Correspondence between continuous-variable and discrete quantum systems of arbitrary dimensions

We establish a mapping between a continuous-variable (CV) quantum system and a discrete quantum system of arbitrary dimension. This opens up the general possibility to perform any quantum information task with a CV system as if it were a discrete system. The Einstein-Podolsky-Rosen state is mapped onto the maximally entangled state in any finite-dimensional Hilbert space and thus can be considered as a universal resource of entanglement. An explicit example of the map and a proposal for its experimental realization are discussed.

Quantum nonlocality test for continuous-variable states with dichotomic observables

There have been theoretical and experimental studies on quantum nonlocality for continuous variables, based on dichotomic observables. In particular, we are interested in two cases of dichotomic observables for the light field of continuous variables: One case is even and odd numbers of photons and the other case is no photon and the presence of photons. We analyze various observables to give the maximum violation of Bell's inequalities for continuous-variable states. We discuss an observable which gives the violation of Bell's inequality for any entangled pure continuous-variable state. However, it does not have to be a maximally entangled state to give the maximal violation of Bell's inequality. This is attributed to a generic problem of testing the quantum nonlocality of an infinite- dimensional state using a dichotomic observable.

Experimentally realizable characterizations of continuous- variable Gaussian states

Measures of entanglement, fidelity, and purity are basic yardsticks in quantum-information processing. We propose how to implement these measures using linear devices and homodyne detectors for continuous-variable Gaussian states. In particular, the test of entanglement becomes simple with some prior knowledge that is relevant to current experiments.

Accumulation of entanglement in a continuous variable memory

We study entanglement accumulation in a memory built out of two continuous variable systems interacting with a qubit that mediates their indirect coupling. We show that, in contrast with the case of bidimensional Hilbert spaces, entanglement superior to one ebit can be accumulated in the memory, even though no entangled resource is used. The protocol is immediately implementable and we assess the role of the main imperfections.

Enhanced surface attachment of protein-type targeting ligands to poly(lactide-co-glycolide) nanoparticles using variable expression of polymeric acid functionality

The density of reactive carboxyl groups on the surface of poly(lactide-co-glycolide) (PLGA) nanoparticles (NP) was modulated using a combination of high-molecular weight (MW) encapped and low MW non-encapped PLGA. Carboxyl groups were activated using carbodiimide chemistry and conjugated to bovine serum albumin and a model polyclonal antibody. Activation of carboxyl,groups in solution-phase PLGA prior to NP formation was compared with a postformation activation of peripheral carboxyl groups on intact NP. Activation before or after NP formation did not influence conjugation efficiency to NP prepared using 100% of the low-MW PLGA. The effect of steric stabilization using poly(vinyl alcohol) reduced conjugation of a polyclonal antibody from 62 mu g/(mg NP) to 32 mu g/(mg NP), but enhanced particulate stability. Increasing the amount of a high-MW PLGA also reduced Conjugation, with the activation post-formation still superior to the preformation approach. Drug release studies showed that high proportions of high-MW PLGA in the NP produced a longer sustained release profile of a model drug (celecoxib). It can be concluded that activating intact PLGA NP is superior to activating component parts prior to NP formation. Also, high MW PLGA could be used to prolong drug release, but at the expense of conjugation efficiency on to the NP surface. (C) 2008 Wiley Periodicals, Inc. J Biomed Mater Res 87A: 873-884, 2008

Surrogate-Based Optimization Using Multifidelity Models with Variable Parameterization and Corrected Space Mapping

Surrogate-based-optimization methods provide a means to achieve high-fidelity design optimization at reduced computational cost by using a high-fidelity model in combination with lower-fidelity models that are less expensive to evaluate. This paper presents a provably convergent trust-region model-management methodology for variableparameterization design models: that is, models for which the design parameters are defined over different spaces. Corrected space mapping is introduced as a method to map between the variable-parameterization design spaces. It is then used with a sequential-quadratic-programming-like trust-region method for two aerospace-related design optimization problems. Results for a wing design problem and a flapping-flight problem show that the method outperforms direct optimization in the high-fidelity space. On the wing design problem, the new method achieves 76% savings in high-fidelity function calls. On a bat-flight design problem, it achieves approximately 45% time savings, although it converges to a different local minimum than did the benchmark.