The archive contains dataset and python scripts that can be used to reproduce figures presented in "Fermionizing the ideal Bose gas via topological pumping".
This record provides the complete figure archive and figure-generation code for the manuscript: “A Differential Null Test for Informational Corrections to Gravity-Related State Reduction.” The archive contains the final manuscript and Supplemental Material figures in both PDF and PNG formats, together with a reproducible Python/Matplotlib script for regenerating the figure set. The figures support a theoretical proposal for a differential null test of informational corrections to gravity-related quantum state reduction. The manuscript develops a matched-pair visibility-residual framework in which ordinary gravitational and environmental baseline terms are cancelled, leaving a testable bound on the informational coupling parameter. The included figures are: Fig1 — main manuscript figure showing the differential null-test structure and visibility-residual logic. FigS1–FigS5 — supplementary figures supporting the branch-density construction, perturbative regime, visibility residuals, coupling bounds, and source-to-energy schematic. The code package includes: generate_prl_figures.py — Python script for regenerating the full figure set. requirements.txt — minimal package requirements. PDF and PNG output folders. SHA256 manifest for file-integrity checking. This Zenodo record is intended to support transparency, reproducibility, and independent inspection of the visual materials associated with the manuscript. The figures are synthetic/theoretical benchmark illustrations and do not represent observational detections or experimental data. Suggested citation use: cite this record when referring to the reproducible figure-generation code or archived figure files associated with the manuscript.
Reproducibility package for the paper "Number-projected coherent-state kernels for variational Bose-field dynamics" submitted to New Journal of Physics (2026). Contains the LaTeX manuscript source, Python benchmark scripts, numerical data (CSV), and publication-quality figures. Scripts reproduce all results (Figs. 1–5) for two-, three-, and four-mode Bose-Hubbard models using number-projected coherent states with fixed-basis Galerkin and moving-basis TDVP methods. Requirements: Python 3.8+, NumPy, SciPy, Matplotlib.