## 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.

## My All 2020 Mathematics A to Z: Gottfried Wilhelm Leibniz

Today’s topic suggestion was suggested by bunnydoe. I know of a project bunnydoe runs, but not whether it should be publicized. It is another biographical piece. Biographies and complex numbers, that seems to be the theme of this year.

# Gottfried Wilhelm Leibniz.

The exact suggestion I got for L was “Leibniz, the inventor of Calculus”. I can’t in good conscience offer that. This isn’t to deny Leibniz’s critical role in calculus. We rely on many of the ideas he’d had for it. We especially use his notation. But there are few great big ideas that can be truly credited to an inventor, or even a team of inventors. Put aside the sorry and embarrassing priority dispute with Isaac Newton. Many mathematicians in the 16th and 17th century were working on how to improve the Archimedean “method of exhaustion”. This would find the areas inside select curves, integral calculus. Johannes Kepler worked out the areas of ellipse slices, albeit with considerable luck. Gilles Roberval tried working out the area inside a curve as the area of infinitely many narrow rectangular strips. We still learn integration from this. Pierre de Fermat recognized how tangents to a curve could find maximums and minimums of functions. This is a critical piece of differential calculus. Isaac Barrow, Evangelista Torricelli (of barometer fame), Pietro Mengoli, and Stephano Angeli all pushed mathematics towards calculus. James Gregory proved, in geometric form, the relationship between differentiation and integration. That relationship is the Fundamental Theorem of Calculus.

This is not to denigrate Leibniz. We don’t dismiss the Wright Brothers though we know that without them, Alberto Santos-Dumont or Glenn Curtiss or Samuel Langley would have built a workable airplane anyway. We have Leibniz’s note, dated the 29th of October, 1675 (says Florian Cajori), writing out $\int l$ to mean the sum of all l’s. By mid-November he was integrating functions, and writing out his work as $\int f(x) dx$. Any mathematics or physics or chemistry or engineering major today would recognize that. A year later he was writing things like $d(x^n) = n x^{n - 1} dx$, which we’d also understand if not quite care to put that way.

Though we use his notation and his basic tools we don’t exactly use Leibniz’s particular ideas of what calculus means. It’s been over three centuries since he published. It would be remarkable if he had gotten the concepts exactly and in the best of all possible forms. Much of Leibniz’s calculus builds on the idea of a differential. This is a quantity that’s smaller than any positive number but also larger than zero. How does that make sense? George Berkeley argued it made not a lick of sense. Mathematicians frowned, but conceded Berkeley was right. By the mid-19th century they had a rationale for differentials that avoided this weird sort of number.

It’s hard to avoid the differential’s lure. The intuitive appeal of “imagine moving this thing a tiny bit” is always there. In science or engineering applications it’s almost mandatory. Few things we encounter in the real world have the kinds of discontinuity that create logic problems for differentials. Even in pure mathematics, we will look at a differential equation like $\frac{dy}{dx} = x$ and rewrite it as $dy = x dx$. Leibniz’s notation gives us the idea that taking derivatives is some kind of fraction. It isn’t, but in many problems we act as though it were. It works out often enough we forget that it might not.

Better, though. From the 1960s Abraham Robinson and others worked out a different idea of what real numbers are. In that, differentials have a rigorous logical definition. We call the mathematics which uses this “non-standard analysis”. The name tells something of its use. This is not to call it wrong. It’s merely not what we learn first, or necessarily at all. And it is Leibniz’s differentials. 304 years after his death there is still a lot of mathematics he could plausibly recognize.

There is still a lot of still-vital mathematics that he touched directly. Leibniz appears to be the first person to use the term “function”, for example, to describe that thing we’re plotting with a curve. He worked on systems of linear equations, and methods to find solutions if they exist. This technique is now called Gaussian elimination. We see the bundling of the equations’ coefficients he did as building a matrix and finding its determinant. We know that technique, today, as Cramer’s Rule, after Gabriel Cramer. The Japanese mathematician Seki Takakazu had discovered determinants before Leibniz, though.

Leibniz tried to study a thing he called “analysis situs”, which two centuries on would be a name for topology. My reading tells me you can get a good fight going among mathematics historians by asking whether he was a pioneer in topology. So I’ll decline to take a side in that.

In the 1680s he tried to create an algebra of thought, to turn reasoning into something like arithmetic. His goal was good: we see these ideas today as Boolean algebra, and concepts like conjunction and disjunction and negation and the empty set. Anyone studying logic knows these today. He’d also worked in something we can see as symbolic logic. Unfortunately for his reputation, the papers he wrote about that went unpublished until late in the 19th century. By then other mathematicians, like Gottlob Frege and Charles Sanders Peirce, had independently published the same ideas.

We give Leibniz’ name to a particular series that tells us the value of π:

$1 - \frac13 + \frac15 - \frac17 + \frac19 - \frac{1}{11} + \cdots = \frac{\pi}{4}$

(The Indian mathematician Madhava of Sangamagrama knew the formula this comes from by the 14th century. I don’t know whether Western Europe had gotten the news by the 17th century. I suspect it hadn’t.)

The drawback to using this to figure out digits of π is that it takes forever to use. Taking ten decimal digits of π demands evaluating about five billion terms. That’s not hyperbole; it just takes like forever to get its work done.

Which is something of a theme in Leibniz’s biography. He had a great many projects. Some of them even reached a conclusion. Many did not, and instead sprawled out with great ambition and sometimes insight before getting lost. Consider a practical one: he believed that the use of wind-driven propellers and water pumps could drain flooded mines. (Mines are always flooding.) In principle, he was right. But they all failed. Leibniz blamed deliberate obstruction by administrators and technicians. He even blamed workers afraid that new technologies would replace their jobs. Yet even in this failure he observed and had bracing new thoughts. The geology he learned in the mines project made him hypothesize that the Earth had been molten. I do not know the history of geology well enough to say whether this was significant to that field. It may have been another frustrating moment of insight (lucky or otherwise) ahead of its time but not connected to the mainstream of thought.

Another project, tantalizing yet incomplete: the “stepped reckoner”, a mechanical arithmetic machine. The design was to do addition and subtraction, multiplication and division. It’s a breathtaking idea. It earned him election into the (British) Royal Society in 1673. But it never was quite complete, never getting carries to work fully automatically. He never did finish it, and lost friends with the Royal Society when he moved on to other projects. He had a note describing a machine that could do some algebraic operations. In the 1690s he had some designs for a machine that might, in theory, integrate differential equations. It’s a fantastic idea. At some point he also devised a cipher machine. I do not know if this is one that was ever used in its time.

His greatest and longest-lasting unfinished project was for his employer, the House of Brunswick. Three successive Brunswick rulers were content to let Leibniz work on his many side projects. The one that Ernest Augustus wanted was a history of the Guelf family, in the House of Brunswick. One that went back to the time of Charlemagne or earlier if possible. The goal was to burnish the reputation of the house, which had just become a hereditary Elector of the Holy Roman Empire. (That is, they had just gotten to a new level of fun political intriguing. But they were at the bottom of that level.) Starting from 1687 Leibniz did good diligent work. He travelled throughout central Europe to find archival materials. He studied their context and meaning and relevance. He organized it. What he did not do, by his death in 1716, was write the thing.

It is always difficult to understand another person. Moreso someone you know only through biography. And especially someone who lived in very different times. But I do see a particular an modern personality type here. We all know someone who will work so very hard getting prepared to do a project Right that it never gets done. You might be reading the words of one right now.

Leibniz was a compulsive Society-organizer. He promoted ones in Brandenberg and Berlin and Dresden and Vienna and Saint Petersburg. None succeeded. It’s not obvious why. Leibniz was well-connected enough; he’s known to have over six hundred correspondents. Even for a time of great letter-writing, that’s a lot.

But it does seem like something about him offended others. Failing to complete big projects, like the stepped reckoner or the History of the Guelf family, seems like some of that. Anyone who knows of calculus knows of the dispute about the Newton-versus-Leibniz priority dispute. Grant that Leibniz seems not to have much fueled the quarrel. (And that modern historians agree Leibniz did not steal calculus from Newton.) Just being at the center of Drama causes people to rate you poorly.

There seems like there’s more, though. He was liked, for example, by the Electress Sophia of Hanover and her daughter Sophia Charlotte. These were the mother and the sister of Britain’s King George I. When George I ascended to the British throne he forbade Leibniz coming to London until at least one volume of the history was written. (The restriction seems fair, considering Leibniz was 27 years into the project by then.)

There are pieces in his biography that suggest a person a bit too clever for his own good. His first salaried position, for example, was as secretary to a Nuremberg alchemical society. He did not know alchemy. He passed himself off as deeply learned, though. I don’t blame him. Nobody would ever pass a job interview if they didn’t pretend to have expertise. Here it seems to have worked.

But consider, for example, his peace mission to Paris. Leibniz was born in the last years of the Thirty Years War. In that, the Great Powers of Europe battled each other in the German states. They destroyed Germany with a thoroughness not matched until World War II. Leibniz reasonably feared France’s King Louis XIV had designs on what was left of Germany. So his plan was to sell the French government on a plan of attacking Egypt and, from there, the Dutch East Indies. This falls short of an early-Enlightenment idea of rational world peace and a congress of nations. But anyone who plays grand strategy games recognizes the “let’s you and him fight” scheming. (The plan became irrelevant when France went to war with the Netherlands. The war did rope Brandenberg-Prussia, Cologne, Münster, and the Holy Roman Empire into the mess.)

And I have not discussed Leibniz’s work in philosophy, outside his logic. He’s respected for the theory of monads, part of the long history of trying to explain how things can have qualities. Like many he tried to find a deductive-logic argument about whether God must exist. And he proposed the notion that the world that exists is the most nearly perfect that can possibly be. Everyone has been dragging him for that ever since he said it, and they don’t look ready to stop. It’s an unfair rap, even if it makes for funny spoofs of his writing.

The optimal world may need to be badly defective in some ways. And this recognition inspires a question in me. Obviously Leibniz could come to this realization from thinking carefully about the world. But anyone working on optimization problems knows the more constraints you must satisfy, the less optimal your best-fit can be. Some things you might like may end up being lousy, because the overall maximum is more important. I have not seen anything to suggest Leibniz studied the mathematics of optimization theory. Is it possible he was working in things we now recognize as such, though? That he has notes in the things we would call Lagrange multipliers or such? I don’t know, and would like to know if anyone does.

Leibniz’s funeral was unattended by any dignitary or courtier besides his personal secretary. The Royal Academy and the Berlin Academy of Sciences did not honor their member’s death. His grave was unmarked for a half-century. And yet historians of mathematics, philosophy, physics, engineering, psychology, social science, philology, and more keep finding his work, and finding it more advanced than one would expect. Leibniz’s legacy seems to be one always rising and emerging from shade, but never being quite where it should.

And that’s enough for one day. All of the 2020 A-to-Z essays should be at this link. Both 2020 and all past A-to-Z essays should be at this link. And, as I am hosting the Playful Math Education Blog Carnival at the end of September, I am looking for any blogs, videos, books, anything educational or recreational or just interesting to read about. Thank you for your reading and your help.

## What Is The Logarithm of a Negative Number?

Learning of imaginary numbers, things created to be the square roots of negative numbers, inspired me. It probably inspires anyone who’s the sort of person who’d become a mathematician. The trick was great. I wondered could I do it? Could I find some other useful expansion of the number system?

The square root of a complex-valued number sounded like the obvious way to go, until a little later that week when I learned that’s just some other complex-valued numbers. The next thing I hit on: how about the logarithm of a negative number? Couldn’t that be a useful expansion of numbers?

No. It turns out you can make a sensible logarithm of negative, and complex-valued, numbers using complex-valued numbers. Same with trigonometric and inverse trig functions, tangents and arccosines and all that. There isn’t anything we can do with the normal mathematical operations that needs something bigger than the complex-valued numbers to play with. It’s possible to expand on the complex-valued numbers. We can make quaternions and some more elaborate constructs there. They don’t solve any particular shortcoming in complex-valued numbers, but they’ve got their uses. I never got anywhere near reinventing them. I don’t regret the time spent on that. There’s something useful in trying to invent something even if it fails.

One problem with mathematics — with all intellectual fields, really — is that it’s easy, when teaching, to give the impression that this stuff is the Word of God, built into the nature of the universe and inarguable. It’s so not. The stuff we find interesting and how we describe those things are the results of human thought, attempts to say what is interesting about a thing and what is useful. And what best approximates our ideas of what we would like to know. So I was happy to see this come across my Twitter feed:

The links to a 12-page paper by Deepak Bal, Leibniz, Bernoulli, and the Logarithms of Negative Numbers. It’s a review of how the idea of a logarithm of a negative number got developed over the course of the 18th century. And what great minds, like Gottfried Leibniz and John (I) Bernoulli argued about as they find problems with the implications of what they were doing. (There were a lot of Bernoullis doing great mathematics, and even multiple John Bernoullis. The (I) is among the ways we keep them sorted out.) It’s worth a read, I think, even if you’re not all that versed in how to calculate logarithms. (but if you’d like to be better-versed, here’s the tail end of some thoughts about that.) The process of how a good idea like this comes to be is worth knowing.

Also: it turns out there’s not “the” logarithm of a complex-valued number. There’s infinitely many logarithms. But they’re a family, all strikingly similar, so we can pick one that’s convenient and just use that. Ask if you’re really interested.

## 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.

## Error

This is one of my A to Z words that everyone knows. An error is some mistake, evidence of our human failings, to be minimized at all costs. That’s … well, it’s an attitude that doesn’t let you use error as a tool.

An error is the difference between what we would like to know and what we do know. Usually, what we would like to know is something hard to work out. Sometimes it requires complicated work. Sometimes it requires an infinite amount of work to get exactly right. Who has the time for that?

This is how we use errors. We look for methods that approximate the thing we want, and that estimate how much of an error that method makes. Usually, the method involves doing some basic step some large number of times. And usually, if we did the step more times, the estimate of the error we make will be smaller. My essay “Calculating Pi Less Terribly” shows an example of this. If we add together more terms from that Leibniz formula we get a running total that’s closer to the actual value of π.

## 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?

## Reblog: Kant & Leibniz on Space and Implications in Geometry

Mathematicians and philosophers are fairly content to share credit for Rene Descartes, possibly because he was able to provide catchy, easy-to-popularize cornerstones for both fields.

Immanuel Kant, these days at least, is almost exclusively known as a philosopher, and that he was also a mathematician and astronomer is buried in the footnotes. If you stick to math and science popularizations you’ll probably pick up (as I did) that Kant was one of the co-founders of the nebular hypothesis, the basic idea behind our present understanding of how solar systems form, and maybe, if the book has room, that Kant had the insight that knowing gravitation falls off by an inverse-square rule implies that we live in a three-dimensional space.

Frank DeVita here writes some about Kant (and Wilhelm Leibniz)’s model of how we understand space and geometry. It’s not technical in the mathematics sense, although I do appreciate the background in Kant’s philosophy which my Dearly Beloved has given me. In the event I’d like to offer it as a way for mathematically-minded people to understand more of an important thinker they may not have realized was in their field.

Kant’s account of space in the Prolegomena serves as a cornerstone for his thought and comes about in a discussion of the transcendental principles of mathematics that precedes remarks on the possibility of natural science and metaphysics. Kant begins his inquiry concerning the possibility of ‘pure’ mathematics with an appeal to the nature of mathematical knowledge, asserting that it rests upon no empirical basis, and thus is a purely synthetic product of pure reason (§6). He also argues that mathematical knowledge (pure mathematics) has the unique feature of first exhibiting its concepts in a priori intuition which in turn makes judgments in mathematics ‘intuitive’ (§7.281). For Kant, intuition is prior to our sensibility and the activity of reason since the former does not grasp ‘things in themselves,’ but rather only the things that can be perceived by the senses. Thus, what we can perceive is based…

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## 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.

## Some Names Which e Doesn’t Have

I’ve outlined now some of the numbers which grew important enough to earn their own names. Most of them are counting numbers; the stragglers are a handful of irrational numbers which proved themselves useful, such as π (pi), or attractive, such as φ (phi), or physically important, such as the fine structure constant. Unnamed except in the list of categories is the number whose explanation I hope to be the first movement of this blog: e.

It’s an important number physically, and a convenient and practical number mathematically. For all that, it defies a simple explanation like π enjoys. The simplest description of which I’m aware is that it is the base of the natural logarithm, which perfectly clarifies things to people who know what logarithms are, know which one is the natural logarithm, and know what the significance of the base is. This I will explain, but not today. For now it’s enough to think of the base as a size of the measurement tool, and to know that switching between one base and another is akin to switching between measuring in centimeters and measuring in inches. What the logarithm is will also wait for explanation; for now, let me hold off on that by saying it’s, in a way, a measure of how many digits it takes to write down a number, so that “81” has a logarithm twice that of “9”, and “49” twice that of “7”, and please don’t take this description so literally as to think the logarithm of “81” is equal to that of “49”.

I agree it’s not clear why we should be interested in the natural logarithm when there are an infinity of possible logarithms, and we can convert a logarithm base e into a logarithm base 10 just by multiplying by the correct number. That, too, will come.

Another common explanation is to say that e describes how fast savings will grow under the influence of compound interest. A dollar invested at one-percent interest, compounded daily, for a year, will grow to just about e dollars. Compounded hourly it grows even closer; compounded by the second it grows closer still; compounded annually, it stays pretty far away. The comparison is probably perfectly clear to those who can invest in anything with interest compounded daily. For my part I note when I finally opened an individual retirement account I put a thousand dollars into an almost thoughtfully selected mutual fund, and within mere weeks had lost \$15. That about finishes off compound interest to me.