On the number of spurious memories in the Hopfield model

The outer-product method for programming the Hopfield model is discussed. The method can result in many spurious stable states-exponential in the number of vectors that are to be stored-even in the case when the vectors are orthogonal

A Random Structure for Optimum Cache Size Distributed hash table (DHT) Peer-to-Peer design

We propose a new and easily-realizable distributed hash table (DHT) peer-to-peer structure, incorporating a random caching strategy that allows for {\em polylogarithmic search time} while having only a {\em constant cache} size. We also show that a very large class of deterministic caching strategies, which covers almost all previously proposed DHT systems, can not achieve polylog search time with constant cache size. In general, the new scheme is the first known DHT structure with the following highly-desired properties: (a) Random caching strategy with constant cache size; (b) Average search time of $O(log^{2}(N))$; (c) Guaranteed search time of $O(log^{3}(N))$; (d) Truly local cache dynamics with constant overhead for node deletions and additions; (e) Self-organization from any initial network state towards the desired structure; and (f) Allows a seamless means for various trade-offs, e.g., search speed or anonymity at the expense of larger cache size.Comment: 13 pages, 2 figures, preprint versio

Multiple Scale-Free Structures in Complex Ad-Hoc Networks

This paper develops a framework for analyzing and designing dynamic networks comprising different classes of nodes that coexist and interact in one shared environment. We consider {\em ad hoc} (i.e., nodes can leave the network unannounced, and no node has any global knowledge about the class identities of other nodes) {\em preferentially grown networks}, where different classes of nodes are characterized by different sets of local parameters used in the stochastic dynamics that all nodes in the network execute. We show that multiple scale-free structures, one within each class of nodes, and with tunable power-law exponents (as determined by the sets of parameters characterizing each class) emerge naturally in our model. Moreover, the coexistence of the scale-free structures of the different classes of nodes can be captured by succinct phase diagrams, which show a rich set of structures, including stable regions where different classes coexist in heavy-tailed and light-tailed states, and sharp phase transitions. Finally, we show how the dynamics formulated in this paper will serve as an essential part of {\em ad-hoc networking protocols}, which can lead to the formation of robust and efficiently searchable networks (including, the well-known Peer-To-Peer (P2P) networks) even under very dynamic conditions

Partial recovery of entanglement in bipartite entanglement transformations

Any deterministic bipartite entanglement transformation involving finite copies of pure states and carried out using local operations and classical communication (LOCC) results in a net loss of entanglement. We show that for almost all such transformations, partial recovery of lost entanglement is achievable by using $2 \times 2$ auxiliary entangled states, no matter how large the dimensions of the parent states are. For the rest of the special cases of deterministic LOCC transformations, we show that the dimension of the auxiliary entangled state depends on the presence of equalities in the majorization relations of the parent states. We show that genuine recovery is still possible using auxiliary states in dimensions less than that of the parent states for all patterns of majorization relations except only one special case.Comment: Significantly revised version; proofs have been completely rewritten to make them more accessible. To appear in Physical Review A [Rapid Communications