738 research outputs found
On product, generic and random generic quantum satisfiability
We report a cluster of results on k-QSAT, the problem of quantum
satisfiability for k-qubit projectors which generalizes classical
satisfiability with k-bit clauses to the quantum setting. First we define the
NP-complete problem of product satisfiability and give a geometrical criterion
for deciding when a QSAT interaction graph is product satisfiable with positive
probability. We show that the same criterion suffices to establish quantum
satisfiability for all projectors. Second, we apply these results to the random
graph ensemble with generic projectors and obtain improved lower bounds on the
location of the SAT--unSAT transition. Third, we present numerical results on
random, generic satisfiability which provide estimates for the location of the
transition for k=3 and k=4 and mild evidence for the existence of a phase which
is satisfiable by entangled states alone.Comment: 9 pages, 5 figures, 1 table. Updated to more closely match published
version. New proof in appendi
Algorithms and lower bounds for de Morgan formulas of low-communication leaf gates
The class consists of Boolean functions
computable by size- de Morgan formulas whose leaves are any Boolean
functions from a class . We give lower bounds and (SAT, Learning,
and PRG) algorithms for , for classes
of functions with low communication complexity. Let
be the maximum -party NOF randomized communication
complexity of . We show:
(1) The Generalized Inner Product function cannot be computed in
on more than fraction of inputs
for As a corollary, we get an average-case lower bound for
against .
(2) There is a PRG of seed length that -fools . For
, we get the better seed length . This gives the first
non-trivial PRG (with seed length ) for intersections of half-spaces
in the regime where .
(3) There is a randomized -time SAT algorithm for , where In particular, this implies a nontrivial
#SAT algorithm for .
(4) The Minimum Circuit Size Problem is not in .
On the algorithmic side, we show that can be
PAC-learned in time
Quantum adiabatic optimization and combinatorial landscapes
In this paper we analyze the performance of the Quantum Adiabatic Evolution
algorithm on a variant of Satisfiability problem for an ensemble of random
graphs parametrized by the ratio of clauses to variables, . We
introduce a set of macroscopic parameters (landscapes) and put forward an
ansatz of universality for random bit flips. We then formulate the problem of
finding the smallest eigenvalue and the excitation gap as a statistical
mechanics problem. We use the so-called annealing approximation with a
refinement that a finite set of macroscopic variables (versus only energy) is
used, and are able to show the existence of a dynamic threshold
starting with some value of K -- the number of variables in
each clause. Beyond dynamic threshold, the algorithm should take exponentially
long time to find a solution. We compare the results for extended and
simplified sets of landscapes and provide numerical evidence in support of our
universality ansatz. We have been able to map the ensemble of random graphs
onto another ensemble with fluctuations significantly reduced. This enabled us
to obtain tight upper bounds on satisfiability transition and to recompute the
dynamical transition using the extended set of landscapes.Comment: 41 pages, 10 figures; added a paragraph on paper's organization to
the introduction, fixed reference
A Quantum Lovasz Local Lemma
The Lovasz Local Lemma (LLL) is a powerful tool in probability theory to show
the existence of combinatorial objects meeting a prescribed collection of
"weakly dependent" criteria. We show that the LLL extends to a much more
general geometric setting, where events are replaced with subspaces and
probability is replaced with relative dimension, which allows to lower bound
the dimension of the intersection of vector spaces under certain independence
conditions. Our result immediately applies to the k-QSAT problem: For instance
we show that any collection of rank 1 projectors with the property that each
qubit appears in at most of them, has a joint satisfiable
state.
We then apply our results to the recently studied model of random k-QSAT.
Recent works have shown that the satisfiable region extends up to a density of
1 in the large k limit, where the density is the ratio of projectors to qubits.
Using a hybrid approach building on work by Laumann et al. we greatly extend
the known satisfiable region for random k-QSAT to a density of
. Since our tool allows us to show the existence of joint
satisfying states without the need to construct them, we are able to penetrate
into regions where the satisfying states are conjectured to be entangled,
avoiding the need to construct them, which has limited previous approaches to
product states.Comment: 19 page
Adiabatic Quantum Computing for Random Satisfiability Problems
The discrete formulation of adiabatic quantum computing is compared with
other search methods, classical and quantum, for random satisfiability (SAT)
problems. With the number of steps growing only as the cube of the number of
variables, the adiabatic method gives solution probabilities close to 1 for
problem sizes feasible to evaluate via simulation on current computers.
However, for these sizes the minimum energy gaps of most instances are fairly
large, so the good performance scaling seen for small problems may not reflect
asymptotic behavior where costs are dominated by tiny gaps. Moreover, the
resulting search costs are much higher than for other methods. Variants of the
quantum algorithm that do not match the adiabatic limit give lower costs, on
average, and slower growth than the conventional GSAT heuristic method.Comment: added discussion of discrete adiabatic method, and simulations with
30 bits 8 pages, 8 figure
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