MIT Research News' Journal

Lava oceans may not explain the brightness of some hot super-Earths

Arguably some of the weirdest, most extreme planets among the more than 4,000 exoplanets discovered to date are the hot super-Earths — rocky, flaming-hot worlds that zing so precariously close to their host stars that some of their surfaces are likely melted seas of molten lava.

These fiery worlds, about the size of Earth, are known more evocatively as “lava-ocean planets,” and scientists have observed that a handful of these hot super-Earths are unusually bright, and in fact brighter than our own brilliant blue planet.

Exactly why these far-off fireballs are so bright is unclear, but new experimental evidence by scientists at MIT shows that the unexpected glow from these worlds is likely not due to either molten lava or cooled glass (i.e. rapidly solidified lava) on their surfaces.

The researchers came to this conclusion after interrogating the problem in a refreshingly direct way: melting rocks in a furnace and measuring the brightness of the resulting lava and cooled glass, which they then used to calculate the brightness of regions of a planet covered in molten or solidified material. Their results revealed that lava and glass, at least as a product of the materials they melted in the lab, are not reflective enough to explain the observed brightness of certain lava-ocean planets.

Their findings suggest that hot super-Earths may have other surprising features that contribute to their brightness, such as metal-rich atmospheres and highly reflective clouds.

“We still have so much to understand about these lava-ocean planets,” says Zahra Essack, a graduate student in MIT’s Department of Earth, Atmospheric, and Planetary Sciences. “We thought of them as just glowing balls of rock, but these planets may have complex systems of surface and atmospheric processes that are quite exotic, and not anything we’ve ever seen before.”

Essack is the first author of a study detailing the team’s results, which appears today in The Astrophysical Journal. Her co-authors are former MIT postdoc Mihkel Pajusalu, who was instrumental in the experiment’s initial setup, and Sara Seager, the Class of 1941 Professor of Planetary Science, with appointments in the departments of Physics and Aeronautics and Astronautics.

More than charcoal balls

Hot super-Earths are between one and 10 times the mass of Earth, and have extremely short orbital periods, circling their host star in just 10 days or less. Scientists have expected that these lava worlds would be so close to their host star that any appreciable atmosphere and clouds would be stripped away. Their surfaces as a result would be at least 850 kelvins, or 1,070 degrees Fahrenheit — hot enough to cover the surface in oceans of molten rock.

Scientists have previously discovered a handful of super-Earths with unexpectedly high albedos, or brightnesses, in which they reflected between 40 and 50 percent of the light from their star. In comparison, the Earth’s albedo, with all of its reflective surfaces and clouds, is only around 30 percent.

“You’d expect these lava planets to be sort of charcoal balls orbiting in space — very dark, not very bright at all,” Essack says. “So what makes them so bright?”

One idea has been that the lava itself may be the main source of the planets’ luminosity, though there had never been any proof, either in observations or experiments.

“So being MIT people, we decided, ok, we should make some lava and see if it’s bright or not,” Essack says.

Making lava

To first make lava, the team needed a furnace that could reach temperatures high enough to melt basalt and feldspar, the two rock types that they chose for their experiments, as they are well-characterized material that are common on Earth.

As it turns out, they initially didn’t have to look farther than the foundry at MIT, a space within the Department of Materials Science and Engineering, where trained metallurgists help students and researchers melt materials in the foundry’s furnace for research and class projects.

Essack brought samples of feldspar to the foundry, where metallurgists determined the type of crucible in which to place them, and the temperatures at which they needed to be heated.

“They drop it in the furnace, let the rocks melt, take it out, and then the whole place turns into a furnace itself — it’s very hot,” Essack says. “And it was an incredible experience to stand next to this bright glowing lava, feeling that heat.”

However, the experiment quickly ran up against an obstacle: The lava, once it was pulled from the furnace, almost instantly cooled into a smooth, glassy material. The process occurred so quickly that Essack wasn’t able to measure the lava’s reflectivity while still molten.

So she took the cooled feldspar glass to a spectroscopy lab she designed and implemented on campus to measure its reflectance, by shining a light on the glass from different angles and measuring the amount of light reflecting back from the surface. She repeated these experiments for cooled basalt glass, samples of which were donated by colleagues at Syracuse University who run the Lava Project. Seager visited them a few years ago for a preliminary version of the experiment, and at that time collected basalt samples now used for Essack’s experiments.

“They melted a huge bunch of basalt and poured it down a slope, and they chipped it up for us,” Seager says.

After measuring the brightness of cooled basalt and feldspar glass, Essack looked through the literature to find reflectivity measurements of molten silicates, which are a major component of lava on Earth. She used these measurements as a reference to calculate how bright the initial lava from the basalt and feldspar glass would be. She then estimated the brightness of a hot super-Earth covered either entirely in lava or cooled glass, or combinations of the two materials.

In the end, she found that, no matter the combination of surface materials, the albedo of a lava-ocean planet would be no more than about 10 percent — pretty dark compared with the 40 to 50 percent albedo observed for some hot super-Earths.

“This is quite dark compared to Earth, and not enough to explain the brightness of the planets we were interested in,” Essack says.

This realization has narrowed the search range for interpreting observations, and directs future studies to consider other exotic possibilities, such as the presence of atmospheres rich in reflective metals.

“We’re not 100 percent sure what these planets are made of, so we’re narrowing the parameter space and guiding future studies toward all these other potential options,” Essack says.

This research was funded, in part, by NASA’s TESS mission and, in part, by the MIT Presidential Fellowship.

Key brain region was “recycled” as humans developed the ability to read

Humans began to develop systems of reading and writing only within the past few thousand years. Our reading abilities set us apart from other animal species, but a few thousand years is much too short a timeframe for our brains to have evolved new areas specifically devoted to reading.

To account for the development of this skill, some scientists have hypothesized that parts of the brain that originally evolved for other purposes have been “recycled” for reading. As one example, they suggest that a part of the visual system that is specialized to perform object recognition has been repurposed for a key component of reading called orthographic processing — the ability to recognize written letters and words.

A new study from MIT neuroscientists offers evidence for this hypothesis. The findings suggest that even in nonhuman primates, who do not know how to read, a part of the brain called the inferotemporal (IT) cortex is capable of performing tasks such as distinguishing words from nonsense words, or picking out specific letters from a word.

“This work has opened up a potential linkage between our rapidly developing understanding of the neural mechanisms of visual processing and an important primate behavior — human reading,” says James DiCarlo, the head of MIT’s Department of Brain and Cognitive Sciences, an investigator in the McGovern Institute for Brain Research and the Center for Brains, Minds, and Machines, and the senior author of the study.

Rishi Rajalingham, an MIT postdoc, is the lead author of the study, which appears today in Nature Communications. Other MIT authors are postdoc Kohitij Kar and technical associate Sachi Sanghavi. The research team also includes Stanislas Dehaene, a professor of experimental cognitive psychology at the Collège de France.

Word recognition

Reading is a complex process that requires recognizing words, assigning meaning to those words, and associating words with their corresponding sound. These functions are believed to be spread out over different parts of the human brain.

Functional magnetic resonance imaging (fMRI) studies have identified a region called the visual word form area (VWFA) that lights up when the brain processes a written word. This region is involved in the orthographic stage: It discriminates words from jumbled strings of letters or words from unknown alphabets. The VWFA is located in the IT cortex, a part of the visual cortex that is also responsible for identifying objects.

DiCarlo and Dehaene became interested in studying the neural mechanisms behind word recognition after cognitive psychologists in France reported that baboons could learn to discriminate words from nonwords, in a study that appeared in Science in 2012.

Using fMRI, Dehaene’s lab has previously found that parts of the IT cortex that respond to objects and faces become highly specialized for recognizing written words once people learn to read.

“However, given the limitations of human imaging methods, it has been challenging to characterize these representations at the resolution of individual neurons, and to quantitatively test if and how these representations might be reused to support orthographic processing,” Dehaene says. “These findings inspired us to ask if nonhuman primates could provide a unique opportunity to investigate the neuronal mechanisms underlying orthographic processing.”

The researchers hypothesized that if parts of the primate brain are predisposed to process text, they might be able to find patterns reflecting that in the neural activity of nonhuman primates as they simply look at words.

To test that idea, the researchers recorded neural activity from about 500 neural sites across the IT cortex of macaques as they looked at about 2,000 strings of letters, some of which were English words and some of which were nonsensical strings of letters.

“The efficiency of this methodology is that you don't need to train animals to do anything,” Rajalingham says. “What you do is just record these patterns of neural activity as you flash an image in front of the animal.”

The researchers then fed that neural data into a simple computer model called a linear classifier. This model learns to combine the inputs from each of the 500 neural sites to predict whether the string of letters that provoked that activity pattern was a word or not. While the animal itself is not performing this task, the model acts as a “stand-in” that uses the neural data to generate a behavior, Rajalingham says.

Using that neural data, the model was able to generate accurate predictions for many orthographic tasks, including distinguishing words from nonwords and determining if a particular letter is present in a string of words. The model was about 70 percent accurate at distinguishing words from nonwords, which is very similar to the rate reported in the 2012 Science study with baboons. Furthermore, the patterns of errors made by model were similar to those made by the animals.

Neuronal recycling

The researchers also recorded neural activity from a different brain area that also feeds into IT cortex: V4, which is part of the visual cortex. When they fed V4 activity patterns into the linear classifier model, the model poorly predicted (compared to IT) the human or baboon performance on the orthographic processing tasks.

The findings suggest that the IT cortex is particularly well-suited to be repurposed for skills that are needed for reading, and they support the hypothesis that some of the mechanisms of reading are built upon highly evolved mechanisms for object recognition, the researchers say.

The researchers now plan to train animals to perform orthographic tasks and measure how their neural activity changes as they learn the tasks.

The research was funded by the Simons Foundation and the U.S. Office of Naval Research.