Application and Perspectives of Simulation Methods Based on Field Theory in Soft Matter

Soft matter science is an important branch in the fields of physics, chemistry, and material science. However, the complexity of soft matter systems, especially their multi-scale structures and rich dynamic behaviors, poses significant challenges to researchers. To address these challenges, simulation methods based on field theory demonstrate unique advantages in simulation techniques. By introducing continuous field variables, they provide a more efficient and macroscopic perspective for describing and handling complex interactions in soft matter systems. This article first introduces the basic principles of polymer field theory and elaborates on their applications in soft matter physics, such as the structure prediction of protein HP models, the static topological entanglement problems of polymer chains, chemical reaction/light induced microphase separation, etc. It then explores the application of modern computational technologies like deep learning in soft matter research, and finally looks forward to the future research trends and developments in the field of soft matter, pointing out that field theory remains a powerful tool for soft matter study.