## From my Third A-to-Z: Osculating Circle

With the third A-to-Z choice for the letter O, I finally set ortho-ness down. I had thought the letter might become a reference for everything described as ortho-. It has to be acknowledged that two or three examples gets you the general idea of what’s got at when something is named ortho-, though.

Must admit, I haven’t that I remember ever solved a differential equation using osculating circles instead of, you know, polynomials or sine functions (Fourier series). But references I trust say that would be a way to go.

I’m happy to say it’s another request today. This one’s from HowardAt58, author of the Saving School Math blog. He’s given me some great inspiration in the past.

## Osculating Circle.

It’s right there in the name. Osculating. You know what that is from that one Daffy Duck cartoon where he cries out “Greetings, Gate, let’s osculate” while wearing a moustache. Daffy’s imitating somebody there, but goodness knows who. Someday the mystery drives the young you to a dictionary web site. Osculate means kiss. This doesn’t seem to explain the scene. Daffy was imitating Jerry Colonna. That meant something in 1943. You can find him on old-time radio recordings. I think he’s funny, in that 40s style.

Make the substitution. A kissing circle. Suppose it’s not some playground antic one level up from the Kissing Bandit that plagues recess yet one or two levels down what we imagine we’d do in high school. It suggests a circle that comes really close to something, that touches it a moment, and then goes off its own way.

But then touching. We know another word for that. It’s the root behind “tangent”. Tangent is a trigonometry term. But it appears in calculus too. The tangent line is a line that touches a curve at one specific point and is going in the same direction as the original curve is at that point. We like this because … well, we do. The tangent line is a good approximation of the original curve, at least at the tangent point and for some region local to that. The tangent touches the original curve, and maybe it does something else later on. What could kissing be?

The osculating circle is about approximating an interesting thing with a well-behaved thing. So are similar things with names like “osculating curve” or “osculating sphere”. We need that a lot. Interesting things are complicated. Well-behaved things are understood. We move from what we understand to what we would like to know, often, by an approximation. This is why we have tangent lines. This is why we build polynomials that approximate an interesting function. They share the original function’s value, and its derivative’s value. A polynomial approximation can share many derivatives. If the function is nice enough, and the polynomial big enough, it can be impossible to tell the difference between the polynomial and the original function.

The osculating circle, or sphere, isn’t so concerned with matching derivatives. I know, I’m as shocked as you are. Well, it matches the first and the second derivatives of the original curve. Anything past that, though, it matches only by luck. The osculating circle is instead about matching the curvature of the original curve. The curvature is what you think it would be: it’s how much a function curves. If you imagine looking closely at the original curve and an osculating circle they appear to be two arcs that come together. They must touch at one point. They might touch at others, but that’s incidental.

Osculating circles, and osculating spheres, sneak out of mathematics and into practical work. This is because we often want to work with things that are almost circles. The surface of the Earth, for example, is not a sphere. But it’s only a tiny bit off. It’s off in ways that you only notice if you are doing high-precision mapping. Or taking close measurements of things in the sky. Sometimes we do this. So we map the Earth locally as if it were a perfect sphere, with curvature exactly what its curvature is at our observation post.

Or we might be observing something moving in orbit. If the universe had only two things in it, and they were the correct two things, all orbits would be simple: they would be ellipses. They would have to be “point masses”, things that have mass without any volume. They never are. They’re always shapes. Spheres would be fine, but they’re never perfect spheres even. The slight difference between a perfect sphere and whatever the things really are affects the orbit. Or the other things in the universe tug on the orbiting things. Or the thing orbiting makes a course correction. All these things make little changes in the orbiting thing’s orbit. The actual orbit of the thing is a complicated curve. The orbit we could calculate is an osculating — well, an osculating ellipse, rather than an osculating circle. Similar idea, though. Call it an osculating orbit if you’d rather.

That osculating circles have practical uses doesn’t mean they aren’t respectable mathematics. I’ll concede they’re not used as much as polynomials or sine curves are. I suppose that’s because polynomials and sine curves have nicer derivatives than circles do. But osculating circles do turn up as ways to try solving nonlinear differential equations. We need the help. Linear differential equations anyone can solve. Nonlinear differential equations are pretty much impossible. They also turn up in signal processing, as ways to find the frequencies of a signal from a sampling of data. This, too, we would like to know.

We get the name “osculating circle” from Gottfried Wilhelm Leibniz. This might not surprise. Finding easy-to-understand shapes that approximate interesting shapes is why we have calculus. Isaac Newton described a way of making them in the Principia Mathematica. This also might not surprise. Of course they would on this subject come so close together without kissing.

## Some Things I’ve Been Reading

I don’t just read comic strips around here. It seems like it, I grant. But there’s other things that catch my interest and that you might also like.

The first: many people have talked about what great thinkers did during their quarantine-induced disruptions to their lives. Isaac Newton is held up as a great example. While avoiding the Plague, after all, he had that great year of discovering calculus, gravity, optics, and an automatic transmission that doesn’t fail after eight years of normal driving. It’s a great story. The trouble is that real thing is always more ambiguous, more hesitant, and less well-defined than the story. The Renaissance Mathematicus discusses, in detail, something closer to the reality of Newton’s accomplishments during that plague year. This is not to say that his work was not astounding. But it was not as much, or as intense, or as superhuman as inspirational tweets would like.

If you do decide the quarantine is a great chance to revolutionize academia, good luck. You need some reference material, though. Springer publishing has put out several hundred of its textbooks as free PDFs or eBooks. A list of 408 of them (the poster claims) is here on Reddit. This is not only a list of mathematics and mathematics-related topics, and I not undrestand the poster’s organization scheme. But there are a lot of books here, including at least two Introduction to Partial Differential Equations texts. There’s something of note there. This could finally be the thing that gets me to learn the mathematical-statistics programming language R. (It will not get me to learn the mathematical-statistics programming language R.)

And, finally, the disruption to everything has messed up academic departments’ routines. Some of those routines are seminars, in which people share the work they’re doing. Fortunately, many of these seminars are moving to online presentations. And then you can join in, and at least listen, without needing even to worry about being the stranger hanging around the mathematics department. Mathseminars.org has a list of upcoming seminars, with links to what the sessions are about and how to join them. The majority are in English, but there are listed seminars in Spanish, Russian, and French.

I grant the seminar titles are filled with enough jargon to intimidate someone not already well-versed in the field. To pick an example set for the 22nd of April, my time, I’ve never even heard of Dieudonné Theory, prismatic or otherwise. Don’t let that throw you. I would expect speaker Arthur-César La Bras to bring people up to a basic understanding swiftly. It’s the seminars whose titles contain words you’re sure you know that are truly baffling, which is why I fear Alexandra Kjuchukova’s The meridional rank conjecture: an attack with crayons. If they’re talking about crayons it can’t be good.

## The End 2016 Mathematics A To Z: Osculating Circle

I’m happy to say it’s another request today. This one’s from HowardAt58, author of the Saving School Math blog. He’s given me some great inspiration in the past.

## Osculating Circle.

It’s right there in the name. Osculating. You know what that is from that one Daffy Duck cartoon where he cries out “Greetings, Gate, let’s osculate” while wearing a moustache. Daffy’s imitating somebody there, but goodness knows who. Someday the mystery drives the young you to a dictionary web site. Osculate means kiss. This doesn’t seem to explain the scene. Daffy was imitating Jerry Colonna. That meant something in 1943. You can find him on old-time radio recordings. I think he’s funny, in that 40s style.

Make the substitution. A kissing circle. Suppose it’s not some playground antic one level up from the Kissing Bandit that plagues recess yet one or two levels down what we imagine we’d do in high school. It suggests a circle that comes really close to something, that touches it a moment, and then goes off its own way.

But then touching. We know another word for that. It’s the root behind “tangent”. Tangent is a trigonometry term. But it appears in calculus too. The tangent line is a line that touches a curve at one specific point and is going in the same direction as the original curve is at that point. We like this because … well, we do. The tangent line is a good approximation of the original curve, at least at the tangent point and for some region local to that. The tangent touches the original curve, and maybe it does something else later on. What could kissing be?

The osculating circle is about approximating an interesting thing with a well-behaved thing. So are similar things with names like “osculating curve” or “osculating sphere”. We need that a lot. Interesting things are complicated. Well-behaved things are understood. We move from what we understand to what we would like to know, often, by an approximation. This is why we have tangent lines. This is why we build polynomials that approximate an interesting function. They share the original function’s value, and its derivative’s value. A polynomial approximation can share many derivatives. If the function is nice enough, and the polynomial big enough, it can be impossible to tell the difference between the polynomial and the original function.

The osculating circle, or sphere, isn’t so concerned with matching derivatives. I know, I’m as shocked as you are. Well, it matches the first and the second derivatives of the original curve. Anything past that, though, it matches only by luck. The osculating circle is instead about matching the curvature of the original curve. The curvature is what you think it would be: it’s how much a function curves. If you imagine looking closely at the original curve and an osculating circle they appear to be two arcs that come together. They must touch at one point. They might touch at others, but that’s incidental.

Osculating circles, and osculating spheres, sneak out of mathematics and into practical work. This is because we often want to work with things that are almost circles. The surface of the Earth, for example, is not a sphere. But it’s only a tiny bit off. It’s off in ways that you only notice if you are doing high-precision mapping. Or taking close measurements of things in the sky. Sometimes we do this. So we map the Earth locally as if it were a perfect sphere, with curvature exactly what its curvature is at our observation post.

Or we might be observing something moving in orbit. If the universe had only two things in it, and they were the correct two things, all orbits would be simple: they would be ellipses. They would have to be “point masses”, things that have mass without any volume. They never are. They’re always shapes. Spheres would be fine, but they’re never perfect spheres even. The slight difference between a perfect sphere and whatever the things really are affects the orbit. Or the other things in the universe tug on the orbiting things. Or the thing orbiting makes a course correction. All these things make little changes in the orbiting thing’s orbit. The actual orbit of the thing is a complicated curve. The orbit we could calculate is an osculating — well, an osculating ellipse, rather than an osculating circle. Similar idea, though. Call it an osculating orbit if you’d rather.

That osculating circles have practical uses doesn’t mean they aren’t respectable mathematics. I’ll concede they’re not used as much as polynomials or sine curves are. I suppose that’s because polynomials and sine curves have nicer derivatives than circles do. But osculating circles do turn up as ways to try solving nonlinear differential equations. We need the help. Linear differential equations anyone can solve. Nonlinear differential equations are pretty much impossible. They also turn up in signal processing, as ways to find the frequencies of a signal from a sampling of data. This, too, we would like to know.

We get the name “osculating circle” from Gottfried Wilhelm Leibniz. This might not surprise. Finding easy-to-understand shapes that approximate interesting shapes is why we have calculus. Isaac Newton described a way of making them in the Principia Mathematica. This also might not surprise. Of course they would on this subject come so close together without kissing.

## Reading the Comics, July 19, 2015: Rerun Comics Edition

I’m stepping my blog back away from the daily posting schedule. It’s fun, but it’s also exhausting. Sometimes, Comic Strip Master Command helps out. It slowed the rate of mathematically-themed comics just enough.

By this post’s title I don’t mean that my post is a rerun. But several of the comics mentioned happen to be. One of the good — maybe best — things about the appearance of comics on Gocomics.com and ComicsKingdom is that comic strips that have ended, such as Randolph Itch, 2 am or (alas) Cul de Sac can still appear without taking up space. And long-running comic strips such as Luann can have earlier strips be seen to a new audience, again without doing any harm to the newest generation of cartoonists. So, there’s that.

Greg Evans’s Luann Againn (July 13, originally run July 13, 1987) makes a joke of Tiffany not understanding the odds of a contest. That’s amusing enough. Estimating the probability of something happening does require estimating how many things are possible, though, and how likely they are relative to one another. Supposing that every entry in a sweepstakes is equally likely to win seems fair enough. Estimating the number of sweepstakes entries is another problem.

Tom Toles’s Randolph Itch, 2 am (July 13, rerun from July 29, 2002) tells a silly little pirates-and-algebra joke. I like this one for the silliness and the artwork. The only sad thing is there wasn’t a natural way to work equations for a circle into it, so there’d be a use for “r”.

## Reading the Comics, December 27, 2014: Last of the Year Edition?

I’m curious whether this is going to be the final bunch of mathematics-themed comics for the year 2014. Given the feast-or-famine nature of the strips it’s plausible we might not have anything good through to mid-January, but, who knows? Of the comics in this set I think the first Peanuts the most interesting to me, since it’s funny and gets at something big and important, although the Ollie and Quentin is a better laugh.

Mark Leiknes’s Cow and Boy (December 23, rerun) talks about chaos theory, the notion that incredibly small differences in a state can produce enormous differences in a system’s behavior. Chaos theory became a pop-cultural thing in the 1980s, when Edward Lorentz’s work (of twenty years earlier) broke out into public consciousness. In chaos theory the chaos isn’t that the system is unpredictable — if you have perfect knowledge of the system, and the rules by which it interacts, you could make perfect predictions of its future. What matters is that, in non-chaotic systems, a small error will grow only slightly: if you predict the path of a thrown ball, and you have the ball’s mass slightly wrong, you’ll make a proportionately small error on what the path is like. If you predict the orbit of a satellite around a planet, and have the satellite’s starting speed a little wrong, your prediction is proportionately wrong. But in a chaotic system there are at least some starting points where tiny errors in your understanding of the system produce huge differences between your prediction and the actual outcome. Weather looks like it’s such a system, and that’s why it’s plausible that all of us change the weather just by existing, although of course we don’t know whether we’ve made it better or worse, or for whom.

Charles Schulz’s Peanuts (December 23, rerun from December 26, 1967) features Sally trying to divide 25 by 50 and Charlie Brown insisting she can’t do it. Sally’s practical response: “You can if you push it!” I am a bit curious why Sally, who’s normally around six years old, is doing division in school (and over Christmas break), but then the kids are always being assigned Thomas Hardy’s Tess of the d’Urbervilles for a book report and that is hilariously wrong for kids their age to read, so, let’s give that a pass.

## Some Stuff About Edmond Halley

When I saw the Maths History tweet about Edmond Halley’s birthday I wondered if the November 8th date given was the relevant one since, after all, in 1656 England was still on the Julian calendar. The MacTutor biography of him makes clear that the 8th of November is his Gregorian-date birthday, and he was born on the 29th of October by the calendar his parents were using, although it’s apparently not clear he was actually born in 1656. Halley claimed it was 1656, at least, and he probably heard from people who knew.

Halley is famous for working out the orbit of the comet that’s gotten his name attached, and correctly so: working out the orbits of comets was one of the first great accomplishments of Newtonian mechanics, and Halley’s work took into account how Jupiter’s gravitation distorts the orbit of a comet. It’s great work. And he’s also famous within mathematical and physics circles because it’s fair to wonder whether, without his nagging and his financial support, Isaac Newton would have published his Principia Mathematica. Astronomers note him as the first Western European astronomer to set up shop in the southern hemisphere and produce a map of that part of the sky, as well.

That hardly exhausts what’s interesting about him: for example, he joined in the late-17th-century fad for diving bell companies (for a while, you couldn’t lose money excavating wrecked ships, until finally everyone did) and even explored the bed of the English Channel in a diving bell of his own design. This is to me the most terrifying thing he did, and that’s even with my awareness he led two scientific sailing expeditions, one of which was cut short after among other things irreconcilable differences with the ship’s other commissioned officer, Lieutenant Edward Harrison (who blamed Halley for the oblivion which Harrison’s book on longitude received), and the second of which included a pause in Recife when Halley was put under guard by a man claiming to be the English consul, and who was actually an agent of the Royal African Company considering whether to seize Halley’s ship[1] as a prize.

After his second expedition Halley published charts showing the magnetic declination, how far a magnetic compass’s “north” is from true north, and introduced one of those great conceptual breakthroughs that charts can give us: he connected the lines showing the points where the declination was equal. These isolines are a magnificent way to diagram three-dimensional information on a two-dimensional chart; we see them in topographic maps, as the contour curves showing where a hill rises or a valley sinks. We see them in weather maps, the lines where the temperature is 70 or 80 Fahrenheit (or 20 or 25 Celsius, if you rather) or where the wind speed is some sufficiently alarming figure. We see them (in three-dimensional form) in medical imaging, where a region of constant density gets the same color and this is used to understand a complicated shape within. Not all these uses derive directly from Halley; as with all really good, widely usable concepts many people discovered the concept, but Halley was among the first to put them to obvious, prominent use.

And something that might serve as comfort to anyone who’s taking a birthday hard: at age 65, Halley began a study of the moon’s saros, the cycle patterns of different relative positions the Sun and Moon have in the sky which describe when eclipses happen. One cycle takes a bit over eighteen years to complete. Halley lived long enough to complete this work.

[1] The Paramore, which — I note because this is just the kind of world it was back then — was constructed in 1694 at the Royal Dockyard at Deptford on the River Thames for a scientific circumnavigation of the globe, and first sailed in April 1698 under Tsar Peter the Great, then busy travelling western Europe under ineffective cover to learn things which might modernize Russia. Halley had hoped to sail in 1696, but he was waylaid by his appointment to the Mint at Chester, courtesy of Newton.

## 16,000 and a Square

I reached my 16,000th page view, sometime on Thursday. That’s a tiny bit slower than I projected based on May’s readership statistics, but May was a busy month and I’ve had a little less time to write stuff this month, so I’m not feeling bad about that.

Meanwhile, while looking for something else, I ran across a bit about mathematical notation in Florian Cajori’s A History of Mathematical Notation which has left me with a grin since. The book is very good about telling the stories of just what the title suggests. It’s a book well worth dipping into because everything you see written down is the result of a long process of experimentation and fiddling about to find the right balance of “expressing an idea clearly” and “expressing an idea concisely” and “expressing an idea so it’s not too hard to work with”.

The idea here is the square of a variable, which these days we’d normally write as $a^2$. According to Cajori (section 304), René Descartes “preferred the notation $aa$ to $a^2$.” Cajori notes that Carl Gauss had this same preference and defended it on the grounds that doubling the symbol didn’t take any more (or less) space than the superscript 2 did. Cajori lists other great mathematicians who preferred doubling the letter for squaring, including Christiaan Huygens, Edmond Halley, Leonhard Euler, and Isaac Newton. Among mathematicians who preferred $a^2$ were Blaise Pascal, David Gregory (who was big in infinite series), and Wilhelm Leibniz.

Well of course Newton and Leibniz would be on opposite sides of the $aa$ versus $a^2$ debate. How could the universe be sensible otherwise?

## Reading the Comics, July 14, 2012

I hope everyone’s been well. I was on honeymoon the last several weeks and I’ve finally got back to my home continent and new home so I’ll try to catch up on the mathematics-themed comics first and then plunge into new mathematics content. I’m splitting that up into at least two pieces since the comics assembled into a pretty big pile while I was out. And first, I want to offer the link to the July 2 Willy and Ethel, by Joe Martin, since even though I offered it last time I didn’t have a reasonably permanent URL for it.

## Descartes and the Terror of the Negative

When René Descartes first described the system we’ve turned into Cartesian coordinates he didn’t put it forth in quite the way we build them these days. This shouldn’t be too surprising; he lived about four centuries ago, and we have experience with the idea of matching every point on the plane to some ordered pair of numbers that he couldn’t have. The idea has been expanded on, and improved, and logical rigor I only pretend to understand laid underneath the concept. But the core remains: we put somewhere on our surface an origin point — usually this gets labelled O, mnemonic for “origin” and also suggesting the zeroes which fill its coordinates — and we pick some direction to be the x-coordinate and some direction to be the y-coordinate, and the ordered pair for a point are how far in the x-direction and how far in the y-direction one must go from the origin to get there.

The most obvious difference between Cartesian coordinates as Descartes set them up and Cartesian coordinates as we use them is that Descartes would fill a plane with four chips, one quadrant each in the plane. The first quadrant is the points to the right of and above the origin. The second quadrant is to the left of and still above the origin. The third quadrant is to the left of and below the origin, and the fourth is to the right of the origin but below it. This division of the plane into quadrants, and even their identification as quadrants I, II, III, and IV respectively, still exists, one of those minor points on which prealgebra and algebra students briefly trip on their way to tripping over the trigonometric identities.

Descartes had, from his perspective, excellent reason to divide the plane up this way. It’s a reason difficult to imagine today. By separating the plane like this he avoided dealing with something mathematicians of the day were still uncomfortable with. It’s easy enough to describe a point in the first quadrant as being so far to the right and so far above the origin. But a point in the second quadrant is … not any distance to the right. It’s to the left. How far to the right is something that’s to the left?

## The Person Who Named e

One of the personality traits which my Dearly Beloved most often tolerates in me is my tendency toward hyperbole, a rhetorical device employed successfully on the Internet by almost four people and recognized as such as recently as 1998. I’m not satisfied saying there was an enormous, slow-moving line for a roller coaster we rode last August; I have to say that fourteen months later we’re still on that line.

I mention this because I need to discuss one of those rare people who can be discussed accurately only in hyperbole: Leonhard Euler, 1703 – 1783. He wrote about essentially every field of mathematics it was possible to write about: calculus and geometry and physics and algebra and number theory and graph theory and logic, on music and the motions of the moon, on optics and the finding of longitude, on fluid dynamics and the frequency of prime numbers. After his death the Saint Petersburg Academy needed nearly fifty years to finish publishing his remaining work. If you ever need to fake being a mathematician, let someone else introduce the topic and then speak of how Euler’s Theorem is fundamental to it. There are several thousand Euler’s Theorems, although some of them share billing with another worthy, and most of them are fundamental to at least sixteen fields of mathematics each. I exaggerate; I must, but I note that a search for “Euler” on Wolfram Mathworld turns up 681 matches, as of this moment, out of 13,081 entries. It’s difficult to imagine other names taking up more than five percent of known mathematics. Even Karl Friedrich Gauss only matches 272 entries, and Isaac Newton a paltry 138.