  We prove that any non-adaptive algorithm that tests whether an unknown
Boolean function $f: \{0, 1\}^n\to \{0, 1\}$ is a $k$-junta or $\epsilon$-far
from every $k$-junta must make $\widetilde{\Omega}(k^{3/2} / \epsilon)$ many
queries for a wide range of parameters $k$ and $\epsilon$. Our result
dramatically improves previous lower bounds from [BGSMdW13, STW15], and is
essentially optimal given Blais's non-adaptive junta tester from [Blais08],
which makes $\widetilde{O}(k^{3/2})/\epsilon$ queries. Combined with the
adaptive tester of [Blais09] which makes $O(k\log k + k /\epsilon)$ queries,
our result shows that adaptivity enables polynomial savings in query complexity
for junta testing.
