Let $\{X_t\}_{t \in \mathbb{N}_0}$ be a discrete-time Markov chain with (countable) state space $\Omega$ and stationary distribution $\pi$.
Let $x,y \in \Omega$ and $P^t(x,y)$ be the probability of moving to state $y$ in $t$ time steps, given that we start at state $x$. The distance (using the total variation distance) between the distribution of the chain at time $t$ and the stationary distribution is given by $$d(t) = \max_{ x \in \Omega} ||P^t(x, \cdot)- \pi||_{TV},$$ where $$P^t(x,y):=\mathbb{P}(X_t=y \ | \ X_0=x).$$
Then, we define for $0< \varepsilon < 1$,
$$t_{mix}(\varepsilon) = \min\{t : d(t) \leq \varepsilon\}$$
and call it the mixing time of the Markov chain when $\varepsilon := \frac{1}{4}$.
My question is fairly simple, but I can't seem to find the answer anywhere:
Why is it used $\varepsilon:=\frac{1}{4}$? (and not $\varepsilon:=\frac{1}{5}$ for example)