E. Paillas

3.5k total citations
18 papers, 314 citations indexed

About

E. Paillas is a scholar working on Astronomy and Astrophysics, Instrumentation and Nuclear and High Energy Physics. According to data from OpenAlex, E. Paillas has authored 18 papers receiving a total of 314 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Astronomy and Astrophysics, 7 papers in Instrumentation and 5 papers in Nuclear and High Energy Physics. Recurrent topics in E. Paillas's work include Galaxies: Formation, Evolution, Phenomena (16 papers), Cosmology and Gravitation Theories (13 papers) and Astronomy and Astrophysical Research (7 papers). E. Paillas is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (16 papers), Cosmology and Gravitation Theories (13 papers) and Astronomy and Astrophysical Research (7 papers). E. Paillas collaborates with scholars based in United Kingdom, Canada and Chile. E. Paillas's co-authors include Nelson Padilla, Yan-Chuan Cai, Baojiu Li, Marius Cautun, Sownak Bose, Ariel G. Sánchez, P. B. Tissera, Claudia del P. Lagos, Will J. Percival and S. Nadathur and has published in prestigious journals such as The Astrophysical Journal, Monthly Notices of the Royal Astronomical Society and Astronomy and Astrophysics.

In The Last Decade

E. Paillas

16 papers receiving 301 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
E. Paillas United Kingdom 10 290 92 87 25 23 18 314
A. Balaguera-Antolínez Spain 12 291 1.0× 82 0.9× 124 1.4× 33 1.3× 22 1.0× 23 303
Bridget Falck United Kingdom 9 337 1.2× 69 0.8× 153 1.8× 21 0.8× 21 0.9× 15 360
Cristiano G. Sabiu South Korea 12 307 1.1× 76 0.8× 100 1.1× 22 0.9× 21 0.9× 24 330
S. Escoffier France 10 263 0.9× 87 0.9× 88 1.0× 37 1.5× 11 0.5× 18 301
Pauline Zarrouk United Kingdom 10 190 0.7× 60 0.7× 40 0.5× 18 0.7× 17 0.7× 14 203
D. Rubin United States 9 252 0.9× 50 0.5× 87 1.0× 12 0.5× 13 0.6× 31 333
Giulio Fabbian United Kingdom 12 337 1.2× 69 0.8× 134 1.5× 14 0.6× 14 0.6× 31 369
Matthew D. Olmstead United States 8 414 1.4× 83 0.9× 162 1.9× 23 0.9× 9 0.4× 9 442
P. G. Castro United Kingdom 8 280 1.0× 35 0.4× 77 0.9× 28 1.1× 15 0.7× 22 331
Long-Long Feng China 13 287 1.0× 59 0.6× 50 0.6× 13 0.5× 8 0.3× 42 326

Countries citing papers authored by E. Paillas

Since Specialization
Citations

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

Fields of papers citing papers by E. Paillas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of E. Paillas

This figure shows the co-authorship network connecting the top 25 collaborators of E. Paillas. A scholar is included among the top collaborators of E. Paillas 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 E. Paillas. E. Paillas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Ivanov, Mikhail M., Kazuyuki Akitsu, Raúl E. Angulo, et al.. (2025). A Parameter-masked Mock Data Challenge for Beyond-two-point Galaxy Clustering Statistics*. The Astrophysical Journal. 990(2). 99–99. 13 indexed citations
2.
Paillas, E., et al.. (2025). Constraining primordial non-Gaussianity with Density-Split Clustering. Journal of Cosmology and Astroparticle Physics. 2025(1). 26–26. 1 indexed citations
3.
Paillas, E., et al.. (2025). Modelling the BOSS void-galaxy cross-correlation function using a neural-network emulator. Journal of Cosmology and Astroparticle Physics. 2025(6). 1–1. 1 indexed citations
4.
Paillas, E., et al.. (2025). Cosmological constraints from the Minkowski functionals of the BOSS CMASS galaxy sample. Journal of Cosmology and Astroparticle Physics. 2025(5). 64–64.
5.
Paillas, E., Carolina Cuesta-Lazaro, Will J. Percival, et al.. (2024). Cosmological constraints from density-split clustering in the BOSS CMASS galaxy sample. Monthly Notices of the Royal Astronomical Society. 531(1). 898–918. 18 indexed citations
6.
Cuesta-Lazaro, Carolina, E. Paillas, Sihan Yuan, et al.. (2024). SUNBIRD: a simulation-based model for full-shape density-split clustering. Monthly Notices of the Royal Astronomical Society. 531(3). 3336–3356. 10 indexed citations
7.
Harnois-Déraps, Joachim, et al.. (2024). Constraining modified gravity with weak-lensing peaks. Monthly Notices of the Royal Astronomical Society. 533(3). 3546–3569. 7 indexed citations
8.
Radinović, Slađana, Hans A. Winther, S. Nadathur, et al.. (2024). Alcock–Paczyński effect on void-finding. Astronomy and Astrophysics. 691. A39–A39. 3 indexed citations
9.
10.
Percival, Will J., S. Nadathur, Hans A. Winther, et al.. (2023). Cosmological measurements from void-galaxy and galaxy-galaxy clustering in the Sloan Digital Sky Survey. Monthly Notices of the Royal Astronomical Society. 523(4). 6360–6370. 8 indexed citations
11.
Paillas, E., Carolina Cuesta-Lazaro, Pauline Zarrouk, et al.. (2023). Constraining νΛCDM with density-split clustering. Monthly Notices of the Royal Astronomical Society. 522(1). 606–625. 25 indexed citations
12.
Rosas-Guevara, Yetli, P. B. Tissera, Claudia del P. Lagos, E. Paillas, & Nelson Padilla. (2022). Revealing the properties of void galaxies and their assembly using the eagle simulation. Monthly Notices of the Royal Astronomical Society. 517(1). 712–731. 18 indexed citations
13.
Paillas, E., Yan-Chuan Cai, Nelson Padilla, & Ariel G. Sánchez. (2021). Redshift-space distortions with split densities. Monthly Notices of the Royal Astronomical Society. 505(4). 5731–5752. 38 indexed citations
14.
Paillas, E., et al.. (2020). Optimal void finders in weak lensing maps. Monthly Notices of the Royal Astronomical Society. 500(2). 2417–2439. 9 indexed citations
15.
Paillas, E., Marius Cautun, Baojiu Li, et al.. (2019). The Santiago–Harvard–Edinburgh–Durham void comparison II: unveiling the Vainshtein screening using weak lensing. Monthly Notices of the Royal Astronomical Society. 484(1). 1149–1165. 49 indexed citations
16.
Cautun, Marius, E. Paillas, Yan-Chuan Cai, et al.. (2018). The Santiago–Harvard–Edinburgh–Durham void comparison – I. SHEDding light on chameleon gravity tests. Monthly Notices of the Royal Astronomical Society. 476(3). 3195–3217. 77 indexed citations
17.
Padilla, Nelson, Joop Schaye, Robert A. Crain, et al.. (2018). The evolution of the baryon fraction in haloes as a cause of scatter in the galaxy stellar mass in theeaglesimulation. Monthly Notices of the Royal Astronomical Society. 482(3). 3261–3273. 12 indexed citations
18.
Paillas, E., Claudia del P. Lagos, Nelson Padilla, et al.. (2017). Baryon effects on void statistics in the EAGLE simulation. Monthly Notices of the Royal Astronomical Society. 470(4). 4434–4452. 25 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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