection and k-means clustering for Boolean matrix factorization, comparing them to coordinate descent-based Boolean thresholding. Our experiments highlight the impact of rank k selection, evaluate model performance under varying test-set sizes, and demonstrate the benefits of UQ for reliable predictions using abstention. We validate our methods on three synthetic datasets (Boolean and Gaussian distributed) and benchmark them against LMF and symmetric LMF (symLMF) on five real-world protein-protein interaction networks, showcasing an improved prediction performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Non-negative matrix factorization

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Dynamic and static Lagrange multiplier μ based Bayesian CP factorization with orthogonal factors: Theory and applications

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Signal Processing 2025年 236卷

作者： Zhou, Jing Zhang, Zhichao School of Mathematics and Statistics Center for Applied Mathematics of Jiangsu Province and Jiangsu International Joint Laboratory on System Modeling and Data Analysis Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Computational Science and Application of Hainan Province Hainan Normal University Haikou571158 China

The existing μ-Singular Value Decomposition (μ-SVD) denoising algorithm is capable of extracting gear fault information under strong noise conditions. However, this algorithm is only applicable to two-dimensional real-valued data and lacks a mechanism for implementing Automatic Rank Determination (ARD) in high-dimensional data. In this paper, a Bayesian and Tensor treatment of μ-SVD is employed to enable ARD. To further investigate the impact of the Lagrange multiplier μ on the proposed μ-variational Bayesian (μ-VB) algorithm, we examine its performance from both static and dynamic perspectives. Simulation results demonstrate that the μ-VB algorithm achieves ARD and performs well in noise reduction. Further the μ-VB algorithm performs better in wireless communication and linear image coding across numerical domains, tensor sizes, orthogonal factors, and μ settings. © 2025 Elsevier B.V.

关键词： Tensors

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Dielectric Properties of Aqueous Electrolytes at the Nanoscale

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Physical Review Letters 2025年第15期134卷 158001-158001页

作者： Maximilian R. Becker Roland R. Netz Philip Loche Douwe Jan Bonthuis Dominique Mouhanna Hélène Berthoumieux Fachbereich Physik Freie Universität Berlin Arnimallee 14 Berlin 14195 Germany Laboratory of Computational Science and Modeling IMX École Polytechnique Fédérale de Lausanne 1015 Lausanne Switzerland and Fachbereich Physik Freie Universität Berlin Arnimallee 14 Berlin 14195 Germany

Despite the ubiquity of aqueous electrolytes, the effect of salt on water organization remains controversial. We introduce a nonlocal and nonlinear field theory for the nanoscale polarization of ions and water and derive the electrolyte dielectric response as a function of salt concentration to first order in a loop expansion. By comparison with molecular dynamics simulations, we show that rising salt concentration induces a dielectric permittivity decrement and Debye screening in the longitudinal susceptibility but leaves the water structure remarkably unchanged.

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Water cavitation results from the kinetic competition of bulk, surface, and surface-defect nucleation events

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Physics of Fluids 2025年第2期37卷

作者： Loche, Philip Kanduč, Matej Schneck, Emanuel Netz, Roland R. Laboratory of Computational Science and Modeling IMX École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Fachbereich Physik Freie Universität Berlin Berlin14195 Germany Department of Theoretical Physics Jožef Stefan Institute Ljubljana1000 Slovenia Physics Department Technische Universität Darmstadt Darmstadt64289 Germany

Water at negative pressures can remain in a metastable state for a surprisingly long time before it reaches equilibrium by cavitation, i.e., by the formation of vapor bubbles. The wide spread of experimentally measured cavitation pressures depending on water purity, surface contact angle, and surface quality implicates the relevance of water cavitation in bulk, at surfaces, and at surface defects for different systems. We formulate a kinetic model that includes all three different cavitation pathways and determine the nucleation attempt frequencies in bulk, at surfaces, and at defects from atomistic molecular dynamics simulations. Our model reveals that cavitation occurs in pure bulk water only for defect-free hydrophilic surfaces with wetting contact angles below 50° to 60° and at pressures of the order of −100 MPa, depending only slightly on system size and observation time. Cavitation on defect-free surfaces occurs only for higher contact angles, with the typical cavitation pressure rising to about −30 MPa for very hydrophobic surfaces. Nanoscopic hydrophobic surface defects act as very efficient cavitation nuclei and can dominate the cavitation kinetics in a macroscopic system. In fact, a nanoscopic defect that hosts a preexisting vapor bubble can raise the critical cavitation pressure much further. Our results explain the wide variation of experimentally observed cavitation pressures in synthetic and biological systems and highlight the importance of surface and defect mechanisms for the nucleation of metastable systems. © 2025 Author(s).

关键词： Nucleation

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