What I Learned Today

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!

Most of what we know about Mars only goes skin deep. We’ve had several orbiters studying the planet with a variety of remote sensing instruments (cameras, lasers, radar, etc.) and several rovers running around on the surface. The Phoenix lander dug around in the soil a little.

But so far, we haven’t been able to look beneath that skin. No drills, no cores, no subsurface probes. We haven’t even gotten a seismometer to the planet, which could be used to learn about the composition of the planet’s interior, and help answer the question of whether Mars still has a molten core. (The Apollo astronauts put seismometers on the Moon to help answer similar questions.)

The InSight mission to Mars seeks to change that. InSight is a lander that will use a seismometer and a heat flow probe to learn about the planet’s interior. (It will also have a surface camera, of course!) The plan is for InSight to launch in early 2016 and land on Mars later that year.

We’ve studied Mars from the outside for decades now… it’s time to look under the hood!

InSight is competing with two other concepts to be the next Discovery mission to Mars. (The others are the Titan Mare Explorer and Comet Hopper.) One of the three will be selected in late 2012. Stay tuned!

The new NASA budget isn’t looking good, and Planetary Science in particular is taking a ***20%*** cut, most of which cuts Mars funding!

In a move that’s equal parts desperation and brilliance, the community is rallying to put on a nationwide Planetary Exploration Car Wash & Bake Sale on June 9. Each local organizer will send a check with the proceeds to Congress, requesting them to apply it to increase the planetary science budget.

If your car doesn’t need washing or you’re watching your waistline, check out this AAS site for information on how to contact congressfolk and a list of useful “talking points.” If you care about the future of planetary exploration, make your voice heard!

Recently I read the announcement that astronomers found a fourth moon orbiting Pluto in Hubble Space Telescope observations. Apparently they were not looking for more moons; instead, they were looking for possible rings around Pluto.

My first thought: Wait, Pluto had three moons before?

I blush to admit that I only knew of Charon, Pluto’s largest moon (1207 km in diameter). I missed the announcement in 2005 of the discovery of two more Pluto moons: Nix (46-137 km) and Hydra (61-167 km). Now’s a good time to catch up! The new moon (temporarily designated P4 as “Pluto’s 4th satellite”) is only 13-34 km in diameter. That’s small, but there is precedent: Phobos and Deimos, the moons of Mars, are only 20 and 15 km in diameter respectively.

Here is a composite of two images that provides the basis of the new moon’s discovery:

The timing of this serendipitous discovery is excellent. The New Horizons mission will fly past Pluto in July of 2015, and perhaps it will have the chance to investigate P4 up close — or even add more moons to Pluto’s tiny family!

The Kepler mission has already reported a slew of fascinating discoveries, including new planets and new kinds of planetary systems, and there is every expectation that in the final two years of observations it will continue to reveal more and more planetary treasures. However, no mission or instrument functions exactly as expected, and Kepler has had its share of challenges in collecting and processing its data. “Overview of the Kepler Science Processing Pipeline” by Jenkins et al. (2010) provides a fascinating behind-the-scenes look at some of these obstacles and their solutions.

Kepler consists of a one-meter telescope that has been staring at the same patch of sky for two years. Its goal is to measure the brightness of 156,000 stars every 29.4 minutes (“long-cadence” observations) and a smaller set of 512 stars ever 58.85 seconds (“short-cadence”). Each star generates a light curve of its brightness as a function of time. Exoplanets are detected as slight drops in the brightness while the planet transits in front of the star. For this light curve to be usable for detecting planets, Kepler needs two things: 1) a stable pointing so that the stars don’t bounce around or smear, and 2) a stable sensitivity so that any perceived brightening is due to an actual change in the stars.

During the first few months of observations, the first requirement was challenged. Kepler uses a set of “guide stars” to help fine-tune its pointing, and unfortunately it turned out that one of the guide stars selected in advance was an eclipsing binary. Whenever it would eclipse (so one star hid the other one), its brightness dropped and Kepler lost lock on it. As a result, the pointing was slightly off for 8 hours every 1.7 days (!). Kepler only downlinks its data once a month, so it took a few months to notice and correct this. The eclipsing binary star was eliminated from the guide star list and this problem has gone away.

The telescope is very sensitive to thermal conditions, any changes in which can wreak havoc with its focus. One of Kepler’s RWAs (reaction wheel assemblies, used to point the spacecraft, e.g., to pivot it towards Earth for data downlink and back to resume looking at the stars) has a heater that inadvertently modifies the telescope’s focus by about 1 micron every 3.2 hours. There’s no way to fix this, so it just has to be modeled and removed from the data in processing. Likewise, the spacecraft has experienced two “safing” events in which most of its systems shut down, which cools the entire assembly; each time when operations resumed, it took five days for the thermal effects to disappear from the data.

Perhaps most challenging is an artifact that manifests as “Moiré patterns caused by an unstable circuit with an operational amplifier oscillating at ~1.5 GHz.” Luckily, the actual impact on the data values is very small, generally only perturbing them by a single increment, but it is virtually impossible to adequately model and remove, so no doubt a source of at least minor frustration:

“Given that the Moiré pattern noise exhibits both high spatial
frequencies and high temporal frequencies, the prospect of reconstructing a high-fidelity model of the effects at the pixel level with an accuracy sufficient to correct the affected data appears unlikely. We are developing algorithms that identify when these Moiré patterns are present and mark the affected CCD regions as suspect on each affected LC.”

And finally, there was a curious overall brightening (termed “argabrightening”) observed in early phases of the mission. About 15 times per month, the background brightness of the entire field increased dramatically for a short time. The current hypothesis is that this was caused by remnant dust particles coming loose from Kepler and floating off, then reflecting sunlight back into the telescope. Detecting and removing affected observations was crucial for yielding consistent light curves. Fortunately, the rate of these events has decreased over time (Kepler might be running out of dust).

I look forward to more fascinating news from this great mission! And I hope they keep sharing the interesting challenges and lessons learned from operating a telescope from so very far away.