60 research outputs found
On Computing Multilinear Polynomials Using Multi-r-ic Depth Four Circuits
International audienceIn this paper, we are interested in understanding the complexity of computing multilinear polynomials using depth four circuits in which polynomial computed at every node has a bound on the individual degree of r (referred to as multi-r-ic circuits). The goal of this study is to make progress towards proving superpolynomial lower bounds for general depth four circuits computing multilinear polynomials, by proving better and better bounds as the value of r increases. Recently, Kayal, Saha and Tavenas (Theory of Computing, 2018) showed that any depth four arithmetic circuit of bounded individual degree r computing a multilinear polynomial on n^O(1) variables and degree d = o(n), must have size at least (n/r^1.1)^{\sqrt{d/r}} when r is o(d) and is strictly less than n^1/1.1. This bound however deteriorates with increasing r. It is a natural question to ask if we can prove a bound that does not deteriorate with increasing r or a bound that holds for a larger regime of r. We here prove a lower bound which does not deteriorate with r , however for a specific instance of d = d (n) but for a wider range of r. Formally, we show that there exists an explicit polynomial on n^{O(1)} variables and degree Θ(log^2(n)) such that any depth four circuit of bounded individual degree r < n^0.2 must have size at least exp(Ω (log^2 n)). This improvement is obtained by suitably adapting the complexity measure of Kayal et al. (Theory of Computing, 2018). This adaptation of the measure is inspired by the complexity measure used by Kayal et al. (SIAM J. Computing, 2017)
Balancing Bounded Treewidth Circuits
Algorithmic tools for graphs of small treewidth are used to address questions
in complexity theory. For both arithmetic and Boolean circuits, it is shown
that any circuit of size and treewidth can be
simulated by a circuit of width and size , where , if , and otherwise. For our main construction,
we prove that multiplicatively disjoint arithmetic circuits of size
and treewidth can be simulated by bounded fan-in arithmetic formulas of
depth . From this we derive the analogous statement for
syntactically multilinear arithmetic circuits, which strengthens a theorem of
Mahajan and Rao. As another application, we derive that constant width
arithmetic circuits of size can be balanced to depth ,
provided certain restrictions are made on the use of iterated multiplication.
Also from our main construction, we derive that Boolean bounded fan-in circuits
of size and treewidth can be simulated by bounded fan-in
formulas of depth . This strengthens in the non-uniform setting
the known inclusion that . Finally, we apply our
construction to show that {\sc reachability} for directed graphs of bounded
treewidth is in
Unbalancing Sets and an Almost Quadratic Lower Bound for Syntactically Multilinear Arithmetic Circuits
We prove a lower bound of Omega(n^2/log^2 n) on the size of any syntactically multilinear arithmetic circuit computing some explicit multilinear polynomial f(x_1, ..., x_n). Our approach expands and improves upon a result of Raz, Shpilka and Yehudayoff ([Ran Raz et al., 2008]), who proved a lower bound of Omega(n^{4/3}/log^2 n) for the same polynomial. Our improvement follows from an asymptotically optimal lower bound for a generalized version of Galvin\u27s problem in extremal set theory
Unbalancing Sets and An Almost Quadratic Lower Bound for Syntactically Multilinear Arithmetic Circuits
We prove a lower bound of Ω(n²/log²n) on the size of any syntactically multilinear arithmetic circuit computing some explicit multilinear polynomial f(x₁,...,x_n). Our approach expands and improves upon a result of Raz, Shpilka and Yehudayoff ([34]), who proved a lower bound of Ω(n^(4/3)/log²n) for the same polynomial. Our improvement follows from an asymptotically optimal lower bound for a generalized version of Galvin's problem in extremal set theory.
A special case of our combinatorial result implies, for every n, a tight Ω(n) lower bound on the minimum size of a family F of subsets of cardinality 2n of a set X of size 4n, so that any subset of X of size 2n has intersection of size exactly n with some member of F. This settles a problem of Galvin up to a constant factor, extending results of Frankl and Rödl [15] and Enomoto et al. [12], who proved in 1987 the above statement (with a tight constant) for odd values of n, leaving the even case open
Arithmetic circuits: the chasm at depth four gets wider
In their paper on the "chasm at depth four", Agrawal and Vinay have shown
that polynomials in m variables of degree O(m) which admit arithmetic circuits
of size 2^o(m) also admit arithmetic circuits of depth four and size 2^o(m).
This theorem shows that for problems such as arithmetic circuit lower bounds or
black-box derandomization of identity testing, the case of depth four circuits
is in a certain sense the general case. In this paper we show that smaller
depth four circuits can be obtained if we start from polynomial size arithmetic
circuits. For instance, we show that if the permanent of n*n matrices has
circuits of size polynomial in n, then it also has depth 4 circuits of size
n^O(sqrt(n)*log(n)). Our depth four circuits use integer constants of
polynomial size. These results have potential applications to lower bounds and
deterministic identity testing, in particular for sums of products of sparse
univariate polynomials. We also give an application to boolean circuit
complexity, and a simple (but suboptimal) reduction to polylogarithmic depth
for arithmetic circuits of polynomial size and polynomially bounded degree
Towards Optimal Depth Reductions for Syntactically Multilinear Circuits
We show that any -variate polynomial computable by a syntactically
multilinear circuit of size can be computed by a
depth- syntactically multilinear () circuit of size at
most . For degree , this improves upon the upper bound of
obtained by Tavenas~\cite{T15} for
general circuits, and is known to be asymptotically optimal in the exponent
when for a small enough constant . Our upper bound
matches the lower bound of proved by Raz and Yehudayoff~\cite{RY09}, and thus cannot be
improved further in the exponent. Our results hold over all fields and also
generalize to circuits of small individual degree.
More generally, we show that an -variate polynomial computable by a
syntactically multilinear circuit of size can be
computed by a syntactically multilinear circuit of product-depth of
size at most . It follows from the lower bounds of Raz and Yehudayoff (CC
2009) that in general, for constant , the exponent in this upper bound
is tight and cannot be improved to
A Near-Optimal Depth-Hierarchy Theorem for Small-Depth Multilinear Circuits
We study the size blow-up that is necessary to convert an algebraic circuit
of product-depth to one of product-depth in the multilinear
setting.
We show that for every positive
there is an explicit multilinear polynomial on variables
that can be computed by a multilinear formula of product-depth and
size , but not by any multilinear circuit of product-depth and
size less than . This result is tight up to the
constant implicit in the double exponent for all
This strengthens a result of Raz and Yehudayoff (Computational Complexity
2009) who prove a quasipolynomial separation for constant-depth multilinear
circuits, and a result of Kayal, Nair and Saha (STACS 2016) who give an
exponential separation in the case
Our separating examples may be viewed as algebraic analogues of variants of
the Graph Reachability problem studied by Chen, Oliveira, Servedio and Tan
(STOC 2016), who used them to prove lower bounds for constant-depth Boolean
circuits
- …