Search arXivSearch

arXiv · 2509.01727

PRIMA: PRIMAger, a far-infrared hyperspectral and polarimetric instrument

Abstract

The PRobe far-Infrared Mission for Astrophysics (PRIMA) is an infrared observatory for the next decade, currently in Phase A, with a 1.8m telescope actively cooled to 4.5K. On board, an infrared camera, PRIMAger, equipped with ultra-sensitive kinetic inductance detector (KID) arrays, will provide observers with coverage of mid-infrared to far-infrared wavelengths from 24 to 264 microns. PRIMAger will offer two imaging modes: the Hyperspectral mode will cover the 24-84 microns wavelength range with a spectral resolution R=8, while the Polarimetric mode will provide polarimetric imaging in 4 broad bands, from 80 to 264 microns. These observational capabilities have been tailored to answer fundamental astrophysical questions such as black hole and star-formation co-evolution in galaxies, the evolution of small dust grains over a wide range of redshifts, and the effects of interstellar magnetic fields in various environments, as well as to open a vast discovery space with versatile photometric and polarimetric capabilities. PRIMAger is being developed by an international collaboration bringing together French institutes (Laboratoire d'Astrophysique de Marseille and CEA) through the center National d'Etudes Spatiales (CNES, France), the Netherlands Institute for Space Research (SRON, Netherlands), and the Cardiff University (UK) in Europe, as well as the Jet Propulsion Laboratory (JPL) and Goddard Space Flight Center (GSFC) in the USA.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Laure Ciesla, Charles Darren Dowell, Marc Sauvage, Denis Burgarella, Jochem Baselmans, Matthieu Béthermin, Jeffrey T. Booth, Charles M. Bradford, Florent Canourgues, Ivan Charles, Anne Costille, Thomas Essinger-Hileman, Lorenza Ferrari, Johan Floriot, Marc Foote, Jason Glenn, Renaud Goullioud, Matt Griffin, Oliver Krause, Willem Jellema, Elizabeth Luthman, Laurent Martin, Margaret Meixner, Tony Pamplona, Klaus M. Pontoppidan, Alexandra Pope, Thomas Prouvé, Jennifer Rocca, Johannes Staguhn, Carole Tucker. 2025-09-01. PRIMA: PRIMAger, a far-infrared hyperspectral and polarimetric instrument. https://doi.org/10.1117/1.jatis.11.3.031625

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

The Simons Observatory: Development of a Pipeline to Detect Rapid Transients in Time-Ordered Data

We introduce a method for detecting astrophysical transients evolving on timescales of milliseconds to minutes using cosmic microwave background (CMB) survey telescopes. While previous transient searches in CMB data operate in map space, our pipeline directly processes the raw time-ordered data, enabling sensitivity to fast, dynamic signals. We integrate our detection approach into the Simons Observatory time-domain pipeline and assess the performance by injecting symmetric, stellar flare-like light curves into simulated observations. For events flaring with a timescale of 0.5 s, the pipeline detects $\gtrsim90$ % of events at flux densities of 800, 1150, 1650, and 4250\,mJy when measured in the 93, 145, 225, and 280 GHz bands respectively. At a fixed peak flux density, the pipeline more readily detects longer flares. The limiting flux density for 90 % completeness is four times lower for a $\ge5$ s flare than for a 0.5 s flare, while the flux density limits for $\gtrsim50$ % detection efficiency are comparable to the rms noise of the time-ordered data. We are able to determine the position of detected events in each observing band, with a positional uncertainty at the detection threshold comparable to the telescope resolution at that band. These results demonstrate the readiness of this pipeline for incorporation into upcoming Simons Observatory data analyses.

astro-ph.IM

Fitting Moving Objects in Up-The-Ramp Data with Applications to the Roman Space Telescope and JWST

A moving object breaks the fundamental property of constant per-pixel count rates in an astronomical image read out up-the-ramp. In this paper, we show how to fit a moving object's path across a detector as that detector is read out nondestructively. We write the full likelihood function for every pixel subject to a constant count rate plus a time-dependent count rate due to a moving source. Assuming the moving source to be point-like and assuming the effective point-spread function to be known, we are left with four parameters that enter the likelihood nonlinearly: two for position and two for velocity. All remaining parameters can be optimized using closed-form expressions. Our approach extracts maximal information on a moving source's position and speed and enables the source to be accurately removed from the image. We investigate the dependence of flux, position, and velocity precision on the target's speed and the readout pattern. We also find a small, positive bias on the recovered flux due to the need to fit for an uncertain position and speed. Our approach can be used for space-based images with minor Solar system bodies in the foreground, e.g.~from Roman and JWST, or for ground-based observations with satellites in the foreground. We demonstrate the promise of our method with a fit to an asteroid track observed serendipitously by the NIRISS instrument on JWST, comparing it to the performance of the JWST pipeline. Python code implementing our approach is available at https://github.com/t-brandt/moving_source. The total computational cost to fit the track of a moving object is $\sim$1 second on a 2023 Macbook Pro.

astro-ph.IM

Options for Compression of radio interferometry data: lossy compression of visibilities and lossless compression of uv-visibility grids for the MHONGOOSE survey

Next generation radio astronomy telescopes are challenging existing data reduction paradigms. With ever more antennas, larger bandwidths, and sometimes multiple primary beams, they often generate more observed data products than can readily be stored long-term. Thus, data storage becomes a major cost driver and processing constraint. In this paper, we test two methods of addressing this problem: grid-stacking, a two-stage lossless compression solution; and the lossy compression of the raw visibilities before traditional processing. To demonstrate these solutions we utilised a deep imaging pipeline based on software for the ASKAP telescope, ASKAPSoft, but applied to a strong source (NGC1566) from the deep MeerKAT HI spectral line project, MHONGOOSE. The grid-stacking solution reproduces the spectrum from traditional processing to within better than 0.7%, and also allows for the reconstruction of other weighting scales without significant computing costs. In comparison, image-stacking also reproduces the spectrum from the traditional processing, to within better than 3% but with worse image residuals in the cube. The lossy compression, even at a near ten-fold reduction in file size, reproduces the spectra almost perfectly (to better than ~0.01% in all cases). Thus both compression methods are promising solutions, and we discuss considerations for their application.

astro-ph.IM