def METHOD_NAME(self):
    top_100_evecs = evecs[:, :100]
    top_100_evals = evals[:100] + 0.2 * torch.randn(100)
    precond_lt = RootLinearOperator(top_100_evecs @ torch.diag_embed(top_100_evals**0.5))
    logdet = top_100_evals.log().sum()
    def precond_closure(rhs):
        rhs2 = top_100_evecs.t() @ rhs
        return top_100_evecs @ torch.diag_embed(1.0 / top_100_evals) @ rhs2
    return precond_closure, precond_lt, logdet