Mission Overview
Treasury of Extremely Metal-Poor O Stars (TEMPOS)
Primary Investigator: Grace Telford
HLSP Authors: Grace Telford, Christiana Erba, Julia Roman-Duval
Released: 2026-09-18
Updated: 2026-09-18
Primary Reference(s): Telford et al. 2026
DOI: 10.17909/fcda-fn73
Citations: See ADS Statistics
Source Data:
- Source Data DOI: 10.17909/207f-2b64
- Proposal ID: HST GO 17491
Overview
The Treasury of Extremely Metal-Poor O Stars (TEMPOS) is a Cycle 31 Hubble Space Telescope (HST) Large Treasury program (HST-GO-17491) targeting hot and massive O-type stars in nearby, metal-poor galaxies (below about 20% of the Solar metallicity). Understanding the physics of both massive stars and the interstellar medium in this regime is essential to interpret observations of metal-poor galaxies, including both low-mass dwarf galaxies and chemically unevolved galaxies in the early Universe. Yet, few FUV spectra of O stars of sufficient quality to characterize their fundamental properties and stellar winds exist at these very low metallicites, and heterogeneous observation design (spectral resolution, wavelength coverage) and incomplete coverage of parameter space pose significant barriers to progress.
TEMPOS obtained new Cosmic Origins Spectrograph (COS) FUV spectra of 12 very metal-poor O stars, building upon archival data to assemble a spectroscopic atlas of 29 homogeneously observed stars that efficiently samples a wide range of spectral types and luminosity classes. The main scientific objective is to measure the stellar and wind properties to serve as an empirical guide for massive-star astrophysics at very low metallicity. To enable this, TEMPOS has also obtained ground-based, moderate-resolution optical spectroscopy of all 29 stars with the DEIMOS and KCWI spectrographs on the Keck II Telescope. In a series of data releases, TEMPOS will provide consistently reduced and coadded FUV and optical spectra, as well as PSF photometry measured from archival HST imaging for each star.
The first data release includes reduced and co-added HST/COS spectra in the G130M + (G160M and/or G140L) gratings for all 29 O stars in TEMPOS. Coadds were produced using the coaddition algorithm from the ULLYSES HST Director's Discretionary Program (Roman-Duval et al. 2025). The TEMPOS HSLP files are structured consistently with those from ULLYSES to enable straightforward analysis of the combined ULLYSES and TEMPOS COS datasets.
Data Products
Data file naming convention:
hlsp_tempos_hst_cos_<galaxy-star-name>_<grating>_v1_cspec.fits
where:
- <galaxy-star-name> is the name of the host galaxy and star, for example: 'leoa-gws-k1' or 'ngc3109-mtk-1'
- <grating> is the COS grating used in the observation, for example: 'g130m', 'g160m', or 'g140l'
Data file types:
| _cspec.fits | reduced and coadded HST/COS spectra (one file per grating for each star) |
Data Access
MAST Portal and Astroquery
The TEMPOS 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 "tempos" 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 TEMPOS products
all_obs = Observations.query_criteria(provenance_name="tempos")
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)
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A web-based interface for cross-mission searches of data at MAST or the Virtual Observatory.
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Search for and download data products for this HLSP programmatically in Python.
Citations
Please remember to cite the appropriate paper(s) below and the DOI 10.17909/fcda-fn73 if you use these data in a published work.
Note: These HLSP data products are licensed for use under CC BY 4.0.




