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Field-theoretic simulations that rely on a partial saddle-point approximation have become powerful tools for studying complex polymer materials. The computational cost of such simulations depends critically upon the efficiency of the iterative algorithm used to identify a partial saddle-point field configuration during each step of a stochastic simulation. We introduce a new algorithm for this purpose that relies on a physically motivated approximation in which the linear response of the density to a small change in a pressure-like field is approximated by the response of a hypothetical homogeneous system. The computational cost of the resulting algorithm is significantly less than that of the commonly used Anderson mixing algorithm.more » « lessFree, publicly-accessible full text available June 21, 2026
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The behavior of complex-Langevin field-theoretic simulations (CL-FTSs) of polymer liquids is sensitive to the nature of saddle-point field configurations, which are solutions of self-consistent field theory (SCFT). Recent work [Kang et al. Macromolecules 2024, 57, 3850] has shown that SCFT saddle-points with real fields are generally not isolated solutions but rather members of a low-dimensional family of continuously-connected complex-valued saddle-points sharing the same Hamiltonian value. We show that this behavior is a natural consequence of the analyticity and translational invariance of the Hamiltonian, which together demand its invariance under generalized translations by displacements with complex components. We also present a numerical algorithm that minimizes the deleterious effects of this generalized symmetry on the stability of CL-FTSs.more » « less
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