Circle Geometry

Today, I thought I’d share a little more about things learned along the way with my curriculum consulting.  As I mentioned before, I’m creating a series of online lectures for the Geometry unit.  This past week, the section I was working on (and will still be working on into next week) is Circle Geometry.

As I also remarked earlier, I’m using the University of Chicago School Mathematics Project’s textbook on Geometry as a reference.  In this text are many theorems about the measure of the angle between two intersecting lines in terms of the measures of the intercepted arcs.

This image is certainly familiar.


The question I had to consider was how to organize all these results in a coherent 5–7-minute lecture.  It turns out that there was too much for just one lecture, so I did spread it out into two.  But I still needed a flow.

Although the results were not new to me, I had never taught this topic before.  My main experience teaching geometry at the high school level was designing and teaching a course on spherical trigonometry as it applies to studying polyhedra.  So this gave me an opportunity to stand back and just think about putting it all together.

I was happy with what I came up with — an approach which could be classified under “combinatorial geometry.”  I decided to pose the following question:


In other words, if you have two intersecting lines, and you draw a circle so that it intersects both lines, what configurations are possible?

Looked at in this way, there are just two considerations:  whether the intersection of the lines is outside, on, or inside the circle, and whether the lines are secant or tangent lines.

It’s not difficult to make the enumeration, so I’ll just give it briefly here.  There is only one configuration if the intersection of the lines lies inside the circle, since both lines must be secant lines.


When the intersection of the lines is on the circle, one of the lines may be tangent, although both cannot be since there is a unique tangent at any given point on a circle.  And when the intersection of the lines is outside the circle, zero, one, or two of the lines may be tangent to the circle.

This enumeration allows for a systematic approach.  If you’ve ever worked through find the angle measures, you know that starting with the arrangement in the upper right corner is the way to begin.  I won’t go through all the details, but I will just indicate that the following figure is all you need:


This simple case is analyzed by considering \angle QOR as an angle exterior to \Delta POQ.  The analysis of all the other cases builds from this.

I decided to include a discussion not found in the UCSMP text — continuity.  Of course this is not a topic which can be rigorously discussed at say, the 10th-grade level.  But why not give students an intuition of the idea?

Let’s start with a few diagrams.


This series illustrates the case that the intersection of the lines is outside the circle, and one of the lines is tangent.  We look at this as the limiting case of a series of pairs of secant lines.

This argument depends upon the fact that the measurement of all arcs and angles varies continuously as S moves around the circle.  While, as mentioned, this cannot be addressed rigorously, it is a very intuitive argument.  Moreover, there are many different software packages you could use to make an animation of this process, and display all the arc and angle measurements as S moves around the circle.

There is no reason not to introduce this argument.  In my pair of lectures, I used more traditional geometrical arguments as well.  It doesn’t hurt students to be exposed to a wide range of proof ideas.

I summarize all of these results in the following graphic.


The measure of the angle indicated with the red dot is half the measure of the intercepted arc, or the sum/difference of the measures of the intercepts arcs, shown in red and blue.  An arc in blue indicates its measure is to be subtracted rather than added.  I was very happy with this graphic.  I think that if a student followed the lecture, they could state every result just by looking at it.

This also proved to be a great segue into looking at the power of a point.  I thought I’d begin with the figure in the upper left, proving the usual theorem using similar triangles.

And now for another continuity argument!


This is a nice way to see that the power of any point on the circle is 0.  It is also a nice contrast to the theorems about the angle between the intersecting lines:  when PT and RT eventually reach 0, you’re not able to conclude anything about a relationship between QT and ST.

This means that there is no theorem relating lengths of segments for the two cases when the intersection of the lines lies on the circle.   I use the following graphic to indicate this, with two cases grayed out when the power of the point offers no conclusion.


Now all of these results are the usual ones found in high school geometry textbooks; nothing new here.  But for me, just having to step back and think about how to put them all together was a fun challenge.

Again, I am surprised at how much I’m learning even though I’m just putting together a few slides on elementary geometry.  The process of writing these lectures is an engaging one, and I hope the students who will eventually watch them will benefit from a perspective not found in more traditional textbooks.

What Is…A Polygon?

A haven’t made a post in quite some time in my “What is a Geometry?” thread.  In working on my online lectures in the section on Polygons, I of course needed to define just what a polygon is.  This turned out to be a little more challenging than I had imagined.  I thought that the issues that arose would make this discussion an interesting continuation of the “What is a Geometry?” thread.

In general, I think that the Wikipedia does a good job with mathematics — but specifically, the definition of a polygon leaves quite a bit to be desired.  I’ll reproduce it here for you:

In elementary geometry, a polygon is a plane figure that is bounded by a finite chain of straight line segments closing in a loop to form a closed polygonal chain, or circuit.  These segments are called its edges or sides, and the points where two edges meet are the polygon’s vertices (singular: vertex) or corners.

OK, maybe not so bad of a start.  There are lots of examples given which fit this definition, but many which do not.  For example, this definition allows consecutive segments to lie on the same line, which is typically disallowed in most other definitions of polygons.

So maybe a clause may be added to the definition which does not allow this.  But then we encounter a polygon like this (I’m using screenshots from my lecture as illustrations):


My definition begins with a list of vertices — but the problem is still the same.  The vertex labeled “4” is on the edge joining the vertices labeled “1” and “2.”  Again, this is usually avoided.

And what about the following figure?


With the Wikipedia definition, a vertex can be an endpoint of more than two edges of a polygon.  Again, problematic.  There would be no way to distinguish this figure from a single polygon and two different triangles sharing a vertex.

Moreover, there is no condition saying that the straight line segments need to be distinct.  So the same segment might occur multiple times as an edge of a polygon.

None of these behaviors is illustrated anywhere on the Wikipedia page.  I’ve done some Wikipedia editing a while back, and would be interested in working on this page when I have more time to devote to such things.

So what is the fix?  I’m using the Geometry text of the University of Chicago School Mathematics Project as a reference, which is one of the most rigorous geometry texts around.  Here is their definition:


They remark that this is the definition used in 23 out of the 45 geometry text they surveyed.  And in fact, it is the rewrite of a definition in previous editions:  “A polygon is the union of segments in the same plane such that each segment intersects exactly two others, one at each of its endpoints.”  This definition was problematic, though, since by this definition, the following is actually a polygon!


Now this revised definition solves all of the problems above — but I couldn’t use it.  Why not?

One of the sections I’ll be writing lectures for is three-dimensional geometry — and (of course) I’ll be saying a lot about polyhedra in this section.  There are Platonic and Archimedean solids, as well as the Kepler-Poinsot polyhedra, like the small stellated dodecahedron shown below.


The faces of the small stellated dodecahedron are pentagrams, five meeting at each vertex.

But the UCSMP definition does not allow edges to cross.  Each edge meets exactly two others, at each of its endpoints.  So that means that an edge cannot cross another in its interior.

Now I just can’t talk about polyhedra without talking about nonconvex examples.  Sure, it is possible to talk about pentagrams with edges crossing as decagons without crossing edges.


But this would be the height of absurdity.  Besides the fact that none of the dozens of books and articles I’ve read on polyhedra in the past few decades ever do such a thing — and I’m sure none ever will.

So I had to go it alone.  I’ll share with you my definition — but I can’t say it’s the best.  The difficulty lies with being mathematically precise while still making the definition accessible to high school students.  Here it is:

A polygon is determined by a list of its vertices. Edges of the polygon connect adjacent vertices in the list, and there is also an edge connecting the last vertex in the list to the first one. All vertices in the list must be different. Finally, no three consecutive vertices of the polygon can lie on the same line, and no vertex can lie in the interior of another edge.

I don’t think this is too bad.  But there is still a subtle glitch, which I haven’t worked out yet, and which doesn’t necessarily need to be worked out at this level.  When I talk about triangles, for example, I allow cases where the sides have lengths 3, 4, and 7, for example.  But I qualify such a triangle by calling it a degenerate triangle.

Since a triangle is a polygon, a degenerate triangle should be a degenerate polygon, right?  The problem is that calling something a “degenerate polygon” gives the impression that it is actually some type of polygon.  But a degenerate triangle, by my definition, is not a polygon.  So when I use the term degenerate polygon, I’m not actually talking about a polygon….

So I’ll let you think this over.  I just wanted to share how surprised I was at how subtle the definition of something so “simple” could be.  An ordinary polygon.

If you find this sort of question intriguing, you might go online and research all the various definitions of polyhedron.  Convex polyhedra are easy to define (as are convex polygons), but when you get into the different types of behavior possible in the nonconvex cases, well, it becomes problematic.  In fact, no one, as far as I know, has ever come up with a satisfactory definition for “polyhedron.”  Might even do a blog post on that some day….

Pythagorean Triples

I recently began writing some lectures for an online course — I’ll talk more about the nature of the course in next week’s post.  The broad topic is geometry, of course a favorite — and the specific topic for this unit is Triangles.

You can’t talk about triangles without talking about the Pythagorean Theorem.  Part of my job is also to compose problems for the lectures as well as for quizzes and exams, and to my surprise, I came up with a few interesting ones.  So I thought I’d share them with you.  I am always a fan of sharing mathematics as it happens!

The questions I wrote are based on the following parameterization of Pythagorean Triples:  Given positive integers p and q, then


is a Pythagorean Triple.  This parameterization generates all primitive Pythagorean Triples — that is, triples whose sides share no common factor.  But it is not possible to get (9,12,15), for example, using this parameterization.  Of course (9,12,15) is just three times the triple (3,4,5); therefore, if you can generate all primitive Pythagorean Triples, you can take multiples of them to generate all Pythagorean Triples.

I thought of my first problem walking down the sidewalk going to lunch the other day.  The simplest Pythagorean Triple, (3,4,5), has side lengths which are in arithmetic progression.  What other Pythagorean Triples have this property?

The simplest way to approach this is to parameterize such a triple by (a,a+d,a+2d), where a>0 is the smallest integer in the arithmetic progression and d>0 is the common difference.  Since the triangle is a right triangle, we must have


which we may rewrite as


Now this factors:


resulting in solutions a=-d or a=3d.  We did assume that d>0, so we eliminate the solution a=-d.  Note that this would generate the triple (a,0,-a), and in fact a^2+0^2=(-a)^2. But one side length is zero and another is negative, so no triangle is possible with these side lengths.

What about the solution a=3d?  Here, we get


which you can observe is just a multiple d of the primitive Pythagorean Triple (3,4,5).

The conclusion?  The only Pythagorean Triples possible whose side lengths are in arithmetic progression are multiples of the (3,4,5) right triangle.

I really didn’t know the answer would come out so nicely — but since the algebra involved was fairly straightforward, I thought I could include this as a non-routine example of an application of the Pythagorean Theorem at the high school level.

The previous problem was part of a lecture.  The next problem was written as a possible exam question for teachers; once I realized I had more than one interesting problem, I thought there would be enough for a blog post….

I was just looking for interesting patterns in Pythagorean Triples, and noticed that with the (6,8,10) triangle, the area and perimeter were both 24.  A coincidence?  Were there other triangles with this property?

Of course there had to be finitely many — as the side lengths get larger, the area gets larger faster than the perimeter, as the area is essentially a quadratic function, while the perimeter is essentially a linear function.  So how many others are there?  Make a mental note of your guess before reading further….

We begin by parameterizing by


the factor of k is necessary since the two-variable version generates all primitive Pythagorean Triples, but not necessarily all Pythagorean Triples.

Setting the perimeter and area equal to each other results in


Cancelling out factors of k, q, and p+q results in


This equation clearly has just three solutions, since one of the factors must be 2 and the other two factors must be 1.

None is particular difficult; let’s take them one at a time.  When k=2, then p=q-p=1, so that q=2.  Substituting back into the parameterization, we obtain the Pythagorean Triple 2(3,4,5), which is the triple (6,8,10).

When p=2, then  k=q-p=1, so that q=3. This generates a new Pythagorean Triple, (5,12,13).

Finally, when q-p=2, then k=p=1 and q=3, so that the Pythagorean Triple (8,6,10) is generated.  Of course this is just a duplicate of the first solution.

Surprised that there was just one more solution?  I was!  It was such a nice, straightforward solution, that I couldn’t help but include it.

There was a third problem which I liked, but the algebra was a little too intense — there was a nice geometrical solution, but it required ideas learned later on in the course.  So here it is if you want a challenge:  suppose you are given two right triangles, and you know that their perimeters and areas are the same.  Prove that they are congruent.

I think you might enjoy solving this purely algebraically.  I did like it so much, though, that I included a simpler version in one of my lectures:  suppose you are given two right triangles, and you know that their hypotenuses are both of length 8 and that their perimeters are equal.  Prove that the triangles are congruent.

To be honest, I never knew I’d find problem solving with the Pythagorean Theorem so interesting.  It’s nice to know that there is always more geometry to learn!  Even with something as apparently simple as the venerable Pythagorean Theorem….

Calculus: The Geometry of Polynomials, II

The original post on The Geometry of Polynomials generated rather more interest that usual.  One reader, William Meisel, commented that he wondered if something similar worked for curves like the Folium of Descartes, given by the equation


and whose graph looks like:


I replied that yes, I had success, and what I found out would make a nice follow-up post rather than just a reply to his comment.  So let’s go!

Just a brief refresher:  if, for example, we wanted to describe the behavior of y=2(x-4)(x-1)^2 where it crosses the x-axis at x=1, we simply retain the (x-1)^2 term and substitute the root x=1 into the other terms, getting


as the best-fitting parabola at x=1.

Now consider another way to think about this:

\displaystyle\lim_{x\to1}\dfrac y{(x-1)^2}=-6.

For examples like the polynomial above, this limit is always trivial, and is essentially a simple substitution.

What happens when we try to evaluate a similar limit with the Folium of Descartes?  It seems that a good approximation to this curve at x=0 (the U-shaped piece, since the sideways U-shaped piece involves writing x as a function of y) is y=x^2/3, as shown below.


To see this, we need to find

\displaystyle\lim_{x\to0}\dfrac y{x^2}.

After a little trial and error, I found it was simplest to use the substitution z=y/x^2, and so rewrite the equation for the Folium of Descartes by using the substitution y=x^2z, which results in


Now it is easy to see that as x\to0, we have z\to1/3, giving us a good quadratic approximation at the origin.

Success!  So I thought I’d try some more examples, and see how they worked out.  I first just changed the exponent of x, looking at the curve


shown below when n=6.


What would be a best approximation near the origin?  You can almost eyeball a fifth-degree approximation here, but let’s assume we don’t know the appropriate power and make the substitution y=x^kz, with k yet to be determined. This results in


Now observe that when k=n-1, we have


so that \displaystyle\lim_{x\to0}z=1/3. Thus, in our case with n=6, we see that y=x^5/3 is a good approximation to the curve near the origin.  The graph below shows just how good an approximation it is.


OK, I thought to myself, maybe I just got lucky.  Maybe introduce a change which will really alter the nature of the curve, such as


whose graph is shown below.


Here, the curve passes through the x-axis at x=1, with what appears to be a linear pass-through.  This suggests, given our previous work, the substitution y=(x-1)z, which results in


We don’t have much luck with \displaystyle\lim_{x\to1}z here.  But if we move the 1 to the other side and factor, we get


Nice!  Just divide through by x-1 to obtain


Now a simple calculation reveals that \displaystyle\lim_{x\to1}z=1. And sure enough, the line y=x-1 does the trick:


Then I decided to change the exponent again by considering


Here is the graph of the curve when n=6:


It seems we have two roots this time, with linear pass-throughs.  Let’s try the same idea again, making the substitution y=(x-1)z, moving the 1 over, factoring, and dividing through by x-1.  This results in


It is not difficult to calculate that \displaystyle\lim_{x\to1}z=n/3.

Now things become a bit more interesting when n is even, since there is always a root at x=-1 in this case.  Here, we make the substitution y=(x+1)z, move the 1 over, and divide by x+1, resulting in


But since n is even, then x^2-1 is a factor of x^n-1, so we have


Substituting x=-1 in this equation gives

-2\left(\dfrac n2\right)=3(-1)z,

which immediately gives  \displaystyle\lim_{x\to1}z=n/3 as well!  This is a curious coincidence, for which I have no nice geometrical explanation.  The case when n=6 is illustrated below.


This is where I stopped — but I was truly surprised that everything I tried actually worked.  I did a cursory online search for Taylor series of implicitly defined functions, but this seems to be much less popular than series for y=f(x).

Anyone more familiar with this topic care to chime in?  I really enjoyed this brief exploration, and I’m grateful that William Meisel asked his question about the Folium of Descartes.  These are certainly instances of a larger phenomenon, but I feel the statement and proof of any theorem will be somewhat more complicated than the analogous results for explicitly defined functions.

And if you find some neat examples, post a comment!  I’d enjoy writing another follow-up post if there is continued interested in this topic.

The Geometry of Polynomials

I recently needed to make a short demo lecture, and I thought I’d share it with you.  I’m sure I’m not the first one to notice this, but I hadn’t seen it before and I thought it was an interesting way to look at the behavior of polynomials where they cross the x-axis.

The idea is to give a geometrical meaning to an algebraic procedure:  factoring polynomials.  What is the geometry of the different factors of a polynomial?

Let’s look at an example in some detail:  f(x)=2(x-4)(x-1)^2.poly0b

Now let’s start looking at the behavior near the roots of this polynomial.


Near x=1, the graph of the cubic looks like a parabola — and that may not be so surprising given that the factor (x-1) occurs quadratically.


And near x=4, the graph passes through the x-axis like a line — and we see a linear factor of (x-4) in our polynomial.

But which parabola, and which line?  It’s actually pretty easy to figure out.  Here is an annotated slide which illustrates the idea.


All you need to do is set aside the quadratic factor of (x-1)^2, and substitute the root, x=1, in the remaining terms of the polynomial, then simplify.  In this example, we see that the cubic behaves like the parabola y=-6(x-1)^2 near the root x=1. Note the scales on the axes; if they were the same, the parabola would have appeared much narrower.

We perform a similar calculation at the root x=4.


Just isolate the linear factor (x-4), substitute x=4 in the remaining terms of the polynomial, and then simplify.  Thus, the line y=18(x-4) best describes the behavior of the graph of the polynomial as it passes through the x-axis.  Again, note the scale on the axes.

We can actually use this idea to help us sketch graphs of polynomials when they’re in factored form.  Consider the polynomial f(x)=x(x+1)^2(x-2)^3.  Begin by sketching the three approximations near the roots of the polynomial.  This slide also shows the calculation for the cubic approximation.


Now you can begin sketching the graph, starting from the left, being careful to closely follow the parabola as you bounce off the x-axis at x=-1.


Continue, following the red line as you pass through the origin, and then the cubic as you pass through x=2.  Of course you’d need to plot a few points to know just where to start and end; this just shows how you would use the approximations near the roots to help you sketch a graph of a polynomial.


Why does this work?  It is not difficult to see, but here we need a little calculus.  Let’s look, in general, at the behavior of f(x)=p(x)(x-a)^n near the root x=a.  Given what we’ve just been observing, we’d guess that the best approximation near x=a would just be y=p(a)(x-a)^n.

Just what does “best approximation” mean?  One way to think about approximating, calculuswise, is matching derivatives — just think of Maclaurin or Taylor series.  My claim is that the first n derivatives of f(x)=p(x)(x-a)^n and y=p(a)(x-a)^n match at x=a.

First, observe that the first n-1 derivatives of both of these functions at x=a must be 0.  This is because (x-a) will always be a factor — since at most n-1 derivatives are taken, there is no way for the (x-a)^n term to completely “disappear.”

But what happens when the nth derivative is taken?  Clearly, the nth derivative of p(a)(x-a)^n at x=a is just n!p(a).  What about the nth derivative of f(x)=p(x)(x-a)^n?

Thinking about the product rule in general, we see that the form of the nth derivative must be f^{(n)}(x)=n!p(x)+ (x-a)(\text{terms involving derivatives of } p(x)). When a derivative of p(x) is taken, that means one factor of (x-a) survives.

So when we take f^{(n)}(a), we also get n!p(a).  This makes the nth derivatives match as well.  And since the first n derivatives of p(x)(x-a)^n and p(a)(x-a)^n match, we see that p(a)(x-a)^n is the best nth degree approximation near the root x=a.

I might call this observation the geometry of polynomials. Well, perhaps not the entire geometry of polynomials….  But I find that any time algebra can be illustrated graphically, students’ understanding gets just a little deeper.

Those who have been reading my blog for a while will be unsurprised at my geometrical approach to algebra (or my geometrical approach to anything, for that matter).  Of course a lot of algebra was invented just to describe geometry — take the Cartesian coordinate plane, for instance.  So it’s time for algebra to reclaim its geometrical heritage.  I shall continue to be part of this important endeavor, for however long it takes….

Geometrical Dissections III: Octagons and Dodecagons

It has been quite a while since I’ve written about geometrical dissections.  For a brief refresher, you might want to look at my first post on dissections.

But recently my interest has been rekindled — to the point that I started writing a paper a few weeks ago!  I often like to share mathematics I’m working on as it’s happening to give you some idea of the process of doing mathematics.  The paper has quite a bit more mathematics in it than I’ll include in this post, but I’ll try to give you the gist of what’s involved.

Recall (again, see my first post for a more thorough discussion) that I’m interested in finding dissections that you can draw on graph paper — I find these more enjoyable as well as being accessible to a wider audience.  So all the dissections I’ll talk about will be based on a grid.

The first example is a dissection of two octagons to one, such as shown below.


In other words, you can take the pieces from the two smaller octagons, move them around, and build the larger octagon.  If you look carefully, you’ll notice that the larger octagon is rotated 45° relative to the smaller octagons.  Geometrically, this is because to get an octagon twice the area of a given octagon, you scale the side lengths by \sqrt2.  Imagine a square — a square with side length S has area S^2, while a square with side length \sqrt2S has area (\sqrt2S)^2=2S^2  — which is double the area.

Now think of a segment of unit length.  To get a segment of length \sqrt2, you need to take a diagonal of a unit square, which rotates the segment by 45° as well as scales it by a factor of \sqrt2.  This is why the larger octagon is rotated with respect to the smaller ones.

But what makes this dissection interesting is that there is an infinite family of very similar dissections.  By slightly varying the parameters, you get  a dissection which looks like this:


Here, you can clearly see the 45° rotation of the larger octagon.  I always enjoy finding infinite families of dissections — it is very satisfying to discover that once you’ve found one dissection, you get infinitely many more for free!

The proof that this always works (which I will omit here!) involves using a geometrical argument — using arbitrary parameters — to show that the green triangles always have to be right isosceles triangles.  This is the essential feature of the dissection which makes it “work” all the time.

The second example I’m including in the paper is a dissection on a triangular grid, like the one below.


Note that the figure on the left is an irregular dodecagon; that is, it has twelve sides.  Recall that the interior angles of a regular dodecagon have measure 150° — but so do the angles of this irregular dodecagon as it is drawn on a triangular grid.

If you look carefully, you’ll see how the sides in the pieces of the dissection on the right match up with sides of the same length from the other pieces.  Also, looking at the dissection on the right, you’ll see that around all the interior vertices, there are two angles with measure 150° and one with measure 60°, adding up to 360° — as we would expect if the pieces fit exactly together.

And — as you might have guessed from the first example — this is also one of an infinite family of dissections.  As long as the sides of the irregular dodecagon alternate and the vertices stay on the triangular lattice, there is a dissection to a rhombus.  Below is another example, and there are infinitely many more….


My third and final example involves irregular dodecagons, but this time on a square grid.  And while I found the previous two dissections several years ago, I found this example just last week!  What inspired me was one of my favorite dissections — from an irregular dodecagon to a square — also found many years ago.


In the spirit of the first two examples, I asked myself if this dissection could be one of an infinite family.  The difficulty here was that there were three parameters determining an irregular dodecagon, as shown below.


We do need b>c so that the dodecagon is convex and actually has 12 sides; if b=c, four pairs of sides are in perfect alignment and the figure becomes an octagon.

There is an additional constraint, however, which complicates things a bit.  The area of this dodecagon must also be the area of some tilted square with vertices on the grid, as illustrated below.  Note that the area of this square is just d^2+e^2.


It is not a difficult geometry exercise to show that the area of the dodecagon is a^2+4(a+b)(c+b).  So in order to create a dissection, we must find a solution to the equation


Again, here is not the place to go into details.  But it is possible to find an infinite family of solutions when a=e.  You get a dissection which looks like this:


I was particularly pleased to have found this eight-piece dissection since most of my attempts until this point had ten pieces or more.  And to give you a sense of this family of dissections, here is an example with different parameters within this family.


You can definitely see the resemblance, but it is also clear that the dodecagon and square are not the same shape as those in the previous dissection.

So these are the three families of geometrical dissections I’ll be including in my paper.  I hope these examples might inspire you to pick up a pencil and graph paper and try to find some infinite families of your own!



In working on a proposal for a book about three-dimensional polyhedra last week, I needed to write a brief section on polygons.  I found that there were so many different types of polygons with such interesting properties, I thought it worthwhile to spend a day talking about them.  If you’ve never thought a lot about polygons before, you might be surprised how much there is to say about them….

So start by imagining a polygon — make it a pentagon, to be specific.  Try to imagine as many different types of pentagons as you can.

How many did you come up with?  I stopped counting when I reached 20….

Likely one of the first to come to mind was the regular pentagon — five equal sides at angles of 108° from each other.  Question:  did you only think of the vertices and edges, or did you include the interior as well?


Why consider this question?  An important geometrical concept is that of convexity.  A convex polygon property has the property that a line segment joining any two points in the polygon lies entirely within the polygon.


The two polygons on the left are convex, while the two on the right are not.  But note that for this definition to make any sense at all, a polygon must include all of its interior points.

Convex polygons have various properties.  For example, if you take the vertices of a convex polygon and imagine stretching a rubber band beyond the vertices and letting it snap back, the rubber band will describe the edges of the polygon.  See this Wikipedia article on convex polygons for more properties of convex polygons.

Did the edges of any of your pentagons cross each other, like the one on the left below?


In this picture, we indicate vertices with dots to illustrate that this is in fact a pentagon.  The points where the edges cross are not considered vertices of the polygon.  The polygon on the right is actually a nonconvex decagon, even though it bears a resemblance to the pentagon on the left.

But not so fast!  If you ask Mathematica to draw the polygon on the left with the five vertices in the order they are traversed when drawing the edges, here is what you get:


So what’s going on here?  Why is the pentagon empty in the middle?  When I gave the same instructions using Tikz in LaTeX (which is how I created the light blue pentagram shown above), the middle pentagon was filled in.

Some computer graphics programs use the even-odd rule when drawing self-intersecting polygons.  This may be thought of in a few ways.  First, if you imagine drawing a segment from a point in the interior pentagon to a point outside, you have to cross two edges of the pentagon, as shown above.  If you draw a segment from a point in one of the light red regions to a point outside, you only need to cross one edge.  Points which require crossing an even number of edges are not considered as being interior to the polygon.

Said another way, if you imagine drawing the pentagram, you will notice that you are actually going around the interior pentagon twice.  Any region traversed twice (or an even number of times) is not considered interior to the polygon.

Why would you want to color a polygon in this way?  There are mathematical reasons, but if you watch this video by Vi Hart all the way through, you’ll see some compelling visual evidence why you might want to do this.

We call polygons whose edges intersect each other self-intersecting or crossed polygons.  And as you’ve seen, including the interiors can be done in one of two different ways.

But wait!  What about this polygon?  Can you really have a polygon where a vertex actually lies on one of the edges?


Again, it all depends on the context.  I think you’re beginning to see that the question “What is a pentagon?” is actually a subtle question.  There are many features a pentagon might have which you likely would not have encountered in a typical high school geometry course, but which still merit some thought.

Up to now, we’ve just considered a polygon as a two-dimensional geometrical object.  What changes when you jump up to three dimensions?

Again, it all depends on your definition.  You might insist that a polygon must lie in a plane, but….

It is possible to specify a polygon by a list of points in three dimensions — just connect the points one by one, and you’ve got a polygon!  Of course with this definition, many things are possible — maybe you can repeat points, and maybe the points do not all lie in the same plane.

An interesting example of such a polygon is shown below, outlined in black.


It is called a Petrie polygon after the mathematician who first described it.  In this case, it is a hexagon — think of holding a cube by two opposite corners, and form a hexagon by the six edges which your fingers are not touching.

There is a Petrie polygon for every Platonic solid, and may be defined as follows:  it is a closed path of connected edges such that no three consecutive edges belong to the same face.  If you look at the figure above, you’ll find this is an alternative way to define a Petrie hexagon on a cube.

And if that isn’t enough, it is possible to define a polygon with an infinite number of sides!  Just imagine the following jagged segment continuing infinitely in both directions.


This is called an apeirogon, and may be used to study the tiling of the plane by squares, four meeting at each vertex of the tiling.

And we haven’t even begun to look at polygons in other geometries — spherical geometry, projective geometry, inversive geometry….

Suffice it to say that the world of polygons is much more than just doodling a few triangles, squares or pentagons.  It is always amazes me how such a simple idea — polygon — can be the source of such seemingly endless investigation!  And serve as another illustration of the seemingly infinite diversity within the universe of Geometry….