I want to find the proof of the spectrum of the hypercube
How to find the spectrum of the hypercube?
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On
There is a proof here: http://www.cs.yale.edu/homes/spielman/eigs/lect12.ps
Or you can look up eigenvalues of Cartesian products and then follow Marion's hint.
On
This is not an independent answer but filling in what Mariano didn't bother to prove.
Start with Mariano's hint: $$A_{n+1}=\begin{pmatrix}A_{n}&I_{2^{n-1}}\\I_{2^{n-1}}&A_{n}\end{pmatrix}$$ Let $\chi_n(\lambda) = \det(\lambda I_{2^{n}} - A_{n+1})$ be the characteristic polynomial of the $n$-dim hypercube.
Notice for any $2m \times 2m$ matrix $X(A)$ of the form $\begin{pmatrix}A & I_m\\I_m & A\end{pmatrix}$. When $A$ is invertible, we have:
$$\begin{pmatrix}A & I_m\\I_m & A\end{pmatrix}\begin{pmatrix}I_m&-A^{-1}\\0&I_m\end{pmatrix} = \begin{pmatrix}A&0\\I_m&A-A^{-1}\end{pmatrix}$$ This implies $$\det X(A) = \det(A)\det(A - A^{-1}) = \det(A^2 - I_{2m}) = \det(A - I_{2m})\det(A + I_{2m})$$ Since both side of this identity are polynomials in entries of $A$, this identity is true even when $A$ is not invertible.
Apply this to $A_{n+1} - \lambda I_{2^n}$, we immediately obtain:
$$\chi_n(\lambda) = \chi_{n-1}(\lambda+1)\chi_{n-1}(\lambda-1)$$ So if the roots for the $(n-1)$-dim hypercube are n-1, n-3, ..., -(n-1) with multiplicities $$\binom{n-1}{0}, \binom{n-1}{1}, \binom{n-1}{2}, \ldots$$ then the roots for the $n$-dim hypercube are n = (n-1)+1, n-2 = (n-3)+1 = (n-1)-1, ... , -n with multiplicities $$1 = \binom{n}{0}, \binom{n}{1} = \binom{n-1}{0} + \binom{n-1}{1}, \binom{n}{2} = \binom{n-1}{1} + \binom{n-1}{2}, \ldots$$
This is just a data point:
Computing characteristic polynomials of their adjacency matrices, one finds the roots for the $d$-dimensional hypercube are $d$, $d-2$, $d-4$, $\dots$, $-d$, with multiplicities $\binom{d}{0}$, $\binom{d}{1}$, $\binom{d}{2}$, $\dots$, $\binom{d}{d}$.
Since this is extraordinarily regular, it suggests that one find a recursive formula. If $A_n$ is the adjacency matrix of hypercube on $2^{n-1}$ vertices, then $A_n=\begin{pmatrix}A_{n-1}&I_{2^{n-2}}\\I_{2^{n-2}}&A_{n-1}\end{pmatrix}$ so we have what to work with.