  The results of Strassen and Raz show that good enough tensor rank lower
bounds have implications for algebraic circuit/formula lower bounds.
  We explore tensor rank lower and upper bounds, focusing on explicit tensors.
For odd d, we construct field-independent explicit 0/1 tensors T:[n]^d->F with
rank at least 2n^(floor(d/2))+n-Theta(d log n). This matches (over F_2) or
improves (all other fields) known lower bounds for d=3 and improves (over any
field) for odd d>3.
  We also explore a generalization of permutation matrices, which we denote
permutation tensors. We show, by counting, that there exists an order-3
permutation tensor with super-linear rank. We also explore a natural class of
permutation tensors, which we call group tensors. For any group G, we define
the group tensor T_G^d:G^d->F, by T_G^d(g_1,...,g_d)=1 iff g_1 x ... x g_d=1_G.
We give two upper bounds for the rank of these tensors. The first uses
representation theory and works over large fields F, showing (among other
things) that rank_F(T_G^d)<= |G|^(d/2). We also show that if this upper bound
is tight, then super-linear tensor rank lower bounds would follow. The second
upper bound uses interpolation and only works for abelian G, showing that over
any field F that rank_F(T_G^d)<= O(|G|^(1+log d)log^(d-1)|G|). In either case,
this shows that many permutation tensors have far from maximal rank, which is
very different from the matrix case and thus eliminates many natural candidates
for high tensor rank.
  We also explore monotone tensor rank. We give explicit 0/1 tensors T:[n]^d->F
that have tensor rank at most dn but have monotone tensor rank exactly n^(d-1).
This is a nearly optimal separation.
