Category Archives: General Mathematics

What is a Manifold?

Preamble
So I have decided to create a few posts about some of the important mathematical ideas that I regularly encounter. The idea is to be rather informal and try to give a general feeling about these objects rather than a proper mathematical definition. I am hoping these posts will be readable to anyone with a reasonable high school education in mathematics. I will assume basic algebra and elementary geometry in the plane for example.

Please email me if you have something you would like me to cover.

So on to manifolds…

Introduction
Manifolds are an important notion in geometry and topology. Basically they are spaces that locally look like the much more familiar Euclidean spaces. This allows the well-understood notions on Euclidean spaces to be generalised to manifolds rather directly.

Coordinates
Recall that the space $latex\mathbb{R}^{n}$ for some integer $latexn$, can be understood by assigning an n-tuple \(x^{\mu}:=(x^{1}, x^{2}, \cdots , x^{n})\) of real numbers to each point; that is we can pick some coordinate system. The choice of coordinates is far from unique and a large part of geometry is related to the freedom in picking coordinates. We will not worry about changes of coordinates here.

coordinates
Above we have a Cartesian coordinate system on the plane. Every point is assigned a pair of numbers.

It was Rene Descartes (1596-1650) who pioneered this analytic approach to geometry; today we honor him the term Cartesian when referring to coordinates. By employing coordinates, algebra and analysis can come to bare on question in geometry. This is in contrast to the axiomatic or synthetic approach that goes back to Euclid (circa 300 BC). The synthetic approach to geometry uses axioms, theorems and logical arguments to study spaces.

Manifolds
We can now describe the notion of a manifold, which is a higher dimensional analogue of a curve or a surface. A manifold of dimension \(n\) is a space, you can think of a collection of points, that locally looks like $latex\mathbb{R}^{n}$ for some integer \(n\). All curves in the two dimensional plane that do not intersect locally look like part of a line. All smooth surfaces in \(\mathbb{R}^{3}\), that is surfaces that do not have sharp kinks, edges, or points all locally look like the two dimensional plane, see figure below. Thus such surfaces are two dimensional manifolds. One should imagine being able to tear any small piece off the smooth surface, then being able to stretch it, push down any “hills” and push up any “valleys”” to end up with a flat piece of the 2-plane.

surface

From Wikipedia

A little more formally, a manifold of dimension \(n\) can be thought of as being built up out of domains, which are open subsets of \(\mathbb{R}^{n}\). Intuitively, an open set is a set of points, in this case a subset of points belonging to \(\mathbb{R}^{n}\), such that any individual point can be displaced and still remain in the set. This gives a notion of points being “near” without the need for the notion of a distance between points. Such domains are commonly denoted as \(U \subset \mathbb{R}^{n}\). One can then “build” a manifold by patching these domains together, a bit like how one would make a patchwork quilt. It is how these domains are patched together that really defines the manifold.

In essence, the domains allows us to employ local coordinates when dealing with manifolds. Thus, one can build the theory of manifolds based on our understanding of the space \(\mathbb{R}^{n}\).

A quite familiar example to us all is the relation between a globe and a map. (I mean the common notion of a map, not the mathematical one!) The globe is a representation of the Earth (or any other planet) on the surface of the two sphere. Small pieces of the globe can always be represented as a map, which you think of as a piece of the two plane. Useful local coordinates on the maps can then be employed.

globe
Image by Christian Fischer.

The picture to have in your mind when thinking about manifolds is the relation between a globe and a map. Small pieces of the globe can always be described by maps (pieces of the 2-plane). Moreover, the entire globe can be covered by a collection of maps: an atlas.

map

Etymology
The etymology of the word “manifold” is old English. The word literally means many folds. Today, generally the word has come to mean any object having many different parts or features. The use of manifold in the mathematical context is adapt, manifolds are generalisations of surfaces that are built up from many domains and have many features not seen on $latex\mathbb{R}^{n}$.

Not manifolds
It is also worth highlighting some spaces that are not manifolds. A very simple example would be a self-intersecting curve in the plane. Such a curve will have regions that look like “X”. At these intersection points we no longer have a manifold structure. Such spaces are known as manifolds with a singularity.

double cone
Image courtesy of Wolfram

The double cone above looks very much like a manifold apart from the point at which the two cones meet. Everywhere not near this apex locally looks like the plane. This is also an example of a manifold with a singularity.

Manifolds with a boundary are not manifold!. For example the finite cylinder has two circles which are one dimensional manifolds as it’s boundaries.

cylinder

Applications
Manifolds can have a variety of extra structures on them. Indeed I have been very loose with the class of manifolds I have discussed here. Anyway, manifolds can have a differentiable structure on them meaning that we can do calculus on them. This is great for physics and indeed smooth manifolds are important in theoretical physics.

For example, smooth manifolds that come with a metric, that is a notion of distance on them, are at the heart of Einstein’s general relativity. Also, smooth manifolds also appear as the phase spaces in classical mechanics and these carry another interesting structure, that of a Poisson bracket.

I will say more about Poisson brackets in another post.

A tale of two pizzas

pizza
Image Credit: Pizza Slice Clip Art from vector.me (by johnny_automatic)
My wife and I were in a pizza shop near Warsaw old town. We were looking at the menu and saw that 31cm pizza costs about 30 PLN and a 61cm pizza costs about 70 PLN. There is of course a little variation with the exact toppings.

Based on this my wife said that we would be better off getting two 31cm pizzas rather than one 61cm pizza.

So I bought the one 61cm pizza.

But why?
In all fairness, my wife did immediately realise her mistake…

The pizzas, which are assumed to be circular, are specified by their (approximate) diameter \(d \), which is of course twice the radius \(r\). Thus surface area of the pizza is given by

\(A = \pi r^{2} \).

Importantly the area varies as \(r^{2}\) and not simply as \(r\). Thus a pizza with twice the diameter, or equivalently twice the radius of a given pizza, has four times the surface area, not twice the surface area.

Simply

\(\frac{A_{2}}{A_{1}} = \frac{\pi (2r)^{2}}{\pi r^{2}} =4\).

Roughly, given that the pizza was not a perfect circle and that 61 is not quite twice 31, I get about twice as much pizza buying the single 61cm as compared with buying two 31cm pizza.

Furthermore, \(70/60 \approx 1.2\). So I get near enough twice the pizza for my money by getting one 61cm pizza as compared with two 31cm.

The pizza

pizza
The result of my mathematics!

Above is the said 61cm pizza. It was very good.

In conclusion
Mathematics can help you make good decisions, like what size pizza to buy!

Does mathematics really "exist"?

Mike Rugnetta asks “Is Math a Feature of the Universe or a Feature of Human Creation?”.

Math is invisible. Unlike physics, chemistry, and biology we can’t see it, smell it, or even directly observe it in the universe. And so that has made a lot of really smart people ask, does it actually even EXIST?!?! Similar to the tree falling in the forest, there are people who believe that if no person existed to count, math wouldn’t be around . .at ALL!!!! But is this true? Do we live in a mathless universe? Or if math is a real entity that exists, are there formulas and mathematical concepts out there in the universe that are undiscovered? Or is it all fiction? Whew!! So many questions, so many theories… watch the episode and let us know what you think!

Mike Rugnetta of PBS’ Idea Channel

The discussion is rather philosophical…

Do all useful mathematical ideas really come from physics?

maths

Image by Saeed.Veradi

Some one once remarked to me that all the important ideas in mathematics come from physics. After a little thought I tend to agree, and for sure many important topics in mathematics have their roots in physics or at least quickly found applications in physics.

Below are some examples of the branches of mathematics that have clear physical applications as well as being of independent interest. The list is by no means complete, in no particular order and will reflect my own interests. Also I will not be at all technical here.

The theory of partial differential equations
This is just so encompassing, I was not sure how to include it! A partial differential equation (PDE) is a differential equation in unknown multivariable functions and their partial derivatives. PDEs are used to model a huge range of phenomena such as sound, heat flow, electromagnetic waves, fluids, the vibrating string, classical fields, superconductivity and so on.

As many branches of mathematics employ tools from differential calculus just about every mathematician will come across a PDE of some kind in his work. I cannot begin to list where the theory PDEs come in useful.

What should be remarked is that not all PDEs have nice solutions that can be expressed in terms of elementary functions. One will often need to turn to numerical methods to solve PDEs.

All the other branches listed below have some interface with PDEs as they are so universal.

Symplectic geometry and classical mechanics
Symplectic and Poisson geometry is essentially the study of manifolds equipped with Poisson brackets; that is a particular kind Lie algebra structure with a Leibniz rule. The study of such structures is fundamental in understanding the Hamiltonian formulation of classical mechanics; classical phase spaces carry such Poisson brackets.

Such geometries have become a large subject of study and also have found applications in diverse areas of mathematics. For example, geometric representation theory, non-commutative geometry, integrable systems and the theory of Lie algebroids have found much use for ideas found in Poisson geometry.

Riemannian geometry
This is loosely the study of spaces, that is manifolds, with the local notion of the length of a path as well as areas and volumes. One should think of Riemannian geometry as a very broad generalisation of the geometry of surfaces in \(\mathbb{R}^{3}\).

Although Bernhard Riemann’s initial work on the subject predates Einstein’s special and general relativity, Riemannian geometry is fundamental in the formulation of relativity. Indeed general relativity, that is Einstein’s theory of gravity as the local geometry of space-time, remains a large motivator for the study of Riemannian geometry.

One should also note that Riemannian geometry has proved useful in group theory, representation theory, algebraic topology and so on.

Functional analysis
Here we have the study of vector spaces equipped with some extra structure such as an inner product or a norm, and operators on such vector spaces. Such structure allows one to think about limits. Functional analysis has its roots in the study of function spaces and transformations on them like the Fourier transform. The main focus of functional analysis is the extension of the theory of integration and probability to infinite dimensional spaces.

The notion of a Hilbert space, which is an infinite dimensional vector space with an inner product, if fundamental in non-relativistic quantum mechanics. Spectral theory of operators on Hilbert spaces, which is part of functional analysis is very important in quantum physics. In particular the algebras of operators on such spaces is deeply linked with physics…

Operator algebras
Really this too can be seen as part of functional analysis. An operator algebra is (loosely) an algebra of linear operators on an infinite dimensional vector space. From a physics point of view operator algebras are found behind the quantum statistical mechanics, axiomatic quantum field theory and non-commutative generalisations of space-time.

Group theory
Group theory can be thought of as the abstract study of symmetry. Many physical systems exhibit symmetries, such as crystal lattices, molecules as well as the much more complicated symmetries that can be found behind electromagnetic theory. The representation theory of groups, “representing groups by linear operators on a vector space”, has fundamental applications in physics and chemistry. For example, all the fundamental particles in nature are classified by the representations of the Poincare group, which is the group describing the symmetries of flat space-time.

Group theory itself is a huge subject, which applications throughout pure and applied mathematics. For example, group theory has been very influential on the development of differential geometry and abstract algebra.

Combinatorics
Combinatorics is the study of finite or countable discrete structures. Loosely combinatorics is about counting the number of elements of some structure. The Fibonacci numbers are a classical example here.

Combinatorics has strong applications in algebra, probability theory, number theory and topology. From the physics side of things we see combinatorics appearing in statistical mechanics and quantum field theory.

Plants can do mathematics?

flag of walesProfs. Howard and Smith A team from the John Innes Centre report in e-Life journal, that plants can do basic mathematics [1]. The calculation allows them to use up their starch reserves at a constant rate so that they run out almost precisely at dawn.

This is the first concrete example in a fundamental biological process of such a sophisticated arithmetic calculation.

Professor Martin Howard from the John Innes Centre

The maths they can do
Plants feed themselves during the day light hours by convert carbon dioxide into sugars and starch. This is the well known process of photosynthesis. Once the sun has set, plants use their store of starch to prevent starvation.

The scientists at the John Innes Centre have shown that plants make precise adjustments to their rate of starch consumption. These adjustments are made so that the starch store lasts until dawn even if the night comes unexpectedly early or the size of the starch store varies.

Mathematical models show that the amount of starch consumed overnight is calculated by arithmetic division.

The plants have mechanisms to measure the size of the starch stores and can use their internal “body clock” to estimate the length of time until dawn. The size of the starch store is then divided by the length of time until dawn to set the rate of starch consumption. It turns out that by dawn, around 95% of starch is used up.

Reference
[1] Scialdone et al. Arabidopsis plants perform arithmetic division to prevent starvation at night, eLife 2013;2:e00669.
DOI: 10.7554/eLife.00669

Link
Plants do sums to get through the night JIC News

G-torsors

Let me quickly define a G-torsor.

Definition A G-torsor is a non-empty set X on which a group G acts freely and transitively.

A little more explicitly, X is a G-torsor if X is a nonempty set that is equipped with a map X × G → X such that
1) x·1 = x
2) x·(gh) = (x·g)·h

for all x in X, and h,g in G such that

(x,g) → (x, g·x)

is an isomorphism of sets.

Note that here we have picked the right action of G on X.

Remark One can modify these definitions to include categories other than sets, for example topological groups and spaces or even Lie groups and spaces.

Note that as we have an isomorphism, as sets, between X and G, they are equivalent objects. However, the subtlety is that there is no preferred identity point in X.

Ethos A G-torsor is a group that has lost its identity.

Once you have picked an identity element in X, you get an isomorphism as groups between X and G. This means that X and G are isomorphic as groups, but not canonically, a choice is needed.

What is the point of all this?
So it seems at first glance that torsors are very abstract objects far too complicated to be of much use to anyone. That is, until you realise that you have been using torsors without knowing it.

A good example of the use of a torsor is the potential difference in electromagnetism. When you measure a voltage, you in fact measure the difference of some voltage relative to some other fixed voltage. In practice one takes the ground to be zero, but this is a choice. Other values would work just as well. You can think of voltages as being elements of a torsor as there is no fixed identity voltage to measure against.

Energy in classical physics is very similar. The energy of a specified isolated system only really makes sense when one has set the “zero point energy”. One can only really measure energy differences relative to the “zero point energy”. This is why one can arbitrarily shift energies without effecting the physics. Actually, this is important when looking at the notion of energy in quantum field theory, but that is another story. Anyway, energies can be viewed as being elements of a torsor, you have no fixed “zero point energy” to measure all other energies against.

Physics is littered with similar examples.

A counter example would be temperature. We have a zero point temperature, that is absolute zero fixed for us.

Mathematics of course has lots of its own examples of torsors.

Consider a vector space V we can take G to be the general linear group GL(V) and X to be the set of all ordered bases of V. The group G acts transitively on X since any basis can be transformed via G to any other basis. In essence, one can take a specified basis and transform it into any other basis. Thus, one can consider all other bases as transformed versions of the initial basis. However, there is no natural choice of this “identity frame”. The set of bases do not form a group, but rather a torsor.

I will let the John Baez explain further here.

Compatible homological vector fields

In an earlier post, here, I showed that the homological condition on an odd vector field \(Q \in Vect(M)\), on a supermanifold \(M\), that is \(2Q^{2}= [Q,Q]=0\), is precisely the condition that \(\gamma^{*}x^{A} = x^{A}(\tau)\), where \(\gamma \in \underline{Map}(\mathbb{R}^{0|1}, M)\), be an integral curve of \(Q\).

A very natural question to answer is what is the geometric interpretation of a pair of mutually commuting homological vector fields?

Suppose we have two odd vector fields \(Q_{1}\) and \(Q_{2}\) on a supermanifold \(M\). Then we insist that any linear combination of the two also be a homological vector field, say \(Q = a Q_{1} + b Q_{2}\), where \(a,b \in \mathbb{R}\). It is easy to verify that this forces the conditions

\([Q_{1}, Q_{1}]= 0 \), $latex[Q_{2}, Q_{2}]= 0 $ and \([Q_{1}, Q_{2}]= 0 \).

That is, both our original odd vector fields must be homological and they mutually commute. Such a pair of homological vector fields are said to be compatible. So far this is all algebraic.

Applications of pairs, and indeed larger sets of compatible vector fields, include the description of n-fold Lie algebroids [1,3] and Q-algebroids [2].

The geometric interpretation
Based on the earlier discussion about integrability of odd flows, a pair of compatible homological vector fields should have something to do with an odd flow. We would like to interpret the compatibility of a pair of homological vector fields as the integrability of the flow of \(\tau = \tau_{1} + \tau_{2}\). Indeed this is the case;

Consider \(\gamma^{*}_{\tau_{1} + \tau_{2}}(x^{A}) = x^{A}(\tau_{1} + \tau_{2}) = x^{A}(\tau_{1}, \tau_{2})\), remembering that we define the flow via a Taylor expansion in the “odd time”. Expanding this out we get

\( x^{A}(\tau_{1}, \tau_{2}) = x^{A} + \tau_{1}\psi_{1}^{A} + \tau_{2}\psi_{2}^{A} + \tau_{1} \tau_{2}X^{A}\).

Now we examine the flow equations with respect to each “odd time”. We do not assume any conditions on the odd vector fields \(Q_{1}\) and \(Q_{2}\) at this stage.

\(\frac{\partial x^{A}}{\partial \tau_{1}} = \psi_{1}^{A} + \tau_{2}X^{A} = Q_{1}^{A}(x(\tau_{1}, \tau_{2}))\)
\(= Q_{1}^{A}(x) + \tau_{1}\psi^{B}_{1} \frac{\partial Q^{A}_{1}(x)}{\partial x^{B}} + \tau_{2}\psi^{B}_{2} \frac{\partial Q^{A}_{1}(x)}{\partial x^{B}} + \tau_{1}\tau_{2}X^{B} \frac{\partial Q^{A}_{1}(x)}{\partial x^{B}}\),

and
\(\frac{\partial x^{A}}{\partial \tau_{2}} = \psi_{2}^{A} {-} \tau_{1}X^{A} = Q_{2}^{A}(x(\tau_{1}, \tau_{2}))\)
\(= Q_{2}^{A}(x) + \tau_{1}\psi^{B}_{1} \frac{\partial Q^{A}_{2}(x)}{\partial x^{B}} + \tau_{2}\psi^{B}_{2} \frac{\partial Q^{A}_{2}(x)}{\partial x^{B}} + \tau_{1}\tau_{2}X^{B} \frac{\partial Q^{A}_{2}(x)}{\partial x^{B}}\).

Then equating coefficients in order of \(\tau_{1}\) and \(\tau_{2}\) we arrive at three types of equations

i) \(\psi_{1}^{A} = Q_{1}^{A}\), \(\psi^{B}_{1} \frac{\partial Q_{1}^{A}}{\partial x^{B}}=0\) and \(\psi_{2}^{A} = Q_{2}^{A}\), \(\psi^{B}_{2} \frac{\partial Q_{2}^{A}}{\partial x^{B}}=0\).

ii) \(X^{A} = \psi^{B}_{2} \frac{\partial Q_{1}^{A}}{\partial x^{B}}\) and \(X^{A} = {-}\psi^{B}_{1} \frac{\partial Q_{2}^{A}}{\partial x^{B}}\).

iii) \(X^{B} \frac{\partial Q_{1}^{A}}{\partial x^{B}} =0\) and \(X^{B} \frac{\partial Q_{2}^{A}}{\partial x^{B}} =0\).

It is now easy to see that;

i) implies that \([Q_{1}, Q_{1}] =0 \) and \([Q_{2}, Q_{2}] =0 \) meaning we have a pair of homological vector fields.

ii) implies that \([Q_{1}, Q_{2}]=0\), that is they are mutually commuting, or in other words compatible.

iii) is rather redundant and follows from the first two conditions.

Thus our geometric interpretation was right.

References
[1] Janusz Grabowski and Mikolaj Rotkiewicz, Higher vector bundles and multi-graded symplectic manifolds, J. Geom. Phys. 59(2009), 1285-1305.

[2]Rajan Amit Mehta, Q-algebroids and their cohomology, Journal of Symplectic Geometry 7 (2009), no. 3, 263-293.

[3] Theodore Th. Voronov, Q-Manifolds and Mackenzie Theory, Commun. Math. Phys. 2012; 315:279-310.

Odd curves and homological vector fields

On a supermanifold one has not just even vector fields but also odd vector fields. Importantly, the Lie bracket of an odd vector field with itself does not automatically vanish.

This is in stark contrast to the even vector fields on a supermanifold and indeed all vector fields on a classical manifold. Odd vector fields that self-commute under Lie bracket are known as homological vector fields and a supermanifold equipped with such a vector field is known as a Q-manifold.

In the literature one is often interested in homological vector fields from an algebraic perspective. Indeed, the nomenclature “homological” refers to the fact that on a Q-manifold one has a cochain complex on the algebra of functions on the supermanifold. You should have in mind the de Rham differential and the differential forms on a manifold in mind here.

In fact, if we think of differential forms as functions on the supermanifold \(\Pi TM\), then the pair \((\Pi TM, d)\) is a Q-manifold.

But can we understand the geometric meaning of a homological vector field?

Odd curves and maps between supermanifolds
Consider a map \(\gamma : \mathbb{R}^{0|1} \longrightarrow M\), for any supermanifold \(M\). We need to be a little careful here as we take $latex\gamma \in \underline{Map}(\mathbb{R}^{0|1}, M)$, that is we include odd maps here. Informally, we will use odd parameters at our free disposal. More formally, we need the inner homs, which requires the use of the functor of points, but we will skip all that.

Let us employ local coordinates $latex(x^{A})$ on \(M\) and \(\tau \) on \(\mathbb{R}^{0|1}\). Then

\(\gamma^{*}(x^{A}) = x^{A}(\tau) = x^{A} + \tau \; \; v^{A}\),

where $latex\widetilde{v^{A}} = \widetilde{A}+1$. This is why we need to include odd variables in our description. Note that as \(\tau\) is odd, functions of this variable can be at most linear.

Aside One can now show that \(\Pi TM = \underline{Map}(\mathbb{R}^{0|1}, M)\). Basically we have local coordinates \((x^{A}, v^{A})\) noting the shift in parity of the second factor. One can show we have the right transformation rules here directly.

Odd Flows
Now consider the flow on odd vector field, that is the differential equation

\(\frac{d x^{A}(\tau)}{d \tau} = X^{A}(x(\tau)) \),

where in local coordinates \(X = X^{A}(x)\frac{\partial}{\partial x^{A}}\).

From our previous considerations the flow equation becomes

\(v^{A} = X^{A}(x) + \tau v^{B} \frac{\partial X^{A}}{\partial x^{B}}\).

Thus equating the coefficients in order of \(\tau\) shows that

\(X^{A}(x) = v^{A}\) and \(v^{B} \frac{\partial X^{A}}{\partial x^{B}}=0\).

Then we conclude that

\(X^{B} \frac{\partial X^{A}}{\partial x^{B}}=0\), which implies that \([X,X]=0\) and thus we have a homological vector field.

Conclusion
The homological condition is the necessary and sufficient condition for the integrability of an odd vector field. Note that in the classical case there are no integrability conditions on vector fields.

Leonhard Euler's birthday

Today, the 15th of April, is Euler’s birthday. Euler, a pioneer of modern mathematics, was born on April 15 1707, in Basel, Switzerland. His work introduced much of today’s modern notation. He worked on quite diverse areas such as mathematical analysis, geometry, number theory, graph theory and so on, as well as making massive impact in the world of physics in areas such as mechanics and optics.

euler
Portrait by Johann Georg Brucker (1756)

Links
Euler Biography (The MacTutor History of Mathematics archive)