Active matter is composed of units that consume energy to move or exert forces, producing collective behaviours without equilibrium counterparts. In this Review, we synthesize progress across biological and synthetic systems, from bacterial swarms and cytoskeletal networks to colloidal rollers and robot swarms. We highlight unifying theoretical frameworks, experimental platforms that allow precise control, and emerging applications in adaptive materials and swarm engineering, and we identify open questions about information, control and thermodynamics in active systems.
Introduction
Few areas of research have developed as quickly as active matter physics. Over the past decade, conceptual and technical advances have transformed what can be measured and engineered1–4, and have brought long-standing questions within reach of experiment5,6.
Yet the field continues to be shaped by the lack of a general theory for systems far from equilibrium7. In this article, we survey recent progress, highlight emerging consensus and disagreement, and identify the developments most likely to move the field forward.
Foundations
Early work established the core concepts and the first quantitative models8–10. These frameworks remain useful but rest on simplifying assumptions whose limits are increasingly apparent11.
A unifying theme is that progress has come from combining new measurements with models that make falsifiable predictions.
Recent advances
Three developments stand out. First, new experimental platforms allow systematic, high-throughput measurements12–14. Second, computational methods now enable predictions that can be tested directly15,16. Third, large collaborative datasets have made it possible to compare results across laboratories and systems17.
Approach
Strengths
Limitations
Controlled experiments
Causal inference, precision
Limited scale and realism
Large-scale observation
Generality, statistical power
Confounding factors
Computational models
Mechanistic insight, prediction
Dependence on assumptions
Open questions
Important questions remain unresolved, including how findings generalize across scales and contexts18, and how best to translate insight into application19,20.
Outlook
We anticipate that the next decade will see active matter physics move from proof-of-principle demonstrations to robust, predictive science. Achieving this will require shared standards, open data and sustained support for interdisciplinary teams.
References
1.
Bello, C. Mechanisms underlying active matter physics: a critical assessment. Lumen 212, 4–7 (1999).
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Ivanova, A., Kim, L., Kim, M. & Raman, P. Active matter: from bacterial swarms to robot collectives. Lumen3, 21–30 (2026). https://doi.org/10.5555/lmn-2026-00008