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Allal Guessab

Publications and source records attributed to Allal Guessab.

9 recordsLinked to original sources

Exactly Diagonal Gram Matrices in Jacobi Weighted Histopolation

In the current work, we study univariate polynomial weighted histopolation on $[-1,1]$, where the data are weighted integrals over a family of intervals. After choosing a polynomial basis, the weighted moment conditions lead to a histopolation matrix whose structure depends on the weight and on the geometry of the cells. We investigate its nonsingularity, which guarantees unisolvence, together with exact diagonality of its Gram matrix, which allows its singular values and spectral condition number to be determined explicitly. For families of intervals whose endpoints belong to a fixed grid, we characterize unisolvence in terms of the connectedness of the associated endpoint graph. In the unisolvent case, this graph is a tree, and the unique paths joining consecutive grid points provide an explicit expression for the inverse matrix. This identity gives explicit formulas for the singular values of both matrices, and shows that their condition numbers in the two-norm coincide and grow linearly with the matrix size. Moreover, it yields the limiting singular value distributions of the two matrix sequences. We also establish a general diagonalization criterion based on discrete weighted orthogonality. The criterion recovers the first kind Chebyshev construction and leads to a diagonal configuration for the constant weight based on discrete sine orthogonality. For interval families with a connected endpoint graph, the corresponding moment vectors define an inner product on the polynomial space and lead to a monic basis with a diagonal weighted Gram matrix. Finally, we derive reduction formulas for cell moments associated with generalized Jacobi weights and introduce an alternative basis for shifted Jacobi weights. Applied to the Chebyshev weight of the fourth kind, this basis, together with a correction of one nonconstant element, yields an exactly diagonal Gram matrix.

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Weighted Derivative Histopolation on Arbitrary Grids: Admissibility and Exact Factorizations

In this paper, we introduce a weighted derivative histopolation framework on families of intervals. The degrees of freedom consist of one scalar normalization and weighted integral moments of the derivative over a prescribed family of subintervals. We prove that the resulting scheme is unisolvent on $\Pi_N$ when the interval family separates polynomials of degree at most $N-1$ through weighted moments and the normalization is nonzero on constants. Thus, the derivative moments determine the polynomial up to an additive constant, and the scalar normalization fixes this remaining degree of freedom. This gives a sharp criterion for the well-posedness of the interpolation problem and a complete characterization of the admissible scalar normalizations. We then show how admissible families of intervals can be constructed from a fixed grid. When the endpoints of the intervals belong to the grid, admissibility is reduced to the nonsingularity of an interval matrix associated with the family, which depends only on the representation of the intervals in terms of consecutive cells. For Jacobi weights, the associated data matrices have a natural block structure in Jacobi polynomial bases, and the reduced derivative matrix can be expressed in terms of shifted Jacobi moment matrices. We next study Chebyshev configurations in which this structure becomes explicit. For the four classical Chebyshev families, suitable polynomial bases lead to diagonal Gram matrices for the reduced derivative matrices. We show that this diagonal structure depends on the simultaneous choice of the weight, the basis, and the grid. Numerical experiments on equispaced and Chebyshev--Lobatto nodes show the behaviour of the method for different interval families and for different Jacobi parameters.

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Spectral distribution of Jacobi weighted histopolation matrices via GLT theory

In this paper we study a weighted histopolation problem on $[-1,1]$ associated with Jacobi weights. In the first part of the present work we prove results in approximation theory, while in the second we analyze the resulting matrices from an asymptotic linear algebra perspective. More in detail, in the first part, given weighted cell averages, we construct a reconstruction operator based on weighted primitives of Jacobi polynomials and investigate the resulting discretization matrices. At any fixed discretization level, we derive an exact factorization of the histopolation matrix through a backward-difference operator and a sampling operator of Jacobi weighted primitives. Combining a sharp integration by parts identity with the three-term recurrence of Jacobi polynomials, we further show that the primitive sampling operator admits an explicit decomposition involving a tridiagonal coupling matrix in the Jacobi spectral index. This yields a tridiagonal factor representation of the histopolation matrix. In the second part, under standard mesh-regularity assumptions, we show that all the various induced matrix sequences belong to the Generalized Locally Toeplitz (GLT) class, by describing in detail the related GLT symbols. As a consequence, we provide the corresponding spectral distributions and discuss their implications for numerical stability when solving the associated linear systems.

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Spectral Schur analysis of structured moment matrices for quadratic histopolation

In this paper we study parameter-dependent structured moment matrices with a canonical block form arising from weighted quadratic histopolation on simplicial meshes. For a strictly positive density on a simplex, we construct compatible face densities and an orthogonal decomposition of the quadratic polynomial space into face and interior components, which induces a natural face-interior block structure. A reduced Schur complement is identified that fully characterizes enrichment and well-posedness and provides a sharp spectral stability result. We show that this quantity coincides with the square root of the smallest eigenvalue of a low-dimensional symmetric positive definite operator. This matrix-based viewpoint yields simple spectral criteria for the invertibility of local moment systems and motivates spectrally preferable choices of face and interior bases with improved conditioning. Using the resulting degrees of freedom together with density and scaling parameters as design variables, we formulate a small eigenvalue optimization problem aimed at improving stability and reducing the condition number of the global reconstruction system. Three-dimensional experiments on uniform and quasi-uniform simplicial meshes illustrate the predicted stability, conditioning, and convergence behaviour of the enriched quadratic reconstruction.

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A General Probability Density Framework for Local Histopolation and Weighted Function Reconstruction from Mesh Line Integrals

In this paper, we study the reconstruction of a bivariate function from weighted integrals along the edges of a triangular mesh, a problem of central importance in tomography, computer vision, and numerical approximation. Our approach relies on local histopolation methods defined through unisolvent triples, where the edge weights are induced by suitable probability densities. In particular, we introduce two new two-parameter families of generalized truncated normal distributions, which extend classical exponential-type laws and provide additional flexibility in capturing local features of the target function. These distributions give rise to new quadratic reconstruction operators that generalize the standard linear histopolation scheme, while retaining its simplicity and locality. We establish their theoretical foundations, proving unisolvency and deriving explicit basis functions, and we demonstrate their improved accuracy through extensive numerical tests. Moreover, we design an algorithm for the optimal selection of the distribution parameters, ensuring robustness and adaptivity of the reconstruction. Finally, we show that the proposed framework naturally extends to any bivariate function whose restriction to the edges defines a valid probability density, thus highlighting its generality and broad applicability.

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Quadratic Weighted Histopolation on Tetrahedral Meshes with Probabilistic Degrees of Freedom

In this paper we introduce three complementary three-dimensional weighted quadratic enrichment strategies to improve the accuracy of local histopolation on tetrahedral meshes. The first combines face and interior weighted moments (face-volume strategy), the second uses only volumetric quadratic moments (purely volumetric strategy), and the third enriches the quadratic space through edge-supported probabilistic moments (edge-face strategy). All constructions are based on integral functionals defined by suitable probability densities and orthogonal polynomials within quadratic trial spaces. We provide a comprehensive analysis that establishes unisolvence and derives necessary and sufficient conditions on the densities to guarantee well-posedness. Representative density families, including two-parameter symmetric Dirichlet laws and convexly blended volumetric families, are examined in detail, and a general procedure for constructing the associated quadratic basis functions is outlined. For all admissible densities, an adaptive algorithm automatically selects optimal parameters. Extensive numerical experiments confirm that the proposed strategies yield substantial accuracy improvements over the classical linear histopolation scheme.

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Weighted and unweighted enrichment strategies for solving the Poisson problem with Dirichlet boundary conditions

In this paper, we propose weighted and unweighted enrichment strategies to enhance the accuracy of the linear lagrangian finite element for solving the Poisson problem with Dirichlet boundary conditions. We first recall key examples of admissible enrichment functions, specifically designed to overcome the limitations of the linear lagrangian finite element in capturing solution features such as sharp gradients and boundary-layer phenomena. We then introduce two novel three-parameter families of weighted enrichment functions and derive an explicit error bound in $L^2$-norm. Numerical experiments confirm the effectiveness of the proposed approach in improving approximation accuracy, demonstrating its potential for a wide range of applications.

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Nonconforming approximation methods for function reconstruction on general polygonal meshes via orthogonal polynomials

In this work, we introduce new families of nonconforming approximation methods for reconstructing functions on general polygonal meshes. These methods are defined using degrees of freedom based on weighted moments of orthogonal polynomials and can reproduce higher-degree polynomials. This setting naturally arises in applications where pointwise evaluations are unavailable and only integral measurements over subdomains are accessible. We develop a unisolvence theory and derive necessary and sufficient conditions for the associated approximation spaces to be unisolvent. Specifically, it is shown that unisolvence depends on the parity of the product of the polynomial degree~$m$ and the number of polygon edges~$N$. When this condition is not satisfied, we introduce an enrichment strategy involving an additional linear functional and a suitably designed enrichment function to ensure unisolvence. Numerical experiments confirm the accuracy of the proposed method.

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A new quadratic and cubic polynomial enrichment of the Crouzeix-Raviart finite element

In this paper, we introduce quadratic and cubic polynomial enrichments of the classical Crouzeix--Raviart finite element, with the aim of constructing accurate approximations in such enriched elements. To achieve this goal, we respectively add three and seven weighted line integrals as enriched degrees of freedom. For each case, we present a necessary and sufficient condition under which these augmented elements are well-defined. For illustration purposes, we then use a general approach to define two-parameter families of admissible degrees of freedom. Additionally, we provide explicit expressions for the associated basis functions and subsequently introduce new quadratic and cubic approximation operators based on the proposed admissible elements. The efficiency of the enriched methods is compared to the triangular Crouzeix--Raviart element. As expected, the numerical results exhibit a significant improvement, confirming the effectiveness of the developed enrichment strategy.

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