Looking for Neo-Tokyo in the Kuiper Belt

In Loeb & Turner (2012), a new Solar System SETI method is described. If Kuiper Belt objects (KBOs) are artificially illuminated, we should be able to detect that based on how their brightness changes with distance (both from us and the sun).

If a KBO has artificial illumination on its surface, then its brightness should only decrease with distance (from us on Earth) squared (a geometric effect of the intensity of the light diluting as it gets further from the source, see Wikipedia’s explanation). But, if a KBO is illuminated solely by the Sun (as we expect them to be), the light is coming from the Sun, so the light gets diluted twice and we would expect it to decrease with distance to the fourth power. The distance from the Sun to the KBO and from the Earth to the KBO are essentially the same because the Earth is relatively close to the Sun. KBOs are 30-50 AU away from the Sun while Earth orbits snuggly at 1 AU. So the distances can only be different by at most at most ~3%, a subtlety I feel should have been made explicit in the paper. Presumably this power law identification could be performed (at least in a rudimentary sense) by putting the data into log space and identifying the linear trend of brightness as a function of distance (hopefully with a slope of -2).

With the completion of the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) and the Large Synoptic Survey Telescope (LSST), there will be an explosion of discoveries of new KBOs (finding ~10-100x more than we know about now). This should open up a window for this new type of proposed search.

Another interesting tidbit was the use of a unit defined as 1% of the solar daylight illumination of Earth, ~ 1.4 · 10^4 erg/(s cm^2). They state that this corresponds roughly to the illumination in a brightly lit office or to that provided by the Sun just as it rises or sets in a clear sky on Earth. I spent an inordinate amount of time wrestling with this fact, as it is repeatedly used as a baseline in the paper and is not immediately obvious to me what this statement even means. It doesn’t feel like outside my office is 100x brighter on a sunny day, but who knows.

Loeb and Turner (2012) Summary

This paper discusses the possibility of detecting artificial illuminated objects in the outskirt of solar system by measuring the flux variation with respect to distance.

The authors begin by arguing that there are two basic illumination classes we use, one is thermal (light bulb) and the other one is quantum (LED). The spectra of those light sources should be very different from natural sources. Therefore, it is possible to detect those sources.

Further, the authors discuss whether we could detect those sources with our current technology and their conclusion is that we could be able to detect illumination level on the equivalent scale of large cities on Earth out to the outskirt of Solar system.

Additionally, the authors quantitatively calculate the flux versus distance slope difference between artificial objects (-2) and natural sources (-4). There are other factors that could affect this slope, including changing phase angle. Those factors influence the flux variation on the scale of 0.1 magnitude and should be able to be averaged out by long period of observation.

Finally, the authors argue that the chances of detecting such objects will be higher when the “dark side of the planet is more in view” or the host star of planet has went into a white dwarf so that the light contrast will be higher.

Cost vs. Plausibility, Stingrays, and Lunar Spelunking

The approach of Davies and Wagner (2013) is a good one as far as SETI papers go, so I’ll start with a quick summary of the salient points.

The primary point of the paper is that a search of data from the Lunar Reconnaissance Orbiter should be performed, looking for anything out-of-place that indicates the presence of non-terrestrial artifacts (or NTAs, to borrow a phrase from Haqq-Misra and Kopparapu (2012)) or past non-terrestrial activity. The authors argue that the moon is a good place to search for artifacts for many reasons: it’s close and we have good, high-resolution data of it, the surface is unchanging (on a hundreds of millions of year timescale), and it’s tectonically inactive, so we don’t have to worry about the artifact’s signature being swamped by thermal/radioactive/magnetic processes from geological action (like we would have on the Earth).

Look at this cute lil’ orbiter

The authors then divide potential NTAs into four classes, based on assumptions that they openly admit are anthropocentric (which is refreshing, compared to some of the other papers we’ve read).

The first class is messages, things that are “deliberate” in catching our attention. One thing to keep in mind is how long the message might have been waiting there – the longer it needs to last, the harder it will be for us to find due to the trade-off of detectability and durability.

The second class is scientific instruments, which have a nice symmetric pro and con. Con: they wouldn’t’ve been made for us to find, so they may not be easy to spot or recognize. Pro: instruments need power supplies, and power supplies are more easily detectable (think solar panels or waste heat).

The third class is trash – things left over from prior expeditions and never cleared away – a category that humans are particularly good at. The authors make a case for searching in lava tubes – trash left there would be protected from asteroid impacts and could lay undisturbed for far longer than something on the surface. I’ll be the first to admit that lunar spelunking for alien artifacts sounds like the most epic job posting ever, but it probably isn’t realistic to expect that a search like that would occur any time soon, even if we had any reason to believe it would be successful.

The final class of NTA is “geo-engineering”, or scars on the moon’s surface left behind by some prior alien activity (mining? excavations? who knows). Features created by geo-engineering might be easier to spot with the data based on scale, but the difficulties come in trying to decide which features are natural vs. NTAs, and which features are even interesting in the first place.

At the end of the paper, having defined some idea of what we might be looking for, the authors give some examples of ways to search the already extant LRO photographic dataset for these features. I decided to organize and expand on their suggestions in the following table:

This table is specifically in reference to the problem of searching for NTAs in LRO photographs, but it could be easily generalized to any big-data SETI project, and even many big-data projects in general. I think this is a useful summary for thinking about the problem of big-data, and a good argument for why the multiple-pronged approach that was being tried by the authors is the way to go.

{Side note: I am a huge proponent for citizen science as a way to make scientific progress while educating and engaging the public. I participated in many citizen science projects in middle and high school, and led a Seafloor Explorer competition for 20 middle school students that classified the objects and wildlife in ~10,000 images of the Atlantic seafloor. The gallery below shows some of the images that my students got very excited about in the classifying process. Applying a citizen science strategy to SETI could be very useful…}

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To end this post, I’m going to change gears and get a little philosophical for a moment. The authors make an interesting case for pursuing SETI in large, already existing databases – many SETI ideas are low cost and high potential reward projects and should be pursued based on cost over plausibility. I still don’t entirely know how I feel about that idea. Could that mentality be politically destructive for SETI in the current funding landscape, and should that matter if science is being done and progress is being made? Does it lend legitimacy to fringe-sounding ideas, like the genomic SETI concept that the authors mention (ex. this paper), or does spending a little bit of effort to test and debunk these ideas actually make the field better in the long run? Are we uncertain enough about the nature of ETI that disregarding plausibility and just prioritizing by cost is actually a more logically consistent way to go about the search?

I don’t have answers, but I think these are interesting questions and we should keep mulling over them.


Is the 9 dimensional haystack enough?

In this post I shall build upon some of the discussion from  Paul Davies (2013).  The article describes a search effort which uses data from the Lunar Reconnaissance Orbiter. They attempt to use data from this satellite with a resolution of about 50 cm/pixel, to find artifacts of ET on the Moon.

An important consideration in this search is the size of the data set that needs to be sifted through. The complete data set is expected to contain about a million frames of 500 Megabytes each, which translates to about 500 Terabytes in all. The search is for something left behind accidentally or on purpose by alien civilizations, a la  Transformers: Dark of the Moon (but mostly smaller?).

The challenge over here is that it is simply to numerous for a human or groups of humans to go over the entire data set manually, and the computer algorithms being used are not necessarily primed to look for signatures or anomalies highlighting the artificial origin. Another example of this is the Kepler mission. It has looked at more than 100,000 stars. A great search technique to find Dyson swarms, or other hallmarks of advanced ET civilization in orbit around a star. The periodic dip if caused not by a planet, but a irregular (non spherical structure) would encode information about its structure, in the residuals.  As has been discussed in Wright et al. (2016), there are a number of anomalies in exoplanet science which might be from astrophysical phenomenon or possibly from an advanced ET civilization. If we find more than one such anomaly in a system, it would be difficult to attribute it to natural sources.

Therefore, from a SETI point of view there is a LOT of information in these giant data sets from missions like Kepler, TESS, LSST, among others. Citizen Science initiatives do help in this by using human cognitive abilities in pattern recognition to pick out these anomalies and outliers; arguably better than any computer can do.  However, when it comes to automated pipelines, we should quantify their efficacy.

The point I would like to make here, is that in the era where we are transcending the radio region of the electromagnetic spectrum into the optical and infrared, we must make use of these existing big astrophysical missions and include them in our quantification of the search volume probed for ET.  However, I propose that we must add a 10th dimension to this haystack which quantifies the ability of our data pipeline to retrieve these signals IF we were to receive them. By this I mean, if there is a pipeline which is analyzing an existing database to find anomalies, the completeness fraction of that pipeline should also be quantified. By inserting artificial signals into the data, and counting the ones we retrieve, this can be done. However, that is an overtly simplistic view of this problem. This is not an easy task since we do not know the nature of these signals and can hence only hypothesize and to a certain extent – guess.

This way we could include Kepler, and other such missions in our search volume (volume searched by all SETI projects so far) using their actual efficiency and not a mere theoretical one.  This 10th dimension fraction should ideally be close to unity for most searches, however as mentioned in the paragraph above, in the absence of knowledge about the nature of the signal we can only hypothesize using our current understanding of Physics.


Addendum: 2018 – 04 – 30

After further research and work on the 9-dimensional haystack , I realize that in the original Haystack proposed by Jill Tarter in 2010, this ability to retrieve potential signals from the data is exactly what she meant in the modulation axis.

9 suffices. Phew!

Scrapyard SETI (Get an Undergrad to Do It)

In Davies & Wagner (2013), the authors describe and motivate an ongoing (circa 2013) search of Lunar Reconnaissance Orbiter imagery for unusual features at the LRO Laboratory at Arizona State University.

The first point of note that I found in the paper was the initial statement of assumptions. They state that anything we could find (outside of communication SETI) will most likely be something “post-biological” due to the long timescales we would have expected it to last. Then they directly state that we have no reasonable way to extrapolate our own technology to guess what type of artifacts we should be looking for. An openness I found refreshing.

What follows is an intriguing and frank basis of motivation for the search of the LRO database (or any database). In the case that we don’t know what we are looking for, they propose that the best way to make meaningful progress with limited resources is to simply search all existing databases for “artificiality” and that choosing which databases to search should be tied only to cost rather than the likelihood of results. This was an interesting thought. Cost is obviously a good thing to keep in mind when deciding on what to do with resources, but in every other field, missions and grants are proposed and evaluated with heavy basis placed on their merit. But what is it is nearly impossible to quantify the merit of an experiment?  We can estimate the number of planets TESS will find (>20,000) or the amount of stars GAIA will get parallax for (>1 billion), but there’s no way for us to know the amount of ETI signatures will be found by performing any given search (although, one could cheekily say 0 based on the results of all other searches). While this seems to make sense at first glance, I think it makes some false equivalencies. Just because we don’t know the utility of two different searches does not mean their utility is equal, as this line of thinking implies. If cost is the only thing that matters, I should just submit two half-cost proposals that each cover half of a database. That’s two half-cost searches for the price of one! In the same vein, some databases are clearly more valuable to search than others. Imagine two equivalent cameras take pictures of the Martian surface, the only difference being one of the cameras can take pictures of much higher resolution. It is clear that while it would be more expensive, looking at the higher resolution data would be much more useful. While it is difficult to quantify the utility of SETI searches, they can be viewed as setting limits on the parameter space (a la Jill Tarter’s Needle In A Cosmic Haystack) that SETI artifacts can inhabit (see Appendix A Wright & Oman-Reagan (2017) for a motivation of this type of quantification).

Besides these points, the authors discuss how automation is ill-suited towards artifact SETI as we have to program in exactly what signatures we want to look for. Currently, they have some students and faculty searching the Narrow Angle Camera images for interesting features by eye. They suggest that the best strategy may be to utilize the time of enthusiastic volunteers to perform the image analysis.

Searching for Monoliths: When Science Fiction Informs Science Reality

In 1999, American satellites in orbit around the moon detected a strange magnetic anomaly emanating from within the crater designated Tycho. An early explanation for origin of the anomaly source was a ferrous meteorite, but that could not account for the strength of the produced magnetic field. A few years later in 2001, an expedition to the anomaly site was dispatched from the lunar base at Clavius. The team was led by astrophysicist and former chair of the US National Council of Astronautics, Dr. Heywood Floyd. The expedition revealed a structure, in more ways than one similar to a black box, with rectangular prismatic dimensions in the ratio of the squares of the first three nonzero natural numbers. This ratio held even when the distances were measured at the finest resolution afforded by modern instruments. Subsequent radioisotopic dating of the surrounding regolith implied that the structure had remained in place for some three million years, long before any lunar activity attributable to any human nation and in fact older than the genus \textit{Homo} itself. Given its age and unnatural design, scientists were led to conclude that the object is not of this world nor of this solar system, but actually an emissary of some advanced extraterrestrial civilization sent to monitor the development of the human race.

Does it sound like science fiction? The above story is indeed fictional and is actually lifted from the plot of 2001: A Space Odyssey, a film and novel by Stanley Kubrick and Arthur C. Clarke (which itself is influenced by Clarke’s earlier short story The Sentinel). However, this is fundamentally the type of object that SETI scientists are now seriously contemplating searching for! (As such, we should be mindful of the great ideas that have come to us from science fiction.) Setting aside great storytelling, one of the core ideas of this film was that the Earth had been visited in the remote past by an alien intelligence who established and left behind artifacts after their survey of the solar system was complete. Whether the artifacts were left deliberately or otherwise inadvertently is less important as is the fundamental question of whether or not it is possible for us to perform an exhaustive search for them. In 2013 (nonfiction timeline), Davies & Wagner suggested exactly this kind of search and also overviewed the kinds of strategies we might use to detect a variety of signatures which would suggest that the Moon had been visited in the remote past. These strategies revolve around searching through the Lunar Reconnaissance Orbiter (LRO) data, which offers high resolution imaging of the lunar surface. In this way, SETI science can “piggyback” off the gains of traditional science, which often acquires data that can dually be utilized for SETI purposes. (Imagine the difficulty of justifying a complete surface map of the Moon for the explicit purpose of searching for alien artifacts in a mission proposal to NASA!) With the LRO data, we are afforded the ability to search for 1-10m class objects which could be the detritus, message-carrier structures, habitats, or instruments of a past alien visitation.

This paper is the logical continuation of the Bracewell 1960 paper applied to the specific case of stationary (possibly perpetually ensconced by craters or more likely subterranean) artifacts on or near the surface of solar system bodies. (The original paper did not deal with this case, but focused more on probes in orbit, which was later expounded upon by Freitas 1983.) In my reaction to Bracewell, I suggested how a search for exposed artifacts on the surface of solar system bodies could be a feasible project given modern artificial item recognition software and machine learning algorithms. However, as the authors point out, there are difficulties with the lifetimes of exposed structures given that any region on the surface of the Moon, for example, is likely to be struck by impactors on vast geological timescales, releasing energies which no known materials would be immune to. This problem arises since the progenitor civilization is expected to be truly primordial given the expanses of cosmic time, and hence their probe is likely to be millions or possibly even billions of years old. Therefore, the artifacts would probably be buried and a subsurface search conducted with penetrating radar or by a human expedition is motivated for the future. For the present however, we are limited to “relatively” recently deposited surface objects which could have been picked up in the LRO survey maps. To process this vast amount of data presents another issue, since although it could be processed without automation, it would probably require tens of thousands of man-hours to sift through it all. The cost and upkeep of such an effort would obviously defeat the purpose of a low-cost, low-effort SETI search. In the case of automation however, machine learning algorithms are limited to identifying only those objects on which it is trained to identify. For example, a machine may be exquisitely capable of identifying particular geometrical shapes, but who is to say that an artifact need be perfectly geometrical? And what of partial or nearly complete obscuration by lunar regolith built up over time? The corner of a cubical object protruding from the ground would be missed by a machine trained to search for cubes. These many difficulties make the whole idea altogether less appealing. Until a general purpose artificial intelligence or serious effort of crowd-sourced volunteers can be employed on such a task, the completeness of the search will remain low. This should not be upsetting though, because as long as the search is incomplete there is still some chance for a positive detection. Who can say, perhaps Clarke and Kubrick will be vindicated some time within this century! (As a humorous aside, it was recounted by Clarke how the astronauts of Apollo 8 were tempted to radio back that they had seen an enigmatic black structure on the surface from orbit, but they decided that it would be in poor taste.)  Nonetheless, it is clear that the search is on for evidence of alien artifacts within the solar system, a search that is certainly nowhere near over.

SETI can be cheap; let’s do it

This post won’t really include much about Davies & Wagner 2013, expect for one line:

“[T]he criteria for searching a database should be primarily tied to cost rather than plausibility. If it costs little to scan data for signs of intelligent manipulation, little is lost in doing so, even though the probability of detecting alien technology at work may be exceedingly low.”

This is remarkably well said, and I completely agree. A huge argument against SETI is that nothing has been found yet, so it’s a waste to keep looking. While this argument is fallacious in itself, it can quite easily be rebutted with the above statement. If searching requires little time/money/effort, than there is no waste.

One great thing about SETI is that it (normally) does not require its own dataset. Astronomers are already observing interesting targets with different instruments at different wavelengths, either to catalog them or to look for anomalies. Any anomalies discovered will probably be scrutinized, so why not borrow the data and look at it from a SETI point of view? There are currently many algorithms searching datasets now (a solution to our big data problems), so altering these algorithms just slightly to look for expected ETI alterations or just anomalies takes minimal effort and, if the algorithm is light, has minimal computation costs. Such searches could even just piggyback off of current searches (flag anomalies) such that there is no additional computational costs.

Davies and Wagner specifically motivate looking through all of the wonderful data we have on the Moon, noting that because the resolution is so great, many artifacts/trash would be visible (assuming they aren’t buried in regolith). Personally I think that looking at these by eye is not the way to go, and that the search should be automated. It would also be neat if some machine learning were applied to find such artifacts, but this would require some kind of training set and therefore not only more work/time/money but also some kind of assumptions about the sizes and shapes of alien artifacts.

I think it would be really neat if someone were to dedicate some time (probably unpaid =/) to developing algorithms for finding anomalies in all of the (mostly planetary) datasets we have (images, transits, gravity anomalies, all-sky surveys in every wavelength). This would not take much, and the algorithms could just run in the background. Follow-ups for any flagged anomalies would include compilation of all possible data and either human or artificial analysis to somehow rank how anomalous the data are. This would simply be really awesome.


The Mock Side of the Moon

If extraterrestrial intelligence has visited the moon, there may be signs of their activities. Or, at least, astrophysicist Paul Davies and his student Robert Wagner seem to think so. In a paper published in Acta Astronautica, Davies and Wagner argue that scrutinizing the surface of the moon for extraterrestrial artifacts may prove beneficial in the search for extraterrestrial intelligence (SETI). They argue this can be archived with the data from NASA’s Lunar Reconnaissance Orbiter (LRO). The mission of the LRO is to serve as a lunar mapping program to flag potential landing sites and characterize the radiation environment, among other things. LRO has the capability to obtain photographs of the lunar surface up to 50 centimeters per pixel using the Narrow Angle Camera (NAC, see Figure 1). The high resolution is required to provide the greatest sensitivity for a correct detect, and mitigate cases like the Martian face. Davies and Wagner believe the hundreds of thousands of photographs provided by NAC can be capitalized for SETI, much like IRAS and WISE have been.

Figure 1: Two LRO images from 2009 (early mission image) and 2011 showing signs of human activity on the moon and the need for high resolution images! Davies and Wagner propose to look at the entirety of images captured by LRO to search for extraterrestrial remnants on the moon. It is easy to detect these surface features as we know where and what to look for. The search for unnatural features on the moon would require extensive human effort or automation of some sort. The images do not line up perfectly because of differences in lighting conditions, angle of the LRO Camera, and other variables. Image brightness and contrast have been altered to highlight surface details. Source: NASA’s Goddard Space Flight Center/ASU

To further bolster their claim, the authors contemplate the types of extraterrestrial artifacts (ETAs) that would persist through the regolith on the lunar surface. They largely consider four classes of artifacts:

  1. Messages, or artifacts designed to be found and interpreted by an intelligent species,
  2. scientific instruments, or observational devices sent across interstellar space (e.g. probes) or remnants of an alien expedition to the moon with potential functionality,
  3. trash, or objects left behind by alien expeditions without any regards to its survival (e.g. radioactive waste, spacecraft remnants), and
  4. geo-engineering structures, or changes to the moon due to alien activities (e.g. mining or construction).

The most attractive scenario for Davies and Wagner would be for aliens to have left a message a few million years ago. They argue anything older than this would be buried on the moon or have been destroyed by meteoric impacts. Such a message could be near an existing landmark on the moon or have a “radio beacon”. On the case of scientific instrument, the search would most likely favor a search for electromagnetic emissions as opposed to a photographic search. The authors note they have searched the poles for signs of “alien solar arrays” and nothing has been identified yet. Robust searches for extraterrestrial trash or geo-engineering would require something other than photography. However, Davies and Wagner argue potential searches include near lava tubes (for trash) and for artificial topographic features (e.g. open-cast mine). Perhaps the most important outcome is the extent of the search. While only 25% of the lunar surface was imaged at the time, the authors have only been able to automate the search for simple pits. They emphasize the need for crowd-sourcing and citizen science (like the now defunct Moon Zoo) in this endeavor as we do not know a priori what to look for.

Movie 1: The moon has been able to keep its secrets until now! Dexter makes an odd observation about the moon (it’s been geo-engineered into a Martian base) and goes to find out what is causing it. He discovers Martians on the moon in a sub-lunar city planning to attack Earth – essentially SETI/SETA in a nut shell as anything is possible with enough imagination. Davies and Wagner propose LRO observe the lunar surface, but for all we know there could interesting things beneath the surface. Source: Dexter’s Laboratory, Cartoon Network/Hanna-Barbera.

While it is a benign project, the premise belongs in science fiction. Davies and Wagner present a very anthropocentric view on ETAs, going so far as to consider “a simple capsule … with a … splash of paint” and “round, open-cast mine[s]” to argue for some of their unorthodox targets. It would appear they want to search for human-like aliens. If we ascribe such human features to them, then perhaps we should consider other searches for them (see Table 1). Freitas Jr. has presented a new approach to SETI in searching for probes that includes the moon and other parts of our Solar System. With all this talk of ETA, this blogger is reminded of a cartoon (see Movie 1) where the strange observations of the moon led to the discovery of a sub-lunar city of Martians. It seems so outlandish, but if we are using our imagination to guess aliens are or have been on the Moon, why stop at the surface? If we consider aliens that are so advanced as to have explored the moon, why should anything they leave be obvious to us on the surface? As with SETI, the lack of data is a problem and makes this search worth a modicum of effort, however tepid and benign the results may be.

Table 1. Cost-Effectiveness Hierarchy of SETI Objective (from Interstellar probes – A new approach to SETI, Robert A. Freitas Jr.)
Estimated Cost
SETI Search Method To Be Employed
Small -instrument visual/photometric artifact searches of Earth-Moon libration orbits to mag. +18
Infrared search for “warm” artifacts (T ³ 50 K) in Earth-Moon libration and solar polar orbits
Radar search for small artifacts in Earth-Moon libration and solar polar orbits (Goldstone, Arecibo)
Continuing ad hoc beacon searches at various radio frequencies, employing as many new and different search procedures as can be devised
Large-instrument artifact search of Earth-Moon libration and solar polar orbits to mag. +25
Large-instrument ecliptic survey to mag. +20/+25, looking for evidence of incoming fusion braking rockets, solar sails, interstellar ramjet plumes, laser pushbeam backlighting, or relic corner reflectors
Proposed NASA Ames/JPL extrasolar radio beacon survey to 100-1000 light-years, using 109 channel MCSA at waterhole frequencies
Beam call signals toward Earth-Moon, Earth-Sol, and Jupiter-Sol libration orbits, and solar polar orbits, using waterhole and other appropriate SETI frequencies
Unmanned photographic/sampler probe to Earth-Moon libration orbits. looking for ET artifacts
Unmanned photographic/sampler probe to Earth-Sol libration points, looking for ET artifacts
Unmanned lunar orbiter/lander, surface mapping and artifact search
Unmanned photographic/sampler probe to Jupiter Sol libration points, looking for ET artifacts
Extended MCSA radio beacon surveys to 1000 light years, across 1-100 GHz
Unmanned mobile Mars lander and orbiter/lander to Martian moons, surface mapping and artifact search
Unmanned mobile lander/orbiter to inner planet, outer planets and moons, surface mapping and artifact search
Manned exploration of Earth’s Moon, surface mapping and artifact search
Full ground-based Cyclops/Orbital Cyclops/”Lunarcibo” radio beacon search to high sensitivity out to 1000-10,000 light-years
Full ground-based Cyclops/Orbital Cyclops/”Lunarcibo” eavesdropping search to high sensitivity out to 10,000 light- years for Type I civilizations, intergalactic range for Type II civilizations
Unmanned mobile lander/orbiter probes to Asteroid Belt, surface mapping and artifact searches
Manned exploration Of Mars and Martian moons
Manned exploration of inner, planets, outer planets and moons
Manned exploration of the Asteroid Belt

Searching for alien artifacts on the moon summary

The paper discusses the possibility of searching indirect ETI evidence using the images taken from the Lunar Reconnaissance Orbiter (LRO).

The authors begin by arguing the advantages of searching for ETI on the Moon. First, the Moon is very close to the Earth, so we could observe the features on the Moon in detail. Second, the surface of the Moon is rarely changed due to the low impact rate from meteorites. Therefore, any large artifacts left by ETI on the Moon should preserve for a quite long time for us to search.

Then the authors classify the kind of artifacts into four categories: 1) messages 2) scientific instruments 3) trash 4) geo-engineering structures. For messages, the authors argue that the chance of finding such messages on the surface might be low. Further recovery of such message might depend on radar technology or excavation. For scientific instruments, the authors argue that it might be worthwhile to look for solar panels at the poles of the Moon but LRO did not find anything. As for trash and geo-engineering structures, the authors suggest future excavation missions might find interesting features.

Finally, the authors discuss how they would carry out the search using the existing data base. First, they suggest either hiring people to examine the images or do a computer automated scan. The problem with computer automation is that it could only find specific features. But we could expect any kind of strange features from ETI.

Response to Davies & Wagner (2013)

The authors argue for the merit of conducting a search for alien artifacts on the surface of the Moon. While they readily acknowledge that the odds of success are exceedingly low, they correctly state that the payoff is enormous. Furthermore, they emphasize the ability and importance of conducting searches using presently available surveys and catalogs, i.e., with very little additional cost or effort beyond those already expended for traditional astronomical endeavors. In this way, the authors are suggesting new search methods.

The surface of the Moon serves as an attractive prospect for hosting alien artifacts for three main reasons: (1) it is nearby, (2) it is largely unchanging, as the rate of meteorite impacts is relatively low, and (3) it is inactive, so artifacts will not have to compete with signals of natural origin. The Lunar Reconnaissance Orbiter provides a powerful opportunity to conduct a comprehensive search of the Moon’s surface.

The authors suggest four main classes of artifacts that could conceivably be found on the Moon. The most attractive prospect is in the form of a message, as it communicates both the existence of an ETI and its willingness to communicate with us. Almost as attractive is the prospect of finding scientific equipment/tools, as these could provide some information about the nature of the ETI. Two other possibilities include finding signatures of past visits by an ETI, either in the form of trash that was left behind, or by finding changes to the Moon’s surface of artificial origin (such as mining).

In my opinion, the most important aspect of this study is the emphasis on utilizing catalogs, surveys, and missions that are already available. This approach will maximize the overall possible search space and enable quicker exploration of the search space. Furthermore, the concept of using citizen science to conduct the search seemingly holds great potential, as many other recent astronomical efforts have utilized a similar approach.