Daniel Manzano

907 citations
30 papers · 573 · h-index 13

Impact in

Papers in

Daniel Manzano

29 papers receiving 567 citations

Peers

Daniel Manzano
Comparison fields: 5 of 41
  • Statistical and Nonlinear Physics 249
  • Atomic and Molecular Physics, and Optics 483
  • Artificial Intelligence 272
  • Applied Mathematics 21
  • Condensed Matter Physics 19
Replace Archak Purkayastha with:
Archak Purkayastha India
Anthony Kiely Ireland
Chikako Uchiyama Japan
Ali Asadian Austria
Jian‐Qi Zhang China
Peter Štelmachovič Slovakia
Joe P. Chen United States
Mischa P. Woods Switzerland
A. Napoli Italy
L.-L. Yan China
Daniel Manzano relative to Archak Purkayastha India Archak Purkayastha's profile →
Citations per field
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Archak Purkayastha · 1×
Citations per year

Countries citing papers authored by Daniel Manzano

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Manzano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201376
2 201259
3 200958
4 201050
5 201447
6 201838
7 201337
8 201635
9 200926
10 201624
11 201021
12 200918
13 201412
14 201610
15 200910
16
Mapping of quantum circuits onto NISQ superconducting processors
20199
17 20247
18 20217
19 20135
20 20215

About Daniel Manzano

Daniel Manzano is a scholar working on Atomic and Molecular Physics, and Optics, Statistical and Nonlinear Physics, Artificial Intelligence, Electrical and Electronic Engineering and Molecular Biology, having authored 30 papers that have together received 573 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (12 papers), Advanced Thermodynamics and Statistical Mechanics (11 papers), Quantum and electron transport phenomena (10 papers), Spectroscopy and Quantum Chemical Studies (8 papers), Quantum Computing Algorithms and Architecture (6 papers), Quantum many-body systems (6 papers), Quantum Mechanics and Applications (3 papers) and Quantum Mechanics and Non-Hermitian Physics (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (249 citations), Atomic and Molecular Physics, and Optics (483 citations), Artificial Intelligence (272 citations), Applied Mathematics (21 citations) and Condensed Matter Physics (19 citations). Daniel Manzano has collaborated with scholars based in Spain, Austria and Singapore. Frequent co-authors include J. S. Dehesa, Pablo I. Hurtado, Hans J. Briegel, Markus Tiersch, Ali Asadian, A. Plastino, Jianshu Cao, Juzar Thingna, P. Sánchez‐Moreno and Chern Chuang. Their work appears in journals such as New Journal of Physics, Scientific Reports, Physica A Statistical Mechanics and its Applications, Journal of Computational and Applied Mathematics and PLoS ONE.

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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