220 research outputs found
On solving systems of random linear disequations
An important subcase of the hidden subgroup problem is equivalent to the
shift problem over abelian groups. An efficient solution to the latter problem
would serve as a building block of quantum hidden subgroup algorithms over
solvable groups. The main idea of a promising approach to the shift problem is
reduction to solving systems of certain random disequations in finite abelian
groups. The random disequations are actually generalizations of linear
functions distributed nearly uniformly over those not containing a specific
group element in the kernel. In this paper we give an algorithm which finds the
solutions of a system of N random linear disequations in an abelian p-group A
in time polynomial in N, where N=(log|A|)^{O(q)}, and q is the exponent of A.Comment: 13 page
Efficient quantum algorithms for some instances of the non-Abelian hidden subgroup problem
In this paper we show that certain special cases of the hidden subgroup
problem can be solved in polynomial time by a quantum algorithm. These special
cases involve finding hidden normal subgroups of solvable groups and
permutation groups, finding hidden subgroups of groups with small commutator
subgroup and of groups admitting an elementary Abelian normal 2-subgroup of
small index or with cyclic factor group.Comment: 10 page
Deterministic Polynomial Time Algorithms for Matrix Completion Problems
We present new deterministic algorithms for several cases of the maximum rank
matrix completion problem (for short matrix completion), i.e. the problem of
assigning values to the variables in a given symbolic matrix as to maximize the
resulting matrix rank. Matrix completion belongs to the fundamental problems in
computational complexity with numerous important algorithmic applications,
among others, in computing dynamic transitive closures or multicast network
codings (Harvey et al SODA 2005, Harvey et al SODA 2006).
We design efficient deterministic algorithms for common generalizations of
the results of Lovasz and Geelen on this problem by allowing linear functions
in the entries of the input matrix such that the submatrices corresponding to
each variable have rank one. We present also a deterministic polynomial time
algorithm for finding the minimal number of generators of a given module
structure given by matrices. We establish further several hardness results
related to matrix algebras and modules. As a result we connect the classical
problem of polynomial identity testing with checking surjectivity (or
injectivity) between two given modules. One of the elements of our algorithm is
a construction of a greedy algorithm for finding a maximum rank element in the
more general setting of the problem. The proof methods used in this paper could
be also of independent interest.Comment: 14 pages, preliminar
On the black-box complexity of Sperner's Lemma
We present several results on the complexity of various forms of Sperner's
Lemma in the black-box model of computing. We give a deterministic algorithm
for Sperner problems over pseudo-manifolds of arbitrary dimension. The query
complexity of our algorithm is linear in the separation number of the skeleton
graph of the manifold and the size of its boundary. As a corollary we get an
deterministic query algorithm for the black-box version of the
problem {\bf 2D-SPERNER}, a well studied member of Papadimitriou's complexity
class PPAD. This upper bound matches the deterministic lower
bound of Crescenzi and Silvestri. The tightness of this bound was not known
before. In another result we prove for the same problem an
lower bound for its probabilistic, and an
lower bound for its quantum query complexity, showing
that all these measures are polynomially related.Comment: 16 pages with 1 figur
Hidden Translation and Translating Coset in Quantum Computing
We give efficient quantum algorithms for the problems of Hidden Translation
and Hidden Subgroup in a large class of non-abelian solvable groups including
solvable groups of constant exponent and of constant length derived series. Our
algorithms are recursive. For the base case, we solve efficiently Hidden
Translation in , whenever is a fixed prime. For the induction
step, we introduce the problem Translating Coset generalizing both Hidden
Translation and Hidden Subgroup, and prove a powerful self-reducibility result:
Translating Coset in a finite solvable group is reducible to instances of
Translating Coset in and , for appropriate normal subgroups of
. Our self-reducibility framework combined with Kuperberg's subexponential
quantum algorithm for solving Hidden Translation in any abelian group, leads to
subexponential quantum algorithms for Hidden Translation and Hidden Subgroup in
any solvable group.Comment: Journal version: change of title and several minor update
On Solving Systems of Diagonal Polynomial Equations Over Finite Fields
We present an algorithm to solve a system of diagonal polynomial equations
over finite fields when the number of variables is greater than some fixed
polynomial of the number of equations whose degree depends only on the degree
of the polynomial equations. Our algorithm works in time polynomial in the
number of equations and the logarithm of the size of the field, whenever the
degree of the polynomial equations is constant. As a consequence we design
polynomial time quantum algorithms for two algebraic hidden structure problems:
for the hidden subgroup problem in certain semidirect product p-groups of
constant nilpotency class, and for the multi-dimensional univariate hidden
polynomial graph problem when the degree of the polynomials is constant.Comment: A preliminary extended abstract of this paper has appeared in
Proceedings of FAW 2015, Springer LNCS vol. 9130, pp. 125-137 (2015
Finding hidden Borel subgroups of the general linear group
We present a quantum algorithm for solving the hidden subgroup problem in the
general linear group over a finite field where the hidden subgroup is promised
to be a conjugate of the group of the invertible lower triangular matrices. The
complexity of the algorithm is polynomial when size of the base field is not
much smaller than the degree.Comment: 12pt, 10 page
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