3,307 research outputs found
Size of Sets with Small Sensitivity: a Generalization of Simon's Lemma
We study the structure of sets with small sensitivity.
The well-known Simon's lemma says that any of
sensitivity must be of size at least . This result has been useful
for proving lower bounds on sensitivity of Boolean functions, with applications
to the theory of parallel computing and the "sensitivity vs. block sensitivity"
conjecture.
In this paper, we take a deeper look at the size of such sets and their
structure. We show an unexpected "gap theorem": if has
sensitivity , then we either have or . This is shown via classifying such sets into sets that can be
constructed from low-sensitivity subsets of for and
irreducible sets which cannot be constructed in such a way and then proving a
lower bound on the size of irreducible sets.
This provides new insights into the structure of low sensitivity subsets of
the Boolean hypercube
Certificate games
We introduce and study Certificate Game complexity, a measure of complexity
based on the probability of winning a game where two players are given inputs
with different function values and are asked to output such that (zero-communication setting).
We give upper and lower bounds for private coin, public coin, shared
entanglement and non-signaling strategies, and give some separations. We show
that complexity in the public coin model is upper bounded by Randomized query
and Certificate complexity. On the other hand, it is lower bounded by
fractional and randomized certificate complexity, making it a good candidate to
prove strong lower bounds on randomized query complexity. Complexity in the
private coin model is bounded from below by zero-error randomized query
complexity.
The quantum measure highlights an interesting and surprising difference
between classical and quantum query models. Whereas the public coin certificate
game complexity is bounded from above by randomized query complexity, the
quantum certificate game complexity can be quadratically larger than quantum
query complexity. We use non-signaling, a notion from quantum information, to
give a lower bound of on the quantum certificate game complexity of the
function, whose quantum query complexity is , then go on
to show that this ``non-signaling bottleneck'' applies to all functions with
high sensitivity, block sensitivity or fractional block sensitivity.
We consider the single-bit version of certificate games (inputs of the two
players have Hamming distance ). We prove that the single-bit version of
certificate game complexity with shared randomness is equal to sensitivity up
to constant factors, giving a new characterization of sensitivity. The
single-bit version with private randomness is equal to , where
is the spectral sensitivity.Comment: 43 pages, 1 figure, ITCS202
On the Sensitivity Complexity of k-Uniform Hypergraph Properties
In this paper we investigate the sensitivity complexity of hypergraph properties. We present a k-uniform hypergraph property with sensitivity complexity O(n^{ceil(k/3)}) for any k >= 3, where n is the number of vertices. Moreover, we can do better when k = 1 (mod 3) by presenting a k-uniform hypergraph property with sensitivity O(n^{ceil(k/3)-1/2}). This result disproves a conjecture of Babai, which conjectures that the sensitivity complexity of k-uniform hypergraph properties is at least Omega(n^{k/2}). We also investigate the sensitivity complexity of other weakly symmetric functions and show that for many classes of transitive-invariant Boolean functions the minimum achievable sensitivity complexity can be O(N^{1/3}), where N is the number of variables. Finally, we give a lower bound for sensitivity of k-uniform hypergraph properties, which implies the sensitivity conjecture of k-uniform hypergraph properties for any constant k
Separations in Query Complexity Based on Pointer Functions
In 1986, Saks and Wigderson conjectured that the largest separation between
deterministic and zero-error randomized query complexity for a total boolean
function is given by the function on bits defined by a complete
binary tree of NAND gates of depth , which achieves . We show this is false by giving an example of a total
boolean function on bits whose deterministic query complexity is
while its zero-error randomized query complexity is . We further show that the quantum query complexity of the same
function is , giving the first example of a total function
with a super-quadratic gap between its quantum and deterministic query
complexities.
We also construct a total boolean function on variables that has
zero-error randomized query complexity and bounded-error
randomized query complexity . This is the first
super-linear separation between these two complexity measures. The exact
quantum query complexity of the same function is .
These two functions show that the relations and are optimal, up to poly-logarithmic factors. Further
variations of these functions give additional separations between other query
complexity measures: a cubic separation between and , a -power
separation between and , and a 4th power separation between
approximate degree and bounded-error randomized query complexity.
All of these examples are variants of a function recently introduced by
\goos, Pitassi, and Watson which they used to separate the unambiguous
1-certificate complexity from deterministic query complexity and to resolve the
famous Clique versus Independent Set problem in communication complexity.Comment: 25 pages, 6 figures. Version 3 improves separation between Q_E and
R_0 and updates reference
- …