  We consider the related problems of estimating the $l_2$-norm and the squared
$l_2$-norm in sparse linear regression with unknown variance, as well as the
problem of testing the hypothesis that the regression parameter is null under
sparse alternatives with $l_2$ separation. We establish the minimax optimal
rates of estimation (respectively, testing) in these three problems.
