M. Khachatryan

1.3k total citations
10 papers, 94 citations indexed

About

M. Khachatryan is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Artificial Intelligence. According to data from OpenAlex, M. Khachatryan has authored 10 papers receiving a total of 94 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Nuclear and High Energy Physics, 6 papers in Astronomy and Astrophysics and 1 paper in Artificial Intelligence. Recurrent topics in M. Khachatryan's work include Astrophysics and Cosmic Phenomena (9 papers), Radio Astronomy Observations and Technology (4 papers) and Particle physics theoretical and experimental studies (3 papers). M. Khachatryan is often cited by papers focused on Astrophysics and Cosmic Phenomena (9 papers), Radio Astronomy Observations and Technology (4 papers) and Particle physics theoretical and experimental studies (3 papers). M. Khachatryan collaborates with scholars based in Italy, United States and Israel. M. Khachatryan's co-authors include N. Sahakyan, Sargis Gasparyan, Damien Bégué, P. Giommi, Asaf Pe’er, L. B. Weinstein, S. Dolan, G. D. Megias, A. Papadopoulou and O. Hen and has published in prestigious journals such as The Astrophysical Journal, Monthly Notices of the Royal Astronomical Society and The Astronomical Journal.

In The Last Decade

M. Khachatryan

8 papers receiving 64 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. Khachatryan Italy	7	86	54	9	9	8	10	94
Duarte Fontes Portugal	10	269 3.1×	51 0.9×	6 0.7×	8 0.9×	9 1.1×	18	275
E. Pueschel Germany	4	100 1.2×	68 1.3×	2 0.2×	5 0.6×	7 0.9×	13	105
C. Abellán Beteta Spain	7	186 2.2×	19 0.4×	6 0.7×	10 1.1×	10 1.3×	14	188
J. Müller Germany	6	129 1.5×	87 1.6×	8 0.9×	4 0.4×	9 1.1×	10	143
Selim Çetin Türkiye	8	131 1.5×	30 0.6×	17 1.9×	5 0.6×	5 0.6×	21	150
S. Prohira United States	6	87 1.0×	48 0.9×	8 0.9×	4 0.4×	3 0.4×	16	96
Jorge Otero-Santos Spain	6	59 0.7×	51 0.9×	9 1.0×	3 0.3×	4 0.5×	15	65
Cari Cesarotti United States	5	103 1.2×	31 0.6×	19 2.1×	4 0.4×	4 0.5×	9	120
Lukas Allwicher Switzerland	8	221 2.6×	38 0.7×	10 1.1×	11 1.2×	11 1.4×	11	223
Markus Bobrowski Germany	4	142 1.7×	28 0.5×	8 0.9×	5 0.6×	6 0.8×	5	144

Countries citing papers authored by M. Khachatryan

Since Specialization

Citations

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

Fields of papers citing papers by M. Khachatryan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Khachatryan

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

Sahakyan, N., et al.. (2025). Modeling Blazar Broadband Emission with Convolutional Neural Networks. III. Proton Synchrotron and Hybrid Models. The Astrophysical Journal. 990(2). 222–222.

Khachatryan, M., et al.. (2024). Persistence and positive steady states of a two-stage structured population model with mixed dispersals. Nonlinear Analysis Real World Applications. 81. 104182–104182.

Sahakyan, N., Damien Bégué, P. Giommi, et al.. (2024). Modeling Blazar Broadband Emission with Convolutional Neural Networks. II. External Compton Model. The Astrophysical Journal. 971(1). 70–70. 7 indexed citations

Sahakyan, N., et al.. (2024). Markarian Multiwavelength Data Center (MMDC): A Tool for Retrieving and Modeling Multitemporal, Multiwavelength, and Multimessenger Data from Blazar Observations. The Astronomical Journal. 168(6). 289–289. 7 indexed citations

Bégué, Damien, N. Sahakyan, P. Giommi, et al.. (2024). Modeling Blazar Broadband Emission with a Convolutional Neural Network. I. Synchrotron Self-Compton Model. The Astrophysical Journal. 963(1). 71–71. 12 indexed citations

Sahakyan, N., et al.. (2022). Gradient boosting decision trees classification of blazars of uncertain type in the fourth Fermi-LAT catalogue. Monthly Notices of the Royal Astronomical Society. 519(2). 3000–3010. 13 indexed citations

Sahakyan, N., et al.. (2022). Modelling the time variable spectral energy distribution of the blazar CTA 102 from 2008 to 2022. Monthly Notices of the Royal Astronomical Society. 517(2). 2757–2768. 13 indexed citations

Papadopoulou, A., S. Gardiner, S. Dytman, et al.. (2021). Inclusive electron scattering and the genie neutrino event generator. Physical review. D. 103(11). 15 indexed citations

Sahakyan, N., et al.. (2020). Exploring the Origin of Multiwavelength Emission from High-Redshift Blazar B3 1343 + 451. Astrophysics. 63(3). 334–348. 4 indexed citations

10.

Sahakyan, N., et al.. (2020). Multiwavelength study of high-redshift blazars. Monthly Notices of the Royal Astronomical Society. 498(2). 2594–2613. 23 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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