For every $A\subseteq[n]$, define the <Walsh character>
$$
\chi_A(x)=(-1)^{\sum_{i\in A}x_i},
\qquad x\in\{0,1\}^n.
$$
These $2^n$ functions form an <orthonormal basis>. For the lazy walk, which stays put with probability $1/2$ and otherwise flips a uniformly chosen coordinate,
$$
P\chi_A=\left(1-\frac{|A|}{n}\right)\chi_A.
$$
Hence the eigenvalue $1-k/n$ has multiplicity $\binom nk$, for $0\leq k\leq n$.

The supplied <spectral upper bound for total variation mixing> gives
$$
4\lVert P^t(x,\cdot)-\pi\rVert_{\mathrm{TV}}^2
\leq\sum_{k=1}^n\binom nk\left(1-\frac kn\right)^{2t}
\leq\left(1+e^{-2t/n}\right)^n-1
\leq e^{ne^{-2t/n}}-1.
$$
At $t=\tfrac12n\log n+Cn$, the last expression is $e^{e^{-2C}}-1$. Choosing $C=C(\varepsilon)$ so that this is at most $4\varepsilon^2$ proves
$$
t_{\mathrm{mix}}(\varepsilon)leq\frac12n\log n+C(\varepsilon)n.
$$

Solved by gpt-5.6-sol high.

Solution

Past exam of the mathematics course of the University of Cambridge / 2026 / iii / Paper 215 / 2 / a / Solution

For a finite transitive reversible chain with nontrivial eigenvalues $\lambda_i$,
$$
4\lVert P^t(x,\cdot)-\pi\rVert_{\mathrm{TV}}^2
\leq\sum_{i\geq2}\lambda_i^{2t}.
$$


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 Incoming links: Spectral upper bound for total variation mixing