Algebraic synthesis of time-optimal unitaries in SU(2) with alternating controls

We present an algebraic framework to study the time-optimal synthesis of arbitrary unitaries in SU(2), when the control set is restricted to rotations around two non-parallel axes in the Bloch sphere. Our method bypasses commonly used control-theoretical techniques, and easily imposes necessary conditions on time-optimal sequences. In a straightforward fashion, we prove that time-optimal sequences are solely parametrized by three rotation angles and derive general bounds on those angles as a function of the relative rotation speed of each control and the angle between the axes. Results are substantially different whether both clockwise and counterclockwise rotations about the given axes are allowed, or only clockwise rotations. In the first case, we prove that any finite time-optimal sequence is composed at most of five control concatenations, while for the more restrictive case, we present scaling laws on the maximum length of any finite time-optimal sequence. The bounds we find for both cases are stricter than previously published ones and severely constrain the structure of time-optimal sequences, allowing for an efficient numerical search of the time-optimal solution. Our results can be used to find the time-optimal evolution of qubit systems under the action of the considered control set, and thus potentially increase the number of realizable unitaries before decoherence

Network service chaining with efficient network function mapping based on service decompositions

Network Service Chaining (NSC) is a service concept which promises increased flexibility and cost-efficiency for future carrier networks. The two recent developments, Network Function Virtualization (NFV) and Software-Defined Networking (SDN), are opportunities for service providers to simplify the service chaining and provisioning process and reduce the cost (in CAPEX and OPEX) while introducing new services as well. One of the challenging tasks regarding NFV-based services is to efficiently map them to the components of a physical network based on the services specifications/constraints. In this paper, we propose an efficient cost-effective algorithm to map NSCs composed of Network Functions (NF) to the network infrastructure while taking possible decompositions of NFs into account. NF decomposition refers to converting an abstract NF to more refined NFs interconnected in form of a graph with the same external interfaces as the higher-level NF. The proposed algorithm tries to minimize the cost of the mapping based on the NSCs requirements and infrastructure capabilities by making a reasonable selection of the NFs decompositions. Our experimental evaluations show that the proposed scheme increases the acceptance ratio significantly while decreasing the mapping cost in the long run, compared to schemes in which NF decompositions are selected randomly

Parallel Graph Decompositions Using Random Shifts

We show an improved parallel algorithm for decomposing an undirected unweighted graph into small diameter pieces with a small fraction of the edges in between. These decompositions form critical subroutines in a number of graph algorithms. Our algorithm builds upon the shifted shortest path approach introduced in [Blelloch, Gupta, Koutis, Miller, Peng, Tangwongsan, SPAA 2011]. By combining various stages of the previous algorithm, we obtain a significantly simpler algorithm with the same asymptotic guarantees as the best sequential algorithm

Degree of separability of bipartite quantum states

We investigate the problem of finding the optimal convex decomposition of a bipartite quantum state into a separable part and a positive remainder, in which the weight of the separable part is maximal. This weight is naturally identified with the degree of separability of the state. In a recent work, the problem was solved for two-qubit states using semidefinite programming. In this paper, we describe a procedure to obtain the optimal decomposition of a bipartite state of any finite dimension via a sequence of semidefinite relaxations. The sequence of decompositions thus obtained is shown to converge to the optimal one. This provides, for the first time, a systematic method to determine the so-called optimal Lewenstein-Sanpera decomposition of any bipartite state. Numerical results are provided to illustrate this procedure, and the special case of rank-2 states is also discussed.Comment: 11 pages, 7 figures, submitted to PR