Formation of Quantum Phase Slip Pairs in Superconducting Nanowires

Macroscopic quantum tunneling (MQT) is a fundamental phenomenon of quantum mechanics related to the actively debated topic of quantum-to-classical transition. The ability to realize MQT affects implementation of qubit-based quantum computing schemes and their protection against decoherence. Decoherence in qubits can be reduced by means of topological protection, e.g. by exploiting various parity effects. In particular, paired phase slips can provide such protection for superconducting qubits. Here, we report on the direct observation of quantum paired phase slips in thin-wire superconducting loops. We show that in addition to conventional single phase slips that change superconducting order parameter phase by $2\pi$, there are quantum transitions changing the phase by $4\pi$. Quantum paired phase slips represent a synchronized occurrence of two macroscopic quantum tunneling events, i.e. cotunneling. We demonstrate the existence of a remarkable regime in which paired phase slips are exponentially more probable than single ones

World Modeling for Intelligent Autonomous Systems

The functioning of intelligent autonomous systems requires constant situation awareness and cognition analysis. Thus, it needs a memory structure that contains a description of the surrounding environment (world model) and serves as a central information hub. This book presents a row of theoretical and experimental results in the field of world modeling. This includes areas of dynamic and prior knowledge modeling, information fusion, management and qualitative/quantitative information analysis

World Modeling for Intelligent Autonomous Systems

The functioning of intelligent autonomous systems requires constant situation awareness and cognition analysis. Thus, it needs a memory structure that contains a description of the surrounding environment (world model) and serves as a central information hub. This book presents a row of theoretical and experimental results in the field of world modeling. This includes areas of dynamic and prior knowledge modeling, information fusion, management and qualitative/quantitative information analysis

World Modeling for Intelligent Autonomous Systems

Within the scope of this work, we have attained a row of theoretical and experimental results in the field of world modeling as well as gathered significant experience and expertise. The covered topics include concepts and approaches for dynamic and prior knowledge modeling, information association, fusion and management as well as their practical realization and experimental evaluation

Three Pillar Information Management System for Modeling the Environment of Autonomous Systems

This contribution is about an information management and storage system for modeling the environment of autonomous systems. The three pillars of the system consist of prior knowledge, environment model and sensory information. The main pillar is the environment model, which supplies the autonomous system with relevant information about its current environment. For this purpose, an abstract representation of the real world is created, where instances with attributes and relations serve as virtual substitutes of entities (persons and objects) of the real world. The environment model is created based on sensory information about the real world. The gathered sensory information is typically uncertain in a stochastic sense and is represented in the environment model by means of Degree-of-Belief (DoB) distributions. The prior knowledge contains all relevant background knowledge (e.g., concepts organized in ontologies) for creating and maintaining the environment model. The concept of the three pillar information system has previously been published. Therefore this contribution focuses on further central properties of the system. Furthermore, the development status and possible applications as well as evaluation scenarios are discussed

Data Association in a World Model for Autonomous Systems

This contribution introduces a three pillar information storage and management system for modeling the environment of autonomous systems. The main characteristics is the separation of prior knowledge, environment model and sensor information. In the center of the system is the environment model, which provides the autonomous system with information about the current state of the environment. It consists of instances with attributes and relations as virtual substitutes of entities (persons and objects) of the real world. Important features are the representation of uncertain information by means of Degree-of-Belief (DoB) distributions, the information exchange between the three pillars as well as creation, deletion and update of instances, attributes and relations in the environment model. In this work, a Bayesian method for fusing new observations to the environment model is introduced. For this purpose, a Bayesian data association method is derived. The main question answered here is the observation-to-instance mapping and the decision mechanisms for creating a new instance or updating already existing instances in the environment model

Remote climate forcing of decadal-scale regime shifts in Northwest Atlantic shelf ecosystems

Author Posting. © Association for the Sciences of Limnology and Oceanography, 2013. This article is posted here by permission of Association for the Sciences of Limnology and Oceanography for personal use, not for redistribution. The definitive version was published in Association for the Sciences of Limnology and Oceanography, doi:10.4319/lo.2013.58.3.0803.Decadal-scale regime shifts in Northwest Atlantic shelf ecosystems can be remotely forced by climate-associated atmosphere–ocean interactions in the North Atlantic and Arctic Ocean Basins. This remote climate forcing is mediated primarily by basin- and hemispheric-scale changes in ocean circulation. We review and synthesize results from process-oriented field studies and retrospective analyses of time-series data to document the linkages between climate, ocean circulation, and ecosystem dynamics. Bottom-up forcing associated with climate plays a prominent role in the dynamics of these ecosystems, comparable in importance to that of top-down forcing associated with commercial fishing. A broad perspective, one encompassing the effects of basin- and hemispheric-scale climate processes on marine ecosystems, will be critical to the sustainable management of marine living resources in the Northwest Atlantic.Funding for this research was provided by the National Science Foundation as part of the Regional and Pan-Regional Synthesis Phases of the U.S. Global Ocean Ecosystem (GLOBEC) Program

Arctic decadal variability from an idealized atmosphere-ice-ocean model : 2. Simulation of decadal oscillations

Author Posting. © American Geophysical Union, 2006. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 111 (2006): C06029, doi:10.1029/2004JC002820.A simple model of the Arctic Ocean and Greenland Sea, coupled to a thermodynamic sea ice model and an atmospheric model, has been used to study decadal variability of the Arctic ice-ocean-atmosphere climate system. The motivating hypothesis is that the behavior of the modeled and ultimately the real climate system is auto-oscillatory with a quasi-decadal periodicity. This system oscillates between two circulation regimes: the Anticyclonic Circulation Regime (ACCR) and the Cyclonic Circulation Regime (CCR). The regimes are controlled by the atmospheric heat flux from the Greenland Sea and the freshwater flux from the Arctic Ocean. A switch regulating the intensity of the fluxes between the Arctic Ocean and Greenland Sea that depends on the inter-basin gradient of dynamic height is implemented as a delay mechanism in the model. This mechanism allows the model system to accumulate the “perturbation” over several years. After the perturbation has been released, the system returns to its initial state. Solutions obtained from numerical simulations with seasonally varying forcing, for scenarios with high and low interaction between the regions, reproduced the major anomalies in the ocean thermohaline structure, sea ice volume, and fresh water fluxes attributed to the ACCR and CCR.This publication is the result of research sponsored by Alaska Sea Grant with funds from the National Oceanic and Atmospheric Administration Office of Sea Grant, Department of Commerce, under grant no. NA 86RG0050 (project no. GC/01-02), and from the University of Alaska with funds appropriated by the state. This research has also been supported by the National Science Foundation and by the International Arctic Research Center, University of Alaska Fairbanks, under auspices of the United States National Science Foundation

Challenges and science-based implications for modern management and conservation of European ungulate populations

Wildlife management systems face growing challenges to cope with increasingly complex interactions between wildlife populations, the environment and human activities. In this position statement, we address the most important issues characterising current ungulate conservation and management in Europe. We present some key points arising from ecological research that may be critical for a reassessment of ungulate management in the future. Ecosystem . Population sustainability . Science-basedmanagement .Wildlifemanagement .Adaptive managemen