# Linear Algebra - Graph

## 3 - Minimum Spanning Forest

### 3.1 - Formulation

Formulating GF(2) vector: subset {Pembroke, Main, Gregorian} is represented by:

Pembroke Athletic Bio-Med Main Keeney Wriston Gregorian
1 1 1
• Edge Representation in term of vectors:
Edge Vector
Pembroke Athletic Bio-Med Main Keeney Wriston Gregorian
{Pembroke, Athletic} 1 1
{Pembroke, Bio-Med} 1 1
{Athletic, Bio-Med} 1 1
{Main, Keeney} 1 1
{Main, Wriston} 1 1
{Keeney, Wriston} 1 1
{Keeney, Gregorian} 1 1
{Wriston, Gregorian} 1 1
• The vector representing {Keeney, Gregorian} is the sum, for example, of the vectors representing {Keeney, Main }, {Main, Wriston}, and {Wriston, Gregorian}.
• A vector with 1’s in entries x and y is the sum of vectors corresponding to edges that form an x-to-y path in the graph. For instance, the span of the vectors representing {Pembroke, Bio-Med}, {Main, Wriston}, {Keeney, Wriston}, {Wriston, Gregorian }
• contains the vectors corresponding to
{Main, Keeney}, {Keeney, Gregorian}, and {Main, Gregorian}
• but not the vectors corresponding to
{Athletic, Bio-Med } or {Bio-Med, Main}

### 3.2 - Algorithm

def Grow(G)
S := 0;
consider the edges in increasing order
for each edge e:
if e’s endpoints are not yet connected
def Grow(V)
S = 0;
repeat while possible:
find a vector v in V not in Span S,
and put it in S.
• Considering edges e of G corresponds to considering vectors v in V
• Testing if e’s endpoints are not connected corresponds to testing if v is not in Span S.

The Grow algorithm for MSF is a specialization of the Grow algorithm for vectors. Same for the Shrink algorithms.

## 4 - Basis

One kind of basis in a graph G: a set S of edges forming a spanning forest.

• Spanning: for each edge xy in G, there is an x-to-y path consisting of edges of S.
• Independent: no cycle consisting of edges of S

A basis for a graph is a spanning forest. Unique Representation shows that, for each edge xy in the graph,

• there is an x-to-y path in the spanning forest, and
• there is only one such path.