Reproducibility data and analysis code for "Adaptive generator matrices for automated collective Monte Carlo moves in semiflexible polymer simulations"

This record contains simulation outputs and post-processing materials supporting the manuscript “Adaptive generator matrices for automated collective Monte Carlo moves in semiflexible polymer simulations” by Takafumi Iwaki and Masato Tanigawa. The deposited datasets cover comparisons between fixed single-column generators (Single Mode) and continuously adapted full generator matrices (Normal Mode) for a coarse-grained semiflexible linear polymer. They include acceptance-ratio sweeps, long learning trajectories, autocorrelation measurements using frozen learned generators, continued-adaptation validation, and a supplementary comparison between piecewise-linear and natural cubic-spline interpolation. The accompanying reproducibility package rebuilds the intermediate CSV files, canonical SVG figures, manuscript tables, and numerical-claim export from the archived simulation outputs. It also verifies the regenerated outputs against archived references. The analysis can be reproduced on Windows, Linux, and macOS using Python, NumPy, and pandas. Four archives are required for the principal manuscript analysis: compare-ns-mini-AR01-06.zip compare-long-AR02-03.zip ACF-AR02-03.zip AR02-after-learn.zip AR02-mini-spline.zip contains an additional interpolation diagnostic and is not required for rebuilding the principal figures and tables. Manuscript-reproducibility-package.zip contains the analysis, validation, and verification scripts. The deposited files reproduce the post-processing chain from saved simulation logs and generator snapshots. They do not rerun the computationally expensive Monte Carlo trajectories themselves. The simulation software is distributed separately in the associated software repository and archive.