Lode Pollet

6.6k total citations · 1 hit paper
128 papers, 4.3k citations indexed

About

Lode Pollet is a scholar working on Atomic and Molecular Physics, and Optics, Condensed Matter Physics and Geophysics. According to data from OpenAlex, Lode Pollet has authored 128 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 116 papers in Atomic and Molecular Physics, and Optics, 80 papers in Condensed Matter Physics and 8 papers in Geophysics. Recurrent topics in Lode Pollet's work include Cold Atom Physics and Bose-Einstein Condensates (77 papers), Physics of Superconductivity and Magnetism (66 papers) and Quantum, superfluid, helium dynamics (62 papers). Lode Pollet is often cited by papers focused on Cold Atom Physics and Bose-Einstein Condensates (77 papers), Physics of Superconductivity and Magnetism (66 papers) and Quantum, superfluid, helium dynamics (62 papers). Lode Pollet collaborates with scholars based in Germany, United States and Switzerland. Lode Pollet's co-authors include Matthias Troyer, Nikolay Prokof’ev, Boris Svistunov, Massimo Boninsegni, Anatoly Kuklov, Kris Van Houcke, Simon Fölling, Jonathon Gillen, Waseem Bakr and Ruichao Ma and has published in prestigious journals such as Nature, Science and Physical Review Letters.

In The Last Decade

Lode Pollet

122 papers receiving 4.2k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Probing the Superfluid–to–Mott Insulator Transition at the Single-Atom Level

2010 558 citations Lode Pollet et al. Science profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Lode Pollet	4.0k	1.9k	383	262	240	128	4.3k
V. Tognetti	1.8k 0.5×	1.2k 0.6×	347 0.9×	125 0.5×	506 2.1×	154	2.6k
Tin-Lun Ho	6.9k 1.7×	2.0k 1.1×	464 1.2×	50 0.2×	648 2.7×	77	7.3k
Philippe Corboz	2.8k 0.7×	2.6k 1.3×	323 0.8×	92 0.4×	276 1.1×	70	3.5k
Yu. M. Bunkov	2.4k 0.6×	1.2k 0.6×	86 0.2×	153 0.6×	146 0.6×	186	2.7k
V. J. Goldman	3.5k 0.9×	1.2k 0.6×	374 1.0×	72 0.3×	83 0.3×	79	3.7k
Christopher Ticknor	2.8k 0.7×	538 0.3×	121 0.3×	236 0.9×	117 0.5×	87	3.0k
Martin W. Zwierlein	10.0k 2.5×	3.4k 1.8×	536 1.4×	39 0.1×	336 1.4×	88	10.3k
Federico Becca	2.9k 0.7×	4.0k 2.1×	262 0.7×	90 0.3×	176 0.7×	128	4.9k
V. L. Pokrovsky	2.1k 0.5×	2.2k 1.2×	120 0.3×	62 0.2×	320 1.3×	118	3.2k
G. E. Astrakharchik	3.6k 0.9×	865 0.5×	190 0.5×	38 0.1×	489 2.0×	106	3.8k

Countries citing papers authored by Lode Pollet

Since Specialization

Citations

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

Fields of papers citing papers by Lode Pollet

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lode Pollet

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

All Works

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20 of 20 papers shown

Capponi, Sylvain, et al.. (2025). Coupling quantum spin ice to matter on the centered pyrochlore lattice. Physical review. B.. 112(14).

Pollet, Lode, et al.. (2025). Neural quantum state study of fracton models. SciPost Physics. 18(3).

Homeier, Lukas, et al.. (2025). Supersolidity in Rydberg tweezer arrays. Physical review. A. 111(1). 1 indexed citations

Sbierski, Björn, et al.. (2024). Magnetism in the two-dimensional dipolar XY model. Physical review. B.. 109(14). 15 indexed citations

Block, Maxwell, Bingtian Ye, Zilin Wang, et al.. (2024). Scalable spin squeezing from finite-temperature easy-plane magnetism. Nature Physics. 20(10). 1575–1581. 17 indexed citations

Kuklov, Anatoly, Lode Pollet, Nikolay Prokof’ev, & Boris Svistunov. (2024). Transverse Quantum Superfluids. Annual Review of Condensed Matter Physics. 16(1). 209–228. 1 indexed citations

Pollet, Lode, et al.. (2024). Exotic symmetry breaking properties of self-dual fracton spin models. Physical Review Research. 6(1). 1 indexed citations

Jaubert, Ludovic D. C., et al.. (2023). The classical Heisenberg model on the centred pyrochlore lattice. SciPost Physics. 15(2). 3 indexed citations

Grusdt, Fabian, et al.. (2023). Phase diagram of mixed-dimensional anisotropic t−J models. Physical review. B.. 107(7). 1 indexed citations

10.

Pollet, Lode, et al.. (2023). Hybrid symmetry breaking in classical spin models with subsystem symmetries. Physical review. B.. 107(5). 1 indexed citations

11.

Bohrdt, Annabelle, et al.. (2023). Robust stripes in the mixed-dimensional t−J model. Physical Review Research. 5(2). 8 indexed citations

12.

Giudici, Giuliano, et al.. (2023). Unsupervised interpretable learning of phases from many-qubit systems. Physical Review Research. 5(1). 6 indexed citations

13.

Pollet, Lode & Fabian Grusdt. (2021). Z 2 parton phases in the mixed-dimensional t-J z model. Bulletin of the American Physical Society. 1 indexed citations

14.

Vanhala, Tuomas I. & Lode Pollet. (2020). Constrained random phase approximation of the effective Coulomb interaction in lattice models of twisted bilayer graphene. Physical review. B.. 102(3). 12 indexed citations

15.

Strand, Hugo U. R., et al.. (2017). The anisotropic Harper-Hofstadter-Mott model: supersolid, striped superfluid, and symmetry protected topological groundstates. Bulletin of the American Physical Society. 2017. 1 indexed citations

16.

Gukelberger, Jan, Lei Wang, & Lode Pollet. (2017). Ising antiferromagnet in the two-dimensional Hubbard model with mismatched Fermi surfaces. Physical review. B.. 95(20). 3 indexed citations

17.

Pollet, Lode. (2013). A review of Monte Carlo simulations for the Bose–Hubbard model with diagonal disorder. Comptes Rendus Physique. 14(8). 712–724. 19 indexed citations

18.

Boninsegni, Massimo, Lode Pollet, Nikolay Prokof’ev, & Boris Svistunov. (2012). Role of Bose Statistics in Crystallization and Quantum Jamming. Physical Review Letters. 109(2). 25302–25302. 29 indexed citations

19.

Endres, Manuel, Marc Cheneau, Takeshi Fukuhara, et al.. (2011). Observation of Correlated Particle-Hole Pairs and String Order in Low-Dimensional Mott Insulators. Science. 334(6053). 200–203. 199 indexed citations

20.

Pollet, Lode, et al.. (2007). Superfluidity of Grain Boundaries in Solid $^4$He. Bulletin of the American Physical Society. 1 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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