Martin Eriksen

1.5k total citations
23 papers, 243 citations indexed

About

Martin Eriksen is a scholar working on Astronomy and Astrophysics, Instrumentation and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Martin Eriksen has authored 23 papers receiving a total of 243 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Astronomy and Astrophysics, 9 papers in Instrumentation and 4 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Martin Eriksen's work include Galaxies: Formation, Evolution, Phenomena (16 papers), Astronomy and Astrophysical Research (9 papers) and Adaptive optics and wavefront sensing (4 papers). Martin Eriksen is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (16 papers), Astronomy and Astrophysical Research (9 papers) and Adaptive optics and wavefront sensing (4 papers). Martin Eriksen collaborates with scholars based in Spain, Netherlands and United Kingdom. Martin Eriksen's co-authors include E. Gaztañaga, F. J. Castander, R. Miquel, Henk Hoekstra, P. Fosalba, Anna Cabré, C. Sánchez, M. Crocce, F. Köhlinger and A. Alarcon and has published in prestigious journals such as Advanced Materials, Monthly Notices of the Royal Astronomical Society and Astronomy and Astrophysics.

In The Last Decade

Martin Eriksen

21 papers receiving 231 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Martin Eriksen Spain 11 205 83 31 30 26 23 243
J. Carretero Spain 9 239 1.2× 110 1.3× 28 0.9× 22 0.7× 36 1.4× 16 262
Mohammadjavad Vakili Netherlands 10 214 1.0× 105 1.3× 28 0.9× 19 0.6× 18 0.7× 12 234
Y. Ascasíbar Netherlands 6 282 1.4× 133 1.6× 56 1.8× 31 1.0× 17 0.7× 12 311
Yolanda Jiménez-Teja Brazil 9 283 1.4× 147 1.8× 34 1.1× 31 1.0× 14 0.5× 16 303
N. Roy Italy 7 165 0.8× 101 1.2× 12 0.4× 22 0.7× 19 0.7× 9 183
F. Brimioulle Germany 9 305 1.5× 151 1.8× 44 1.4× 41 1.4× 30 1.2× 10 320
Lyndsay Old United Kingdom 9 223 1.1× 139 1.7× 18 0.6× 12 0.4× 21 0.8× 9 243
W. O'Mullane United States 2 224 1.1× 90 1.1× 29 0.9× 12 0.4× 31 1.2× 5 254
Sarah Casura Australia 9 271 1.3× 146 1.8× 40 1.3× 13 0.4× 18 0.7× 20 308
Francisco Prada Spain 11 240 1.2× 132 1.6× 49 1.6× 19 0.6× 15 0.6× 14 263

Countries citing papers authored by Martin Eriksen

Since Specialization
Citations

This map shows the geographic impact of Martin Eriksen'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 Martin Eriksen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Eriksen more than expected).

Fields of papers citing papers by Martin Eriksen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin Eriksen. 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 Martin Eriksen. The network helps show where Martin Eriksen may publish in the future.

Co-authorship network of co-authors of Martin Eriksen

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Eriksen. A scholar is included among the top collaborators of Martin Eriksen 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 Martin Eriksen. Martin Eriksen 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
1.
Chávez‐Ángel, Emigdio, Martin Eriksen, Alejandro Castro‐Álvarez, et al.. (2025). Applied Artificial Intelligence in Materials Science and Material Design. Advanced Intelligent Systems. 7(8). 13 indexed citations
2.
Baugh, C. M., E. Gaztañaga, F. J. Castander, et al.. (2025). ANNZ+: an enhanced photometric redshift estimation algorithm with applications on the PAU survey. Journal of Cosmology and Astroparticle Physics. 2025(1). 97–97.
3.
4.
Botifoll, Marc, Enzo Rotunno, María Chiara Spadaro, et al.. (2025). Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Advanced Materials. e06785–e06785. 2 indexed citations
5.
Spinoso, Daniele, P. Arnalte-Mur, A. Fernández-Soto, et al.. (2024). The PAU Survey: The quasar Lyα and UV luminosity functions at 2.7 < z < 5.3. Astronomy and Astrophysics. 690. A388–A388. 3 indexed citations
6.
Csizi, B., Luca Tortorelli, M. Siudek, et al.. (2024). The PAU Survey: Galaxy stellar population properties estimates with narrowband data. Astronomy and Astrophysics. 689. A37–A37. 2 indexed citations
7.
Joachimi, Benjamin, Martin Eriksen, M. Siudek, et al.. (2021). The PAU Survey: narrow-band photometric redshifts using Gaussian processes. Monthly Notices of the Royal Astronomical Society. 503(3). 4118–4135. 9 indexed citations
8.
Eriksen, Martin, A. Amara, J. Carretero, et al.. (2021). The PAU survey: estimating galaxy photometry with deep learning. Monthly Notices of the Royal Astronomical Society. 506(3). 4048–4069. 10 indexed citations
9.
Eriksen, Martin, A. Alarcon, J. Carretero, et al.. (2020). The PAU Survey: Photometric redshifts using transfer learning from simulations. Monthly Notices of the Royal Astronomical Society. 497(4). 4565–4579. 15 indexed citations
10.
Gaztañaga, E., Rupert A. C. Croft, J. Carretero, et al.. (2020). The PAU survey: Ly α intensity mapping forecast. Monthly Notices of the Royal Astronomical Society. 501(3). 3883–3899. 11 indexed citations
11.
Cabayol-Garcia, L., Martin Eriksen, A. Alarcon, et al.. (2019). The PAU Survey: background light estimation with deep learning techniques. Monthly Notices of the Royal Astronomical Society. 491(4). 5392–5405. 3 indexed citations
12.
Norberg, P., C. M. Baugh, A. Alarcon, et al.. (2018). The PAU Survey: spectral features and galaxy clustering using simulated narrow-band photometry. Monthly Notices of the Royal Astronomical Society. 481(3). 4221–4235. 12 indexed citations
13.
Eriksen, Martin & Henk Hoekstra. (2018). Implications of a wavelength-dependent PSF for weak lensing measurements. Monthly Notices of the Royal Astronomical Society. 477(3). 3433–3448. 7 indexed citations
14.
Eriksen, Martin & E. Gaztañaga. (2018). Combining spectroscopic and photometric surveys using angular cross-correlations – III. Galaxy bias and stochasticity. Monthly Notices of the Royal Astronomical Society. 480(4). 5226–5241. 4 indexed citations
15.
Carretero, J., P. Tallada-Crespí, F. J. Castander, et al.. (2017). CosmoHub and SciPIC: Massive cosmological data analysis, distribution and generation using a Big Data platform. 488–488. 17 indexed citations
16.
Eriksen, Martin & E. Gaztañaga. (2015). Combining spectroscopic and photometric surveys using angular cross-correlations – I. Algorithm and modelling. Monthly Notices of the Royal Astronomical Society. 452(2). 2149–2167. 8 indexed citations
17.
Eriksen, Martin & E. Gaztañaga. (2015). Combining spectroscopic and photometric surveys using angular cross-correlations – II. Parameter constraints from different physical effects. Monthly Notices of the Royal Astronomical Society. 452(2). 2168–2184. 12 indexed citations
18.
Eriksen, Martin & E. Gaztañaga. (2015). Combining spectroscopic and photometric surveys: Same or different sky?. Monthly Notices of the Royal Astronomical Society. 451(2). 1553–1560. 11 indexed citations
19.
Miquel, R., et al.. (2014). Precise photometric redshifts with a narrow-band filter set: the PAU survey at the William Herschel Telescope. Monthly Notices of the Royal Astronomical Society. 442(1). 92–109. 36 indexed citations
20.
Furnes, Gunnar Κ., et al.. (1998). A Field Study of Flow Induced Vibrations on a Deepwater Drilling Riser. Offshore Technology Conference. 3 indexed citations

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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