🔭 astrophysics

TSSC comet-centered data products from TESS 3I/ATLAS observations

The TESS Science Support Center has released two publicly available high-level science products—background-corrected comet-centered image time series and aperture light curves—derived from TESS observations of the interstellar object 3I/ATLAS in January 2026 to facilitate the study of its post-perihelion activity.

Original authors: Jorge Martinez-Palomera, Amy Tuson, TESS Science Support Center

Published 2026-02-16

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CC BY 4.0

Original authors: Jorge Martinez-Palomera, Amy Tuson, TESS Science Support Center

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 universe as a giant, dark ocean, and for the first time in history, we've spotted a strange, icy visitor from another star system sailing through our neighborhood. This visitor is 3I/ATLAS, the third interstellar comet ever discovered. It's a cosmic wanderer, moving so fast and on such a wild path that it doesn't belong to our Sun's family.

To get a better look at this cosmic tourist, NASA's TESS satellite (a space telescope usually hunting for planets around other stars) decided to take a special vacation photo session. Instead of just snapping a quick picture, TESS stared at the comet for a week straight in January 2026, taking high-definition snapshots every few minutes.

However, looking at a moving comet from space is like trying to take a clear photo of a hummingbird while standing on a bumpy, shaking boat, with other birds and bright lights flashing in the background. The raw data TESS sent back was messy. It was full of "noise"—scattered starlight, background stars, and the satellite's own quirks.

Here is what this paper is really about:

1. The "Digital Darkroom" (Cleaning the Data)

The authors, Jorge and Amy, acted like expert photo editors. They took the raw, messy images and ran them through a special software program (think of it as a super-powered Photoshop for space).

The Problem: The comet is faint and has a long, wispy tail. In the raw images, it was hard to tell where the comet ended and the background stars began. It was like trying to see a faint ghost in a room full of bright lamps.
The Solution: They built a mathematical model to "subtract" the background. Imagine you are trying to hear a whisper in a noisy room. They figured out exactly how loud the "noise" (the background stars and scattered light) was at every single moment and subtracted it, leaving only the whisper (the comet).
The Result: They created a clean, comet-centered movie. Now, instead of the comet drifting across the screen, the camera is locked onto the comet, making it look like it's sitting still while the universe spins around it.

2. The "Flashlight" Test (Measuring Brightness)

Once the images were clean, they needed to measure how bright the comet was. But a comet isn't just a single dot; it has a bright, solid center (the nucleus) and a giant, fuzzy cloud of gas and dust (the tail).

The Analogy: Imagine shining a flashlight on a foggy night. You have the bright beam in the center, and then a hazy glow spreading out.
The Method: The team created three different "flashlight buckets" (called apertures) to catch the light:
1. Small Bucket: Catches just the super-bright core.
2. Medium Bucket: Catches the core and a bit of the immediate fuzz.
3. Huge Bucket: Catches the core and the entire, long tail.
By measuring how much light fell into these buckets over time, they created a light curve. This is like a graph showing the comet's heartbeat, revealing how active it is as it gets closer to the Sun.

3. Why This Matters

This paper isn't just about pretty pictures; it's about making data usable for everyone.

Before this, scientists would have to do all this messy cleaning work themselves, which is like trying to build a house without a foundation.
Now, the authors have packaged all the cleaned images and the brightness graphs into a "High-Level Science Product." Think of this as a pre-fabricated house ready for other scientists to move into and start their own research immediately.
These data are now free for anyone to download from NASA's archives.

The Bottom Line

This paper is a user manual and a gift to the scientific community. It says: "We found this amazing interstellar comet, we cleaned up the telescope's messy photos, we measured its brightness in three different ways, and we packaged it all up so you can study it without having to do the hard math first."

Thanks to this work, scientists around the world can now focus on the big questions: What is this comet made of? How does it behave when it gets close to the Sun? And what does it tell us about the other star systems it came from?

1. Problem Statement

The interstellar comet 3I/ATLAS (discovered July 1, 2025) represents the third known interstellar object to traverse the Solar System. Characterizing such objects is critical for understanding the population of interstellar comets and their unique physical behaviors. While ground-based and space-based observatories have monitored 3I/ATLAS, standard TESS (Transiting Exoplanet Survey Satellite) data processing pipelines are optimized for stationary point sources (stars) or transiting exoplanets. They are not inherently designed to handle:

Moving targets: 3I/ATLAS moves significantly across the CCD during observations.
Extended morphology: Unlike a point source, 3I/ATLAS possesses a prominent nucleus and an extended tail, which complicates standard aperture photometry and background subtraction.
Data Gaps: The specific observation window (Sector 1751) contained data gaps due to contingency modes and downlinks, requiring robust handling of time-series data.

The challenge was to create high-precision, high-cadence photometric data products specifically tailored for this moving, extended object to facilitate scientific analysis of its activity post-perihelion.

2. Methodology

The authors, from the University of Maryland, Baltimore County, and NASA Goddard Space Flight Center, utilized the TESS Science Support Center (TSSC) framework and the tess-asteroids Python package (v1.5.0) to process Full Frame Images (FFIs). The processing pipeline involved the following key steps:

Data Acquisition:
- Observation Window: January 15–22, 2026 (TESS Sector 1751).
- Instrument: TESS Camera 2, CCD 3.
- Cadence: 200s Full Frame Images (FFIs); Target Pixel Files (TPFs) at 20s and 120s cadences were also collected.
- Total Frames: 1,835 frames processed.
Image Processing Pipeline:
1. Ephemeris & Coordinate Conversion: JPL Horizons provided the ephemeris, converted to pixel coordinates using tesswcs.
2. Cutout Generation: A 111 × 71 pixel cutout was extracted for every frame, centered on the predicted comet position. This size was chosen to fully enclose the extended tail.
3. Time Correction: Barycentric Dynamical Time (TDB) corrections were applied using lkspacecraft and SPICE kernels.
4. Advanced Background Correction (Iterative): A two-component model was subtracted from the flux:
  - Scattered Light: Modeled using a space-dependent linear model with PCA components to interpolate flux over stars. Pixels containing the comet and background stars were masked via $\sigma$ -clipping and ephemeris data.
  - Background Stars: Modeled using a time-dependent linear model over a 1-day window to account for stellar variability.
5. Quality Masking: Pixels with anomalies (saturation, strap columns, poor background constraints) were flagged.
Photometric Extraction:
Three distinct apertures were defined to capture different morphological components:
- Core Small: Pixels containing $\ge$ 1% of the Point Response Function (PRF) flux.
- Core Large: Pixels containing $\ge$ 0.1% of the PRF flux.
- Total Aperture: Pixels with flux $\ge$ $1e^{-s^{-1}}$ in the median-stacked image, capturing the nucleus and the full tail.

3. Key Contributions

The primary contribution of this work is the release of two High-Level Science Products (HLSPs) hosted at the Mikulski Archive for Space Telescopes (MAST) and Zenodo:

Comet-Centered Image Time Series: A background-corrected sequence of image cutouts, removing scattered light and stellar contamination.
Aperture Light Curves: Three distinct light curves (Core Small, Core Large, Total) extracted from the corrected images.

Additionally, the authors released:

GitHub Repository: Containing Jupyter notebooks that document the data extraction, processing logic, and tutorials for using the products.
Metrics: Quality metrics including the fraction of good quality pixels, background light curves, and model statistics.

4. Results

Imaging: The median-stacked image (Figure 1, left) clearly reveals 3I/ATLAS with a prominent core and an extended tail, confirming the success of the cutout size selection.
Photometry:
- The light curves (Figure 1, right) show the comet's brightness evolution over the 7-day observation window.
- Median Magnitudes (TESS band):
  - Core Small: $12.03 \pm 0.01$
  - Core Large: $11.61 \pm 0.01$
  - Total (Nucleus + Tail): $11.02 \pm 0.01$
Data Quality: The pipeline successfully identified and flagged specific events, such as the comet crossing background stars (grey markers in Fig 1) and edge effects caused by the tail interacting with the background model (red markers).

5. Significance

Scientific Utility: These data products provide the TESS and Solar System communities with the first high-precision, near-continuous photometry of an interstellar comet during its post-perihelion phase. This allows for detailed studies of outgassing, dust production, and tail dynamics that are difficult to achieve with ground-based telescopes due to atmospheric interference and day/night cycles.
Methodological Advancement: The work demonstrates a robust pipeline for processing TESS data for moving, extended objects. The iterative background correction and specific aperture definitions serve as a template for future observations of asteroids and comets by TESS and similar missions.
Accessibility: By standardizing these products in FITS format and providing open-source code, the TSSC ensures that researchers can immediately begin analyzing the unique behavior of 3I/ATLAS without needing to reprocess raw FFIs.

Note on Timeline: The paper is a "Draft version" dated February 16, 2026, describing observations that occurred in January 2026. This implies the document is a prospective or near-future publication within the context of the provided text.