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.
An increased estimate of the merger rate of double neutron stars from observations of a highly relativistic system
2003482 citationsM. Burgay, N. D’Amico et al.Natureprofile →
Compact Object Modeling with the StarTrack Population Synthesis Code
2007468 citationsKrzysztof Belczyński, V. Kalogera et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of V. Kalogera'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 V. Kalogera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites V. Kalogera more than expected).
This network shows the impact of papers produced by V. Kalogera. 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 V. Kalogera. The network helps show where V. Kalogera may publish in the future.
Co-authorship network of co-authors of V. Kalogera
This figure shows the co-authorship network connecting the top 25 collaborators of V. Kalogera.
A scholar is included among the top collaborators of V. Kalogera 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 V. Kalogera. V. Kalogera is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Valsecchi, Francesca, E. Glebbeek, Will M. Farr, et al.. (2011). An Evolutionary Model for the Massive Black Hole X-Ray Binary M33 X-7.. ASPC. 447. 271.
O’Shaughnessy, R., et al.. (2006). Constraining population synthesis models via observations of compact-object binaries and supernovae. arXiv (Cornell University).2 indexed citations
17.
Sepinsky, J. F., B. Willems, & V. Kalogera. (2006). Interacting Binaries with Eccentric Orbits. AAS. 209.3 indexed citations
18.
Kalogera, V. & Krzysztof Belczyński. (2004). Mapping inspiral rates on population synthesis parameters.5 indexed citations
19.
Burgay, M., N. D’Amico, Andrea Possenti, et al.. (2003). An increased estimate of the merger rate of double neutron stars from observations of a highly relativistic system. Nature. 426(6966). 531–533.482 indexed citations breakdown →
20.
Grandclément, Philippe, V. Kalogera, & A. Vecchio. (2002). Searching for Gravitational Waves from the Inspiral of Precessing Binary Systems. I. Reduction of Detection Efficiency. arXiv (Cornell University).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.