Preeti Parashar

1.0k citations
36 papers · 703 indexed · h-index 14
Topics
Quantum Information and Cryptography (23 papers)Quantum Mechanics and Applications (18 papers)Algebraic structures and combinatorial models (13 papers)
Partner nations
IndiaItalySpain

In The Last Decade

Preeti Parashar

35 papers receiving 676 citations

Peers

Preeti Parashar
Comparison fields: 5 of 37
  • Artificial Intelligence 606
  • Atomic and Molecular Physics, and Optics 588
  • Statistical and Nonlinear Physics 131
  • Geometry and Topology 57
  • Algebra and Number Theory 54
Replace M. El Baz with:
M. El Baz Morocco
Carlos Palazuelos Spain
Michał Studziński Poland
Lech Jakóbczyk Poland
Paolo Aniello Italy
Marek Mozrzymas Poland
Donald Bures
Juha-Pekka Pellonpää Finland
Gen Kimura Japan
Todd Tilma Japan
Preeti Parashar relative to M. El Baz Morocco M. El Baz's profile →
Citations per field
00.5×3.6×
M. El Baz · 1×
Citations per year

Countries citing papers authored by Preeti Parashar

Since Specialization
Citations

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

Fields of papers citing papers by Preeti Parashar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Preeti Parashar

This figure shows the co-authorship network connecting the top 25 collaborators of Preeti Parashar. A scholar is included among the top collaborators of Preeti Parashar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Preeti Parashar. Preeti Parashar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 13
2 4
3 11
4 1
5 33
6 6
7 1
8 17
9 25
10 26
11 1
12 7
13 2
14
Two-photon algebra deformations
1
15 2
16 7
17 1
18 1
19 1
20 16

About Preeti Parashar

Preeti Parashar is a scholar working on Algebra and Number Theory, Geometry and Topology and Statistical and Nonlinear Physics, having authored 36 papers that have together received 703 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (23 papers), Quantum Mechanics and Applications (18 papers) and Algebraic structures and combinatorial models (13 papers). The work is most often cited by research in Artificial Intelligence (606 citations), Atomic and Molecular Physics, and Optics (588 citations) and Algebra and Number Theory (54 citations). Preeti Parashar has collaborated with scholars based in India, Italy and Spain. Frequent co-authors include Swapan Rana, Maciej Lewenstein, Pankaj Agrawal, Arun Kumar Pati, V. K. Dobrev, Ludwik Dąbrowski, Shao-Ming Fei, Sergio Albeverio, Andreas Winter and Wen‐Li Yang. Their work appears in journals such as Physical Review A, Journal of Mathematical Physics and The European Physical Journal C.

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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