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Neta by Edited and Switzerland; Lausanne, CP-1015 Lausanne, a Balbi Amedeo biosignatures searches exoplanetary future for of impact information the Quantifying e flmtdsailetn.Ti ilb rebt ntecs of case the in both true be sur- will a This from extent. galaxy spatial entire limited the of in vey treat- inhabited statistical possible the of rigorous on conclusions distribution a draw to years), order in light system necessary be of stellar will ment tens our few of a vicinity within immediate (i.e., the to biosignatures for exoplanets. rocky habitable of imaging direct the Space Hab- such missions observatory (HabEX envisioned [Habitable scale, Observatory time Exoplanet longer itable a or On 13 14]. ref. ref. [JWST] (ARIEL) Telescope Large-survey Exoplanet Space Remote-sensing Webb Atmospheric James as [such most tories the European opportuni- the Telescope on with realistic Large (e.g., biosignatures Extremely ground be the of from will detection both targets, the there promising attempting decades, Over for habitable of observations. ties potentially couple follow-up of for next (12) suitable sample the (PLATO) more the planets refine nearby of will the Oscillations missions and (TESS) In space and (11), Satellite (6–9). Transits (CHEOPS) Survey worlds Satellite PLAnetary Exoplanet ExoPlanet other sig- CHaracterising Transiting spectroscopic on (10), the for activity looking term, of biological near goal composition—we of the atmospheric to their in closer of characterization—and, getting study are their the to to exoplanets particular, of detection the (3–5). one life of least presence that at the features have to physical conducive have should now planets be such galaxy may is many our that it and in speaking, (2) Generally every the (1). that on planets conclusions believed such statistical robust of draw populations to us allowing galaxy, O iatmnod iia Universit Fisica, di Dipartimento 5 ic ehooia iiain iliiilyrsrc h search the restrict initially will limitations technological Since from shifting rapidly research current of focus the With naie lnt nteglx ihapoaiiyexceed- probability a with galaxy the in planets inhabited eetdtosnso lnt riigohrsasi our in have stars other observations orbiting astronomical planets decades, of 2 thousands detected past the ver † ] h ag VOtclI Surveyor UV/Optical/IR Large the )], | exoplanets a,1 § ih tep isgauedtcinthrough detection attempt might n lui Grimaldi Claudio and | aeinanalysis Bayesian ∗ iRm TrVraa”013Rm,Italy; Roma, 00133 Vergata,” “Tor Roma di a n ihddctdsaeobserva- space dedicated with and ) ` | c etoSuieRcrh nioFri 08 oa Italy Roma, 00184 Fermi, Enrico Ricerche e Studi Centro rgno life of origin b,c,1 ‡ n h Origins the and , b aoaoyo hsc fCmlxMte,EoePltcnqeF Polytechnique Ecole Matter, Complex of Physics of Laboratory doi:10.1073/pnas.2007560117/-/DCSupplemental at online information supporting contains article This 1 the under Published Submission.y Direct PNAS a is article This interest.y competing no declare wrote authors and The research, performed research, designed paper.y C.G. the and A.B. contributions: Author the with combined , took on life it datum, of that to single appearance attempt a evidence the on early was conditioned the universe i.e., of the rate in the in emerging quantify methodology life Bayesian of be the missions. context will of future the Earth application from beyond previous collected be notable life will A of evidence presence new the as updated on knowl- credence existing or how showing edge perspective, Bayesian a of found. adoption given be a will evidence in no exoplanets where more case or the one in on and life volume of detection positive a ntepoaiiyo ieo te lnt.W ugs a to in way be pertaining those can a particular, that suggest in independently, others We estimated credence from principle planets. existing probability decades) other unknown to on 2 this life respect disentangle next of with the probability gain the in information on collected of possibly data terms new be in of In could impact galaxy. the that assessing the (those in in interested focus planets are rather inhabited we of we of particular, and question abundance abiogenesis, present the the the bypass in on involved We scales perspective. time different the a from verse of rate the on knowledge previous (16). abiogenesis our update future would how considered evidence line this along developments Further (15). § ‡ † * owo orsodnemyb drse.Eal mdoblirm2if.tor [email protected] Email: addressed. be claudio.grimaldi@epfl.ch. may correspondence whom To https://asd.gsfc.nasa.gov/firs/ https://asd.gsfc.nasa.gov/luvoir/ http://www.jpl.nasa.gov/habex/. https://www.eso.org/sci/facilities/eelt/. a,hwvr infiatylwrti estimate. this Putative lower significantly . mechanism however, panspermia may, than the through life abundant of imply transfer more would interstellar detection be single to indepen- a even exobiospheres arose population planets, life galactic other if on the Conversely, dently would about exoplanets. volume life-hosting information of sample of added reach such no within in bring distance biosignatures few a that detecting show Earth, we a not methodology, Bayesian from within a Using years planets searches. future light on pres- of the biosignatures out tens detectable ruling or of discovering exploresence either article of This spectro- implications decades. compelling of next the most the way the of by endeavors among worlds scientific is extrasolar detection on biosignature life scopic for search The Significance eew ugs napoc oti rbe ae nthe on based problem this to approach an suggest we Here u td ake h su fhwfeun iei nteuni- the in is life frequent how of issue the tackles study Our NSlicense.y PNAS y . ≈ . 3.8 y o iet vleintelligence evolve to life for Gyr . y https://www.pnas.org/lookup/suppl/ NSLts Articles Latest PNAS ed ´ rl de erale ´ | f6 of 1

ASTRONOMY to the probability that a specific survey can in fact observe habit- i.e., a large probability. Of course, there is no telling if this is a universal able planets. A related relevant question addressed by our study feature of any , but it nevertheless hints to a significant upper is how hypotheses that assign a lower or higher credence to the limit on pd. presence of life outside Earth—i.e., a pessimistic, neutral, or Finally, p1 is the probability that life indeed appears on a habitable planet besides Earth. This is, essentially, the probability of abiogenesis and is a truly optimistic attitude toward —are weighed and ¯ unknown factor, which makes k = pdp1N, the expected number of planets compared in light of new, sparse evidence. Finally, we consider with biosignatures in the , highly indeterminate. how our results are altered when accounting for the possibility In the present work, we leave unaddressed the possibility of both false that the distribution of life is correlated over some characteristic negatives (biosignatures that are present but go undetected) and false distance, such as in panspermia scenarios. positives (gases of abiotic origin that are mistakenly interpreted as prod- ucts of life): however, we note that in principle, both can be incorporated Methods in our formalism through another probability factor, following, for exam- Main Assumptions. Our statistical model assumes that there are N poten- ple, the Bayesian framework outlined in refs. 20 and 21 (SI Appendix, tially habitable planets in the Milky Way (i.e., rocky planets orbiting the section II). Our procedure could also be easily specialized for technosigna- habitable zone of their host star) and that a survey has looked for spec- tures, incorporating the appropriate probabilistic factors, along the lines troscopic biosignatures within a radius R centered around Earth. Statistical of ref. 22. estimates based on available data suggest that the percentage of -like In modeling π(R) we focus on the thin disk component of the galaxy and (GK-type) and M dwarf stars in our galaxy hosting rocky planets in the hab- adopt an axisymmetric model of the number density of exoplanets: itable zone is about 10 to 20% and 24%, respectively (3–5), resulting in a 10 number of potentially habitable planets of order N = 10 . We adopt this e−r/rs e−|z|/zs ρ(r) = N , [4] estimate as a fiducial value for N in our analysis, without referring to the 2 4πr zs particular spectral type of the host star (for a recent analysis of this issue, see s ref. 17). We further assume that the probability of detecting biosignatures where r is the radial distance from the galactic center, z is the height from within the survey volume is p, so that the expected number of biosignature the galactic plane, r = 8.15 kilo-light years (kly), and z = 0.52 kly (23). For detections is s s ¯ R smaller than about 1 kly and taking rE ' 27 kly, the Taylor expansion of k(R) = pNπ(R), [1] 3 3 π(R) for small R yields π(R) ' (4π/3)ρ(rE)R /N = (R/a) , with a = 14.2 kly. where π(R) is the probability of a habitable planet being within R, given by Although Eq. 4 assumes that the density profile of habitable exoplanets is proportional to that of stars in the galaxy, other factors such as the metallic- Z −1 ity gradient may affect the overall radial dependence of ρ(r) (SI Appendix, π(R) = N drρ(r)θ(R − |r − rE|), [2] section III). Throughout this work, we take an observational radius of R = 100 ly where rE is the position vector of the Earth relative to the galactic center which, although corresponding to a galactic fractional volume of only and θ(x) is the Heavyside step function. The number density function, ρ(r), π(R = 100 ly) ' 3.5 × 10−7, is an optimistic upper limit of the search range is defined in such a way that ρ(r)dr gives the expected number of habitable attainable over the next couple of decades. In choosing pa we consider two planets within the volume element dr about r, so that R drρ(r) = N. limiting situations: 1) pa = 1, which corresponds to an ideal survey that has The probability p is a shorthand for the various factors that concur to searched for biosignatures in all of the existing habitable planets within a make the presence of detectable biosignatures possible. In our Bayesian given distance R from Earth, and 2) pa → 0, which corresponds to an exceed- analysis we distinguish the factors ascribed to the selection effects of a ingly small number of targeted planets compared to initial sample size (SI specific survey from those that are truly inherent to the presence of biosig- Appendix, section I). natures. To this end, we adopt a formalism similar to the one first suggested The probability that a survey searching for biosignature within R finds in ref. 18: this is akin to the (19) used in the context of the remotely detectable biosignatures on exactly k = 0, 1, 2, ... exoplanets search for extraterrestrial but adapted to the search for biosig- follows a binomial distribution: natures. In our notation, this reduces to writing down the probability p as the product of independent probabilities: N P (R) = [π(R)p]k[1 − π(R)p]N−k. [5] k k p = papdpl. [3] The average number of exoplanets detectable by the survey is k¯(R) = The first probability, pa, pertains to astrophysical factors and observational ¯ Npπ(R), so that by keeping k(R) finite, the large N limit of Pk(R) reduces limitations. Given an exoplanetary survey, only a fraction of systems will to a Poissonian distribution: be suitable for the search of biosignatures. For example, one may look only for planets in the habitable zone of specific types of stars. The value ¯ k [k(R)] −¯k(R) of p can also account for the fact that not all planets in the habit- Pk(R) = e . [6] a k! able zone of their star will indeed be habitable. Furthermore, there are other selection effects involved in the specific observational strategy: for By rewriting Eq. 1 as example, in a survey, there will be strict requirements on the geo- k¯(R) = kp¯ π(R), [7] metrical configuration of the orbital plane, while a direct imaging survey a will be limited by the variability of the reflected starlight as the planet our analysis translates the outcome of a search for biosignatures into an orbits the star. In principle, a good estimate of pa can be obtained from increase in the posterior information on k¯. In practice, we use Bayes theorem astrophysical and observational considerations. Eventually, a given survey to update the prior probability distribution function (PDF) of k¯, after gath- will only sample the quantity Nπ(R)pa. For example, the number of plan- ering the evidence that exactly k biosignatures are detected in the survey, ets that can be scanned for biosignatures following the TESS survey can which is parameterized by paπ(R). be estimated to be ≈ 4, while it would be ≈ 11 for future ground-based imaging (18). Bayesian Analysis. By isolating the probability factor in p that pertains to The other probability factors in Eq. 3, pd and pl, are not related to a astrophysical and observational constraints, pa, from those referring to the specific survey and pertain exclusively to the likelihood that life-harboring probability of abiogenesis and formation of biotic atmospheres, pd and pl, planets in the galaxy display biosignatures. The probability pd quantifies the we parameterize the survey by paπ(R) and the expected number of exo- ¯ fact that in general, detectable biosignatures are not expected to accom- planets in the entire galaxy producing biosignatures by k = pdplN. Next, we pany all instances of life on a planet. For example, chemical byproducts of denote Ek as the event of detecting exactly k biosignatures during the sur- ¯ ¯ life can significantly alter an exoplanet atmosphere only after some time vey, so that using k(R) = kpaπ(R), Eq. 6 gives the likelihood of Ek being true has passed from the appearance of life. Furthermore, depending on geo- given k¯: logical and astrophysical factors, life might go extinct after a few hundred ¯ k [kpaπ(R)] ¯ million years, as it may have happened on . If we focus on free molec- P(E |k¯) = e−kpaπ(R). [8] k k! ular as the quintessential biosignature gas, this has been remotely ¯ detectable in the Earth atmosphere for ≈ 2 Gyr, roughly half the Earth’s age. We aim to find the posterior PDF of k resulting from the event Ek. To this ¯ If we take this as representative of the average, this would point to pd ≈ 0.5, end we consider the prior PDF of k, that is, the probability distribution we

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Fig. k of likelihood the is where model a as PDF prior the of form functional specific a to refer to ascribe olwn h oi fBys hoe,tepseirPFi hsobtained thus is PDF posterior the theorem, Bayes’ from of logic the Following ¯ min ABC DEF 1 ial,w osdrhr nytoeet eutn rmtesurvey: the from resulting events two only here consider we Finally, ecnie he ifrn oeso h ro endi h interval the in defined prior the of models different three consider We k ¯ ,and ), ,udtdi ih fteeiec,satn rmannnomtv,psiitc n piitcpir(lc ahdcre) h otnoscre refer curves continuous The curves). dashed (black prior optimistic and pessimistic, noninformative, a from starting evidence, the of light in updated ), otmsi model (optimistic to p i a k ¯ = eut o uvysacigframshrcbointrswti distance a within biosignatures atmospheric for searching survey a for Results = max i ie ro D nfr in uniform PDF prior a gives 0 and 0 k ¯ = aee ytesubscript the by labeled eoegteigteevidence the gathering before ie ihyifraiepirfvrn ml ausof values small favoring prior informative highly a gives 2 E 0 p n eeto foebiosignature, one of detection and , a M E k = ¯ p( k 2 p etk initially take We . ). ,gvn h ag fpoaiiista h ennme flf-ern lnt slre than larger is planets life-bearing of number mean the that probabilities of range the giving 1, k ¯ ie h model the given P ( M |M k ¯ (E k p( ¯ k ¯ 0 hsi oee ytkn h noninformed the taking by modeled is this : |M esatb suign ro knowledge prior no assuming by start We min ), k k ¯ i ) |M |E i ∝ 1 = k i 1 = hc ie qa egtt l orders all to weight equal gives which ), k ¯ , ) orsod oannnomdpirwhich prior noninformed a to corresponds 1 M = −i ) for , Z = eas eko o ueta at that sure for know we because d i P kP ¯ = (E M k ¯ k ¯ (E P ,1 2: 1, 0, k min hc togyfvr ag values large favors strongly which , (E . | k k ¯ k ¯ k ¯ | k )p( p min k ¯ max ≤ |M a )p( E k ¯ = k ¯ k to ) |M k ¯ ntefloig ewill we following, the In . ≤ alhbtbepaesi h uvyosre) h limit The observed). survey the in planets habitable (all 1 10 = |M k ¯ ) k ¯ max , i max ) −2 nnnomdmodel (noninformed , N E k ¯ 1 min 10 = IAppendix, (SI n may one , M 8 : which , p( k ¯ p |M a [11] [10] [9] = ). k ¯ oniewt h ros h hddaesi h CFecmastelimiting the encompass CCDF the in areas shaded The priors. the with coincide 0 t abrlf ete eetbeo o) rmorstandpoint, our illustration From plan- of not). other or whether detectable ignore therefore, (either we life Earth, harbor the ets of exclusion the with tance of PDF posterior the w netgt h feto varying of effect the investigate (we biosignatures with planet one in just roughly having to corresponds npriua,reducing of robust particular, assertion is of In nevertheless conclusion initial lowering This will a the prior. against value weakly log-uniform informative noninformative, only biosignatures a added affecting detectable modest, the of remain ly, existence the 100 out within rule will entire surveys as the in weaker for coincide val probabilities even posterior becomes and of prior it smallness the and by ly, naturally explained for is cutoff tion the than upper CCDF, smaller an prior times corresponding being the deviation of than main smaller (CCDF) somewhat function is distribution cumulative range tary the (p survey in complete a line) assuming dashed (long pos- the prior nondetection, of of PDF case the terior In ly. 100 within biosignatures lntwti h niesre oue(R hardly volume survey is entire the within volume planet survey enough small rare such are within biosignatures surprising. none with finding planets that that assuming to i.1A Fig. ycnrs,tedsoeyo isgaue nee single a even on biosignatures of discovery the contrast, By 10 5 R R yohtclrno elztoso h ik a galaxy Way Milky the of realizations random hypothetical = p rmarnol hsnpiti h aay However, galaxy. the in point chosen randomly a from a 0 yfo at.SonaetepseirPF(A–C PDF posterior the are Shown Earth. from ly 100 → k ¯ oprsteipc fosrigo o observing not or observing of impact the compares min hrfr,ee ntehptei htfuture that hypothesis the in even Therefore, 0. k ¯ min k ¯ a ewl eo .Hr etk o h sake the for take we Here 1. below well be can ifr nymrial rmtelog-uniform the from marginally only differs 10 = k ¯ k ¯ max p k ¯ a min −5 rmteeiec ahrdwti dis- a within gathered evidence the from k ¯ = max hslmtdrsos onondetec- to response limited This . ogv nie fhwsalti s it is, this small how of idea an give to : ssonb e hr-ahdcre nthe in curves short-dashed red by shown is 0 and/or below a 1 = k ¯ . k ¯ .Tersligcomplemen- resulting The ). k ¯ max π min (R p k ¯ a NSLts Articles Latest PNAS ) i.S8 ). 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ASTRONOMY bring a response markedly different from the prior: we find a pos- Fig. 1 B and C show the posterior PDFs and CCDFs result- terior PDF strongly peaked around k¯ = 3 × 106 and a probability ing from detection or nondetection starting from a pessimistic exceeding 95% that k¯ > 105. For the sake of comparison, this hypothesis about k¯. While the response to nondetection practi- would imply that exoplanet biosignatures, if distributed homoge- cally coincides with the prior expectation (an unsurprising result, neously throughout the galaxy, are far more common than given that the prior favors small values of k¯), the event of detect- stars. Even larger values of k¯ would be inferred by detecting a ing a biosignature increases the cutoff on k¯ from ∼ 10−3 before biosignature in a sample with few targeted planets, as illustrated the detection to at least ∼ 106 after a biosignature is observed by the limiting case pa = 0 in Fig. 1 A and D (dotted lines) (SI within the entire volume sample (R = 100 ly, pa = 1). In the opti- Appendix, section I). We further note that although changing mistic model of Fig. 1 C and F the prior strongly constrains the k¯min does not modify this conclusion, a detection event assuming posteriors resulting from the events of both detection and non- −1 6 k¯max smaller than π(R) ≈ 10 would bring a response totally detection. In particular, the smallness of π(R) shifts the CCDF −1 independent of the sample fraction pa, hinting to a larger k¯max resulting from the nondetection by a factor of only ∼ 10 in k¯ (SI Appendix, Fig. S8). (Fig. 1F), not justifying thus a substantial revision of the initial To provide a more complete analysis of the noninformed optimistic stance. case, we have considered also the log–log-uniform prior, which has been designed to reflect total ignorance about the num- Model Comparison. By adopting impartial judgement about the ber of conditions conducive to life (24). Although the log–log- probability of Mi being true (i = 0, 1, 2), we compute the Bayes uniform PDF slightly favors large values of k¯, the resulting factor Bij often used in model selection, giving the plausibility posteriors are in semiquantitative agreement with those result- of model Mi compared to Mj in the face of the evidence (i.e., ing from the log-uniform prior of Fig. 1 A and D (SI Appendix, detection or nondetection): section IV).

P(Ek |Mi ) Informative Priors. A log-uniform PDF is probably the best prior Bij (Ek ) = . [12] reflecting the lack of information on k¯ even at the order- P(Ek |Mj ) of-magnitude level. However, it is also worthwhile to explore how more informative prior distributions are updated once As a reference, Bij > 10 is usually considered as strong reason to new evidence is gathered. Two interesting limiting cases are prefer model Mi over Mj . those reflecting a pessimistic or optimistic stance on the ques- Model comparison through the Bayes factor (Fig. 2) shows tion of extraterrestrial life. On one hand, it has been argued that if no detection is made, a pessimistic credence with regard that abiogenesis may result from complex chains of chemi- to extraterrestrial life would strongly increase its likelihood with cal reactions that have a negligibly low probability of occur- respect to an optimistic one, with a Bayes factor above 10, only if ring. Furthermore, contingent events which are thought to have pa is larger than 40%. The increase with respect to a neutral, non- favored an enduring biosphere on Earth (like, for example, a informative stance would be, instead, basically insignificant for stabilizing the rotation axis of the planet, plate tectonic, all pa values. This teaches us that unless future surveys will search etc.) may be so improbable to further lower the population for biosignatures within a significant fraction of the volume of biosignature-bearing exoplanets. This view would result in a within 100 ly (say, pa > 10%), detecting none will not support more pessimistic attitude toward the prior, with small values of convincingly either hypothesis. On the other hand, if a detec- k¯ being preferred with respect to large ones. We model this tion is made, the optimistic scenario would be hugely favored ¯−1 ¯ ¯−2 8 case by adopting the uniform in k prior p(k|M2) ∝ k in (Bayes factor larger than 10 ) with respect to the pessimistic ¯ ¯ the interval kmin to kmax. Conversely, the astronomically large and would be substantially preferable even with respect to a neu- number of rocky planets in the Milky Way combined with the tral position when pa is close to 0. Somewhat counterintuitively, assumption that the Earth is not special in any way (often however, finding a single biosignature within a significant frac- termed “principle of mediocrity”) may suggest the optimistic tion of the volume R = 100 ly (i.e., pa larger than 40 to 50%) hypothesis that life is very common in the galaxy and the uni- would not justify entirely the preference for an optimistic cre- verse, resulting in a prior which weighs large values of k¯ more dence compared to the noninformative hypothesis. These results favorably. We capture this view by taking the uniform in k¯ put on a quantitative and rigorous statistical basis the common ¯ prior p(k|M0). intuitive idea that the discovery of even a single unambiguous

A B 11 40 non-detection 10 detection 30 20 1010

B20 B 109 02 10 (pessimistic/optimistic) (optimistic/pessimistic)

108 4 3 102 Bayes factor 2 1 B21 (pessimistic/noninformative) 10 B01 (optimistic/noninformative) 1 100 0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0

pa pa

Fig. 2. Bayes factor as a function of pa, in a survey searching for atmospheric biosignatures within a distance R = 100 ly. (A) Bayes factor from the comparison of the pessimistic vs. optimistic model (red) and pessimistic vs. noninformative model (blue), when no biosignature detection is made. (B) Bayes factor from the comparison of the optimistic vs. pessimistic model (red) and optimistic vs. noninformative model (blue), when exactly one biosignature detection is made.

4 of 6 | www.pnas.org/cgi/doi/10.1073/pnas.2007560117 Balbi and Grimaldi Downloaded by guest on September 30, 2021 Downloaded by guest on September 30, 2021 ab n Grimaldi and Balbi χ lnt ihnarltv distance relative a within planets g and where relative the on pair depends the it distance for that model assuming simple by significance a function, presence distribution adopt statistical the We the how detection. impact biosignature in of would interested correlations only generic are stud- of future we for here subject However, interesting an ies. be could This abio- (29). independent an genesis from might observationally scenarios distinguished be various even and mechanisms, panspermia specific to in on also present present are being biosignatures function of distribution probability pair the where rewriting and biosignatures of correlation we that scale biosphere. length a typical establishing and a on and that depend denote distance probability will relative the biosignatures well their occur, as simultaneously on can inhabited produce panspermia is planets if planet nearby two way, probability a this enhanced if In an inhabited (29). in is result planet scale would a time that favor this short transfer, relatively conditions a clus- the If within stellar after biosphere (25–28). a in distances of system, flourishing interstellar the stellar over same or to the transferred ters, according be within However, example, might planets, For well. life case. among as scenario, the panspermia life be hypothetical harbor not the may planets this other general, not in or independently whether life harboring of of probability some has planet given the Scenarios. Panspermia of toward Impact attitude our life. extraterrestrial change of frequency radically would biosignature 10 value length correlation p 3. Fig. .N .Btla xlrn xpae ouain ihNS’ elrMission. Kepler Cassan NASA’s A. with 2. populations exoplanet Exploring Batalha, M. N. 1. A a (|r

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) 5 1, + probability k  10 − ) 0.0 0.2 0.4 0.6 0.8 1.0 ie h relative the gives r sfollows: as 10 r fbiosignatures if E -2 |), p a χ =0.1 1 = 10 while , -1 ξ R (C . [14] [13] Proc. rmEarth, from ae atrfo h oprsno h piitcv.nnnomtv model. noninformative vs. optimistic the of comparison the from factor Bayes )   100 10 10 =1 50 (kly) 0 nieglx sgvnby given is galaxy entire ueadFte rnlnFn,adnravsdfn fSlcnValley Silicon of fund donor-advised a Fund, Franklin Foundation. Fetzer Community Grants by and and Insti- Questions Space) tute Foundational in the from Life FQXi-MGB-1924 U.O and FQXi-MGA-1801 2019-3 Grant (DC-VUM-2017-034, Agency ACKNOWLEDGMENTS. Appendix. life Availability. Data of discovery possible the of order significance in Earth. beyond space), the deep weaken in to experimental not of survivability through the example, of (for studies should independently scenario panspermia assessed the of be viability conclu- the This that one. suggests optimistic sion the for over hypothesis and noninformative (χ elsewhere, correlation detected nonin- complete is the a to life respect when with knowledge on scenario Depending optimistic one. the formative of 3C) (Fig. volume with case, around uncorrelated maximum the broad to respect with within biosignatures. harboring exoplanets of fraction maximum imposing by satisfied matically 13 p flf sdtce na nopeesml (with sample incomplete an in detected is life if of values larger much For k number total the planets, than biosignatures of with planets more be cannot parameter The ern lnt nteglx slre hnagvnvle(taken value given a life- than of larger number is the galaxy as the that in probability planets the bearing account, into taken are and galaxy, unity. entire approach the through homogeneously ¯ .J .Zn,B .S asn conigfrmlilct ncluaigeaEarth. eta calculating in multiplicity for Accounting Hansen, S. orbiting M. planets B. Earth-size Zink, of K. J. Prevalence Marcy, 4. W. G. Howard, W. A. Petigura, A. E. 3. (R = h vrg ubro biosignatures of number average the 3A, Fig. in shown As i.3B Fig. o.R srn Soc. Astron. R. Not. u-iestars. sun-like 10 eue to reduces k ¯ p ) ,oe h oa number total the over (R), 5 a ≤ p 10 R o h aeo lutain erae usatal even substantially decreases illustration) of sake the for d N R k p 1 ¯ , (R l hw hti osbecreain ntebiosignatures the in correlations possible if that shows (R 100 = k ¯ h vrg ubro xpae isgaue nthe in biosignatures exoplanet of number average the , N (R ) rc al cd c.U.S.A. Sci. Acad. Natl. Proc. = ) (R o any for esehne ytepnpri mechanism panspermia the by enhanced gets ), χ 10 = ) kp ¯ y hssosa eraei h ae factor Bayes the in decrease a as shows This ly. 4–5 (2019). 246–252 487, l aaaeicue ntemnsrp and manuscript the in included are data All sntubudd swti n radius any within as unbounded, not is 2 a

N Bayes factor B ..akolde upr yteIainSpace Italian the by support acknowledges A.B. R 01 C π d

R (optimistic/noninformative) (R rρ()g 0.1 k ¯ 10 For . ξ 1 10 otie within contained ), = ol vnsrnl ao the favor strongly even would 100) = 10 = -2 k ¯ R ξ p p asemawuddsrbt life distribute would panspermia , nteetr aay safnto fthe of function a as galaxy, entire the in d d a (|r χ =0.1 R ξ p rρ()g 3 l ≤ and 97–97 (2013). 19273–19278 110, < − R eto IIIB ). section , Appendix (SI ly 10 N d 1 r rρ()g E -1 / hr a en anin gain no be may there χ, l,ti odto sauto- is condition this kly, (|r |)θ k ¯ max NSLts Articles Latest PNAS (R − k ¯  slre hnareference a than larger is 100 (|r where ,  r 50 10 10 |r − =1 E (kly) |) k 0 ¯ R − (R nohrwords, other In . r − p E k )/ ¯ a k r ¯ | (R ota Eq. that so ), E 0 = max k ¯ R 10 |) = )/ hwn a showing ξ 1 . nthe in .1) /N 0 yand ly 100 k ≈ ¯ R | there , 10 would sthe is f6 of 5 [15] Mon. 3 10 SI ly 2

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