Quantum algorithms: A?survey of some recent results

Quantum algorithms are a field of growing interest within the theoretical computer science as well as the physics community. Surprisingly, although the number of researchers working on the subject is ever-increasing, the number of quantum algorithms found so far is quite small. In fact, the task of designing new quantum algorithms has been proven to be extremely difficult. In this paper we give an overview of the known quantum algorithms and briefly describe the underlying ideas. Roughly, the algorithms presented are divided into hidden subgroup type algorithms and in amplitude amplification type algorithms. While the former deal with problems of group-theoretical nature and have the promise to yield strong separations of classical and quantum algorithms, the latter have been proved to be a prolific source of algorithms in which a polynomial speed-up as compared to classical algorithms can be achieved. We also discuss quantum algorithms which do not fall under these two categories and give a survey of techniques of general interest in quantum computing such as adiabatic computing, lower bounds for quantum algorithms, and quantum interactive proofs.     

Meta-analysis: a tool for medical and scientific discoveries.

Medicine has made increasing use of meta-analysis, largely as a quantitative procedure for combining results of clinical trials. Meta-analysis begins with a comprehensive review of the literature. The next step is a systematic analysis of the quality and content of each study. Finally, results are combined statistically and conclusions are drawn from this new overview of the data. This paper presents a brief historical perspective on the use of meta-analysis in medicine with emphasis on the medical library. The authors conclude that in the future, medical librarians will play a significant role in the application of this useful technique.     

Chaos theory, informational needs, and natural disasters

This study applies chaos theory to a system-wide analysis of crisis communication in a natural disaster. Specifically, we analyze crisis communication during the 1997 Red River Valley flood in Minnesota and North Dakota. This flood, among the worst in modern American history, consumed entire metropolitan areas, displacing thousands of people. The conditions and decisions leading to the disaster, and the subsequent reactions are retraced. Communication related to river crest predictions (fractals), the shock at the magnitude of the crisis (cosmology episode), novel forms of reorganizing (self-organization), and agencies that aided in establishing a renewed order (strange attractors) are evaluated. Ultimately, we argue that preexisting sensemaking structures favoring rationalized, traditional views of a complex system led officials to make inappropriately unequivocal predictions and ultimately diminished the effectiveness of the region's crisis communication and planning.