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Mission Overview

Rocky Worlds DDT ("ROCKY-WORLDS")

 

Primary Investigator: Nestor Espinoza, Hannah Diamond-Lowe

HLSP Authors: Taylor Bell, Leonardo A. Dos Santos

Released: 2025-09-17

Updated: 2026-01-14

Primary Reference(s): rockyworlds.stsci.edu

DOI: 10.17909/qsyr-ny68

Read Me

Source Data:

 

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GJ 3929 b JWST Raw Measurements

Figure 1. Raw flux and PSF-metric measurements from a Rocky Worlds DDT eclipse observation of GJ 3929b taken with JWST/MIRI’s F1500W filter.

GJ 3929 b JWST Light Curve Fit

Figure 2. An example fit to a JWST/MIRI F1500W eclipse observation of GJ 3929b collected by the Rocky Worlds DDT Program.

GJ 3929 HST Spectrum

Figure 3. Co-added Lyman-alpha spectrum of GJ 3929 as observed in Visit 8 (black). The blue curves represent a family of random models of the intrinsic Lyman-alpha emission of GJ 3929 that fit the data. The red curves represent the same models, but with models of the interstellar medium absorption included.

 

Overview

The Rocky Worlds Director's Discretionary Time (DDT) Program is a joint James Webb Space Telescope (JWST) and Hubble Space Telescope (HST) Program. It implements the top recommendations from the Working Group on Strategic Exoplanet Initiatives with HST and JWST, which compiled the views of the community in regards to many topics including specific concepts for a 500-hour DDT JWST exoplanet program (Redfield et al. 2024). The program's main objectives are to search for evidence for atmospheres on rocky exoplanets orbiting M-dwarfs via secondary eclipse measurements at 15 um using the MIRI instrument, as well as to characterize the stellar UV properties with HST. 

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Data Products

JWST Data Products

The JWST data products follow the naming convention:

hlsp_rocky-worlds_jwst_miri_<target>-<eclipse>_<filter>_v1.0_<product>.<ext>

where:

  • <target> is the name of the target, for example, "gj3929b"
  • <eclipse> is the identifier for the observation, for example, "ecl001"
  • <filter> is the name of the filter used for the observation
  • <product> is the type of data product, either "eclipse-cat" or "lc"
  • <ext> is the file extension, either "fits" or "h5"

Data file types:

_eclipse-cat.fits Eclipse catalog fits file. Science-ready, high-level data products for individual observations that can be used to investigate planetary and stellar properties.
_eclipse-cat.h5 Eclipse catalog netCDF4/HDF5 file. Science-ready, high-level data products for individual observations that can be used to investigate planetary and stellar properties. Content is identical to the _eclipse-cat.fits files, but in netCDF4/HDF5 format.
_lc.h5 Light curve netCDF4/HDF5 file. Intermediate-level data products that can be used to reproduce and/or improve upon the analyses that led to the high-level data products.

 

A full description of the columns and units in each file is available in the Read Me file.

HST Data Products

The HST data products follow the naming convention:

hlsp_rocky-worlds_hst_stis_<target>_<filter>_v1.0_<product>.fits

where:

  • <target> is the name of the target, for example, "gj3929b"
  • <filter> is the name of the filter used for the observation
  • <product> is the type of data product, either "spec" (spectrum) or "lc" (light curve)

Data file types:

_spec.fits

Co-added UV spectrum of the host star. Multiple intermediate-level

files will be produced for each grating. A high-level product that stitches all the

different modes is created when all observations are obtained. It includes one

science extension with the observed data and another extension with a model for

the intrinsic stellar Lyman-𝛼 emission line. This product is updated every time a

new relevant observation is obtained.

_lc.fits

 

Light curve FITS file. Intermediate- to high-level data product that can be

used to reproduce and/or improve upon analyses of flares and stellar variability.

It includes one science extension with the observed data and another extension

that includes a flare model fit to the data if one is detected. One HLSP is created

per HST visit
_x1d.fits

The _x1d files are intermediate-level data products. They correspond to the _x1d fits files (extracted 1-d spectra) that automatically come out of the CALSTIS pipeline, with the difference that its background spectra and source spectra are extracted at custom locations. These custom locations can be inferred from the metadata available in the headers. The customization is sometimes necessary, since CALSTIS may not be able to automatically infer the trace position of faint sources in the FUV, such as M dwarfs.

 

A full description of the columns and units in each file is available in the Read Me file.

Data Access

MAST Portal and Astroquery

The ROCKY-WORLDS data products are available in the MAST Search Portal (web-based, cross-mission search interface) and Astroquery (Python package to search for and download files from Python scripts you write).

  • In the MAST Search Portal, set the Provenance Name filter to "ROCKY-WORLDS" in an Advanced Search to find these data. The user guide for how to search and download products using the MAST Portal is available here.
  • For Astroquery, the following example code demonstrates how to search for and download these products. This code assumes that you want to download all products from this HLSP, so you may want to consider narrowing down your search for large HLSPs (> 10 GB) or those with many individual files (> 10k). You can find more astroquery.mast tutorials here.
from astroquery.mast import Observations
# Search for all ROCKY-WORLDS products
all_obs = Observations.query_criteria(provenance_name="rocky-worlds")
data_products = Observations.get_product_list(all_obs)
# Print the number of data products that would be downloaded
print(len(data_products))
# Download data
Observations.download_products(data_products)

  • MAST Portal

    Link to the MAST Portal Webpage
    A web-based interface for cross-mission searches of data at MAST or the Virtual Observatory.
    Portal

  • MAST Astroquery

    Search for and download data products for this HLSP programmatically in Python.
    MAST Astroquery

Direct Download

The data products for this HLSP are also available for direct download using the links in the table below. For the most up-to-date status regarding each observation and future targets, please refer to the Rocky Worlds DDT Website for the full Observing Schedule.

GJ-3929 b
Artist's Image JWST Products HST Products

GJ-3929 b

exoplanet_gj3929b.png

 

Eclipse 1: 

Eclipse 2: 

Visit 8:

Source Data: 

Source Data:

Code Examples

The authors of this HLSP have provided a few code examples for working with the data in Python, shown below. For more code on how to work with and analyze data from Rocky Worlds DDT, see the rocky-worlds-utils Github repository.

Reading the JWST Eclipse Catalog

This example shows how to open the JWST eclipse catalog file in Python and how to read metadata from netCDF4/HDF5 files.

import xarray as xr

# Open Eclipse Catalog
filename = "hlsp_rocky-worlds_jwst_miri_gj3929b-ecl001_f1500w_v1.0_eclipse-cat.h5"
ds = xr.load_dataset(filename)

# Prints out summary information about the dataset
print(ds)

# An example of how to get access to the metadata stored in the file
print(ds.attrs['HLSPTARG'])

Plotting the JWST Light Curve

This example opens the JWST light curve file and creates a plot of the flux over time, highlighting the best fit model results for this eclipse:

import xarray as xr
import numpy as np
import matplotlib.pyplot as plt
from astropy.stats import sigma_clip
 
filename_lc = 'hlsp_rocky-worlds_jwst_miri_gj3929b-ecl001_f1500w_v1.0_lc.h5'
ds_lc = xr.load_dataset(filename_lc)
 
# Compute the x-axis offset for tidy x-ticks
t_offset = int(np.floor(np.nanmin(ds_lc.time.values)))
 
# Setup the 3 panel figure
fig, axs = plt.subplot_mosaic('A;B;C', figsize=(10*0.8,7.5*0.8), sharex=True, gridspec_kw={'hspace':0.075})
 
# Plot the raw light curve measurements and the fitted model
axs['A'].errorbar(ds_lc.time-t_offset, sigma_clip(ds_lc.rawFlux[0], 10), ds_lc.rawFluxErr[0], fmt='.', c='k', alpha=0.1)
axs['A'].plot(ds_lc.time-t_offset, ds_lc.fullModel[0], '-', c='r', lw=1, label='Full Fitted Model', zorder=np.inf)
 
# Plot the systematics-removed measurements and the fitted eclipse model
axs['B'].errorbar(ds_lc.time-t_offset, ds_lc.cleanedFlux[0], ds_lc.rawFluxErr[0], fmt='.', c='k', alpha=0.1)
axs['B'].plot(ds_lc.time-t_offset, ds_lc.astroModel[0], '-', c='r', lw=1, label='Fitted Eclipse Model', zorder=np.inf)
 
# Plot the data-model residuals in units of ppm
axs['C'].errorbar(ds_lc.time-t_offset, (ds_lc.rawFlux[0]-ds_lc.fullModel[0])*1e6, ds_lc.rawFluxErr[0]*1e6, fmt='.', c='k', alpha=0.1)
axs['C'].axhline(0, c='r', lw=1, zorder=np.inf)
 
# Setup the figure axes and other details
axs['A'].set_title(f"{ds_lc.attrs['PLANET']} Fiducial Light Curve Fit")
axs['A'].set_ylabel("Raw Flux")
axs['B'].set_ylabel("Cleaned Flux")
axs['C'].set_ylabel("Residuals (ppm)")
axs['C'].set_xlabel(f"Time (BJD_TDB - {t_offset})")
axs['A'].legend(loc=1)
axs['B'].legend(loc=1)
fig.align_ylabels([axs['A'], axs['B'], axs['C']])
 
plt.show()

Plotting the HST Spectrum

This example opens the HST spectrum file and creates a plot for GJ 3929:

import matplotlib.pyplot as plt
from astropy.io import fits

filename = "hlsp_rocky-worlds_hst_stis_gj3929_g140m_v1.0_spec.fits"

observed_spectrum = fits.getdata(filename, ext=1)

# Plot full observed spectrum
ax = plt.subplot()
ax.plot(observed_spectrum['WAVELENGTH'],
        observed_spectrum['FLUX'])
ax.set_xlabel(r'Wavelength [${\rm \AA}$]')
ax.set_ylabel(r'Flux density [erg s$^{-1}$ cm$^{-2}$ ${\rm \AA}^{-1}$]')
ax.set_xlim(min(observed_spectrum['WAVELENGTH']), max(observed_spectrum['WAVELENGTH']))
plt.show()

# Plot observed Lyman-alpha spectrum and the reconstruction model
model_spectrum = fits.getdata(filename, ext=2)
ax = plt.subplot()
ax.errorbar(observed_spectrum['WAVELENGTH'],
            observed_spectrum['FLUX'],
            yerr=observed_spectrum['FLUXERROR'],
            label='Observed spectrum')
ax.errorbar(model_spectrum['WAVELENGTH'],
            model_spectrum['FLUX'],
            yerr=model_spectrum['FLUXERROR'],
            label='Reconstruction model')

plt.legend(loc=2)
ax.set_xlabel(r'Wavelength [${\rm \AA}$]')
ax.set_ylabel(r'Flux density [erg s$^{-1}$ cm$^{-2}$ ${\rm \AA}^{-1}$]')
ax.set_xlim(min(model_spectrum['WAVELENGTH']), max(model_spectrum['WAVELENGTH']))
plt.show()

Citations

Please remember to cite the appropriate paper(s) below and the DOI 10.17909/qsyr-ny68 if you use these data in a published work. 

Note: These HLSP data products are licensed for use under CC BY 4.0.

References

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