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The cut capacity of $(S,S^c)$, with $S^c=V\setminus S$ the complement of a set, isOnly outward directed edges contribute; incoming and internal edges contribute nothing.^[ref]

Here is the accounting behind the bound, using nonnegative original edge amounts $f_{uv}$ in a finite flow network. Sum the divergence of a flow over the vertices in $S$:An edge with both endpoints in $S$ appears once with a plus sign at its tail and once with a minus sign at its head, so those contributions cancel. An outward edge appears only with a plus sign; an incoming edge appears only with a minus sign. Since $s\in S$, $t\notin S$ and every other vertex satisfies flow conservation, the left side is the flow value. ThusThe inequality uses two facts separately: each forward flow is at most its flow network edge capacity, and each backward flow is nonnegative. This is the weak duality bound underlying the max-flow min-cut theorem. It is an accounting proof, requiring no choice of augmenting paths.

For $S=\{s,b\}$ in the running example, explicitly add the two divergences of a flow:The internal $s\to b$ edge cancels. The $a\to b$ edge is a genuine original directed edge entering $S$, so its flow is subtracted; this is different from a backward edge in a residual network. Its flow network edge capacity is neither added to nor subtracted from cut capacity, which remains $c_{sa}+c_{bt}=6$.

Equality in the bound holds precisely when every outward edge is saturated and every incoming edge carries zero flow, becauseand every term is nonnegative. For $S=\{s\}$ the two outward edges are saturated and there are no incoming edges, so the gap is zero. For $S=\{s,b\}$ all outward edges are still saturated, but the incoming flow of $1$ gives a gap of $1$. This explains exactly why the second cut of a flow network is not a minimum cut.

Flow conservation requires equal total inflow and outflow at every vertex other than the source and sink:Equivalently, the divergence of a flow is zero there.^[ref]

This is a steady accounting condition: an intermediate vertex neither creates the routed resource nor accumulates it. Splitting is allowed; equality between individual incoming and outgoing edges is not required. For the running flow, the equation at $a$ is $f_{sa}=f_{ab}+f_{at}$, or $3=1+2$, and at $b$ it is $f_{sb}+f_{ab}=f_{bt}$, or $2+1=3$.

Capacity constraints alone do not ensure flow conservation. For instance, changing only $f_{ab}$ from $1$ to $0$ keeps every edge amount within its flow network edge capacity, but leaves an excess inflow of $1$ at $a$ and an excess outflow of $1$ at $b$. It is therefore not a feasible flow. Changing all affected edge amounts together to $(f_{sa},f_{sb},f_{ab},f_{at},f_{bt})=(2,2,0,2,2)$ restores both equations and gives flow value $4$.

A minimum cut is a cut of a flow network of least cut capacity for the prescribed source $s$ and sink $t$. The max-flow min-cut theorem equates that least cut capacity with the greatest flow value.^[ref]

To certify a particular minimum cut, exhibit a feasible flow whose flow value equals its cut capacity. Every feasible flow is bounded above by every cut capacity, so this single equality proves both optimalities.^[ref]

In the running example, the four possible source sides $\{s\}$, $\{s,a\}$, $\{s,b\}$ and $\{s,a,b\}$ have cut capacities $5,5,6,5$, respectively. The feasible flow of flow value $5$ therefore certifies three different minimum cuts. A minimum cut need not be unique; the optimum cut capacity is the same for all of them. Merely saturating many edges does not give this certificate: flow conservation and the particular cut of a flow network must also be checked.