Exact kinetic propagators for coherent state complex Langevin simulations

We introduce and benchmark an improved algorithm for complex Langevin simulations of bosonic coherent state path integrals in the preprint. Our approach utilizes a Strang splitting of the imaginary-time propagator rather than the conventional linear-order Taylor expansion, allowing us to construct an action that incorporates higher-order terms at negligible computational cost. The resulting algorithm enjoys guaranteed linear stability independent of the imaginary-time discretization, enabling more resource-efficient simulations. We demonstrate this improved performance for single-species bosons and for two-component bosons with Rashba spin-orbit coupling. The enclosed data set shows a method comparison between the standard \"primitive\" approach and the quadratic propagator technique used in this manuscript for many thermodynamic observables of interest.
, Both methods involve complex Langevin sampling of a coherent state path integral, built from a second-quantized description of interacting bosons at finite temperature. Details are provided in the enclosed manuscript as well as the following publications: https://doi.org/10.1103/PhysRevLett.131.173403 and https://doi.org/10.1103/PhysRevLett.124.070601
, # Exact kinetic propagators for coherent state complex Langevin simulations

This README.txt file was generated on 2025-08-18 by Ethan McGarrigle.

GENERAL INFORMATION

Date of data collection: 2025-07-01 through 2025-08-01

Geographic location of data collection: University of California Santa Barbara, Santa Barbara, California, USA

Information about funding sources that supported the collection of the data: This work was enabled by field-theoretic simulation tools developed under support from the National Science Foundation (CMMT Program, DMR-2104255). Use was made of computational facilities purchased with funds from the NSF (CNS-1725797) and administered by the Center for Scientific Computing (CSC). This work made use of the BioPACIFIC Materials Innovation Platform computing resources of the National Science Foundation Award No. DMR-1933487. The CSC is supported by the California NanoSystems Institute and the Materials Research Science and Engineering Center (MRSEC; NSF DMR 2308708..., , **Changes after Sep 11, 2025:** Extended the data sets to include more simulations at finer imaginary time discretizations. The data format is the same as the previous version, i.e. the column meanings are the same. The revised data sets include more rows corresponding to larger values of N_{\tau}, the number of imaginary time points employed in a given simulation.