Quantum Machine Intelligence

244 papers and 1.6k indexed citations

About

The 244 papers published in Quantum Machine Intelligence in the last decades have received a total of 1.6k indexed citations. Papers published in Quantum Machine Intelligence usually cover Artificial Intelligence (218 papers), Computational Theory and Mathematics (55 papers) and Atomic and Molecular Physics, and Optics (49 papers) specifically the topics of Quantum Computing Algorithms and Architecture (188 papers), Quantum Information and Cryptography (139 papers) and Neural Networks and Reservoir Computing (41 papers). The most active scholars publishing in Quantum Machine Intelligence are Davide Venturelli, Daniel K. Park, Tak Hur, Masoud Mohseni, Andrea Skolik, Patrick van der Smagt, Jarrod R. McClean, Martin Leib, Christa Zoufal and Haimeng Zhao.

In The Last Decade

Quantum Machine Intelligence

176 papers receiving 1.5k citations

Fields of papers published in Quantum Machine Intelligence

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Quantum Machine Intelligence. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Quantum Machine Intelligence.

Countries where authors publish in Quantum Machine Intelligence

Since Specialization
Citations

This map shows the geographic impact of research published in Quantum Machine Intelligence. 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 papers published in Quantum Machine Intelligence with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quantum Machine Intelligence more than expected).

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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2026