Abdulla Al Mamon

620 total citations
21 papers, 432 citations indexed

About

Abdulla Al Mamon is a scholar working on Astronomy and Astrophysics, Nuclear and High Energy Physics and Statistical and Nonlinear Physics. According to data from OpenAlex, Abdulla Al Mamon has authored 21 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Astronomy and Astrophysics, 15 papers in Nuclear and High Energy Physics and 2 papers in Statistical and Nonlinear Physics. Recurrent topics in Abdulla Al Mamon's work include Cosmology and Gravitation Theories (21 papers), Galaxies: Formation, Evolution, Phenomena (20 papers) and Black Holes and Theoretical Physics (13 papers). Abdulla Al Mamon is often cited by papers focused on Cosmology and Gravitation Theories (21 papers), Galaxies: Formation, Evolution, Phenomena (20 papers) and Black Holes and Theoretical Physics (13 papers). Abdulla Al Mamon collaborates with scholars based in India, Japan and South Africa. Abdulla Al Mamon's co-authors include Sudipta Das, Kazuharu Bamba, Andronikos Paliathanasis, Amir Hadi Ziaie, Umesh Kumar Sharma, Ambuj Kumar Mishra and Ujjal Debnath and has published in prestigious journals such as The European Physical Journal C, Journal of Cosmology and Astroparticle Physics and General Relativity and Gravitation.

In The Last Decade

Abdulla Al Mamon

21 papers receiving 404 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Abdulla Al Mamon India 11 423 326 39 37 7 21 432
Ankan Mukherjee India 11 417 1.0× 277 0.8× 35 0.9× 30 0.8× 2 0.3× 14 431
Juan Carlos Hidalgo Mexico 14 424 1.0× 282 0.9× 21 0.5× 18 0.5× 9 1.3× 50 442
Georges Obied United States 10 518 1.2× 429 1.3× 67 1.7× 26 0.7× 8 1.1× 12 541
Víctor H. Cárdenas Chile 14 296 0.7× 190 0.6× 26 0.7× 18 0.5× 4 0.6× 32 328
Ruchika Ruchika India 11 469 1.1× 294 0.9× 19 0.5× 25 0.7× 1 0.1× 14 497
M. Shahalam India 9 365 0.9× 281 0.9× 63 1.6× 34 0.9× 8 1.1× 17 370
Pavel D. Naselsky Russia 9 297 0.7× 113 0.3× 50 1.3× 33 0.9× 4 0.6× 14 313
Claudia Quercellini Italy 14 784 1.9× 563 1.7× 57 1.5× 29 0.8× 3 0.4× 19 790
Sudeep Das United States 12 373 0.9× 183 0.6× 16 0.4× 14 0.4× 4 0.6× 17 407
M. Migliaccio Italy 12 287 0.7× 144 0.4× 13 0.3× 39 1.1× 4 0.6× 23 321

Countries citing papers authored by Abdulla Al Mamon

Since Specialization
Citations

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

Fields of papers citing papers by Abdulla Al Mamon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Abdulla Al Mamon. 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 Abdulla Al Mamon. The network helps show where Abdulla Al Mamon may publish in the future.

Co-authorship network of co-authors of Abdulla Al Mamon

This figure shows the co-authorship network connecting the top 25 collaborators of Abdulla Al Mamon. A scholar is included among the top collaborators of Abdulla Al Mamon 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 Abdulla Al Mamon. Abdulla Al Mamon 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.
Mamon, Abdulla Al, et al.. (2023). Dynamical systems analysis of an interacting scalar field model in an anisotropic universe. Journal of Cosmology and Astroparticle Physics. 2023(10). 50–50. 5 indexed citations
2.
Sharma, Umesh Kumar, et al.. (2023). Interacting New Tsallis holographic dark energy. Chinese Journal of Physics. 89. 657–666. 1 indexed citations
3.
Mamon, Abdulla Al, et al.. (2023). Cosmic consequences of Barrow holographic dark energy with Granda–Oliveros cut-off in fractal cosmology. General Relativity and Gravitation. 55(6). 2 indexed citations
4.
Mamon, Abdulla Al, et al.. (2022). An extended analysis for a generalized Chaplygin gas model. The European Physical Journal C. 82(3). 10 indexed citations
5.
Mamon, Abdulla Al, et al.. (2022). Dynamical system analysis of logotropic dark fluid with a power law in the rest-mass energy density. Physics of the Dark Universe. 35. 100970–100970. 5 indexed citations
6.
Mamon, Abdulla Al, Ambuj Kumar Mishra, & Umesh Kumar Sharma. (2022). Barrow Holographic dark energy in fractal cosmology. International Journal of Geometric Methods in Modern Physics. 19(14). 13 indexed citations
7.
Mamon, Abdulla Al, et al.. (2021). Statefinder and Om Diagnostics for New Generalized Chaplygin Gas Model. Universe. 7(10). 362–362. 11 indexed citations
8.
Sharma, Umesh Kumar, et al.. (2021). Interacting Rényi Holographic Dark Energy in the Brans-Dicke Theory. Advances in High Energy Physics. 2021. 1–17. 12 indexed citations
9.
Mamon, Abdulla Al. (2021). Constraints on kinematic model from Pantheon SNIa, OHD and CMB shift parameter measurements. Modern Physics Letters A. 36(8). 2150049–2150049. 2 indexed citations
10.
Mamon, Abdulla Al, et al.. (2020). The logotropic dark fluid: Observational and thermodynamic constraints. International Journal of Modern Physics D. 29(15). 2050097–2050097. 6 indexed citations
11.
Mamon, Abdulla Al, Amir Hadi Ziaie, & Kazuharu Bamba. (2020). A generalized interacting Tsallis holographic dark energy model and its thermodynamic implications. The European Physical Journal C. 80(10). 30 indexed citations
12.
Mamon, Abdulla Al, et al.. (2020). Testing lambert W equation of state with observational hubble parameter data. New Astronomy. 86. 101567–101567. 1 indexed citations
13.
Mamon, Abdulla Al & Kazuharu Bamba. (2018). Observational constraints on the jerk parameter with the data of the Hubble parameter. The European Physical Journal C. 78(10). 67 indexed citations
14.
Mamon, Abdulla Al. (2018). Constraints on a generalized deceleration parameter from cosmic chronometers. Modern Physics Letters A. 33(10n11). 1850056–1850056. 41 indexed citations
15.
Mamon, Abdulla Al & Sudipta Das. (2017). A parametric reconstruction of the deceleration parameter. The European Physical Journal C. 77(7). 83 indexed citations
16.
Mamon, Abdulla Al. (2017). Reconstruction of interaction rate in holographic dark energy model with Hubble horizon as the infrared cut-off. International Journal of Modern Physics D. 26(11). 1750136–1750136. 16 indexed citations
17.
Mamon, Abdulla Al & Sudipta Das. (2015). Study of non-canonical scalar field model using various parametrizations of dark energy equation of state. The European Physical Journal C. 75(6). 9 indexed citations
18.
Das, Sudipta, Ujjal Debnath, & Abdulla Al Mamon. (2015). Generalized second law of thermodynamics for non-canonical scalar field model with corrected-entropy. The European Physical Journal C. 75(10). 9 indexed citations
19.
Das, Sudipta & Abdulla Al Mamon. (2014). Cosmic acceleration in non-canonical scalar field model: an interacting scenario. Astrophysics and Space Science. 355(2). 371–380. 22 indexed citations
20.
Das, Sudipta & Abdulla Al Mamon. (2014). An Interacting Model of Dark Energy in Brans-Dicke Theory. Astrophysics and Space Science. 351(2). 651–660. 16 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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