  We map the problem of diffusion in the quenched trap model onto a new
stochastic process: Brownian motion which is terminated at the coverage "time"
${\cal S}_\alpha=\sum_{x=-\infty} ^\infty (n_x)^\alpha$ with $n_x$ being the
number of visits to site $x$. Here $0<\alpha=T/T_g<1$ is a measure of the
disorder in the original model. This mapping allows us to treat the intricate
correlations in the underlying random walk in the random environment. The
operational "time" ${\cal S}_\alpha$ is changed to laboratory time $t$ with a
L\'evy time transformation. Investigation of Brownian motion stopped at "time"
${\cal S}_\alpha$ yields the diffusion front of the quenched trap model which
is favorably compared with numerical simulations. In the zero temperature limit
of $\alpha\to 0$ we recover the renormalization group solution obtained by C.
Monthus. Our theory surmounts critical slowing down which is found when $\alpha
\to 1$. Above the critical dimension two mapping the problem to a continuous
time random walk becomes feasible though still not trivial.
