DAN Two-Layer Retrieval Data Release (Sols 3501–4100) This repository contains processed Dynamic Albedo of Neutrons (DAN) two-layer retrieval products and supporting summary products for Curiosity observations spanning sols 3501–4100. The release is organized into region-level summary products and per-location retrieval products. File names use a consistent `site / drive / start_sol / stop_sol` convention so that products from different subdirectories can be matched directly. Retrievals are performed on coadds of all observations at a given site/drive, producing one retrieval per location. Repository structure 2_layer_DAN_sols_3501_4100/└── retrieval_products/ retrieval_products/ This directory contains the observation-level retrieval products and diagnostics. retrieval_products/├── background_subtracted_coadd/├── coadd_observations/├── coadd_product/├── corner_plots/├── GMMs/│ ├── unmix_2/│ │ └── gmm_mix/│ └── unmix_variable/│ ├── gmm_mix/│ └── gmm_selection/├── MCMC_backend/├── SNR/├── times/└── walker_plots/ Naming convention Most files share a common stem: site_<SITE>_drive_<DRIVE>_start_sol_<START>_stop_sol_<STOP> For example: site_026_drive_1274_start_sol_542_stop_sol_542This stem is followed by a product-specific suffix, for example: - _bg_dat.npy- _label_matched.txt- _coadded.npy- _corner_plot.png- _gmm_mix.png- _gmm_selection.png- _MCMC.h5.zip- _CETN_SNR.npy- _CTN_SNR.npy- _times.npy- _walker_plot.png This convention allows all products associated with a given coadded retrieval to be aligned by filename. Retrieval content The products in this release correspond to a two-layer retrieval framework. The primary retrieved physical parameters are: - Bottom Layer WEH: bottom-layer water-equivalent hydrogen, in wt%- Top Layer WEH: top-layer water-equivalent hydrogen, in wt%- Bottom Layer Σ_abs: bottom-layer bulk macroscopic neutron absorption cross section (BNACS), in cm^2/g- Top Layer Σ_abs: top-layer bulk macroscopic neutron absorption cross section (BNACS), in cm^2/g- Depth: modeled interface depth between the two layers, in cm Posterior diagnostics may also include an additional logf[counts] fit parameter in the MCMC products. Observation-level products Each retrieval generally includes one file in each of the subdirectories below. background_subtracted_coadd/ Files ending in _bg_dat.npy contain the background-subtracted count data used in retrieval processing. coadd_observations/ Files ending in _label_matched.txt list the DAN observation label or labels contributing to the coadded retrieval product. These files provide the traceability link between the retrieval and the original contributing observation set. coadd_product/ Files ending in _coadded.npy contain the coadded observation-space product used as the retrieval input. corner_plots/ Files ending in _corner_plot.png are posterior diagnostic figures showing parameter distributions and pairwise covariances. GMMs/ This directory contains Gaussian mixture model post-processing products. - unmix_2/ contains fixed two-component mixture summaries.- unmix_variable/ contains variable-component mixture exploration products. Within these directories: - gmm_mix/ contains posterior unmixing summary plots.- gmm_selection/ contains model-selection plots used to compare mixture counts. These products support interpretation of multimodal posterior structure. MCMC_backend/ Files ending in _MCMC.h5.zip are compressed HDF5 backends containing the archived MCMC chains. These are the primary reproducibility products for users who want to regenerate posterior summaries, diagnostics, or alternate post-processing results. SNR/ This directory contains per-observation signal-to-noise products: - *_CETN_SNR.npy- *_CTN_SNR.npy These arrays store time-bin-level SNR values associated with the retrieval input data. times/ Files ending in _times.npy contain the time-bin definitions associated with the DAN die-away measurement. walker_plots/ Files ending in _walker_plot.png show the evolution of the MCMC walkers as a function of iteration number and are intended for quality control and convergence assessment. Recommended use A typical use pattern is: 1. Start with regional_summaries/ to review region-scale behavior and identify observations of interest.2. Use coadd_observations/ to trace a retrieval back to the contributing DAN observation labels.3. Use coadd_product/, background_subtracted_coadd/, SNR/, and times/ for observation-space analysis.4. Use corner_plots/, walker_plots/, and GMMs/ for posterior interpretation and quality control.5. Use MCMC_backend/ when full reproducibility or custom post-processing is required. Acknowledgment If you use these products in published work, please cite the associated data release and the relevant scientific publications describing the DAN retrieval methodology.