TITLE: Isomorphism between $E_8$ lattice and lattice defined by Extended Hamming Code
QUESTION [12 upvotes]: I have read that the following two lattices are isomorphic, and of course it seems believable, but it would be nice to have a sketch of how to construct the bijection.
Let $C$ be some extended $(8,4,4)$ Hamming Code. For example, let it be generated by:
$$G = \left(\begin{array}{cccc} 1 & 0 & 0 & 0 \\ 0 & 1 & 0 & 0 \\ 0 & 0 & 1 & 0 \\ 0 & 0 & 0 & 1 \\ 1 & 1 & 0 & 1 \\ 1 & 0 & 1 & 1 \\ 0 & 1 & 1 & 1 \\ {\bf 1} & {\bf 1} & {\bf 1} & {\bf 0}\end{array}\right)$$
Let $L$ be the lattice defined as containing all points in $\mathbb{Z}^8$ such that reduction modulo $2$ component-by-component ($\phi$) gives you a codeword, or in other words, $L = \{x \in \mathbb{Z}^8: \phi(x) \in C\}$.
It is well-known and pretty easy to show that the minimum norm is $2$. These minimum norm vectors of norm $2$ corresponding to weight $0$ codewords have a $\pm 2$ in one of the $8$ entries, so there are $2 \times 8 = 16$ of these. The vectors of norm $2$ corresponding to weight $4$ codewords have a $\pm 1$ in four digits. There are $14$ weight $4$ codewords, so there are $14 \times 2^4$ of these. Then there are $2^4 + 14 \times 2^4 = 15 \times 16 = 240$ vectors of minimum norm $2$.
Let $E$ by the $E_8$ lattice with the even construction so that the parity is even and all points are either all integral or all half-integral. By a similar argument, there are also $240$ vectors of minimum norm $\sqrt{2}$. But these look different. For example, any vectors with a $1$ in two of the eight positions has minimum norm $2$, and each of these you can permute the signs to give ${{8}\choose{2}} \times 4$ of them. Any half-integer vector of minimum norm $2$ must have all $\frac{1}{2}$ with an even number of positive (or negative) entries, so there are ${{8}\choose{2}} \times 4 + \left({{8}\choose{8}} + {{8}\choose{6}} + {{8}\choose{4}} + {{8}\choose{2}} + {{8}\choose{0}}\right) = 112 + 2^7 = 240$ total minimum norm $\sqrt{2}$.
My problem is that the vectors of minimum norm in $L$ and $E$ are totally different, even after rescaling. In $L$, there are vectors with $1$ and $4$ nonzero entries, while in $E$ there are vectors with $2$ and $8$ nonzero entries. Plus, the way that the minimum norm vectors are counted doesn't give a lot of insight. How do you get from $E$ to $L$ (and vice-versa)?

REPLY [15 votes]: Here's a recipe to identify any even unimodular lattice $L$ of rank $8$
with $E_8$.  To go in reverse, just use the inverse matrix.
I'll illustrate it with your $L$ (which must use the inner product
$(x,y) = \frac12 \sum_{i=1}^8 x_i y_i$ to give $E_8$).
Step 1: choose some vector of norm $4$ in $L$.  Write it as $2 e_8$
for some half-lattice unit vector $e_8$.  The choice doesn't matter
because all $2160$ vectors of this norm are equivalent under the
isometry group.  We can use $e_8 = \frac12(1,1,1,1,1,1,1,1)^t$
("t" for transpose since you're using column vectors).
Step 2: Any of the $240$ vectors $v$ of norm $2$ has inner product
$0$, $\pm 1$, or $\pm 2$ with $2 e_8$.  Each of the extreme values $\pm 2$
occurs only $14$ times, in $7$ pairs $\{v,e_8-v\}$ or $\{v,-e_8-v\}$
according to the choice of sign.  Choose one of each of the seven pairs
with inner product $+1$.  Subtract $e_8$ from each of these seven vectors
to get a half-lattice vector $e_i$ ($i=1,\ldots,7$) of norm $1$ orthogonal
to $e_8$.  The $i$th pair is then $e_8 \pm e_i$, so choosing the other
vector in each pair just changes $e_i$ to $-e_i$.  In our setting,
the fourteen $v$'s are 0,1 vectors coming from the fourteen
word of weight $4$ in $C$, with complementary words forming pairs.
Choose one from each pair, and obtain unit vectors
$e_i = \frac12(\pm1, \pm1, \pm1, \pm1, \pm1, \pm1, \pm1, \pm1)^t$,
each with four plus and four minus signs.
Step 3: At this point $L$ contains all the vectors $\pm e_i \pm e_j$.
I claim that the $e_i$ ($i=1,\ldots,7$) are orthogonal not just to $e_8$
but also to each other.  Indeed $(e_i,e_j) = (e_i+e_8, e_j+e_8) - 1$
is an integer, and cannot be $\pm 1$ unless $i = j$ because by Cauchy-Schwarz
$(e_i,e_j) = \pm 1$ implies $e_j = \pm e_i$.  So in our setting
the $\pm1$ matrix with columns $2e_1,\ldots,2e_8$ is a Hadamard matrix.
Step 4: We have found a sublattice of index 2 in $L$ consisting of
the even-sum linear combinations of the $e_i$ and thus isomorphic with $D_8$.
To recover $L$, we put in one of the two vectors
$\frac12(e_1 + e_2 + \cdots + e_7 \pm e_8)$ generating
the nontrivial even cosets of $D_8$ in its dual.
Try the plus sign, and check whether the resulting vector is in $L$.
If yes, we have our isomorphism with $E_8$.  If not, we get the isomorphism
by changing $e_8$ to $-e_8$.  For your lattice, the change-of-basis matrix
from $E_8$ to $L$ is $1/2$ times a Hadamard matrix $H$, so the inverse map is
$2H^{-1} = H^t/4$.  If I did this right, one choice for $H$ is
$$
\left(
\begin{array}{cccccccc}
+ & + & + & + & + & + & + & + \\
+ & + & + & - & - & - & - & + \\
+ & - & - & + & + & - & - & + \\
- & + & - & + & - & + & - & + \\
- & + & - & - & + & - & + & + \\
- & - & + & + & - & - & + & + \\
- & - & + & - & + & + & - & + \\
+ & - & - & - & - & + & + & +
\end{array}
\right) \ \; . 
$$
As a bonus we can counting the choices we've made along the way
to find (by taking $L$ to be $E_8$ itself) that $E_8$ has
$7! 2^6 2160 = 696729600$, which agrees with the known
size of the Weyl group $W(E_8)$.