16,354 research outputs found
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
Iterated multiplication in
We show that , the basic theory of bounded arithmetic corresponding to
the complexity class , proves the axiom expressing the
totality of iterated multiplication satisfying its recursive definition, by
formalizing a suitable version of the iterated multiplication
algorithm by Hesse, Allender, and Barrington. As a consequence, can
also prove the integer division axiom, and (by results of Je\v{r}\'abek) the
RSUV-translation of induction and minimization for sharply bounded formulas.
Similar consequences hold for the related theories - and
.
As a side result, we also prove that there is a well-behaved
definition of modular powering in .Comment: 57 page
On the construction of elliptic Chudnovsky-type algorithms for multiplication in large extensions of finite fields
International audienceWe indicate a strategy in order to construct bilinear multiplication algorithms of type Chudnovsky in large extensions of any finite field. In particular, using the symmetric version of the generalization of Randriambololona specialized on the elliptic curves, we show that it is possible to construct such algorithms with low bilinear complexity. More precisely, if we only consider the Chudnovsky-type algorithms of type symmetric elliptic, we show that the symmetric bilinear complexity of these algorithms is in O(n(2q)^log * q (n)) where n corresponds to the extension degree, and log * q (n) is the iterated logarithm. Moreover, we show that the construction of such algorithms can be done in time polynomial in n. Finally, applying this method we present the effective construction, step by step, of such an algorithm of multiplication in the finite field F 3^57. Index Terms Multiplication algorithm, bilinear complexity, elliptic function field, interpolation on algebraic curve, finite field
Nondeterministic quantum communication complexity: the cyclic equality game and iterated matrix multiplication
We study nondeterministic multiparty quantum communication with a quantum
generalization of broadcasts. We show that, with number-in-hand classical
inputs, the communication complexity of a Boolean function in this
communication model equals the logarithm of the support rank of the
corresponding tensor, whereas the approximation complexity in this model equals
the logarithm of the border support rank. This characterisation allows us to
prove a log-rank conjecture posed by Villagra et al. for nondeterministic
multiparty quantum communication with message-passing.
The support rank characterization of the communication model connects quantum
communication complexity intimately to the theory of asymptotic entanglement
transformation and algebraic complexity theory. In this context, we introduce
the graphwise equality problem. For a cycle graph, the complexity of this
communication problem is closely related to the complexity of the computational
problem of multiplying matrices, or more precisely, it equals the logarithm of
the asymptotic support rank of the iterated matrix multiplication tensor. We
employ Strassen's laser method to show that asymptotically there exist
nontrivial protocols for every odd-player cyclic equality problem. We exhibit
an efficient protocol for the 5-player problem for small inputs, and we show
how Young flattenings yield nontrivial complexity lower bounds
Root finding with threshold circuits
We show that for any constant d, complex roots of degree d univariate
rational (or Gaussian rational) polynomials---given by a list of coefficients
in binary---can be computed to a given accuracy by a uniform TC^0 algorithm (a
uniform family of constant-depth polynomial-size threshold circuits). The basic
idea is to compute the inverse function of the polynomial by a power series. We
also discuss an application to the theory VTC^0 of bounded arithmetic.Comment: 19 pages, 1 figur
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