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PLAnetary Transits and Oscillations of stars is an ESA M-class satellite planned for launch by the end of 2026 and dedicated to the wide-field search of transiting planets around bright and nearby stars, with a strong focus on discovering habitable rocky planets hosted by solar-like stars. The choice of the fields to be pointed at is a crucial task since it has a direct impact on the scientific return of the mission. In this paper, we describe and discuss the formal requirements and the key scientific prioritization criteria that have to be taken into account in the Long-duration Observation Phase (LOP) field selection, and apply a quantitative metric to guide us in this complex optimization process. We identify two provisional LOP fields, one for each hemisphere (LOPS1 and LOPN1), and we discuss their properties and stellar content. While additional fine-tuning shall be applied to LOP selection before the definitive choice, which is set to be made two years before launch, we expect that their position will not move by more than a few degrees with respect to what is proposed in this paper.
In this paper we present all of the formal requirements, scientific criteria, and prioritization algorithms, leading to a preliminary (yet close to final) choice for the two LOP fields, one in the northern ecliptic hemisphere (LOPN1: LOP field North 1) and one in the southern one (LOPS1: LOP field South 1). This paper is also intended to stimulate a discussion within the community to converge on a final choice for the LOP fields. A second, future paper will be devoted to the fine-tuning of the LOP fields and to the selection of candidate SOP fields. The present paper is organized as follows. In Sect. 2 we describe thegeometry and the general constraints on the field selection problem. In Sect. 3 we define a quantitativemetric to prioritize a given LOP field according to its scientific value, and apply this metric to a grid of possible pointings in Sect. 4. Finally, we identify and characterize the content of LOPN1 and LOPS1 in Sects. 5 and 6, respectively. Some final remarks and future perspectives are summarized in Sect. 7. For the sake of clarity, a glossary with the most used acronyms in this work is shown in Table 1.
The present work is the first attempt to identify the LOP fields using a consistent and quantitative approach. The coordinates of the SOP and LOP fields previously selected, as reported in some papers (such as Nascimbeni et al. 2016; Miglio et al. 2017; Marchiori et al. 2019; Montalto et al. 2021), all centered at Galactic latitude b = 30, were merely a working hypothesis to verify their compliance with the PLATO Science Requirements Document (SRD; v8.0). The definitive choice for the first observing field will be formally delivered two years before launch with the possibility of fine tuning the target list up to nine months before launch. In this section, we review the starting points of this selection process.
While the PIC will contain only the targets that are to be observed by PLATO on the final LOP and SOP fields, an all-sky version of it, including all the stars compliant with the P1-P2-P4-P5 definition (except the requirements on photometric noise), is also available (asPIC; Montalto et al. 2021) and will be the starting point of our simulations. Additional catalogs are being compiled in parallel for operational purposes (including instrumental calibration, validation, and fine pointing).
The field selection process involves a complex optimization task to merge several (often competing) constraints and prioritization criteria of both an engineering and scientific nature. We discuss those criteria by splitting them into four main classes as detailed in the following subsections.
Target counts. The number of observed targets included in the PLATO stellar samples as defined by the SRD must pass a specified threshold for each of the four stellar samples monitored by PLATO (P1, P2, P4, and P5). For the Stellar Sample 1 (P1), the LOP fields combined must contain at least 15 000 (goal: 20 000) F5-K7 dwarfs and subgiants brighter than V = 11 and be observed with a photometric precision better than 50 ppm in one hour. Other analogous thresholds are set for samples P2, P4, and P5, but they can be safely neglected in this context because they are always met for every possible choice for the LOP fields (see Sect. 6).
Follow-up resources. The whole follow-up process is an important part of the mission, in particular to confirm the planetary nature of the candidates and to measure their masses through high-precision radial velocities (RVs). The location of the LOP fields has some obvious and important implications for the available ground-based facilities (based on the celestial coordinates of the targets and their annual visibility) that will be assessed in Sect. 2.3. More subtly, the fraction of false positives and the actual content of the target list in terms of astrophysical parameters also have a profound impact on the follow-up (see Sect. 6).
Special targets of interest. Especially at the fine-tuning stage, it makes sense to check whether specific objects of high scientificinterest land on the actual CCD collecting area or if this could be made feasible by only minor adjustments to the pointing. This includes, for instance, nearby open clusters, known transiting planets, and very bright solar analogs. Some of these objects will be discussed in Sect. 6.
Synergy with other missions. Other space missions, most notably Kepler and TESS, have already monitored a significant fraction of the sky in search of planetary transits. While the main goal of PLATO is to exploit its unprecedented level of photometric precision for the detection and characterization of true Earth analogs, it is worth investigating whether interesting additional science may come up by the overlap with other observed fields.
The PLATO attitude will be defined not only by a pointing direction, but also by a rotation angle around the Z axis of the payload (P/L) module. Given a pointing direction, different rotation angles will result in a different set of stars observed. Some of the field selection criteria are only weakly dependent on the choice of the rotation angle (e.g., the P1 counts), whereas some are strongly dependent (e.g., visibility of individual targets close to the edges of the field of view). The choice of the rotation angle determines the angle between the solar panels of the spacecraft and the Sun. Therefore, there is a dependency between the choice of the rotation angle at the start of the observations and the time at which it is necessary to make the first 90 degree roll to keep the action of the sun shield within the requirements. The constraints related to the spacecraft such as: power produced by the solar panels at a given sun incidence angle, allowed ranges for early or late 90 degree rolls along the year compliant with the gap requirements, stray light requirements, etc., are not consolidated at this stage of the project and therefore we cannot define reliable criteria for the choice of the optimal rotation angle now. The mission team is working toward a better understanding of the design in order to provide enough information to the PLATO Science Working Team to make a choice.
As a starting point for the identification of the LOP fields, we have to define a quantitative metric to evaluate and compare the priorities of each possible choice. As discussed in the previous section, there are many available criteria and they have a complex interplay with each other. Nevertheless, a simple metric can be devised as guidance for a more educated guess. Since fixing a field implies freezing the pool from which the target list is drawn (according to the requirements for samples P1-P2-P4-P5 specified in the SRD), our approach is (1) to define a prioritization metric at target level, then (2) to define the same metric at the field level by evaluating its integral over the list of P1 targets, which are considered to be those that are most crucial for the success of PLATO. It is a natural first step to review what has been done in the past to solve the same problem by Kepler and TESS teams.
In our case, we could ask ourselves how to develop a metric based on Eq. (1), but that is more suited to the PLATO LOP field selection. First of all, the factor does not make sense in our case and can be set to one, because by design every LOP target is continuously monitored throughout the nominal duration of the LOP field. Then, as mentioned above, this target-based metric should be summed over the total number of P1 targets within a given field, that is:(2)
As for the astrophysical contamination, which is mostly due to blended, detached eclipsing binaries mimicking a planetary transit, a more sophisticated approach is required. Focusing on the specific characteristics of PLATO, including its pixel scale and PSF size, Bray et al. (in prep.) exploited a binary population model to estimate the false positive ratio (FPR) (defined as the ratio between FPs and the total number of detections) as a function of the line of sight, and for different bins of planetary radius. As expected, the Galactic latitude b is the key variable in determining the FPR, the dependence on longitude l being very weak and not even statistically significant for most bins. After neglecting the l dependence, we fit the parameters of an exponential law to the (b, FPR) relation found for terrestrial-sized planets by Bray et al.:(3)
In the next section, we evaluate and compare the quantity for a set of different LOP choices as guidance in the field selection process. Adding too many parameters at once in such a complex task would be confusing, and it would create an issue about how these additional terms are arbitrarily weighted with each other. Rather, we discuss the other prioritization criteria a posteriori, after having identified the sky regions where the expression in Eq. (4) is maximized.
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