Computer & IT

A general rule in data processing is that disturbances cause the distortion or deletion of information during data storage or transfer. Methods for conventional computers were developed that automatically identify and correct errors: Data are processed several times and if errors occur, the most likely correct option is chosen. As quantum systems are even more sensitive to environmental disturbances than classical systems, a quantum computer requires a highly efficient algorithm for error correction.
The research group of Rainer Blatt from the Institute for Experimental Physics of the University of Innsbruck and the Institute for Quantum Optics and Quantum Information of the Austrian Academy of Sciences has now demonstrated such an algorithm experimentally. “The difficulty arises because quantum information cannot be copied,“ explains Schindler. “This means that we cannot save information repeatedly and then compare it.“ Therefore, the physicists use one of the peculiarities of quantum physics and use quantum mechanical entanglement to perform error correction.
The Innsbruck physicists demonstrate the mechanism by storing three calcium ions in an ion trap. All three particles are used as quantum bits (qubits), where one ion represents the system qubit and the other two ions auxiliary qubits. “First we entangle the system qubit with the other qubits, which transfers the quantum information to all three particles,” says Philipp Schindler. “Then a quantum algorithm determines whether an error occurs and if so, which one. Subsequently, the algorithm itself corrects the error.“ After having made the correction, the auxiliary qubits are reset using a laser beam. “This last point is the new element in our experiment, which enables repetitive error correction,“ says Rainer Blatt. “Some years ago, American colleagues demonstrated the general functioning of quantum error correction. Our new mechanism allows us to repeatedly and efficiently correct errors.“

Social Media Expert Explores Dynamics of Online Networking
Birds of a feather flock together in cyberspace. At least that's what Dr. Cuihua (Cindy) Shen, assistant professor of Emerging Media and Communication at University of Texas Dallas, has shown in a research article published in the journal First Monday.
Examining an online community using social network analysis, Shen tested the social drivers that shaped the collaboration dynamics among a group of users from SourceForge, the largest open source community on the Web.

Who Connects with Whom? A Social Network Analysis of an Online Open Source Software Community co-written by Peter Monge shows that users in online communities choose which users to interact with, and that their choices reveal the motivations and processes that create collective networks.

"Taken together, we found that accomplished developers tend to connect with other accomplished developers, essentially forming an elitist circle in the OSS (open source software) community. By contrast, it is more difficult for less successful developers to establish collaborative relations, and even if they do, they tend to connect with others who have a similar lower level of performance and experience," Shen writes in the article.

OSS refers to computer software products that permit users to study, change, improve and re-distribute the software. This process is different from the traditional and proprietary model of software development, and it allows developers to establish social relations by collaborating in software project teams.

"Developers who are working or have worked on the same project are linked to each other thereby creating collaboration networks," Shen said of OSS communities.

"By conceptualizing an online community as a network of participants and examining the formation of social ties, this research demonstrates that social network analysis can be a useful approach to studying the dynamics of online social systems."

Shen hopes the article will lead to new discoveries in her field: "Testing and comparing network formation mechanisms in online social networks across different domains will open new avenues for understanding the social and collaborative dynamics in contemporary networked media environments."


'Hanging' Computers Can Be Life Threatening

When your email program or word processor "hangs" it is annoying, you lose messages or have to reboot your computer and start that writing project again if you hadn't saved the text. But, we depending increasingly on computers in almost all walks of life, not least critical systems such as air-traffic control, in which the computer "hanging" can be life threatening.
Now, researchers at the Università degli Studi di Napoli Federico II and at Naples company SESM SCARL have developed a software tool that works at the operating system (OS) level and can detect when a computer program "hangs" and so allow a safe exit from any given system without crashing the computer as a whole and requiring a reboot of important systems. Writing in the International Journal of Critical Computer-Based Systems, SESM's Gabriella Carrozza explain their detection framework. The framework allows the non-intrusive monitoring of complex systems, based on multiple sources of data gathered at the OS level and the data collected data are then combined to reveal hang failures automatically.

Faults in software represent a major threat to the smooth running of sophisticated computer systems, according to Carrozza and colleagues. Testing and static code analysis are used widely to help detect and remove "bugs" in a system during development. However, once a software system is in place and being used in a real-world application, any number of problems can still occur, perhaps revealing bugs that were missed or simply triggered by memory overloads and timing errors. Such problems can cause just one critical component of the system to "hang" without crashing the whole system and without it being immediately obvious to operators or users of the system that there is a problem until it is too late.

Current software tools simply poll the health status of system components, or analyse system log files to uncover error messages and to correlate these with problematic memory or CPU component activity. However, they cannot spot "hangs" at the time they occur because the system might otherwise respond normally, but for the hanging failure.

The new approach taken by the Italian team relies on several simple monitors which exploit the OS support to trigger alarms when the behaviour of the system differs from the nominal one. "Our experimental results show that this framework increases the overall capacity of detecting hang failures, it exhibits a 100% coverage of observed failures, while keeping low the number of false positives, less than 6% in the worst case," the team says. Response time, or latency, between a hang occurring and it being detected is about 0.1 seconds on average, while the impact on computer performance of running the hang-detection software is, they add, negligible.