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It is a very challenging task to solve a nonlinear integral equation in multidimensions. The main purpose of this paper is to develop and analyze a spectral collocation method for a class of nonlinear Fredholm integral equations of the second kind in multidimensions. The proposed spectral collocation method is based on a multivariate Legendre approximation in the frequency space. It is shown by both theory and numerics that the proposed spectral collocation scheme not only significantly reduces the number of degrees of freedom but also produces very accurate approximations. [ABSTRACT FROM AUTHOR]

The microspectrophotometer/microspectrofluorimeter was used to find the azulenes on the intact surface of 30 allelopathic and medicinal plant species growing in moderate or drought climatic conditions. Here in the maxima range of 580-620 nm, peculiar to blue pigments (azulenes), were clearly observed. The pigments were found in blue or silver leaves (needles) or plant parts (petioles, flowers and pollen). The peaks 590-610 nm, characteristic to azulenes were also observed in the absorbance spectra of ethanolic 10 min -extracts from the leaf surface, and 24 h - extracts from whole leaves. Among plants studied, the pigments were first observed in 14 terrestrial species (Anthriscus sylvestris, Lolium perenne, Petasites spurius, Phlomis tuberosa, Crambe maritima, Seseli gummiferum, Filipendula ulmaria, Echinocystis lobata, Colutea cilica, Rhus coriaria, Quercus pubescens, Pinus brutia and 2 algae (Chara vulgaris and Spirogyra sp.) use of spectral methods is recommended to search new azulene-containing species for pharmacy, agriculture and ecology. [ABSTRACT FROM AUTHOR]

This study utilizes a spectral tau method to acquire an accurate numerical solution of the time-fractional diffusion equation. The central point of this approach is to use double basis functions in terms of certain Chebyshev polynomials, namely Chebyshev polynomials of the seventh-kind and their shifted ones. Some new formulas concerned with these polynomials are derived in this study. A rigorous error analysis of the proposed double expansion further corroborates our research. This analysis is based on establishing some inequalities regarding the selected basis functions. Several numerical examples validate the precision and effectiveness of the suggested method. [ABSTRACT FROM AUTHOR]

We propose a novel and simple spectral method based on the semi-discrete Fourier transforms to discretize the fractional Laplacian (− Δ) α 2 . Numerical analysis and experiments are provided to study its performance. Our method has the same symbol | ξ | α as the fractional Laplacian (− Δ) α 2 at the discrete level, and thus it can be viewed as the exact discrete analogue of the fractional Laplacian. This unique feature distinguishes our method from other existing methods for the fractional Laplacian. Note that our method is different from the Fourier pseudospectral methods in the literature which are usually limited to periodic boundary conditions (see Remark 1.1). Numerical analysis shows that our method can achieve a spectral accuracy. The stability and convergence of our method in solving the fractional Poisson equations were analyzed. Our scheme yields a multilevel Toeplitz stiffness matrix, and thus fast algorithms can be developed for efficient matrix-vector multiplications. The computational complexity is O (2 N log ⁡ (2 N)) , and the memory storage is O (N) with N the total number of points. Extensive numerical experiments verify our analytical results and demonstrate the effectiveness of our method in solving various problems. [ABSTRACT FROM AUTHOR]

This paper is concerned with the numerical approximation of initial‐boundary‐value problems of a three‐parameter family of Bona–Smith systems, derived as a model for the propagation of surface waves under a physical Boussinesq regime. The work proposed here is focused on the corresponding problem with Dirichlet boundary conditions and its approximation in space with spectral methods based on Jacobi polynomials, which are defined from the orthogonality with respect to some weighted L2$L^{2}$ inner product. Well‐posedness of the problem on the corresponding weighted Sobolev spaces is first analyzed and existence and uniqueness of solution, locally in time, are proved. Then, the spectral Galerkin semidiscrete scheme and some detailed comments on its implementation are introduced. The existence of numerical solution and error estimates on those weighted Sobolev spaces are established. Finally, the choice of the time integrator to complete the full discretization takes care of different stability issues that may be relevant when approximating the semidiscrete system. Some numerical experiments illustrate the results. [ABSTRACT FROM AUTHOR]

The paper is concerned with the mathematical theory and numerical approximation of systems of partial differential equations (pde) of hyperbolic, pseudo-parabolic type. Some mathematical properties of the initial-boundary-value problem (ibvp) with Dirichlet boundary conditions are first studied. They include the weak formulation, well-posedness and existence of traveling wave solutions connecting two states, when the equations are considered as a variant of a conservation law. Then, the numerical approximation consists of a spectral approximation in space based on Legendre polynomials along with a temporal discretization with strong stability preserving (SSP) property. The convergence of the semidiscrete approximation is proved under suitable regularity conditions on the data. The choice of the temporal discretization is justified in order to guarantee the stability of the full discretization when dealing with nonsmooth initial conditions. A computational study explores the performance of the fully discrete scheme with regular and nonregular data. [ABSTRACT FROM AUTHOR]

This paper briefly examines how literature addresses the numerical solution of partial differential equations by the spectral Tau method. It discusses the implementation of such a numerical solution for PDE’s presenting the construction of the problem’s algebraic representation and exploring solution mechanisms with different orthogonal polynomial bases. It highlights contexts of opportunity and the advantages of exploring low-rank approximations and well-conditioned linear systems, despite the fact that spectral methods usually give rise to dense and ill-conditioned matrices. It presents Tau Toolbox, a Python numerical library for the solution of integro-differential problems. It shows numerical experiments illustrating the implementations’ accuracy and computational costs. Finally, it shows how simple and easy it is to use the Tau Toolbox to obtain approximate solutions to partial differential problems. [ABSTRACT FROM AUTHOR]

Abstract This study utilizes a spectral tau method to acquire an accurate numerical solution of the time-fractional diffusion equation. The central point of this approach is to use double basis functions in terms of certain Chebyshev polynomials, namely Chebyshev polynomials of the seventh-kind and their shifted ones. Some new formulas concerned with these polynomials are derived in this study. A rigorous error analysis of the proposed double expansion further corroborates our research. This analysis is based on establishing some inequalities regarding the selected basis functions. Several numerical examples validate the precision and effectiveness of the suggested method.

The complexity of thermal analysis in practical systems has emerged as a subject of interest in various fields of science and engineering. Extended surfaces, commonly called fins, are crucial cooling and heating mechanisms in many applications, such as refrigerators and power plants. In this study, by using a deterministic approach, we discuss the thermal analysis of conduction, convection, and radiation in the presence of a magnetic force within an extended surface. The present study develops a deep neural network to analyze the mathematical model and to estimate the contributions of each dimensionless model parameter to the thermal dynamics of fins. The deep neural network used in this study makes use of a feedforward architecture in which the weights and biases are updated through backward propagation. The accuracy of the neural network model is validated using results obtained from a spectral-based linearization method. The efficiency rate of the extended surfaces is computed using the neural network and spectral methods. The results obtained demonstrate the accuracy of the neural network-based technique. The findings of this study in relation to the novel mathematical model reveal that utilizing materials with variable thermal conductivity enhances the efficiency rate of the extended surface.

Caputo-Hadamard-type fractional calculus involves the logarithmic function of an arbitrary exponent as its convolutional kernel, which causes challenges in numerical approximations. In this paper, we construct and analyze a spectral collocation approach using mapped Jacobi functions as basis functions and construct an efficient algorithm to solve systems of fractional pantograph delay differential equations involving Caputo-Hadamard fractional derivatives. What we study is the error estimates of the derived method. In addition, we tabulate numerical results to support our theoretical analysis.

This paper employs a numerical method for the numerical treatment of the time fractional Fokker–Planck equation. This method is based on applying the spectral Petrov–Galerkin method. We utilize suitable combinations for the shifted Chebyshev polynomial of the fifth-kind as basis functions. The key idea of the suggested strategy is to transform the governed boundary-value problem into a set of linear algebraic equations using the spectral Petrov–Galerkin method. Several approaches are available to solve the resultant linear system. An in-depth investigation is conducted on the convergence and error analysis of the expansion of the shifted Chebyshev polynomial function of the fifth kind. Many examples are provided to illustrate the precision of the suggested approach. [ABSTRACT FROM AUTHOR]

In this study, we utilize a specific combination of orthogonal Gegenbauer polynomials as basis functions that satisfy homogeneous boundary conditions in the spatial variable and homogeneous initial conditions in the temporal variable. We derive an expression for the fractional derivative of the temporal basis and another expression for the second‐order derivative of the spatial basis. Subsequently, we discretize the nonlinear Fisher problem using the spectral collocation method to transform the problem into the solution of a nonlinear system of algebraic equations. We then solve this resulting system using Newton's method with an initial guess approaching zero. Furthermore, we conduct an error analysis of the proposed method and assess its applicability through three test problems, providing comparisons for validation. [ABSTRACT FROM AUTHOR]

We study a generalization of the classical multidimensional scaling procedure (cMDS) which is applicable in the setting of metric measure spaces. Metric measure spaces can be seen as natural 'continuous limits' of finite data sets. Given a metric measure space |${\mathcal{X}} = (X,d_{X},\mu _{X})$|⁠ , the generalized cMDS procedure involves studying an operator which may have infinite rank, a possibility which leads to studying its traceability. We establish that several continuous exemplar metric measure spaces such as spheres and tori (both with their respective geodesic metrics) induce traceable cMDS operators, a fact which allows us to obtain the complete characterization of the metrics induced by their resulting cMDS embeddings. To complement this, we also exhibit a metric measure space whose associated cMDS operator is not traceable. Finally, we establish the stability of the generalized cMDS method with respect to the Gromov–Wasserstein distance. [ABSTRACT FROM AUTHOR]

This research aims to analyze and implement two numerical spectral schemes for solving linear and nonlinear time fractional Cable equations (TFCEs). Two modified sets of shifted Gegenbauer polynomials (SGPs) are used as basis functions. The approximation of the solution is written as a product of the two chosen basis function sets. For these methods, the principle idea is to convert the problem governed by the underlying conditions into a set of linear and nonlinear algebraic equations that can be solved using appropriate numerical techniques. The upper estimate of the truncation error for the proposed expansion is investigated. In the end, four examples are presented to illustrate the accuracy of the suggested schemes. [ABSTRACT FROM AUTHOR]

This document is a special issue of the journal "Mathematics in Engineering, Science & Aerospace" that focuses on advances in mathematical modeling and its applications. The issue covers a diverse range of topics including reliability, operation research, multi-objective optimization, machine learning, fluid dynamics, software reliability, numerical analysis, and supply chain. The articles included in this collection have been peer-reviewed and cover various domains. Some specific topics discussed in the articles include simulating wave solutions using trigonometric B-spline functions, innovation diffusion models, adaptability of origami structures, effects of voltage unbalanced on induction motors, job-shop scheduling problems, support vector machines, spectral methods for solving partial differential equations, blood flow in stenosed arteries, predator-prey cooperation dynamics, software reliability growth models, entropy measures for intuitionistic fuzzy sets, stability of chemically reacting flows, Petri net modeling of signaling pathways, and system reliability analysis. The authors express gratitude to the contributors and reviewers, as well as the editorial board of the journal. [Extracted from the article]

This research study presents some essential aspects of spectral methods and their application to obtain the numerical solutions of Partial Differential Equations (PDEs). The proposed scheme is based on the spectral collocation of Lagrange and Techbychef orthogonal polynomials for both space and time integrations. The solution of PDEs is approximated as the weighted sum of the polynomials. Using collocation at the grid points, a system of equations is generated to obtain the weights of polynomials. We conclude the study by demonstrating approximate solutions for some popular PDEs. The proposed scheme achieves a greater precision with a smaller number of points than Finite Difference methods and exhibits comparatively better accuracy over Finite Element Methods in the case of approximation by higher order polynomials. This technique outperforms any existing methods of lines for time integration coupled with any scheme for spatial approximation. [ABSTRACT FROM AUTHOR]

Caputo-Hadamard-type fractional calculus involves the logarithmic function of an arbitrary exponent as its convolutional kernel, which causes challenges in numerical approximations. In this paper, we construct and analyze a spectral collocation approach using mapped Jacobi functions as basis functions and construct an efficient algorithm to solve systems of fractional pantograph delay differential equations involving Caputo-Hadamard fractional derivatives. What we study is the error estimates of the derived method. In addition, we tabulate numerical results to support our theoretical analysis. [ABSTRACT FROM AUTHOR]

This work develops a method for solving nonlinear evolution equations. The method, termed a bivariate spectral linear partition method (BSLPM), combines the Chebyshev spectral collocation method, bivariate Lagrange interpolation, and a linear partition technique as an underlying linearization method. It is developed for an nth-order nonlinear differential equation and then used to solve three known evolution problems. The results are compared with known exact solutions from literature. The method's applicability, reliability, and accuracy are confirmed by the congruence between the numerical and exact solutions. Tables, error graphs, and convergence graphs were generated using MATLAB (R2015a), to confirm the order of accuracy of the method and verify its convergence. The performance of the method is also observed against other methods performing well in these types of differential equations and is found to be comparable in terms of accuracy. The proposed method is also efficient as it uses minimal computation time. [ABSTRACT FROM AUTHOR]

In this paper, we provide a collocation spectral scheme for systems of nonlinear Caputo–Hadamard differential equations. Since the Caputo–Hadamard operators contain logarithmic kernels, their solutions can not be well approximated using the usual spectral methods that are classical polynomial-based schemes. Hence, we construct a non-polynomial spectral collocation scheme, describe its effective implementation, and derive its convergence analysis in both L 2 and L ∞ . In addition, we provide numerical results to support our theoretical analysis. [ABSTRACT FROM AUTHOR]

An operational approach developed earlier for the spectral method that uses Legendre polynomials is generalized here for arbitrary systems of basis functions (not necessarily orthogonal) that satisfy only two conditions: the result of multiplication by or of differentiation with respect to is expressed in the same functions. All systems of classical orthogonal polynomials satisfy these conditions. In particular, we construct a spectral method that uses Chebyshev polynomials, which is most effective for numerical computations. This method is applied for numerical solution of the linear functional equations that appear in problems of generalized summation of series as well as in the problems of analytical continuation of discrete maps. We also demonstrate how these methods are used for solution of nonstandard and nonlinear boundary value problems for which ordinary algorithms are not applicable. [ABSTRACT FROM AUTHOR]

Many attempts have been made in the past to regain the spectral accuracy of the spectral methods, which is lost drastically due to the presence of discontinuity. In this article, an attempt has been made to show that mollification using Legendre and Chebyshev polynomial based kernels improves the convergence rate of the Fourier spectral method. Numerical illustrations are provided with examples involving one or more discontinuities and compared with the existing Dirichlet kernel mollifier. Dependence of the efficiency of the polynomial mollifiers on the parameter P$$ P $$ is analogous to that in the Dirichlet mollifier, which is detailed by analyzing the numerical solution. Further, they are extended to linear scalar conservation law problems. [ABSTRACT FROM AUTHOR]

Dynamic graphs are rich data structures that are used to model complex relationships between entities over time. In particular, anomaly detection in temporal graphs is crucial for many real-world applications such as intrusion identification in network systems, detection of ecosystem disturbances, and detection of epidemic outbreaks. In this article, we focus on change point detection in dynamic graphs and address three main challenges associated with this problem: (i) how to compare graph snapshots across time, (ii) how to capture temporal dependencies, and (iii) how to combine different views of a temporal graph. To solve the above challenges, we first propose Laplacian Anomaly Detection (LAD) which uses the spectrum of graph Laplacian as the low dimensional embedding of the graph structure at each snapshot. LAD explicitly models short-term and long-term dependencies by applying two sliding windows. Next, we propose MultiLAD, a simple and effective generalization of LAD to multi-view graphs. MultiLAD provides the first change point detection method for multi-view dynamic graphs. It aggregates the singular values of the normalized graph Laplacian from different views through the scalar power mean operation. Through extensive synthetic experiments, we show that (i) LAD and MultiLAD are accurate and outperforms state-of-the-art baselines and their multi-view extensions by a large margin, (ii) MultiLAD's advantage over contenders significantly increases when additional views are available, and (iii) MultiLAD is highly robust to noise from individual views. In five real-world dynamic graphs, we demonstrate that LAD and MultiLAD identify significant events as top anomalies such as the implementation of government COVID-19 interventions which impacted the population mobility in multi-view traffic networks. [ABSTRACT FROM AUTHOR]

Graph clustering is a fundamental technique in data analysis with applications in many different fields. While there is a large body of work on clustering undirected graphs, the problem of clustering directed graphs is much less understood. The analysis is more complex in the directed graph case for two reasons: the clustering must preserve directional information in the relationships between clusters, and directed graphs have non-Hermitian adjacency matrices whose properties are less conducive to traditional spectral methods. Here, we consider the problem of partitioning the vertex set of a directed graph into k ≥ 2 clusters so that edges between different clusters tend to follow the same direction. We present an iterative algorithm based on spectral methods applied to new Hermitian representations of directed graphs. Our algorithm performs favourably against the state-of-the-art, both on synthetic and real-world data sets. Additionally, it can identify a 'meta-graph' of k vertices that represents the higher-order relations between clusters in a directed graph. We showcase this capability on data sets about food webs, biological neural networks, and the online card game Hearthstone. [ABSTRACT FROM AUTHOR]

Abstract: Solving analytically intractable partial differential equations (PDEs) that involve at least one variable defined on an unbounded domain arises in numerous physical applications. Accurately solving unbounded domain PDEs requires efficient numerical methods that can resolve the dependence of the PDE on the unbounded variable over at least several orders of magnitude. We propose a solution to such problems by combining two classes of numerical methods: (i) adaptive spectral methods and (ii) physics-informed neural networks (PINNs). The numerical approach that we develop takes advantage of the ability of PINNs to easily implement high-order numerical schemes to efficiently solve PDEs and extrapolate numerical solutions at any point in space and time. We then show how recently introduced adaptive techniques for spectral methods can be integrated into PINN-based PDE solvers to obtain numerical solutions of unbounded domain problems that cannot be efficiently approximated by standard PINNs. Through a number of examples, we demonstrate the advantages of the proposed spectrally adapted PINNs in solving PDEs and estimating model parameters from noisy observations in unbounded domains.

In this article, we propose two numerical schemes for solving the time-fractional heat equation (TFHE). The proposed methods are based on applying the collocation and tau spectral methods. We introduce and employ a new set of basis functions: The unified Chebyshev polynomials (UCPs) of the first and second kinds. We establish some new theoretical results regarding the new UCPs. We employ these results to derive the proposed algorithms and analyze the convergence of the proposed double expansion. Furthermore, we compute specific integer and fractional derivatives of the UCPs in terms of their original UCPs. The derivation of these derivatives will be the fundamental key to deriving the proposed algorithms. We present some examples to verify the efficiency and applicability of the proposed algorithms.

The main objective of this study is to present a computationally efficient numerical method for solving fractional-order differential equations with initial conditions. The proposed method is based on the newly developed generalized derivative operational matrix and generalized integral operational matrix derived from Laguerre polynomials, which belong to the class of orthogonal polynomials. Through the utilization of these operational matrices, the fractional-order problems can be transformed into a system of Sylvester-type matrix equations. This system is easily solvable using any computational software, thereby providing a practical framework for solving such equations. The results obtained are compared against various benchmarks, including an existing exact solution, Podlubny numerical techniques, analytical and numerical solvers, and reported solutions from stochastic techniques employing hybrid approaches. This comparative analysis serves to validate the accuracy of our proposed design scheme.

This paper is dedicated to deriving novel formulae for the high‐order derivatives of Chebyshev polynomials of the fifth‐kind. The high‐order derivatives of these polynomials are expressed in terms of their original polynomials. The derived formulae contain certain terminating 4F3(1) hypergeometric functions. We show that the resulting hypergeometric functions can be reduced in the case of the first derivative. As an important application—and based on the derived formulas—a spectral tau algorithm is implemented and analyzed for numerically solving the convection–diffusion equation. The convergence and error analysis of the suggested double expansion is investigated assuming that the solution of the problem is separable. Some illustrative examples are presented to check the applicability and accuracy of our proposed algorithm. [ABSTRACT FROM AUTHOR]

We develop a numerical method for computing with orthogonal polynomials that are orthogonal on multiple, disjoint intervals for which analytical formulae are currently unknown. Our approach exploits the Fokas–Its–Kitaev Riemann–Hilbert representation of the orthogonal polynomials to produce an O(N)$\operatorname{O}(N)$ method to compute the first N recurrence coefficients. The method can also be used for pointwise evaluation of the polynomials and their Cauchy transforms throughout the complex plane. The method encodes the singularity behavior of weight functions using weighted Cauchy integrals of Chebyshev polynomials. This greatly improves the efficiency of the method, outperforming other available techniques. We demonstrate the fast convergence of our method and present applications to integrable systems and approximation theory. [ABSTRACT FROM AUTHOR]

The main objective of this study is to present a computationally efficient numerical method for solving fractional-order differential equations with initial conditions. The proposed method is based on the newly developed generalized derivative operational matrix and generalized integral operational matrix derived from Laguerre polynomials, which belong to the class of orthogonal polynomials. Through the utilization of these operational matrices, the fractionalorder problems can be transformed into a system of Sylvester-type matrix equations. This system is easily solvable using any computational software, thereby providing a practical framework for solving such equations. The results obtained are compared against various benchmarks, including an existing exact solution, Podlubny numerical techniques, analytical and numerical solvers, and reported solutions from stochastic techniques employing hybrid approaches. This comparative analysis serves to validate the accuracy of our proposed design scheme. [ABSTRACT FROM AUTHOR]

In this article, we propose two numerical schemes for solving the time-fractional heat equation (TFHE). The proposed methods are based on applying the collocation and tau spectral methods. We introduce and employ a new set of basis functions: The unified Chebyshev polynomials (UCPs) of the first and second kinds. We establish some new theoretical results regarding the new UCPs. We employ these results to derive the proposed algorithms and analyze the convergence of the proposed double expansion. Furthermore, we compute specific integer and fractional derivatives of the UCPs in terms of their original UCPs. The derivation of these derivatives will be the fundamental key to deriving the proposed algorithms. We present some examples to verify the effciency and applicability of the proposed algorithms. [ABSTRACT FROM AUTHOR]

The purpose of this work is to analyze the heat transfer characteristics of Vascomax®C300 during high-speed sliding. This work extends previous research that is intended to help predict the wear-rate of connecting shoes for a hypersonic rail system at Holloman Air Force Base to prevent critical failure of the system. Solutions were generated using finite element analysis and spectral methods. The frictional heat generated by the pin-on-disk is assumed to flow uniformly and normal to the face of the pin and the pin is assumed to be a perfect cylinder resulting in two-dimensional heat flow. Displacement data obtained from the experiment is used to define the moving boundary. The distribution of temperature resulting from transient finite element analysis is used to justify a one-dimensional model. Spectral methods are then employed to calculate the spatial derivatives improving the approximation of the function which represents the data. It is concluded that a one-dimensional approach with constant heat transfer parameters sufficiently models the high-speed pin-on-disk experiment. [ABSTRACT FROM AUTHOR]

A complete understanding of the stability of fluid flows under varying magnetic field profiles is imperative for achieving control of plasma and operating fluids in the blankets of future fusion reactors. In this context, the primary objective of this study is to investigate the influence of varying magnetic profiles on the flow regime of a generic fluid, which is representative of both thermonuclear plasma and conductive fluids within a nuclear fusion reactor. To this aim in this work non-modal stability theory is adopted to perform stability analysis of a magneto-hydrodynamic (MHD) flow in an infinite circular pipe in order to study the effects of the magnetic field on the fluid dynamics of the pipe flow. In particular, the effects on the general stability of two magnetic field profiles are compared with the reference case of a pipe Poiseuille flow without magnetic field. Firstly, the classic modal stability technique is employed to study asymptotical stability. Then, non-modal stability analysis is applied to magneto-hydrodynamic pipe flow to study the system's response for a finite time immediately after a perturbation. Fourier–Chebyshev Petrov–Galerkin spectral method is used to compute the eigenvalues and pseudospectra of the weak formulation associated with the linearised system. Investigations on the dependence of spectra and transient growths on the specific magnetic profiles are conducted for different values of perturbation wave numbers. The obtained results show that in general the magnetic field has an effect of stabilization on the system, which depends on the specific magnetic profile considered. In addition, the non-modal stability analysis reveals that the inclusion of the magnetic field mitigates the effects of perturbations also in the short term, a phenomenon that cannot be seen using only modal stability analysis.

A well-known reduced model employed to study the wave dynamics is the Boussinesq model. Despite being extensively studied, to our knowledge, there is no research available on a Boussinesq model featuring a sponge layer. Therefore, in this work, we present a Boussinesq model with a sponge layer. Furthermore, we carry out a numerical investigation to explore the advantages and limitations of the proposed model. For this purpose, we compare the numerical solutions of the model with and without the sponge in certain scenarios. The numerical solutions are computed by a pseudospectral method. Our results show that the Boussinesq model with a sponge layer is numerically stable and advantageous because it is able to absorb low-amplitude waves, allowing it to run the numerical simulations for long periods of time without requiring a large spatial domain, but it is not able to absorb high-amplitude waves.

The spectral collocation method for solving two-point boundary value problems for second order differential equations is implemented, based on representing the solution as an expansion in Chebyshev polynomials. The approach allows a stable calculation of both the spectral representation of the solution and its pointwise representation on any required grid in the definition domain of the equation and additional conditions of the multipoint problem. For the effective construction of SLAE, the solution of which gives the desired coefficients, the Chebyshev matrices of spectral integration are actively used. The proposed algorithms have a high accuracy for moderate-dimension systems of linear algebraic equations. The matrix of the system remains well-conditioned and, with an increase in the number of collocation points, allows finding solutions with ever-increasing accuracy.

Laplacian Eigenmaps (LE) is a widely used dimensionality reduction and data reconstruction method. When the data has multiple connected components, the LE method has two obvious deficiencies. First, it might reconstruct each component as a single point, resulting in loss of information within the component. Second, it only focuses on local features but ignores the location information between components, which might cause the reconstructed components to overlap or to completely change their relative positions. To solve these two problems, this article first modifies the optimization objective of the LE method, by characterizing the relative positions between components of data with the similarity between high-density core points, and then solves the optimization problem by using a gradient descent method to avoid the over-compression of data points in the same connected component. A series of experiments on synthetic data and real-world data verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we propose a unified non‐conforming least‐squares spectral element approach for solving Stokes equations with various non‐standard boundary conditions. Existing least‐squares formulations mostly deal with Dirichlet boundary conditions and are formulated using ADN theory‐based regularity estimates. However, changing boundary conditions lead to a search for parameters satisfying supplementing and complimenting conditions, which is not easy always. Here, we have avoided ADN theory‐based regularity estimates and proposed a unified approach for dealing with various boundary conditions. Stability estimates and error estimates have been discussed. Numerical results displaying exponential accuracy have been presented for both two‐ and three‐dimensional cases with various boundary conditions. [ABSTRACT FROM AUTHOR]

The need for developing metrological support for the measurement of gas components in metals and alloys and trace impurities in various industrial products (metallurgy, medicine, etc.) is analyzed. The authors examine the needs of industries for the development of more sensitive measurement methods and procedures, as well as an expanded nomenclature of reference materials having a lower error (uncertainty) of the certified characteristic than the certified characteristic error of currently existing type-approved composition reference materials. Reference materials developed for use in state regulation should be traceable to the primary standards of mass (molar) fraction and mass (molar) concentration: GET 196-2023 State Primary Standard for the units of the mass (molar) fraction and mass (molar) concentration of components in liquid and solid substances and materials based on spectral methods; GET 176-2019 State Primary Standard for the units of mass (molar, atomic) fraction and mass (molar) concentration of components in liquid and solid substances and materials based on coulometry; GET 217-2018 State Primary Standard for the units of mass fraction and mass (molar) concentration of inorganic components in aqueous solutions based on gravimetric and spectral methods; GET 208-2019 State Primary Standard for the units of mass (molar) fraction and mass (molar) concentration of organic components in liquid and solid substances and materials based on liquid and gas chromatography-mass spectrometry with isotope dilution and gravimetry. The need for and ways of developing and creating a metrological support system for Raman spectrometry in the Russian Federation are analyzed, including to confirm the traceability of units for quantitative Raman analysis. To address these issues, GET 196-2023 includes sulfur, carbon, and hydrogen analyzers; an inductively coupled plasma mass spectrometer; and a Raman system. The composition and metrological characteristics of GET 196-2023 are presented. In addition, a draft state hierarchy scheme for instruments measuring mass (molar) fraction and mass (molar) concentration, as well as fluorescence, of components in liquid and solid substances and materials based on spectral methods has been developed and presented. The draft state verification scheme establishes the procedure and methods for transferring the units of the mass (molar) fraction (in absolute units) and mass (molar) concentration of components (grams per cubic decimeter; mole per cubic decimeter) from GET 196-2023 to measuring instruments with indication of measurement error and uncertainty. Also, secondary and working standards are used to transfer relative fluorescence units to measuring instruments. [ABSTRACT FROM AUTHOR]

We analyze a new spectral graph matching algorithm, GRAph Matching by Pairwise eigen-Alignments (GRAMPA), for recovering the latent vertex correspondence between two unlabeled, edge-correlated weighted graphs. Extending the exact recovery guarantees established in a companion paper for Gaussian weights, in this work, we prove the universality of these guarantees for a general correlated Wigner model. In particular, for two Erdős-Rényi graphs with edge correlation coefficient 1 - σ 2 and average degree at least polylog (n) , we show that GRAMPA exactly recovers the latent vertex correspondence with high probability when σ ≲ 1 / polylog (n) . Moreover, we establish a similar guarantee for a variant of GRAMPA, corresponding to a tighter quadratic programming relaxation of the quadratic assignment problem. Our analysis exploits a resolvent representation of the GRAMPA similarity matrix and local laws for the resolvents of sparse Wigner matrices. [ABSTRACT FROM AUTHOR]

Graph matching aims at finding the vertex correspondence between two unlabeled graphs that maximizes the total edge weight correlation. This amounts to solving a computationally intractable quadratic assignment problem. In this paper, we propose a new spectral method, graph matching by pairwise eigen-alignments (GRAMPA). Departing from prior spectral approaches that only compare top eigenvectors, or eigenvectors of the same order, GRAMPA first constructs a similarity matrix as a weighted sum of outer products between all pairs of eigenvectors of the two graphs, with weights given by a Cauchy kernel applied to the separation of the corresponding eigenvalues, then outputs a matching by a simple rounding procedure. The similarity matrix can also be interpreted as the solution to a regularized quadratic programming relaxation of the quadratic assignment problem. For the Gaussian Wigner model in which two complete graphs on n vertices have Gaussian edge weights with correlation coefficient 1 - σ 2 , we show that GRAMPA exactly recovers the correct vertex correspondence with high probability when σ = O (1 log n) . This matches the state of the art of polynomial-time algorithms and significantly improves over existing spectral methods which require σ to be polynomially small in n. The superiority of GRAMPA is also demonstrated on a variety of synthetic and real datasets, in terms of both statistical accuracy and computational efficiency. Universality results, including similar guarantees for dense and sparse Erdős–Rényi graphs, are deferred to a companion paper. [ABSTRACT FROM AUTHOR]