Ryan LaRose

1.4k citations
16 papers · 739 · h-index 10

Impact in

Papers in

Ryan LaRose

14 papers receiving 730 citations

Peers

Ryan LaRose
Comparison fields: 5 of 48
  • Artificial Intelligence 677
  • Computational Theory and Mathematics 147
  • Atomic and Molecular Physics, and Optics 246
  • Computational Mathematics 2
  • Hardware and Architecture 19
Replace Christa Zoufal with:
Christa Zoufal Switzerland
Johannes Jakob Meyer Germany
Sumner Alperin-Lea Canada
Nicholas Chancellor United Kingdom
Abhinav Anand Canada
Sukin Sim United States
Hermanni Heimonen Singapore
Marcello Benedetti United Kingdom
Hongxiang Chen China
Joshua Job United States
Ryan LaRose relative to Christa Zoufal Switzerland Christa Zoufal's profile →
Citations per field
00.5×10×
Christa Zoufal · 1×
Citations per year

Countries citing papers authored by Ryan LaRose

Since Specialization
Citations

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

Fields of papers citing papers by Ryan LaRose

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ryan LaRose, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ryan LaRose Line = papers co-authored together Ryan LaRose links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2019226
2 2020202
3 2019123
4 202390
5 202224
6
Variational Quantum Linear Solver: A Hybrid Algorithm for Linear Systems
201916
7 202215
8 202312
9 20249
10 20229
11 20185
12 20243
13 20223
14 20222
15
Jurisdiction over American Private Military Contractors: The Illusion of a Loophole in the Law and the Reality of No Oversight
20120
16 20250

About Ryan LaRose

Ryan LaRose is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Information Systems, Computer Networks and Communications and Political Science and International Relations, having authored 16 papers that have together received 739 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (13 papers), Quantum Information and Cryptography (10 papers), Neural Networks and Reservoir Computing (3 papers), Cloud Computing and Resource Management (2 papers), Quantum many-body systems (2 papers), Quantum and electron transport phenomena (2 papers), Military and Defense Studies (1 paper) and Image and Signal Denoising Methods (1 paper). The work is most often cited by research in Artificial Intelligence (677 citations), Computational Theory and Mathematics (147 citations), Atomic and Molecular Physics, and Optics (246 citations), Computational Mathematics (2 citations) and Hardware and Architecture (19 citations). Ryan LaRose has collaborated with scholars based in United States, Spain and United Kingdom. Frequent co-authors include Brian Coyle, Łukasz Cincio, Patrick J. Coles, Alexander Poremba, Sumeet Khatri, Andrew Sornborger, Carlos Bravo-Prieto, M. Cerezo, Yiğit Subaşı and William J. Zeng. Their work appears in journals such as Physical review. A, Quantum, Quantum Machine Intelligence, npj Quantum Information and IEEE Transactions on Quantum Engineering.

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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