Published March 10, 2026 | Version v1
Dataset Open

Europa dose maps (from Yoffe et al., 2025; Astrobiology)

  • 1. Weizmann Institute of Science

Description

Ion/Electron Deposited Energy Maps (.npz)

 

Overview

 

This repository stores NumPy .npz bundles output by G4beamline post‑processing for deposited energy/dose in water ice.

Files include 1D ion depth profiles and 2D integrated surface maps derived from electron grids, optionally with ions added.

Units: dose rates in MGy yr^-1. Depth in mm. Density labels in g cm^-3.

File Naming

 

EDep_ions_MGy_density-{density}.npz

Example: EDep_ions_MGy_density-0.5.npz

integrated_deposited_energy_{hemisphere}_electrons.npz

Example: integrated_deposited_energy_trailing_electrons.npz

integrated_deposited_energy_{hemisphere}_both.npz

Example: integrated_deposited_energy_leading_both.npz

{hemisphere} is leading or trailing.

Contents by File Type

 

Ion depth profiles: EDep_ions_MGy_density-{density}.npz

 

Keys

z: 1D array of depths in mm (increasing)

p: 1D dose profile for H+ in MGy yr^-1 (same length as z)

O: 1D dose profile for O^{2+} in MGy yr^-1

S: 1D dose profile for S^{3+} in MGy yr^-1

Notes

Species keys are present only if that species was simulated; missing keys imply zero.

All species share the same depth grid z.

Integrated maps (2D): integrated_deposited_energy_{hemisphere}_electrons.npz

 

Keys

vals: 2D array (surface grid) of electron dose integrated over depth, MGy yr^-1

Notes

Shape matches the electron hemisphere grid used during generation.

Axes correspond to the model’s surface discretization (longitude/latitude bins). If you need explicit coordinate arrays, keep them alongside the source pipeline or regenerate them from it.

Integrated maps (2D, electrons + ions): integrated_deposited_energy_{hemisphere}_both.npz

 

Keys

vals: 2D array (surface grid) of total dose integrated over depth, MGy yr^-1

Notes

Constructed as the electron integrated map plus the depth‑integrated ion profile applied uniformly across the hemisphere (uniform scalar offset from ions).

Loading Examples (Python)

 

Ion depth profiles

Load and plot species; compute total ion dose vs depth

import numpy as np

import matplotlib.pyplot as plt

 

dat = np.load('EDep_ions_MGy_density-0.5.npz')

z = dat['z']  # mm

ED_p = dat['p'] if 'p' in dat else 0*z

ED_O = dat['O'] if 'O' in dat else 0*z

ED_S = dat['S'] if 'S' in dat else 0*z

 

ED_total = ED_p + ED_O + ED_S  # MGy/yr vs depth

 

plt.loglog(z, ED_p, label='H+')

plt.loglog(z, ED_O, label='O++')

plt.loglog(z, ED_S, '--', label='S+++')

plt.loglog(z, ED_total, 'k', label='Total ions')

plt.xlabel('Depth [mm]'); plt.ylabel('Dose rate [MGy yr$^{-1}$]'); plt.legend(); plt.show()

Depth‑integrated ion scalar to combine with electron maps

# If z is nonuniform, use np.trapz for accuracy

ion_scalar = np.trapz(ED_total, z)  # MGy/yr integrated over depth

Integrated surface maps (electrons only or both)

import numpy as np

import matplotlib.pyplot as plt

 

M_el = np.load('integrated_deposited_energy_trailing_electrons.npz')['vals']

M_both = np.load('integrated_deposited_energy_trailing_both.npz')['vals']

 

fig, ax = plt.subplots(1, 2, figsize=(10,4), constrained_layout=True)

im0 = ax[0].imshow(M_el, origin='upper'); ax[0].set_title('Electrons (depth‑integrated)')

im1 = ax[1].imshow(M_both, origin='upper'); ax[1].set_title('Electrons + ions (depth‑integrated)')

for a in ax: a.set_xlabel('Longitude bin'); a.set_ylabel('Latitude bin'); a.grid(alpha=0.2)

fig.colorbar(im0, ax=ax[0], fraction=0.046, pad=0.04, label='MGy yr$^{-1}$')

fig.colorbar(im1, ax=ax[1], fraction=0.046, pad=0.04, label='MGy yr$^{-1}$')

plt.show()

Conventions and Units

 

Dose values are MGy yr^-1. (1 Gy = 1 J kg^-1.)

Depth z is in mm measured from the surface inward.

density in filenames is the bulk density in g cm^-3 of the ice used in the conversion.

Hemispheres: leading or trailing with respect to orbital motion.

Best Practices

 

Always inspect dat.files to see which species exist in an ion bundle:

np.load(path).files returns the available keys.

Ensure species depth grids match before combining different ions; in these bundles all species share the same z by construction.

When comparing to electron grids, remember that the integrated maps here do not carry explicit longitude/latitude coordinate arrays—carry them alongside if needed in your workflow.

Reproducibility Notes

 

The ion bundle is built so repeated runs append/update species while enforcing the same z grid.

The “both” map assumes ions are spatially uniform over the hemisphere (uniform scalar from depth‑integrated ion dose). If you later have spatially resolved ion maps, prefer recomputing “both” from matching grids.

Files

Files (703.2 MB)

Name Size Download all
md5:26f273c000387e2a20ce35a50b9c5e4d
140.6 MB Download
md5:9b5516c9856949ee17e784e52cbbb752
140.6 MB Download
md5:7e29dad8b87ace623ab73a0cad6d6baf
140.6 MB Download
md5:d26bb0b33e98345add801b87378727cd
140.6 MB Download
md5:dcb52f35cc23b428d14e604b324f89e6
140.6 MB Download

Additional details

Related works

Is described by
Publication: 10.1089/ast.2024.0140 (DOI)

Software

Programming language
Python