Mathematics and Digital Art: Update 3

It’s hard to believe it’s been a month since my last update!  This semester has been unusually busy.

At the end of my last update, I said I’d talk more about using L-systems in class.  I decided to focus on the symmetrical Koch-like images I had been working on for the past few years.  There are two reasons for this.  First, it’s fresh — and demonstrates that creating new fractal images is an active research topic; not everything is known.  Second, you need to know some elementary number theory in order to create symmetrical images.  Since none of the mathematics we studied so far was closely related to number theory, this was a great opportunity to see yet another application of a different branch of mathematics.

Day007koch-45-175

I started with introducing the basics of modular arithmetic.  This was new to most students, but the motivation was easy:  the direction you’re pointing after any given move is relevant to deciding if your sequence of segments closes up.  And any time you turn counterclockwise, you increment the direction by the angle you turn, but subtract 360° when you go over 360° since a turn of 360° doesn’t alter your direction.  This is just using a modulus of 360 for the direction you’re pointing.

Then, I reminded them how to find the prime factorization of numbers in order to create a 2-adic valuation.  Recall that the 2-adic valuation of a number is the exponent of the highest power of 2 which divides that number.  This is significant since the 2-adic valuation (mod 2) indicates how to turn when drawing a Koch-like curve:  a 0 represents one angle (60° for the Koch curve), and a 1 represents the other (240° for the Koch curve).  So we created charts like this:

Day0902adic

Then finally, I showed students how to find angle pairs which created symmetrical images using a theorem in a paper I’m working on for the College Mathematics Journal.  As the proof involves significantly more mathematics at a level beyond what we could reasonably discuss in the course, I just showed them the result.  I won’t go into details here, but I’d be glad to share a draft of the paper if you’re interested and adventurous….

For their project work, they had to create images using the results of the theorem in Processing.  Karla created this image, which I find interesting since it exhibits six-fold symmetry, but the exterior elements have seven points on them.  So rarely do you encounter 6 and 7 together in geometry.

Day090karla

Peyton created this image, which is suggestive of a complete image, but which doesn’t include all the line segments.  But the overall symmetry of the image is clear; you can complete it in your mind’s eye.

Day090Peyton

I also asked students to create an image which did not close up, to experiment with parameters which generated a more chaotic image.  Colette created this image, which reminded her of the top of a pine tree.

Day090Colette

Some students did have difficulty using the theorem correctly to generate images with symmetry, so next semester I’ll spend a little extra time making sure everyone’s on track.

We also had another guest speaker visit the class since the last update.  I met Gwen Fisher at the Art Exhibition in Santa Clara at the Regional MAA meeting last month, and thought she would be a great fit for our class.  What I liked about her art is that she works with beads in very mathematical ways — and her work is very different from anything we had been doing in the class.

She brought in several of examples of her beadwork to pass around.  You can see many beautiful pieces on her website, including this Wisdom Mandala piece she designed.

Day090Gwen
Wisdom Mandala, by Gwen Fisher.

What was wonderful about her presentation was that Gwen discussed both the design and the execution of her pieces.  My students were very engaged, and asked lots of questions along the way.

It turns out, though, that I had seen a talk she gave two or three years ago at another conference!  Of course you can’t remember every speaker you see at every conference you attend, especially out of context.  But after seeing her talk, I realized some of the slides looked strangely familiar, and that is because I had actually seen them before….

One more bit of news.  You might remember that Mathematics and Digital Art has been offered as a First-Year Seminar course this year, meaning that only first-year students may enroll, and the maximum number of students in the course is set at 16.

Being a faculty member at the University of San Francisco, I am also working on a project with colleagues in creating a Mathematics for Educators minor — a series of courses aimed at prospective middle-school teachers to broaden their knowledge of mathematics especially suited to middle-school students.  And of course a digital art course would fit nicely into this framework.

But what if a student decides to opt for the minor after their first year?  Well, they couldn’t take digital art.  So now, the course is a regular offering in the Mathematics and Statistics Department, open to any student at USF.  I’m very excited about this, and really hope to spread the word about the Imagifractalous world of mathematics and digital art!

I’ll keep you updated in the Fall, as I have more changes in store for the course.  I plan to move completely to Processing, since now everything I used Sage for has been rewritten for Processing.  And next semester, I’ll include a short unit on binary trees as well.  Stay tuned….

Imagifractalous! 6: Imagifractalous!

No, the title of today’s post is not a typo….

About a month ago, a colleague who takes care of the departmental bulletin boards in the hallway approached me and asked if I’d like to create a bulletin board about mathematical art.  There was no need to think it over — of course I would!

Well, of course we would, since I immediately recruited Nick to help out.  We talked it over, and decided that I would describe Koch-like fractal images on the left third of the board, Nick would discuss fractal trees on the right third, and the middle of the bulletin board would highlight other mathematical art we had created.

I’ll talk more about the specifics in a future post — especially since we’re still working on it!  But this weekend I worked on designing a banner for the bulletin board, which is what I want to share with you today.

BBoardBanner

I really had a lot of fun making this!  I decided to create fractals for as many letters of Imagifractalous! as I could, and use isolated letters when I couldn’t.  Although I did opt not to use a third fractal “A,” since I already had ideas for four fractal letters in the second line.

The “I”‘s came first.  You can see that they’re just relatively ordinary binary trees with small left and right branching angles.  I had already incorporated the ability to have the branches in a tree decrease in thickness by a common ratio with each successive level, so it was not difficult to get started.

I did use Mathematica to help me out, though, with the spread of the branches.  Instead of doing a lot of tweaking with the branching angles, I just adjusted the aspect ratio (the ratio of the height to the width of the image) of the displayed tree.  For example, if the first “I” is displayed with an aspect ratio of 1, here is what it would look like:

2017-04-16Tree1

I used an aspect ratio of 6 to get the “I” to look just like I wanted.

Next were the “A”‘s.  The form of an “A” suggested an iterated function system to me, a type of transformed Sierpinski triangle.  Being very familiar with the Sierpinski triangle, it wasn’t too difficult to modify the self-similarity ratios to produce something resembling an “A.”  I also like how the first “A” is reminiscent of the Eiffel Tower, which is why I left it black.

I have to admit that discovering the “R” was serendipitous.  I was reading a paper about trees with multiple branchings at each node, and decided to try a few random examples to make sure my code worked — it had been some time since I tried to make a tree with more than two branches at each node.

fR

When I saw this, I immediately thought, “R”!  I used this image in an earlier draft, but decided I needed to change the color scheme.  Unfortunately, I had somehow overwritten the Mathematica notebook with an earlier version and lost the code for the original “R,” but luckily it wasn’t hard to reproduce since I had the original image.  I knew I had created the branches only using simple scales and rotations, and could visually estimate the original parameters.

The “C” was a no-brainer — the fractal C-curve!  This was fairly straightforward since I had already written the Mathematica code for basic L-systems when I was working with Thomas last year.  This fractal is well-known, so it was an easy task to ask the internet for the appropriate recursive routine to generate the C-curve:

+45  F  -90  F  +45

For the coloring, I used simple linear interpolation from the RGB values of the starting color to the RGB values of the ending color.  Of course there are many ways to use color here, but I didn’t want to spend a lot of time playing around.  I was pleased enough with the result of something fairly uncomplicated.

For the “T,” it seemed pretty obvious to use a binary tree with branching angles of 90° to the left and right.  Notice that the ends of the branches aren’t rounded, like the “I”‘s; you can specify these differences in Mathematica.  Here, the branches are emphasized, not the leaves — although I did decide to use small, bright red circles for the leaves for contrast.

The “L” is my favorite letter in the entire banner!  Here’s an enlarged version:

fL

This probably took the longest to generate, since I had never made anything quite like it before.  My inspiration was the self-similarity of the L-tromino, which may be made up of four smaller copies of itself.

2017-04-16Ltromino

The problem was that this “L” looked too square — I wanted something with a larger aspect ratio, but keeping the same self-similarity as much as possible.  Of course exact self-similarity isn’t possible in general, so it took a bit of work to approximate is as closely as I could.  I admit the color scheme isn’t too creative, but I liked how the bold, primary colors emphasized the geometry of the fractal.

The “O” was the easiest of the letters — I recalled a Koch-like fractal image I created earlier which looked like a wheel with spokes and which had a lot of empty space in the interior.  All I needed to do was change the color scheme from white-on-gray  to black-on-white.

Finally, the “S.”  This is the fractal S-curve, also known as Heighway’s dragon.  It does help to have a working fractal vocabulary — I knew the S-curve existed, so I just asked the internet again….  There are many ways to generate it, but the easiest for me was to recursively producing a string of 0’s and 1’s which told me which way to turn at each step.  Easy from there.

So there it is!  Took a lot of work, but it was worth it.  I’ll take a photo when it’s actually displayed — and update you when the entire bulletin board is finally completed.  We’ve only got until the end of the semester, so it won’t be too long….

Imagifractalous! 5: Binary Trees III

Last week I talked about working with binary trees whose branching ratio is 1 or greater.  The difficulty with having a branching ratio larger than one is that the tree keeps growing, getting larger and larger with each iteration.

But when you work with software like Mathematica, for example, and you create such a tree, you can specify the size of the displayed image in screen size.

So the trees above both have branching ratio 2 and branching angle of 70°.  The left image is drawn to a depth of 7, and the right image is drawn to a depth of 12.  I specified that both images be drawn the same size in Mathematica.

But even though they are visually the same size, if you start with a trunk 1 unit in length, the left image is about 200 units wide, while the second is 6000 units wide!

So this prompted us to look at scaling back trees with large branching ratios.  In other words, as trees kept getting larger, scale them back even more.  You saw why this was important last week:  if the scale isn’t right, when you overlap trees with r less than one on top of the reciprocal tree with branching ratio 1/r, the leaves of the trees won’t overlap.  The scale has to be just right.

2017-04-08ris2d.png

So what should these scale factors be?  This is such an interesting story about collaboration and creativity — and how new ideas are generated — that I want to share it with you.

For your usual binary tree with branching ratio less than one, you don’t have to scale at all.  The tree remains bounded, which is easy to prove using convergent geometric series.
2017-01-20ris1

What about the case when r is exactly 1, as shown in the above figure?  At depth n, if you start with a trunk of length 1, the path from the base of the trunk to the leaf is a path of exactly n + 1 segments of length 1, and so can’t be any longer than n + 1 in length.  As the branching angle gets closer to 0°, you do approach this bound of n + 1.  So we thought that scaling back by a factor of n + 1 would keep the tree bounded in the case when r is 1.

What about the case when r > 1?  Let’s consider the case when r = 2 as an example.  The segments in any path are of length 1, 2, 4, 8, 16, etc., getting longer each time by a power of 2.  Going to a depth of n, the total length is proportional to 2^n in this case.  In general, the total length is about 2\cdot r^n for arbitrary r, so scaling back by a factor of r^n would keep the trees bounded as well.

So we knew how to keep the trees bounded, and started including these scaling factors when drawing our images.  But there were two issues.  First, we still had to do some fudging when drawing trees together with their reciprocal trees.  We could still create very appealing images, but we couldn’t use the scale factor on its own.

And second — and perhaps more importantly — Nick had been doing extensive exploration on his computer generating binary trees.  Right now, we had three different cases for scaling factors, depending on whether r < 1, r = 1, or r > 1.  But in Nick’s experience, when he moved continuously through values of r less than 1 to values of r greater than one, the transition looked very smooth to him.  There didn’t seem to be any “jump” when passing through r = 1, as happened with the scale factors we had at the moment.

I wasn’t too bothered by it, though.  There are lots of instances in mathematics where 1 is some sort of boundary point.  Take geometric series, for example.  Or perhaps there is another boundary point which separates three fundamentally different types of solutions.  For example, consider the quadratic equation

x^2+c=0.

The three fundamentally different solution sets correspond to  c < 0, c = 0, and c > 0.  There is a common example from differential equations, too, though I won’t go into that here.  Suffice it to say, this type of trichotomy occurs rather frequently.

I tried explaining this to Nick, but he just wouldn’t budge.  He had looked at so many binary trees, his intuition led him to firmly believe there just had to be a way to unify these scale factors.

I can still remember the afternoon — the moment — when I saw it.  It was truly beautiful, and I’ll share it in just a moment.  But my point is this:  I was so used to seeing trichotomies in mathematics, I was just willing to live with these three scale factors.  But Nick wasn’t.  He was tenacious, and just insisted that there was further digging to do.

Don’t ask me to explain how I came up with it.  It was like that feeling when you just were holding on to some small thing, and now you couldn’t find it.  But you never left the room, so it just had to be there.  So you just kept looking, not giving up until you found it.

And there is was:  if the branching ratio was and you were iterating to a depth of n, you scaled back by a factor of

\displaystyle\sum_{k=0}^n r^k.

This took care of all three cases at once!  When r < 1, this sum is bounded (think geometric series), so the boundedness of the tree isn’t affected.  When r = 1, you just get n + 1 — the same scaling factor we looked at before!  And when r > 1, this sum is large enough to scale back your tree so it’s bounded.

Not only that, this scale factor made proving the Dual Tree Theorem so nice.  The scaling factors for a tree with r < 1 and its reciprocal tree with branching ratio 1/r matched perfectly.  No need to fudge!

This isn’t the place to go into all the mathematics, but I’d be happy to share a copy of our paper if you’re interested.  We go into a lot more detail than I ever could in a blog post.

This is how mathematics happens, incidentally.  It isn’t just a matter of finding a right answer, or just solving an equation.  It’s a give-and-take, an exploration, a discovery here and there, tenacity, persistence.  A living, breathing endeavor.

But the saga isn’t over yet….  There is a lot more to say about binary trees.  I’ll do just that in my next installment of Imagifractalous!

Imagifractalous! 4: Fractal Binary Trees II

Now that the paper Nick and I wrote on binary trees was accepted for Bridges 2017 (yay!), I’d like to say a little more about what we discovered.  I’ll presume you’ve already read the first Imagifractalous! post on binary trees (see Day077 for a refresher if you need it).

Recall that in that post, I discussed creating binary trees with branching ratios which were 1 or larger.  Below are three examples of binary trees, with branching ratios less that 1, equal to 1, and larger than 1, respectively.

2016-12-18threetrees.png

It was Nick’s insight to consider the following question:  how are trees with branching ratio r related to those with branching ratio 1/r?  He had done a lot of exploring with graphics in Python, and observed that there was definitely some relationship.

Let’s look at an example.  The red tree is a binary tree with branching ratio r less than one, and the gray tree has a branching ratio which is the reciprocal r.  Both are drawn to the same depth.

2016-12-03-doubletree1.png

Of course you notice what’s happening — the leaves of the trees are overlapping!  This was happening so frequently, it just couldn’t be coincidence.  Here is another example.

tree1

Notice how three copies of the trees with branching ratio less than one are covering some of the leaves of a tree with the reciprocal ratio.

Now if you’ve ever created your own binary trees, you’ll likely have noticed that I left out a particularly important piece of information:  the size of the trunks of the trees.  You can imagine that if the sizes of the trunks of the r trees and the 1/r trees were not precisely related, you wouldn’t have the nice overlap.

Here is a figure taken from our paper which explains just how to find the correct relationship between the trunk sizes.  It illustrates the main idea which we used to rigorously prove just about everything we observed about these reciprocal trees.

tree2

Let’s take a look at what’s happening.  The thick, black tree has a branching ratio of 5/8, and a branching angle of 25°.  The thick, black path going from O to P is created by following the sequence of instructions RRRLL (and so the tree is rendered to a depth of 5).

Now make a symmetric path (thick, gray, dashed) starting at P and going to O.  If we start at P with the same trunk length we started with at O, and follow the exact same instructions, we have to end up back at O.

The trick is to now look at this gray path backwards, starting from O.  The branches now get larger each time, by a factor of 8/5 (since they were getting smaller by a factor of 5/8 when going in the opposite direction).  The size of the trunk, you can readily see, is the length of the last branch drawn in following the black path from O to P.  This must be (5/8)5 times the length of the trunk, since the tree is of depth 5.

The sequence of instructions needed to follow this gray path is RRLLL.  It turns out this is easy to predict from the geometry.  Recall that beginning at P, we followed the instructions RRRLL along the gray path to get to O.  When we reverse this path and go from O to P, we follow the instructions in reverse — except that in going in the reverse direction, what was previously a left turn becomes a right turn, and vice versa.

So all we need to do to get the reverse instructions is to reverse the string RRRLL to get LLRRR, and then change the L‘s to R‘s and the R‘s to L‘s, yielding RRLLL.

There’s one important detail to address:  the fact that the black tree with branching ratio 5/8 is rotated by 25° to make everything work out.  Again, this is easy to see from the geometry of the figure.  Look at the thick gray path for a moment.  Since following the instructions RRLLL means that in total, you make one more left turn than you do right turns, the last branch of the path must be oriented 25° to the left of your starting orientation (which was vertical).  This tells you precisely how much you need to rotate the black tree to make the two paths have the same starting and ending points.

Of course one example does not make a proof — but in fact all the important ideas are contained in this one illustration.  It is not difficult to make the argument more general, and we have successfully accomplished that (though this blog is not the place for it!).

If you look carefully at the diagram, you’ll count that there are exactly 10 leaves in common with these two trees with reciprocal branching ratios.  There is some nice combinatorics going on here, which is again easy to explain from the geometry.

You can see that these common leaves (illustrated with small, black dots) are at the ends of gray branches which are oriented 25° from the vertical.  Recall that this specific angle came from the fact that there was one more L than there were R‘s in the string RRLLL.

Now if you have a sequence of 5 instructions, the only way to have exactly one more L than R‘s is to have precisely three L‘s (and hence two R‘s).  And the number of ways to have three L‘s in a string of length 5 is just

\displaystyle{5\choose3}=10.

Again, these observations are easy to generalize and prove rigorously.

And where does this take us?

canopies.png

On the right are 12 copies of a tree with a braching ratio of r less than one and a branching angle of 30°, and on the left are 12 copies of a tree with a reciprocal branching ratio of 1/r, also with a branching angle of 30°.  All are drawn to depth 4, and the trunks are appropriately scaled as previously discussed.

These sets of trees produce exactly the same leaves!  We called this the Dual Tree Theorem, which was the culmination of all these observations.  Here is an illustration with both sets of trees on top of each other.

2016-12-14gtree.png

As intriguing as this discovery was, it was only the beginning of a much broader and deeper exploration into the fractal world of binary trees.  I’ll continue a discussion of our adventures in the next installment of Imagifractalous!

Mathematics and Digital Art: Update 2

It’s been about a month since my first update, so it’s time for another status report on my second semester teaching Mathematics and Digital Art.  It really has been a wonderful semester so far!

Later we’ll look at some student work (like Collette’s iterated function system),

IFSCollette

but first, I’d like to talk about course content.

The main difference from last semester in terms of topics covered was including a unit on L-systems instead of polyhedra.  You might recall the reasons for this:  first, students didn’t really see a connection between the polyhedra unit and the rest of the course, and second, the little bit of exposure to L-systems (by way of project work) was well-received.

Day007koch1

I’ve talked a lot about L-systems on my blog, but as a brief refresher, here is the prototypical L-system, the Koch curve.  The scheme is to recursively follow the sequence of turtle graphics instructions

F  +60  F  +240  F  +60  F.

There is also an excellent pdf available online, The Algorithmic Beauty of Plants.  This is where I first learned about L-systems.  It is a beautifully illustrated book, and I am fortunate enough to own a physical copy which I bought several years ago.

Talking about L-systems is also a great way to introduce Processing, since I have routines for creating L-systems written in Python.  Up to this point, we’ve just explored changing parameters in the usual algorithm, but there will a deeper investigation later.

One main focus, however, was just seeing the fractal produced by the algorithm.  When working in the Sage environment, the system automatically produced a graphic with axes labeled, enabling you to see what fractal image you created.

In Processing, though, you need to specify your screen space ahead of time.  So if your image is drawn off-screen, well, you just won’t see it.  You have to do your own scaling and translating, which is sometimes not a trivial undertaking.

I also decided to introduce both finite and infinite geometric series in conjunction with L-systems.  This had two main applications.

First, we looked at the Sierpinski triangle.  Begin with any triangle, and take out the triangle formed by joining the midpoints of the sides.  Then repeat recursively, creating the Sierpinski triangle.

Sierp3

Now assume your original triangle had an area of 1, and calculate the area of all the triangles you removed.  Since the process is repeated infinitely, this sum is just an infinite geometric series.  Interestingly, the sum of this series is 1, meaning, in some sense, you’ve taken away all the area — but the Sierpinski triangle is still left over!  This illustrates an idea not usually encountered by students before:  infinite sets of points with no area.  Makes for a nice discussion.

Second, we looked at the Koch curve (and similarly defined curves).  Using a geometric sequence, you can look at the length of any iteration of the polygonal path drawn by the recursive algorithm.  And, as expected, these paths get longer each time, and their lengths tend to infinity as the number of iterations increases.  This is another nice way to involve geometric sequences and series.

We’ll be doing more with L-systems in the next few weeks, so I’ll finish this discussion on my next update.

A highlight of the past month was a visit by artist Stacy Speyer.

004 I'llNeverKnow
I’ll Never Know, by Stacy Speyer.

Having worked with weaving and textiles for some time, Stacy has moved on to an investigation of polyhedral forms.

075-WovenGeoInstallVert

Stacy’s talk provided a wonderful insight into integrating mathematics and art in ways we did not study in class.  One of the goals of the Bridges papers presentations and the guest speakers is to do precisely this

She writes:

I’m now on a mission to share the fun of making geometric forms with others; I designed Cubes and Things, a 3D coloring book.  These easy-to-make paper constructions have patterns that can be colored which emphasize different kinds of symmetric properties of the polyhedra.  I bring this fun activity to schools and other groups in the form of Polyhedra Parties.  And whenever possible, I still work on making more geometric art and learning more about math.

Visit Stacy’s website to take a look at her book, and view many more examples of her stunning work!

Now we’ll take a look at a few more examples of student artwork.  These pieces were submitted for the assignment on iterated function systems.  Karla created a piece which reminded her of icicles or twinkling lights.

IFSKarla

Lainey thought her piece looked like a bolt lightning coming out of a wizard’s staff.

IFSLainey

And Peyton’s piece reminder her of flowers.

IFSPeyton

Finally, as I did last semester, I asked students for some mid-semester comments on how the course was going.  You can see the complete prompt on Day 19 of the course website.  Here are a few of the comments:

I like how it takes a subject that we are all required to take and creates a real, palpable output. Rather than some types of math, where everything is theoretical, it creates a clear chain of events with an even clearer consequence.

[A]fter seeing the kinds of art works there are that involve the kind of math and programming we use, it opened up a new world of artistic possibilities.

What I enjoy most about this course aside from it being small and very interactive in terms of doing labs and having all of our questions answered, is the fact that I would never thought I would be able to create images using programming or math let alone enjoying the satisfaction of the final product.

I was pleased to read these responses, as they suggest the course is fulfilling its intended purpose.  But there were also suggestions for improvement — there was a consensus that the math moved a bit too quickly.  When we start the discussion on number theory for analyzing the Koch curve next week, I’ll make sure to keep an eye on the pace.  I’ll let you know how it goes in my next update in April!

On Coding VIII: LaTeX II

Today, I’ll conclude my remarks about my passion for using LaTeX.  As I was writing the last installment of On Coding, I realized that I had more to say than would fit in just one post.

Yet another wonderful thing about LaTeX is how many mathematicians and scientists use it — and therefore write packages for it.  You can go to the Comprehensive TeX Archive Network and download packages which make Feynman diagrams for physics, molecular structures for chemistry, musical scores, and even crossword puzzles or chessboards!  There are literally thousands of packages available.  And like LaTeX, it’s all open source.  That is a feature which cannot be overstated.  Arguably the world’s best and most comprehensive computer typesetting platform is absolutely free.

The package I use most often is TikZ — it’s a really amazing graphics package written by Till Tantau.  You can do absolutely anything in TikZ, really.  One extremely important feature is that you can easily put mathematical symbols in any graphic.

tikz1

This is nice because any labels in your diagram will be in the same font as your text.  I always find it jarring when I’m reading a mathematics paper or book, and the diagrams are labelled in some other font.

There is so much more to say about TikZ.  I plan to talk about it in more detail in a future installment about computer graphics, so I’ll stop here and leave you with one more graphic made with TikZ.

latex2

Another package I use fairly often is the hyperref package.  This is especially useful when you’re creating some type of report which relies on information found on the web.  For example, when I request funding for a conference, I need to include a copy of the conference announcement.  So I create a hyperlink (in blue, though you can customize this) in the document which takes you to the announcement online when you click on it.

These hyperlinks can also be linked to other documents in the cloud, so you can have a “master” document which links to all the documents you need.  Now that I’m approaching 100 blog entries, I plan on making an index this way.  I’ll create a pdf (using LaTeX, of course) which lists posts by topic with brief descriptions as well as hyperlinks to the relevant blog posts.

On to the next LaTeX feature!  I learned about this one from a colleague (thanks, Noah!) when I was writing some notes on Taylor series for calculus.  I used it as a text when I taught calculus; the notes are about 100 pages long.

I wanted to share these notes with others, and the style of the notes was such that the exercises weren’t at the end of the sections, but interwoven with the text.  Students are supposed to do the exercises as they encounter them.

But for other calculus teachers, it was helpful to include solutions to the exercises.  The problem in creating a solutions manual was that if I ever edited the notes, I’d have to also edit the solutions manual in parallel.  I knew this was going to happen, since when I gave exams on this material, I added those problems as supplementary exercises to the text.

Enter the ifthen package in LaTeX.  I created an exercise environment, so that every time I included an exercise, I had a block which looked like this:

\begin{exercise}

{….the exercise….}

{….the solution….}

\end{exercise}

Think of this as an exercise function with two arguments:  the text of the exercise, and the text of the solution.

Then I created a boolean variable called teacheredition.  If this variable was true, the exercise function printed the solutions with each exercise.  If false, the solutions were omitted.  This control structure was made easy by some functions in the ifthen package.

And that’s all there was to it!  So every time I created an exercise, I added the solution right after it.  Of course the exercises were automatically numbered as well.  No separate solutions manual.  Everything was all in one place.  If you have ever had to deal with this type of issue before, you’ll immediately recognize how unbelievably useful the ability to do this is!

While not really features of LaTeX itself, there are now places in the cloud where you can work on LaTeX documents with others.  I’d like to talk about the one Nick and I are currently using, called ShareLaTeX.   This is an environment where you can create a project, and then share it with others so they can work on it, too.

So when Nick and I work on a paper together, we do it in ShareLaTeX.  It’s extremely convenient.  We can edit the paper on our own, but most often, we use ShareLaTeX when we’re working together.  Usually, we’re working on different parts of the paper — but when one of us has something we want the other to see, it’s easy to just scroll down (or up) in the document and look at what’s been done.

Also nice is that it’s easy to copy projects — so as we’re about to make a big change (like use different notation, or alter a fundamental definition), our protocol is to make a copy of the current project to work on, and then download the older version of the project (just in case the internet dies).

It’s wonderful to use.  And it actually really came in handy when Nick was working on his Bridges paper for last year.  His computer hard drive seriously crashed.  But since we were working on ShareLaTeX, the draft of his paper was unharmed.

I hope this is enough to convince you that it might be worthwhile to learn a little LaTeX!  I seriously don’t know what I’d do without it.  And — as it bears repeating — it’s all open source, available to anyone.  So, really, why isn’t the whole world using LaTeX?  That’s a mystery for another day….

What is…Spherical Geometry?

This week, we’ll look at another type of geometry, namely spherical geometry.  Quite simply, this is the geometry of a sphere.  Here, a sphere is a set of points equidistant from a given center.  In other words, throughout this post, you should imagine only a surface, with nothing inside it — think of the rind of an orange, without any of the slices.  I began to describe spherical geometry in my original post, What is a Geometry?, so I’ll briefly summarize the ideas in that post first.  It wouldn’t hurt to review it…

From a Euclidean standpoint, there are points on the sphere, but obviously no straight lines.  In spherical geometry, we define a Point to be a pair of antipodal points on the sphere, and a Line to be a great circle on the sphere.  This results in two nice theorems of spherical geometry:  any two distinct Lines determine (intersect in) a single Point, and any two distinct points determine a single Line.

This is a departure from Euclidean geometry, for this means that there are no parallel Lines in spherical geometry, since distinct Lines always intersect.  But there is something more going on here.

Consider the statement “Any two distinct Lines determine a single Point.”  Now perform the following simple replacement:  change the occurrence of “Line” to “Point,” and vice versa.  This gives the statement “Any two distinct Points determine a single Line,”  and is called the dual of the original statement.

Thus, we have the situation that some statement and its dual are both true.  Now if this is true of some set of statements in spherical geometry — that the dual of each statement is true — and we derive a new result from this set of statements, then the following remarkable thing happens.  Since the dual of any statement we used is true, then the dual of the new result must also be true!  Just replace each statement used to derive the new result with its dual, and you get the dual of the new result as a true statement as well.

This is the principle of duality in mathematics, and is a very important concept.  We will encounter it again when we investigate projective geometry.

Triangles and trigonometry are different on the sphere, as well.  A spherical triangle is composed of three arcs of great circles, as in the image below.

Fig31.png

If this were Earth, you could imagine starting at the North Pole, following 0 degrees of longitude to the Equator (shown in yellow), follow the Equator to 30 degrees east longitude, then follow this line of longitude back to the North Pole.

On the sphere, though, sides of a triangle are actually angles.  Sure, you could measure the length of the arcs given the radius of the sphere, but that’s not as useful.  Consider the choice of units on the Earth — kilometers or miles?  We don’t want important  geometrical results to depend on the choice of units.  So a side is specified by the angle subtended by the arc at the center of the sphere.  This makes sense since the sides are arcs of great circles, and the center of any great circle is the center of the sphere.

The angles between the sides are angles, too!  A great circle is just the intersection of a plane passing through the origin and the sphere.  So the angle between any two sides is defined to be the angle between the planes which contain them.

Really nothing from Euclidean trigonometry is valid on the sphere.  For example, if you look at the triangle above, you can see that the angles between the sides are 30, 90, and 90 degrees.  These angles add to 210!  In fact, the three angles of a triangle always add up to more than 180 degrees on a sphere.  (You may notice that the sides of this triangle are also 30, 90, and 90 degrees, but this is just a coincidence.  The sides and angles are usually different.)

If A, B, and C are the angles of a spherical triangle, it turns out that the area of the triangle is proportional to ABC – 180.  This means that the smaller a triangle is, the closer the angle sum is to 180 degrees.

sphtriangle

There is no Pythagorean Theorem on the sphere, either.  In addition, if a, b, and c are the sides opposite angles A, B, and C, respectively, then we have formulas like

\cos c=\cos a\cos b+\sin a\sin b\cos C

and

\cos C=-\cos A\cos B+\sin A\sin B\cos c.

One interesting consequence of the second of these formulas is this.  If you know the angles of a triangle, you can determine the sides.  You can’t do this in Euclidean trigonometry, since the triangles may be similar, but of different sizes.  In other words, there are no similar triangles on the sphere.  Spherical triangles are just congruent, or not. You can’t have two different triangles with the same angles.

For now, we’ve considered our sphere as being embedded in a Euclidean space.  The definition of this surface is easy:  just choose a point as the center of your sphere, and then find all points which are a given, fixed distance — the radius of the sphere — from that point.  Sounds easy enough.

But can you imagine a sphere without thinking of the three-dimensional space around it?  Or put another way, imagine you were a tiny ant, on a sphere of radius 1,000,000 km.  That’s over 150 times the radius of the Earth!  How would you know you were actually on the surface of a sphere?  If you were that small and the sphere were that large, it would seem awfully flat to you….

So how could you determine the sphere was curved?  This is a question for differential geometry, which among other things, is about the geometry of a surface without any reference to a space it’s embedded in.  This is called the surface’s intrinsic geometry.

As an example of looking at the intrinsic geometry of the sphere, consider Lines.  Now you can’t say they’re great circles any more, since this relies on thinking of a sphere as being embedded in three-dimensional space; in other words, its extrinsic geometry.  You need the concept of a geodesic — in other words, the idea of a “shortest path.”

So if you’re the ant crawling between two points on a sphere, and you wanted to take the shortest path, you would have to follow a great circle arc.  So it is possible to define Lines only using properties of the surface itself.  But the mathematics to do this is really extremely challenging.

Lots of new ideas here — but we’ve just scratched the surface of a study of spherical geometry.  You can see how very different spherical geometry is from both Euclidean and taxicab geometry.  Hopefully you’re well on your way to wrapping your head around our original question, What is a Geometry?….