Notes - Rings and Modules HT24, Presentations


Flashcards

Suppose $M$ is a finitely-generated $R$-module. What is a presentation of $M$?


Two homomorphisms $\phi : R^n \to M$ and $\psi : R^m \to R^n$ such that

\[\text{Im } \phi = M\]

(i.e. it’s surjective) and

\[\text{Im } \psi = \ker \phi\]

Suppose:

  • $M$ is a nonzero finitely generated $R$-module
  • $R$ is a PID

Quickly prove that there is then a presentation (actually a resolution) for $M$, i.e.

  • $\exists n \in \mathbb N$ such that there is a surjective homomorphism $\phi : R^n \to M$
  • There exists a free module $R^m$ with $m \le n$ and an injective homomorphism $\psi : R^m \to R^n$ such that $\text{Im } \psi = \ker \phi$. (The fact that $\psi$ is injective means it is it a resolution)

And in particular, these imply that

\[M \cong R^n/(\text{Im } \psi)\]

  • For the first part, consider the map $\phi : R^n \to M, e _ i \mapsto m _ i$ where $e _ i$ is a standard basis for $R^n$ and $m _ i$ is a collection of generators for $M$. Then this is a surjective homomorphism.
  • For the second part, since $R$ is a PID, the submoudle $\ker \phi$ is a free submodule of rank $n \le m$ (this is the general result that the submodules of a finitely generated free module over a PID have rank at most the rank of the big module). Hence we can pick a basis $\{x _ 1, \cdots, x _ m\}$ and define $\psi : R^m \to R^n$ by sending $x _ i \mapsto e _ i$. This is an injective homomorphism.

Suppose $A$ is an $n \times m$ presentation matrix for a module $M$, corresponding to the pair of maps

\[\begin{aligned} &\phi : R^n \to M \\\\ &\psi : R^m \to R^n \end{aligned}\]

where $\ker \phi = \text{Im } \psi$. Describe four ways that you can modify the presentation matrix so that it still presents the same module.


  • Can pre- or post- multiply by an invertible matrix, since this represents a change of basis in either $R^n$ or $R^m$ (in particular, this implies you can multiply rows by a unit).
  • Can remove a row of zeroes, since this corresponds to the trivial relation $0 = 0$, which is not neccessary.
  • If a row looks like some basis vector like $e _ i$, we can remove both the column and row $i$. This represents the relation $m _ i = 0$ for some member of the generating set $m _ i$, and so any relation in which is appears can be shortened.

Suppose $A$ is an $n \times m$ presentation matrix for a module $M$, corresponding to the pair of maps

\[\begin{aligned} &\phi : R^n \to M && \text{surjective hom.}\\\\ &\psi : R^m \to R^n && \text{injective hom.} \end{aligned}\]

where $\ker \phi = \text{Im } \psi$. If $\{e _ 1, \ldots, e _ n\}$ is a basis for $R^n$ and $\phi$ is defined so that $e _ i \mapsto m _ i$ for some generating set $\{m _ 1, \cdots, m _ n\}$, what does $\ker \phi$ concretely represent?


The “module of relations”, all the ways that the generators $m _ i$ can be combined to get $0$.

Suppose $A$ is an $n \times m$ presentation matrix for a module $M$, corresponding to the pair of maps

\[\begin{aligned} &\phi : R^n \to M && \text{surjective hom.}\\\\ &\psi : R^m \to R^n && \text{injective hom.} \end{aligned}\]

where $\ker \phi = \text{Im } \psi$. Let $\{e _ 1, \ldots, e _ n\}$ is a basis for $R^n$ and $\phi$ is defined so that $e _ i \mapsto m _ i$ for some generating set $\{m _ 1, \cdots, m _ n\}$. If the presentation matrix has a column $(\alpha _ 1, \alpha _ 2, \alpha _ 3)^\top$, what does this concretely represent?


The fact that

\[\alpha_1 m_1 + \alpha_2 m_2 + \alpha_3 m_3 = 0\]

Suppose we have a $\mathbb F[t]$-module $M$ where the action of $f(x) \in \mathbb F[t]$ corresponds to $f(A) v$. In order to do things like find the JNF or CNF, we need to find a presentation of $M$ in the form of a presentation matrix. How can this be done?


The module is generated by the basis vectors $e _ 1, \cdots, e _ n$. For each vector we have the relation that

\[xe_i - Ae_i = 0\]

which can be collected into the presentation matrix

\[xI - A\]

(For example…)

\[A = \begin{pmatrix}1 & -1 & 1 \\\\ 0 & 0 & 1 \\\\ 0 & 1 & 0\end{pmatrix}\]

has presentation matrix

\[xI - A = \begin{pmatrix}x-1 & 1 & -1 \\\\ 0 & x & -1 \\\\ 0 & -1 & x\end{pmatrix}\]

since, e.g. for the second column,

\[e_1 + x e_2 - e_3 = e_1 + Ae_2 - e_3 = e_1 - e_1 + e_3 - e_3 = 0\]



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