Daniel Tasca

1.6k citations
31 papers · 1.1k · h-index 18

Impact in

Papers in

Daniel Tasca

31 papers receiving 1.1k citations

Peers

Daniel Tasca
Comparison fields: 5 of 46
  • Acoustics and Ultrasonics 401
  • Instrumentation 104
  • Atomic and Molecular Physics, and Optics 795
  • Biophysics 110
  • Artificial Intelligence 532
Replace Gabriela Barreto Lemos with:
Gabriela Barreto Lemos Brazil
Gregory A. Howland United States
Paul‐Antoine Moreau United Kingdom
Kam Wai Clifford Chan United States
Sebastião Pádua Brazil
Ermes Toninelli United Kingdom
Ivano Ruo Berchera Italy
Reuben S. Aspden United Kingdom
Hugo Defienne United Kingdom
Alessia Allevi Italy
Daniel Tasca relative to Gabriela Barreto Lemos Brazil Gabriela Barreto Lemos's profile →
Citations per field
00.5×2×2.5×
Gabriela Barreto Lemos · 1×
Citations per year

Countries citing papers authored by Daniel Tasca

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Tasca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012193
2 2015138
3 2013123
4 201161
5 201754
6 200949
7 201838
8 201338
9 201334
10 202134
11 200933
12 200832
13 202032
14 202031
15 201828
16 200824
17 201422
18 201521
19 201317
20 201616

About Daniel Tasca

Daniel Tasca is a scholar working on Atomic and Molecular Physics, and Optics, Acoustics and Ultrasonics, Artificial Intelligence, Statistical and Nonlinear Physics and Instrumentation, having authored 31 papers that have together received 1.1k indexed citations. Recurring topics across this work include Quantum Information and Cryptography (15 papers), Orbital Angular Momentum in Optics (15 papers), Quantum Mechanics and Applications (12 papers), Random lasers and scattering media (8 papers), Laser-Matter Interactions and Applications (4 papers), Mechanical and Optical Resonators (3 papers), Spectroscopy and Quantum Chemical Studies (3 papers) and Quantum Computing Algorithms and Architecture (3 papers). The work is most often cited by research in Acoustics and Ultrasonics (401 citations), Instrumentation (104 citations), Atomic and Molecular Physics, and Optics (795 citations), Biophysics (110 citations) and Artificial Intelligence (532 citations). Daniel Tasca has collaborated with scholars based in Brazil, United Kingdom and Poland. Frequent co-authors include Miles J. Padgett, Robert W. Boyd, Stephen Patrick Walborn, Reuben S. Aspden, P. H. Souto Ribeiro, Fabricio Toscano, Antonio Zelaquett Khoury, Gerald S. Buller, K. Dechoum and Wagner Tavares Buono. Their work appears in journals such as Physical Review A, Physical Review Letters, Physical Review Research, New Journal of Physics and Optics Express.

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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