Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Taking census of physics

Nature Reviews Physics volume 1, pages 89–97 (2019)Cite this article

Subjects

Abstract

Over the past decades, the diversity of areas explored by physicists has exploded, encompassing new topics from biophysics and chemical physics to network science. However, it is unclear how these new subfields emerged from the traditional subject areas and how physicists explore them. To map out the evolution of physics subfields, here, we take an intellectual census of physics by studying physicists’ careers. We use a large-scale publication data set, identify the subfields of 135,877 physicists and quantify their heterogeneous birth, growth and migration patterns among research areas. We find that the majority of physicists began their careers in only three subfields, branching out to other areas at later career stages, with different rates and transition times. Furthermore, we analyse the productivity, impact and team sizes across different subfields, finding drastic changes attributable to the recent rise in large-scale collaborations. This detailed, longitudinal census of physics can inform resource allocation policies and provide students, editors and scientists with a broader view of the field’s internal dynamics.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Census of the physics subfields.
Fig. 2: Evolution of physics subfields and careers.
Fig. 3: Productivity and impact across physics communities.

References

  1. Jones, B. F. The burden of knowledge and the “death of the renaissance man”: Is innovation getting harder? Rev. Econ. Stud. 76, 283–317 (2009).

    Article  Google Scholar 

  2. Clauset, A., Larremore, D. B. & Sinatra, R. Data-driven predictions in the science of science. Science 355, 477–480 (2017).

    Article  ADS  Google Scholar 

  3. Fortunato, S. et al. Science of science. Science 359, eaao0185 (2018).

    Article  Google Scholar 

  4. Deville, P. et al. Career on the move: geography, stratification, and scientific impact. Sci. Rep. 4, 4770 (2014).

    Article  Google Scholar 

  5. Sinatra, R., Deville, P., Szell, M., Wang, D. & Barabási, A.-L. A century of physics. Nat. Phys. 11, 791 (2015).

    Article  Google Scholar 

  6. Deville, P. Understanding social dynamics through big data. Thesis, Univ. Catholique Louvain (2015).

  7. AIP Publishing. PACS 2010 regular edition. AIP https://publishing.aip.org/publishing/pacs/pacs-2010-regular-edition (2018).

  8. APS Physics. APS data sets for research. APS https://journals.aps.org/datasets (2018).

  9. Dyson, F. Birds and frogs. Not. AMS 56, 212–223 (2009).

    MathSciNet  MATH  Google Scholar 

  10. Uzzi, B., Mukherjee, S., Stringer, M. & Jones, B. Atypical combinations and scientific impact. Science 342, 468–472 (2013).

    Article  ADS  Google Scholar 

  11. Foster, J. G., Rzhetsky, A. & Evans, J. A. Tradition and innovation in scientists’ research strategies. Am. Sociol. Rev. 80, 875–908 (2015).

    Article  Google Scholar 

  12. Chen, P. & Redner, S. Community structure of the physical review citation network. J. Informetr. 4, 278–290 (2010).

    Article  Google Scholar 

  13. Herrera, M., Roberts, D. C. & Natali, G. Mapping the evolution of scientific fields. PloS One 5, e10355 (2010).

    Article  ADS  Google Scholar 

  14. Pan, R., Sinha, S., Kaski, K. & Saramäki, J. The evolution of interdisciplinarity in physics research. Sci. Rep. 2, 551 (2012).

    Article  ADS  Google Scholar 

  15. Guevara, M. R., Hartmann, D., Aristarán, M., Mendoza, M. & Hidalgo, C. A. The research space: using career paths to predict the evolution of the research output of individuals, institutions, and nations. Scientometrics 109, 1695–1709 (2016).

    Article  Google Scholar 

  16. Leslie, S. W. The Cold War and American Science. (Columbia University Press, New York, 1993).

    Google Scholar 

  17. Kaiser, D. I. Booms, busts, and the world of ideas: Enrollment pressures and the challenge of specialization. Osiris 27, 276–302 (2012).

    Article  Google Scholar 

  18. Martin, J. Solid State Insurrection: How the Science of Substance made American Physics Matter. (University of Pittsburgh Press, Pittsburgh, 2018).

    Book  Google Scholar 

  19. ATLAS. ATLAS experiment reports. CERN https://atlas.cern/updates/atlas-news/atlas-experiment-reports-its-first-physics-results-lhc (2018).

  20. Jia, T., Wang, D. & Szymanski, B. K. Quantifying patterns of research-interest evolution. Nat. Human. Behav. 1, 0078 (2017).

    Article  Google Scholar 

  21. Kaiser, D. I. Whose mass is it anyway? particle cosmology and the objects of theory. Social. Stud. Sci. 36, 533–564 (2006).

    Article  Google Scholar 

  22. Crosta, P. M. & Packman, I. G. Faculty productivity in supervising doctoral students? dissertations at cornell university. Econ. Educ. Rev. 24, 55–65 (2005).

    Article  Google Scholar 

  23. Malmgren, R. D., Ottino, J. M. & Amaral, L. A. N. The role of mentorship in protégé performance. Nature 465, 622 (2010).

    Article  ADS  Google Scholar 

  24. Chariker, J. H., Zhang, Y., Pani, J. R. & Rouchka, E. C. Identification of successful mentoring communities using network-based analysis of mentor–mentee relationships across nobel laureates. Scientometrics 111, 1733–1749 (2017).

    Article  Google Scholar 

  25. Zuckerman, H. Patterns of productivity, collaboration, and authorship. Am. Sociol. Rev. 32, 391–403 (1967).

    Article  Google Scholar 

  26. Ma, Y. & Uzzi, B. The scientific prize network predicts who pushes the boundaries of science. https://arxiv.org/abs/1808.09412 (2018).

  27. Sekara, V. et al. The chaperone effect in science. PNAS (in the press).

  28. Szell, M. & Sinatra, R. Research funding goes to rich clubs. Proc. Natl. Acad. Sci. 112, 14749–14750 (2015).

    Article  ADS  Google Scholar 

  29. Sinatra, R., Wang, D., Deville, P., Song, C. & Barabási, A.-L. Quantifying the evolution of individual scientific impact. Science 354, aaf5239 (2016).

    Article  Google Scholar 

  30. Liu, L. et al. Hot streaks in artistic, cultural, and scientific careers. Nature 559, 396–399 (2018).

    Article  ADS  Google Scholar 

  31. Radicchi, F., Fortunato, S. & Castellano, C. Universality of citation distributions: Toward an objective measure of scientific impact. Proc. Natl. Acad. Sci. 105, 17268–17272 (2008).

    Article  ADS  Google Scholar 

  32. Pavlidis, I., Petersen, A. M. & Semendeferi, I. Together we stand. Nat. Phys. 10, 700 (2014).

    Article  Google Scholar 

  33. Wuchty, S., Jones, B. & Uzzi, B. The increasing dominance of teams in production of knowledge. Science 316, 1036–1039 (2007).

    Article  ADS  Google Scholar 

  34. Shen, H.-W. & Barabási, A.-L. Collective credit allocation in science. Proc. Natl. Acad. Sci. 111, 12325–12330 (2014).

    Article  ADS  Google Scholar 

  35. Lehmann, S., Jackson, A. & Lautrup, B. Measures for measures. Nature 444, 1003–1004 (2006).

    Article  ADS  Google Scholar 

  36. Lehmann, S., Jackson, A. & Lautrup, B. A quantitative analysis of indicators of scientific performance. Scientometrics 76, 369–390 (2008).

    Article  Google Scholar 

  37. Hicks, D., Wouters, P., Waltman, L., Rijcke, S. D. & Rafols, I. Bibliometrics: the Leiden Manifesto for research metrics. Nature 520, 429–431 (2015).

    Article  ADS  Google Scholar 

  38. Waltman, L. A review of the literature on citation impact indicators. J. Informetr. 10, 365–391 (2016).

    Article  Google Scholar 

  39. Lillquist, E. & Green, S. The discipline dependence of citation statistics. Scientometrics 84, 749–762 (2010).

    Article  Google Scholar 

  40. Radicchi, F. & Castellano, C. Rescaling citations of publications in physics. Phys. Rev. E 83, 046116 (2011).

    Article  ADS  Google Scholar 

  41. Newman, M. The first-mover advantage in scientific publication. EPL (Europhys. Lett.) 86, 68001 (2009).

    Article  ADS  Google Scholar 

  42. Van Noorden, R. Interdisciplinary research by the numbers. Nat. News 525, 306 (2015).

    Article  Google Scholar 

  43. Szell, M., Ma, Y. & Sinatra, R. A Nobel Opportunity for Interdisciplinarity. Nat. Phys. 14, 1075–1078 (2018).

    Article  Google Scholar 

  44. Bromham, L., Dinnage, R. & Hua, X. Interdisciplinary research has consistently lower funding success. Nature 534, 684–687 (2016).

    Article  ADS  Google Scholar 

  45. arXiv. The arXiv repository. Cornell University Library https://arxiv.org/ (2018).

  46. Martín-Martín, A., Orduna-Malea, E. & Delgado López-Cózar, E. Coverage of highly-cited documents in google scholar, web of science, and scopus: a multidisciplinary comparison. Scientometrics 116, 2175–2188 (2018).

    Article  Google Scholar 

  47. Farmer, J. D. Physicists attempt to scale the ivory towers of finance. Comput. Sci. & Eng. 1, 26–39 (1999).

    Article  Google Scholar 

  48. May, R. M. The Scientific Wealth of Nations. Science 7, 793–796 (1997).

    Article  Google Scholar 

  49. King, D. K. The scientific impact of nations. Nature 430, 311–316 (2004).

    Article  ADS  Google Scholar 

  50. Zhang, Q., Perra, N., Goncalves, B., Ciulla, F. & Vespignani, A. Characterizing scientific production and consumption in physics. Sci. Rep. 3, 1640 (2013).

    Article  ADS  Google Scholar 

  51. Balassa, B. Trade liberalization and 'revealed' comparative advantage. Manchester School 33, 99–123 (1965).

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the John Templeton Foundation Grant #61066 (A.-L.B., F.B., R.S. and M.S.), the Intellectual Themes Initiative (ITI) project ‘Just Data’, funded by Central European University (F.M. and R.S.), the National Science Foundation grant SBE 1829344 (D.W.) and the Air Force Office of Scientific Research grants FA9550-15-1-0077 (A.-L.B., R.S. and M.S.), FA9550-15-1-0364 (A.-L.B. and R.S.), FA9550-15-1-0162 (D.W.) and FA9550-17-1-0089 (D.W.).

Author information

Author notes

  1. These authors contributed equally: Federico Battiston, Federico Musciotto

Authors and Affiliations

  1. Department of Network and Data Science, Central European University, Budapest, Hungary

    Federico Battiston, Federico Musciotto, Albert-László Barabási, Michael Szell & Roberta Sinatra

  2. Kellogg School of Management, Northwestern University, Evanston, IL, USA

    Dashun Wang

  3. Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL, USA

    Dashun Wang

  4. Network Science Institute, Northeastern University, Boston, MA, USA

    Albert-László Barabási, Michael Szell & Roberta Sinatra

  5. Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, MA, USA

    Albert-László Barabási

  6. MTA KRTK Agglomeration and Social Networks Lendulet Research Group, Centre for Economic and Regional Studies, Hungarian Academy of Sciences, Budapest, Hungary

    Michael Szell

  7. Department of Mathematics, Central European University, Budapest, Hungary

    Roberta Sinatra

  8. ISI Foundation, Torino, Italy

    Roberta Sinatra

Authors
  1. Federico Battiston
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Federico Musciotto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dashun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Albert-László Barabási
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Michael Szell
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Roberta Sinatra
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

A.-L.B., R.S., M.S. and D.W. conceived the study. All authors designed the research, discussed the results and commented on the manuscript. F.B., F.M. and R.S. developed the methods. F.B. and F.M. analysed the data. M.S. and R.S. directed the research. F.B., F.M., M.S. and R.S. led the writing of the manuscript and A.-L.B. and D.W. edited the manuscript. F.B. and F.M. wrote the supplementary information.

Corresponding author

Correspondence to Roberta Sinatra.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s noteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Battiston, F., Musciotto, F., Wang, D. et al. Taking census of physics. Nat Rev Phys 1, 89–97 (2019). https://doi.org/10.1038/s42254-018-0005-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s42254-018-0005-3

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing