Earth has many unique features for a planet, such as a magnetic field, a large moon, and plate tectonics. It’s also the only planet we know of that harbors life. These facts form the basis of the Rare Earth hypothesis, which posits that we haven’t found aliens because other planets in the Galaxy probably don’t have all the right conditions for life. 

Another characteristic of Earth is that about 30% of its surface is land and about 70% is ocean. Recently, Columbia University Assistant Professor David Kipping investigated whether the proportion of Earth’s surface covered by dry land versus ocean, or its land fraction, is another reason Earth is habitable not only for simple single-celled organisms, but also for intelligent species like humans. 

To test this hypothesis, Kipping created 4 statistical models of planets with different land fractions that intelligent aliens could potentially evolve on. First, he created an equation to describe the likelihood that a planet in its star’s habitable zone has a particular land fraction, known as a probability distribution. Kipping weighted this probability distribution toward the extreme ends, making it more likely that a planet would be covered by a single huge landmass or a single vast ocean than by a mix of both, as on Earth. 

Kipping then incorporated this land fraction probability distribution into his statistical models to calculate the probability that a random planet will have that land fraction and host intelligent life. The 4 scenarios Kipping tested were: 1) that intelligent life is more likely to emerge on land-dominated planets, 2) that it’s more likely to emerge on ocean-dominated planets, 3) that it’s more likely to emerge on planets with roughly equal amounts of land and ocean, and 4) that its emergence is independent of a planet’s land fraction. 

As a first step in determining the kinds of planets intelligent aliens would tend to emerge on, Kipping used each model to predict the probability that intelligent life would emerge on a planet with the same land fraction as Earth. He then compared these probabilities by calculating the ratios between each value. Because Earth is the only known planet with intelligent life, a model that predicted a greater probability for humanity’s existence on Earth would be more likely to reflect reality.

Kipping considered it strong evidence that a given model was more realistic than another if the ratio between 2 of them was greater than 10, meaning one model was 10 times more likely to predict the existence of Earth and humanity. Kipping found that no comparison of any 2 models passed this threshold. However, the models assuming that intelligent life prefers ocean-dominated planets or planets with a land-ocean balance were 2.5 and 3 times more likely to predict the existence of humanity than the model assuming that intelligent life prefers land-dominated planets. Additionally, the model assuming that intelligent life prefers a land-ocean balance was always more likely to predict humanity than any other model, though marginally. 

Kipping also addressed whether finding more planets with intelligent life would affect which model was deemed most realistic, for example, if scientists discovered conclusive evidence of life on Mars in its distant past. Here, Kipping identified 2 complications. First, it’s uncertain how much of Mars’s surface was once covered by water – some estimate it had a land fraction as high as 81%, while others estimate it was as low as 25%. Second, proving that Mars once had life would not prove it once had intelligent life.

Regardless, Kipping reran the models assuming that ancient Mars had a land fraction comparable to Earth’s. Adding this second data point produced ratios similar to those in the earlier Earth-only calculations, meaning it still didn’t make any single model 10 times more likely to predict the existence of humans and Martians, respectively. 

Kipping then took the 10-times threshold and reversed the calculations to find what conditions would exceed it. In doing so, he calculated that astronomers would need to find 14 other planets with intelligent life and known land fractions to robustly determine whether intelligent life is more likely to occur on desert planets, ocean planets, balanced planets, or without bias.

Kipping concluded that he can’t yet definitively state whether there is something special about Earth’s land fraction when it comes to producing intelligent species. However, Earth’s existence would suggest that intelligent life is unlikely to favor extreme desert planets, so the Milky Way probably isn’t filled with Tatooines and Jakkus. And while his analysis doesn’t debunk the Rare Earth hypothesis, it does undermine the argument that Earth’s ocean size explains why Earth is rare. 

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The Star Wars series depicted alien heroes fighting against evildoers and their planet-destroying superweapons “a long time ago in a galaxy far, far away.” But what do scientists really know about alien planets in distant galaxies beyond our own? These worlds, known as extragalactic exoplanets, are expected to exist, assuming the Milky Way is no different from other galaxies. However, we have yet to find them since other galaxies are still too far, far away for modern exoplanet-observing techniques.

Recently, a team of astronomers analyzed a stream of over 700,000 stars that the Milky Way likely absorbed from the dissolving Sagittarius dwarf galaxy. These stars are very distant, so the team investigated whether any of them host large, close-orbiting exoplanets called hot Jupiters, which are relatively easy to find.  

They established a set of 3 criteria to narrow down their list of stars. First, each star should appear bright enough when observed by the Transiting Exoplanet Survey Satellite, or TESS, to ensure high-precision results from the team’s data processing software. Second, each star must have more than a 50% likelihood that it originated from the Sagittarius dwarf galaxy, based on motion and position measurements from the Gaia mission. Finally, each star should have a radius of less than twice the Sun’s, as it’s easier to find planets around smaller stars. They used these criteria to limit their candidate list to around 20,000 stars.

After selecting their candidate stars, the team analyzed publicly available TESS catalog data using the software packages eleanor and TESS-Gaia Light Curve, or TGLC. These tools allowed them to plot each star’s brightness over time, in graphs called light curves. Then, the astronomers looked for periodic brightness dips in these light curves as evidence that an exoplanet passed in front of the star. From this, they excluded several thousand additional stars with too much light interference from their surroundings, reducing their final sample size to just over 15,000 stars.

To find hot Jupiters, the team looked for brightness dips at intervals of 14 hours to 10 days, which is the typical orbital period range for hot Jupiters. Then, they used geometry to derive each exoplanet’s radius from the fraction of the starlight it blocked. They excluded candidates with dips corresponding to objects with radii at least twice that of Jupiter’s, as these are likely caused by orbiting companion stars rather than exoplanets.

Among all the stars they surveyed, the team’s strongest candidate to host a hot Jupiter was a star labeled TIC 92223525. They calculated that this star could host an exoplanet with a radius 1.76 times the size of Jupiter’s and an orbital period of 7.2 days. However, when they reviewed this star’s light curve, they found that it was likely contaminated by its neighbor, TIC 92223526. The regular brightness dips from this system of orbiting stars mimicked that of an exoplanet, creating a false positive for TIC 92223525 that was difficult to detect during initial screening. As a result, the team ultimately excluded this candidate, leaving them with no confirmed exoplanets.

The researchers drew several conclusions from their inability to find hot Jupiters in their sample of stars from the Sagittarius dwarf stream. They estimated that if more than 1% of these stars hosted hot Jupiters, it would have been highly unlikely not to detect one in a sample of over 15,000 stars. This places an upper limit of about 1% on the occurrence rate of hot Jupiters. If this estimate is accurate, then even an ideal exoplanet search team would need to examine over 11,000 stars to find an extragalactic hot Jupiter. Accounting for more realistic levels of scientific uncertainty, a future team would likely need to study at least 80,000 stars to find one. 

Although this survey of the Sagittarius dwarf stream yielded null results, the team suggested that future researchers continue searching it and other star streams from different galaxies. Scientists have identified over 20 such streams in the Milky Way. Researchers studying these streams could find the first extragalactic exoplanet or provide evidence that other galaxies produce fewer hot Jupiters than our own. But let’s hope none of them find the first extragalactic Death Star!

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