Thursday, 17 January 2008

What can be said about the homotopy groups of a CW-complex in terms of its (co)homology?

Try looking up some references on rational homotopy theory. Rational homotopy theory studies the homotopy groups tensor Q, so basically you kill all torsion information. If we focus only on homotopy groups tensor Q, the question you ask becomes easier. As Steven Sam mentions in the comments, the homotopy groups of spheres are really crazy. But the rational homotopy groups of spheres are quite tractable (in fact completely known, by a theorem of Serre) and can be more or less obtained from cohomology, if I recall correctly.



One particularly impressive theorem, of Deligne-Griffiths-Morgan-Sullivan, says that if your space is a compact Kähler manifold (e.g. a smooth complex projective variety), and if you know its rational cohomology ring, then you can compute for instance the ranks of all of its homotopy groups (maybe you need an extra assumption that the space is simply connected or has nilpotent fundamental group).

Wednesday, 16 January 2008

gr.group theory - Abelianization of a semidirect product

I agree with Ryan and Victor, except that you don't need presentations. The subgroup $[G ltimes H,G ltimes H]$ is generated by $[H,H] cup [G,H] cup [G,G]$, so you can write
$$(G ltimes H)^{ab} = (G ltimes H) / langle [H,H] cup [G,H] cup [G,G] rangle.$$
If you apply the relators $[H,H]$, you get $G ltimes H^{ab}$; then if you apply the relators $[G,H]$, you get $G times (H^{ab})_G$; then finally if you apply $[G,G]$, you get $G^{ab} times (H^{ab})_G$. You can add this as an extra half-paragraph or footnote rather than giving a citation.



I don't think that the referee has the right to demand a longer explanation than this, unless maybe you are writing a textbook.

evolution - Why is 'Grudger' an evolutionary stable strategy?

I am currently reading 'The Selfish Gene' by Richard Dawkins, which I am sure many here have read. The topic are evolutionary stable strategies (ESS) regarding cooperation.



I apologise for the long question. If you are already familiar with the topic and Dawkins' model of Cheat, Sucker and Grudger: my question is, how can Grudger be an ESS if it could be invaded both by Suckers (because they have no disadvantage against Grudger) and Cheats (because a Cheat minority is unlikely to meet the same Grudger twice, turning Grudger into Sucker effectively)?



More detailed:



The model



Near the end of chapter 10 (p 185 in my version), Dawkins uses a model of birds who clean each other of parasites, therefore helping in survival (as cleaning themselves they cannot reach every spot of their body). He defines three different behaviours for the model:



  • Sucker - birds who indiscriminately help and clean other birds

  • Cheat - birds who let others help them but never do so themselves

  • Grudger - birds who help others and remember who they helped. If the same bird does not help them later (reciprocate), they will not help that bird again.

Claim: Cheat and Grudger are ESS



He claims that both Cheat and Grudger in themselves are ESS - that is, if all birds behave this way, none of the other behaviours can develop because they will be immediately penalised by lower chances of reproducing.



The part that makes sense: Suckers is not an ESS, Cheat is



Sucker is of course not an ESS. If all birds were Suckers, any Cheat that developed would have a huge reproductive advantage and Cheat genes would overtake the population.



Being an ESS makes sense for Cheat. If all birds cheat, nobody will ever be helping each other. A minority of Suckers would be spending all their time helping and not getting anything in return, Cheats have the advantage and Suckers die out again. Grudger would be unlikely to meet a Cheat who they helped before again, so they too will spend all their time helping and die out again.



The part that confuses: Grudger is an ESS?



But Dawkins also claims that Grudger is an ESS, and he seems very confident in that. Now I don't consider myself enough of a smartypants to claim that he's wrong, but I don't understand how Grudger can be an ESS. If all birds behave in this way, and for any reason some Sucker developed - the Sucker would have no disadvantage. All birds would still always be helping each other, so nothing would stop the Suckers from propagating equally well as the Grudgers, invading the gene pool. That's already the ESS broken, but even further, the presence of Suckers would mean that if Cheats came up, they would have a realistic chance of surviving - Grudgers would shun them after having helped once, but if the number of Suckers is large enough, Cheats will have an advantage.



Moreover, back to the initial setting of Grudgers only - if a Cheat developed, he would be unlikely to meet the same Grudger twice, receiving the benefit all the time but never paying the cost. He would have an advantage and spread Cheat genes.



The problem



I'm not familiar enough with how these kinds of models are calculated in order to state chances that Cheats will take over completely, but however I think of it Grudger does not seem to be an ESS to me.



Does anyone have an explanation why Dawkins is so sure that it is? Seeing as in nature we do see patterns like Sucker and Grudger all the time, I must be missing something important here.

Tuesday, 15 January 2008

Protein Biology Cheat Sheet - Biology

For 95% of the work I do with protein, I find this chart very helpful, showing common post-translational modifications, for each amino acid, with molecular weights, associated codons, pKa values, 1- and 3-letter amino acid codes, chemical structure and chemical properties (polar, non-polar, aromatic, acidic, basic).

ct.category theory - What precisely Is "Categorification"?

The Wikipedia answer is one answer that is commonly used: replace sets with categories, replace functions with functors, and replace identities among functions with natural transformations (or isomorphisms) among functors. One hopes for newer deeper results along the way.



In the case of work of Lauda and Khovanov, they often start with an algebra (for example ${bf C}[x]$ with operators $d (x^n)= n x^{n-1}$ and $x cdot x^n = x^{n+1}$ subject to the relation $d circ x = x circ d +1$) and replace this with a category of projective $R$-modules and functors defined thereupon in such a way that the associated Grothendieck group is isomorphic to the original algebra.



Khovanov's categorification of the Jones polynomial can be thought of in a different way even though, from his point of view, there is a central motivating idea between this paragraph and the preceding one. The Khovanov homology of a knot constructs from the set of $2^n$ Kauffman bracket smoothing of the diagram ($n$ is the crossing number) a homology theory whose graded Euler characteristic is the Jones polynomial. In this case, we can think of taking a polynomial formula and replacing it with a formula that inter-relates certain homology groups.



Crane's original motivation was to define a Hopf category (which he did) as a generalization of a Hopf algebra in order to use this to define invariants of $4$-dimensional manifolds. The story gets a little complicated here, but goes roughly like this. Frobenius algebras give invariants of surfaces via TQFTs. More precisely, a TQFT on the $(1+1)$ cobordism category (e.g. three circles connected by a pair of pants) gives a Frobenius algebra. Hopf algebras give invariants of 3-manifolds. What algebraic structure gives rise to a $4$-dimensional manifold invariant, or a $4$-dimensional TQFT? Crane showed that a Hopf category was the underlying structure.



So a goal from Crane's point of view, would be to construct interesting examples of Hopf categories. Similarly, in my question below, a goal is to give interesting examples of braided monoidal 2-categories with duals.



In the last sense of categorification, we start from a category in which certain equalities hold. For example, a braided monoidal category has a set of axioms that mimic the braid relations. Then we replace those equalities by
$2$-morphisms that are isomorphisms and that satisfy certain coherence conditions. The resulting $2$-category may be structurally similar to another known entity. In this case, $2$-functors (objects to objects, morphisms to morphisms, and $2$-morphisms to $2$-morphisms in which equalities are preserved) can be shown to give invariants.



The most important categorifications in terms of applications to date are
(in my own opinion) the Khovanov homology, Oszvath-Szabo's invariants of knots, and Crane's original insight. The former two items are important since they are giving new and interesting results.

Monday, 14 January 2008

mathematics education - effective teaching

I just watched the video -- I didn't know of it and it is certainly very interesting and provides much food for thought.



From the perspective of someone who teaches, I could relate to parts of it: particularly the decreasing ability to understand student's questions. From the perspective of someone who was a student, though, I do remember learning during lectures: perhaps not in all courses, but certainly in some which I still remember fondly. These courses were usually lecture-based; although in one case the lecturer would ask questions to the students all the time: picking a starting person and then moving systematically along the audience. This used to instill the "fear of God" in some people, but it meant one had to be on top of the material. I enjoyed that and, in fact, it boosted my confidence.



Now to answer the question, in the University of Edinburgh (where I am based) we started a few years ago to teach some of the introductory courses incorporating some element of Peer Instruction. I personally have not taught introductory courses for a while, so I cannot say how this is panning out. The School of Physics (I'm in Maths) has been teaching the first-year introductory course using Peer Instruction for some time now and they seem to be very happy with the result.



I wonder whether some variant of this method can work for final-year courses, though.

pr.probability - Is there an introduction to probability theory from a structuralist/categorical perspective?

One can argue that an object of the right category of spaces in measure theory is not a set equipped
with a $sigma$-algebra of measurable sets, but rather a set $S$ equipped with a $sigma$-algebra $M$ of measurable
sets and a $sigma$-ideal $N$ of $M$ consisting of sets of measure $0$.
The reason for this is that you can hardly state any theorem of measure theory or probability
theory without referring to sets of measure $0$.
However, objects of this category contain less data than the usual measured spaces,
because they are not equipped with a measure.
Therefore I prefer to call them measurable spaces.
A morphism of measurable spaces $(S,M,N)to(T,P,Q)$ is a map $Sto T$ such that
the preimage of every element of $P$ is a union of an element of $M$ and a subset of an element of $N$
and the preimage of every element of $Q$ is a subset of an element of $N$.



Irving Segal proved that for a measurable space the following properties are equivalent:



  1. The Boolean algebra $M/N$ of equivalence classes of measurable sets is complete;

  2. The space of equivalence classes of all bounded (or unbounded) real-valued functions on $S$ is Dedekind-complete;

  3. Radon-Nikodym theorem is true for $(S,M,N)$;

  4. Riesz theorem is true for $(S,M,N)$;

  5. Equivalence classes of bounded functions on $S$ form a von Neumann algebra (aka $W^*$-algebra).

  6. $(S,M,N)$ is a coproduct (disjoint union) of points and real lines.

A measurable space that satisfies these conditions is called localizable.



This theorem tells us that if we want to prove anything nontrivial about measurable
spaces, we better restrict ourselves to localizable measurable spaces.
We also have a nice illustration of the claim I made in the first paragraph:
None of these statements would be true without identifying objects that differ
on a set of measure $0$.
For example, take a non-measurable set $G$
and a family of one-element subsets of $G$ indexed by themselves.
This family of measurable sets does not have a supremum in the Boolean algebra
of measurable sets, thus disproving a naïve version of (1).



Another argument for restricting to localizable spaces is the following version of
Gelfand-Neumark theorem:




The category of localizable measurable spaces is equivalent to the category of commutative von Neumann algebras (aka $W^*$-algebras) and their morphisms (normal unital homomorphisms of $^*$-algebras).




I actually prefer to define the category of localizable measurable spaces
as the opposite category of the category of commutative $W^*$-algebras.
The reason for this is that the classical definition of measurable space
exhibits immediate connections only to descriptive set theory (and with additional
effort to Boolean algebras), which are mostly
irrelevant for the central core of mathematics,
whereas the description in terms of operator algebras immediately connects
measure theory to other areas of the central core (noncommutative geometry,
algebraic geometry, complex geometry, differential geometry etc.).
Also it is easier to use in practice. Let me illustrate this statement
with just one example: When we try to define measurable bundles of Hilbert spaces
on a localizable measurable space set-theoretically, we run into all sorts of problems
if the fibers can be non-separable, and I do not know how to fix this problem in the set-theoretic framework.
On the other hand, in the algebraic framework we can simply say that a bundle
of Hilbert spaces is a Hilbert module over the corresponding $W^*$-algebra.



Categorical properties of $W^*$-algebras (hence of localizable measurable spaces)
were investigated by Guichardet.
Electronic version of this paper is available here.
Let me mention some of his results.
The category of localizable measurable spaces admits equalizers and coequalizers,
arbitrary coproducts and hence arbitrary colimits.
It also admits products, although they are quite different from what one might think.
For example, the product of two real lines is not $Bbb R^2$ with the two obvious projections.
The product contains $Bbb R^2$, but it also has a lot of other stuff, for example, the diagonal of $Bbb R^2$,
which is needed to satisfy the universal property for the two identity maps on $Bbb R$.
The more intuitive product of measurable spaces ($Bbb Rtimes Bbb R=Bbb R^2$) corresponds to the spatial
tensor product of von Neumann algebras and forms a part of a symmetric monoidal
structure on the category of measurable spaces.
See Guichardet's paper for other categorical properties (monoidal structures
on measurable spaces, flatness, existence of filtered limits, etc.).



Finally let me mention pushforward and pullback properties of measures on measurable spaces.
I will talk about more general case of $L^p$ spaces instead of just measures (i.e., $L^1$ spaces).
For the sake of convenience let $L_p(M) := L^{1/p}(M)$, where $M$ is a measurable space.
Here $p$ can be an arbitrary complex number with a nonnegative real part.
Note that you don't need a measure on $M$ to define $L_p(M)$.
In particular, $L_0$ is the space of all bounded functions (i.e., the $W^*$-algebra itself),
$L_1$ is the space of finite complex-valued measures (the dual of
$L_0$ in the $sigma$-weak topology), and $L_{1/2}$ is the Hilbert space of half-densities.
I will also talk about extended positive part $E^+L_p$ of $L_p$ for real $p$.
In particular, $E^+L_1$ is the space of all (not necessarily finite) positive measures.



Pushforward for $L_p$ spaces: Suppose we have a morphism of measurable spaces $Mto N$.
If $p=1$, then we have a canonical map $L_{1}(M) to L_{1}(N)$, which just the dual of $L_{0}(N) to L_{0}(M)$
in the $sigma$-weak topology. Geometrically, this is the fiberwise integration map.
If $pneq 1$, then we only have a pushforward map of the extended positive parts:
$E^+L_p(M) to E^+L_p(N)$, which is non-additive unless $p=1$.
Geometrically, this is the fiberwise $L_p$ norm.
Thus $L_1$ is a functor from the category of measurable spaces to the category of Banach spaces
and $E^+L_p$ is a functor to the category of "positive homogeneous $p$-cones".
The pushforward map preserves the trace on $L_1$ and hence
sends a probability measure to a probability measure.



To define pullback of $L_p$ spaces (in particular, $L_1$ spaces) one needs to pass to a different
category of measurable spaces.
In algebraic language, if we have two $W^*$-algebras $A$ and $B$, then
a morphism from $A$ to $B$ is a usual morphism of $W^*$-algebras $f: Ato B$
together with an operator valued weight $T: E^+(B)→E^+(A)$ associated to $f$.
Here $E^+(A)$ denotes the extended positive part of A (think of positive functions on $mathrm{Spec} A$
that can take infinite values).
Geometrically, this is a morphism $mathrm{Spec} f:  mathrm{Spec} B to mathrm{Spec} A $ between the corresponding
measurable spaces and a choice of measure on each fiber of $mathrm{Spec} f$.
Now we have a canonical additive map $E^+L_p(mathrm{Spec} A) to E^+L_p(mathrm{Spec} B)$,
which makes $E^+L_p$ into a contravariant functor from the category of measurable spaces
equipped with a fiberwise measure to the category of “positive homogeneous additive cones”.



If we want to have a pullback of $L_p$ spaces themselves and not just their extended positive parts,
we need to replace operator valued weights in the above definition
by finite complex-valued operator valued weights $T: B to A$ (think of fiberwise complex-valued measure).
Then $L_p$ becomes a functor from the category of measurable spaces to the category
of Banach spaces (if the real part of $p$ is at most $1$) or quasi-Banach spaces (if the real part of $p$ is greater than $1$).
Here $p$ is an arbitrary complex number with a nonnegative real part.
Notice that for $p=0$ we get the original map $f: Ato B$ and in this (and only this) case we don't need $T$.



Finally, if we restrict ourselves to an even smaller subcategory of measurable
spaces equipped with a finite operator valued weight T such that $T(1)=1$
(i.e., T is a conditional expectation; think of fiberwise probability measure), then the pullback map preserves
the trace on $L_1$ and in this case the pullback of a probability measure is a probability measure.



There is also a smooth analog of the theory described above: The category of measurable spaces
and their morphisms is replaced by the category of smooth manifolds and submersions,
$L_p$ spaces are replaced by bundles of $p$-densities, operator valued weights are
replaced by sections of the bundle of relative $1$-densities,
integration map on $1$-densities is defined via Poincaré duality (to avoid circular dependence
on measure theory) etc.
The forgetful functor that sends a smooth manifold to its underlying measurable space
commutes with everything and preserves everything.