Military officers who cannot count

This from a US reporter in Afghanistan:

The Afghan forces have a lot of hurdles to overcome in the next two years. [There] is still a very high illiteracy rate. The Americans are trying to train the Afghans up to, for the soldiers, to a first-grade level, and the officers, a third-grade level. One officer told me that a lot of these soldiers cannot only not read or write but many can’t even count, and the US tries to get around this in some novel ways. I’ll give you a good example. They actually draw a rectangle in the dirt for [a commander] who can’t tell how many soldiers he has, or should have, and the Americans tell him that, listen, if the soldiers standing at attention fill this rectangle in the dirt, [he] would now have a full complement of soldiers.

— Pentagon correspondent Tom Bowman, speaking from Kandahar

All Things Considered for 20120502, “What The Afghanistan Deal Means For U.S. Troops”. Online at http://www.npr.org/2012/05/02/151877348/what-the-afghanistan-deal-means-for-u-s-troops, time 2:00–47 , accessed 20120502.

The origin of the symbol Θ (big theta) in asymptotic notation

In a recent review of Roger Hart’s superb Chinese Roots of Linear Algebra (2010) I’ve described what I believe is the motivation of Donald Knuth’s symbol Θ (“big theta”) in asymptotic notation.

I think it is a graphic pun on the O (“big O”) that stands for German Ordnung ‘order’, as in “order of growth”. I suggest that the bar in the middle of Θ is intended to represent tight bounds above and below, in contrast to big O (upper bound) and big omega (lower bound). I have not seen this explanation anywhere else.

Hart’s book is presently described on the Johns Hopkins University Press site, though such listings tend not to be permanent. The Project MUSE page for his book is at https://muse.jhu.edu/books/9780801899584.

For more on Hart’s research, see his website, http://rhart.org/.

Calculus III progresses

I am struggling to get caught up on my Calculus III homework. The first exam is 12 days away. I’m deep in the section of the book about which the instructor said, “This is the longest homework section in the semester and it will be the majority of the first exam. Those are the problems to stress about.” (I am obedient in all things, sir.) He recommends ten hours of homework a week for a five-hour-a-week class.

When I started the term, it was taking me an average of 30 minutes per problem — something I can’t imagine the other students are experiencing. I spent four hours on actual problem-solving today, plus perhaps another hour or so of flash-card making and other sorts of review. It hardly seems very much time. But I am pleased to find that my average speed is now down to 20 minutes/problem. That’s cause for optimism, even if it still feels as though my brain is a corroded mass of old gears. Come to think of it, I’ve had that sensation every time I’ve taken math recently, but somehow the immediacy of the sensation is replaced by a feeling of accomplishment after the stress of the moment has passed. It has been 25 years since I took Calculus II, but I think the gear-box is getting back to functioning condition.

Initially, I studied by taking careful notes on the ideas of each section in the text book, and only doing problems afterwards. But now I think that’s for the birds. Doing problems and groping my way through the ideas as I need to has proven a more effective way to get comfortable with the material. The notion that theoretical understanding, gained from reading the chapter, is a useful guide to problem-solving, is nonsense here just as it is in every other field I know of.

By far the most common cause of error in my work is sloppy arithmetic errors — half the time, it is just the result of getting plus and minus signs wrong. This in spite of considerable effort to avoid such mistakes. I have had this problem since my childhood. Using LaTeX to do my problems makes it easier to find them, since I can now actually read and even search mechanically through what I’ve written.

Tales from Calculus III

Twenty-five years after I took Calculus II, I am enrolled in Calculus III at City College. I’ve heard from many students that the instructor is one of the best in the program — he is leading one of ten sections this semester and I drew him by chance. Below are some observations recently sent to a few correspondents.

The instructor has said firmly:

The more problems you do, the more shortcuts you will figure out for yourself. The only way you can do this is to do a ridiculous number of problems. You must work almost every day on this stuff, for a couple of hours a day.

Homework is not graded, but we are supposed to keep a special notebook in which “assignments”, meaning hard problems apart from the homework proper, are to be done — and those he will examine on occasion. If we’ve done them. On Thursday morning we were supposed to visit his office before class to show him that we do, indeed, possess such a notebook. The point was to encourage students to make the effort to identify a notebook for those problems early in the term. I was the only one who came, though, and I’m going to be using LaTeX, with his blessing.

The assignment sheet for the semester went up just before class on Tuesday and he announced it in class and told us to do the first three sections, 23 problems in all, mostly vectors, which are not well handled in LaTeX. I spent six hours doing the first assignment and got through 19 of the 23; the last four remain undone several days later, despite my good intentions. On the day they were official due, several of the students were still asking him when he would post the problem sets.

This instructor says he is going at solving problems but his memory is terrible, so he has never learned LaTeX. Instead, he uses MathType, which provides a GUI. It’s a pity, because a math course is really the ideal place to introduce LaTeX and guide students in elementary use of it.

The instructor made a pitch to interest me in abstract algebra. I must admit, what he showed me seemed quite interesting and intuitively clear. I have yet to understand what the place of math will ultimately be in my life — I only know I am not yet done with this question.

I am the only student in the class of around 30 who is taking notes on a computer. Some students do open up a computer briefly, but it seems to have something to do with messaging. I ran into a little trouble today with LaTeX because I had anticipated that we was going to introduce determinants, which I haven’t learned how to handle yet (actually it’s not hard, I now see — the amsmath package has everything I’m likely to need).


A correspondent, seeing the comment about doing “a ridiculous number of problems,” replied:

That sounds reasonable to me. The “problem” is that the advent of software like Wolfram|Alpha removes any real usefulness from this kind of skill … it is now a purely aesthetic amusement.

But I disagree. Skill brings understanding, and understanding leads to insight into other things whose existence you can predict but whose content and requirements you can’t easily anticipate. Much of the mathematical and theoretical component of the computer science education at City College consists of exposure to proofs, or to things like proofs such as building a linked list in C++, and so on. It is not as though we will ever need to build our own linked lists or derive Chebyshev’s inequality. But struggling to produce them myself helps me to understand and retain them, and there is considerable value in that.

‘Factorial’ in Chinese (jiēchéng 階乘/阶乘)

As with the overwhelming majority of technical terms in mathematics and the sciences, the Chinese word corresponding to English factorial is compositionally transparent — you can tell much more easily what it means by analyzing it than you can its English counterpart. (At least, by analyzing it in writing.)

Factorial is jiēchéng 階乘/阶乘, meaning “stepped multiplication”. Chinese mathematics in symbols usually uses the form n! just as other languages do, but the word is sometimes written out in full, and at those time it becomes clear that it is being treated a noun. For instance: ēnde jiēchéng, written n 的階乘, and meaning ‘the factorial of n‘. In English, factorial can certainly function as a noun, but in the form n factorial (corresponding to n!) I think it is more natural to think of it as a suffixed function-modifier, like “five squared”, “the quotient doubled”, and so on. The current version of the Oxford English Dictionary (accessed on-line, 20111215) does not list this particular usage, but identifies factorial first of all as an adjective, in usage such as factorial expression, factorial function, and so on.

Emanuel Derman and Paul Wilmott on mathematical models and self-delusion (2009)

Derman and Wilmott:

Simple clear models with explicit assumptions about small numbers of variables are … the best way to leverage your intuition without deluding yourself.

— “Financial Modelers’ Manifesto,” January 7, 2009, Posted at http://www.wilmott.com/blogs/paul/index.cfm/2009/1/8/Financial-Modelers-Manifesto , accessed 20111214. (Forum discussion at http://www.wilmott.com/messageview.cfm?catid=3&threadid=67869)

Y. R. Chao and Henry Sheffer added to the Mathematics Genealogy Project

I mentioned in an earlier post that my “grandteacher”, Y. R. Chao 趙元任, did his dissertation on a problem in logic, even though he is best known for his work as a linguist and composer. (Though I think that his Language and Symbolic Systems, 1968, and his methodology in descriptive and historical linguistics all clearly show his predilections.)

I’m happy to say that Mitch Keller, who runs the Mathematics Genealogy Project, has now agreed that both Chao and his teacher, Henry Sheffer, deserve to be listed in the records there, even though their degrees were from departments of Philosophy. Chao’s entry is here and Sheffer’s can be found from it.

It seems that none of Chao’s students has a degree in a strictly mathematical field, though perhaps some will be found in the future.

Math in the Movies

Today a cryptographer said in my presence, “In the movies, the only option for a math guy is to go crazy.” Certainly, it seems that math is more often used as a symbol of deep or contorted thinking than as an achievable skill or pastime for a normal person.

But maybe the situation is not quite so bad. Since 1996, Arnold Reinhold has been collecting references to math in a website currently at http://world.std.com/~reinhold/mathmovies.html . Mathematics seems to make a few worthy appearances.

But hardly as many as there might be. What does this say about Anglophone society? I have the impression mathematics is taken more seriously as a pursuit for normal people in South and East Asia, Russia, and Israel — I wonder if the situation better in movies made in those places. Or maybe the movie-making world and the world of mathematical competence are just about mutually exclusive, and so few pathways exist for improving the portrayal of math in the movies.

Actually, I am not bothered so much by depictions of crazy mathematicians. There have been, after all, some great mathematicians with spectactularly quirky personalities, if not outright mental illness — Cantor, Gödel, Boltzmann, and Newton come to mind among the first-rung names, and there are many others elsewhere in the vast nimbus of minds. Being strange or mentally ill does not of itself invalidate a person’s thoughts, in any case. (Does that really need to be said?) What bothers me most is the standard cinematic trope of of the math genius who has instant insights and doesn’t need to work to prove or develop them. You might call it the Rāmānujan syndrome. Wesley Crusher and Will Hunting are prime examples. It’s hard to think of a stereotype more damaging to the development of healthy intellectual skills in normal people.

Something could be done to correct this stereotyping, which I’m sure takes place because of ignorance rather than ill will on the part of scriptwriters and directors. How about a movie or two in which problem-solving is shown as it really is: something carried out by normal people through patient hard work and practice, through a skill that can be cultivated by the sane and the normal. After all, solving problems of one sort or another is something everyone does, and it is rarely a matter of sudden inspiration — instant, complete, and requiring no further labor. Then again, maybe someone thinks that isn’t dramatic enough for a movie.

Doctoral pedigrees

The Mathematics Genealogy Project at North Dakota State University documents lines of academic filiation (primarily through doctoral degrees) in mathematics. It makes for interesting reading. Though my degree is “Asian Linguistics”, I can connect myself to the mainstream mathematical tree through a sub-branch of four progenitor Doktorväter:

  • Josiah Royce, 1878 (Philosophy)

  • Henry M. Sheffer, 1908 (Philosophy)

  • Yuen Ren Chao 趙元任, 1918 (Philosophy)

  • Jerry Norman, 1969 (Oriental Languages)

[Update 20111213: Chao and Sheffer are now in the tree; see this post.] Sheffer and initially Chao studied logic, a field developed at Harvard by Royce. Sheffer is best known for having introduced the NAND operation to Boolean logic. Chao’s main scholarly contributions were in Chinese historical phonology and modern grammar. Jerry Norman has pioneered the rigorous study of Chinese dialect classification, which you might say is a type of applied logic.

Through Royce, I can trace my “pedigree” to various luminaries of the Humanist era: Erasmus, Vesalius, Ficino, Copernicus, Leibniz, and Marin Mersenne, a student of prime numbers after whom is named the Mersenne twister, a pseudo-random number generator now widely used on personal computers. To Kant, as well, and to non-Humanists like Thomas à Kempis and Thomas Cranmer. Most lines peter out in the early 15th century; earlier stragglers include the mathematician and theologian Heinrich von Langenstein, an antecedent of Copernicus who received his Theol. Dr. in 1375, while the neo-Platonist Georgios Plethon Gemistos seems to have received the first of his degrees in 1380.

There is romance in seeing one’s connection to people like Leibniz and Erasmus, but it means little beyond that. Does anyone with a PhD today, in any field, not belong to those lines of filiation? As of today, Erasmus is shown to have 95301 descendants listed in mathematics alone. I have learned an enormous amount from Jerry Norman, and it is justice to call him my Doktorvater. I find myself in strong agreement with Chao’s model of formal Chinese historical phonology, too, and I have a special love for logic. But the model of linguistic fieldwork I use owes considerably more to Robert Austerlitz and Li Fang Kuei 李方桂 than to Chao, whose approach I consider altogether too literary. I also identify myself intellectually with my maternal grandfather, who left school when he was 12 but was a voracious reader and lifelong pursuer of ideas. At best, all that a paper pedigree can do is remind me to try to be true to the effort that generations of scholars, known and unknown, have made in order to seek knowledge and see clearly — to those ideas and those people all human beings are equally heirs.


There is at least one program available to generate graphs from the Project: see http://www.davidalber.net/geneagrapher/.

Code-switching between comfortable cognitive aptitudes and the main aptitudes used in math and coding

I continue to reflect on different kinds of thinking I rely on in my current activities.

My study of and research on Chinese involves a kind of technical thinking about abstract linguistic categories, but those categories and the evidence for them require doing long stretches of basically mechanical, clerical work — collation of field notes or minute philological details — the aptitude for which the people at the Johnson O’Connor foundation call “graphoria”. In this work one does relatively little interesting original thinking, except to the extent that one is aware of the higher-level problems to which the mechanical work and the minute details will contribute. And there is also something meditative and satisfying about paying close attention to minute details for a long stretch of time, so the work by no means simply mindless rote action. Working with Chinese words, spoken and written, in particular, seems to stir my musical and graphic-analytical proclivities, and I have the sensation that Chinese grammar moves a kind of structural thinking, as well. So the mechanical work is not without its interest and satisfactions, though those do not compare to the kind of thinking one can eventually do when one has the necessary data assembled for actually attacking a problem in a unified way. I often think that one of the things that makes formal linguistics so uninteresting is that its practitioners seem to spend a lot of time avoiding actually handling data at length.

In programming and mathematics, however, neither the graphoria nor any aspect of language or music aptitudes seem to be directly helpful. In fact, I often find that my motivation to turn my mind to non-linguistic quantitative thinking is hindered by whatever time I have recently spent on mechanical or linguistic work, because those are inevitably easier to pick up quickly than math or a complex programming task. I experience a wrenching “code-switching” moment when I have to do this. I have still to find a good way to get my mind into the mood for math quickly if I have been doing those “lower”-level tasks. The only effective way I have found so far is to put clerical tasks completely away from myself for weeks at a time, but in real life it is not possible to do that, and certainly not for the coming half year, until my last two or three book projects are done.

I get a little help from using a timer to force myself to to spend some period of time working concentratedly on one type of task before switching to another. But the code-switching remains jarring even with the pressure of the timer to aid the switch. I wonder daily if overcoming code-switching is after all simply a matter of patience and concentration.

“Suppose” for math proofs, in LaTeX

Slightly adapted from a suggestion by Scott Pakin, here is LaTeX code to generate the “suppose” symbol used by some mathematicians in writing proofs:

\newlength{\Swidth}
\newcommand{\suppose}{%
\settowidth{\Swidth}{S}
\makebox[\Swidth]{\(_{\rule{.15ex}{.8ex}}\)}\llap{S}%
}

“Suppose there exists some \(x\) in set \(U\ldots\)” becomes \(\suppose\ \exists\ x\in U\ldots\)



The symbol is the letter S with a vertical bar through the bottom curve:

Perception of time and suspension of finality (studying math)

What experiences well known to me involve an altered perception of time?

One of them is improving a piece of my own prose. After laboring to bring ideas into being as words and then to cantilever those words themselves until everything balances like a Calder mobile, I may raise my head – feeling that a very long time has passed – to find that not even an hour has gone by on the clock. There follows the relief of realizing that less time has elapsed in the material world than in my experience of it — relief since so often it is the other way around, and when it is the other way around I feel a little cheated and frustrated.

Another case is the enlivening of words by music. Sometimes the result is what known as “opera time”, in which the events of a musical drama are out of step with the tempo of the same events in real life. I mentioned this effect in passing in recent posts about Donna Elvira and the cantus firmus in some of the Bach choruses. Because altered perception of narrative time is related to the visceral appreciation of music, I think of this effect as having something in common with kinesthesia, the subjective sensation of body movement and position, an idea and feeling of keen interest to me in my daily life and study habits. Of course, not all music produces this effect to the same extent and I know different listeners react differently, too.


Since taking the first steps toward making my peace with mathematics almost two years ago, I have struggled with a third form of altered time-perception: a special feeling that comes about in trying to read and understand a mathematical idea, to fully follow or compose a proof, to formulate and solve a problem. There has been nothing in my life up to now as a humanist — linguistic fieldworker and student of the Chinese script and medieval prosody — that has prepared me for this experience. Part of the sensation is that my mind is being forced into a lower gear-ratio: suddenly, my engine has to make many more revolutions to get the wheels to turn just once.

The low-gear feeling reminds me of a half-hour spent some years ago in a tiny café in Longyan 龍巖, a small Chinese city where a market for coffee developed around 2004. In order to serve my companion and me two cups of coffee, perhaps 8 ounces in all, the café owner ground beans in a hand-operated burr mill for ten minutes, cranking rapidly the whole time. Long before he was done I felt embarrassed at the exertion he had taken on himself to make a good impression on me. He had few customers but I was the first foreigner his shop had ever had, so it was a matter of some moment for him. He had paid a lot of money to have an expert come up from Xiamen 廈門 to teach him how to make and serve coffee the “right way”, exactly the right way. His coffee was thin — but after all it was pretty good, better than you would get today in one of the big-name coffee chains here in New York.

In studying Classical Chinese, or reading collections of philological notes on an ancient dictionary manuscript, or collating piles of handwritten dialect data, you learn not to crave instantaneous satisfaction and even to distrust any result arrived at quickly. But by comparison with mathematics, all of those feel like short-term activities whose conceptual finiteness is easy to demonstrate. The reason for the difference must be that the kind of thinking we do in solving humanistic problems does not require such continual recasting of hypothesis and mindset, or for most of us (I hope I am not shocking anyone) as much rigor, either.

Unlike the other two examples I have cited — polishing my own writing, listening to thoughtfully constructed vocal music — the bending of time by mathematics is unpleasant, except in retrospect after I have succeeded in reaching a solution of some sort. I hope more practice will bring me more facility — that is a prescription that certainly works in studying Chinese, and it is what divides the good students from the mediochre ones. Sometimes mediochre students are vastly more brilliant than good ones, but Chinese requires more than brilliance for its mastery; it also requires the investment of time in what may appear to be drudgery. It requires, in short, commitment to some partial vision of the future along with a willingness to ignore the clock. As for math, impatience is certainly my chief obstacle, and impatience is one of what Epictetus calls “things that are up to us”. I have tried techniques to increase my stamina and concentration, and to recover more quickly from periodic cognitive exhaustion. And to suppress the arrogant expectation that I can cut through the difficulties quickly. Nothing I have tried helps in a way that I could call striking — I mean that nothing lives up to my arrogant expectation that I can continue to indulge in arrogant expectation — and most of it does not help at all, except to distract me and waste enough time to make me feel a little cheated and frustrated again.

In the end, I think what will really matter is my own willingness to suspend impatience and all expectation of achieving finality, to refuse to feel them. I do not find it hard to attain this suspension on some occasions — when I listen to Beethoven’s late music — but in doing math you are not listening; it is as though you are actually composing the music, yourself.

Herb Gross’s calculus lectures

For studying calculus, doing problem sets is the main thing, until the process becomes more or less mechanical. You can do that on your own for the most part.

If you crave understanding, however, you cannot find better on-line lectures than those of Prof. Herbert Gross.

Prof. Gross taught mathematics at MIT and Bunker Hill Community College for a lifetime, and around 1970 he prepared a series of videos — the clearest instructional films I can remember seeing.

The main series, “Calculus Revisited”, is part of MIT OpenCourseWare. The multivariable calculus videos are not included there yet, however, so has posted them himself on his own website:

Note that there are extensive paper (PDF) materials intended to supplement the videos.

Prof. Gross’s videos are far and away the best of their kind that I have seen, and never mind that they’re vintage 1969 and black and white. (Calculus itself dates from around 1660-1860 and the era of ink and quill.)

I contacted Herb Gross earlier this year and asked him about the origins of his project. He told me that he developed this curriculum over about three years with Harold Mickley, the director of the Center for Advanced Engineering Study (CAES) at MIT. It was intended for industry. Gross and Mickley went over the lecture plans in detail to ensure that everything was as clear as possible. No cue cards (the predecessor of the teleprompter) were used, since the blackboard content was written out in advance and provided a running outline of each lecture. He added, “Our feeling is that it was fine to overload the content because people could view the video at their own pace, pausing the video and/or fast forwarding it as desired. To keep things from being boring or looking ‘canned’ to the students, we left enough space on the board for me to interject supplementary remarks with the black chalk.” I asked about the filming schedule; he was not positive but said he thought it was two or three videos a day twice a week.

He said, “By MIT standards I was a mediocre math student but an excellent math instructor.” Not only an excellent instructor but a most generous one. Herb Gross and MIT have done the calculus student an immense service.

A math professor I enjoyed

I want to describe one of the professors I know at the Grove School of Engineering at the City College of New York.

This man, in his sixties, teaches math-heavy courses in the Computer Science department. His course descriptions still mention Fortran, though I think he teaches mainly in C and C++. But mentioning Fortran is good for producing a certain effect, and my guess is he desires that effect. He doesn’t hold with electronic bulletin boards and just hands out a multi-generationally photocopied one-page syllabus with the current year’s changes marked in pen. It is usually not straight on the page. His lectures are mostly proofs, which he delivers looking alternately at the board or at a corner of the ceiling at the back of the room — though he does engage occasionally in a sort of Socratic baiting of students. (“What is an ‘even number’?” Then shoot down all student answers on the way to the truth.) His exams are all problems from the book. He might as well be drawing in the sand with a stick in the time of Archimedes. But you can learn a lot from him if you work hard.

He seems very gruff, but I’ve spoken with him at length in private and I find him deeply concerned about whether students are learning the material or not. He is particularly unhappy about the fact that the distribution of student grades is bimodal — it is hard to “teach to the middle”, he says, when there is none.

Newton’s own suffering at math

Mr Machin told me that telling Sir I. once that he admired very much his fine problems in Geometry, but infinitely more his Theory of the Moon for which he had no rule that was all sagacity – Sir I. smiled & said his head never ached but with his studies on the moon —

Halley told me he often pressed Sir I. to compleat his Theory of the Moon saying no body else euer could, Sir I. told him it had made his head ach & kept him awake so often that he would think of it no more, but Sir I. said afterwards to me that if he lived till Halley had made six years observations he would haue t’other stroke at it.

From “Drafts of portions of John Conduitt’s intended Life of Newton”, The Newton Project http://www.newtonproject.sussex.ac.uk/view/texts/normalized/THEM00169