{"title":"Sectional Kolmogorov N-widths for parameter-dependent function spaces: a general framework with application to parametrized Friedrichs’ systems","authors":"Christian Engwer, Mario Ohlberger, Lukas Renelt","doi":"10.1007/s10444-026-10375-8","DOIUrl":"10.1007/s10444-026-10375-8","url":null,"abstract":"<div><p>We investigate parametrized variational problems where for each parameter the solution may originate from a different parameter-dependent function space. Our main motivation is the theory of Friedrichs’ systems, a large abstract class of linear PDE problems whose solutions are sought in operator- (and thus parameter-)dependent graph spaces. Other applications include function spaces on parametrized domains or discretizations involving data-dependent stabilizers. Concerning the set of all parameter-dependent solutions, we argue that in these cases, the interpretation as a “solution manifold” widely adopted in the model order reduction community is no longer applicable. Instead, we propose a novel framework based on the theory of fiber bundles and explain how established concepts such as approximability generalize by introducing a sectional Kolmogorov <i>N</i>-width. Further, we prove exponential approximation rates of this <i>N</i>-width if a norm equivalence criterion is fulfilled. Applying this result to problems with Friedrichs’ structure then gives a sufficient criterion that can be easily verified.</p></div>","PeriodicalId":50869,"journal":{"name":"Advances in Computational Mathematics","volume":"52 6","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149214567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Local multilevel preconditioned Jacobi-Davidson method for elliptic eigenvalue problems on adaptive meshes","authors":"Jianing Guo, Qigang Liang, Xuejun Xu","doi":"10.1007/s10444-026-10373-w","DOIUrl":"10.1007/s10444-026-10373-w","url":null,"abstract":"<div><p>In this work, we propose an efficient adaptive multilevel preconditioned Jacobi-Davidson (PJD) method for eigenvalue problems with singularity. Our multilevel method utilizes a local smoothing strategy to solve the preconditioned Jacobi-Davidson algebraic systems arising from adaptive finite element methods (AFEM). As a result, the algorithm holds optimal computational complexity <span>(varvec{O(N)})</span>. The theoretical analysis reveals that our method has a uniform convergence rate with respect to mesh levels and degrees of freedom. Further, the convergence rate is not affected by highly discontinuous coefficients within the domain. Numerical results verify our theoretical findings.</p></div>","PeriodicalId":50869,"journal":{"name":"Advances in Computational Mathematics","volume":"52 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149189367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paul Schwerdtner, Prakash Mohan, Julie Bessac, Marc T. Henry de Frahan, Benjamin Peherstorfer
{"title":"Operator inference aware quadratic manifolds with isotropic reduced coordinates for nonintrusive model reduction","authors":"Paul Schwerdtner, Prakash Mohan, Julie Bessac, Marc T. Henry de Frahan, Benjamin Peherstorfer","doi":"10.1007/s10444-026-10367-8","DOIUrl":"10.1007/s10444-026-10367-8","url":null,"abstract":"<div><p>Quadratic manifolds for nonintrusive reduced modeling are typically trained to minimize the reconstruction error on snapshot data, which means that the error of models fitted to the embedded data in downstream learning steps is ignored. In contrast, we propose a greedy training procedure that takes into account both the reconstruction error on the snapshot data and the prediction error of reduced models fitted to the data. Because our procedure learns quadratic manifolds with the objective of achieving accurate reduced models, it avoids oscillatory and other non-smooth embeddings that can hinder learning accurate reduced models. Numerical experiments on transport and turbulent flow problems show that quadratic manifolds trained with the proposed greedy approach lead to reduced models with up to two orders of magnitude higher accuracy than quadratic manifolds trained with respect to the reconstruction error alone.</p></div>","PeriodicalId":50869,"journal":{"name":"Advances in Computational Mathematics","volume":"52 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149090372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Image noise removal via Nash game theory involving non-local and fractional operators","authors":"Requia Addouch, Noureddine Moussaid, Omar Gouasnouane, Anouar Ben-loghfyry","doi":"10.1007/s10444-026-10371-y","DOIUrl":"10.1007/s10444-026-10371-y","url":null,"abstract":"<div><p>In this work, we introduce a novel image denoising model that combines fractional-order total variation (FOTV) and nonlocal operators within the framework of Nash game theory. The primary contributions of this work lie in the mathematical modeling, the theoretical well-posedness analysis, and the Nash game formulation, which provides a principled framework for balancing noise reduction and detail preservation. After establishing the existence and uniqueness of solutions to the proposed model, we validate its performance through extensive experiments on various test images. The results demonstrate that our method outperforms classical variational approaches, namely total variation (TV), FOTV, and nonlocal means (NLM) filtering, in terms of both visual quality and quantitative PSNR measures.</p></div>","PeriodicalId":50869,"journal":{"name":"Advances in Computational Mathematics","volume":"52 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149090374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"HDG methods for the semilinear elliptic optimal control problem: a priori and a posteriori error estimates","authors":"Huangxin Chen, Haitao Leng","doi":"10.1007/s10444-026-10370-z","DOIUrl":"10.1007/s10444-026-10370-z","url":null,"abstract":"<div><p>In this paper, we investigate a semilinear elliptic optimal control problem using a semidiscrete scheme in which the state and adjoint state variables are discretized by a hybridized discontinuous Galerkin (HDG) method, and the control variable is discretized by the variational discretization concept. For the HDG method applied to the semilinear elliptic equation, we prove a priori error estimates on quasi-uniform meshes and a posteriori error estimates on shape-regular meshes that satisfy the mesh condition (3.25). The global Lipschitz continuity on the nonlinear term is not required in the proofs. Then, these results are used to analyze the semilinear elliptic optimal control problem. As a consequence, by using the discrete functional analysis tools, we prove the existence of a subsequence of discrete solutions that converge to a solution of the continuous problem. Furthermore, for the control, state, and adjoint state variables, we prove a priori error estimates on quasi-uniform meshes and a posteriori error estimates on shape-regular meshes under the mesh condition (3.25) and the assumption that the second-order sufficient optimality conditions hold. Importantly, the proofs do not rely on the assumptions that the nonlinear term and its gradient are globally Lipschitz continuous, nor that the <span>(L^{infty })</span> norm of the difference between the adjoint state and its discretization is sufficiently small. Finally, we verify the theoretical results and show the robustness of the obtained a posteriori error estimators by two- and three-dimensional numerical examples.</p></div>","PeriodicalId":50869,"journal":{"name":"Advances in Computational Mathematics","volume":"52 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149090375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Eigenvalue bounds of a block three-by-three nonsymmetric positive semi-definite matrix","authors":"Sheng-Zhong Song, Zheng-Da Huang","doi":"10.1007/s10444-026-10368-7","DOIUrl":"10.1007/s10444-026-10368-7","url":null,"abstract":"<div><p>For a block three-by-three nonsymmetric positive semi-definite matrix that appears in many applications or in the study of preconditioning techniques, we estimate the lower and upper bounds of the real and the imaginary parts of eigenvalues of this matrix. The bounds are expressed in terms of the extreme eigenvalues or singular values of the associated block matrices. Numerical experiments demonstrate that our estimated bounds are relatively sharp and can indeed predict the effectiveness of the preconditioner.</p></div>","PeriodicalId":50869,"journal":{"name":"Advances in Computational Mathematics","volume":"52 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149090377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Atlas-based meshless finite differences for elliptic partial differential equations on manifolds represented as point clouds","authors":"Yichen Su, Ka Chun Cheung, Leevan Ling","doi":"10.1007/s10444-026-10369-6","DOIUrl":"10.1007/s10444-026-10369-6","url":null,"abstract":"<div><p>We present a systematic investigation of atlas-based radial basis function finite difference (RBFFD) methods for solving elliptic partial differential equations on smooth, compact surfaces represented as point clouds. This approach organizes point cloud data according to coordinate charts and computes differentiation weights collectively within each chart, contrasting with traditional RBFFD methods that construct independent stencils at each point. While the theoretical convergence framework has been established, practical implementation strategies and convergence behavior under different refinement regimes remain unexplored. We address these gaps by formalizing implementation strategies for both intrinsic and extrinsic formulations, including practical algorithms for atlas construction and local parameterization from point cloud data. We conduct convergence studies under two refinement scenarios: simultaneous refinement validates theoretical convergence rates, while the fixed-atlas regime reveals accuracy saturation due to geometric discretization error. We compare different local parameterization approaches and investigate weighted variants to improve method performance. Numerical experiments on various complex surfaces demonstrate that atlas-based RBFFD methods accurately solve elliptic problems without requiring explicit surface parameterizations or mesh connectivity.</p></div>","PeriodicalId":50869,"journal":{"name":"Advances in Computational Mathematics","volume":"52 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10444-026-10369-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149090373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Trefftz Discontinuous Galerkin methods for scattering by periodic structures","authors":"Armando Maria Monforte, Andrea Moiola","doi":"10.1007/s10444-026-10372-x","DOIUrl":"10.1007/s10444-026-10372-x","url":null,"abstract":"<div><p>We propose a Trefftz discontinuous Galerkin (TDG) method for the approximation of plane-wave scattering by periodic diffraction gratings, modelled by the two-dimensional Helmholtz equation. The periodic obstacle may include penetrable and impenetrable regions. The TDG method requires the approximation of the Dirichlet-to-Neumann (DtN) operator on the periodic cell faces, and relies on plane wave discrete spaces. For polygonal meshes, all linear-system entries can be computed analytically. Using a Rellich identity, we prove a new explicit stability estimate for the Helmholtz solution, which is robust in the small material jump limit.</p></div>","PeriodicalId":50869,"journal":{"name":"Advances in Computational Mathematics","volume":"52 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10444-026-10372-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Higher-order approximation rates for ReLU CNNs in Korobov spaces","authors":"Yuwen Li, Guozhi Zhang","doi":"10.1007/s10444-026-10348-x","DOIUrl":"10.1007/s10444-026-10348-x","url":null,"abstract":"<div><p>This paper investigates the <span>(L_p)</span> approximation error for higher-order Korobov functions using deep convolutional neural networks (CNNs) with rectified linear unit (ReLU) activation functions. For target functions having a mixed derivative of order <span>(m+1)</span> in each direction, we improve the classical approximation rate of second order to <span>((m+1))</span>-th order (modulo a logarithmic factor) in terms of the depth of CNNs. The key ingredients in our analysis include the <span>(L_p)</span> approximation error of sparse grid functions within higher-order Korobov spaces, the precise ReLU product factors decomposition of high-order sparse grid basis functions, and the approximation of polynomials with non-negative bounded input variables by CNNs. The results suggest that higher-order expressivity of CNNs does not severely suffer from the curse of dimensionality.</p></div>","PeriodicalId":50869,"journal":{"name":"Advances in Computational Mathematics","volume":"52 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149035306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"G-invariant representations using coorbits: bi-Lipschitz properties","authors":"Radu Balan, Efstratios Tsoukanis","doi":"10.1007/s10444-026-10363-y","DOIUrl":"10.1007/s10444-026-10363-y","url":null,"abstract":"<div><p>Let <span>({mathcal {V}})</span> be a finite-dimensional real vector space with a finite group <i>G</i> acting orthogonally on it. We address the general problem of constructing Euclidean-stable embeddings of the orbit space <span>({mathcal {V}}/G)</span>. Our approach builds on embeddings derived from subsets of sorted coorbits. The main result establishes that whenever such embeddings are injective, they are automatically bi-Lipschitz. Furthermore, we show that stable embeddings can be achieved in reduced dimensions, and that any continuous or Lipschitz <i>G</i>-invariant map can be factored through these embeddings.</p></div>","PeriodicalId":50869,"journal":{"name":"Advances in Computational Mathematics","volume":"52 5","pages":""},"PeriodicalIF":2.6,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10444-026-10363-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149035305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}