# Affine dimension of a simplex determined by $k+1$ points

In Boyd and Vandenberghe's Convex Optimization, they say $k+1$ points $v_0,\dots, v_k\in\mathbb{R}^n$ are affinely independent if $v_1-v_0,\dots, v_k-v_0$ are linearly independent. They then go on to define the simplex defined by $v_0,\dots, v_k$ to be the convex hull of these points, i.e. the set $C$ given by $$C:=\operatorname{conv}\{v_0,\dots, v_k\} = \{\theta_0v_0+\cdots+ \theta_kv_k\mid \theta_i\ge 0\forall i, \sum_{i=1}^k \theta_i=1\}.$$

They claim that the affine dimension of $C$ is equal to $k$, that is the dimension of $V:=\operatorname{aff}(C)-x^*$, where $x^*\in \operatorname{aff}(C)$ is arbitrary. (Note that $V$ is a subspace of $\mathbb{R}^n$ and is independent of the choice of $x^*$.) I was trying to rigorously prove this by finding a basis of this subspace, but I was getting lost in the details.

Looking for help on the proof of this using just the information here (i.e, not using some alternative definition of a simplex, unless proven equivalent). Details would be appreciated! I am not sure if finding a basis is too difficult here or if there is a more clever solution. Note that $$\operatorname{aff}(C):=\{\gamma_0y_0+\cdots +\gamma_ly_l\mid y_0,\dots,y_l\in C,\gamma_0+\cdots\gamma_l=1\}\\ =\big\{(\gamma_0\theta_{00}+\cdots \gamma_l\theta_{l0})v_0+\cdots +(\gamma_0\theta_{0k}+\cdots \gamma_l\theta_{lk})v_k\mid \gamma_0+\cdots+\gamma_k=1, \\\theta_{ij}\ge 0\forall i,j, \sum_{j=0}^k \theta_{ij}=1\forall1\le i\le l\big\}.$$

For those interested, after thinking about it a little more, it's not too hard of a problem. One can easily show that $$\text{aff}C-v_0=\text{span}\{v_1-v_0,\dots,v_k-v_0\}$$ by some basic manipulation of the above definitions. Since $v_0,\dots, v_k$ are affinely independent, the result follows (since $v_0\in \text{aff}C$). I can put details if desired, but it's fairly elementary.
• It's equivalent to showing that $v_i-v_0$ for all $1 \leq i \leq k$ is a basis for $\mathbb{R}^k.$ – Vivek Kaushik May 20 '17 at 19:02
• @VivekKaushik these are vectors in $\mathbb{R}^{n}$, so this is obviously not true. – Satana May 20 '17 at 19:07
• You're right sorry. I didn't read the $v_i \in \mathbb{R}^n.$ I thought our space was $\mathbb{R}^k.$ – Vivek Kaushik May 20 '17 at 19:07