The ARIEL Mission Reference Sample
Tiziano Zingales, Giovanna Tinetti, Ignazio Pillitteri, Jèrèmy Leconte, Giuseppina Micela, Subhajit Sarkar
NNoname manuscript No. (will be inserted by the editor)
The ARIEL Mission Reference Sample
Tiziano Zingales · Giovanna Tinetti · Ignazio Pillitteri · Jérémy Leconte · Giuseppina Micela · Subhajit Sarkar
Received: date / Accepted: date
Abstract
The ARIEL (Atmospheric Remote-sensing Exoplanet Large-survey)mission concept is one of the three M4 mission candidates selected by the Eu-ropean Space Agency (ESA) for a Phase A study, competing for a launch in2026. ARIEL has been designed to study the physical and chemical propertiesof a large and diverse sample of exoplanets, and through those understandhow planets form and evolve in our galaxy.Here we describe the assumptions made to estimate an optimal sample ofexoplanets – including both the already known exoplanets and the "expected”ones yet to be discovered – observable by ARIEL and define a realistic missionscenario. To achieve the mission objectives, the sample should include gaseousand rocky planets with a range of temperatures around stars of different spec-tral type and metallicity. The current ARIEL design enables the observationof ∼ Tiziano ZingalesUniversity College LondonINAF- Osservatorio Astronomico di PalermoGiovanna TinettiUniversity College LondonIgnazio PillitteriINAF - Osservatorio Astronomico di PalermoJérémy LeconteCNRS, Université de BordeauxLaboratoire d’Astrophysique de BordeauxGiuseppina MicelaINAF - Osservatorio Astronomico di PalermoSubhajit SarkarCardiff University, Cardiff, UK a r X i v : . [ a s t r o - ph . E P ] J a n Tiziano Zingales et al. during its four year mission lifetime. This nominal list of planets is expectedto evolve over the years depending on the new exoplanet discoveries.
Keywords
Exoplanets · ARIEL space mission · Planetary population he ARIEL Mission Reference Sample 3 number of exoplanets expected to exist with a particular size, orbital periodrange and orbiting a star of a particular spectral type and metallicity. Here wedescribe the assumptions made to estimate an optimal sample of exoplanetsobservable by ARIEL and define the Mission Reference Sample (MRS). It isclear that this nominal list of planets will change over the years depending onthe new exoplanetary discoveries.In Section 2 we explain the method used to estimate the number and theparameters of the planetary systems yet to be discovered. All the potentialARIEL targets will be presented in Section 3, where we show all the planetsthat can be observed individually during the mission lifetime, and out of whichwe want to select the optimal sample. Section 4 is dedicated to the selectionand description of an ARIEL MRS fulfilling the mission requirements, wecompare the proposed ARIEL MRS to the sample expected to be discoveredby TESS, confirming that TESS could provide a large fraction of the ARIELtargets. A sample including only planets known today is identified. In Section5 we show a possible MRS which maximises the coverage of the planetary andstellar physical parameters.1.2 Description of the modelsWe use the ESA Radiometric Model (Puig et al., 2015) to estimate the per-formances of the ARIEL mission given the planetary, stellar and orbital char-acteristics: namely the stellar type and brightness, the planetary size, mass,equilibrium temperature and atmospheric composition, the orbital period andeccentricity. This tool takes into account the mission instrumental parametersand planetary system characteristics to calculate: – The SNR (Signal to Noise Ratio) that can be achieved in a single transit; – The SNR that can be achieved in a single occultation; – The number of transit/occultation revisits necessary to achieve a specifiedSNR; – The total number and types of targets that can be included in the missionlifetime.In this work, the input planet list for the radiometric model is a combina-tion of known and simulated exoplanets, as detailed in the following sections.We used the instrument parameters of the ARIEL payload as designed dur-ing the phase A study. To increase the efficiency of our simulations we useda Python tool as a wrap of the ESA Radiometric Model, so we could testdifferent mission configurations that fulfil the mission science objectives. Theresults were validated with ExoSim, a time domain simulator used for theARIEL space mission, but thanks to its modularity it can be used to studyany transit spectroscopy instrument from space or ground. ExoSim has beendeveloped by Sarkar et al. (2016); Sarkar and Pascale (2015); Pascale et al.(2015) (see App A).
Tiziano Zingales et al. m K = 7 usedto infer the number density of stars in the Solar neighbourhood is shown inTab 1. Mass (M (cid:12) ) Spectral type N ∗ (K < ) Table 1
Star counts considering different spectral types with limiting magnitude m K = 7. The number density and the number of stars are related through Eq 1: ρ ∗ = N ∗ ( K < πd (1)where the distance d has been calculated in the ARIEL Radiometric Model(Puig et al., 2015) using the relation between K magnitude m K and the dis-tance d : m K = − . R ∗ S s ( ∆λ ) d S K ( ∆λ ) (2)In Eq 2, R ∗ is the stellar radius, S K ( ∆λ ) is the zero point flux for the standardK-band filter profile, ∆λ is the filter band pass given in Cohen et al. (2003) and S s ( ∆λ ) the stellar flux density evaluated over the same bandwidth. We neglectthe interstellar absorption since our stars are at a relatively short distance.2.2 Planetary population and occurrence rateIn this section we briefly review the current knowledge about the occurrencerate of planets, i.e. the average expected number of planets per star. Fressinet al. (2013) used the Kepler statistics to publish the planetary occurrence ratesaround F, G, K main sequence stars ordered by orbital periods and planetarytypes. An accurate planetary occurrence rate is pivotal to the reliability of the he ARIEL Mission Reference Sample 5 DensityStar / pc ρ ( F6-F9 ) 0.0039 ρ ( G0-G8 ) 0.0044 ρ ( K0-K5 ) 0.0049 ρ ( K7-M1 ) 0.0074 ρ ( M2-M3 ) 0.0059 ρ ( M4 - late M ) 0.0118
Table 2
Main sequence star densities considering different spectral types with limitingmagnitude m K = 7 estimate of the existing planets in the Solar neighbourhood. We used the plan-etary occurrence rate values for F,G,K and M stars from Fressin et al. (2013),being the most conservative and currently the most complete, i.e. coveringall planetary types and stars. Therefore, our estimates for the ARIEL sampleare very conservative. Mulders et al. (2016) updated the planetary occurrencerate for planets between 0 . R ⊕ and 4 R ⊕ and orbital period <
50 days, usinga more recent list of planets discovered by the Kepler satellite. Fig 2 showsthe comparison between Mulders et al. (2016) and Fressin et al. (2013). Thedifferences between the two occurrence rates can be up to an order of mag-nitude. Mulders et al. (2015) show that M stars have 3.5 times more smallplanets (1 . − . R ⊕ ) than FGK stars, but two times fewer Neptune-sized andlarger ( > . R ⊕ ) planets. The fraction of M-stars considered in our work isonly ∼
7% of the total stellar sample, so we are significantly underestimat-ing the number of small planets around M-dwarfs, which are optimal targetsfor transit spectroscopy. More recent and complete results from Mulders andcollaborators are expected to be published in the next months and they arenot yet available for our simulations. Given the discrepancy between Muldersand Fressin’s statistics we expect a substantial improvement in our estimateswhen the most recent Kepler statistics will become available.Fressin et al. (2013) provided the following statistics for different planetaryclasses: – Jupiters: 6 R ⊕ < R p ≤ R ⊕ – Neptunes: 4 R ⊕ < R p ≤ R ⊕ – Small Neptunes: 2 R ⊕ < R p ≤ R ⊕ – Super Earths: 1 . R ⊕ < R p ≤ R ⊕ – Earths: 0 . R ⊕ < R p ≤ . R ⊕ We adopted a size resolution of 1 R ⊕ in each of these classes.The number of planets can be estimated as: N p = 43 πd ρ ∗ P t,p P geom (3)where d is the radius of a sphere with the Sun at the centre, ρ ∗ is the numberdensity of the stars, P t,p is the probability of having a t-type planet orbit-ing with an orbital period p (See Fig 1). P geom = R ∗ /a is the geometricalprobability of a transit. Tiziano Zingales et al.
We simulated all the transiting planets in the solar system neighbourhoodup to m K = 14, all these planets described by N p constitute the “MissionReference Population”.To include in the population sample the exoplanets known today, everytime we predict a system with the same physical properties of a known sys-tem we replace it with the known one. In Sec 3 we show that in the solarsystem neighbourhood there are ∼ T p = T ∗ (cid:18) R ∗ a (cid:19) (cid:18) − Aε (cid:19) (4)Here T ∗ and R ∗ are the stellar temperature and radius, a the semi-majoraxis of the orbit, A is the planetary albedo and ε is the atmospheric emissivity.The ARIEL space mission will focus on planets with an orbital periodshorter than 50 days. As expected, shorter periods mean shorter semi-majoraxis and, therefore, from Eq 4, typically higher effective temperature. Fig. 1
Average number of planets per star and per size bin with an orbital period shorterthan 85 days orbiting around F, G, K stars. The statistics was extracted from the Q1 - Q6Kepler data (Fressin et al., 2013).he ARIEL Mission Reference Sample 7
10 20 30 40 50Period (days)10 -4 -3 -2 -1 P l a n e t a r y o cc u rr e n c e r a t e ( % ) . R ⊕ − . R ⊕ Mulders (metal poor star)Mulders (metal rich star)Fressin
Fig. 2
Comparison of three different distributions estimating the planetary occurrence rateas a function of orbital period for planets between 0 . R ⊕ and 4 R ⊕ . Blue and green lines:results from Mulders et al. (2016) for two metallicity classes. Red line: results from Fressinet al. (2013). The Fressin et al. (2013) statistics strongly underestimates the occurence ofsub Neptune size planets compared to Mulders et al. (2016) and other more recent estimates.The reason is the large number of small planets discovered after 2013. H ) of the atmosphere: H = k Tµ g (5)The mass estimate is not a trivial task, given the range of planetary den-sities observed today. We used a Python tool written by Chen and Kipping(2016) to estimate the mass of all the planets in our simulated sample. In theARIEL planetary sample there are both known and simulated planets. Chenand Kipping (2016) use the currently known planets to derive the statisticaldistribution of the mass of a given planet when its radius is known. Thus, foreach planet in our initial sample, the mass is randomly drawn following thisdistribution except for known systems. In Fig 3 we show the mass distributionfor all the planets in our simulations. Moreover, as a very few planets have aradius larger than 20 R ⊕ , we use that radius as an upper limit. There is alreadya well known degeneracy in the 7 − R ⊕ range: objects with a radius withinthat range can be planets as well as very cool stars. However, this shouldnot be too concerning, as observations have shown that very short-period,low-mass stellar companions are much less frequent than hot giant planets(Piskorz et al., 2015). Tiziano Zingales et al.
Fig. 3
Mass-Radius distribution for all the simulated planets. The mass-radius relationshiphas been calculated with the Chen and Kipping (2016) tool.he ARIEL Mission Reference Sample 9
ARIEL 3-tiersSurvey ( ∼ ≥ ∼ ∼ Table 3
Summary of the survey tiers and the observational methods they will be accom-plished. Each tier is expressed in terms of nominal mission lifetime ARIEL could spend onthem.
The key questions and objectives of each tier can be summarised as follows(see Tinetti et al., in prep. for further details):
Survey : – What fraction of planets are covered by clouds? – Tier 1 mode is particu-larly useful for discriminating between planets that are likely to have clearatmospheres, versus those that are so cloudy that no molecular absorp-tion features are visible in transmission. Extremely cloudy planets may beidentified simply from low-resolution observations over a broad wavelength range. This preliminary information will therefore allow us to take an in-formed decision about whether to continue the spectral characterization ofthe planet at higher spectral resolution, and therefore include or not theplanet in the Tier 2 sample. – What fraction of small planets have still hydrogen and helium retained fromthe protoplanetary disk? – Primordial (primary atmosphere) atmospheresare expected to be mainly made of hydrogen and helium, i.e. the gaseouscomposition of the protoplanetary nebula. If an atmosphere is made ofheavier elements, then the atmosphere has probably evolved (secondary at-mosphere). An easy way to distinguish between primordial (hydrogen-rich)and evolved atmospheres (metal-rich), is to examine the transit spectra ofthe planet: the main atmospheric component will influence the atmosphericscale height, thus changing noticeably the amplitude of the spectral fea-tures. This question is essential to understand how super-Earths formedand evolved. – Can we classify planets through colour-colour diagrams or colour-magnitudediagrams? – Colour-colour or colour-magnitude diagrams are a traditionalway of comparing and categorising luminous objects in astronomy. Simi-larly to the Herzsprung-Russell diagram, which led to a breakthrough inunderstanding stellar formation and evolution, the compilation of similardiagrams for exoplanets might lead to similar developments (Triaud et al.,2014). – What is the bulk composition of the terrestrial exoplanets? – The planetarydensity may constrain the composition of the planet interior. However thismeasurement alone may lead to non-unique interpretations (Valencia et al.,2007). A robust determination of the composition of the upper atmosphereof transiting planets will reveal the extent of compositional segregationbetween the atmosphere and the interior, removing the degeneracy origi-nating from the uncertainty in the presence and mass of their (inflated?)atmospheres. – What is the energy balance of the planet? – Eclipse photometric measure-ments in the optical and infrared can provide the bulk temperature andalbedo of the planet, thereby allowing the estimation of the planetary en-ergy balance and whether the planet has an internal heat source or not.
Deep :A key objective of ARIEL is to understand whether there is a correlationbetween the chemistry of the planet and basic parameters such as planetarysize, density, temperature and stellar type and metallicity. Spectroscopic mea-surements at higher resolution will allow in particular to measure: – The main atmospheric component for small planets; – The chemical abundances of trace gases, which is pivotal to understandthe type of chemistry (equilibrum/non equilibrium). – The atmospheric thermal structure, both vertical and horizontal; – The cloud properties, i.e. cloud particles size and distribution, he ARIEL Mission Reference Sample 11 – The elemental composition in gaseous planets. This information can beused to constrain formation scenarios (Öberg et al., 2011).
Benchmark :A fraction of planets around very bright stars will be observed repeatedlythrough time to obtain: – A very detailed knowledge of the planetary chemistry and dynamics; – An understanding of the weather, and the spatial and temporal variabilityof the atmosphere.Benchmark planets are the best candidates for phase-curve spectroscopic mea-surements.3.2 Key science questionsIn this section we show a full list of potential targets for ARIEL: these areexpected to evolve until launch, and will be updated regularly to include newplanet discoveries.ARIEL Tier 1 (Survey) will analyse a large sample of exoplanets to addressscience questions where a statistically significant population of objects needsto be observed. ARIEL Tier 1 will also allow a rapid, broad characterisationof planets permitting a more informed selection of Tier 2 and Tier 3 planetarycandidates. For most Tier 1 planetary candidates, Tier 1 performances can bereached between 1 and 2 transits/eclipses. In Fig 4 and 5 we show that in thesolar system neighbourhood there are ∼ R )110100100010000 N u m b e r o f p l a n e t s Fig. 4
Complete set of Tier 1 planets from the ARIEL missione reference population. Thefinal list of Tier 1 planets will include an optimal sub-sample. Different colours indicate thenumber of transits/eclipses needed to reach Tier 1 performances. The planets shown herecan achieve the Tier 1 requirements combining the signal of ≤
300 500 700 900 1100 1300 1500 1700 1900 2100 2300Temperature ( K )0100200300400500600700800 N u m b e r o f p l a n e t s Fig. 5
Temperature distribution for the planets illustrated in fig. 4. R )110100100010000 N u m b e r o f p l a n e t s Fig. 6
Planets from the ARIEL mission reference population in the Deep mode (Tier 2)with a small/moderate number of transits/eclipses, divided in size bins. The final list ofTier 2 planets will include an optimal sub-sample. Different colours indicate the number oftransits/eclipses needed to reach Tier 2 performances.
300 500 700 900 1100 1300 1500 1700 1900 2100 2300Temperature ( K )050100150200250 N u m b e r o f p l a n e t s Fig. 7
Temperature distribution for the planets illustrated in fig. 6.he ARIEL Mission Reference Sample 13 ( R ⊕ ) N u m b e r o f p l a n e t s Fig. 8
Number of planets from the mission reference population observable by ARIEL inthe Benchmark mode with a <
25 number of transits/eclipses, divided in size bins. Differentcolours indicate the number of transits/eclipses needed to reach Tier 3 performances.
300 500 700 900 1100 1300 1500 1700 1900 2100 2300Temperature ( K )020406080100120140 N u m b e r o f p l a n e t s Fig. 9
Temperature distribution for the planets illustrated in fig. 8.4 Tiziano Zingales et al.
In Section 3 we presented a comprehensive list of planet candidates whichcould be observed with the ARIEL space mission. Here we discuss possibleoptimisations of the Mission Reference Sample, which ideally should includea large and diverse sample of planets, have the right balance among the threeTiers and, most importantly, must be completed during the nominal missionlifetime (4 years including the commissioning phase).
Fig. 10
Overview of the ARIEL MRS, comparing the number of planets observable in thethree tiers during the mission lifetime.
In Fig 10 we show a possible MRS with all the three tiers nested together.The first MRS shows the maximum number of targets, taking into accountthe nominal mission lifetime. It has been built starting from all the targetsfeasible within one transit/eclipse, and adding all the targets that can be donewithin 2, 3, 4 and so on transits/eclipses in ascending order. This is just oneof the possible configurations for the MRS, and one would expect the ARIELMRS to evolve in response of new exoplanetary discoveries in the next decade.4.1 MRS Tier 1: SurveyOur simulations indicate that the current ARIEL design as presented at theend of the Phase A study, allows to observe 1002 planets in Tier 1. All theplanets can be observed in 1538 satellite visits i.e. 37% of the mission lifetime.Most giant planets and Neptunes fulfil the Tier 1 science objectives in 1 tran-sit/eclipse, the smaller planets require up to 6 events (fig. 11 and 12 ). Fig. 13and 14 illustrate how the 1002 planets are distributed in terms of planetarysize, temperature, density and stellar type. he ARIEL Mission Reference Sample 15 R )1101001000 N u m b e r o f p l a n e t s Fig. 11
ARIEL MRS Tier 1 planets organised in size-bins. Different colours indicate thenumber of transits/eclipses needed to reach Tier 1 performances.
300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500Temperature ( K )020406080100 N u m b e r o f p l a n e t s Fig. 12
ARIEL MRS Tier 1 planets organised in temperature-bins. Different colours indi-cate the number of transits/eclipses needed to reach Tier 1 performances. R )1101001000 N u m b e r o f p l a n e t s g / cm Fig. 13
ARIEL MRS Tier 1 planets organised in size-bins. Different colours indicate dif-ferences in the simulated planetary densities.
300 500 700 900 11001300150017001900210023002500Planetary Temperature (K)020406080100 N u m b e r o f p l a n e t s T * ( K ) Fig. 14
ARIEL MRS Tier 1 planets organised in temperature-bins. Different colours indi-cate differences in the simulated stellar temperatures.6 Tiziano Zingales et al. ∼
500 planets in Tier 2 assuming 60% of the mission lifetime. Fig. 17 and18 illustrate how the 500 planets are distributed in terms of planetary size,temperature, density and stellar type.Most gaseous planets fulfil the Tier 2 science objectives in less than fivetransits/eclipses, the small planets require up to twenty events (fig. 15 and 16). We included a variety of planets from cold (300 K) to very hot (2500 K)as shown in Fig 16. We scheduled also ∼
50 planets that will be studied withboth transit and eclipse methods, indicated by stripes in Fig 15). These arethe best candidates for phase-curves observations, which can be included atthe expenses of the number of Tier 2 planets observed. ( R ⊕ ) N u m b e r o f p l a n e t s
502 planets 60.2 %49 planets can be done with both methods
Fig. 15
ARIEL MRS Tier 2 planets organised in size-bins. Different colours indicate thenumber of transits/eclipses needed to reach Tier 2 performances. Stripes indicate planetsthat will be studied with both transit and eclipse methods
300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500Temperature ( K )01020304050 N u m b e r o f p l a n e t s Fig. 16
ARIEL MRS Tier 2 planets organised in temperature-bins. Different colours indi-cate the number of transits/eclipses needed to reach Tier 2 performances.he ARIEL Mission Reference Sample 17 R )1101001000 N u m b e r o f p l a n e t s g / cm Fig. 17
ARIEL MRS Tier 2 planets organised in size-bins. Different colours indicate dif-ferences in the simulated planetary densities.
300 500 700 900 11001300150017001900210023002500Planetary Temperature (K)01020304050 N u m b e r o f p l a n e t s T * ( K ) Fig. 18
ARIEL MRS Tier 2 planets organised in temperature-bins. Different colours indi-cate differences in the simulated stellar temperatures.8 Tiziano Zingales et al.
300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500Temperature ( K )0123456789 N u m b e r o f p l a n e t s Fig. 19
Temperature distribution of the planets observable by ARIEL in the Benchmark.he ARIEL Mission Reference Sample 19
Earths Super Earths Sub Neptunes Neptunes\GiantsType10 N u m b e r o f P l a n e t s TESS Targets StarsFull-Frame Images
Fig. 20
Comparison between the TESS targets (Sullivan et al., 2015) and the ARIEL MRS(green bars). ∼
210 transiting planets fulfill the ARIEL previous criteria.It means that, even if ARIEL were launched tomorrow, it would observe atleast 210 relevant targets. Using the planets known today, we could organisethe MRS into the following three tiers: – Survey: 210 planets using 30% of the mission lifetime (Fig 21); – Deep: 158 planets using 60% of the mission lifetime (Fig 26); – Benchmark: 67 planets using 10% of the mission lifetime (Fig 27).In Fig 21, 22 and 23 we show the key physical parameters of the knownplanets defining the current observable MRS. In Fig 24 and 25 we show theproperties of the stellar hosts. As mentioned previously, the number of knownplanets is expected to increase dramatically in the future.Pictorial representation (M. Ollivier, private comm.) of the known planetssky coordinates and their sky visibility all over the year is given in Fig 28. Itshows that objects far away from the ecliptic plane will be visible longer thanthe planet close to this plane. R )051015202530 N u m b e r o f P l a n e t s
210 planets TRAPPIST-1 planets
Fig. 21
ARIEL MRS with currently available planets radius distribution.
300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500
Temperature (K)0510152025 N u m b e r o f P l a n e t s TRAPPIST-1 planets
Fig. 22
ARIEL MRS with currently available planets temperature distribution. .
10 0 .
13 0 .
17 0 .
22 0 .
28 0 .
36 0 .
46 0 .
60 0 .
77 1 .
00 1 .
29 1 .
67 2 .
15 2 .
78 3 .
59 4 .
64 5 .
99 7 .
74 10 . Density ( g / cm )051015202530 N u m b e r o f P l a n e t s Fig. 23
ARIEL MRS with currently available planets density distribution. N u m b e r o f S t a r s Fig. 24
Temperature distribution of the stellar hosts for the planets shown in fig. 21he ARIEL Mission Reference Sample 21 - . - . - . - . - . - . - . - . - . - . - .
00 0 .
05 0 .
10 0 .
15 0 .
20 0 .
25 0 .
30 0 .
35 0 .
40 0 .
45 0 . Metallicity0369121518 N u m b e r o f S t a r s Fig. 25
Metallicity distribution of the stellar hosts for the planets shown in fig. 21 R )05101520 N u m b e r o f P l a n e t s
158 planets300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500Temperature (K)0510152025 N u m b e r o f P l a n e t s Fig. 26
Planets known today and observable by ARIEL in Deep mode, distributed insize-bins ( top ) and temperature bins ( bottom ) – 158 planets.2 Tiziano Zingales et al. R )02468101214 N u m b e r o f P l a n e t s
67 planets300 500 700 900 1100 1300 1500 1700 1900 2100 2300 2500Temperature (K)01234567 N u m b e r o f P l a n e t s Fig. 27
Planets known today and observable by ARIEL in Benchmark mode, distributedsize-bins ( top ) and temperature bins ( bottom ) – 67 planets.he ARIEL Mission Reference Sample 23
Fig. 28
A plot illustrating the fraction of the year for which a given location in the sky (inequatorial coordinates) is visible to ARIEL, as seen from a representative operational orbitof ARIEL at L2. Yellow dots: planets observed in Tier 1. Red dots: planets observed in Tier2. Green dots: planets observed in Tier 3. (Marc Ollivier, private communication)
In this section we show another possible selection of the Tier 1 sample thatmaximises also the diversity of stellar hosts, additionally to other planet pa-rameters. In particular, the stellar metallicity is expected to play an importantrole in the planet formation process and type of chemistry of the planet (Venotet al., 2015). ARIEL will also collect important data to understand better therelationship between stellar metallicity and planetary characteristics.5.1 MethodWe will limit our analysis to those systems which can be studied in up to sixvisits for each planet (either a transit or an occultation).We chose four physical quantities that define a 4D space to distributethe ARIEL targets. The quantities are: stellar effective temperature (T eff ),metallicity ([Fe/H]), planetary radius (R pl ) and planetary theoretical equi-librium temperature (T pl ). For the metallicity we use the values observed inthe solar neighbourhood and reported by Casagrande et al. (2011). We adoptthree bins for stellar T eff , [Fe/H] and planetary R pl , while for the T pl we use Table 4
Bins of T eff , [Fe/H], R pl , T pl defining the 4D parameter space. Stellar Temp.: T eff < T (K) < < T (K) < T > < -0.15 − . < [Fe/H] < .
15 [Fe/H] > . pl R pl < ⊕ < R ⊕ < pl > ⊕ Labels Earths/ Super Earths Neptunes JupitersPlanet Temp.: T pl contiguous bins: [250, 500, 800, 1200, 1600, 2600] K five bins, as detailed in Table 4. The three T eff bins correspond approximatelyto the ranges of spectral types M-Late / K stars, Early K-G stars and F-Gstars, respectively, as indicated in the labels in Fig 30 to 32. Analogously, weseparated the sample in low metallicity, solar metallicity and high metallicity,according to individual temperature values. The binning into 3 intervals ofT eff , [Fe/H] and R pl is a reasonable trade-off between a detailed representa-tion of the sample and a simple visualization of the richness and diversity ofthe physical configurations of the sample. We inferred from Casagrande et al.(2011) that the metallicities of stars in the solar neighbourhood are consistentwith a normal distribution with mean -0.1 and standard deviation sd=0.2.Using such model distribution we simulated the values of [Fe/H] for each starin the ARIEL sample.The 4D space of T eff , [Fe/H], R pl and T pl is composed by a total of3 × × × × pl , T pl , spectral type, and [Fe/H] values.The 1002 systems in Fig. 30 tend to populate the cells corresponding to F-G-early and K stars orbited by Neptunes/Jupiters size planets (with a numberof planets per cell N > he ARIEL Mission Reference Sample 25
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; Low [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; Solar
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; High [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; Low [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; Solar
12 54 27544 155 27240 118 3905 22 2031 5 54 0 5 10 15 20
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; High [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) F−G; Low [Fe/H]
24 21463 74 27586 139 43329 113 4399 20 301 0 5 10 15 20
Radius (Rearth) P l ane t T e m p . ( K ) F−G; Solar
Radius (Rearth) P l ane t T e m p . ( K ) F−G; High [Fe/H]
Fig. 29
Distribution of the 9545 planets in the 4D space of T eff , [Fe/H], R pl , T pl . Aboveeach panels we indicate the spectral type and metallicity. The numbers in each cell arethe numbers of planets with the corresponding properties. The colour scale indicates morepopulated cells (darker orange/brown). Grey cells without any number indicate no objects. and F stars. We managed to select 908 planets and, in particular, 594 of themrequire only 1 visit (65.4%), 151 planets require 2 visits (16.6%), 83 planetsrequire 3 visits (9.1%), 41 planets require 4 visits (4.5%), and 39 planets require5 visits (4.4%). The corrected sample is shown in Fig 31, where now ∼ Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; Low [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; Solar
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; High [Fe/H]
10 5 10 15 20
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; Low [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; Solar
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; High [Fe/H]
21 33 3 112 510 5 10 15 20
Radius (Rearth) P l ane t T e m p . ( K ) F−G; Low [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) F−G; Solar
Radius (Rearth) P l ane t T e m p . ( K ) F−G; High [Fe/H]
62 2 616 3 75 241 11
Fig. 30
Same as Fig. 29 1002 planets of the Mission Reference Sample. shown in Fig. 31. Compared to Fig. 30, we see that we can efficiently cover mostof the 4D space in planetary sizes, planetary temperatures, host temperaturesand metallicities, apart from those combination of parameters correspondingto not physical or rare systems (e.g., very hot planets around very cool stars).Our selection is composed by 908 unique planets requiring a total of 1504visits. Among already known systems, 92 of the initial 211 systems are in thisnew list. This selection is not unique, and depends on our choices, but ourexercise shows that we have great freedom on the final choice on how to spendARIEL observing time, as it can be easily tuned on specific needs. Fig. 32shows the average number of visits required to cover each cell of the 4D space.The number of visits needed for Jupiters and Neptunes is, typically, one ortwo, while Earths/Super Earths require from 3 to 5 visits each. To summarise,out of the 908 planets in our selection there are 594 planets requiring only1 visit (65.4%), 151 planets requiring 2 visits (16.6%), 83 planets requiring 3visits (9.1%), 41 planets requiring 4 visits (4.5%), and 39 planets requiring 5visits (4.4%). he ARIEL Mission Reference Sample 27
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; Low [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; Solar
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; High [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; Low [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; Solar
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; High [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) F−G; Low [Fe/H]
10 1010 10 1010 10 1010 10 109 10 10 0 5 10 15 20
Radius (Rearth) P l ane t T e m p . ( K ) F−G; Solar
Radius (Rearth) P l ane t T e m p . ( K ) F−G; High [Fe/H]
Fig. 31
Same as Fig. 30 for the selected sample of 908 known and simulated planetarysystems. They have been selected by filling each cell with up to 10 objects and for a budgetof total satellite visits of about 1500.
As a final comment, we have verified that, by increasing the maximumnumber of systems per 4D cell while keeping fixed the total number of visitsto ∼ In this paper we demonstrated that the current ARIEL design enables theobservation of 900-1000 planets during its four-year lifetime, depending on thephysical parameters of the planet/star systems which one wants to optimise.
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; Low [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; Solar
Radius (Rearth) P l ane t T e m p . ( K ) M−Late K; High [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; Low [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; Solar
Radius (Rearth) P l ane t T e m p . ( K ) Early K−G; High [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) F−G; Low [Fe/H]
Radius (Rearth) P l ane t T e m p . ( K ) F−G; Solar
Radius (Rearth) P l ane t T e m p . ( K ) F−G; High [Fe/H]
Fig. 32
Average number of visits required for the sample selected in Fig. 31. The binningis as in Figs. 30 to 31.
The optimal sample of targets fulfils all the science objectives of the mission.While we currently know only ∼
200 transiting exoplanets which could bepart of the mission reference sample, new space missions and ground-basedobservatories are expected to discover thousands of new planets in the nextdecade. NASA-TESS alone is expected to deliver most ARIEL targets.
Ackowledgements
T. Z. is supported by the European Research CouncilERC projects
ExoLights (617119) and from INAF trough the "Progetti PremialiâĂİ funding scheme ofthe Italian Ministry of Education, University, and Research. I.P and G.M. aresupported by Ariel ASI-INAF agreement No. 2015-038-R.0. G.T. is supportedby a Royal Society URF. We thank Enzo Pascale and Ludovig Puig for theirhelp in setting up the ESA’s Radiometric model. he ARIEL Mission Reference Sample 29
Appendix A ESA Radiometric Model validation with ExoSim
We compare the out-of-transit signal and noise from ESA Radiometric Model(ERM) with that from ExoSim. An early version of ARIEL with a gratingdesign was used for the instrument model in each. We model 55 Cancri andGJ 1214 with the same PHOENIX spectra in each simulator and include onlyphoton noise and the noise floor, N min ( λ ), which is dominated by dark currentnoise. All the calculations are done per unit time and per spectral bin ( R = 30in Ch1 and R = 100 in Ch0). The noise variance was compared assuming anaperture mask on the final images, and the noiseless signal per unit time wascompared assuming no aperture. In the ERM, we use the following expressionfor N min giving the noise variance: N min ( λ ) = 2 . f λ mR∆ pix I dc (6)where I dc is the dark current per pixel, m is the reciprocal linear dispersion ofthe spectrum in µ m wavelength per µ m distance, R is the spectral resolvingpower and ∆ pix is the pixel pitch. The noise variance from ExoSim is given asthe average of 50 realizations with a standard deviation (shown as error barsin the following figures). For 55 Cancri e case (Fig 33), over all wavelengthbins, the ERM signal is always within 2% of ExoSim, and the averaged noisevariance within 5% of the ERM. In 94% of the bins, the ERM noise varianceis within the standard deviation from ExoSim. Fig. 33
Comparison between the out-of-transit signal (left) and noise (right) simulated byExoSim (white points) and the ESA Radiometric Model (blue points) for the star 55 Cancri.Subplots show the percent difference of the ERM from ExoSim.
For GJ 1214 (Fig 34), the ERM signal is within 4% of ExoSim over all binsand the averaged noise variance within 6% of ExoSim over all bins. The ERMnoise variance is always within the standard deviation from ExoSim over allbins.There is therefore good agreement between the two simulators.
Fig. 34
Comparison between the out-of-transit signal (left) and noise (right) simulated byExoSim (white points) and the ESA Radiometric Model (blue points) for the star GJ 1214.Subplots show the percent difference of the ERM from ExoSim.he ARIEL Mission Reference Sample 31
Appendix B Known planets observable by ARIEL
Planet planetary properties stellar properties Observation
R ( R ⊕ ) M ( M ⊕ ) P (days) T (K) R ( R (cid:12) ) T (K) Planet planetary properties stellar properties Observation
R ( R ⊕ ) M ( M ⊕ ) P (days) T (K) R ( R (cid:12) ) T (K) he ARIEL Mission Reference Sample 33 Planet planetary properties stellar properties Observation
R ( R ⊕ ) M ( M ⊕ ) P (days) T (K) R ( R (cid:12) ) T (K) Planet planetary properties stellar properties Observation
R ( R ⊕ ) M ( M ⊕ ) P (days) T (K) R ( R (cid:12) ) T (K) Table 5
List of known planets observable by ARIEL. The former to last column representsthe number of transits/eclipses necessary to fulfil the ARIEL Tier 1 goals.he ARIEL Mission Reference Sample 35
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