March 2, 2015 — Jeffrey Bryant, Scientific Information Group
2015 is shaping up to be an interesting year in space exploration. For the first time, we will get up-close views of a dwarf planet. In fact, two different spacecraft will visit two different dwarf planets. The Dawn spacecraft is nearing its second primary target, Ceres, later this week. Later this year, the New Horizons spacecraft will visit Pluto.
December 29, 2014 — Tom Sherlock, User Interface Group
As an amateur astronomer, I’m always interested in ways to use Mathematica in my hobby. In earlier blog posts, I’ve written about how Mathematica can be used to process and improve images taken of planets and nebulae. However, I’d like to be able to control my astronomical hardware directly with the Wolfram Language.
In particular, I’ve been curious about using the Wolfram Language as a way to drive my telescope mount, for the purpose of automating an observing session. There is precedent for this because some amateurs use their computerized telescopes to hunt down transient phenomena like supernovas. Software already exists for performing many of the tasks that astronomers engage in—locating objects, managing data, and performing image processing. However, it would be quite cool to automate all the different tasks associated with an observing session from one notebook.
Mathematica is highly useful because it can perform many of these operations in a unified manner. For example, Mathematica incorporates a vast amount of useful astronomical data, including the celestial coordinates of hundreds of thousands of stars, nebula, galaxies, asteroids, and planets. In addition to this, Mathematica‘s image processing and data handling functionality are extremely useful when processing astronomical data.
August 14, 2014 — Tom Sherlock, User Interface Group
The planet Mars comes into opposition, the point closest to the Earth, about every 780 days, or a bit over two years. The Martian opposition this year was on April 9. This past May, on a rare clear, warm night, I attempted to capture some images of the red planet. Unfortunately once I had my telescope set up, Mars had passed behind a large tree, so the images I captured were distorted by tree branches. Nevertheless, I did manage to capture a set of frames, and hoped that image processing with Mathematica could produce something usable.
August 7, 2014 — Jeffrey Bryant, Scientific Information Group
We are reposting this blog post due to the ESA’s success yesterday, August 6, 2014.
We recently posted a blog entry celebrating the anniversary of the Apollo 11 landing on the Moon. Now, just a couple weeks later, we are preparing for another first: the European Space Agency’s attempt to orbit and then land on a comet. The Rosetta spacecraft was launched in 2004 with the ultimate goal of orbiting and landing on comet 67P/Churyumov–Gerasimenko. Since the launch, Rosetta has already flown by asteroid Steins, in 2008, and asteroid 21 Lutetia, in 2010.
NASA and the European Space Agency (ESA) have a long history of sending probes to other solar system bodies that then orbit those bodies. The bodies have usually been nice, well-behaved, and spherical, making orbital calculations a fairly standard thing. But, as Rosetta recently started to approach comet 67P, we began to get our first views of this alien world. And it is far from spherical.
August 21, 2013 — Jeffrey Bryant, Scientific Information Group
In today’s world, people often forget about the wonders of the night sky. Modern conveniences provided by civilization such as electricity and lighting result in light pollution that obscures our views. Pictures like the one below that I took near Champaign, Illinois show the yellow glow of city lights that reduces the contrast with the night sky and makes it difficult to see some of the more visually stunning, but lower contrast sights like the Milky Way. But you can still make out the Milky Way in my photo as a cloudy stripe that runs up from the southern horizon during summer in the Northern hemisphere, or winter if you are in the Southern hemisphere.
January 8, 2013 — Jeffrey Bryant, Scientific Information Group
The physics involved in simulating galaxy collisions can be extremely complex. The most accurate simulations take into account not just points representing stars, but also magnetic fields and invisible dark matter, as well as n-body interactions allowing the individual stars to interact with each other. These complex simulations are usually carried out on large-scale supercomputers over long periods of time. One of the more interesting aspects of galaxy collisions is that they can create density variations resulting in all kinds of emergent structure. Density waves can develop that lead to star formation from compressed gas clouds.
A couple of years ago, I wrote a Demonstration that provides a simplified solution to galaxy collisions. This Demonstration is designed to run in real time inside a Manipulate, so the problem has been simplified by removing n-body interactions, dark matter, magnetic fields, and so on. Basically, it treats the two galaxies as large point masses with lots of massless test particles orbiting them. The test particles respond only to the two galaxy “centers.” In a real galaxy collision, the chances of two stars getting close enough to each other to interact directly is very remote, so it’s not too far of a stretch to ignore this effect for a first-order approximation. The more stars that are included in the simulation (by minimizing the star separation parameter), the more intricate the results (and the more computationally intense). In fact, as more stars are added, it becomes easier to see density variations where many test masses cluster together, but it still looks very discrete. Real galaxies, like the Milky Way, can have hundreds of billions of stars. Trying to carry out a point simulation with that many stars becomes a bit taxing on most home systems, and definitely exceeds the time constraints of a real-time dynamic tool like Manipulate. So how can we better visualize these density variations? I decided to try to modify my Demonstration to use one of the new features in Mathematica 9, namely volumetric rendering. This way, we can simulate the galaxy collisions with fewer numbers of points, but render the results as if there were billions of stars, resulting in a more realistic and informative visualization.
December 27, 2010 — Tom Sherlock, User Interface Group
Here is a shot I took of M27, the famous Dumbbell Nebula, with my home-brew 90mm astrograph and inexpensive equatorial mount.
Actually, it isn’t a single shot, but a combination of about 30 fairly short exposures, added together. Adding together short subframes rather than taking a single longer exposure makes it possible to create astrophotos without additional equipment for “guiding” the telescope. Guiding means applying small corrections, either manually or automatically, during the exposure to compensate for imperfections in either the mount’s alignment away from the polar axis or the mount’s drive mechanism. Combining the subframes has the additional benefit of reducing noise and increasing the signal to produce a result similar to a much longer exposure.
September 13, 2010 — Jeffrey Bryant, Scientific Information Group
Almost everyone has heard of the asteroid belt. This is the place between the orbit of Mars and Jupiter that is home to a very large percentage of the known minor planets in the solar system. Movies love to have space battles in asteroid belts to add to dramatic dogfight scenes. Even the Star Wars universe pays homage to asteroids: in The Empire Strikes Back, C3PO makes a popular statement about the possibility of successfully navigating an asteroid field.
Popular fiction, especially in Hollywood, loves to twist reality for cinematic effect. Often it shows an asteroid belt as an intricate maze of chaotically tumbling boulders that are moving at high speeds relative to each other, requiring advanced evasion techniques to avoid hitting one of them. They are also often shown to collide with each other at high speed, resulting in large explosions.
In reality, at least for our asteroid belt, things are not quite so dramatic. If you were actually in our asteroid belt, the chances that you would see an asteroid are fairly small. Most of them are quite small relative to the Earth and the space between them is relatively large. NASA has sent numerous probes through the belt, and not one has had an accidental encounter with an asteroid, although there have been a couple of intentional encounters. We know very little about the physical characteristics of asteroids compared to planets. Very few have been visited. However, their orbital dynamics are well studied and show some pretty amazing features. Let’s take a look at a view of all of the asteroids used in Mathematica‘s AstronomicalData out to the orbit of Jupiter.
October 6, 2009 — Jeffrey Bryant, Scientific Information Group
The Sloan Digital Sky Survey (SDSS) is an ongoing endeavor to map the sky in great detail, with many different goals. One of the larger objectives is to map the structure of the cosmos by determining the positions of galaxies and their relativistic redshift (basically their distance). Using this data and Mathematica, you can plot the information and reveal the structure of the cosmos.
In my spare time, I queried the SDSS website, which is database driven, and in eight separate queries I was able to get all galaxies in the survey out to a redshift of 0.5. According to Wolfram|Alpha, this corresponds to looking back in time 5.02 billion years ago, or a distance of 6.14 billion light years, when the light we’re now seeing from the most distant galaxies started its journey here. That’s a billion years before our solar system formed. It’s taken this long for the light to reach us.
March 3, 2009 — Jeffrey Bryant, Scientific Information Group
In this day and age, it’s quite common to have to do some housecleaning on your computer to make room for more clutter. While moving stuff around on my home computer and trying to figure out what data I had and where it could be moved to free up space on my hard drive, I ran across an old FITS data file from my college days. The cryptic filename only told me that it was taken in May and that it was likely the 132nd image in a sequence. I was curious and decided I would investigate it to see what I had uncovered. Perhaps it was a dull star-field image from my data-collecting days in the study of dwarf novae; I wasn’t sure. Mathematica was the most convenient tool I had handy for viewing FITS data, so I decided to take it for a spin.