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Note:These pages make extensive use of the latest XHTML and CSS Standards. They ought to look great in any standards-compliant modern browser. Unfortunately, they will probably look horrible in older browsers, like Netscape 4.x and IE 4.x. Moreover, many posts use MathML, which is, currently only supported in Mozilla. My best suggestion (and you will thank me when surfing an ever-increasing number of sites on the web which have been crafted to use the new standards) is to upgrade to the latest version of your browser. If that's not possible, consider moving to the Standards-compliant and open-source Mozilla browser.

February 26, 2017

Variance in a Metric Space

Posted by Tom Leinster

Here’s a small observation for a Sunday afternoon. When you have a random variable in n\mathbb{R}^n or some other similar space, you can take its expected value. For a random variable XX in an arbitrary metric space, you can’t take the expected value — it simply doesn’t make sense. But you can take its variance, and the right definition is

Var(X)=12𝔼(d(X 1,X 2) 2), Var(X) = \tfrac{1}{2} \mathbb{E}(d(X_1, X_2)^2),

where X 1X_1 and X 2X_2 are independent and distributed identically to XX.

Posted at 4:05 PM UTC | Permalink | Followups (6)

February 22, 2017

Functional Equations III: Explaining Relative Entropy

Posted by Tom Leinster

Much of this functional equations course is about entropy and its cousins, such as means, norms, and measures of diversity. So I thought it worth spending one session talking purely about ways of understanding entropy, without actually proving anything about it. I wanted especially to explain how to think about relative entropy — also known as relative information, information gain, and Kullback-Leibler divergence.

My strategy was to do this via coding theory. Information is a slippery concept, and reasoning about it takes some practice. But putting everything in the framework of coding makes everything more concrete. The central point is:

The entropy of a distribution is the mean number of bits per symbols in an optimal encoding.

All this and more is in the course notes. The part we did today starts on page 11.

Next week: relative entropy is the only quantity that satisfies a couple of reasonable properties.

Posted at 12:13 AM UTC | Permalink | Followups (1)

February 18, 2017

Distributive Laws

Posted by Emily Riehl

Guest post by Liang Ze Wong

The Kan Extension Seminar II continues and this week, we discuss Jon Beck’s “Distributive Laws”, which was published in 1969 in the proceedings of the Seminar on Triples and Categorical Homology Theory, LNM vol 80. In the previous Kan seminar post, Evangelia described the relationship between Lawvere theories and finitary monads, along with two ways of combining them (the sum and tensor) that are very natural for Lawvere theories but less so for monads. Distributive laws give us a way of composing monads to get another monad, and are more natural from the monad point of view.

Beck’s paper starts by defining and characterizing distributive laws. He then describes the category of algebras of the composite monad. Just as monads can be factored into adjunctions, he next shows how distributive laws between monads can be “factored” into a “distributive square” of adjunctions. Finally, he ends off with a series of examples.

Before we dive into the paper, I would like to thank Emily Riehl, Alexander Campbell and Brendan Fong for allowing me to be a part of this seminar, and the other participants for their wonderful virtual company. I would also like to thank my advisor James Zhang and his group for their insightful and encouraging comments as I was preparing for this seminar.

Posted at 7:06 AM UTC | Permalink | Followups (16)

February 14, 2017

Functional Equations II: Shannon Entropy

Posted by Tom Leinster

In the second instalment of the functional equations course that I’m teaching, I introduced Shannon entropy. I also showed that up to a constant factor, it’s uniquely characterized by a functional equation that it satisfies: the chain rule.

Notes for the course so far are here. For a quick summary of today’s session, read on.

Posted at 11:06 PM UTC | Permalink | Followups (12)

February 13, 2017

M-theory from the Superpoint

Posted by David Corfield

You may have been following the ‘Division algebra and supersymmetry’ story, the last instalment of which appeared a while ago under the title M-theory, Octonions and Tricategories. John (Baez) was telling us of some work by his former student John Huerta which relates these entities. The post ends with a declaration which does not suffer from comparison to Prospero’s in The Tempest

But this rough magic

I here abjure. And when I have required

Some heavenly music – which even now I do –

To work mine end upon their senses that

This airy charm is for, I’ll break my staff,

Bury it certain fathoms in the earth,

And deeper than did ever plummet sound

I’ll drown my book.

Posted at 1:21 PM UTC | Permalink | Followups (8)

February 10, 2017

The Heilbronn Institute and the University of Bristol

Posted by Tom Leinster

The Heilbronn Institute is the mathematical brand of the UK intelligence and spying agency GCHQ (Government Communications Headquarters). GCHQ is one of the country’s largest employers of mathematicians. And the Heilbronn Institute is now claiming to be the largest funder of “pure mathematics” in the country, largely through its many research fellowships at Bristol (where it’s based) and London.

In 2013, Edward Snowden leaked a massive archive of documents that shone a light on the hidden activities of GCHQ and its close partner, the US National Security Agency (NSA), including whole-population surveillance and deliberate stifling of peaceful activism. Much of this was carried out without the permission — or even knowledge — of the politicians who supposedly oversee them.

All this should obviously concern any mathematician with a soul, as I’ve argued. These are our major employers and funders. But you might wonder about the close-up picture. How do spy agencies such as GCHQ and the NSA work their way into academic culture? What do they do to ensure a continuing supply of mathematicians to employ, despite the suspicion with which most of us view them?

Alon Aviram of the Bristol Cable has just published an article on this, describing specific connections between GCHQ/Heilbronn and the University of Bristol — and, more broadly, academic mathematicians and computer scientists:

Alon Aviram, Bristol University working with the surveillance state. The Bristol Cable, 7 February 2017.

It includes some quotes from me and from legendary computer-security scientist Ross Anderson, as well as some nuggets from a long leaked Heilbronn “problem book” that’s interesting in its own right.

Posted at 2:42 PM UTC | Permalink | Post a Comment

February 7, 2017

Functional Equations I: Cauchy’s Equation

Posted by Tom Leinster

This semester, I’m teaching a seminar course on functional equations. Why? Among other reasons:

  1. Because I’m interested in measures of biological diversity. Dozens (or even hundreds?) of diversity measures have been proposed, but it would be a big step forward to have theorems of the form: “If you want your measure to have this property, this property, and this property, then it must be that measure. No other will do.”

  2. Because teaching a course on functional equations will force me to learn about functional equations.

  3. Because it touches on lots of mathematically interesting topics, such as entropy of various kinds and the theory of large deviations.

Today was a warm-up, focusing on Cauchy’s functional equation: which functions f:f: \mathbb{R} \to \mathbb{R} satisfy

f(x+y)=f(x)+f(y)x,y? f(x + y) = f(x) + f(y) \,\,\,\, \forall x, y \in \mathbb{R}?

(I wrote about this equation before when I discovered that one of the main references is in Esperanto.) Later classes will look at entropy, means, norms, diversity measures, and a newish probabilistic method for solving functional equations.

Read on for today’s notes and an outline of the whole course.

Posted at 11:25 PM UTC | Permalink | Followups (8)

The Category Theoretic Understanding of Universal Algebra

Posted by Emily Riehl

Guest post by Evangelia Aleiferi

We begin the second series of the Kan Extension Seminar by discussing the paper The Category Theoretic Understanding of Universal Algebra: Lawvere Theories and Monads by Martin Hyland and John Power, published in 2007. The subject of the above is to give a historical survey on the two main category theoretic formulations of universal algebra, the first being Lawvere theories and the second the theory of monads. Lawvere theories were introduced by William Lawvere in 1963 as part of his doctoral thesis, in order to provide an elegant categorical base for studying universal algebra, while monads were structures that had been already used in different areas of mathematics.

The article starts with the definition of a Lawvere theory and the category of its models, together with some of their properties. Later the authors proceed to relate the notion of monad to Lawvere theories and they give an explanation as to why they were dominantly used in the understanding of universal algebra, compared to Lawvere theories. Lastly they describe how monads and Lawvere theories can be used in formulating computational effects, motivated by the work of Moggi and Plotkin, and they propose future developments based on the connection between computational effects and universal algebra.

At this point, I would like to take the opportunity to thank Emily Riehl, Alexander Campbell and Brendan Fong for organizing the Kan Extension Seminar, as well as all the other participants for being such a great motivation!

Posted at 5:45 AM UTC | Permalink | Followups (31)