488 research outputs found
Correlation in Hard Distributions in Communication Complexity
We study the effect that the amount of correlation in a bipartite
distribution has on the communication complexity of a problem under that
distribution. We introduce a new family of complexity measures that
interpolates between the two previously studied extreme cases: the (standard)
randomised communication complexity and the case of distributional complexity
under product distributions.
We give a tight characterisation of the randomised complexity of Disjointness
under distributions with mutual information , showing that it is
for all . This smoothly interpolates
between the lower bounds of Babai, Frankl and Simon for the product
distribution case (), and the bound of Razborov for the randomised case.
The upper bounds improve and generalise what was known for product
distributions, and imply that any tight bound for Disjointness needs
bits of mutual information in the corresponding distribution.
We study the same question in the distributional quantum setting, and show a
lower bound of , and an upper bound, matching up to a
logarithmic factor.
We show that there are total Boolean functions on inputs that have
distributional communication complexity under all distributions of
information up to , while the (interactive) distributional complexity
maximised over all distributions is for .
We show that in the setting of one-way communication under product
distributions, the dependence of communication cost on the allowed error
is multiplicative in -- the previous upper bounds
had the dependence of more than
Quantum Information Complexity and Amortized Communication
We define a new notion of information cost for quantum protocols, and a
corresponding notion of quantum information complexity for bipartite quantum
channels, and then investigate the properties of such quantities. These are the
fully quantum generalizations of the analogous quantities for bipartite
classical functions that have found many applications recently, in particular
for proving communication complexity lower bounds. Our definition is strongly
tied to the quantum state redistribution task.
Previous attempts have been made to define such a quantity for quantum
protocols, with particular applications in mind; our notion differs from these
in many respects. First, it directly provides a lower bound on the quantum
communication cost, independent of the number of rounds of the underlying
protocol. Secondly, we provide an operational interpretation for quantum
information complexity: we show that it is exactly equal to the amortized
quantum communication complexity of a bipartite channel on a given state. This
generalizes a result of Braverman and Rao to quantum protocols, and even
strengthens the classical result in a bounded round scenario. Also, this
provides an analogue of the Schumacher source compression theorem for
interactive quantum protocols, and answers a question raised by Braverman.
We also discuss some potential applications to quantum communication
complexity lower bounds by specializing our definition for classical functions
and inputs. Building on work of Jain, Radhakrishnan and Sen, we provide new
evidence suggesting that the bounded round quantum communication complexity of
the disjointness function is \Omega (n/M + M), for M-message protocols. This
would match the best known upper bound.Comment: v1, 38 pages, 1 figur
On the communication complexity of sparse set disjointness and exists-equal problems
In this paper we study the two player randomized communication complexity of
the sparse set disjointness and the exists-equal problems and give matching
lower and upper bounds (up to constant factors) for any number of rounds for
both of these problems. In the sparse set disjointness problem, each player
receives a k-subset of [m] and the goal is to determine whether the sets
intersect. For this problem, we give a protocol that communicates a total of
O(k\log^{(r)}k) bits over r rounds and errs with very small probability. Here
we can take r=\log^{*}k to obtain a O(k) total communication \log^{*}k-round
protocol with exponentially small error probability, improving on the O(k)-bits
O(\log k)-round constant error probability protocol of Hastad and Wigderson
from 1997.
In the exist-equal problem, the players receive vectors x,y\in [t]^n and the
goal is to determine whether there exists a coordinate i such that x_i=y_i.
Namely, the exists-equal problem is the OR of n equality problems. Observe that
exists-equal is an instance of sparse set disjointness with k=n, hence the
protocol above applies here as well, giving an O(n\log^{(r)}n) upper bound. Our
main technical contribution in this paper is a matching lower bound: we show
that when t=\Omega(n), any r-round randomized protocol for the exists-equal
problem with error probability at most 1/3 should have a message of size
\Omega(n\log^{(r)}n). Our lower bound holds even for super-constant r <=
\log^*n, showing that any O(n) bits exists-equal protocol should have \log^*n -
O(1) rounds
On The Communication Complexity of Linear Algebraic Problems in the Message Passing Model
We study the communication complexity of linear algebraic problems over
finite fields in the multi-player message passing model, proving a number of
tight lower bounds. Specifically, for a matrix which is distributed among a
number of players, we consider the problem of determining its rank, of
computing entries in its inverse, and of solving linear equations. We also
consider related problems such as computing the generalized inner product of
vectors held on different servers. We give a general framework for reducing
these multi-player problems to their two-player counterparts, showing that the
randomized -player communication complexity of these problems is at least
times the randomized two-player communication complexity. Provided the
problem has a certain amount of algebraic symmetry, which we formally define,
we can show the hardest input distribution is a symmetric distribution, and
therefore apply a recent multi-player lower bound technique of Phillips et al.
Further, we give new two-player lower bounds for a number of these problems. In
particular, our optimal lower bound for the two-player version of the matrix
rank problem resolves an open question of Sun and Wang.
A common feature of our lower bounds is that they apply even to the special
"threshold promise" versions of these problems, wherein the underlying
quantity, e.g., rank, is promised to be one of just two values, one on each
side of some critical threshold. These kinds of promise problems are
commonplace in the literature on data streaming as sources of hardness for
reductions giving space lower bounds
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