Rahul Maitra

433 total citations
32 papers, 332 citations indexed

About

Rahul Maitra is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Rahul Maitra has authored 32 papers receiving a total of 332 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Atomic and Molecular Physics, and Optics, 16 papers in Artificial Intelligence and 5 papers in Computational Theory and Mathematics. Recurrent topics in Rahul Maitra's work include Quantum Computing Algorithms and Architecture (16 papers), Spectroscopy and Quantum Chemical Studies (13 papers) and Advanced Chemical Physics Studies (13 papers). Rahul Maitra is often cited by papers focused on Quantum Computing Algorithms and Architecture (16 papers), Spectroscopy and Quantum Chemical Studies (13 papers) and Advanced Chemical Physics Studies (13 papers). Rahul Maitra collaborates with scholars based in India, United States and Japan. Rahul Maitra's co-authors include Debashis Mukherjee, Dipayan Datta, Sauvik Chatterjee, G. Naaresh Reddy, Takahito Nakajima, Anindya Ghosh, Sudip Bhattacharjee, Ashot V. Arzumanyan, Biswajit Chowdhury and S. E. Lyubimov and has published in prestigious journals such as The Journal of Chemical Physics, Green Chemistry and The Journal of Physical Chemistry A.

In The Last Decade

Rahul Maitra

30 papers receiving 331 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Rahul Maitra India 11 215 122 70 44 35 32 332
Riddhish Pandharkar United States 11 160 0.7× 44 0.4× 134 1.9× 12 0.3× 33 0.9× 16 333
Romit Chakraborty United States 10 137 0.6× 36 0.3× 143 2.0× 18 0.4× 25 0.7× 14 327
Wei‐Ning Zhang China 16 123 0.6× 51 0.4× 245 3.5× 22 0.5× 31 0.9× 82 717
Guillaume Hoffmann France 9 38 0.2× 62 0.5× 50 0.7× 10 0.2× 15 0.4× 24 204
Patrick Maurer Austria 13 539 2.5× 323 2.6× 29 0.4× 5 0.1× 29 0.8× 26 665
Andrew V. Zeigarnik Russia 14 106 0.5× 16 0.1× 261 3.7× 16 0.4× 10 0.3× 32 505
Julian Yarkony United States 5 186 0.9× 34 0.3× 87 1.2× 3 0.1× 42 1.2× 7 280
Scott E. Smart United States 15 421 2.0× 404 3.3× 91 1.3× 3 0.1× 16 0.5× 35 616
Marian Dryzhakov France 8 493 2.3× 53 0.4× 37 0.5× 6 0.1× 13 0.4× 9 880
Eliseo Marin‐Rimoldi United States 7 49 0.2× 10 0.1× 102 1.5× 6 0.1× 15 0.4× 15 276

Countries citing papers authored by Rahul Maitra

Since Specialization
Citations

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

Fields of papers citing papers by Rahul Maitra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rahul Maitra

This figure shows the co-authorship network connecting the top 25 collaborators of Rahul Maitra. A scholar is included among the top collaborators of Rahul Maitra 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 Rahul Maitra. Rahul Maitra 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
1.
Maitra, Rahul, et al.. (2025). Determination of Molecular Symmetry Adapted Eigenroots in the Variational Quantum Eigensolver Framework. International Journal of Quantum Chemistry. 125(7). 1 indexed citations
2.
Anand, Kartik, et al.. (2025). Construction of Chemistry-Inspired Dynamic Ansatz Utilizing Generative Machine Learning. The Journal of Physical Chemistry A. 129(26). 5889–5900.
3.
Maitra, Rahul, et al.. (2025). Many-body approach to projective solution of generalized operators: Formulation and application to quantum computing. The Journal of Chemical Physics. 162(16). 3 indexed citations
4.
Maitra, Rahul, et al.. (2025). Efficient quantum state preparation through seniority driven operator selection. The Journal of Chemical Physics. 163(15).
5.
Maitra, Rahul, et al.. (2024). Machine learning assisted construction of a shallow depth dynamic ansatz for noisy quantum hardware. Chemical Science. 15(9). 3279–3289. 10 indexed citations
6.
Maitra, Rahul, et al.. (2024). Noise-independent route toward the genesis of a COMPACT ansatz for molecular energetics: A dynamic approach. The Journal of Chemical Physics. 160(12). 10 indexed citations
7.
Maitra, Rahul, et al.. (2024). Toward a resource-optimized dynamic quantum algorithm via non-iterative auxiliary subspace corrections. The Journal of Chemical Physics. 161(14). 4 indexed citations
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Maitra, Rahul, et al.. (2023). Machine learning aided dimensionality reduction toward a resource efficient projective quantum eigensolver: Formal development and pilot applications. The Journal of Chemical Physics. 158(24). 244101–244101. 9 indexed citations
11.
Maitra, Rahul, et al.. (2023). Development of a compactAnsatzvia operator commutativity screening: Digital quantum simulation of molecular systems. The Journal of Chemical Physics. 159(1). 15 indexed citations
12.
Maitra, Rahul, et al.. (2022). Iterative quantum phase estimation with variationally prepared reference state. International Journal of Quantum Chemistry. 123(3). 11 indexed citations
13.
Maitra, Rahul, et al.. (2022). A Synergistic Approach towards Optimization of Coupled Cluster Amplitudes by Exploiting Dynamical Hierarchy. ChemPhysChem. 24(4). e202200633–e202200633. 7 indexed citations
14.
Maitra, Rahul, et al.. (2020). Formulation of a Dressed Coupled-Cluster Method with Implicit Triple Excitations and Benchmark Application to Hydrogen-Bonded Systems. Journal of Chemical Theory and Computation. 16(10). 6317–6328. 8 indexed citations
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Maitra, Rahul, Yoshinobu Akinaga, & Takahito Nakajima. (2017). A coupled cluster theory with iterative inclusion of triple excitations and associated equation of motion formulation for excitation energy and ionization potential. The Journal of Chemical Physics. 147(7). 74103–74103. 12 indexed citations
17.
Maitra, Rahul, et al.. (2012). Unitary group adapted state-specific multi-reference coupled cluster theory: Formulation and pilot numerical applications. The Journal of Chemical Physics. 137(2). 24105–24105. 37 indexed citations
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Das, Sanghamitra, Dipayan Datta, Rahul Maitra, & Debashis Mukherjee. (2008). Development and pilot molecular applications of the uncoupled state-specific MRCC (UC-SS-MRCC) theory. Chemical Physics. 349(1-3). 115–120. 19 indexed citations
20.
Maitra, Rahul, Dipayan Datta, & Debashis Mukherjee. (2008). Use of a convenient size-extensive normalization in multi-reference coupled cluster (MRCC) theory with incomplete model space: A novel valence universal MRCC formulation. Chemical Physics. 356(1-3). 54–63. 6 indexed citations

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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