Cavoretto, R.

De Rossi, A.

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Institutional Research Information System University of Turin

Special Issue SA2022 – Software for Approximation 2022, Volume 15 · 2022 · Pages i–iiSoftware for Approximation 2022 (SA2022)Roberto Cavoretto a,b · Alessandra De Rossi a,bAbstractThe guest editors provide a summary of the main facts about the Workshop “Software for Approximation2022” (SA2022) held at the Department of Mathematics “Giuseppe Peano” of the University of Torino(Italy), on February 3-4, 2022. This workshop was organized in collaboration with MathWorks, withthe goal to bring together researchers working in different fields of approximation and implementingalgorithms in MATLAB or other programming languages.This Special Issue contains peer-reviewed original articles appearing on volume 15 (2022) of the journal “Dolomites ResearchNotes on Approximation. The volume collects software-oriented papers dealing with new research results presented at theWorkshop “Software for Approximation 2022” (SA2022) held – in hybrid form – at the Department of Mathematics “GiuseppePeano” of the University of Torino (Italy), on February 3-4, 2022.The entire details of the workshop are available on the webpagehttps://sites.google.com/view/sa2022torino.Throughout this two-day event, out of 72 participants we had a total of 20 scientific communications, consisting of 1 plenarytalk and 19 contributed talks, in the field of Approximation Theory and its Applications. All talks were focused on emphasizingthe main features of the developed software, also highlighting the main implementation details.Figure 1: Professor Alessandra De Rossi during Paolo Panarese’s plenary talk.The approximation software discussed in this volume refers to several research topics like quasi-MonteCarlo cubature [8],differentiation by interpolating polynomials [7], kernel-based approximation [9], partition of unity methods [3, 4], numericalsolution of integral equations [2], numerical methods for stiff problems [6] and phase field models [5], algorithms for computationof Lebesgue constants [1], and an overview of some approximation techniques [10].aDepartment of Mathematics “Giuseppe Peano”, University of Torino, via Carlo Alberto 10, 10123 Torino, ItalybMember of the INdAM Research group GNCSCavoretto · De Rossi iiFinally, we would like to thank the scientific and organizing committees, the local organizers, the speakers and all theparticipants for making the workshop possible. Last but not least we gratefully acknowledge support from the Department ofMathematics “Giuseppe Peano” of the University of Torino, the Gruppo Nazionale per il Calcolo Scientifico (GNCS) of INdAM,MathWorks, the Research ITalian network on Approximation (RITA), and the UMI Group TAA (Teoria dell’Approssimazione eApplicazioni).References[1] L. Bruni Bruno, A. Alonso Rodríguez, F. Rapetti. Computing weights for high order Whitney edge elements. Dolomites Res. Notes Approx.,Special Issue SA2022, 15:1–12, 2022.[2] I. M. Bulai, M. C. De Bonis, C. Laurita, V. Sagaria. MatLab toolbox for the numerical solution of linear Volterra integral equations arising inmetastatic tumor growth models. Dolomites Res. Notes Approx., Special Issue SA2022, 15:13–24, 2022.[3] R. Cavoretto, A. De Rossi, W. Erb. GBFPUM - A MATLAB package for partition of unity based signal interpolation and approximation ongraphs. Dolomites Res. Notes Approx., Special Issue SA2022, 15:25–34, 2022.[4] R. Cavoretto, A. De Rossi, S. Lancellotti, E. Perracchione. Software implementation of the partition of unity method. Dolomites Res. NotesApprox., Special Issue SA2022, 15:35–46, 2022.[5] D. Conte, G. Frasca-Caccia. A MATLAB code for the computational solution of a phase field model for pitting corrosion. Dolomites Res. NotesApprox., Special Issue SA2022, 15:47–65, 2022.[6] D. Conte, G. Pagano, B. Paternoster. Two classes of linearly implicit numerical methods for stiff problems: analysis and MATLAB software.Dolomites Res. Notes Approx., Special Issue SA2022, 15:66–80, 2022.[7] F. Dell’Accio, F. Di Tommaso, N. Siar, M. Vianello. DISC: an adaptive numerical Differentiator by local polynomial Interpolation onmultivariate SCattered data. Dolomites Res. Notes Approx., Special Issue SA2022, 15:81–91, 2022.[8] G. Elefante, A. Sommariva, M. Vianello. CQMC: an improved code for low-dimensional Compressed Quasi-MonteCarlo cubature. DolomitesRes. Notes Approx., Special Issue SA2022, 15:92–100, 2022.[9] F. Marchetti. A note on the usage of the pinv MATLAB function. Dolomites Res. Notes Approx., Special Issue SA2022, 15:101–108, 2022.[10] P. Panarese. Approximation techniques with MATLAB. Dolomites Res. Notes Approx., Special Issue SA2022, 15:109–140, 2022.Dolomites Research Notes on Approximation ISSN 2035-6803

Software for Approximation 2022 (SA2022)

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Software for Approximation 2022 (SA2022)

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