Reproduction Code and Data for " Kramers-Kronig Relations and Causality in Non-Markovian Open Quantum Dynamics: Kernel, State, and Effective Kernel"

This dataset contains the numerical code and data supporting the figures and numerical results reported in: K. Liu, "Kramers-Kronig Relations and Causality in Non-Markovian Open Quantum Dynamics: Kernel, State, and Effective Kernel," arXiv:2604.17058 (2026). https://doi.org/10.48550/arXiv.2604.17058 The manuscript studies the analytic structure of three objects central to non-Markovian open quantum dynamics — the Nakajima–Zwanzig memory kernel, the reduced-state Laplace transform, and the force-fit effective kernel — and establishes Kramers–Kronig (KK) relations for each, with consequences for CPTP consistency, passivity–analyticity compatibility, and the algebraic origin of upper-half-plane zero placement in a Jaynes–Cummings model. This archive provides: - the full research codebase used to generate all six manuscript figures (Python; a few auxiliary Julia scripts); - all underlying numerical data (pickled NumPy/SciPy results and JSON scan outputs); - a README that maps each manuscript figure to its generator script and gives the SHA-1 hash of the figure PDF as deposited with the paper, so that reproduced output can be verified byte-for-byte. Status of the code. This is a raw dump of the research code as it stood when the manuscript figures were produced; it has not been refactored into a run-out-of-the-box package. The figure scripts were written for the original research directory layout (code/src/ alongside sibling data/ and tex/figures/ directories) and resolve paths relative to the script file, so reproducing a figure requires either restoring that directory structure or editing the DATA_DIR / FIG_DIR / OUT_DIR path constants at the top of each script. In two cases the figure code was rewritten during the project and the newer generator inherited the output filename of the script it replaced, while the older script is retained for provenance and still writes a same-named PDF from an earlier stage of the work; the README's figure-to-script mapping table and its "Why two figure scripts can mislead" section identify the correct generator in each case. See the in-archive README.md for full guidance and the ground-truth hashes. Software environment: Python 3.11 with NumPy, SciPy, Matplotlib, and mpmath; some exploratory scans were run on the Soochow University cluster (SLURM). See requirements.txt and the in-archive README for details.