Michele Dolfi

737 total citations
14 papers, 368 citations indexed

About

Michele Dolfi is a scholar working on Atomic and Molecular Physics, and Optics, Condensed Matter Physics and Artificial Intelligence. According to data from OpenAlex, Michele Dolfi has authored 14 papers receiving a total of 368 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Atomic and Molecular Physics, and Optics, 7 papers in Condensed Matter Physics and 2 papers in Artificial Intelligence. Recurrent topics in Michele Dolfi's work include Physics of Superconductivity and Magnetism (6 papers), Quantum many-body systems (5 papers) and Cold Atom Physics and Bose-Einstein Condensates (3 papers). Michele Dolfi is often cited by papers focused on Physics of Superconductivity and Magnetism (6 papers), Quantum many-body systems (5 papers) and Cold Atom Physics and Bose-Einstein Condensates (3 papers). Michele Dolfi collaborates with scholars based in Switzerland, United States and Sweden. Michele Dolfi's co-authors include Matthias Troyer, Sebastian Keller, Markus Reiher, Bela Bauer, Adrian Kantian, Thierry Giamarchi, Peter Staar, Timothée Ewart, Birgit Pfitzmann and Zoran Ristivojević and has published in prestigious journals such as Physical Review Letters, Nature Communications and The Journal of Chemical Physics.

In The Last Decade

Michele Dolfi

14 papers receiving 362 citations

Peers

Michele Dolfi
Natalia Chepiga Netherlands
Simon D. Smart United Kingdom
Ushnish Ray United States
Philipp T. Dumitrescu United States
Hugh G. A. Burton United Kingdom
B. Kloss United States
Brian Austin United States
Michele Dolfi
Citations per year, relative to Michele Dolfi Michele Dolfi (= 1×) peers Emanuel H. Rubensson

Countries citing papers authored by Michele Dolfi

Since Specialization
Citations

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

Fields of papers citing papers by Michele Dolfi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michele Dolfi

This figure shows the co-authorship network connecting the top 25 collaborators of Michele Dolfi. A scholar is included among the top collaborators of Michele Dolfi 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 Michele Dolfi. Michele Dolfi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Mishra, Lokesh, et al.. (2024). Statements: Universal Information Extraction from Tables with Large Language Models for ESG KPIs. 193–214. 2 indexed citations
2.
Mishra, Lokesh, et al.. (2024). ESG Accountability Made Easy: DocQA at Your Service. Proceedings of the AAAI Conference on Artificial Intelligence. 38(21). 23814–23816. 2 indexed citations
3.
Pfitzmann, Birgit, et al.. (2022). DocLayNet: A Large Human-Annotated Dataset for Document-Layout Segmentation. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 3743–3751. 33 indexed citations
4.
Caborni, Chiara, et al.. (2021). Using Knowledge Graphs to Navigate Through Geological Concepts Extracted from Documents. 2 indexed citations
5.
Staar, Peter, et al.. (2020). Corpus processing service: A Knowledge Graph platform to perform deep data exploration on corpora. SHILAP Revista de lepidopterología. 1(2). 7 indexed citations
6.
Kantian, Adrian, Michele Dolfi, Matthias Troyer, & Thierry Giamarchi. (2019). Understanding repulsively mediated superconductivity of correlated electrons via massively parallel density matrix renormalization group. Physical review. B.. 100(7). 10 indexed citations
7.
Dolfi, Michele, et al.. (2016). Density redistribution effects in fermionic optical lattices. Physical review. A. 94(6). 1 indexed citations
8.
Keller, Sebastian, Michele Dolfi, Matthias Troyer, & Markus Reiher. (2015). An efficient matrix product operator representation of the quantum chemical Hamiltonian. The Journal of Chemical Physics. 143(24). 244118–244118. 132 indexed citations
9.
Dolfi, Michele, Adrian Kantian, Bela Bauer, & Matthias Troyer. (2015). Minimizing nonadiabaticities in optical-lattice loading. Physical Review A. 91(3). 12 indexed citations
10.
Dolfi, Michele, Bela Bauer, Sebastian Keller, & Matthias Troyer. (2015). Pair correlations in doped Hubbard ladders. Physical Review B. 92(19). 51 indexed citations
11.
Shinaoka, Hiroshi, Michele Dolfi, Matthias Troyer, & Philipp Werner. (2014). Hybridization expansion Monte Carlo simulation of multi-orbital quantum impurity problems: matrix product formalism and improved sampling. reroDoc Digital Library. 17 indexed citations
12.
Bauer, Bela, Łukasz Cincio, Michele Dolfi, et al.. (2014). Chiral spin liquid and emergent anyons in a Kagome lattice Mott insulator. Nature Communications. 5(1). 5137–5137. 1 indexed citations
13.
Dolfi, Michele, Bela Bauer, Sebastian Keller, et al.. (2014). Matrix product state applications for the ALPS project. Computer Physics Communications. 185(12). 3430–3440. 69 indexed citations
14.
Dolfi, Michele, Bela Bauer, Matthias Troyer, & Zoran Ristivojević. (2012). Multigrid Algorithms for Tensor Network States. Physical Review Letters. 109(2). 20604–20604. 29 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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