Silvia Noschese

693 total citations
39 papers, 428 citations indexed

About

Silvia Noschese is a scholar working on Computational Theory and Mathematics, Atomic and Molecular Physics, and Optics and Statistical and Nonlinear Physics. According to data from OpenAlex, Silvia Noschese has authored 39 papers receiving a total of 428 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computational Theory and Mathematics, 14 papers in Atomic and Molecular Physics, and Optics and 13 papers in Statistical and Nonlinear Physics. Recurrent topics in Silvia Noschese's work include Matrix Theory and Algorithms (23 papers), Numerical methods in inverse problems (12 papers) and Electromagnetic Scattering and Analysis (11 papers). Silvia Noschese is often cited by papers focused on Matrix Theory and Algorithms (23 papers), Numerical methods in inverse problems (12 papers) and Electromagnetic Scattering and Analysis (11 papers). Silvia Noschese collaborates with scholars based in Italy, United States and Morocco. Silvia Noschese's co-authors include Lothar Reichel, Guang-Xin Huang, Paolo Buttà, Michiel E. Hochstenbach, Nicola Guglielmi, G. Rodríguez, Paolo Emilio Ricci and Pierpaolo Natalini and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Computational and Applied Mathematics and Linear Algebra and its Applications.

In The Last Decade

Silvia Noschese

35 papers receiving 414 citations

Peers

Silvia Noschese
Comparison fields: 5 of 73
  • Computational Theory and Mathematics 175
  • Statistical and Nonlinear Physics 93
  • Mathematical Physics 92
  • Applied Mathematics 92
  • Atomic and Molecular Physics, and Optics 88
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Ivan Slapničar Croatia View profile →
Citations per field, relative to Silvia Noschese
Silvia Noschese · 1×
Citations per year, relative to Silvia Noschese
Silvia Noschese · 1×

Countries citing papers authored by Silvia Noschese

Since Specialization
Citations

This map shows the geographic impact of Silvia Noschese's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Silvia Noschese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Silvia Noschese more than expected).

Fields of papers citing papers by Silvia Noschese

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Silvia Noschese. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Silvia Noschese. The network helps show where Silvia Noschese may publish in the future.

Co-authorship network of co-authors of Silvia Noschese

This figure shows the co-authorship network connecting the top 25 collaborators of Silvia Noschese. A scholar is included among the top collaborators of Silvia Noschese based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Silvia Noschese. Silvia Noschese is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 0
2 1
3 6
4 1
5 9
6 4
7 7
8 18
9 18
10 4
11 1
12 2
13
The structured distance to normality of an irreducible real tridiagonal matrix.
14
14 18
15 12
16 26
17
On the eigenvalues of a kernel considered by A.M. Ostrowski
0
18
An iterative method for computing the eigenvalues of second kind Fredholm operators and applications
1
19 5
20 1

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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