300 research outputs found
Alternation-Trading Proofs, Linear Programming, and Lower Bounds
A fertile area of recent research has demonstrated concrete polynomial time
lower bounds for solving natural hard problems on restricted computational
models. Among these problems are Satisfiability, Vertex Cover, Hamilton Path,
Mod6-SAT, Majority-of-Majority-SAT, and Tautologies, to name a few. The proofs
of these lower bounds follow a certain proof-by-contradiction strategy that we
call alternation-trading. An important open problem is to determine how
powerful such proofs can possibly be.
We propose a methodology for studying these proofs that makes them amenable
to both formal analysis and automated theorem proving. We prove that the search
for better lower bounds can often be turned into a problem of solving a large
series of linear programming instances. Implementing a small-scale theorem
prover based on this result, we extract new human-readable time lower bounds
for several problems. This framework can also be used to prove concrete
limitations on the current techniques.Comment: To appear in STACS 2010, 12 page
Time-Space Lower Bounds for Simulating Proof Systems with Quantum and Randomized Verifiers
A line of work initiated by Fortnow in 1997 has proven model-independent
time-space lower bounds for the problem and related problems
within the polynomial-time hierarchy. For example, for the
problem, the state-of-the-art is that the problem cannot be solved by
random-access machines in time and space simultaneously for .
We extend this lower bound approach to the quantum and randomized domains.
Combining Grover's algorithm with components from time-space
lower bounds, we show that there are problems verifiable in time with
quantum Merlin-Arthur protocols that cannot be solved in time and
space simultaneously for , a
super-quadratic time lower bound. This result and the prior work on
can both be viewed as consequences of a more general formula for
time lower bounds against small-space algorithms, whose asymptotics we study in
full.
We also show lower bounds against randomized algorithms: there are problems
verifiable in time with (classical) Merlin-Arthur protocols that cannot
be solved in randomized time and space simultaneously for , improving a result of Diehl. For quantum Merlin-Arthur protocols, the
lower bound in this setting can be improved to .Comment: 38 pages, 5 figures. To appear in ITCS 202
Easiness Amplification and Uniform Circuit Lower Bounds
We present new consequences of the assumption that time-bounded algorithms can be "compressed" with non-uniform circuits. Our main contribution is an "easiness amplification" lemma for circuits. One instantiation of the lemma says: if n^{1+e}-time, tilde{O}(n)-space computations have n^{1+o(1)} size (non-uniform) circuits for some e > 0, then every problem solvable in polynomial time and tilde{O}(n) space has n^{1+o(1)} size (non-uniform) circuits as well. This amplification has several consequences:
* An easy problem without small LOGSPACE-uniform circuits. For all e > 0, we give a natural decision problem, General Circuit n^e-Composition, that is solvable in about n^{1+e} time, but we prove that polynomial-time and logarithmic-space preprocessing cannot produce n^{1+o(1)}-size circuits for the problem. This shows that there are problems solvable in n^{1+e} time which are not in LOGSPACE-uniform n^{1+o(1)} size, the first result of its kind. We show that our lower bound is non-relativizing, by exhibiting an oracle relative to which the result is false.
* Problems without low-depth LOGSPACE-uniform circuits. For all e > 0, 1 < d < 2, and e < d we give another natural circuit composition problem computable in tilde{O}(n^{1+e}) time, or in O((log n)^d) space (though not necessarily simultaneously) that we prove does not have SPACE[(log n)^e]-uniform circuits of tilde{O}(n) size and O((log n)^e) depth. We also show SAT does not have circuits of tilde{O}(n) size and log^{2-o(1)}(n) depth that can be constructed in log^{2-o(1)}(n) space.
* A strong circuit complexity amplification. For every e > 0, we give a natural circuit composition problem and show that if it has tilde{O}(n)-size circuits (uniform or not), then every problem solvable in 2^{O(n)} time and 2^{O(sqrt{n log n})} space (simultaneously) has 2^{O(sqrt{n log n})}-size circuits (uniform or not). We also show the same consequence holds assuming SAT has tilde{O}(n)-size circuits. As a corollary, if n^{1.1} time computations (or O(n) nondeterministic time computations) have tilde{O}(n)-size circuits, then all problems in exponential time and subexponential space (such as quantified Boolean formulas) have significantly subexponential-size circuits. This is a new connection between the relative circuit complexities of easy and hard problems
Classical and quantum Merlin-Arthur automata
We introduce Merlin-Arthur (MA) automata as Merlin provides a single
certificate and it is scanned by Arthur before reading the input. We define
Merlin-Arthur deterministic, probabilistic, and quantum finite state automata
(resp., MA-DFAs, MA-PFAs, MA-QFAs) and postselecting MA-PFAs and MA-QFAs
(resp., MA-PostPFA and MA-PostQFA). We obtain several results using different
certificate lengths.
We show that MA-DFAs use constant length certificates, and they are
equivalent to multi-entry DFAs. Thus, they recognize all and only regular
languages but can be exponential and polynomial state efficient over binary and
unary languages, respectively. With sublinear length certificates, MA-PFAs can
recognize several nonstochastic unary languages with cutpoint 1/2. With linear
length certificates, MA-PostPFAs recognize the same nonstochastic unary
languages with bounded error. With arbitrarily long certificates, bounded-error
MA-PostPFAs verify every unary decidable language. With sublinear length
certificates, bounded-error MA-PostQFAs verify several nonstochastic unary
languages. With linear length certificates, they can verify every unary
language and some NP-complete binary languages. With exponential length
certificates, they can verify every binary language.Comment: 14 page
Efficient holographic proofs
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1996.Includes bibliographical references (p. 57-63).by Alexander Craig Russell.Ph.D
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