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Education & Academic

After 100 Years, Ramanujan Gap Filled

A century ago, Srinivasa Ramanujan and G. H. Hardy started a famous correspondence about mathematics so amazing that Hardy described it as “scarcely possible to believe.” On May 1, 1913, Ramanujan was given a permanent position at the University of Cambridge. Five years and a day later, he became a Fellow of the Royal Society, then the most prestigious scientific group in the world at that time. In 1919 Ramanujan was deathly ill while on a long ride back to India, from February 27 to March 13 on the steamship Nagoya. All he had was a pen and pad of paper (no Mathematica at that time), and he wanted to write down his equations before he died. He claimed to have solutions for a particular function, but only had time to write down a few before moving on to other areas of mathematics. He wrote the following incomplete equation with 14 others, only 3 of them solved. Within months, he passed away, probably from hepatic amoebiasis. His final notebook was sent by the University of Madras to G. H. Hardy, who in turn gave it to mathematician G. N. Watson. When Watson died in 1965, the college chancellor found the notebook in his office while looking through papers scheduled to be incinerated. George Andrews rediscovered the notebook in 1976, and it was finally published in 1987. Bruce Berndt and Andrews wrote about Ramanujan's Lost Notebook in a series of books (
Design & Visualization

Gigapixel Images in Mathematica

Professional cameras offer a resolution of 50 megapixels and more. In addition, projects like GigaPan allow one to create gigapixel panoramas with billions of pixels. How can we process these images on a desktop computer with 8 GB of RAM? One of Mathematica 9's new and exciting features is out-of-core image processing. What does the out-of-core term really mean? It is a way to process very large images that are too big to fit into main memory. Let's say we have a machine with 8 GB of RAM, and let's assume that Mathematica can use up to 7.2 GB of that memory (the remaining 0.8 GB will be used by the operating system). Freshly started, Mathematica 9 on Windows 8 takes up about 200 MB of memory, so the kernel can use about 7 GB of RAM. What is the maximal size of the image that we can load into the kernel (we don't want to visualize it at this point)? If we assume that the image is in the RGB color space and a single byte encoding, then the following formula gives a maximal width (and height) of an image that can be loaded at once into the memory:
Best of Blog

Data Science of the Facebook World

More than a million people have now used our Wolfram|Alpha Personal Analytics for Facebook. And as part of our latest update, in addition to collecting some anonymized statistics, we launched a Data Donor program that allows people to contribute detailed data to us for research purposes. A few weeks ago we decided to start analyzing […]

Computation & Analysis

Exploding Art: da Vinci Code of Another Sort

What does programming have to do with a passion for the arts and history? Well, if you turn education into a game and add a bit of coding, then you can easily end up in the realm of a modern paradigm called, fancily, "gamification." Though gamification is a very wide concept based on game use in non-game contexts (design, security, marketing, even protein folding, you name it), at heart it is very simple: play, have fun, and get things done. I may have oversimplified things here for the sake of a rhyme, but if you bear with my lengthy prelude, we may just see a simple case of turning passion into software. My obsession with diagrams and simple line drawings began almost unnoticeably in the winter of 2003 in New York City after attending an exhibition at The Metropolitan Museum of Art: "the first comprehensive survey of Leonardo da Vinci's drawings ever presented in America." You may think it'd be a drag---crowds marching very slowly in a single long line coiling through the exhibition hallways. But perception of time transforms when you stare at 500-year-old craft. I think it was then that it started to dawn on me what special value a first sketch has. A first act when an idea, something very subjective, evasive, living solely inside one's mind, materializes as a solid reality, now perceivable by another human being. Imagine it happened ages ago. Wouldn't you be curious what was going on at that moment in time, what got frozen in this piece of craft in front of you?
Education & Academic

From Close to Perfect—A Triangle Problem

RootApproximant can turn an approximate solution into a perfect solution, such as for a square divided into fifty 45°-60°-75° triangles. A square can be divided into triangles, for example by connecting opposite corners. It's possible to divide a square into seven similar but differently sized triangles or ten acute isosceles triangles. Classic puzzles involve cutting a square into eight acute triangles, or twenty 1 - 2 - √5 triangles. The last image uses 45°-60°-75° triangles, but one triangle has a flaw. It's easy to divide a square with similar right triangles. Can a square be divided into similar non-right triangles? In his paper "Tilings of Polygons with Similar Triangles" (Combinatorica, 10(3), 1990 pp. 281–306), Laczkovich proved exactly three triangles provided solutions, with angles 22.5°-45°-122.5°, 15°-45°-120°, and 45°-60°-75°. I read his paper to try to make an image for the 45°-60°-75° case, but his construction was complex, and seemed to require thousands of triangles, so I tried to find my own solutions. All my attempts had flaws, such as the last image above, so I made a contest out of it: $200, minus a dollar for every triangle in the solution.
Education & Academic

The Mathematics of Queues

Waiting in line is a common, though not always pleasant, experience for us all. We wait patiently to be served by the next free teller at a bank, clear the security check at an airport, or be answered by technical support when we call a phone service provider. At a more abstract level, these waiting lines, or queues, are also encountered in computer and communication systems. For example, every email you send is broken up into a series of packets. Each packet is then sent off to its destination by the best available route to avoid the queues formed by other packets in the network. Hence, queues play an important role in our lives, and it seems worthwhile to spend some time understanding their dynamics, with a view to answering questions such as, "How many tellers does your bank need to provide good customer service?" or "How can you speed up the security check?" or "On average, how long will you have to wait for technical support?" My purpose in writing this post is to give a gentle introduction to queueing theory, which attempts to answer such questions, using new functions that are available in Mathematica 9. Queueing theory has its origins in the research of the Danish mathematician A. K. Erlang (1878–1929). While working for the Copenhagen Telephone Company, Erlang was interested in determining how many circuits and switchboard operators were needed to provide an acceptable telephone service. This investigation resulted in his seminal paper "The Theory of Probabilities and Telephone Conversations," which was published in 1909. Erlang proved that the arrivals for such queues can be modeled as a Poisson process, which immediately made the problem mathematically tractable. Another major advance was made by the American engineer and computer scientist Leonard Kleinrock (1934–), who used queueing theory to develop the mathematical framework for packet switching networks, the basic technology behind the internet. Queueing theory has continued to be an active area of research and finds applications in diverse fields such as traffic engineering and hospital emergency room management.
Announcements & Events

Register Now for the First European Wolfram Technology Conference!

Our first ever European Wolfram Technology Conference will be held June 11–12 in Frankfurt, Germany (pre-conference training on June 10 in Friedrichsdorf). Join Wolfram developers and experts as we look at how combined computation expertise across all our technologies—Wolfram|Alpha, Computable Document Format, Wolfram SystemModeler, Wolfram Workbench, and of course Mathematica—can empower you and your organization in research, development, deployment—and progress.
Computation & Analysis

Mathematica’s Role in Powering Energy Saving Solutions

Using Mathematica and other Wolfram technologies, Joseph Hirl, founder of Agilis Energy, has developed a new approach to energy analytics that is helping building owners and energy equipment suppliers around the world cut energy consumption and costs. At the core of the company's success is its Mathematica-based dynamic energy analysis application, which gives the full picture of a building's performance, measures the impact of potential operational changes, and quantifies the results. About Mathematica's role in the development of the tool and the Agilis business, Hirl says, "The flexibility of Mathematica is tremendous. Our ability to build and develop this program with a lean staff has allowed us to build out a substantial business." The application, which has now been used at more than 800 sites in at least 12 different industries, begins with data streams, including high-interval smart meter data as well as Mathematica's built-in WeatherData. It then applies sophisticated statistics and dynamic visualization functionality to generate what Hirl calls an "MRI of a building," a dynamic interface with a simulation of the building's energy use and demand and forecasting and benchmarking tools.
Computation & Analysis

Behind the Scenes at the National Museum of Mathematics Meta-Logo

The National Museum of Mathematics, which opened in Manhattan in December, doesn't have a logo. It has an infinite family of logos. And the logos the museum uses for official business are not created by design professionals. They're designed by the museum's visitors. The logo is itself an exhibit in the museum. The museum's unique meta-logo was conceived and implemented at Wolfram Research. When I say "implemented," I don't mean just "calculated" or "rendered," but actually "programmed." This is a logo that requires an implementation.