What I Learned Today

Perhaps you saw the recent Venus transit of the Sun. But what about an Earth transit?

Obviously we can’t see such a phenomenon while sitting on the Earth itself. But some clever astronomers have done calculations to work out when the Earth would transit the Sun from the perspective of other bodies in the solar system, including the Moon and Jupiter.

“In January 2014, Jupiter will witness a transit of Earth. And we can see it too, the astronomers say, by training NASA’s Hubble Space Telescope on the huge planet and studying the sunlight it reflects.”
(From NBCNews, June 4, 2012)

Using Jupiter as a mirror seems a curious strategy, since the reflected light will also be influenced by the chemical makeup of Jupiter’s atmosphere. However, just as with the hunt for exoplanets, if we can stare at Jupiter for long enough before the transit occurs, we can build a good enough model so its factors can be subtracted out from the Earth+Jupiter signal during the transit. Scientists first plan to test this strategy with a Venus transit that Jupiter will see (Earth won’t) in September of this year. And I’ve seen talk that they used the Moon as a mirror to observe the recent Venus transit from the Earth vicinity — but I haven’t been able to find any images of the result yet. Here’s how it works:

Finding planets? Old hat. What about finding moons?

It seems likely that planets around other stars might also be hosts to their own moons. In addition to just wanting to know what’s out there, detecting exomoons could have implications for the habitability of exoplanets. While gas giants themselves might not be habitable, their potential rocky moons could be, if the planet orbits in the habitable zone. Also, moons can help stabilize a planet’s orbital inclination over long time periods, making it easier for life to maintain its hold rather than experiencing dramatic oscillations in environmental conditions.

This video shows the expected effect that a moon could have on the light curves we observe remotely:

The Hunt for Exomoons – Lightcurve Demo from Alex Parker on Vimeo.

The effect here is quite noticeable because the moon is at high inclination (out of the plane of the planet’s rotation around its star).

HEK (the Hunt for Exomoons with Kepler) is a collaboration established with hopes of finding the first exomoon in Kepler data. They were successful in getting some crowdfunding from PetriDish.org to purchase a supercomputer for their search. Laudably, they plan to post numeric posterior results from their search as an aid to the community.

Exomoons are theorized to tweak the planet’s transit curve in a variety of ways, but they are subtle and in many cases can be confused with other causes (like interactions with other planets in the same system). The community is still working to develop reliable models.

So, no exomoons have yet been found — but it’s probably just a matter of time.

If you haven’t heard by now, the Kepler mission has opened up a firehose of exoplanet (candidate) detections. We’re up to more than 2300 candidates found by the mission, with more to come.

I’ve just discovered an awesome animation that Dan Fabrycky created to visualize systems discovered by Kepler that have more than one detected transiting exoplanet. (Note: this includes unconfirmed planet candidates as well.)

“There are 885 planet candidates in 361 systems. In this video, orbits are to scale with respect to each other, and planets are to scale with respect to each other (a different scale from the orbits). The colors are in order of semi-major axis. Two-planet systems (242 in all) have a yellow outer planet; 3-planet (85) green, 4-planet (25) light blue, 5-planet (8) dark blue, 6-planet (1, Kepler-11) purple.

I could stare at this for hours. Wow.

Stressful, according to “Choosing Mars Time: Analysis of the Mars Exploration Rover Experience” by Deborah S. Bass, Roxana C. Wales, and Valerie L. Shalin. Almost certainly, one would adjust quite easily to a Mars-length day (24 hours + 39 minutes) if it were synchronized to the rest of the planet. But as the Mars Exploration Rover scientists and mission operators discovered, keeping Mars time on Earth plunges you perpetually into jet lag limbo.

The decision was made to run MER mission operations on Mars time so that personnel could be synchronized with the rovers’ wake/sleep cycles. They slept while the rovers were awake, and they were awake in turn to receive the latest data and make plans for the next sol’s commands to send back, while the rovers slept. This meant that for those on Mars time, each “day” rotated 39 minutes forward relative to local Earth time — as if they were gradually sliding westward almost (but not quite) one time zone per day. To help with the time-shifting, the buildings were outfitted with black-out curtains and cots and irregular (to Earthlings) meal service. My favorite touch: personnel were given special watches designed to tick off 24:37 per day instead of 24:00.

However, the bizarre schedule was challenging not just due to fatigue and physiological issues but, as the authors discuss, sociological ones, like maintaining connections to friends or family members, or figuring out how to pick up your child from school when (by your calendar) that pick-up time moves 37 minutes earlier each day! An extra complexity arose from the fact that the two rovers, Spirit and Opportunity, were on opposite sides of Mars — so there were actually two different Mars times observed during the mission, depending which rover you were supporting.

Although efforts were made to provide reasonable meal service, it wasn’t perfect:

“Operations staff occasionally were confused about whether the [food] cart would be present when they had a break as they were tracking multiple clocks simultaneously as well as working a schedule that did not follow the normal workday/weekend cycle.”

But there was one reliable source of calories: ice cream.

“Free ice cream, provided as a reward for a successful mission, was also available to the team at all hours. Because the ice cream was easily available, operations personnel ate more of it than they would have normally (3-5 ice cream bars/day was not unusual). Some people gained weight. There is anecdotal evidence that team members relied on the ice cream as both a reward and a pick-me-up to push through the harder parts of their shift work.”

I’ve been told that personnel also wore biometric devices, to track blood pressure, heart rate, and so on. This was a grand experiment from the human physiology perspective: 250 people living with an altered clock, for 90 days, and not in isolation but instead while trying to perform their jobs and live their regular lives as much as possible. I haven’t yet identified a paper analyzing that data or reporting on the conclusions, but I’d love to find such a thing!

The 1976 Viking landers conducted a handful of experiments that involved injecting a nutrient-laden solution into Martian soil, then measuring gases given off in response. Indeed, gases were observed from the regular soil, but not from soil that was first heated to 160 C (sterilized). That seemed intriguing to many scientists—but others noted that the same result could be obtained through (abiotic) chemical oxidation triggered by the application of water. If I understand the arguments, heating the soil would break down the presumed oxidizer in the soil so it would then react less or not at all to a new injection of moisture.

But lo and behold, the scientists who (still) insist that Viking found life have published a new paper: “Complexity Analysis of the Viking Labeled Release Experiments” by Bianciardi, Miller, Straat, and Levin. They’ve used “complexity variables” to characterize the time series data, then clustered them (with k-means clustering, k=2). Indeed, they found that presumed “active” samples (including some examples from Earth) clustered together while presumed “inactive” samples (including some controls from Earth) clustered in a different group.

Since my dissertation was on clustering, I thought I should take a look and see how this machine learning method was being used in this setting. And, well, I’m just not convinced. Yes, they do seem to have gotten two distinct populations. But they only used 15 samples (11 from Mars, 4 from Earth) and that hardly seems sufficient to characterize the range of behavior, nor are they all obviously comparable (one time series consists of “core temperature readings taken every minute from a rat in constant darkness”; how is this related to possible bacterial activity in soil? Is darkness relevant? What about a rat in daylight, or a diurnal cycle?). The authors have agreed that more data would be better. I think more data, and thoughtfully chosen, would be essential.

My other reservation is about the “complexity variables” that were used. These are presented with no justification or discussion:

• LZ complexity
• Hurst exponent
• Largest Lyapunov exponent
• Correlation dimension
• Entropy
• BDS statistic
• Correlation time

Especially since these generated the 7D space in which the clustering happened, it’d be nice to have some intuition about why these might relate to life. There are some brief comments about life being “ordered” and of “high complexity” (and I’ve worked on this subject myself!) but I’m not convinced that the distinction they found is truly meaningful.

I don’t want to be unscientifically biased or negative. The results as presented in the paper do seem to show a quantitative separation between active and inactive samples. But this should be conducted with hundreds or thousands of samples from the Earth at the very least, where we have tons of examples of life-bearing soils as well as artificial or sterilized samples. These could fill out the feature space and properly position the Viking observations in more context.

Of course, it would also be useful to get more Martian samples!