September 25, 2007 — Mark Sofroniou, Kernel Development

I’ve been working on arithmetic in Mathematica for more than 12 years. You might think that’s silly; after all, how hard can arithmetic be?

Today we were reminded again about how hard it can be. A nasty little bug in Excel 2007 came to light, whereby the result of computing, for example, 850*77.1 is displayed as 100000:

850*77.1 in Excel 2007

Of course, this works just fine in Mathematica:

850*77.1 in Mathematica

But why is arithmetic so difficult to get right?

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September 25, 2007 — Marcus Wynne, Public Relations Manager

Every Friday night at 10pm US Eastern Time, around 12 million people tune in to CBS and watch a hit television show called NUMB3RS. It’s the most popular CBS drama on Friday nights. NUMB3RS tracks the crime-solving exploits of an FBI team assisted by a brilliant mathematics professor.

The show is about how to use math to solve crimes.

If you add up all the bachelor’s, master’s and PhD degrees awarded in mathematics in a given US academic year, there are only around 20 thousand. And presumably, not every single one of them watches this show.

So why are 12 million people tuning in on a regular basis to watch a show about math?

Because this show makes math—especially cutting-edge higher mathematics—interesting in a way that no popular television show has done before, much as another show on CBS—CSI: Crime Scene Investigation—led the way in making science both accessible and entertaining to the mass television market.

NUMB3RS is therefore the first successful television drama to make advanced mathematics accessible, interesting and entertaining in a dramatic format.

So how did that happen? Where does the TV math come from?

From the behind-the-scenes brain trust at Wolfram Research.

Amy Young, Michael Trott, Eric Weisstein, and Ed Pegg Jr

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September 21, 2007 — Daniel Lichtblau, Symbolic Algorithms Developer, Algorithms R&D

I think last year’s Wolfram Technology Conference went pretty well. Lots of interesting talks, and I even got to wear fangs and a tie in preparation for Halloween.

I did have a couple of misgivings. The days started early and went late, and in some instances I thought certain simultaneous talks in parallel tracks should have been separated. A colleague of mine felt similarly. We both voiced our concerns to the SPTB (Scheduling Powers That Be).

Bad idea—now we’re dragged in for scheduling this year’s Technology Conference. (Some Midwesterners might say “drug in.” But I’m from somewhere else.)

As the conference takes place October 11-13, this means there has to be some serious scheduling work afoot right now.

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September 20, 2007 — Jason Cawley, Chief of Operations, Wolfram Solutions

The Federal Reserve cut the federal funds rate this week for the first time in four years.

And it happens that I am working on a new economics data function for Mathematica—so I wanted to see what typically results after such a reduction in the federal funds rate.

The Fed makes much of its data available on the web through the FRED II database. So, all I had to do was point Mathematica’s powerful Import function to the site, and I instantly had the data in Mathematica for analysis. It took one line of code.

A couple of short Mathematica evaluations later, and I had a list of all the previous occasions when this rate fell 0.5% or more. I immediately noticed that these large drops sometimes come in “runs,” and decided to focus on the large cuts in each such sequence. I found 15 of these which go back to 1954.

Federal funds rate pattern

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September 13, 2007 — Rob Knapp, Manager of Numerical Computation, Algorithms R&D

Today’s earthquakes near Sumatra fortunately didn’t lead to a major tsunami. But figuring out when tsunamis will develop is a difficult matter—and an interesting exercise in applied mathematics.

The main phenomenon is the propagation of so-called shallow water waves—water waves whose wavelength is large compared to the depth of the ocean. Those waves satisfy a partial differential equation (PDE) that was figured out in the 1800s. The equation is a nasty nonlinear one—that can’t be solved exactly.

I’ve been working on the numerical differential equation capabilities of Mathematica for more than a decade. Our goal is to automate the solutions of all types of equations—so users just have to enter their equation, and Mathematica then does all the analysis to select and apply the best algorithm.

The shallow-water equations are a good test—that I’m happy to say Mathematica passes with flying colors. One essentially just has to type the equations in, and get the solution, which is then easy to visualize—especially using the new visualization capabilities of Mathematica 6. (Click the image below to see the Mathematica animation.)

Click for Tsunami Animation Exported from Mathematica

Let me explain a little about what’s involved in getting this.

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September 11, 2007 — Stephen Wolfram

I don’t have much time for hobbies these days, but occasionally I get to indulge a bit. A few days ago I did a videoconference talking about one of my favorite hobbies: hunting for the fundamental laws of physics.

Physics was my first field (in fact, I became a card-carrying physicist when I was a teenager). And as it happens, the talk I just gave (for the European Network on Random Geometry) was organized by one of my old physics collaborators.

Physicists often like to think that they’re dealing with the most fundamental kinds of questions in science. But actually, what I realized back in 1981 or so is that there’s a whole layer underneath.

There’s not just our own physical universe to think about, but the whole universe of possible universes.

If one’s going to do theoretical science, one had better be dealing with some kind of definite rules. But the question is: what rules?

Nowadays we have a great way to parametrize possible rules: as possible computer programs. And I’ve built a whole science out of studying the universe of possible programs—and have discovered that even very simple ones can generate all sorts of rich and complex behavior.

Well, that’s turned out to be relevant in modeling all sorts of systems in the physical and biological and social sciences, and in discovering interesting technology, and so on.

But here’s my big hobby question: what about our physical universe? Could it be operating according to one of these simple rules?

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