Complexified Path Integrals and the Phases of Quantum Field Theory

The path integral by which quantum field theories are defined is a particular solution of a set of functional differential equations arising from the Schwinger action principle. In fact these equations have a multitude of additional solutions which are described by integrals over a complexified path. We discuss properties of the additional solutions which, although generally disregarded, may be physical with known examples including spontaneous symmetry breaking and theta vacua. We show that a consideration of the full set of solutions yields a description of phase transitions in quantum field theories which complements the usual description in terms of the accumulation of Lee-Yang zeroes. In particular we argue that non-analyticity due to the accumulation of Lee-Yang zeros is related to Stokes phenomena and the collapse of the solution set in various limits including but not restricted to, the thermodynamic limit. A precise demonstration of this relation is given in terms of a zero dimensional model. Finally, for zero dimensional polynomial actions, we prove that Borel resummation of perturbative expansions, with several choices of singularity avoiding contours in the complex Borel plane, yield inequivalent solutions of the action principle equations.Comment: 15 pages, 9 figures (newer version has better images

Innovative public governance through cloud computing: Information privacy, business models and performance measurement challenges

Purpose: The purpose of this paper is to identify and analyze challenges and to discuss proposed solutions for innovative public governance through cloud computing. Innovative technologies, such as federation of services and cloud computing, can greatly contribute to the provision of e-government services, through scaleable and flexible systems. Furthermore, they can facilitate in reducing costs and overcoming public information segmentation. Nonetheless, when public agencies use these technologies, they encounter several associated organizational and technical changes, as well as significant challenges. Design/methodology/approach: We followed a multidisciplinary perspective (social, behavioral, business and technical) and conducted a conceptual analysis for analyzing the associated challenges. We conducted focus group interviews in two countries for evaluating the performance models that resulted from the conceptual analysis. Findings: This study identifies and analyzes several challenges that may emerge while adopting innovative technologies for public governance and e-government services. Furthermore, it presents suggested solutions deriving from the experience of designing a related platform for public governance, including issues of privacy requirements, proposed business models and key performance indicators for public services on cloud computing. Research limitations/implications: The challenges and solutions discussed are based on the experience gained by designing one platform. However, we rely on issues and challenges collected from four countries. Practical implications: The identification of challenges for innovative design of e-government services through a central portal in Europe and using service federation is expected to inform practitioners in different roles about significant changes across multiple levels that are implied and may accelerate the challenges' resolution. Originality/value: This is the first study that discusses from multiple perspectives and through empirical investigation the challenges to realize public governance through innovative technologies. The results emerge from an actual portal that will function at a European level. © Emerald Group Publishing Limited

Sparse logistic principal components analysis for binary data

We develop a new principal components analysis (PCA) type dimension reduction method for binary data. Different from the standard PCA which is defined on the observed data, the proposed PCA is defined on the logit transform of the success probabilities of the binary observations. Sparsity is introduced to the principal component (PC) loading vectors for enhanced interpretability and more stable extraction of the principal components. Our sparse PCA is formulated as solving an optimization problem with a criterion function motivated from a penalized Bernoulli likelihood. A Majorization--Minimization algorithm is developed to efficiently solve the optimization problem. The effectiveness of the proposed sparse logistic PCA method is illustrated by application to a single nucleotide polymorphism data set and a simulation study.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS327 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Nuclear Incompressibility at Finite Temperature and Entropy

Features of the nuclear isothermal incompressibility $\kappa$ and adiabatic incompressibility $\kappa_Q$ are investigated. The calculations are done at zero and finite temperatures and non zero entropy and for several equations of state. It is shown that $\kappa_Q$ decreases with increasing entropy while the isothermal $\kappa$ increases with increasing $T$. A duality is found between the adiabatic $\kappa_Q$ and the T=0 isothermal $\kappa$. Our isothermal results are compared with a recent lattice Monte Carlo calculation done at finite $T$. The necessity of including correlations is shown if $\kappa$ is to have a peak with increasing $T$ as seen in the Monte Carlo calculations. A peak in $\kappa$ is linked to attractive scattering correlations in two nucleons channel in the virial expansion in our approach which are Pauli blocked at low $T$.Comment: 5 page

Mitigating ground effect on mini quadcopters with model reference adaptive control

Mitigating ground effect becomes a big challenge for autonomous aerial vehicles when they are flying in close proximity to the ground. This paper aims to develop a precise model of ground effect on mini quadcopters, provide an advanced control algorithm to counter the model uncertainty and, as a result, improves the command tracking performance when the vehicle is in the ground effect region. The mathematical model of ground effect has been established through a series of experiments and validated by a flight test. The experiments show that the total thrust generated by rotors increases linearly as the vehicle gets closer to the ground, which is different from the commonly-used ground effect model for a single rotor vehicle. In addition, the model switches from a piecewise linear to a quadratic function when the rotor to rotor distance is increased. A control architecture that utilizes the model reference adaptive controller (MRAC) has also been designed, where MRAC is added to the altitude loop. The performance of the proposed control algorithm has been evaluated through a set of flight tests on a mini quadcopter platform and compared with a traditional proportional–integral–derivative (PID) controller. The results demonstrate that MRAC dramatically improves the tracking performance of altitude command and can reduce the rise time by 80 % under the ground effect