Jack Y. Araz

422 total citations
18 papers, 144 citations indexed

About

Jack Y. Araz is a scholar working on Nuclear and High Energy Physics, Atomic and Molecular Physics, and Optics and Artificial Intelligence. According to data from OpenAlex, Jack Y. Araz has authored 18 papers receiving a total of 144 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Nuclear and High Energy Physics, 6 papers in Atomic and Molecular Physics, and Optics and 6 papers in Artificial Intelligence. Recurrent topics in Jack Y. Araz's work include Particle physics theoretical and experimental studies (13 papers), High-Energy Particle Collisions Research (5 papers) and Quantum many-body systems (5 papers). Jack Y. Araz is often cited by papers focused on Particle physics theoretical and experimental studies (13 papers), High-Energy Particle Collisions Research (5 papers) and Quantum many-body systems (5 papers). Jack Y. Araz collaborates with scholars based in United Kingdom, France and Canada. Jack Y. Araz's co-authors include Michael Spannowsky, Benjamin Fuks, Mariana Frank, Shankha Banerjee, Michael Spannowsky, Andreas Goudelis, S. Schenk, A. G. Buckley, Sabine Kraml and Matthew Wingate and has published in prestigious journals such as Physics Letters B, Journal of Magnetism and Magnetic Materials and Physical review. D.

In The Last Decade

Jack Y. Araz

18 papers receiving 142 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jack Y. Araz United Kingdom	8	104	57	26	22	6	18	144
Luiz Vale Silva Spain	9	262 2.5×	27 0.5×	18 0.7×	27 1.2×	6 1.0×	24	284
T. J. Khoo United States	5	165 1.6×	28 0.5×	11 0.4×	44 2.0×	6 1.0×	12	189
Cyrille Marquet Switzerland	3	64 0.6×	43 0.8×	57 2.2×	6 0.3×	8 1.3×	6	128
P. H. Beauchemin United States	3	46 0.4×	37 0.6×	39 1.5×	6 0.3×	3 0.5×	4	100
Tim Engel Switzerland	8	152 1.5×	18 0.3×	16 0.6×	10 0.5×	3 0.5×	13	172
J. Jesús Aguilera-Verdugo Mexico	3	63 0.6×	15 0.3×	16 0.6×	15 0.7×	18 3.0×	3	88
Malin Sjödahl Sweden	10	251 2.4×	20 0.4×	10 0.4×	13 0.6×	2 0.3×	22	261
K. Terashi Japan	6	78 0.8×	27 0.5×	14 0.5×	19 0.9×	1 0.2×	15	106
E. L. Barberio Australia	6	269 2.6×	16 0.3×	10 0.4×	31 1.4×	4 0.7×	10	280
Rui-Xiang Shi China	8	315 3.0×	30 0.5×	9 0.3×	27 1.2×	3 0.5×	12	320

Countries citing papers authored by Jack Y. Araz

Since Specialization

Citations

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

Fields of papers citing papers by Jack Y. Araz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jack Y. Araz. 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 Jack Y. Araz. The network helps show where Jack Y. Araz may publish in the future.

Co-authorship network of co-authors of Jack Y. Araz

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

All Works

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18 of 18 papers shown

Araz, Jack Y., et al.. (2025). Point cloud-based diffusion models for the Electron-Ion Collider. Physics Letters B. 868. 139694–139694. 2 indexed citations

Araz, Jack Y.. (2024). Spey: Smooth inference for reinterpretation studies. SciPost Physics. 16(1). 5 indexed citations

Araz, Jack Y., Michael Spannowsky, & Matthew Wingate. (2024). Exploring thermal equilibria of the Fermi-Hubbard model with variational quantum algorithms. Physical review. A. 109(6). 2 indexed citations

Araz, Jack Y., A. G. Buckley, Gregor Kasieczka, et al.. (2024). Les Houches guide to reusable ML models in LHC analyses. City Research Online (City University London). 2 indexed citations

Araz, Jack Y., et al.. (2023). Signal region combination with full and simplified likelihoods in MadAnalysis 5. SciPost Physics. 14(1). 5 indexed citations

Araz, Jack Y., A. G. Buckley, & Benjamin Fuks. (2023). Searches for new physics with boosted top quarks in the MadAnalysis 5 and Rivet frameworks. The European Physical Journal C. 83(7). 6 indexed citations

Araz, Jack Y., S. Schenk, & Michael Spannowsky. (2023). Toward a quantum simulation of nonlinear sigma models with a topological term. Physical review. A. 107(3). 7 indexed citations

Araz, Jack Y., A. G. Buckley, Benjamin Fuks, et al.. (2023). Strength in numbers: Optimal and scalable combination of LHC new-physics searches. SciPost Physics. 14(4). 2 indexed citations

Araz, Jack Y. & Michael Spannowsky. (2023). Quantum-probabilistic Hamiltonian learning for generative modeling and anomaly detection. Physical review. A. 108(6). 11 indexed citations

10.

Araz, Jack Y., Juan Carlos Criado, & Michael Spannowsky. (2022). Identifying magnetic antiskyrmions while they form with convolutional neural networks. Journal of Magnetism and Magnetic Materials. 563. 169806–169806. 4 indexed citations

11.

Araz, Jack Y. & Michael Spannowsky. (2022). Classical versus quantum: Comparing tensor-network-based quantum circuits on Large Hadron Collider data. Physical review. A. 106(6). 23 indexed citations

12.

Araz, Jack Y. & Michael Spannowsky. (2021). Quantum-inspired event reconstruction with Tensor Networks: Matrix Product States. Durham Research Online (Durham University). 10 indexed citations

13.

Araz, Jack Y., et al.. (2021). Precision SMEFT bounds from the VBF Higgs at high transverse momentum. Durham Research Online (Durham University). 16 indexed citations

14.

Araz, Jack Y., Mariana Frank, & Benjamin Fuks. (2020). Reinterpreting the results of the LHC with MadAnalysis 5: uncertainties and higher-luminosity estimates. The European Physical Journal C. 80(6). 531–531. 28 indexed citations

15.

Araz, Jack Y. & Benjamin Fuks. (2020). Implementation of the ATLAS-SUSY-2018-32 analysis (sleptons and electroweakinos with two leptons and missing transverse energy; 139 fb−¹). Modern Physics Letters A. 36(1). 2141005–2141005. 3 indexed citations

16.

Araz, Jack Y. & Benjamin Fuks. (2020). Implementation of the ATLAS-SUSY-2018-31 analysis in the MadAnalysis 5 framework (sbottoms with multi-bottoms and missing transverse energy; 139 fb−¹). Modern Physics Letters A. 36(1). 2141010–2141010. 2 indexed citations

17.

Araz, Jack Y., Shankha Banerjee, Mariana Frank, Benjamin Fuks, & Andreas Goudelis. (2018). Dark matter and collider signals in an MSSM extension with vector-like multiplets. Physical review. D. 98(11). 8 indexed citations

18.

Araz, Jack Y., Mariana Frank, & Benjamin Fuks. (2017). DifferentiatingU(1)′supersymmetric models with right sneutrino and neutralino dark matter. Physical review. D. 96(1). 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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