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The Simpsons' secret formula: it's written by maths geeks Without doubt, the most mathematically sophisticated television show in the history of primetime broadcasting is The Simpsons. This is not a figment of my deranged mind, which admittedly is obsessed with both The Simpsons and mathematics, but rather it is a concrete claim backed up in a series of remarkable episodes. The first proper episode of the series in 1989 contained numerous mathematical references (including a joke about calculus), while the infamous "Treehouse of Horror VI" episode presents the most intense five minutes of mathematics ever broadcast to a mass audience. Moreover, The Simpsons has even offered viewers an obscure joke about Fermat's last theorem, the most notorious equation in the history of mathematics. These examples are just the tip of the iceberg, because the show's writing team includes several mathematical heavyweights. The 2006 episode "Marge and Homer Turn a Couple Play", for example, contains a triple dose of secret mathematics.

How does Tupper’s self-referential formula work? [I write this post with a certain degree of embarrassment, because in the end it turns out (1) to be more simple than I anticipated, and (2) already done before, as I could have found if I had internet access when I did this. :-)] The so-called “Tupper’s self-referential formula” is the following, due to Jeff Tupper. Graph the set of all points such that in the regionwhere N is the following 544-digit integer: 48584506361897134235820959624942020445814005879832445494830930850619 34704708809928450644769865524364849997247024915119110411605739177407 85691975432657185544205721044573588368182982375413963433822519945219 16512843483329051311931999535024137587652392648746133949068701305622 95813219481113685339535565290850023875092856892694555974281546386510 73004910672305893358605254409666435126534936364395712556569593681518 43348576052669401612512669514215505395545191537854575257565907405401 57929001765967965480064427829131488548259914721248506352686630476300 The result is the following graph: .

Free Science and Engineering books Algorithms and Data Structures: The Basic Toolbox Algorithms are at the heart of every nontrivial computer application, and algorithmics is a modern and active area of computer science. Every computer scientist and every professional programmer should know about the basic algorithmic toolbox: structures that allow efficient organization and retrieval of data, frequently used algorithms, and basic techniques for modeling, understanding and solving algorithmic problems. Operating Systems: Three Easy Pieces Operating Systems: Three Easy Pieces covers the fundamentals of operating systems, including virtualization of the CPU and memory, threads and concurrency, and file and storage systems. Quantum Mechanical Tunneling in Chemical Physics Quantum mechanical tunneling plays important roles in a wide range of natural sciences, from nuclear and solid-state physics to proton transfer and chemical reactions in chemistry and biology.

Mathematics Books Online General Elementary Algebra & Trigonometry Abstract Algebra Mathematical Analysis & Calculus Differential Equations The Geometry of 3-Manifolds Dr. Lisa Randall, a professor of theoretical physics at Harvard, introduces the lecture. McMullen graduated from Williams College, and went on to study at Cambridge University and the Institut des Hautes Etudes Scientifique in France. 8 math talks to blow your mind Mathematics gets down to work in these talks, breathing life and logic into everyday problems. Prepare for math puzzlers both solved and unsolvable, and even some still waiting for solutions. Ron Eglash: The fractals at the heart of African designs When Ron Eglash first saw an aerial photo of an African village, he couldn’t rest until he knew — were the fractals in the layout of the village a coincidence, or were the forces of mathematics and culture colliding in unexpected ways? Here, he tells of his travels around the continent in search of an answer. How big is infinity? There are more whole numbers than there are even numbers … right?

Algebraic Topology Course, The University of New South Wales Mathematics Video Tutorials, N J Wildberger SEE: Guide to Download The University of New South Wales Video Lecture Lecture Details : This is the Introductory lecture to a beginner's course in Algebraic Topology given by N J Wildberger of the School of Mathematics and Statistics at UNSW in 2010. This first lecture introduces some of the topics of the course and three problems.

ONLINE SCIENCE AND MATH TEXTBOOKS Page of NeuraLinksPlus by Prof. Mark Dubin Aeronautics - Basics of Space Flight - Online Textbook From JPL Algebra - Online Textbook Anatomy - Neuroimaging of Human Brain Function - Online Textbook National Academy Press colloquium Mathematical Tools for Physics Mathematical Tools for Physics Physics 315, University of Miami James Nearing

Predicting the future of the past tense Verbs evolve and homogenize at a rate inversely proportional to their prevalence in the English language, according to a formula developed by MIT and Harvard University mathematicians who've invoked evolutionary principles to study our language over the past 1,200 years. The team, which reported their findings in the Oct. 11 issue of Nature, conceives of linguistic development as an essentially evolutionary scheme. Just as genes and organisms undergo natural selection, words--specifically, irregular verbs that do not take an "-ed" ending in the past tense--are subject to powerful pressure to "regularize" as the language develops. "We're really on the front lines of developing the mathematical tools to study evolutionary dynamics," says Jean-Baptiste Michel, a graduate student at Harvard Medical School.

The Paradox of the Proof On August 31, 2012, Japanese mathematician Shinichi Mochizuki posted four papers on the Internet. The titles were inscrutable. The volume was daunting: 512 pages in total. The claim was audacious: he said he had proved the ABC Conjecture, a famed, beguilingly simple number theory problem that had stumped mathematicians for decades.

Joint PhD ML/Heinz-Machine Learning Department - Carnegie Mellon University With the critical importance of addressing global policy problems ranging from disease pandemics to crime and terrorism, and the continuously increasing size and complexity of policy data, the use of machine learning has become essential for data-driven policy analysis and for development of new, practical information technologies that can be directly applied for the public good. The numerous challenges facing our world will require broad, successful innovations at the intersection of machine learning and public policy, to develop novel methods which address critical policy challenges. The Joint PhD Program in Machine Learning and Public Policy is a new program for students to gain the skills necessary to develop new state-of-the-art machine learning technologies and apply these successfully to real-world policy issues. Students in this program will be involved in courses and research from both the Machine Learning Department and the Heinz College.

Open Educational Resources Utah's Open Textbook Projects Utah has geared up to begin providing teachers, students, and parents with materials to support the Utah Core Standards, instruction, and teaching. Created by groups of content and teaching experts, including university faculty, district and school specialists, teachers, and USOE staff.