Technion – Israel Institute of Technology

About: Technion – Israel Institute of Technology is a education organization based out in Haifa, Israel. It is known for research contribution in the topics: Population & Upper and lower bounds. The organization has 31714 authors who have published 79377 publications receiving 2603976 citations. The organization is also known as: Technion Israel Institute of Technology & Ṭekhniyon, Makhon ṭekhnologi le-Yiśraʼel.

Zero-knowledge from secure multiparty computation

Abstract: We present a general construction of a zero-knowledge proof for an NP relation R(x,w) which only makes a black-box use of a secure protocol for a related multi-partyfunctionality f. The latter protocol is only required to be secure against a small number of "honest but curious" players. As an application, we can translate previous results on the efficiency of secure multiparty computation to the domain of zero-knowledge, improving over previous constructions of efficient zero-knowledge proofs. In particular, if verifying R on a witness of length m can be done by a circuit C of size s, and assuming one-way functions exist, we get the following types of zero-knowledge proof protocols.Approaching the witness length. If C has constant depth over ∧,∨,⊕, - gates of unbounded fan-in, we get a zero-knowledge protocol with communication complexity m·poly(k)·polylog(s), where k is a security parameter. Such a protocol can be implemented in either the standard interactive model or, following a trusted setup, in a non-interactive model."Constant-rate" zero-knowledge. For an arbitrary circuit C of size s and a bounded fan-in, we geta zero-knowledge protocol with communication complexity O(s)+poly(k). Thus, for large circuits, the ratio between the communication complexity and the circuit size approaches a constant. This improves over the O(ks) complexity of the best previous protocols.

Quantum Theory Needs No ‘Interpretation’

Abstract: Purpose of this article is to stress the fact that Quantum Theory does not need an interpretation other than being an algorithm for computing probabilities associated with macroscopic phenomena and measurements. It does not ''describ'' reality, and the wave function is not objective entity, it only gives the evolution of our probabilities for the outcomes potential experiments. (AIP) (c)

Uniform Uncertainty Principle for Bernoulli and Subgaussian Ensembles

Abstract: The paper considers random matrices with independent subgaussian columns and provides a new elementary proof of the Uniform Uncertainty Principle for such matrices. The Principle was introduced by Candes, Romberg and Tao in 2004; for subgaussian random matrices it was carlier proved by the present authors, as a consequence of a general result based on a generic chaining method of Talagrand. The present proof combines a simple measure concentration and a covering argument, which are standard tools of high-dimensional convexity.

Spanning-tree based coverage of continuous areas by a mobile robot

Abstract: The paper considers the problem of covering a continuous planar area by a square-shaped tool attached to a mobile robot. Using a tool-based approximation of the work-area, we present an algorithm that covers every point of the approximate area. The algorithm, called spanning tree covering (STC), subdivides the work-area into disjoint cells corresponding to the square-shaped tool, then follows a spanning tree of the graph induced by the cells, while covering every point precisely once. We present and analyze three versions of the STC algorithm. The first version is an off-line algorithm that computes an optimal covering path in linear time O(N), where N is the number of cells comprising the approximate area. The second version is an online or sensor based algorithm, that completes an optimal covering path in time O(N), but requires O(N) memory for its implementation. The third version of STC is "ant"-like, where the robot may leave pheromone-like markers during the coverage process. The ant-like STC algorithm runs in time O(N) and requires only O(1) memory. We present simulation results of the three STC algorithms, demonstrating their effectiveness in cases where the tool size is significantly smaller than the work-area characteristic dimension.