Planning assistance for the 30/20 GHz program, volume 3

The three basic experiment categories and consolidated experiments proposed by members of the Carrier Working Group are defined by category and by carrier. The three experiment categories are: (1) Possible Service (PS); (2) Possible Service and Technology (PSAT); and (3) Possible Technology (PT). Under Task 9 Western Union provided review, recommendations and critique of the NASA generated Statement of Work (SOW) defining the technical requirements governing design, launch and operation of the 30/20 GHz experimental systems

Planning assistance for the 30/20 GHz program, volume 1

Functional requirements for the 30/20 GHz communication system, planning assistance for the 30/20 GHz program, and a review of specified conceptual designs and recommendations are provided

Experimental demonstration of a graph state quantum error-correction code

Scalable quantum computing and communication requires the protection of quantum information from the detrimental effects of decoherence and noise. Previous work tackling this problem has relied on the original circuit model for quantum computing. However, recently a family of entangled resources known as graph states has emerged as a versatile alternative for protecting quantum information. Depending on the graph's structure, errors can be detected and corrected in an efficient way using measurement-based techniques. In this article we report an experimental demonstration of error correction using a graph state code. We have used an all-optical setup to encode quantum information into photons representing a four-qubit graph state. We are able to reliably detect errors and correct against qubit loss. The graph we have realized is setup independent, thus it could be employed in other physical settings. Our results show that graph state codes are a promising approach for achieving scalable quantum information processing

Thermal Studies on Rubidium Dinitramide

The present study has been carried out to investigate conflicting reports in the literature on the nature of the thermal decomposition of the energetic oxidant rubidium dinitramide in the liquid state. The techniques employed included DSC, simultaneous TG-DTA, simultaneous TG-mass spectrometry and thermomicroscopy. The measurements were supplemented by quantitative chemical analysis of the reaction products. The results showed that, following fusion at 106 °C, the overall decomposition proceeded in a single exothermic reaction stage forming a mixture of rubidium nitrate and rubidium nitrite in the molar ratio 1.2 : 1

Survival of entanglement in thermal states

We present a general sufficiency condition for the presence of multipartite entanglement in thermal states stemming from the ground state entanglement. The condition is written in terms of the ground state entanglement and the partition function and it gives transition temperatures below which entanglement is guaranteed to survive. It is flexible and can be easily adapted to consider entanglement for different splittings, as well as be weakened to allow easier calculations by approximations. Examples where the condition is calculated are given. These examples allow us to characterize a minimum gapping behavior for the survival of entanglement in the thermodynamic limit. Further, the same technique can be used to find noise thresholds in the generation of useful resource states for one-way quantum computing.Comment: 6 pages, 2 figures. Changes made in line with publication recommendations. Motivation and concequences of result clarified, with the addition of one more example, which applies the result to give noise thresholds for measurement based quantum computing. New author added with new result

The self-assembly of DNA Holliday junctions studied with a minimal model

In this paper, we explore the feasibility of using coarse-grained models to simulate the self-assembly of DNA nanostructures. We introduce a simple model of DNA where each nucleotide is represented by two interaction sites corresponding to the phosphate-sugar backbone and the base. Using this model, we are able to simulate the self-assembly of both DNA duplexes and Holliday junctions from single-stranded DNA. We find that assembly is most successful in the temperature window below the melting temperatures of the target structure and above the melting temperature of misbonded aggregates. Furthermore, in the case of the Holliday junction, we show how a hierarchical assembly mechanism reduces the possibility of becoming trapped in misbonded configurations. The model is also able to reproduce the relative melting temperatures of different structures accurately, and allows strand displacement to occur.Comment: 13 pages, 14 figure

An Artificial Neural Network Approach to Learning from Factory Performance in a Kanban-Based System

Many Just-In-Time (JIT) manufacturing environments generate operational data reflecting both efficient and inefficient factory performance. Frequently data for inefficient performance is lost or discarded for fear of replicating poor performance. The purpose of this paper is two fold. First, historical JIT shop data is analyzed using a genetic algorithm (GA) to determine which shop factors are important determinants offactory performance. Second, subsequent to these important factors being identified by a GA, an artificial neural network (ANN) is used to learn the relationships between these factors and factory performance. The ANN can then be used to predict factory performance for future shop conditions and enhance shop performance. While ANN learning techniques have previously been applied to JIT production systems (Wray, Rakes, and Rees, 1997) (Markham, Mathieu, and Wray, 2000), these techniques have only been trained on data sets that reflect an efficient factory. Mathieu, Wray, and Markham (2002) investigated inefficient and efficient JIT factory performance but did not deploy either ANNs or a GA. In this paper an example application is presented using a GA to specify important shop factors and to predict saturated, starved or efficient factory performance based on dynamic shop floor data