Editorial: Statistical and Nonlinear Physics Crosses a Threshold

Abstract

We are delighted to announce the transition of the American Physical Society's (APS) Topical Group on Statistical and Nonlinear Physics (GSNP) to a Division (DSNP [1]) as a result of a steady growth in membership. Divisions are the largest units representing subfields within APS, with increased opportunities for scientific sessions at meetings, broader participation, and better representation within APS governance. We find it very fitting that Physical Review E, the APS journal with which the scope of our activities best aligns, has graciously invited us to mark this event in its pages. PRE and GSNP were born in the same period—the journal in 1993 and the topical group only a few years later in 1997—with a similar unifying intent: the interfaces of the field were rapidly multiplying, and there was a need to anchor many disparate systems to their strong disciplinary roots within physics. There is also a strong overlap with the scope of topics that PRE is home to [2]: Statistical physics; nonlinear dynamics and chaos; networks and complex systems; biological physics; soft matter including polymers, liquid crystals, and granular materials; mechanics, interfaces, and films; fluid dynamics; plasma physics; computational physics, machine learning, and artificial intelligence. The shift in emphases within GSNP have also mirrored the shift in focus of PRE. When PRE started in 1993, its subtitle was “Statistical physics, plasmas, fluids, and related interdisciplinary topics.” In 2000, the subtitle of PRE added soft matter physics. Thereafter, new areas of research, such as network science and machine learning have become a significant part of PRE. GSNP has also expanded its focus to accommodate emerging topics in these years.