# Mathematics

Art and Mathematics  –  Martin Strauss
(Session 2)

With just a little historical revisionism, we can say that Art has provided inspiration for many fields within Mathematics. Conversely, Mathematics gives techniques for analyzing, appreciating, and even creating Art, as well as the basis for gallery design, digital cameras, and processing of images. In this class we will explore the Mathematics in great works of Art as well as folk art, as a way of studying and illustrating central mathematical concepts in familiar and pleasing material. And we’ll make our own art, by drawing, painting, folding origami papers, and more. Major topics include Projection, Symmetry, Wave Behavior, and Distortion. Projection includes the depiction of three-dimensional objects in two dimensions. What mathematical properties must be lost, and what can be preserved? How does an artwork evoke the feeling of three-dimensional space? We’ll study perspective, depictions of globes by maps, and the role of curvature. Turning to symmetry, we’ll study rotational and reflective symmetry that arise in tiling and other art and math. We’ll study more generalized symmetry like scaling and self-similarity that occurs in fractals as well as every self-portrait, and is central to mathematical concepts of dimension and un very different from the work at coarser scales—it is not self-similar. Describing light as waves and color as wavelength at once explains how mirrors, lenses, and prisms work and explains some uses of light and color in art. Finally, we ask about distorting fabrics and strings, and ask about the roles of cutting, gluing, and of stretching without cutting or gluing. Is a distorted human figure still recognizable, as long as it has the right number of organs and limbs, connected properly? Background in Math and interest in Art suggested. No artistic talent is necessary, though artistically talented students are encouraged to bring art supplies if they are inexpensive and easily transportable.

Fibonacci Numbers  –  Mel Hochster
(Session 3)
The Fibonacci numbers are the elements of the sequence 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55- where every term is simply the sum of the two preceding terms. This sequence, which was originally proposed as describing the reproduction of rabbits, occurs in astonishingly many contexts in nature. It will be used as a starting point for the exploration of some very substantial mathematical ideas: recursive methods, modular arithmetic, and other ideas from number theory, and even the notion of a limit: the ratios of successive terms (e.g. 13/8, 21/13. 55/34) approach the golden mean, already considered by the ancient Greeks, which yields what may be the most aesthetically pleasing dimensions for a rectangle. As a by-product of our studies, we will be able to explain how people can test certain, very special but immensely large numbers, for being prime. We’ll also consider several games and puzzles whose analysis leads to the same circle of ideas, developing them further and reinforcing the motivations for their study.

Graph Theory  –  Doug Shaw
(Sessions 1, 2, & 3)

Ignore your previous knowledge of algebra, geometry, and even arithmetic! Start fresh with a simple concept: Take a collection of points, called vertices, and connect some of them with lines called edges. It doesn’t matter where you draw the vertices or how you draw the lines – all that matters is that two vertices are either related, or not. We call that a “graph” and you’ve taken the first step on the Graph Theory road! Graphs turn up in physics, biology, computer science, communications networks, linguistics, chemistry, sociology, mathematics- you name it! In this course we will discuss properties that graphs may or may not have, hunt for types of graphs that may or may not exist, learn about the silliest theorem in mathematics, and the most depressing theorem in mathematics, learn how to come up with good algorithms, model reality, and construct some mathematical proofs. We will go over fundamental results in the field, and also some results that were only proved in the last year or so! And, of course, we will present plenty of currently unsolved problems for you solve and publish when you get home!

Hex and the 4 Cs  –  Stephen DeBacker
(Session 1)

Mathematical Modeling in Biology –  Trachette Jackson and Patrick Nelson
Mathematical biology is an exciting interdisciplinary field that combines applied mathematics, scientific computing, biology, ecology, physiology and medicine.  This branch of mathematics is growing with phenomenal speed! For the mathematician, biology opens up new and exciting areas of study, while for the biologist, mathematical and computational modeling offers another powerful research tool that can provide insight into the complexity of a biological system. Mathematical biologists typically investigate problems in diverse and exciting areas such as the topology of DNA, cell physiology, the study and spread of infectious diseases, population ecology, neuroscience, tumor growth and treatment strategies, and organ development and embryology. This course will be a venture into the field of mathematical modeling in biology and the biomedical sciences using techniques from calculus, dynamical systems and scientific computing.  Interactive lectures, group projects, computer demonstrations, and guest speakers will help introduce some of the fundamentals of mathematical modeling and its usefulness in biology, physiology and medicine.  For example, the cell division cycle is a sequence of regulated events which describes the passage of a single cell from birth to division. There is an elaborate cascade of molecular interactions that function as the mitotic clock and ensures that the sequential changes that take place in a dividing cell take place on schedule. What happens when the mitotic clock speeds up or simply stops ticking? These kinds of malfunctions can lead to cancer and mathematical modeling can help predict under what conditions a small population of cells with a compromised mitotic clock can result in a fully developed tumor.  Students who can speak the languages of mathematics and computation along with biology and medicine will be able to solve some of the most challenging problems of the 21st century.  Wouldn’t it be amazing if mathematics could guide future experiments that lead to a cure AIDS or Cancer?

Mathematics and Music Theory  –  Lon Mitchell
(Session 2)

Mathematicians can create complex and beautiful theorems from relatively basic assumptions, while Music Theorists often try to identify basic patterns and rules in complex and beautiful music. In this course, we will explore some of the recent attempts to meet in the middle, connecting mathematical patterns and structures to music from the ancient to the modern. In Mathematics, we will explore topics such as group theory, graph theory, geometry, and metric spaces, encountering some of the most important structures in the modern discipline. Fundamental results of these areas will be discussed, and students will construct and explore examples and related patterns. In Music Theory, we will take existing music by composers such as Bach and Beethoven and use mathematical structures to provide a possible explanation of what they were thinking as they composed. In addition, we will investigate the techniques of modern composers such as Arnold Schoenberg who advocated composition based on prescribed axioms. Students will be given the chance to write music using these different techniques. Although we will use the modern (Western) twelve-tone scale as a reference, our explorations will take us into discussions of tuning, temperament, and the physics of sound. We will investigate mathematical theories of what makes the best scale, how some of those scales occur in the music of other cultures, and how modern composers have engineered exotic scales to suit their aesthetics. Software allowing students to experiment with creating their own musical systems will be provided. Prospective students should have a good command of (high-school) algebra and experience with reading music in some form.

Mathematics and the Internet  –  Mark Conger
(Session 1)
How can gigabytes of information move over unreliable airwaves using unreliable signaling, and arrive perfectly intact? How can I have secure communication with a website run by a person I’ve never met? How can a large image or sound file be transferred quickly? Why is Google so good at finding what I’m looking for? How do computers work, anyway? The answers to all these questions involve applications of abstract mathematics. In Mathematics and the Internet, we’ll develop the math on its own, but also show how it is essential to making the Internet operate as it does. Our journey will take us through logic, probability, group theory, finite fields, calculus, number theory, and any other areas of math that might come up. We’ll apply our results to coding theory, cryptography, search engines, and compression. We’ll also spend several days building primitive computers out of transistors, logic gates, and lots of wire. If all goes well, we’ll connect them to the Internet!

Mathematics of Cryptography  –  Anna Weigandt
(Session 3)
Ever since humans first developed the ability to write there has been an ongoing battle between codemakers and codebreakers. The armies of ancient Sparta and Rome both used ciphers to relay secret battle plans, and the ancient Mesopotamians developed encryption techniques in order to protect commercially valuable techniques for glazing pottery. From a modern perspective, the codes used by the ancients are laughably insecure. Indeed, much of what made them secure was that they were being used during a period when most people were illiterate. Because of the advent of computers, codemakers today need to use far more sophisticated techniques in order to create secure codes. Many of these techniques are mathematical in nature. One of the cryptography systems that we will discuss in this class is called RSA and is used to ensure the security of your credit card information when you make a purchase on the internet. We’ll see that at its heart, what makes the RSA system secure is that it is very hard to factor a big number. The numbers used in the RSA system are actually so big that factoring them would take you millions of years. Even if you were using a supercomputer! This class will give an historical introduction to the mathematics of cryptography, beginning with codes used by the Roman legions and building up to the RSA cryptography system discussed above. What will really make the class unique is that there won’t be any lecturing. You will discover the mathematics of cryptography by working on problems and sharing your solutions with your classmates.

Mathematics of Decisions, Elections and Games  –  Michael A. Jones
(Session 2)

You make decisions every day, including whether or not to sign up for this course. The decision you make under uncertainty says a lot about who you are and how you value risk. To analyze such decisions and provide a mathematical framework, utility theory will be introduced and applied to determine, among other things, a student’s preference for desserts and for the offer the banker makes to a contestant in the television show Deal or No Deal. Our analysis will touch on behavioral economics, including perspectives of 2017 Nobel Prize winner Richard Thaler. Elections are instances in which more than one person’s decision is combined to arrive at a collective choice. But how are votes tallied? Naturally, the best election procedures should be used. But Kenneth Arrow was awarded the Nobel Prize in Economics in 1972, in part, because he proved that there is no best election procedure. Because there is no one best election procedure, once the electorate casts its ballots, it is useful to know what election outcomes are possible under different election procedures – and this suggests mathematical and geometric treatments to be taught in the course. Oddly, the outcome of an election often stays more about which election procedure was used, rather than the preferences of the voters! Besides politics, this phenomenon is present in other settings that we’ll consider which include: the Professional Golfers’ Association tour which determines the winner of tournaments under different scoring rules (e.g. stroke play and the modified Stableford system), the method used to determine rankings of teams in the NCAA College Football Coaches poll, and Major League Baseball MVP balloting. Anytime one person’s decisions can affect another person, that situation can be modeled by game theory. That there is still a best decision to make that takes into account that others are trying to make their best decisions is, in part, why John F. Nash was awarded the Nobel Prize in Economics in 1994 (see the movie A Beautiful Mind, 2002). Besides understanding and applying Nash’s results in settings as diverse as the baseball mind games between a pitcher and batter and bidding in auctions, we’ll examine how optimal play in a particular game is related to a proof that there are the same number of counting numbers {1, 2, 3, } as there are positive fractions. We will also examine the Gale-Shapley algorithm, which is used, for example, to match physicians to residency programs and to match students to colleges (the college admissions problem). Lloyd S. Shapley and Alvin E. Roth were awarded the Nobel Prize in Economics in 2012 for their work on matching.