Jeffrey D. Scargle
- Astronomy and Astrophysics top 5%
- Nuclear and High Energy Physics top 10%
- Artificial Intelligence top 10%
- Atmospheric Science
- Statistical and Nonlinear Physics top 10%
- Co-authors
- M. J. WayJ. P. NorrisN. GehrelsAshok N. SrivastavaKamal AliAshley T. BarnesL. J. CaroffPeter D. Noerdlinger
- Topics
- Stellar, planetary, and galactic studies (12 papers)Solar and Space Plasma Dynamics (9 papers)Pulsars and Gravitational Waves Research (6 papers)
- Partner nations
- United StatesItalyUnited Kingdom
In The Last Decade
Jeffrey D. Scargle
56 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 124
- Astronomy and Astrophysics 742
- Nuclear and High Energy Physics 247
- Artificial Intelligence 116
- Atmospheric Science 88
- Statistical and Nonlinear Physics 83
Countries citing papers authored by Jeffrey D. Scargle
This map shows the geographic impact of Jeffrey D. Scargle'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 Jeffrey D. Scargle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffrey D. Scargle more than expected).
Fields of papers citing papers by Jeffrey D. Scargle
This network shows the impact of papers produced by Jeffrey D. Scargle. 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 Jeffrey D. Scargle. The network helps show where Jeffrey D. Scargle may publish in the future.
Co-authorship network of co-authors of Jeffrey D. Scargle
This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey D. Scargle. A scholar is included among the top collaborators of Jeffrey D. Scargle 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 Jeffrey D. Scargle. Jeffrey D. Scargle is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 14 | |
| 2 | Time series exploration in Python and MATLAB: Unevenly sampled data, parametric modeling, and periodograms | 0 |
| 3 | Tanagra: Timing Analysis of Grating Data | 1 |
| 4 | 19 | |
| 5 | Joint segmentation of multivariate astronomical time series :
\n bayesian sampling with a hierarchical model | 33 |
| 6 | 2 | |
| 7 | 82 | |
| 8 | 7 | |
| 9 | Discovery of Planetary Systems With SIM | 2 |
| 10 | 2 | |
| 11 | Spatial Autocatalytic Dynamics: An Approach to Modeling Prebiotic Evolution | 1 |
| 12 | Wavelet methods in astronomical time series analysis | 11 |
| 13 | 2 | |
| 14 | 49 | |
| 15 | 238 | |
| 16 | 10 | |
| 17 | 1 | |
| 18 | 23 | |
| 19 | 28 | |
| 20 | 18 |
About Jeffrey D. Scargle
Jeffrey D. Scargle is a scholar working on Astronomy and Astrophysics, Instrumentation and Signal Processing, having authored 60 papers that have together received 1.3k indexed citations. Recurring topics across this work include Stellar, planetary, and galactic studies (12 papers), Solar and Space Plasma Dynamics (9 papers) and Pulsars and Gravitational Waves Research (6 papers). The work is most often cited by research in Astronomy and Astrophysics (742 citations), Nuclear and High Energy Physics (247 citations) and Instrumentation (57 citations). Jeffrey D. Scargle has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include M. J. Way, J. P. Norris, N. Gehrels, Ashok N. Srivastava, Kamal Ali, Ashley T. Barnes, L. J. Caroff, Peter D. Noerdlinger, James N. Imamura and F. Pacini. Their work appears in journals such as Nature, Physical Review Letters and The Journal of Chemical Physics.
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.