{"title":"Efficient solution of sequences of parametrized Lyapunov equations with applications","authors":"Davide Palitta, Zoran Tomljanović, Ivica Nakić, Jens Saak","doi":"arxiv-2312.08201","DOIUrl":"https://doi.org/arxiv-2312.08201","url":null,"abstract":"Sequences of parametrized Lyapunov equations can be encountered in many\u0000application settings. Moreover, solutions of such equations are often\u0000intermediate steps of an overall procedure whose main goal is the computation\u0000of quantities of the form $f(X)$ where $X$ denotes the solution of a Lyapunov\u0000equation. We are interested in addressing problems where the parameter\u0000dependency of the coefficient matrix is encoded as a low-rank modification to a\u0000emph{seed}, fixed matrix. We propose two novel numerical procedures that fully\u0000exploit such a common structure. The first one builds upon recycling Krylov\u0000techniques, and it is well-suited for small dimensional problems as it makes\u0000use of dense numerical linear algebra tools. The second algorithm can instead\u0000address large-scale problems by relying on state-of-the-art projection\u0000techniques based on the extended Krylov subspace. We test the new algorithms on\u0000several problems arising in the study of damped vibrational systems and the\u0000analyses of output synchronization problems for multi-agent systems. Our\u0000results show that the algorithms we propose are superior to state-of-the-art\u0000techniques as they are able to remarkably speed up the computation of accurate\u0000solutions.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138630442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Convergence analysis of Hermite approximations for analytic functions","authors":"Haiyong Wang, Lun Zhang","doi":"arxiv-2312.07940","DOIUrl":"https://doi.org/arxiv-2312.07940","url":null,"abstract":"In this paper, we present a rigorous analysis of root-exponential convergence\u0000of Hermite approximations, including projection and interpolation methods, for\u0000functions that are analytic in an infinite strip containing the real axis and\u0000satisfy certain restrictions on the asymptotic behavior at infinity within this\u0000strip. Asymptotically sharp error bounds in the weighted and maximum norms are\u0000derived. The key ingredients of our analysis are some remarkable contour\u0000integral representations for the Hermite coefficients and the remainder of\u0000Hermite spectral interpolations. Further extensions to Gauss--Hermite\u0000quadrature, Hermite spectral differentiations, generalized Hermite spectral\u0000approximations and the scaling factor of Hermite approximation are also\u0000discussed. Numerical experiments confirm our theoretical results.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138630212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anna Pidnebesna, David Hartman, Aneta Pokorná, Matěj Straka, Jaroslav Hlinka
{"title":"Computing approximate symmetries of complex networks","authors":"Anna Pidnebesna, David Hartman, Aneta Pokorná, Matěj Straka, Jaroslav Hlinka","doi":"arxiv-2312.08042","DOIUrl":"https://doi.org/arxiv-2312.08042","url":null,"abstract":"The symmetry of complex networks is a global property that has recently\u0000gained attention since MacArthur et al. 2008 showed that many real-world\u0000networks contain a considerable number of symmetries. These authors work with a\u0000very strict symmetry definition based on the network's automorphism. The\u0000potential problem with this approach is that even a slight change in the\u0000graph's structure can remove or create some symmetry. Recently, Liu 2020\u0000proposed to use an approximate automorphism instead of strict automorphism.\u0000This method can discover symmetries in the network while accepting some minor\u0000imperfections in their structure. The proposed numerical method, however,\u0000exhibits some performance problems and has some limitations while it assumes\u0000the absence of fixed points. In this work, we exploit alternative approaches\u0000recently developed for treating the Graph Matching Problem and propose a\u0000method, which we will refer to as Quadratic Symmetry Approximator (QSA), to\u0000address the aforementioned shortcomings. To test our method, we propose a set\u0000of random graph models suitable for assessing a wide family of approximate\u0000symmetry algorithms. The performance of our method is also demonstrated on\u0000brain networks.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138630314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rectified deep neural networks overcome the curse of dimensionality when approximating solutions of McKean--Vlasov stochastic differential equations","authors":"Ariel Neufeld, Tuan Anh Nguyen","doi":"arxiv-2312.07042","DOIUrl":"https://doi.org/arxiv-2312.07042","url":null,"abstract":"In this paper we prove that rectified deep neural networks do not suffer from\u0000the curse of dimensionality when approximating McKean--Vlasov SDEs in the sense\u0000that the number of parameters in the deep neural networks only grows\u0000polynomially in the space dimension $d$ of the SDE and the reciprocal of the\u0000accuracy $epsilon$.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138629920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Error Analysis for the Implicit Boundary Integral Method","authors":"Yimin Zhong, Kui Ren, Olof Runborg, Richard Tsai","doi":"arxiv-2312.07722","DOIUrl":"https://doi.org/arxiv-2312.07722","url":null,"abstract":"The implicit boundary integral method (IBIM) provides a framework to\u0000construct quadrature rules on regular lattices for integrals over irregular\u0000domain boundaries. This work provides a systematic error analysis for IBIMs on\u0000uniform Cartesian grids for boundaries with different degree of regularities.\u0000We first show that the quadrature error gains an addition order of\u0000$frac{d-1}{2}$ from the curvature for a strongly convex smooth boundary due to\u0000the ``randomness'' in the signed distances. This gain is discounted for\u0000degenerated convex surfaces. We then extend the error estimate to general\u0000boundaries under some special circumstances, including how quadrature error\u0000depends on the boundary's local geometry relative to the underlying grid.\u0000Bounds on the variance of the quadrature error under random shifts and\u0000rotations of the lattices are also derived.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138630132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Discretely Nonlinearly Stable Weight-Adjusted Flux Reconstruction High-Order Method for Compressible Flows on Curvilinear Grids","authors":"Alexander Cicchino, Siva Nadarajah","doi":"arxiv-2312.07725","DOIUrl":"https://doi.org/arxiv-2312.07725","url":null,"abstract":"Provable nonlinear stability bounds the discrete approximation and ensures\u0000that the discretization does not diverge. For high-order methods, discrete\u0000nonlinear stability and entropy stability, have been successfully implemented\u0000for discontinuous Galerkin (DG) and residual distribution schemes, where the\u0000stability proofs depend on properties of L2-norms. In this paper, nonlinearly\u0000stable flux reconstruction (NSFR) schemes are developed for three-dimensional\u0000compressible flow in curvilinear coordinates. NSFR is derived by merging the\u0000energy stable FR (ESFR) framework with entropy stable DG schemes. NSFR is\u0000demonstrated to use larger time-steps than DG due to the ESFR correction\u0000functions. NSFR differs from ESFR schemes in the literature since it\u0000incorporates the FR correction functions on the volume terms through the use of\u0000a modified mass matrix. We also prove that discrete kinetic energy stability\u0000cannot be preserved to machine precision for quadrature rules where the surface\u0000quadrature is not a subset of the volume quadrature. This paper also presents\u0000the NSFR modified mass matrix in a weight-adjusted form. This form reduces the\u0000computational cost in curvilinear coordinates through sum-fcatorization and\u0000low-storage techniques. The nonlinear stability properties of the scheme are\u0000verified on a nonsymmetric curvilinear grid for the inviscid Taylor-Green\u0000vortex problem and the correct orders of convergence were obtained for a\u0000manufactured solution. Lastly, we perform a computational cost comparison\u0000between conservative DG, overintegrated DG, and our proposed entropy conserving\u0000NSFR scheme, and find that our proposed entropy conserving NSFR scheme is\u0000computationally competitive with the conservative DG scheme.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138630638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mirco Ciallella, Stephane Clain, Elena Gaburro, Mario Ricchiuto
{"title":"Very high order treatment of embedded curved boundaries in compressible flows: ADER discontinuous Galerkin with a space-time Reconstruction for Off-site data","authors":"Mirco Ciallella, Stephane Clain, Elena Gaburro, Mario Ricchiuto","doi":"arxiv-2312.07170","DOIUrl":"https://doi.org/arxiv-2312.07170","url":null,"abstract":"In this paper we present a novel approach for the design of high order\u0000general boundary conditions when approximating solutions of the Euler equations\u0000on domains with curved boundaries, using meshes which may not be boundary\u0000conformal. When dealing with curved boundaries and/or unfitted discretizations,\u0000the consistency of boundary conditions is a well-known challenge, especially in\u0000the context of high order schemes. In order to tackle such consistency\u0000problems, the so-called Reconstruction for Off-site Data (ROD) method has been\u0000recently introduced in the finite volume framework: it is based on performing a\u0000boundary polynomial reconstruction that embeds the considered boundary\u0000treatment thanks to the implementation of a constrained minimization problem.\u0000This work is devoted to the development of the ROD approach in the context of\u0000discontinuous finite elements. We use the genuine space-time nature of the\u0000local ADER predictors to reformulate the ROD as a single space-time\u0000reconstruction procedure. This allows us to avoid a new reconstruction (linear\u0000system inversion) at each sub-time node and retrieve a single space-time\u0000polynomial that embeds the considered boundary conditions for the entire\u0000space-time element. Several numerical experiments are presented proving the\u0000consistency of the new approach for all kinds of boundary conditions.\u0000Computations involving the interaction of shocks with embedded curved\u0000boundaries are made possible through an a posteriori limiting technique.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"86 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138630206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proving the stability estimates of variational least-squares Kernel-Based methods","authors":"Meng Chen, Leevan Ling, Dongfang Yun","doi":"arxiv-2312.07080","DOIUrl":"https://doi.org/arxiv-2312.07080","url":null,"abstract":"Motivated by the need for the rigorous analysis of the numerical stability of\u0000variational least-squares kernel-based methods for solving second-order\u0000elliptic partial differential equations, we provide previously lacking\u0000stability inequalities. This fills a significant theoretical gap in the\u0000previous work [Comput. Math. Appl. 103 (2021) 1-11], which provided error\u0000estimates based on a conjecture on the stability. With the stability estimate\u0000now rigorously proven, we complete the theoretical foundations and compare the\u0000convergence behavior to the proven rates. Furthermore, we establish another\u0000stability inequality involving weighted-discrete norms, and provide a\u0000theoretical proof demonstrating that the exact quadrature weights are not\u0000necessary for the weighted least-squares kernel-based collocation method to\u0000converge. Our novel theoretical insights are validated by numerical examples,\u0000which showcase the relative efficiency and accuracy of these methods on data\u0000sets with large mesh ratios. The results confirm our theoretical predictions\u0000regarding the performance of variational least-squares kernel-based method,\u0000least-squares kernel-based collocation method, and our new weighted\u0000least-squares kernel-based collocation method. Most importantly, our results\u0000demonstrate that all methods converge at the same rate, validating the\u0000convergence theory of weighted least-squares in our proven theories.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"169 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138630149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aljowhara H. Honain, Khaled M. Furati, Ibrahim O. Sarumi, Abdul Q. M. Khaliq
{"title":"Rational Approximations for Oscillatory Two-Parameter Mittag-Leffler Function","authors":"Aljowhara H. Honain, Khaled M. Furati, Ibrahim O. Sarumi, Abdul Q. M. Khaliq","doi":"arxiv-2312.07444","DOIUrl":"https://doi.org/arxiv-2312.07444","url":null,"abstract":"The two-parameter Mittag-Leffler function $E_{alpha, beta}$ is of\u0000fundamental importance in fractional calculus. It appears frequently in the\u0000solutions of fractional differential and integral equations. Nonetheless, this\u0000vital function is often expensive to compute. Several attempts have been made\u0000to construct cost-effective and accurate approximations. These attempts focus\u0000mainly on the completely monotone Mittag-Leffler functions. However, when\u0000$alpha > 1$ the monotonicity property is largely lost and as such roots and\u0000oscillations are exhibited. Consequently, existing approximants constructed\u0000mainly for $alpha in (0,1)$ often fail to capture this oscillatory behavior.\u0000In this paper, we construct computationally efficient and accurate rational\u0000approximants for $E_{alpha, beta}(-t)$, $t ge 0$, with $alpha in (1,2)$.\u0000This construction is fundamentally based on the decomposition of Mittag-Leffler\u0000function with real roots into one without and a polynomial. Following which new\u0000approximants are constructed by combining the global Pad'e approximation with\u0000a polynomial of appropriate degree. The rational approximants are extended to\u0000approximation of matrix Mittag-Leffler and different approaches to achieve\u0000efficient implementation for matrix arguments are discussed. Numerical\u0000experiments are provided to illustrate the significant accuracy improvement\u0000achieved by the proposed approximants.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138629921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Splitting ADI scheme for fractional Laplacian wave equations","authors":"Tao Sun, Hai-Wei Sun","doi":"arxiv-2312.06206","DOIUrl":"https://doi.org/arxiv-2312.06206","url":null,"abstract":"In this paper, we investigate the numerical solution of the two-dimensional\u0000fractional Laplacian wave equations. After splitting out the Riesz fractional\u0000derivatives from the fractional Laplacian, we treat the Riesz fractional\u0000derivatives with an implicit scheme while solving the rest part explicitly.\u0000Thanks to the tensor structure of the Riesz fractional derivatives, a splitting\u0000alternative direction implicit (S-ADI) scheme is proposed by incorporating an\u0000ADI remainder. Then the Gohberg-Semencul formula, combined with fast Fourier\u0000transform, is proposed to solve the derived Toeplitz linear systems at each\u0000time integration. Theoretically, we demonstrate that the S-ADI scheme is\u0000unconditionally stable and possesses second-order accuracy. Finally, numerical\u0000experiments are performed to demonstrate the accuracy and efficiency of the\u0000S-ADI scheme.","PeriodicalId":501061,"journal":{"name":"arXiv - CS - Numerical Analysis","volume":"98 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138574863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}