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Astronomy

Academics

On the Detection of Gravitational Waves by LIGO

Earlier today at a press conference held at the National Science Foundation headquarters in Washington, DC, it was announced that the Laser Interferometer Gravitational-Wave Observatory (LIGO) confirmed the first detection of a gravitational wave. The image reproduced below shows the signal read off from the Hanford, Washington, LIGO installation. The same signal could be seen in the data from the Livingston, Louisiana, site as well. While this signal may not seem like much, it is one of the most important scientific discoveries of our lifetime.

B. P. Abbott et al., Phys. Rev. Lett. 116, 061102 (2016)

Academics

Solar Eclipses from Past to Future, Earth to Jupiter

You may have heard that on March 20 there was a solar eclipse. Depending on where you are geographically, a solar eclipse may or may not be visible. If it is visible, local media make a small hype of the event, telling people how and when to observe the event, what the weather conditions will be, and other relevant details. If the eclipse is not visible in your area, there is a high chance it will draw very little attention. But people on Wolfram Community come from all around the world, and all---novices and experienced users and developers---take part in these conversations. And it is a pleasure to witness how knowledge of the subject and of Wolfram technologies and data from different parts of the world are shared.
Academics

Serial Interface Control of Astronomical Telescopes

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.
Academics

Fixing Bad Astrophotography II: Imaging Mars with Mathematica

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.
Academics

Rosetta—First Mission to Orbit and Land on a Comet

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.
Academics

Visualizing Our Place in the Milky Way Galaxy with Mathematica

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.
Academics

Volumetric Rendering of Colliding Galaxies

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.
Academics

Fixing Bad Astrophotography Using Mathematica 8 and Advanced Image Deconvolution

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. Before we go further, it's fun to look up information about M27 using the new Wolfram|Alpha features built in to Mathematica 8.