Category Archives: Astronomy

Life On Ocean Worlds

One of the great philosophical mysteries of our age is, in the words ascribed to Enrico Fermi (AKA, “the pope of physics”): “Where is Everybody?” [3]  (This is known as Fermi’s Paradox, though he didn’t originate it, nor is it really a ‘paradox’.  It’s still a Fermi-grade question, though.)

Humans have been watching the skies for millennia, and in the past century have looked ever wider and deeper into the universe, not to mention into physics and the biology. Everything we know indicates that there could very well be life and even technological civilizations everywhere in the vast universe.  But we have never seen evidence of life beyond Earth.

Where is everybody?

Coming up with answers to Fermi’s question is a great scientific parlor game.

In 2002, Stephen Webb describes 50 answers [2], and in his 2015 update he gives 75 (!) [3].  The “solutions” listed by Webb range from “they are already here”, through “they are so strange we don’t recognize that they are there”, as well as the possibility that life really is very, very rare.

Along the way, he points out many uncertainties in our estimates of how likely the development of life and “intelligent” life may be (e.g., we have only our own planet to extrapolate from), as well as unknowable hypotheses about the possible psychology or politics of putative non-human civilizations (e.g., just because we want to talk to everyone doesn’t mean anyone wants to talk to us).

There are also disturbing warnings that “civilizations” are likely to self-destruct before escaping their home planet, or, even worse, may be snuffed out in the nest by predators or catastrophes. (With this in mind, blasting our electromagnetic presence in all directions might not have been a healthy life style choice.)

Webb’s compendium of “solutions” is fun to read, but the game is hardly over.


At the 2017 Habitable Worlds workshop, S. Alan Stern proposes yet another solution to the Fermi Paradox: most life evolves in “interior water ocean worlds”, i.e., in oceans under thick ice covers [1].

most life, and most intelligent life in the universe inhabits interior water ocean worlds (WOWs) where their presence is cloaked by massive overlying burdens of rock or ice between their abode and the universe.

There are several such worlds in our own solar system, and at times in the past the Earth itself flirted with such conditions, covered over with a kilometer of ice.

Artist’s concept of Europa’s frozen surface. Credit: JPL-Caltech

Stern notes that these worlds appear to be highly conducive to the development of life.  The ice cap protects and stabilizes the ocean environment, providing a nest for fragile life to develop over long, evolutionary periods of time.  Thus, however likely life is to develop, ice worlds are prime candidates for successful evolution.

However, Stern also makes the interesting inference that life that evolved under a deep ice cap would have no direct view of the universe.  The protective shield overhead would also block out most evidence of other stars and planets. An emerging civilization under the ice would not know about the universe, at least until technology develops that detects (indirectly) the space above the ice.  Even then, intelligent beings might have difficulty imagining life that does not live under ice, so they might not think to look for signals from us or send signals we could detect.

Stern also argues that life adapted to an ice-covered ocean would find space travel difficult, at least compared to species adapted to the surface under a gaseous atmosphere. In addition to the technical challenge of penetrating many kilometers of rock hard ice, life-support would be necessary to support a dense, liquid environment.

He combines these arguments to answer the “Where is everybody?” question:  if much life develops in ice covered oceans, and any civilizations in such environments unlikely to know or care about the wider universe, then this explains why we haven’t heard from them.

This is an interesting idea to think about.  It is certainly useful to break out of the parochial idea that an Earthlike planet is the only or ideal locus for life or “civilization”.  In fact, we know that life on Earth has just barely survived at least five major extinction events, and an ice world might well be a safer crèche.

I’ll also note that his comment that life on such a planet “either cannot communicate or are simply not aware that other worlds exist” works both ways.  It is difficult for us to detect such inhabitants, and we haven’t be looking until recently.  In our own solar system, there are several ice worlds, but we still have no idea if they are inhabited or not.


On the other hand, several aspects of Stern’s argument are less convincing to me.

An ice-covered ocean world might be a favorable site for life to start, but it might also be a closed system that is quickly exhausted.  Experience on Earth certainly indicates that a closed “ark” will rapidly be overgrown, clogged, and die out.   It is likely that only some ice worlds will be sufficiently “active” or open enough for life to persist.  But who knows until we actually check.

I have to say that I find the arguments about the supposed psychology of native to ice worlds highly speculative, to say the least.  It is true that life on Earth can directly sense the solar system and wider universe, and there are plausible arguments that this knowledge has strongly influenced the development of what we call intelligence.  But it is very difficult to guess the implications of not having an open sky.

I also think that, should a technological civilization develop under an icecap, it will surely develop undertanding of the outside universe. They’ll surely learn about gravity, and when they learn to detect and manipulate electromagnetism, they’ll soon notice a lot of interesting stuff coming in through their icy roof.  For that matter, no matter how difficult space travel might be, wouldn’t they deploy robot explorers and harvesters on the outer side of the ice.  And from that perch, who would not look up and see other worlds?

In short, I’ll buy the idea that ice worlds are good places for life to develop, though they may not be great places to sustain life for billions of years.  But I reserve judgement on questions of how the lack of a sky might influence the development of “civilizations”.


In this article, Stern describes yet one more case for why there could be some extraterrestrial civilizations that we have not seen or heard.  But this clearly isn’t “the answer”. He joins the roster of all the dozens of other hypotheses (Indeed, Webb has a solution called “Cloudy Skies Are Common” ([3], p. 183), which probably subsumes Stern’s solution as a sub case.).

On the other hand, this thesis is yet more reason why icy ocean worlds are really interesting and really need to be explored..  There very well could be life under the ice, and we really should find out what we can.

We have several such worlds close at hand in our solar system that we could visit and actually see what is down under the ice. (EuropaEceladus!  Titan!)

Let’s go, already!


  1. S. Alan Stern, An Answer to Fermi’s Paradox in the Prevalence of Ocean Worlds?, in Habitable Worlds 2017: A System Science Workshop. 2017: Laramie, Wyoming. https://www.hou.usra.edu/meetings/habitableworlds2017/pdf/4006.pdf
  2. Stephen Webb, If the Universe Is Teeming with Aliens … WHERE IS EVERYBODY? Fifty Solutions to the Fermi Paradox and the Problem of Extraterrestrial Life, New York, Copernicus Books In Association With Praxis Pub, 2002.
  3. Stephen Webb, If the Universe Is Teeming with Aliens … WHERE IS EVERYBODY? Seventy-Five Solutions to the Fermi Paradox and the Problem of Extraterrestrial Life, New York, Springer, 2015.

 

Space Saturday

Dark Energy Survey Data Available

If the fate of the Antarctic ice is the single most important question about our own planet, looking outward, the most important question surely must be “What is Dark Energy?

For the past decade, the Dark Energy Survey has begun to measure fast swaths of the visible sky, with the goal to better understand DE.  The DES is an awesome project, and a world-wide collaboration: the paper that ‘splains the data dump has 200 authors listed.


I’m particularly fond of this project not only because of the shear romantic appeal (we basically have no idea about the physics 95% of our universe), but also because the data is collected every night in Chile, and shot up the spine of the Americas to the National Center for Supercomputing Applications, my old institution. (I used to have an office just down the hall from the team who built that part of the data system.)

After the first three years of data collection, the DES has just dropped a huge public “Data Release 1”.  Come and get it!

I haven’t really looked at the data in any detail, though I can confirm that it is definitely open to the public.

I’ll note that this is yet another example of the challenges of “citizen science”. Anyone can have this data, and can do whatever they want with it.  Should we expect a flood of cool discoveries from the Internet “crowd”?  I wouldn’t bet on it.

The data is not pretty pictures, and doing science with it requires quite a bit of technical knowledge.  In fact, just understanding how the data was created requires a ton of background. The researchers have gone to a lot of work to create solid, useful data [1].

This just goes to show that real science (as opposed to Hollywood or Washington science) isn’t just looking at a screen and saying, “aha”.  Making data available is great, but it neither makes scientists redundant, nor necessarily generates more knowledge.


  1. T. M. C. Abbott, F. B. Abdalla, S. Allam, A. Amara, J. Annis, J. Asorey, S. Avila, O. Ballester, M. Banerji, W. Barkhouse, L. Baruah, M. Baumer, K. Bechtol, M . R. Becker, A. Benoit-Lévy, G. M. Bernstein, E. Bertin, J. Blazek, S. Bocquet, D. Brooks, D. Brout, E. Buckley-Geer, D. L. Burke, V. Busti, R. Campisano, L. Cardiel-Sas, A. C arnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, R. Cawthon, C. Chang, C. Conselice, G. Costa, M. Crocce, C. E. Cunha, C. B. D’Andrea, L. N. da Costa, R. Das, G. Daues, T. M. Davis, C. Davis, J. De Vicente, D. L. DePoy, J. DeRose, S. Desai, H. T. Diehl, J. P. Dietrich, S. Dodelson, P. Doel, A. Drlica-Wagner, T. F. Eifler, A. E. Elliott, A. E. Evrard, A. Farahi, A. Fausti Neto, E. Fernandez, D. A. Finley, M. Fitzpatrick, B. Flaugher, R. J. Foley, P. Fosalba, D. N. Friedel, J. Frieman, J. García-Bellido, E. Gaz tanaga, D. W. Gerdes, T. Giannantonio, M. S. S. Gill, K. Glazebrook, D. A. Goldstein, M. Gower, D. Gruen, R. A. Gruendl, J. Gschwend, R. R. Gupta, G. Gutierrez, S. Hamilton, W. G. Hartley, S. R. Hinton, J. M. Hislop, D. Hollowood, K. Honscheid, B. Hoyle, D. Huterer, B. Jain, D. J. James, T. Jeltema, M. W. G. Johnson, M. D. Johnson, S. Juneau, T. Kacpr zak, S. Kent, G. Khullar, M. Klein, A. Kovacs, A. M. G. Koziol, E. Krause, A. Kremin, R. Kron, K. Kuehn, S. Kuhlmann, N. Kuropatkin, O. Lahav, J. Lasker, T. S. Li, R. T. Li, A. R. Liddle, M. Lima, H. Lin, P. López-Reyes, N. MacCrann, M. A. G. Maia, J. D. Maloney, M. Manera, M. March, J. Marriner, J. L. Marshall, P. Martini, T. McClintock, T. McKay, R . G. McMahon, P. Melchior, F. Menanteau, C. J. Miller, R. Miquel, J. J. Mohr, E. Morganson, J. Mould, E. Neilsen, R. C. Nichol, D. Nidever, R. Nikutta, F. Nogueira, B. Nord, P. Nugent, L. Nunes, R. L. C. Ogando, L. Old, K. Olsen, A. B. Pace, A. Palmese, F. Paz-Chinchón, H. V. Peiris, W. J. Percival, D. Petravick, A. A. Plazas, J. Poh, C. Pond, A. Por redon, A. Pujol, A. Refregier, K. Reil, P. M. Ricker, R. P. Rollins, A. K. Romer, A. Roodman, P. Rooney, A. J. Ross, E. S. Rykoff, M. Sako, E. Sanchez, M. L. Sanchez, B. Santiago, A. Saro, V. Scarpine, D. Scolnic, A. Scott, S. Serrano, I. Sevilla-Noarbe, E. Sheldon, N. Shipp, M.L. Silveira, R. C. Smith, J. A. Smith, M. Smith, M. Soares-Santos, F. Sobre ira, J. Song, A. Stebbins, E. Suchyta, M. Sullivan, M. E. C. Swanson, G. Tarle, J. Thaler, D. Thomas, R. C. Thomas, M. A. Troxel, D. L. Tucker, V. Vikram, A. K. Vivas, A. R. Wal ker, R. H. Wechsler, J. Weller, W. Wester, R. C. Wolf, H. Wu, B. Yanny, A. Zenteno, Y. Zhang and J. Zuntz, The Dark Energy Survey Data Release 1. The DES Collaboration, 2018. https://arxiv.org/abs/1801.03181

 

 

Cassini End of Mission

After twenty years in space (launched 10 years Bi, Before iPhone), traveling over a billion KM, and returning data for 13 years from more than a light-hour from Earth, the Cassini Spacecraft ended its mission this week.

The project has accomplished lots of amazing science, represented by 3,948 papers so far. There will surely be a few more—lets go for 5K papers!

The end was a planned dive into the atmosphere of Saturn, collecting a few more bits of data on the way down, and assuring the complete destruction of the spacecraft.

As has been explained before, the spacecraft needed to be vaporized to prevent even the slighted chance that it might contaminate the area with Earth microbes. Aside from not wanting to harm any life that might exist on the moons or dust, we also don’t want to accidentally leave something that a later spacecraft might find and not realize was inadvertently sent from Earth.

(Which, if you think about it is way, way cool. How many human endeavors have to worry about the possibility of contaminating alien ecosystems, even in principle?)

Hence, the final dive.

This montage of images, made from data obtained by Cassini’s visual and infrared mapping spectrometer, shows the location on Saturn where the NASA spacecraft entered Saturn’s atmosphere on Sept. 15, 2017. Credit NASA/JPL-Caltech/Space Science Institute

Cassini signed off permanently on September 15. Loss of Signal. End of Mission. Lots of accomplishments.

 

Space Saturday

Cool NASA Imagery of Solar Eclipse

The total eclipse was spooky and cool, and an opportunity for science and nerdism to rule.

The experiences and reports on the ground were awesome. But NASA is observing the Earth in a lot of ways and from a lot of angles that are not on the ground. And they release some really cool examples from Monday.

As they put it, “So Many Ways to View an Eclipse”.

They have several time lapse compilations that show the shadow of the moon racing across the Earth.

I love this one because the circular shadow is so clear to see.

The eclipse also showed up in other traces, including temperature maps, views of the top of the atmosphere, and, of course, images of the sun.

Science Rulz!


  1. NASA Earth Observatory, So Many Ways to View an Eclipse, in NASA Earth Observatory 2017. https://earthobservatory.nasa.gov/IOTD/view.php?id=90796&src=eoa-iotd

 

Space Saturday

Dark Energy Survey Reports

The Universe we live in has a lot of matter and energy in it. We can see and measure matter and energy, but it is now clear that we can see only about 2% of what is there. We can tell that there is a lot of matter and energy out there that we simply cannot measure, it is called Dark Matter and Dark Energy. The universe is about 26% Dark Matter, and about 70% Dark Energy. What is all this Dark stuff? No one knows, but we sure need to find out, right?

Since 2013, a global collaboration of astronomers has been systematically surveying the sky to confirm the existence and assess the amount of Dark Energy. The Dark Energy Survey  is a heroic project, using a large telescope facility in the high desert of the Andes to spot and measure supernova. A massive amount of data is collected each night and stored in digital images.

The data is transferred through an optic fiber channel that runs up the spine of the America’s to Illinois, right down the street from where I sit. The data is organized into the archive, which is analyzed by science teams around the globe. It takes hours to transfer each night’s (irreplaceable) data to the data center, every day.

This summer, the DES is releasing a burst of ten papers to report the first year’s results [1]. (It has taken several years to analyze the first year’s data.  Unlike Hollywood movies, real life data analysis is hard work and takes time.)

The details of these analyses are largely beyond my own understanding, though I understand very well the scale of the computation and the system engineering this has required: this project is trying to measure the whole sky, and is looking for brief events that must be zoomed into. “Challenging” doesn’t begin to describe it.

Glancing through the papers, it is clear that this massive effort is yielding pretty solid results. To pick one paper arbitrarily, “Dark Energy Survey Year 1 Results: Cosmological Constraints from Cosmic Sheardiscusses one important thrust of the research, attempting to document the actual expansion of the Universe, and to improve estimates for the infamous cosmological constant that represents the “anti gravity” effects of Dark Matter and Energy.

The report itself is attributed to 135 authors from 51 institutions, and is based on observations of 36 million galaxies. The bulk of the paper describes the (complex) methods used to assemble and interpret the observational data. The results are close to earlier estimates of cosmological parameters from much smaller datasets. Results from other studies in this batch combine with these to tighten the estimated bounds on these values.

It’s all overwhelming, but as the authors dryly note, we really have no understanding of these fundamental facts yet. These are deep and fundamental mysteries, and we really need to know. The DES is an important step in understanding our universe.

Despite the overall success of modern cosmological study, however, there remain several fundamental mysteries that enter the model as purely phenomenological parameters. These include our lack of understanding of the value of the cosmological constant or of any motivation for a different driver of cosmic acceleration.” (p.2)


  1. The Dark Energy Survey. DES Year 1 Cosmology Results: Papers. 2017, https://www.darkenergysurvey.org/des-year-1-cosmology-results-papers/.
  2. The Dark Energy Survey. Home – The Dark Energy Survey. 2017, https://www.darkenergysurvey.org/.
  3. M. A. Troxel, N. MacCrann, J. Zuntz, T. F. Eifler, E. Krause, S. Dodelson, D. Gruen, J. Blazek, O. Friedrich, S. Samuroff, J. Prat, L. F. Secco, C. Davis, A. Ferté, J. DeRose, A. Alarcon, A. Amara, E. Baxter, M. R. Becker, G. M. Bernstein, S. L. Bridle, R. Cawthon, C. Chang, A. Choi, J. De Vicente, A. Drlica-Wagner, J. Elvin-Poole, J. Frieman, M. Gatti, W. G. Hartley, K. Honscheid, B. Hoyle, E. M. Huff, D. Huterer, B. Jain, M. Jarvis, T. Kacprzak, D. Kirk, N. Kokron, C. Krawiec, O. Lahav, A. R. Liddle, J. Peacock, M. M. Rau, A. Refregier, R. P. Rollins, E. Rozo, E. S. Rykoff, C. Sánchez, I. Sevilla-Noarbe, E. Sheldon, A. Stebbins, T. N. Varga, P. Vielzeuf, M. Wang, R. H. Wechsler, B. Yanny, T. M. C. Abbott, F. B. Abdalla, S. Allam, J. Annis, K. Bechtol, A. Benoit-Lévy, E. Bertin, D. Brooks, E. Buckley-Geer, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, M. Crocce, C. E. Cunha, C. B. D’Andrea, L. N. da Costa, D. L. DePoy, S. Desai, H. T. Diehl, J. P. Dietrich, P. Doel, E. Fernandez, B. Flaugher, P. Fosalba, J. García-Bellido, E. Gaztanaga, D. W. Gerdes, T. Giannantonio, D. A. Goldstein, R. A. Gruendl, J. Gschwend, G. Gutierrez, D. J. James, T. Jeltema, M. W. G. Johnson, M. D. Johnson, S. Kent, K. Kuehn, S. Kuhlmann, N. Kuropatkin, T. S. Li, M. Lima, H. Lin, M. A. G. Maia, M. March, J. L. Marshall, P. Martini, P. Melchior, F. Menanteau, R. Miquel, J. J. Mohr, E. Neilsen, R. C. Nichol, B. Nord, D. Petravick, A. A. Plazas, A. K. Romer, A. Roodman, M. Sako, E. Sanchez, V. Scarpine, R. Schindler, M. Schubnell, M. Smith, R. C. Smith, M. Soares-Santos, F. Sobreira, E. Suchyta, M. E. C. Swanson, G. Tarle, D. Thomas, D. L. Tucker, V. Vikram, A. R. Walker, J. Weller, Y. Zhang and (DES Collaboration), Dark Energy Survey Year 1 Results: Cosmological Constraints from Cosmic Shear. The Dark Eneergy Survey, 2017. http://www.darkenergysurvey.org/wp-content/uploads/2017/08/y1a1_cosmic_shear-1.pdf

 

Checking in with Cassini

The Cassini spacecraft has completed 5 of its 22 final swoops, conducting a feverish rush of observations on the outbound segment.

This science program was the product of long planning and discussion, to try to jam in as much science as possible, and to take advantage of the unique opportunities of each minute of each orbit. (If you fly all the way to Saturn, you want to get as many pix as possible, no?)

One observation peered at close range at one of the rings for its entire 14 hour rotation around Saturn, to get a detailed record. Another observation observed an occultation of Sirius by Saturn’s atmosphere, data not available from any other available method.

Cassini also took close up (well, from 168,000 KM), 1KM per pixel images of my new favorite moon, Enceladus. We’re on our way, Encie!

Credit NASA/JPL-Caltech/Space Science Institute

This week also saw and episode that gives perspective to just how far out at the edge of the possible Cassini is flying. The spacecraft is tiny and far away, and communicates via the Deep Space Network. Like many people who have fussed about with computer networks, I consider the DSN as nearly miraculous. It is a tribute to its designers and operators that we take for granted that we will be able to up and down link our spacecraft, even out at Saturn and beyond. (We are not worthy!)

Nothing is perfect, and like all engineering, end-to-end issues ultimately rule. This week some of the data downlinked from Cassini was lost because of heavy rains in Australia. First of all: rain in the desert? What’s the deal with that?.   Second: we are all thankful for the blessing of rain on that parched continent.

The problem, of course, is that the signals from Saturn are weak and far away. The natural radio noise from a rainstorm is not gigantic, but is sure is close, and (literally) drowned out the downlink.

The downside of one-of-a-kind observations is that and error or loss is unrecoverable. That data will never be seen.

As I said, rare problems serve to highlight just how robust the DSN has been for decades now.

Cassini continues to roll along, working like mad right up to the end in September.


  1. Cassini Science Communications Team. Cassini Significant Events 5/17/17 – 5/23/17. 2017. https://saturn.jpl.nasa.gov/news/3066/cassini-significant-events-51717-52317/

 

Space Saturday

Astronomy Leads The Way In Big Data

Jay Kremer and colleagues at University of Copenhagen write in IEEE Intelligent Systems about, “Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy [1].

This article is a nice survey of the kinds of data that astronomers collect, and the challenges of analyzing, and, indeed, simply handling it all.

I have worked with Astronomers in the past, and one of the coolest things is that when they have a dataset that covers “everything”, they really mean everything—the entire Universe, at least as much as we can see from where we are. And it is so romantic. Every study deals with space and time, matter and energy, theory and observation. Astronomical data makes you feel tiny and insignificant. Yet we are part of this gigantic picture, and our brains are capable of learning so much about it.

Anyway….

Kramer walk through many aspects of  contemporary Astronomical data. They describe the data (visible light and spectrographic measures), which are captured in detailed images of the sky. Billions of pixels recorded from signals that have travelled incomprehensible distances over inconceivable time spans, to intersect with us here and now.

No human could view all this information, nor make sense of it. The data is run through pipelines that use algorithms to clean up the data and look for “interesting” stuff. These days, the processing also automatically generates catalogs of objects in the image, i.e., tries to find everything interesting in the image. Of course, the details depend on the data source and what you are looking for—stars, galaxies, planets, asteroids, or many other possible targets.

Over the years, astronomers have employed all kinds of image analysis, including machine learning techniques to automate these processes. In fact, many techniques pioneered by astronomers have been adopted for other uses. Astronomers have also pioneered the use of crowdsourced “citizen science” to aid the development and validation of these algorithms. Galaxy Zoo was one of the first and most successful such citizen science project, and has spawned dozens of clones.

In order to understand and answer questions about these massive datasets, e Astronomers have also pioneered statistical methods and search techniques. Kramer also discusses the difficult challenges of creating models that connect theory to the observational data. Much of astronomy is about trying to go from theoretical physics to “pixels in the image”, and vice versa.

Finally, they note that most of the data is openly available (though you really can’t download a copy, because it too freaking much). Most of the software is available, too. (This openness is possible largely because no one knows how to make money off astronomy, not even astronomers.) This means that there is opportunity for anyone to get into the game, to create new analyses, or to discover new science. Much of the data has hardly been studied at all, so who knows what you might be able to do?


In one sense, this article is nothing new. For centuries, Astronomy has led the development of instruments, data analysis, and theory. Looking out at the universe is both the hardest, and the most informative, scientific observations of all, and Astronomers are always working at the edge of what is technically possible.

In the past few years, there has been an accelerating trend to cut pubic funding for scientific research. The remaining funds are ever more tightly rationed, forcing hard choices, and difficult arguments about the relative benefits of different activities. Inevitably, there are strong pressures to reduce activities that have little obvious and direct benefit for people or important political interest groups.

One of the prime targets has been large-scale astrophysics, which requires expensive equipment and is, by definition, not about current life on Earth. It doesn’t even employ large numbers of people, at least once construction has finished. What good is it, except to fill the curiosity of a few egg heads?

This political picture is important to keep in mind when reading this article. They are responding to the “Why should we pay for these large investigations?”

In short, one reason to support Astronomy research is that this work can drive many data technologies that are increasingly important in may fields closer to home (and more profitable).

This is not the most romantic reason to do Astronomy, but it is a valid and important point.


  1. Jan Kremer, Kristoffer Stensbo-Smidt, Fabian Gieseke, Kim Steenstrup Pedersen, and Christian Igel, Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. IEEE Intelligent Systems, 32 (2):16-22, 2017. http://ieeexplore.ieee.org/document/7887648/

 

Space Saturday