Production of Neutral Fermion in Linear Magnetic Field through Pauli Interaction

We calculate the production rate of neutral fermions in linear magnetic fields through the Pauli interaction. It is found that the production rate is exponentially decreasing function with respect to the inverse of the magnetic field gradient, which shows the non-perturbative characteristics analogous to the Schwinger process. It turns out that the production rate density depends on both the gradient and the strength of magnetic fields in 3+1 dimension. It is quite different from the result in 2+1 dimension, where the production rate depends only on the gradient of the magnetic fields, not on the strength of the magnetic fields. It is also found that the production of neutral fermions through the Pauli interaction is a magnetic effect whereas the production of charged particles through minimal coupling is an electric effect.Comment: 11 pages, 2 figure

Semiclassical Quantization for the Spherically Symmetric Systems under an Aharonov-Bohm magnetic flux

The semiclassical quantization rule is derived for a system with a spherically symmetric potential $V(r) \sim r^{\nu}$ $(-2<\nu <\infty)$ and an Aharonov-Bohm magnetic flux. Numerical results are presented and compared with known results for models with $\nu = -1,0,2,\infty$. It is shown that the results provided by our method are in good agreement with previous results. One expects that the semiclassical quantization rule shown in this paper will provide a good approximation for all principle quantum number even the rule is derived in the large principal quantum number limit $n \gg 1$. We also discuss the power parameter $\nu$ dependence of the energy spectra pattern in this paper.Comment: 13 pages, 4 figures, some typos correcte

Universal quantum gates based on a pair of orthogonal cyclic states: Application to NMR systems

We propose an experimentally feasible scheme to achieve quantum computation based on a pair of orthogonal cyclic states. In this scheme, quantum gates can be implemented based on the total phase accumulated in cyclic evolutions. In particular, geometric quantum computation may be achieved by eliminating the dynamic phase accumulated in the whole evolution. Therefore, both dynamic and geometric operations for quantum computation are workable in the present theory. Physical implementation of this set of gates is designed for NMR systems. Also interestingly, we show that a set of universal geometric quantum gates in NMR systems may be realized in one cycle by simply choosing specific parameters of the external rotating magnetic fields. In addition, we demonstrate explicitly a multiloop method to remove the dynamic phase in geometric quantum gates. Our results may provide useful information for the experimental implementation of quantum logical gates.Comment: 9 pages, language revised, the publication versio

A dynamic inexact energy systems planning model for supporting greenhouse-gas emission management and sustainable renewable energy development under uncertainty--A case study for the City of Waterloo, Canada

In this study, a dynamic interval-parameter community-scale energy systems planning model (DIP-CEM) was developed for supporting greenhouse-gas emission (GHG) management and sustainable energy development under uncertainty. The developed model could reach insight into the interactive characteristics of community-scale energy management systems, and thus capable of addressing specific community environmental and socio-economic features. Through integrating interval-parameter and mixed-integer linear programming techniques within a general optimization framework, the DIP-CEM could address uncertainty (expressed as interval values) existing in related costs, impact factors and system objectives as well as facilitate dynamic analysis of capacity-expansion decisions under such a uncertainty. DIP-CEM was then applied to the City of Waterloo, Canada to demonstrate its applicability in supporting decisions of community energy systems planning and GHG-emission reduction management. One business-as-usual (BAU) case and two GHG-emission reduction cases were analyzed with desired plans of GHG-emission reduction. The results indicated that the developed DIP-CEM could help provide sound strategies for dealing with issues of sustainable energy development and GHG-emission reduction within an energy management system.Community Energy systems Greenhouse gas Renewable energy Sustainable energy development Uncertainty

Planning of energy system management and GHG-emission control in the Municipality of Beijing--An inexact-dynamic stochastic programming model

Concerns over increasing energy price, exacerbating power shortage and changing climatic conditions are emerging associated with municipal energy management systems. Most of the previous studies could hardly address multiple uncertainties that exist in such systems; this may lead to incomplete, simplified or even false solutions, and could jeopardize the robustness of management decisions. This study is to develop a dynamic inexact stochastic energy systems planning model (DITS-MEM) for managing municipal energy systems and greenhouse-gas (GHG) emissions under uncertainty. Through integrating mixed-integer, interval-parameter and two-stage stochastic programming techniques, DITS-MEM can handle not only the uncertainties expressed as interval values and probabilistic distributions associated with GHG-emission reduction targets, but also the dynamics of capacity-expansion issues. The developed model is then applied to the Beijing Municipality. The results suggest that the DITS-MEM model is applicable in reflecting complexities of multi-uncertainty, dynamic and interactive municipal energy management systems, and capable of addressing two-stage stochastic problem of GHG-emission reduction. The obtained solutions can provide decision bases for formulating GHG-reduction policies and assessing the associated economic implications in purchasing emission credits or bearing economic penalties.Energy systems planning GHG emission Uncertainty

Integer programming with random-boundary intervals for planning municipal power systems

Uncertainty attached to municipal power systems has long been crucial considerations for the related planners. Such an uncertainty could be expressed as random-boundary intervals (RBIs). In this study, an integer programming with random-boundary intervals (IPRBI) approach was developed for municipal electricity-supply management under uncertainty. A concept of random-boundary interval (RBI) was introduced to reflect dual uncertainties that exist in many system components. A solution method named two-boundary approach (TBA) was proposed to solve the IPRBI model. A case study was provided for demonstrating applicability of the developed method. The results indicated that the RBI and integer-interval concepts were effective in dealing with highly uncertain parameters. The IPRBI method solutions could be used for generating efficient electricity-supply schemes under various complexities. They can also be used for analyzing tradeoffs between system cost and electricity-shortage risk. Compared with the existing methods, IPRBI was advantageous in reflecting the complexities of system uncertainties that were presented as RBIs, integer-intervals and intervals.Random-boundary interval Integer-interval Uncertainty Correlation Electricity supply planning

IFTEM: An interval-fuzzy two-stage stochastic optimization model for regional energy systems planning under uncertainty

The development of optimization models for energy systems planning has attracted considerable interest over the past decades. However, the uncertainties that are inherent in the planning process and the complex interactions among various uncertain parameters are challenging the capabilities of these developed tools. Therefore, the objective of this study is to develop a hybrid interval-fuzzy two-stage stochastic energy systems planning model (IFTEM) to deal with various uncertainties that can be expressed as fuzzy numbers, probability distributions and discrete intervals. The developed IFTEM is then applied to a hypothetical regional energy system. The results indicate that the IFTEM has advantages in reflecting complexities of various system uncertainties as well as dealing with two-stage stochastic decision problems within energy systems.Energy systems planning Interval-fuzzy Two-stage optimization

Community-scale renewable energy systems planning under uncertainty--An interval chance-constrained programming approach

In this study, an inexact community-scale energy model (ICS-EM) has been developed for planning renewable energy management (REM) systems under uncertainty. This method is based on an integration of the existing interval linear programming (ILP), chance-constrained programming (CCP) and mixed integer linear programming (MILP) techniques. ICS-EM allows uncertainties presented as both probability distributions and interval values to be incorporated within a general optimization framework. It can also facilitate capacity-expansion planning for energy-production facilities within a multi-period and multi-option context. Complexities in energy management systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The developed method has then been applied to a case of long-term renewable energy management planning for three communities. Useful solutions for the planning of energy management systems have been generated. Interval solutions associated with different risk levels of constraint violation have been obtained. They can be used for generating decision alternatives and thus help decision makers identify desired policies under various economic and system-reliability constraints. The generated solutions can also provide desired energy resource/service allocation and capacity-expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs and constraint-violation risks can also be tackled. Higher costs will increase system stability, while a desire for lower system costs will run into a risk of potential instability of the management system. They are helpful for supporting (a) adjustment or justification of allocation patterns of energy resources and services, (b) formulation of local policies regarding energy consumption, economic development and energy structure, and (c) analysis of interactions among economic cost, system reliability and energy-supply security.Community Decision making Energy systems Environment Greenhouse gas Management Renewable energy Uncertainty