Daniel K. Mark

919 citations
14 papers · 711 · 1 hit paper · h-index 10

Impact in

Papers in

Daniel K. Mark

13 papers receiving 702 citations

Daniel K. Mark's Hit Papers

Preparing random states and benchmarking with many-body quantum chaos 2023 · 123 citations
1230+1+2Years since publication4080120

Peers

Daniel K. Mark
Comparison fields: 5 of 18
  • Atomic and Molecular Physics, and Optics 578
  • Artificial Intelligence 202
  • Statistical and Nonlinear Physics 57
  • Condensed Matter Physics 20
  • Nuclear and High Energy Physics 18
Replace A. R. Klots with:
A. R. Klots United States
A. N. Korotkov United States
W. Liu United States
Kang Xue China
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Zi-Yong Ge China
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Xiang-Fa Zhou China
Daniel K. Mark relative to A. R. Klots United States A. R. Klots's profile →
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Countries citing papers authored by Daniel K. Mark

Since Specialization
Citations

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

Fields of papers citing papers by Daniel K. Mark

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel K. Mark. 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 Daniel K. Mark. The network helps show where Daniel K. Mark may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel K. Mark, 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 Daniel K. Mark Line = papers co-authored together Daniel K. Mark links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2020134
2
Preparing random states and benchmarking with many-body quantum chaos
Hit paper breakdown →
2023123
3 202095
4 202388
5 202383
6 202447
7 202435
8 202334
9 202334
10 202023
11
Emergent Randomness and Benchmarking from Many-Body Quantum Chaos
20217
12 20257
13 20231
14 20250

About Daniel K. Mark

Daniel K. Mark is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence, Statistical and Nonlinear Physics, Electronic, Optical and Magnetic Materials and Nuclear Energy and Engineering, having authored 14 papers that have together received 711 indexed citations. Recurring topics across this work include Quantum many-body systems (12 papers), Quantum Information and Cryptography (4 papers), Quantum Computing Algorithms and Architecture (3 papers), Cold Atom Physics and Bose-Einstein Condensates (2 papers), Quantum chaos and dynamical systems (2 papers), Metamaterials and Metasurfaces Applications (1 paper) and Strong Light-Matter Interactions (1 paper). The work is most often cited by research in Atomic and Molecular Physics, and Optics (578 citations), Artificial Intelligence (202 citations), Statistical and Nonlinear Physics (57 citations), Condensed Matter Physics (20 citations) and Nuclear and High Energy Physics (18 citations). Daniel K. Mark has collaborated with scholars based in United States, Austria and Singapore. Frequent co-authors include Olexei I. Motrunich, Soonwon Choi, Cheng-Ju Lin, Joonhee Choi, Adam L. Shaw, Manuel Endres, Jordan S. Cotler, Hsin-Yuan Huang, Xueyue Zhang and Eun Jong Kim. Their work appears in journals such as Physical review. B., Physical Review X, Physical Review Letters, Nature and PRX Quantum.

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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