The PLATO field selection process III. Selection of the Prime Sample for the LOPS2 field

This paper presents the quantitative metrics, selection thresholds, and astrophysical properties of the Prime Sample, a high-quality subset of 15,000 stars from the PLATO Input Catalog chosen for the LOPS2 field to facilitate the discovery of Earth-like planets in habitable zones.

The Gist

Imagine the PLATO mission as a massive, high-tech cosmic fishing expedition. Its goal isn't just to catch any fish; it wants to find the "Holy Grail" of the ocean: an Earth-like planet orbiting a star just like our Sun, in a zone where life could exist.

To do this, PLATO is a satellite launching in 2027 that will stare at a specific patch of the southern sky (called LOPS2) for at least two years, watching for tiny dips in starlight that signal a planet passing in front of a star.

However, PLATO will see thousands of potential candidates. The problem is that we can't check all of them. Confirming a planet requires powerful ground-based telescopes to measure the star's "wobble" (using a technique called Radial Velocity). We only have so much telescope time and money.

This paper is essentially the rulebook for creating the "VIP List" (called the Prime Sample). It explains how the scientists decided which 15,000 stars out of a catalog of 217,000 get the "Golden Ticket" to be the primary targets for this mission.

Here is how they made the cut, explained with some everyday analogies:

1. The Two "Scorecards" (The Metrics)

The scientists didn't just pick stars randomly. They invented two scoring systems (metrics) to rank every star, kind of like a video game character creator where you want the perfect stats.

• Metric M (The "Detectability" Score):

  • The Analogy: Imagine trying to hear a whisper in a noisy room.
  • The Logic: This score asks: "How easy is it for PLATO to see the planet?"
  • The Winners: Small, cool stars (like K-dwarfs) get high scores. Why? Because a small star is like a small stage; if a planet walks across it, it blocks a huge chunk of the light (a loud whisper). Big, bright stars are like a massive stage; a small planet blocks very little light (a quiet whisper). Also, brighter stars are easier to see.
  • The Result: The best targets are small, cool, and bright stars.

• Metric R (The "Follow-up" Score):

  • The Analogy: Imagine trying to weigh a feather on a bathroom scale.
  • The Logic: This score asks: "How easy is it for us on Earth to confirm the planet?"
  • The Logic: To confirm a planet, we need to measure the star's wobble. If the star is too dim, our telescopes can't get a good enough signal. If the star is too big or spinning too fast, it's hard to measure the wobble.
  • The Result: Again, small, cool, and bright stars get the highest scores.

2. The Selection Process (The "Cut")

The scientists took their list of 217,000 stars and ran them through a filter based on these two scores.

• The "No-Go" Zones: They automatically threw out giant, evolved stars (like Red Giants). Think of these as "too messy" to study because they spin fast and pulse, making it impossible to get a clean reading. They also threw out stars that were too faint, because even if we saw a planet, we wouldn't have the telescope time to confirm it.
• The "VIP" Exceptions: They made special rules to include:
  • The absolute brightest stars (even if they aren't perfect for the math), because they are just too valuable to miss.
  • Some very bright "Red Dwarf" stars (M-dwarfs), because new infrared telescopes are getting really good at studying them.

The Final Cut: They tweaked the "passing grade" on the second score (Metric R) until exactly 15,000 stars remained. This is their "Prime Sample."

3. What Does the "Prime Sample" Look Like?

If you were to look at this list of 15,000 stars, you would find:

• The Sweet Spot: Most are "Goldilocks" stars—not too hot (like F-stars), not too cool (like M-stars), but mostly G and K stars (very similar to our Sun).
• Distance: They are relatively close neighbors, mostly within 200 light-years.
• The "Bright Tail": About 7,000 of them are bright enough (magnitude < 11) that we can do the most precise measurements on them. These are the "Super VIPs."

4. Why Does This Matter?

• No Double Booking: Once this list is made public, no one else (no other astronomers) can propose to use PLATO to look at these specific 15,000 stars. They are reserved exclusively for the mission's main goal: finding Earth twins.
• The Promise: The European Space Agency promises that for these 15,000 stars, they won't just find a candidate; they will do the hard work to confirm the planets and measure their mass and size.
• The Future: This list will be released before the satellite even launches, so the world can start planning how to help confirm these discoveries once the data starts coming in.

Summary

Think of the PLATO mission as a massive search party. This paper is the map they drew to decide exactly which 15,000 houses to knock on. They didn't knock on every door in the neighborhood; they used a smart algorithm to find the houses most likely to have the "treasure" (an Earth-like planet) and where the "lock" (confirmation) is easiest to pick.

The result is a curated, high-quality list of stars that gives humanity the best possible chance of answering the question: "Are we alone?"

Technical Summary

1. Problem Statement

The PLATO (PLanetary Transits and Oscillations of stars) mission, scheduled for launch in early 2027, aims to discover Earth-like planets in the habitable zones (HZ) of nearby solar-type stars. While the mission will monitor a vast catalog of stars (the PLATO Input Catalog, or PIC), the Ground-based Observing Program (GOP) has limited resources to perform the necessary follow-up observations (specifically high-precision Radial Velocity measurements) to confirm candidates and measure their masses.

The core challenge is to define a Prime Sample (PS)—a subset of approximately 15,000 stars within the first Long-duration Observation Phase field (LOPS2)—that maximizes the scientific yield. This sample must balance two competing requirements:

1. Photometric Detectability: The stars must be suitable for PLATO to detect transits of Earth-sized planets in the HZ.
2. Follow-up Feasibility: The stars must be bright and stable enough for ground-based spectrographs to confirm the planets via Radial Velocity (RV).

The selection process must be objective, reproducible, and capable of ranking targets to handle operational constraints (e.g., when two targets cannot be observed simultaneously).

2. Methodology

The authors developed a quantitative selection framework based on two merit functions (metrics) derived from stellar parameters available in the PIC (specifically the LOPS2PIC2.2_t catalog).

A. The Photometric Detection Metric ($M$)

This metric estimates the Signal-to-Noise ratio (S/N) for detecting an Earth-analog transit in the habitable zone.

• Formula: $M \propto R_{\star}^{-2} T_{eff}^{-1} 10^{-0.2(m_{\star} - m_0)}$
• Derivation: It scales the transit depth ($\delta \approx (R_p/R_{\star})^2$) by the number of transits and duration, normalized against the instrument's noise-to-signal ratio (NSR).
• Normalization: Set such that $M=1$ corresponds to the detection threshold for an Earth-twin around a solar twin with an NSR of 80 ppm.
• Dominant Factor: The metric is heavily dependent on stellar radius ($R_{\star}$); smaller stars yield higher values.

B. The Follow-up Metric ($R$)

This metric estimates the S/N achievable for ground-based RV follow-up of an Earth-mass planet in the HZ.

• Formula: $R \propto M_{\star}^{-1/2} T_{eff}^{-1} R_{\star}^{-1/2} 10^{-0.2(m_{\star} - m_0)}$
• Derivation: Based on the Keplerian RV semi-amplitude ($K$) and photon noise limitations of optical spectrographs.
• Nature: Unlike $M$, $R$ is a relative metric. It is not an absolute detection threshold but a ranking tool to prioritize targets based on the available GOP resources.
• Normalization: Calibrated such that a solar twin at $V \approx 11$ has $R=1$.

C. Selection Criteria

The final Prime Sample is selected using a logical expression combining these metrics with hard constraints and specific exceptions:

1. Hard Constraints:
   • $R_{\star} < 1.5 R_{\odot}$ (Excludes evolved giants with rapid rotation/pulsations).
   • $V < 14$ (Excludes faint stars where RV follow-up is prohibitively expensive).
   • $M > 1$ (Ensures photometric detectability).
2. Exceptions (Forced Inclusion):
   • P2 Sample: All stars with $V < 8.5$ (868 stars) are included regardless of other metrics, as they are critical for asteroseismology and high-precision RVs.
   • P4 Sample: M-dwarfs with $H < 9$ (2MASS) are included to leverage Near-Infrared (NIR) spectrographs (e.g., NIRPS).
3. Threshold Tuning: The threshold for $R$ is treated as a free parameter. It is tuned to exactly 0.73861 to ensure the final count of targets within the nominal LOPS2 footprint is 15,000.

3. Key Contributions

• Generalizable Metrics: The paper introduces a robust, general method ($M$ and $R$) for ranking any list of stars for transit surveys, moving away from simple fixed thresholds to continuous merit functions.
• Quantitative Selection Logic: The authors provide the exact mathematical formulation (Eq. 23) used to extract the 15,000 targets, ensuring reproducibility.
• Handling of Edge Cases: The methodology explicitly accounts for:
  • Bright stars ($V < 8.5$) forced into the sample for asteroseismology.
  • M-dwarfs included via NIR capabilities.
  • Safety margins around the field of view (FOV) to account for pointing errors.
• Integration with Mission Planning: The $M$ metric is adopted as the basis for the tPICScientificRanking column in the official catalog, used by the Target Programming Tool (TPT) to schedule observations.

4. Results

The selection process applied to the 217,741 stars in the tPIC resulted in the following characteristics for the Prime Sample (PS):

• Sample Size: 17,101 stars total (including a safety margin), with 15,000 falling within the nominal LOPS2 footprint.
• Stellar Composition:
  • Spectral Types: Dominated by late F (18%), G (38%), and K (37%) dwarfs. M-dwarfs constitute 8%, and subgiants 2%.
  • Brightness: ~40% of the sample (7,000 stars) are brighter than $V=11$, making them ideal for high-precision RVs and asteroseismology.
  • Distance: Median distance is 137 pc. No stars are further than 300 pc.
• Planetary Potential:
  • The sample includes 184 known planet hosts (84 confirmed, 30 transiting confirmed), including high-multiplicity systems like TOI-700 and HD 23472.
  • The calculated Habitable Zone periods ($P_{HZ}$) and radii ($a_{HZ}$) are centered slightly below Earth-Sun values, ensuring that $\ge 3$ transits can be detected within the nominal 2-year mission duration.
• Observability: While the field is in the Southern sky, ~21% of the PS stars are north of declination $-35^{\circ}$, allowing follow-up from mid-latitude Northern observatories (e.g., Mauna Kea, La Palma).

5. Significance

• Mission Readiness: This paper defines the "Goldilocks" target list that will be released to the community 9 months before launch. It sets the stage for the first Guest Observer (GO) call, clarifying that PS targets are reserved for the core mission and cannot be proposed by external GOs.
• Scientific Yield Optimization: By prioritizing stars based on the combined probability of detection and confirmation, the PS maximizes the likelihood of finding and characterizing true Earth analogs, a primary goal of the ESA PLATO mission.
• Data Release Strategy: The paper clarifies the data release policy: PS data will be held for proprietary analysis until scientific validation is complete (max 1 year after L0/L1 release), ensuring the consortium can deliver fully characterized planetary systems.
• Preparatory Observations: The selection enables immediate preparatory work, such as the 4MOST high-resolution spectroscopic survey, which will obtain chemical abundances and activity indicators for the PS stars before PLATO launch.

In summary, this paper provides the rigorous statistical and astrophysical foundation for the PLATO mission's most critical target list, ensuring the mission is optimized to achieve its historic goal of finding Earth-like planets around Sun-like stars.