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The Atacama Cosmology Telescope: Release of A databaSe of millimeTeR ObservatioNs of Asteroids Using acT (ASTRONAUT)

This paper introduces ASTRONAUT, a publicly accessible Amazon S3 database hosted on AWS that provides millimeter-wavelength flux measurements for 170 asteroids observed by the Atacama Cosmology Telescope between 2017 and 2021, accompanied by a Jupyter notebook for data analysis.

Original authors: Ricco C. Venterea, John Orlowski-Scherer, Nicholas Battaglia, Sigurd Naess, Steve K. Choi, Allen Foster, Joseph Golec, Bruce Patridge, Cristóbal Sifón, Edward J. Wollack

Published 2026-06-02

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CC BY 4.0

Original authors: Ricco C. Venterea, John Orlowski-Scherer, Nicholas Battaglia, Sigurd Naess, Steve K. Choi, Allen Foster, Joseph Golec, Bruce Patridge, Cristóbal Sifón, Edward J. Wollack

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the Atacama Cosmology Telescope (ACT) as a giant, high-powered security camera sitting in the Chilean desert. Its main job is to take pictures of the oldest light in the universe (the Cosmic Microwave Background) to help scientists understand how the universe began. But, just like a security camera that sweeps across a parking lot, it inevitably catches other things moving in the frame—specifically, asteroids.

This paper announces the release of a new digital library called ASTRONAUT (A databaSe of millimeTeR ObservatioNs of Asteroids Using acT). Think of this library as a massive, public "photo album" stored in the cloud (Amazon Web Services) that contains measurements of 170 different asteroids.

Here is the breakdown of what the team did, using simple analogies:

1. The "Accidental" Discovery

The ACT telescope wasn't originally built to hunt for asteroids. It was built to look at the faint glow of the Big Bang. However, because the telescope scans huge patches of the sky repeatedly, it accidentally took "snapshots" of many asteroids as they drifted through its view between 2017 and 2021.

Usually, looking at asteroids requires expensive, dedicated time on powerful telescopes. But because ACT was already looking at the sky for its main job, it collected this asteroid data for "free" as a side effect.

2. Seeing the "Skin" of the Asteroid

The telescope looks at these space rocks using millimeter waves (a type of light we can't see, but is similar to radio waves).

The Analogy: Imagine an asteroid is a baked potato. If you look at it with a regular camera (optical light), you see the shiny skin. If you look at it with millimeter waves, you are essentially feeling the warmth just beneath the skin.
Why it matters: This allows scientists to study the "regolith" (the dusty, rocky surface layer) of the asteroid. Different materials heat up and cool down differently, so by measuring this "warmth," scientists can guess what the asteroid is made of.

3. The Challenge: Finding a Needle in a Haystack

Asteroids are very faint at these wavelengths.

The Analogy: Trying to see an asteroid in millimeter light is like trying to spot a single firefly in a stadium full of bright floodlights. The "floodlights" are the noise in the data.
The Solution: The team didn't just look at one photo. They took thousands of "depth-1" maps (which are like single, quick snapshots taken as the sky drifts by) and stacked them on top of each other. By layering these images, the faint signal of the asteroid gets brighter, while the random noise cancels out. They only kept the data for asteroids that were bright enough to be clearly seen (a signal-to-noise ratio of 5 or higher).

4. The "Light Curve" Recipe

The paper explains how to turn these raw measurements into a "light curve."

The Analogy: Imagine you are tracking a runner. You don't just want to know where they are at one moment; you want to see a video of them running over time. A "light curve" is a graph that shows how bright an asteroid gets and fades as it spins and moves closer to or further from Earth.
The Normalization: Because asteroids change distance from the Sun and Earth, their brightness naturally changes. The team created a mathematical "recipe" (a normalization process) to adjust all the data as if every asteroid were standing at the exact same distance from the Sun and Earth. This makes it fair to compare them.

5. The Library (ASTRONAUT)

The main point of this paper is to hand the keys to this data over to the public.

The Bucket: The data is stored in an Amazon S3 bucket. Think of this as a giant, public digital warehouse.
The Tools: To help people use this warehouse, the authors provided a "Jupyter Notebook." This is like a pre-written instruction manual or a recipe book that anyone can download from GitHub. It shows users exactly how to:
1. Go to the warehouse.
2. Ask for the data on a specific asteroid (like Vesta or Ceres).
3. Download the numbers (flux, error bars, and time).
4. Plot a graph (light curve) to see how that asteroid behaves.

Summary

In short, the Atacama Cosmology Telescope took thousands of accidental photos of asteroids while studying the universe's history. The authors have cleaned up this data, adjusted it so it's easy to compare, and put it in a free, public online library. They also provided a step-by-step guide (a notebook) so that any scientist or student can download the data and start creating their own graphs to study the composition of these space rocks.

Technical Summary: The Atacama Cosmology Telescope: Release of A databaSe of millimeTeR ObservatioNs of Asteroids Using acT (ASTRONAUT)

Problem and Motivation
Studies of asteroid regolith composition at millimeter (mm) wavelengths offer unique insights into early planetary formation and subsurface properties, as these measurements probe the top layers of asteroid surfaces. However, mm-wave flux data for asteroids remains scarce compared to optical and infrared observations. Traditional mm-wave observations are resource-intensive, often requiring targeted searches with large facilities, and are limited by the faintness of asteroids at these wavelengths due to spectral slopes and beam dilution factors ( $10^3$ – $10^6$ times worse than optical). While cosmology observatories like the Atacama Cosmology Telescope (ACT) conduct repeated, wide-field surveys in the mm to sub-mm range, incidental observations of asteroids from these surveys have historically been underutilized for asteroid science due to a lack of accessible, processed data products.

Methodology
This paper presents the release of ASTRONAUT (A databaSe of millimeTeR ObservatioNs of Asteroids Using acT), a public database hosted on Amazon Web Services (AWS) via an Amazon Simple Storage Service (S3) bucket. The data derives from ACT observations conducted between 2017 and 2021 in three frequency bands centered near 90, 150, and 220 GHz (denoted f090, f150, and f220).

The data processing pipeline utilizes "depth-1" maps, which are shallowly exposed images (approx. 5-minute equivalent exposure) generated from ACT's standard scanning strategy. The methodology involves:

Source Extraction: Asteroid fluxes are measured from depth-1 maps using a matched-filter technique optimized for point sources to maximize signal-to-noise (S/N) and suppress atmospheric noise.
Astrometry: The JPL Horizons API is used to interpolate asteroid orbits and determine their precise locations on the depth-1 maps based on ACT observation times.
Flux Normalization: Raw flux measurements are normalized to a standard geometry (1 AU from Earth and Sun, and a reference phase angle) using a weighting scheme ( $W_i$ ) based on the Rayleigh-Jeans limit of the Standard Thermal Model. This accounts for varying Earth/asteroid and Sun/asteroid distances and phase angles across observations.
Calibration: Data are calibrated using flux maps of Uranus compared to dedicated scans, with systematic uncertainties (e.g., beam size) incorporated into the final error bars.

Key Contributions
The primary contribution of this work is the public release of a curated dataset containing 170 asteroids that achieved a signal-to-noise ratio of $\ge 5$ in at least one frequency band after stacking observations. The database provides:

Normalized Flux Values ( $F_0$ ): Flux density measurements corrected for geometric variations.
Associated Error Bars: Including statistical noise and systematic uncertainties.
Weighting Factors ( $W_i$ ): Geometric parameters allowing users to reconstruct fluxes for specific observation epochs.
Observation Times: Recorded in Unix time, corresponding to the asteroid's position during the array crossing (approx. 4 minutes).

To facilitate access, the authors provide a Python-based interface and a Jupyter Notebook hosted on a GitHub repository. These tools allow users to query the S3 bucket for specific asteroids, arrays, and frequencies, retrieve FITS files, and generate light curves. The dataset is also mirrored on the Legacy Archive for Microwave Background Data Analysis (LAMBDA) in tar file format.

Results
The paper validates the dataset by comparing ACT flux measurements for five specific asteroids—(1) Ceres, (4) Vesta, (7) Iris, (6) Hebe, and (18) Melpomene—against historical measurements from Redman et al. (1998). The comparisons, performed by scaling ACT data to the Redman observation epochs using the provided weighting factors, show consistency within uncertainties. The paper demonstrates the utility of the database by generating example light curves, such as for asteroid (705) Erminia, illustrating how the data can be used to track flux variations over time.

Significance and Claims
The authors position ASTRONAUT as a resource to increase access to incidental asteroid observations from cosmology surveys, which offer a cost-effective method for collecting mm-wave data compared to targeted searches. The paper modestly claims that this database enables the creation of light curves and facilitates the study of asteroid regolith properties. The authors note that while the term "light curve" is non-standard in the asteroid community (where flux density as a function of epoch is the standard definition), it is used here for clarity to a broader audience.

The paper concludes by identifying future applications for this data, specifically the potential to create multi-observatory light curves (combining ACT, SPT, and ALMA data) and to calculate phase curves to better understand mm-wave flux variations as a function of asteroid rotation. The work emphasizes that the data is freely available to encourage further scientific exploitation of these incidental observations.