Affine projections of symmetric polynomials

We introduce a new model for computing polynomials-a depth 2 circuit with a symmetric gate at the top and plus gates at the bottom, i.e. the circuit computes a symmetric function in linear functions-S_m^d(l₁, l₂, …, l_m) (S_m^d is the d´th elementary symmetric polynomial in m variables, and the l_i´s are linear functions). We refer to this model as the symmetric model. This new model is related to standard models of arithmetic circuits, especially to depth 3 circuits. In particular we show that, in order to improve the results of Shpilka and Wigderson (1999), i.e. to prove super-quadratic lower bounds for depth 3 circuits, one must first prove a super-linear lower bound for the symmetric model. We prove two nontrivial linear lower bounds for our model. The first lower bound is for computing the determinant, and the second is for computing the sum of two monomials. The main technical contribution relates the maximal dimension of linear subspaces on which S_m^d vanishes, and lower bounds to the symmetric model. In particular we show that an answer of the following problem (which is very natural, and of independent interest) will imply lower bounds on symmetric circuits for many polynomials: “what is the maximal dimension of a linear subspace of C^m, on which S_m^d vanishes?” We give two partial solutions to the problem above, each enables us to prove a different lower bound