Christopher Bonnett

898 total citations
8 papers, 341 citations indexed

About

Christopher Bonnett is a scholar working on Astronomy and Astrophysics, Artificial Intelligence and Instrumentation. According to data from OpenAlex, Christopher Bonnett has authored 8 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Astronomy and Astrophysics, 3 papers in Artificial Intelligence and 2 papers in Instrumentation. Recurrent topics in Christopher Bonnett's work include Galaxies: Formation, Evolution, Phenomena (7 papers), Astronomy and Astrophysical Research (2 papers) and Cosmology and Gravitation Theories (2 papers). Christopher Bonnett is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (7 papers), Astronomy and Astrophysical Research (2 papers) and Cosmology and Gravitation Theories (2 papers). Christopher Bonnett collaborates with scholars based in Spain, United States and Germany. Christopher Bonnett's co-authors include Jean Coupon, J. Weller, Markus Michael Rau, S. Seitz, B. Hoyle, Y. Mellier, E. Semboloni, Liping Fu, Konrad Kuijken and Michael J. Hudson and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, Computer Physics Communications and Astrophysics Source Code Library.

In The Last Decade

Christopher Bonnett

8 papers receiving 334 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Christopher Bonnett Spain	7	294	157	44	41	34	8	341
Markus Michael Rau United States	12	222 0.8×	80 0.5×	76 1.7×	46 1.1×	18 0.5×	28	342
D. Tuccillo France	5	226 0.8×	122 0.8×	22 0.5×	42 1.0×	16 0.5×	5	290
J. L. Fischer United States	7	317 1.1×	199 1.3×	15 0.3×	44 1.1×	13 0.4×	7	366
Kai Polsterer Germany	11	206 0.7×	58 0.4×	45 1.0×	48 1.2×	40 1.2×	36	317
C. Bonnett United Kingdom	3	454 1.5×	168 1.1×	17 0.4×	29 0.7×	40 1.2×	3	504
W G Hartley United Kingdom	12	465 1.6×	267 1.7×	13 0.3×	58 1.4×	16 0.5×	16	509
T. M. C. Abbott Chile	2	414 1.4×	144 0.9×	17 0.4×	24 0.6×	34 1.0×	2	464
C. Marinoni France	15	621 2.1×	244 1.6×	42 1.0×	46 1.1×	19 0.6×	26	695
I. Sevilla-Noarbe Spain	9	169 0.6×	56 0.4×	22 0.5×	26 0.6×	11 0.3×	27	215
Benjamin Giblin United Kingdom	15	607 2.1×	234 1.5×	34 0.8×	23 0.6×	64 1.9×	25	672

Countries citing papers authored by Christopher Bonnett

Since Specialization

Citations

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

Fields of papers citing papers by Christopher Bonnett

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christopher Bonnett

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

All Works

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8 of 8 papers shown

1.

Bonnett, Christopher. (2015). Using neural networks to estimate redshift distributions. An application to CFHTLenS. Monthly Notices of the Royal Astronomical Society. 449(1). 1043–1056. 37 indexed citations

2.

Hoyle, B., Markus Michael Rau, K. Paech, et al.. (2015). Anomaly detection for machine learning redshifts applied to SDSS galaxies. Monthly Notices of the Royal Astronomical Society. 452(4). 4183–4194. 44 indexed citations

3.

Hoyle, B., Markus Michael Rau, Christopher Bonnett, S. Seitz, & J. Weller. (2015). Data augmentation for machine learning redshifts applied to Sloan Digital Sky Survey galaxies. Monthly Notices of the Royal Astronomical Society. 450(1). 305–316. 28 indexed citations

4.

Kilbinger, M., Christopher Bonnett, & Jean Coupon. (2014). athena: Tree code for second-order correlation functions. Astrophysics Source Code Library. 16 indexed citations

5.

Cárdenas‐Montes, Miguel, et al.. (2014). POSTER: High-performance implementations for shear-shear correlation calculation. 8109. 290–291. 1 indexed citations

6.

Hudson, Michael J., B. Gillis, Jean Coupon, et al.. (2014). CFHTLenS: co-evolution of galaxies and their dark matter haloes. Monthly Notices of the Royal Astronomical Society. 447(1). 298–314. 95 indexed citations

7.

Velander, M., Edo van Uitert, Henk Hoekstra, et al.. (2013). CFHTLenS: the relation between galaxy dark matter haloes and baryons from weak gravitational lensing. Monthly Notices of the Royal Astronomical Society. 437(3). 2111–2136. 112 indexed citations

8.

Cárdenas‐Montes, Miguel, et al.. (2013). GPU-based shear–shear correlation calculation. Computer Physics Communications. 185(1). 11–18. 8 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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