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Quantum State Reduction for Universal Measurement Based Computation

Physical Review Letters 2010年第2期105卷 020502-020502页

作者： Xie Chen Runyao Duan Zhengfeng Ji Bei Zeng Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts USA Centre for Quantum Computation and Intelligent Systems (QCIS) Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China Perimeter Institute for Theoretical Physics Waterloo Ontario Canada State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Institute for Quantum Computing University of Waterloo Waterloo Ontario Canada Department of Combinatorics and Optimization University of Waterloo Waterloo Ontario Canada

Measurement based quantum computation, which requires only single particle measurements on a universal resource state to achieve the full power of quantum computing, has been recognized as one of the most promising models for the physical realization of quantum computers. Despite considerable progress in the past decade, it remains a great challenge to search for new universal resource states with naturally occurring Hamiltonians and to better understand the entanglement structure of these kinds of states. Here we show that most of the resource states currently known can be reduced to the cluster state, the first known universal resource state, via adaptive local measurements at a constant cost. This new quantum state reduction scheme provides simpler proofs of universality of resource states and opens up plenty of space to the search of new resource states.

关键词： Quantum computers

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Multi-error-correcting amplitude damping codes

Multi-error-correcting amplitude damping codes

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IEEE International Symposium on Information Theory

作者： Runyao Duan Markus Grassl Zhengfeng Ji Bei Zeng State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China Centre for Quantum Computation and Intelligent Systems (QCIS) Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia Centre for Quantum Technologies National University of Singapore Singapore Perimeter Institute of Theoretical Physics Waterloo ONT Canada State Key Laboratory of Computer Science Institute of Software Chinese Academy and Sciences Beijing China Institute for Quantum Computing and the Department of Combinatorics and Optimization University of Waterloo Waterloo ONT Canada

ISBN: (纸本)9781424478903

We construct new families of multi-error-correcting quantum codes for the amplitude damping channel. Our key observation is that, with proper encoding, two uses of the amplitude damping channel simulate a quantum erasure channel. This allows us to use concatenated codes with quantum erasure-correcting codes as outer codes for correcting multiple amplitude damping errors. Our new codes are degenerate stabilizer codes and have parameters which are better than the amplitude damping codes obtained by any previously known construction.

关键词： Damping Quantum mechanics Quantum computing Error correction codes Noise level Laboratories Phase noise Physics computing Intelligent systems computer science

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Evolving coordinated spatial tactics for autonomous entities using influence maps

Evolving coordinated spatial tactics for autonomous entities...

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CIG2009 - 2009 IEEE Symposium on Computational Intelligence and Games

作者： Avery, Phillipa Louis, Sushil Avery, Benjamin Evolutionary Computing Systems Laboratory Dept. of Computer Science and Engineering University of Nevada Reno NV United States

ISBN: (纸本)9781424448159

We evolve tactical control for entity groups in a naval real-time strategy game. Since tactical maneuvering involves spatial reasoning, our evolutionary algorithm evolves a set of influence maps that help specify an entity's spatial objectives. The entity then uses the A* route finding algorithm to generate waypoints according to the influence map, and follows them to achieve spatial objectives. Using this representation, our evolutionary algorithm quickly evolves increasingly better capture-the-flag tactics on three increasingly difficult maps. These preliminary results indicate (1) the usefulness of our particular influence map encoding for representing spatially resolved tactics and (2) the potential for using co-evolution to generate increasingly complex and competent tactics in our game. More generally, this work represents another step in our ongoing effort to investigate the co-evolution of competent game players in a real-time, continuous, environment that does not assume complete knowledge of the game state. ©2009 IEEE.

关键词： evolutionary algorithms

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Dependable workflow scheduling in global grids

Dependable workflow scheduling in global grids

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2009 10th IEEE/ACM International Conference on Grid computing, Grid 2009

作者： Rahman, Mustafizur Ranjan, Rajiv Buyya, Rajkumar Grid Computing and Distributed Systems Laboratory Department of Computer Science and Software Engineering University of Melbourne Australia Service Oriented Computing Research Group School of Computer Science and Engineering University of New South Wales Australia

ISBN: (纸本)9781424451494

In this paper, a reputation-based Grid workflow scheduling algorithm is proposed to counter the effect of inherent unreliability and temporal characteristics of computing resources in large scale, decentralized Grid overlays. The proposed approach builds upon structured peer-to-peer indexing and overlay networking techniques to create a scalable wide-area networking of Grid sites for supporting dependable scheduling of applications. The scheduling algorithm considers reliability of a Grid resource as a statistical property, which is globally computed in the decentralized Grid overlay based on dynamic feedbacks or reputation scores assigned by individual service consumers (Grid Resource Brokers). The proposed algorithm can dynamically adapt to changing resource conditions and offer significant performance gains as compared to traditional approaches in the event of unsuccessful job execution or resource failure. We evaluate and demonstrate the feasibility of our approach through an extensive trace driven simulation. The results show that our scheduling technique can reduce the makespan up to 50% and successfully isolate the failure-prone resources from the system. © 2009 IEEE.

关键词： Scheduling algorithms

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A distributed heuristic for decentralized workflow scheduling in global grids

A distributed heuristic for decentralized workflow schedulin...

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2009 10th IEEE/ACM International Conference on Grid computing, Grid 2009

ISBN: (纸本)9781424451494

Efficient scheduling is a key concern for the effectual execution of performance driven Grid applications, such as workflows. Many list heuristics have been developed for scheduling workflows in centralized Grid environment. However, in this paper, we present a distributed list heuristic for decentralized scheduling of workflow applications in global Grids. The simulation results show that the proposed scheduling approach is scalable with respect to increased workload on the system. © 2009 IEEE.

关键词： Scheduling

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Prediction of novel precursor miRNAs using a context-sensitive Hidden Markov Model (CSHMM)

Prediction of novel precursor miRNAs using a context-sensiti...

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8th Asia-Pacific Bioinformatics Conference, APBC 2010

作者： Agarwal, Sumeet Vaz, Candida Bhattacharya, Alok Srinivasan, Ashwin Department of Physics Systems Biology Doctoral Training Centre University of Oxford Parks Road Oxford OX1 3PU United Kingdom Center for Computational Biology and Bioinformatics School of Information Technology Jawaharlal Nehru University New Delhi 110067 India School of Life Sciences Jawaharlal Nehru University New Delhi 110067 India Oxford University Computing Laboratory Wolfson Building Parks Road Oxford OX1 3QD United Kingdom IBM India Research Lab. 4-C Vasant Kunj Institutional Area Phase II Vasant Kunj New Delhi 110070 India School of Computer Science and Engineering Centre for Health Informatics University of New South Wales Sydney Australia

Background: It has been apparent in the last few years that small non coding RNAs (ncRNA) play a very significant role in biological regulation. Among these microRNAs (miRNAs), 22-23 nucleotide small regulatory RNAs, have been a major object of study as these have been found to be involved in some basic biological processes. So far about 706 miRNAs have been identified in humans alone. However, it is expected that there may be many more miRNAs encoded in the human genome. In this report, a "context-sensitive" Hidden Markov Model (CSHMM) to represent miRNA structures has been proposed and tested extensively. We also demonstrate how this model can be used in conjunction with filters as an ab initio method for miRNA identification. Results: The probabilities of the CSHMM model were estimated using known human miRNA sequences. A classifier for miRNAs based on the likelihood score of this "trained" CSHMM was evaluated by: (a) cross-validation estimates using known human sequences, (b) predictions on a dataset of known miRNAs, and (c) prediction on a dataset of non coding RNAs. The CSHMM is compared with two recently developed methods, miPred and CID-miRNA. The results suggest that the CSHMM performs better than these methods. In addition, the CSHMM was used in a pipeline that includes filters that check for the presence of EST matches and the presence of Drosha cutting sites. This pipeline was used to scan and identify potential miRNAs from the human chromosome 19. It was also used to identify novel miRNAs from small RNA sequences of human normal leukocytes obtained by the Deep sequencing (Solexa) methodology. A total of 49 and 308 novel miRNAs were predicted from chromosome 19 and from the small RNA sequences respectively Conclusion: The results suggest that the CSHMM is likely to be a useful tool for miRNA discovery either for analysis of individual sequences or for genome scan. Our pipeline, consisting of a CSHMM and filters to reduce false positives shows promise as

关键词： RNA

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Evolving coordinated spatial tactics for autonomous entities using influence maps

Evolving coordinated spatial tactics for autonomous entities...

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IEEE Symposium on Computational Intelligence and Games, CIG

作者： Phillipa Avery Sushil Louis Benjamin Avery Evolutionary Computing Systems Laboratory Department of Computer Science and Engineering University of Nevada Reno NV USA Evolutionary Computing Systems Laboratory Dept. of Computer Science and Engineering University of Nevada Reno USA

关键词： Boats evolutionary computation Strategic planning Competitive intelligence Distributed control Automatic control Spatial resolution Encoding Application software computer applications

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Scheduling parallel applications on Utility Grids: Time and cost trade-off management

Scheduling parallel applications on Utility Grids: Time and ...

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32nd Australasian computer science Conference, ACSC 2009

作者： Garg, Saurabh Kumar Buyya, Rajkumar Siegel, H.J. Grid Computing and Distributed Systems Laboratory Department of Computer Science and Software Engineering University of Melbourne VIC 3010 Australia Electrical and Computer Engineering Department Colorado State University Fort Collins United States Computer Science Department Colorado State University Fort Collins United States

ISBN: (纸本)9781920682729

With the growth of Utility Grids and various Grid market infrastructures, the need for efficient and cost effective scheduling algorithms is also increasing rapidly, particularly in the area of meta-scheduling. In these environments,users not only may have conflicting requirements with other users, but also they have to manage the trade-off between time and cost such that their applications can be executed most economically in the minimum time. Thus, choosing of the best Grid resources becomes a challenge in such a competitive market. This paper presents two novel heuristics for scheduling parallel applications on Utility Grids that manage and optimize the trade-off between time and cost constraints. The performance of the heuristics is evaluated through extensive simulations of a real-world environment with real parallel workload models to demonstrate the practicality of our algorithms. We compare our scheduling algorithms against other common algorithms used by current meta-schedulers. The results shows that our algorithms outperform other algorithms by minimizing the time and cost of application execution on Utility Grids. Copyright © 2009, Australian computer Society, Inc.

关键词： Scheduling algorithms

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Abstracts from the 2011 Joint Annual Meeting of the Society for Northwestern Vertebrate Biology and Washington Chapter of the Wildlife Society, Held at the Wesley Inn, Gig Harbor, Washington, March 23–25, 2011

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Northwestern Naturalist 2011年第2期92卷 136-166页

作者： Michael J. Adams Christopher A. Pearl Jessica Y. Adkins Daniel D. Roby Ladd Bayliss Peter J. Loschl Donald E. Lyons Yasuko Suzuki Hannah E. Anderson Sarah T. Hamman Keith B. Aubry Catherine M. Raley John J. Rohrer Eric C. Lofroth Scott H. Fitkin Michael L. Best Hartwell H. Welsh Jamie B. Bettaso Don T. Ashton Hartwell H. Welsh Scott McBain Lindsay M. Biga Andrew R. Blaustein Susan F. Brady R. Steven Wagner Daniel J. Selski James E. Johnson R. Bruce Bury Wynn W. Cudmore Hartwell H. Welsh Nathan D. Chelgren Tara Chestnut Chaucney W. Anderson Julie Kirshtein Megan T. Cook Tiffany S. Garcia Stephen Corn Erin Muths Amanda Kissel Rick Scherer Eric Delvin Jonathan D. Bakker Peter W. Dunwiddie Diana L. Dishman Deborah A. Duffield Harriet R. Huber Dyanna M. Lambourn Karen M. Dvornich Greg Falxa Gary M. Fellers Patrick M. Kleeman David Miller Brandon Fessler Jason T. Irwin Daniel D. Beck R. Steven Wagner Marc P. Hayes John A. Frew Christian E. Grue Chris R. Friesen Robert T. Mason Stevan J. Arnold Suzanne Estes Tiffany S. Garcia Katie M. Dugger Josh Johnson Mike Rochelle A. J. Kroll Stephanie S. Gervasi Caren S. Goldberg Dan Davis Erica Bree Rosenblum Bill Bosworth Lisette P. Waits Purnima Govindarajulu Gregory A. Green Steve Negri Jennifer R. Griffiths Daniel E. Schindler Christian E. Grue Karen M. Dvornich Adam G. Hansen David A. Beauchamp Casey M. Baldwin Marc P. Hayes Gretchen Padgett-Flohr Blake R. Hossack Winsor H. Lowe Paul Stephen Corn Aaron N. Johnston Kris Kendell Dave Prescott Scott Stevens Peter M. Kiffney Carol Volk Kerensa A. King Christian E. Grue James M. Grassley Andrew J. Kroll Matt Hane Josh Johnston Mike Rochelle Stuart Farber Niels Leuthold Michael J. Adams John P. Hayes Bo Li Michael T. Brett Kent B. Livezey Ilon E. Logan Teresa J. Lorenz Kimberly A. Sullivan Amanda V. Bakian Deanna Lynch Nancy Thomas Krysten Schuler Steven Jeffries Joshua Malt Kelly R. McAllister Joanne P. Schuett-Hames Aimee P. McIntyre Jay E. Jones Eric M. Lund Frithiof T. Waterstrat Jack N. Giovanini Stephen D. Duke Marc P. Hayes US Forest Service Pacific Northwest Research Station Olympia WA 98512 kaubry@fs.fed.us US Forest Service Okanogan-Wenatchee National Forest Methow Valley Ranger District Winthrop WA 98862 British Columbia Ministry of Environment Victoria BC V8W9M1 Washington Department of Fish and Wildlife Winthrop WA 98862 Humboldt State University 1 Harpst St. Arcata CA 95521 addsmike14@*** US Forest Service Pacific Southwest Research Station 1700 Bayside Dr. Arcata CA 95521 hwelsh@fs.fed.us US Fish and Wildlife Service Arcata Field Office 1655 Heindon Road Arcata CA 95521 jamie_bettaso@fws.gov Redwood Sciences Laboratory US Forest Service1700 Bayview Drive Arcata CA 99521 dashton@fs.fed.us hwelsh@fs.fed.us McBain &amp Trush 980 7th Street Arcata CA 95521 scott@*** Oregon State University Environmental Sciences Graduate Program Corvallis OR 97331 lindsay.biga@science.oregonstate.edu Oregon State University Department of Zoology Corvallis OR 97331 US Geological Survey Forest and Rangeland Ecosystem Science Center 3200 SW Jefferson Way Corvallis OR 97331 buryb@usgs.gov Life Science Department Chemeketa Community College Salem OR 97309 wynn.cudmore@chemeketa.edu US Forest Service Redwood Sciences Laboratory 1700 Bayview Drive Arcata CA 95521 hwelsh@fs.fed.us USGS Oregon Water Science Center 2130 SW 5th Avenue Portland OR 97207 chestnut@usgs.gov USGS Headquarters 12201 Sunrise Valley Drive Reston VA 20192 US Geological Survey Northern Rocky Mountain Science Center Aldo Leopold Wilderness Research Institute 790 E. Beckwith Avenue Missoula MT 59801 scorn@usgs.gov US Geological Survey Fort Collins Science Center 2150 Centre Avenue Building C Fort Collins CO 80526 Department of Biological Sciences Simon Fraser University Burnaby BC V5A 1S6 Colorado State University Department of Fishery and Wildlife Biology Fort Collins CO 80523 The Nature Conservancy 120 Union Ave SE Olympia WA 98501 edelvin@tnc.org School of Forest Resources University of Washington Seattle WA

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Emotion classification based on gamma-band EEG

Emotion classification based on gamma-band EEG

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31st Annual International Conference of the IEEE engineering in Medicine and Biology Society: engineering the Future of Biomedicine, EMBC 2009

作者： Li, Mu Lu, Bao-Liang Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781424432967

In this paper, we use EEG signals to classify two emotions-happiness and sadness. These emotions are evoked by showing subjects pictures of smile and cry facial expressions. We propose a frequency band searching method to choose an optimal band into which the recorded EEG signal is filtered. We use common spatial patterns (CSP) and linear-SVM to classify these two emotions. To investigate the time resolution of classification, we explore two kinds of trials with lengths of 3s and 1s. Classification accuracies of 93:5% ± 6:7% and 93:0%±6:2% are achieved on 10 subjects for 3s-trials and 1s-trials, respectively. Our experimental results indicate that the gamma band (roughly 30-100 Hz) is suitable for EEG-based emotion classification. ©2009 IEEE.

关键词： Signal processing

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