4 research outputs found
Proofs of proximity for context-free languages and read-once branching programs
Proofs of proximity are probabilistic proof systems in which the verifier only queries a sub-linear number of input bits, and soundness only means that, with high probability, the input is close to an accepting input. In their minimal form, called Merlin-Arthur proofs of proximity ( MAP ), the verifier receives, in addition to query access to the input, also free access to an explicitly given short (sub-linear) proof. A more general notion is that of an interactive proof of proximity ( IPP ), in which the verifier is allowed to interact with an all-powerful, yet untrusted, prover. MAP s and IPP s may be thought of as the NP and IP analogues of property testing, respectively
Recommended from our members
Proofs of proximity for context-free languages and read-once branching programs
Proofs of proximity are proof systems wherein the verifier queries a sublinear number of bits, and soundness only asserts that inputs that are far from valid will be rejected. In their minimal form, called MA proofs of proximity (MAP), the verifier receives, in addition to query access to the input, also free access to a short (sublinear) proof. A more general notion is that of interactive proofs of proximity (IPP), wherein the verifier is allowed to interact with an omniscient, yet untrusted prover. We construct proofs of proximity for two natural classes of properties: (1) context-free languages, and (2) languages accepted by small read-once branching programs. Our main results are: 1. MAPs for these two classes, in which, for inputs of length n, both the verifier's query complexity and the length of the MAP proof are O˜(n).2. IPPs for the same two classes with constant query complexity, poly-logarithmic communication complexity, and logarithmically many rounds of interaction
Recommended from our members
Proofs of Proximity for Context-Free Languages and Read-Once Branching Programs (Extended Abstract)
Hamming Weight Proofs of Proximity with One-Sided Error
We provide a wide systematic study of proximity proofs with one-sided error for the Hamming weight problem (the language of bit vectors with Hamming weight at least ), surpassing previously known results for this problem. We demonstrate the usefulness of the one-sided error property in applications: no malicious party can frame an honest prover as cheating by presenting verifier randomness that leads to a rejection.
We show proofs of proximity for with one-sided error and sublinear proof length in three models (MA, PCP, IOP), where stronger models allow for smaller query complexity. For -bit input vectors, highlighting input query complexity, our MA has query complexity, the PCP makes queries, and the IOP makes a single input query. The prover in all of our applications runs in expected quasi-linear time. Additionally, we show that any perfectly complete IP of proximity for with input query complexity has proof length .
Furthermore, we study PCPs of proximity where the verifier is restricted to making a single input query (SIQ). We show that any SIQ-PCP for must have a linear proof length, and complement this by presenting a SIQ-PCP with proof length .
As an application, we provide new methods that transform PCPs (and IOPs) for arbitrary languages with nonzero completeness error into PCPs (and IOPs) that exhibit perfect completeness. These transformations achieve parameters previously unattained