The PLATO Input Catalogue of targets (tPIC) for the first Long Pointing Field

This paper presents the first public release of the PLATO Input Catalogue (tPIC2.2), a comprehensive list of 217,741 stars selected from Gaia DR3 data and interstellar dust maps to serve as targets for the mission's first Long Pointing Field at South, fulfilling all core science requirements for detecting terrestrial planets.

The Gist

Imagine the European Space Agency (ESA) is about to launch a massive, high-tech "space camera" called PLATO. Its mission is to take a long, steady look at the stars to find new worlds—specifically, Earth-like planets orbiting in the "Goldilocks zone" (not too hot, not too cold) where life could exist.

However, there's a catch. The spacecraft is like a smartphone with a very slow internet connection. It can't send back full, high-definition photos of the entire sky every second. If it tried, the data would clog the connection, and the mission would fail.

The Solution: A "Wanted Poster" List
To solve this, the scientists had to create a pre-approved "Wanted Poster" list before the mission even launched. They had to pick exactly which stars to watch, down to the pixel, so the spacecraft only sends back data for those specific targets. This list is called the tPIC (PLATO Input Catalogue).

This paper is the official announcement of the first version of that list, specifically for the first major "long-term staring" mission (called LOPS2).

Here is a breakdown of how they built this list, using some everyday analogies:

1. The Target List: Who are we looking for?

The scientists didn't just pick random stars. They needed specific "types" of stars to maximize their chances of finding Earth-like planets. Think of it like a casting call for a movie:

• The "Main Stars" (P1, P2, P5): They wanted stars similar to our Sun (yellow, orange, or slightly cooler). These are the "A-list actors." They need to be bright enough to see clearly but not so bright that they blind the camera.
• The "Supporting Cast" (P4): They also wanted a huge number of M-dwarfs (small, cool, red stars). These are the "character actors." They are smaller and dimmer, but they are very common, and finding planets around them is easier because the planets block a bigger chunk of the star's light.
• The "Guest Stars": They also included a list of stars that we already know have planets. This is like inviting the famous actors who have already won awards to the set, just to make sure we can test our equipment on them.

The Result: The final list contains 217,741 stars. It's a massive roll call, carefully curated to fit the camera's specific needs.

2. The Selection Process: The "Filter"

How did they pick these stars from the billions in the sky?

• The Map: They used the Gaia satellite, which is like a cosmic GPS that has mapped the positions and brightness of billions of stars.
• The Filter: They applied a digital "sieve." They asked: "Is this star the right size? Is it the right temperature? Is it too far away? Is it too dim?"
• The Crowd Control: Imagine standing in a crowded room. If you try to listen to one person, you might hear their neighbor talking too. In space, stars can be so close together that their light blends. The scientists used 3D maps of the dust and gas in space (interstellar medium) to figure out which stars were actually distinct and which were just "blended" together in the camera's view. They filtered out the ones that would cause a "traffic jam" of light.

3. The "Cosmic Makeup" (Extinction)

Space isn't empty; it's filled with dust and gas that acts like a dirty window or a foggy lens. This dust dims the stars and makes them look redder than they really are.

• The scientists built a 3D map of this cosmic dust.
• For every star on their list, they calculated exactly how much "makeup" (dust) was covering it. They then "cleaned" the star's image mathematically to reveal its true brightness and color. This is crucial because if you don't know how bright a star really is, you can't calculate the size of the planet orbiting it.

4. The "Resume" for Every Star

Once they picked the stars, they didn't just write down their names. They built a detailed resume for each one:

• Temperature: How hot is the star?
• Size: How big is it compared to our Sun?
• Mass: How heavy is it?
• Distance: How far away is it?

They used complex math to estimate these numbers just by looking at the star's light and position. This is vital because the size of the planet depends entirely on the size of the star. If you think a star is the size of a beach ball but it's actually the size of a beach, your planet calculation will be wrong.

5. The "Noise" Check

The scientists also calculated the "noise" for each star. Imagine trying to hear a whisper in a noisy room.

• Some stars are in crowded areas (noisy room).
• Some are in quiet areas (quiet room).
• They ranked the stars based on how "quiet" the background noise is. The quieter the star, the easier it is to hear the tiny "whisper" of a planet passing in front of it.

Why Does This Matter?

This paper is the blueprint for the mission. Without this list, the PLATO telescope would be flying blind, wasting its limited data connection on the wrong stars.

By releasing this list (the tPIC), the scientists are saying: "Here is the exact list of stars we will watch. We have checked their resumes, cleaned their images, and ranked them by how likely they are to host an Earth-like planet. Now, the world can start preparing to analyze the data when the mission launches."

In a nutshell: This paper is the ultimate "Guest List" for the most important party in the galaxy, ensuring that the PLATO mission only invites the stars that have the best chance of hosting a new home for life.

Technical Summary

1. Problem Statement

The ESA PLAnetary Transits and Oscillations of stars (PLATO) mission aims to detect and characterize terrestrial exoplanets in the habitable zones of bright solar-type stars. A critical operational constraint is the spacecraft's telemetry rate, which prevents the downlink of full-frame CCD images at the cadence required for planet detection. Consequently, a pre-selection of targets is mandatory before launch.

The mission requires a specific set of stellar targets to be observed during its Long-duration Observation Phase (LOP) to maximize the detection of Earth-analogs and study stellar oscillations (asteroseismology). The challenge lies in constructing a homogeneous, high-precision catalog of targets that:

• Meets strict spectral type and luminosity class requirements (FGK dwarfs/subgiants and M dwarfs).
• Adheres to magnitude limits to ensure the required photometric precision (noise levels < 50 ppm in 1 hour).
• Accounts for interstellar extinction and blending effects in crowded fields.
• Provides accurate fundamental stellar parameters (radius, mass, effective temperature) essential for deriving planet radii and habitability.

2. Methodology

The authors constructed the tPIC2.2 (PLATO Input Catalogue for targets), specifically for the first Long Pointing Field in the South (LOPS2). The methodology involved several rigorous steps:

• Data Sources: The primary data source is Gaia Data Release 3 (DR3), supplemented by Hipparcos and Tycho-2 data for brighter stars where Gaia data might be saturated or unavailable. Interstellar extinction was modeled using the 3D dust maps of Lallement et al. (2022) and Vergely et al. (2022).
• Target Selection Criteria: The selection was based on four primary stellar samples defined by the ESA Science Requirements Document (SciRD):
  • P1 & P2: FGK dwarfs and subgiants (F5–K7) with $V \le 11$ and $V \le 8.5$ respectively, requiring high photometric precision.
  • P4: M dwarfs ($V \le 16$).
  • P5: A large sample of FGK dwarfs/subgiants ($V \le 13$) for statistical studies.
  • Selection boundaries in the Color-Magnitude Diagram (CMD) were defined using linear models derived from TRILEGAL simulations and Gaia DR3 data, optimizing the separation between target stars and contaminants.
• Photometric Corrections & Calibration:
  • Systematic corrections from Gaia DR3 (e.g., saturation, color-dependent terms) were applied.
  • Visible Magnitude ($V$): Derived via polynomial calibration of Gaia $(G_{BP} - G_{RP})$ colors to Johnson $V$ using synthetic stellar spectra (MARCS, BT-Settl).
  • PLATO Magnitude ($P$): Derived by integrating synthetic spectra over the PLATO response functions (Appendix B) and interpolating relations between $(P-G)$ and $(G_{BP}-G_{RP})$.
• Stellar Parameter Determination:
  • Extinction: Iterative calculation of monochromatic extinction ($A_{550}$) converted to specific bands ($A_G, A_V, A_P$) based on stellar temperature.
  • Effective Temperature ($T_{eff}$): Derived from intrinsic colors using polynomial relations calibrated against high-quality samples (Casagrande et al. 2010; Mann et al. 2015).
  • Radius & Mass: Calculated using Stefan-Boltzmann law (for FGK) and empirical mass-luminosity relations (for M dwarfs), utilizing bolometric corrections and Gaia parallaxes.
  • Uncertainties: Estimated via Monte Carlo simulations perturbing photometry, distances, and reddening.
• Noise Estimation: The Noise-to-Signal Ratio (NSR) was provided by the PLATO Performance Team, accounting for random and systematic noise at the Beginning Of Life (BOL) for the specific field geometry.
• Exoplanet Hosts: A dedicated list of known confirmed and candidate planet hosts within the LOPS2 field was compiled from Exo-MerCat, the NASA Exoplanet Archive, and the Open Exoplanet Catalog.

3. Key Contributions

• First Public Release (tPIC2.2): The paper presents the first public release of the target catalog for the LOPS2 field, containing 217,741 stars.
• Homogeneous Parameter Set: Unlike previous catalogs that often rely on heterogeneous literature values, this work provides a homogeneous derivation of fundamental parameters ($T_{eff}$, Radius, Mass) for the vast majority of targets using a unified pipeline based on Gaia DR3 and 3D extinction maps.
• Comprehensive Flagging System: The catalog includes a robust set of bitmask flags to identify:
  • Sample membership (P1, P2, P4, P5).
  • Non-single stars (binaries, eclipsing, astrometric).
  • Data quality issues (Gaia astrometric excess, blending).
  • Planet host status (discovery method: transit, RV, imaging, etc.).
• Scientific Ranking: A metric ($M$) is introduced to rank targets based on the expected signal-to-noise ratio for transit detection, normalized by stellar properties.
• Integration of Planet Hosts: The catalog explicitly includes 789 known planet host stars (confirmed or candidates) within the field, ensuring they are prioritized for follow-up.

4. Results

• Catalog Statistics:
  • Total Targets: 217,741 stars.
  • FGK Dwarfs/Subgiants (P1, P2, P5): 202,315 stars.
  • M Dwarfs (P4): 15,037 stars.
  • Known Planet Hosts: 789 stars.
• Distance Regimes: The median distance is 512 pc for FGK stars and 133 pc for M dwarfs, reflecting the different magnitude limits and intrinsic brightness of these populations.
• Sample Compliance:
  • P1: 12,900 targets (Goal: $\ge$ 15,000 cumulative over all fields; this is for one field).
  • P2: 868 targets (Goal: $\ge$ 1,000).
  • P4: 15,037 targets (Goal: $\ge$ 5,000).
  • P5: 189,415 targets (Goal: $\ge$ 245,000).
  • Note: The paper notes that while the counts for a single field (LOPS2) do not meet the cumulative mission goals, the catalog is designed to be part of a larger set of fields, and the P5 sample is disjoint from P1/P2 to maximize coverage.
• Comparisons:
  • vs. asPIC1.1: Stellar parameters and extinctions are compatible. tPIC shows slightly lower extinction in low-reddening regions and higher in high-reddening regions, likely due to improved 3D map resolution.
  • vs. TICv8.2: Parameters are generally compatible, though TIC tends to list higher extinction and $T_{eff}$ for hot stars ($>6500$ K), which in tPIC are often part of the planet-host sample taken from external catalogs.

5. Significance

• Mission Readiness: The tPIC is the operational database that will drive the PLATO mission's core science. It ensures that the telescope points at the optimal stars to achieve the mission's primary goal: finding Earth-analogs.
• Precision Exoplanet Science: By providing homogeneous and accurate stellar parameters (especially radius), the catalog directly reduces the uncertainty in derived planet radii, a critical factor in determining if a planet is terrestrial and potentially habitable.
• Asteroseismology: The selection of bright, oscillating FGK stars (P1/P2) enables detailed studies of stellar interiors and ages, which are crucial for characterizing the planetary systems.
• Community Resource: The public release allows the broader astronomical community to plan ground-based spectroscopic follow-up and other observations, maximizing the scientific return of the PLATO mission.
• Future Updates: The catalog is designed to be dynamic, with updates scheduled every three months (spacecraft rotation) to include newly discovered exoplanet hosts.

In conclusion, the tPIC2.2 represents a critical milestone in the PLATO mission, successfully translating complex mission requirements into a scientifically robust, data-rich catalog ready for the first long-duration observation phase.