Oscillator Representation of the BCFT Construction of D-branes in Vacuum String Field Theory

Starting from the boundary CFT definition for the D-branes in vacuum string field theory (VSFT) given in hep-th/0105168, we derive the oscillator expression for the D24-brane solution in the VSFT on D25-brane. We show that the state takes the form of a squeezed state, similar to the one found directly in terms of the oscillators and reported in hep-th/0102112. Both the solutions are actually one parameter families of solutions. We also find numerical evidence that at least for moderately large values of the parameter $(b)$ in the oscillator construction the two families of solutions are same under a suitable redefinition of the parameter. Finally we generalize the method to computing the oscillator expression for a D-brane solution with constant gauge field strength turned on along the world volume.Comment: Latex, 43 pages, 3 figures, references adde

Quantum Query Complexity of Multilinear Identity Testing

Motivated by the quantum algorithm in \cite{MN05} for testing commutativity of black-box groups, we study the following problem: Given a black-box finite ring $R=\angle{r_1,...,r_k}$ where $\{r_1,r_2,...,r_k\}$ is an additive generating set for $R$ and a multilinear polynomial $f(x_1,...,x_m)$ over $R$ also accessed as a black-box function $f:R^m\to R$ (where we allow the indeterminates $x_1,...,x_m$ to be commuting or noncommuting), we study the problem of testing if $f$ is an \emph{identity} for the ring $R$. More precisely, the problem is to test if $f(a_1,a_2,...,a_m)=0$ for all $a_i\in R$. We give a quantum algorithm with query complexity $O(m(1+\alpha)^{m/2} k^{\frac{m}{m+1}})$ assuming $k\geq (1+1/\alpha)^{m+1}$. Towards a lower bound, we also discuss a reduction from a version of $m$-collision to this problem. We also observe a randomized test with query complexity $4^mmk$ and constant success probability and a deterministic test with $k^m$ query complexity.Comment: 12 page

Depth-4 Lower Bounds, Determinantal Complexity : A Unified Approach

Tavenas has recently proved that any n^{O(1)}-variate and degree n polynomial in VP can be computed by a depth-4 circuit of size 2^{O(\sqrt{n}\log n)}. So to prove VP not equal to VNP, it is sufficient to show that an explicit polynomial in VNP of degree n requires 2^{\omega(\sqrt{n}\log n)} size depth-4 circuits. Soon after Tavenas's result, for two different explicit polynomials, depth-4 circuit size lower bounds of 2^{\Omega(\sqrt{n}\log n)} have been proved Kayal et al. and Fournier et al. In particular, using combinatorial design Kayal et al.\ construct an explicit polynomial in VNP that requires depth-4 circuits of size 2^{\Omega(\sqrt{n}\log n)} and Fournier et al.\ show that iterated matrix multiplication polynomial (which is in VP) also requires 2^{\Omega(\sqrt{n}\log n)} size depth-4 circuits. In this paper, we identify a simple combinatorial property such that any polynomial f that satisfies the property would achieve similar circuit size lower bound for depth-4 circuits. In particular, it does not matter whether f is in VP or in VNP. As a result, we get a very simple unified lower bound analysis for the above mentioned polynomials. Another goal of this paper is to compare between our current knowledge of depth-4 circuit size lower bounds and determinantal complexity lower bounds. We prove the that the determinantal complexity of iterated matrix multiplication polynomial is \Omega(dn) where d is the number of matrices and n is the dimension of the matrices. So for d=n, we get that the iterated matrix multiplication polynomial achieves the current best known lower bounds in both fronts: depth-4 circuit size and determinantal complexity. To the best of our knowledge, a \Theta(n) bound for the determinantal complexity for the iterated matrix multiplication polynomial was known only for constant d>1 by Jansen.Comment: Extension of the previous uploa