Extracting entangled qubits from Majorana fermions in quantum dot chains through the measurement of parity

We propose a scheme for extracting entangled charge qubits from quantum-dot chains that support zero-energy edge modes. The edge mode is composed of Majorana fermions localized at the ends of each chain. The qubit, logically encoded in double quantum dots, can be manipulated through tunneling and pairing interactions between them. The detailed form of the entangled state depends on both the parity measurement (an even or odd number) of the boundary-site electrons in each chain and the teleportation between the chains. The parity measurement is realized through the dispersive coupling of coherent-state microwave photons to the boundary sites, while the teleportation is performed via Bell measurements. Our scheme illustrates \emph{localizable entanglement} in a fermionic system, which serves feasibly as a quantum repeater under realistic experimental conditions, as it allows for finite temperature effect and is robust against disorders, decoherence and quasi-particle poisoning.Comment: Accepted by Scientific Report

Rootstock and seasonal variations affect anthocyanin accumulation and quality traits of ‘Kyoho’ grape berries in subtropical double cropping system

The double cropping system has been commercially adopted in subtropical viticulture regions. However, very limited information about rootstock and seasonal effects on berry quality traits are available for this unique production system. Developing ‘Kyoho’ berries from own-rooted vines and from vines on 5C and 1202C rootstocks were periodically sampled from veraison until harvest in two consecutive cropping cycles to document the potential seasonal influence on rootstock effects. Anthocyanin concentration in berry skin, total soluble solids content (TSS), and titratable acidity (TA) were analyzed. In both cropping cycles, own-rooted vines produced berries with the highest anthocyanin concentration while vines on 1202C produced berries with the lowest anthocyanin concentration among the three scion/rootstocks. Anthocyanin concentrations were not differentiated by the differential climate pattern between the summer and the winter cropping cycles. Berries of own-rooted ‘Kyoho’ and ‘Kyoho’/5C vines accumulated satisfactory and equal amount of TSS in both cropping cycles. 1202C rootstocks did not affect berry TSS in the summer cropping cycle but reduced TSS in the winter cropping cycle. Significant rootstock and seasonal effects on berry TA were detected. Own-rooted vines produced berries with the lowest TA while vines on 1202C produced berries with the highest TA among the three scion/rootstock combinations. TA of berries from the winter cropping cycle was significantly higher than that from the summer cropping cycle especially in ‘Kyoho’/1202C. Relationships between anthocyanins and TSS of developing berries after veraison properly fitted into a sigmoidal function regardless of rootstocks and cropping cycles. However, the duration of the initial lag phase, the onset and the trend of both quality triats in the increasing phase, and the presence and degree of the final lag phase in the relationship were all modulated by rootstocks and by seasonal variations.

Heterogeneous Graph Neural Networks for Fraud Detection and Explanation in Supply Chain Finance

It is a critical mission for financial service providers to discover fraudulent borrowers in a supply chain. The borrowers’ transactions in anongoing business are inspected to support the providers’ decision on whether to lend the money. Considering multiple participants in a supply chain business, the borrowers may use sophisticated tricks to cheat, making fraud detection challenging. In this work, we propose a multitask learning framework, MultiFraud, for complex fraud detection with reasonable explanation. The heterogeneous information from multi-view around the entities is leveraged in the detection framework based on heterogeneous graph neural networks. MultiFraud enables multiple domains to share embeddings and enhance modeling capabilities for fraud detection. The developed explainer provides comprehensive explanations across multiple graphs. Experimental results on five datasets demonstrate the framework’s effectiveness in fraud detection and explanation across domains

Performance of CMS ECAL Preshower in 2007 test beam

The Preshower detector is part of the CMS Electromagnetic Calorimeter, located in the endcap regions, in front of the lead tungstate crystals. It consist of two orthogonal planes of silicon strip sensors interleaved with two planes of lead absorbers. A combined beam test of close-to-final prototypes of the Hadron calorimeter, the crystal calorimeter and the Preshower detector was performed in the summer of 2007. Calibrations were made using electron and pion data. The combined crystal and Preshower energy resolution was studied using electrons. Good signal/noise performance was obtained in both sets of measurement

An Integrated Service-Oriented Development Platform for Realization of e-Business Systems

Enterprises need to be responsive to meet dynamic businesses and requirements. Service-oriented architecture can improve e-Business applications in integration and flexibility. Therefore, service-oriented architecture has been envisioned as an appropriate computational paradigm for e-business applications. This paper proposes a multi-model driven collaborative development platform for building service-oriented e-Business systems. The platform supports service-oriented software engineering and application developments. It employs three views, i.e., business view, process view, and service view to support business and technical consultants’ operations. Consultants can collaborate from distributed sites of, e.g., clients and IT vendors to provide their clients’ with rapid system development and demonstration. The proposed platform is service-oriented and driven by three models, i.e., service meta-model, process model and business model. All of these three models are supported by a semantic reasoning engine to facilitate intelligent service discovery, process execution and business-business integration. A simple example has been used to demonstrate its functionality