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## String diagrams, duality, and trace

Previously we introduced string diagrams and saw that they were a convenient way to talk about tensor products, partial compositions of multilinear maps, and symmetries. But string diagrams really prove their use when augmented to talk about duality, which will be described topologically by bending input and output wires. In particular, we will be able to see topologically the sense in which the following four pieces of information are equivalent:

• A linear map $U \to V$,
• A linear map $U \otimes V^{\ast} \to 1$,
• A linear map $V^{\ast} \to U^{\ast}$,
• A linear map $1 \to U^{\ast} \otimes V^{\ast}$.

Using string diagrams we will also give a diagrammatic definition of the trace $\text{tr}(f)$ of an endomorphism $f : V \to V$ of a finite-dimensional vector space, as well as a diagrammatic proof of some of its basic properties.

Below all vector spaces are finite-dimensional and the composition convention from the previous post is still in effect.

## Introduction to string diagrams

Today I would like to introduce a diagrammatic notation for dealing with tensor products and multilinear maps. The basic idea for this notation appears to be due to Penrose. It has the advantage of both being widely applicable and easier and more intuitive to work with; roughly speaking, computations are performed by topological manipulations on diagrams, revealing the natural notation to use here is 2-dimensional (living in a plane) rather than 1-dimensional (living on a line).

For the sake of accessibility we will restrict our attention to vector spaces. There are category-theoretic things happening in this post but we will not point them out explicitly. We assume familiarity with the notion of tensor product of vector spaces but not much else.

Below the composition of a map $f : a \to b$ with a map $g : b \to c$ will be denoted $f \circ g : a \to c$ (rather than the more typical $g \circ f$). This will make it easier to translate between diagrams and non-diagrams. All diagrams were drawn in Paper.

## Finite noncommutative probability, the Born rule, and wave function collapse

The previous post on noncommutative probability was too long to leave much room for examples of random algebras. In this post we will describe all finite-dimensional random algebras with faithful states and all states on them. This will lead, in particular, to a derivation of the Born rule from statistical mechanics. We will then give a mathematical description of wave function collapse as taking a conditional expectation.

## ab, ba, and the spectrum

Let $a, b$ be two $n \times n$ matrices. If $a, b$ don’t commute, then $ab \neq ba$; however, the two share several properties. If either $a$ or $b$ is invertible, then $ab$ is conjugate to $ba$, so in particular they have the same characteristic polynomial.

What if neither $a$ nor $b$ are invertible? As it turns out, $ab$ and $ba$ still have the same characteristic polynomial, although they are not conjugate in general (e.g. we might have $ab = 0$ but $ba$ nonzero). There are several ways of proving this result, which implies in particular that $ab$ and $ba$ have the same eigenvalues.

What if $a, b$ are linear transformations on an infinite-dimensional vector space? Do $ab$ and $ba$ still have the same eigenvalues in an appropriate sense? As it turns out, the answer is yes, and the key lemma in the proof is an interesting piece of “noncommutative high school algebra.”

## The quaternions and Lie algebras I

Someone who has just read the previous post on how exponentiating quaternions gives a nice parameterization of $\text{SO}(3)$ might object as follows: “that’s nice and all, but there has to be a general version of this construction for more general Lie groups, right? You can’t always depend on the nice properties of division algebras.” And that someone would be right. Today we’ll begin to describe the appropriate generalization, the exponential map from a Lie algebra to its Lie group. To simplify the exposition, we’ll restrict to the case of matrix groups; that is, nice subgroups of $\text{GL}_n(\mathbb{F})$ for $\mathbb{F} = \mathbb{R}$ or $\mathbb{C}$, which will allow us to mostly avoid differential geometry.

The theory of Lie groups and Lie algebras is regarded to be one of the most beautiful in mathematics, and it is also fundamental to many areas, so today’s post is an extended discussion motivating the definition of a Lie algebra. In the next post we will actually do something with them.

For studying the hydrogen atom, our interest in Lie algebras comes from the following. If a Lie group $G$ acts smoothly on a smooth manifold $M$, its Lie algebra acts by differential operators on the space $C^{\infty}(M)$ of smooth functions, and these differential operators are the “infinitesimal generators” which give us conserved quantities for the evolution of a quantum system on $M$ (in the case that $G$ consists of symmetries of the Hamiltonian). Despite the fact that Lie algebras are commonly sold as a tool for understanding Lie groups, arguably in quantum mechanics the Lie algebra of symmetries of a Hamiltonian is more fundamental. This is important in sitations where the Lie algebra can sometimes exist without an associated Lie group.

## A linear algebra puzzle

I won’t get around to substantive blog posts for at least a few more days, so here is a puzzle.

We usually thinks of groups that occur in nature as permutations of a set which preserve some structure on that set. For example, the general linear group $\text{GL}_n(F)$ preserves the structure of being an $F$-vector space of dimension $n$.

What structure does the special linear group $\text{SL}_n(F)$ preserve?

(I have an answer, but I’m curious if it can be stated in a more elementary way.)

A (maximal) flag in a vector space $V$ of dimension $n$ is a chain $V_0 \subset V_1 \subset ... \subset V_n$ of subspaces such that $\dim V_i = i$. The flag variety of $G = \text{SL}(V) = \text{SL}_n$ is, for our purposes, the “space” of all maximal flags. $\text{SL}_n$ acts on the flag variety in the obvious way, and the stabilizer of any particular flag is a Borel subgroup $B$. If $e_1, ... e_n$ denotes a choice of ordered basis, one can define the standard flag $0, \text{span}(e_1), \text{span}(e_1, e_2), ...$, whose stabilizer is the space of upper triangular matrices of determinant $1$ with respect to the basis $e_i$. This is the standard Borel, and all other Borel subgroups are conjugate to it. Indeed, it’s not hard to see that $\text{SL}_n$ acts transitively on the flag variety, so the flag variety can be identified with the homogeneous space $G/B$.