A. Mott

8.7k total citations
7 papers, 161 citations indexed

About

A. Mott is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, A. Mott has authored 7 papers receiving a total of 161 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Nuclear and High Energy Physics, 2 papers in Artificial Intelligence and 1 paper in Cognitive Neuroscience. Recurrent topics in A. Mott's work include High-Energy Particle Collisions Research (4 papers), Particle physics theoretical and experimental studies (4 papers) and Computational Physics and Python Applications (2 papers). A. Mott is often cited by papers focused on High-Energy Particle Collisions Research (4 papers), Particle physics theoretical and experimental studies (4 papers) and Computational Physics and Python Applications (2 papers). A. Mott collaborates with scholars based in United States and United Kingdom. A. Mott's co-authors include M. Spiropulu, Daniel A. Lidar, Jean-Roch Vlimant, Joshua Job, Alexander Zlokapa, M. Paulini, C. Rogan, R. Wilkinson, R. Y. Zhu and Adolf Bornheim and has published in prestigious journals such as Nature, Journal of High Energy Physics and Physical review. A.

In The Last Decade

A. Mott

6 papers receiving 153 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
A. Mott United States	4	123	34	32	20	16	7	161
Rui-Hao Li United States	4	109 0.9×	72 2.1×	29 0.9×	29 1.4×	24 1.5×	5	204
Panagiotis Spentzouris United States	3	54 0.4×	16 0.5×	27 0.8×	8 0.4×	6 0.4×	10	82
Elizabeth Crosson United States	6	154 1.3×	101 3.0×	8 0.3×	23 1.1×	7 0.4×	8	179
Antonio Anna Mele Germany	6	176 1.4×	105 3.1×	6 0.2×	26 1.3×	10 0.6×	10	213
Aniruddha Bapat United States	6	237 1.9×	132 3.9×	8 0.3×	64 3.2×	11 0.7×	11	275
Leo Zhou United States	6	208 1.7×	81 2.4×	6 0.2×	70 3.5×	29 1.8×	9	235
Stavros Efthymiou Switzerland	7	145 1.2×	137 4.0×	5 0.2×	20 1.0×	11 0.7×	9	218
Ian Hincks Canada	6	142 1.2×	109 3.2×	6 0.2×	12 0.6×	27 1.7×	7	185
Dan Gresh United States	5	252 2.0×	163 4.8×	5 0.2×	52 2.6×	45 2.8×	11	302
Javier Orduz United States	7	51 0.4×	12 0.4×	39 1.2×	9 0.5×	10 0.6×	15	102

Countries citing papers authored by A. Mott

Since Specialization

Citations

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

Fields of papers citing papers by A. Mott

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Mott

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

All Works

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7 of 7 papers shown

1.

Zlokapa, Alexander, A. Mott, Joshua Job, et al.. (2020). Quantum adiabatic machine learning by zooming into a region of the energy surface. Physical review. A. 102(6). 17 indexed citations

2.

Mott, A., Daniel Zoran, Mike Chrzanowski, Daan Wierstra, & Danilo Jimenez Rezende. (2018). S3TA: A Soft, Spatial, Sequential, Top-Down Attention Model. 1 indexed citations

3.

Mott, A., Joshua Job, Jean-Roch Vlimant, Daniel A. Lidar, & M. Spiropulu. (2017). Solving a Higgs optimization problem with quantum annealing for machine learning. Nature. 550(7676). 375–379. 133 indexed citations

4.

Khachatryan, V., D. Anderson, A. Apresyan, et al.. (2016). Measurement of transverse momentum relative to dijet systems in PbPb and pp collisions at s(NN)=2.76 TeV. Repository KITopen (Karlsruhe Institute of Technology). 2 indexed citations

5.

Tu, Y., A. Apresyan, J. M. Lawhorn, et al.. (2012). Centrality dependence of dihadron correlations and azimuthal anisotropy harmonics in PbPb collisions at âSNN = 2.76 Tev. eScholarship (California Digital Library). 3 indexed citations

6.

Apresyan, A., J. Bunn, J. Duarte, et al.. (2012). J/ψ and ψ(2S) production in pp collisions at √s=7Tev. Journal of High Energy Physics. 2012(11). 11. 2 indexed citations

7.

Chatrchyan, S., M. Dubinin, M. Spiropulu, et al.. (2011). Search for Supersymmetry in pp Collisions at √s = 7 Te V in Events with Two Photons and Missing Transverse Energy. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 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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