SearcharxivSearch

arXiv · 2609.26938

The Simons Observatory: Commissioning of the Mid-Frequency Small Aperture Telescopes

Abstract

The Simons Observatory (SO) is a cosmic microwave background (CMB) survey experiment observing from an altitude of 5,200 m in the Atacama Desert in Chile. The SO Small Aperture Telescopes (SATs) will cover six spectral bands between 30 and 280 GHz primarily to search for evidence of primordial gravitational waves in the large angular scale $B$-modes of the CMB polarization. The first two Mid-Frequency (MF) SATs, operating in the 90 and 150 GHz frequency bands, began commissioning observations in late 2023, and we present the results of those observations here. Each MF SAT operates with approximately 9,400 biased transition-edge sensors (TES) at 1 mm of precipitable water vapor (PWV), representing a typical 80% yield. Planet observations confirm the telescope optics performance, calibrate the instrument response, and measure the end-to-end optical efficiency of the SATs. The realized instrument efficiencies are within the range expected based on instrument model predictions. In nominal observing conditions, the noise equivalent temperatures from both telescopes combined are $2.4~\mathrm{μK_{CMB}\sqrt{s}}$ at 90 GHz and $3.2~\mathrm{μK_{CMB}\sqrt{s}}$ at 150 GHz, substantially outperforming the baseline instantaneous sensitivity targets for the observatory.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kathleen Harrington, Remington Gerras, Nicholas Galitzki, Samuel Day-Weiss, Yoshinori Sueno, Thomas Alford, Michael J. Randall, Kyohei Yamada, Maximiliano Silva-Feaver, Kevin Crowley, Shunsuke Adachi, Alexandre E. Adler, Prakamya Agrawal, Simone Aiola, David Alonso, Kam Arnold, Susanna Azzoni, Andrew Bazarko, Sanah Bhimani, Simon Biquard, Bryce Bixler, Josh Borrow, Michael L. Brown, Erminia Calabrese, Yuji Chinone, Steve K. Choi, Nadia Dachlythra, Mark Devlin, Simon Dicker, Peter N. Dow, Shannon M. Duff, Jo Dunkley, Rolando Dunner, Daniel Dutcher, Hamza El Bouhargani, Josquin Errard, Allen Foster, Ken Ganga, John Groh, Yilun Guan, Jon E. Gudmundsson, Saianeesh Haridas, Masaya Hasegawa, Matthew Hasselfield, Shawn W. Henderson, Carlos Hervías-Caimapo, Adam D. Hincks, Renée Hložek, Johannes Hubmayr, Bradley R. Johnson, Yutaro Kasai, Brian Keating, Ben Keller, Theodore Kisner, Brian J. Koopman, Akito Kusaka, Adrian Lee, JB Lloyd, Anto Lonappan, Marius Lungu, Aashrita Mangu, Michael McCrackan, Jeff McMahon, Jenna Moore, Thomas W. Morris, Hironobu Nakata, Federico Nati, Laura Newburgh, David V. Nguyen, John Orlowski-Scherer, Lyman Page, Ioannis Paraskevakos, Tristan Pinsonneault-Marotte, Erik Rosenberg, Yuki Sakurai, Goureesankar Sathyanathan, Thomas P. Satterthwaite, Yudai Seino, Elle Shaw, Sara M. Simon, Suzanne T. Staggs, Junna Sugiyama, Junya Suzuki, Satoru Takakura, Osamu Tajima, Alex Thomas, Daniel B. Thomas, Tran Tsan, Eve Vavagiakis, Yuhan Wang, John Wilson. 2026-09-22. The Simons Observatory: Commissioning of the Mid-Frequency Small Aperture Telescopes. https://arxiv.org/abs/2609.26938

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

KEEP EXPLORING

Related papers

Denoising Interferometric Observations Using Visibility-Informed Neural Networks

The upcoming observations from the Square Kilometer Array Observatory will provide the astronomical community with a wealth of observations of important objects at long wavelengths. Full analysis of these outputs will necessitate specialized methods and software. Using synthetic observations of protoplanetary discs as an example, we present VIREO, a machine-learning-based visibility-informed method for denoising interferometric images. VIREO operates on image-plane observations, but it is informed by the interferometric measurement process through the UV-derived point spread function supplied as an additional input and used in the loss function. VIREO outperforms traditional cleaning methods and PSF-ignorant denoising models by producing data that is quantitatively cleaner and more conducive to analysis of the planets within the disc. Applying VIREO to archival ALMA data creates images with significantly less background noise, while maintaining, and in some cases enhancing, the substructure. By demonstrating the general utility of visibility-informed models, our results suggest that VIREO can be applied across interferometric observatories when trained on appropriate datasets.

astro-ph.IM

GREX-PLUS Science Book v2

GREX-PLUS (Galaxy Reionization EXplorer and PLanetary Universe Spectrometer) is a mission candidate for a JAXA strategic L-class mission to be launched in the 2030s. Its primary science goals are two-fold: galaxy formation and evolution, and planetary system formation and evolution. The GREX-PLUS spacecraft will carry a telescope with a 1 m primary mirror aperture cooled down to 50 K. The two science instruments will be onboard: a wide-field camera in the 2--8 $μ$m wavelength band and a high-resolution spectrometer with a wavelength resolution of 30,000 in the 10--18 $μ$m band. The GREX-PLUS wide-field camera aims to detect the first generation of galaxies at redshift $z>15$. The GREX-PLUS high-resolution spectrometer aims to identify the location of the water ``snowline'' in protoplanetary disks. Both instruments will provide unique datasets for a broad range of scientific topics, including galaxy mass assembly, the origin of supermassive blackholes, infrared background radiation, molecular spectroscopy in the interstellar medium, transit spectroscopy of exoplanet atmospheres, planetary atmospheres in the Solar System, and so on. This document is the second version of a collection of scientific themes that can be achieved with GREX-PLUS. Each section in Chapters~2 and 3 is based on presentations at several GREX-PLUS Science Workshops.

astro-ph.IM

Differentiable astrophysics at scale: solving and differentiating ODE ensembles on the GPU

Astronomers increasingly fit their models with gradient-based methods, such as Hamiltonian Monte Carlo, which need the derivatives of the model with respect to its parameters. In many analyses a prediction requires solving a small system of ordinary differential equations (ODEs) for thousands to millions of parameter sets, and this ensemble of integrations often sets the cost of the analysis. We introduce to the astronomical community GRADSOLVE, a JAX library that moves this computation to graphics processing units (GPUs): it integrates each member of the ensemble in its own GPU thread with its own step size and returns the derivatives with respect to the parameters in the same pass. We measure the speed-up it provides in three examples from different fields of astronomy, stellar orbits in the Galactic potential, the expansion history of a dark-energy cosmology and the spin precession of binary black holes, with every code held to the same accuracy requirement. For a million trajectories GRADSOLVE runs 8.5 to 1500 times faster than the serial CPU code of each example running on all 128 cores of a CPU, and several orders of magnitude faster than on one core. On the same GPU it is also 11 to 15 times faster than DIFFRAX, the state-of-the-art ODE library in JAX, in all three examples. With GRADSOLVE a million such integrations take seconds or less on one GPU, so gradient-based analyses that need ensembles of this size become routine. The code is publicly available at https://github.com/ECLIPSE-AI4Science/gradsolve.

astro-ph.IM