Data and code associated to the paper "Time-dependent variational Monte Carlo without bias"

This Zenodo entry contains the data, scripts and source code needed toreproduce the numerical experiments and figures of the publication**"Time-dependent variational Monte Carlo without bias"** (W. Krinitsin, M. Schmitt): https://doi.org/10.48550/arXiv.2605.03930 The folder layout follows the figures of the paper. Each numericalexperiment lives in its own subdirectory and follows the layout produced by[encap](https://github.com/computational-quantum-science/encap) (a thin wrapper that copies the mainscript and its auxiliary files into a self-contained run directory): * `run.py` (or `eval_*.jl`) — the main script* `input.json` — all parameters of the run* `nets/`, `sampler/`, `src/` — auxiliary Python / Julia modules used by `run.py`* `*.csv`, `*.h5`, `*.npy` — data produced by the run The plots themselves are generated by the Julia notebook **`plots.ipynb`**at the top level of this entry. All paths inside the notebook and insideeach script are relative to this folder; nothing outside it is needed. ## Top-level layout ```zenodo/├── README.md ├── plots.ipynb Julia notebook that produces all figures├── figures/ Output PDFs of plots.ipynb├── figure3_bias_example/ Bias example (Figure 3)├── figure4_crit_tfim/ Critical TFIM TDVP + fidelity (Figure 4)├── figure5_snr_norm/ SNR / renormalization analysis (Figure 5)└── figure6_tci/ TCI vs. exact comparison (Figure 6)``` Each subfolder contains its own `README.md` describing the experiments andhow they feed into the corresponding figure.