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#51 | |||
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Core Member [109%]
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I suppose that is one way of teaching it. |
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#52 |
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Core Member [406%]
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Much of the richness of mathematics arises from the fact that objects can be viewed from very different theoretical perspectives.
In the article of the OP, a purely algebraic stance was taken, because that's what the intended audience could grasp. High school kids do not have a functioning knowledge of geometry, topology, or analysis sufficient to serve as an *intuitive* basis for understanding the complex numbers; but they know the Quadratic Formula! The fact that these different views of an object exist is how almost all advanced mathematical work proceeds. When considering problems in one domain, it is common practice to "map" them to a domain where a corresponding theory provides a solution; this is then carried back to the original domain by means of the "mapping". A simple example is using a "change of variables" in calculus to do an integral: by applying an appropriate transform to a messy integrand, it is morphed into a function that is easy to integrate; after this simple integration is completed, the result is carried back by means of the inverse transform. This approach is so powerful, in fact, that much of mathematics has shifted in emphasis to studying such mappings in abstract. The entire fields of Topology and Algebra are now mostly about mappings between objects; the mappings themselves are the new objects! The "bridge" field of Algebraic Topology is this in Spades. This process can be repeated hierarchically: collections of mappings can constitute spaces having their own geometries, and mappings between these are studied... etc. In Analysis, this is subsumed under the field of Functional Analysis, where the objects of study are algebra-preserving mappings between a space of functions and a base field. This is of special interest to me, because most of my theoretical work is in this area. Here is a simple example: Consider the Cartesian Plane, R2. Each point is an ordered pair of real numbers. Consider the point (a,b). I could identify this point with the line that has intercept a and slope b: the mapping L(x)=a + bx from R to R. I have identified each point with a function. Given a function, L(x)= a +bx, I could pull out its coefficients or order 0 and 1, and put them in an ordered pair, (a,b), which I can think of as a point in R2. I have identified a function with a point. Now I can ask all kinds of interesting questions. Notice that a line in R2 consists of infinitely many points. Regarding each of these points as a function (using the coordinates of each point as coefficients to define a function as above), I see that the original line characterizes an infinite collection of lines (as functions) in another space, called the "Dual Space". This allows me to geometrize, topologize, and analyze spaces where the "points" are functions: function spaces. This process can be repeated hierarchically, forever. This approach has resulted in the emergence of entirely new areas of mathematics. A very recent one is "Information Geometry", where each point in the space is a probability distribution, and the goal is to find the "best path" in this space from one probability distribution to another. Believe it or not, this is very practical, having significant applications in machine intelligence particularly in the areas of document understanding, and certain kinds of optimization. Quite a few of the problems I have posed here on the Forum have this flavor. Keep your eyes open and you will notice this.
Last edited by Monte314; 07-30-2012 at 08:12 AM.
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#53 | ||||||
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Core Member [109%]
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I noticed this myself when in university, so much so, that I was thinking of doing a dissertation on Lattice Theory in my final year, even though for my degree in maths, we didn't need to do a dissertation.
Excellent points. I'll keep this in mind in the future. |
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