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Wormhole geometries in f(Q) gravity and the energy conditions

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arXiv 2021年

作者： Banerjee, Ayan Pradhan, Anirudh Tangphati, Takol Rahaman, Farook Atrophysics Research Centre School of Mathematics Statistics and Computer Science University of KwaZulu–Natal Private Bag X54001 Durban4000 South Africa Department of Mathematics Institute of Applied Sciences and Humanities GLA University Uttar Pradesh Mathura281 406 India Department of Physics Faculty of Science Chulalongkorn University Bangkok10330 Thailand Department of Mathematics Jadavpur University Kolkata700032 India

Following the recent theory of f(Q) gravity, we continue to investigate the possible existence of wormhole geometries, where Q is the non-metricity scalar. Recently, the non-metricity scalar and the corresponding field equations have been studied for some spherically symmetric configurations in [Phys. Lett. B 821, 136612 (2021) and Phys. Rev. D 103, 124001 (2021)]. One can note that field equations are different in these two studies. Following [Phys. Rev. D 103, 124001 (2021)], we systematically study the field equations for wormhole solutions and found the violation of null energy conditions in the throat neighborhood. More specifically, considering specific choices for the f(Q) form and for constant redshift with different shape functions, we present a class of solutions for static and spherically symmetric wormholes. Our survey indicates that wormhole solutions could not exist for specific form function f(Q) = Q+ αQ2. To summarize, exact wormhole models can be constructed with violation of the null energy condition throughout the spacetime while being ρ ≥ 0 and vice versa. Copyright © 2021, The Authors. All rights reserved.

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A multi-path delivery system with random refusal against online booking using Type-2 fuzzy logic-based fireworks algorithm

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Decision Analytics Journal 2023年 6卷

作者： Maji, Somnath Maity, Samir Giri, Debasis Castillo, Oscar Maiti, Manoranjan Department of Computer Science and Engineering Maulana Abul Kalam Azad University of Technology NH-12 Haringhata West Bengal Nadia 741249 India Department of Information Science Maulana Abul Kalam Azad University of Technology NH-12 Haringhata West Bengal Nadia 741249 India Department of Information Technology Maulana Abul Kalam Azad University of Technology NH-12 Haringhata West Bengal Nadia 741249 India Department of Computer Science Tijuana Institute of Technology Av Castillo de Chapultepec 562 Tomas Aquino B.C. Tijuana 22414 Mexico Department of Applied Mathematics Vidyasagar University Medinipur 721102 India

With the development of the internet and the availability of smart phones, online shopping and the number of digital buyers have increased enormously under the present social context (COVID-19). The major pitfall of this marketing system is the random non-availability of/refusal by customers. Nowadays, with the development of infrastructure, there are several route connections among the different locations worldwide. Considering these, we formulate some multi-path routing for goods delivery with refusal problems (MPRfGDwRPs) against online booking having different route connections between nodes (customers) and solved by a novel Type-2 fuzzy logic based fireworks algorithm (T2FLFWA) developed for discrete problems with probability-based selection and generation based prime mutation. In T2FLFWA, inferences are drawn to obtain the amplitude coefficient against the assumed spark number and iteration ratio. Some instances from TSPLIB are solved and supremacy of T2FLFWA is established through ANOVA test. In MPRfGDwRP, a delivery man starts with goods from a warehouse against customers’ online demands under cash-on-delivery or cash-on bookings systems and delivers the appropriate goods to the respective customers located at different locations. The random refusal or non-availability of customers is considered. The optimum travel plan and appropriate routes between the nodes are selected for minimum total cost. The models are illustrated numerically through a real-life problem. Some managerial conclusions are drawn. The novelty of the investigation is that for the first time, T2FLFWA for discrete problems is developed, delivery man's routing plan with multiple paths between nodes with refusals is formulated and its solution using T2FLFWA is presented. © 2022 The Author(s)

关键词： Fireworks algorithm Goods delivery problem Multi-path routing Probabilistic refusal Type-2 fuzzy logic

Measuring the Substructure Mass Power Spectrum of 23 SLACS Strong Galaxy-Galaxy Lenses with Convolutional Neural Networks

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arXiv 2024年

作者： Fagin, Joshua Vernardos, Georgios Tsagkatakis, Grigorios Pantazis, Yannis Shajib, Anowar J. O’Dowd, Matthew The Graduate Center The City University of New York 365 Fifth Avenue New YorkNY10016 United States Department of Astrophysics American Museum of Natural History Central Park West and 79th Street NY10024-5192 United States Department of Physics and Astronomy Lehman College The CUNY BronxNY10468 United States Institute of Computer Science FORTH HeraklionGR-70013 Greece Institute of Applied and Computational Mathematics FORTH HeraklionGR-70013 Greece Department of Astronomy & Astrophysics University of Chicago ChicagoIL606374 United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States

Strong gravitational lensing can be used as a tool for constraining the substructure in the mass distribution of galaxies. In this study we investigate the power spectrum of dark matter perturbations in a population of 23 Hubble Space Telescope images of strong galaxy-galaxy lenses selected from The Sloan Lens ACS (SLACS) survey. We model the dark matter substructure as a Gaussian Random Field perturbation on a smooth lens mass potential, characterized by power-law statistics. We expand upon the previously developed machine learning framework to predict the power-law statistics by using a convolutional neural network (CNN) that accounts for both epistemic and aleatoric uncertainties. For the training sets, we use the smooth lens mass potentials and reconstructed source galaxies that have been previously modelled through traditional fits of analytical and shapelet profiles as a starting point. We train three CNNs with different training set: the first using standard data augmentation on the best-fitting reconstructed sources, the second using different reconstructed sources spaced throughout the posterior distribution, and the third using a combination of the two data sets. We apply the trained CNNs to the SLACS data and find agreement in their predictions. Our results suggest a significant substructure perturbation favoring a high frequency power spectrum across our lens population. © 2024, CC BY.

关键词： Convolutional neural networks

Real-space investigation of polarons in hematite Fe2O3

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arXiv 2023年

作者： Redondo, Jesus Reticcioli, Michele Gabriel, Vit Wrana, Dominik Ellinger, Florian Riva, Michele Franceschi, Giada Rheinfrank, Erik Sokolovic, Igor Jakub, Zdenek Kraushofer, Florian Alexander, Aji Patera, Laerte L. Repp, Jascha Schmid, Michael Diebold, Ulrike Parkinson, Gareth S. Franchini, Cesare Kocan, Pavel Setvin, Martin Department of Surface and Plasma Science Faculty of Mathematics and Physics Charles University Prague180 00 Czech Republic Institute of Applied Physics TU Wien Vienna1040 Austria Institute of Physics Czech Academy of Sciences Cukrovarnická 10 Prague 6162 00 Czech Republic University of Vienna Faculty of Physics Center for Computational Materials Science Vienna Austria Institute of Experimental and Applied Physics University of Regensburg Regensburg93040 Germany Institute of Physical Chemistry University of Innsbruck Innsbruck6020 Austria Dipartimento di Fisica e Astronomia Università di Bologna Bologna40127 Italy

In polarizable materials, electronic charge carriers interact with the surrounding ions, leading to quasiparticle behaviour. 1,2 The resulting polarons play a central role in many materials properties including electrical transport, 3-5 optical properties, 6 surface reactivity7,8 and magnetoresistance, 9,10 and polaron properties are typically investigated indirectly through such macroscopic characteristics. Here, noncontact atomic force microscopy (nc-AFM) 11 is used to directly image polarons in Fe2O3 at the single quasiparticle limit. A combination of Kelvin probe force microscopy (KPFM) 12 and kinetic Monte Carlo (KMC) simulations shows that Ti doping dramatically enhances the mobility of electron polarons, and density functional theory (DFT) calculations indicate that a metallic transition state is responsible for the enhancement. In contrast, hole polarons are significantly less mobile and their hopping is hampered further by the introduction of trapping centres. © 2023, CC BY.

关键词： Polarons

On the Choice of Thresholding Parameters for Non-Gaussian Noise Distribution

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Journal of Mathematical sciences (United States) 2020年第4期246卷 519-524页

作者： Kudryavtsev, A.A. Shestakov, O.V. Department of Mathematical Statistics Faculty of Computational Mathematics and Cybernetics M. V. Lomonosov Moscow State University Moscow Russian Federation Institute of Informatics Problems Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences Moscow Russian Federation

The paper considers the problem of estimating the signal function from noisy observations using threshold processing of its wavelet expansion coefficients. Under general assumptions about the properties of the noise distribution, the asymptotic order of the optimal threshold is calculated, minimizing the loss function, based on the probability that the maximum error in the wavelet coefficients exceeds a given critical level. © 2020, Springer science+Business Media, LLC, part of Springer Nature.

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CP-PINNS: DATA-DRIVEN CHANGEPOINTS DETECTION IN PDES USING ONLINE OPTIMIZED PHYSICS-INFORMED NEURAL NETWORKS

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arXiv 2022年

作者： Dong, Zhikang Polak, Pawel Department of Applied Mathematics and Statistics Stony Brook University Stony BrookNY11794 United States Institute for Advanced Computational Science Stony Brook University Stony BrookNY11794 United States Center of Excellence in Wireless and Information Technology Stony Brook University Stony BrookNY11794 United States

We investigate the inverse problem for Partial Differential Equations (PDEs) in scenarios where the parameters of the given PDE dynamics may exhibit changepoints at random time. We employ Physics-Informed Neural Networks (PINNs) – universal approximators capable of estimating the solution of any physical law described by a system of PDEs, which serves as a regularization during neural network training, restricting the space of admissible solutions and enhancing function approximation accuracy. We demonstrate that when the system exhibits sudden changes in the PDE dynamics, this regularization is either insufficient to accurately estimate the true dynamics, or it may result in model miscalibration and failure. Consequently, we propose a PINNs extension using a Total-Variation penalty, which allows to accommodate multiple changepoints in the PDE dynamics and significantly improves function approximation. These changepoints can occur at random locations over time and are estimated concurrently with the solutions. Additionally, we introduce an online learning method for re-weighting loss function terms dynamically. Through empirical analysis using examples of various equations with parameter changes, we showcase the advantages of our proposed model. In the absence of changepoints, the model reverts to the original PINNs model. However, when changepoints are present, our approach yields superior parameter estimation, improved model fitting, and reduced training error compared to the original PINNs model. Copyright © 2022, The Authors. All rights reserved.

关键词： Dynamics

A fuzzy assessment model for freestyle swimmers - a comparative analysis of the MCDA methods

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Procedia computer science 2021年 192卷 4148-4157页

作者： Jakub Więckowski Larisa Dobryakova Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul.Żołnierska 49 71-210 Szczecin Poland

Multi-Criteria Decision Analysis methods are readily used in decision support models. However, many methods in this group of methods cause a problem with choosing an appropriate method for a given problem. One of such methods is COMET (Characteristic Objects Method), which compares pairs of Characteristic Objects (COs) when calculating preference values of alternatives. In this paper, the COMET method was used to create a model that evaluates swimming athletes regarding their predisposition to compete in freestyle sprint events. Besides, to reduce the complexity of the problem, a division of the initial structure was applied, which made it possible to reduce the number of comparisons to 0.7e -8 % of their initial number. To verify the obtained results, it was decided to use selected MCDA methods to solve the same problem. The correlation between the rankings was examined using the Pearson correlation coefficient and the WS similarity coefficient. Based on the results obtained, it can be concluded that the proposed model gives results that guarantee a high correlation with the results from the other methods. Moreover, it can be useful in evaluating and selecting swimming athletes for participation in given events.

关键词： Sport management COMET MCDA Swimming

A circuit-generated quantum subspace algorithm for the variational quantum eigensolver

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arXiv 2024年

作者： Hirsbrunner, Mark R. Mullinax, J. Wayne Shen, Yizhi Williams-Young, David B. Klymko, Katherine Van Beeumen, Roel Tubman, Norm M. Department of Physics University of Illinois at Urbana-Champaign UrbanaIL61801 United States USRA Research Institute for Advanced Computer Science Mountain ViewCA94043 United States KBR Inc. NASA Ames Research Center Moffett FieldCA94035 United States Intelligent Systems Division NASA Ames Research Center Moffett FieldCA94035 United States Applied Mathematics and Computational Research Division Lawrence Berkeley National Lab BerkeleyCA94720 United States NERSC Lawrence Berkeley National Lab BerkeleyCA94720 United States

Recent research has shown that wavefunction evolution in real- and imaginary-time can generate quantum subspaces with significant utility for obtaining accurate ground state energies. Inspired by these methods, we propose combining quantum subspace techniques with the variational quantum eigensolver (VQE). In our approach, the parameterized quantum circuit is divided into a series of smaller subcircuits. The sequential application of these subcircuits to an initial state generates a set of wavefunctions that we use as a quantum subspace to obtain high-accuracy groundstate energies. We call this technique the circuit subspace variational quantum eigensolver (CSVQE) algorithm. By benchmarking CSVQE on a range of quantum chemistry problems, we show that it can achieve significant error reduction in the best case compared to conventional VQE, particularly for poorly optimized circuits, greatly improving convergence rates. Furthermore, we demonstrate that when applied to circuits trapped at a local minima, CSVQE can produce energies close to the global minimum of the energy landscape, making it a potentially powerful tool for diagnosing local minima. © 2024, CC BY-NC-SA.

关键词： Ground state

A new multi-criteria model for ranking chess players

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Procedia computer science 2021年 192卷 4290-4299页

作者： Aleksandra Kaczyńska Joanna Kołodziejczyk Wojciech Sałabun Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Żołnierska 49 71-210 Szczecin Poland

Chess is a very demanding sport as it requires advanced planning and strategic thinking skills. The degree of difficulty of the game also depends on the time allotted for a game, which can range from a few minutes to several tens of minutes. For this reason, the games are divided into several categories: standard, blitz, and bullet. However, as many chess players specialize in only some of the categories, it is difficult to determine the best chess player. It is very important to keep a proper ranking of the players. One way to recognize their achievements is the FIDE (Fédération Internationale des Échecs) titles awarded to the best players. However, there is still the problem of how to determine the best among the Grandmasters. There are many very talented players competing in chess. Creating a single ranking for all types of chess, regardless of the time allotted for the game, is a difficult challenge, as many undeniably outstanding chess players do not specialize in all types. Creating a ranking for only one type would not accurately describe the level of players. Therefore, a ranking was created based on all of them using the COMET method, which belongs to the multi-criteria decision-making methods (MCDA). It is based on fuzzy logic and uses characteristic objects for the assessment of alternatives, which guarantees immunity to the paradox of reversal rankings. Expert opinion was used for correct evaluation. This article presents the ranking of chess players regardless of the type of game they specialize in, to prove that it should be possible to identify the single best chess player.

关键词： Chess MCDA COMET players evaluation decision making