Coherent control and giant enhancement of multiphoton ionization and high-order-harmonic generation driven by intense frequency-comb laser fields: An ab initio theoretical investigation

This is the published version, also available here: http://dx.doi.org/10.1103/PhysRevA.87.043407.We present an ab initio theoretical investigation of the coherent control and significant enhancement of multiphoton ionization (MPI) and high-order-harmonic generation (HHG) of atoms and molecules by means of intense frequency-comb laser fields. We show that the nonperiodically or quasiperiodically time-dependent Schrödinger equation for the frequency-comb laser excitation problem can be transformed exactly into a time-independent non-Hermitian generalized Floquet matrix eigenvalue problem by means of the many-mode Floquet theory and the complex-scaling transformation. The generalized Floquet Hamiltonian can be optimally discretized and the complex quasienergy eigenvalues and eigenfunctions can be solved accurately and efficiently by means of the generalized pseudospectral method. The procedure is applied to a case study of the resonance-enhanced MPI and HHG of atomic hydrogen driven by an intense frequency-comb laser field. Our study shows that both the MPI and HHG rates can be coherently controlled by tuning the laser parameters such as the pulse-to-pulse carrier-envelope-phase (CEP) shift. In particular, both the MPI and HHG rates exhibit dramatic enhancement by tuning the CEP shift, due to the phenomenon of multiphoton resonances

Core-Selecting Auctions for Dynamically Allocating Heterogeneous VMs in Cloud Computing

In a cloud market, the cloud provider provisions heterogeneous virtual machine (VM) instances from its resource pool, for allocation to cloud users. Auction-based allocations are efficient in assigning VMs to users who value them the most. Existing auction design often overlooks the heterogeneity of VMs, and does not consider dynamic, demand-driven VM provisioning. Moreover, the classic VCG auction leads to unsatisfactory seller revenues and vulnerability to a strategic bidding behavior known as shill bidding. This work presents a new type of core-selecting VM auctions, which are combinatorial auctions that always select bidder charges from the core of the price vector space, with guaranteed economic efficiency under truthful bidding. These auctions represent a comprehensive three-phase mechanism that instructs the cloud provider to judiciously assemble, allocate, and price VM bundles. They are proof against shills, can improve seller revenue over existing auction mechanisms, and can be tailored to maximize truthfulness.published_or_final_versio

Fourth-order modified method for the Cauchy problem for the Laplace equation

AbstractWe consider the Cauchy problem for the Laplace equation in the half plane x>0,y∈R where the Cauchy data is given at x=0 and the solution is sought in the interval 0<x⩽1. The problem is ill-posed: the solution (if it exists) does not depend continuously on the data. In order to solve the problem numerically, it is necessary to modify the equation so that a bound on the solution is imposed. We study a modification of the equation, where a fourth-order mixed derivative term is added. Error estimates for this equation are given, which show that the solution of the modified equation is an approximation of the solution of the Cauchy problem for the Laplace equation, and it is shown that when the data error tends to zero, the error in the approximate solution tends to zero logarithmically. Numerical implementation is considered and a simple example is given

Fourier regularization for a backward heat equation

AbstractIn this paper a simple and convenient new regularization method for solving backward heat equation—Fourier regularization method is given. Meanwhile, some quite sharp error estimates between the approximate solution and exact solution are provided. A numerical example also shows that the method works effectively

Optimal error bound and Fourier regularization for identifying an unknown source in the heat equation

AbstractIn this paper we investigate a problem of the identification of an unknown source from one supplementary temperature measurement at a given instant of time for the transient heat equation. Under an a priori condition we answer the question concerning the best possible accuracy for the problem. The Fourier regularization method is utilized for solving the problem, and its convergent rate is analyzed. Numerical results are presented to illustrate the accuracy and efficiency of the method

Improving multi-objective reservoir operation optimization with sensitivity-informed dimension reduction

There is another ORE record for this article: http://hdl.handle.net/10871/21284This study investigates the effectiveness of a sensitivity-informed method for multi-objective operation of reservoir systems, which uses global sensitivity analysis as a screening tool to reduce computational demands. Sobol's method is used to screen insensitive decision variables and guide the formulation of the optimization problems with a significantly reduced number of decision variables. This sensitivity-informed method dramatically reduces the computational demands required for attaining high-quality approximations of optimal trade-off relationships between conflicting design objectives. The search results obtained from the reduced complexity multi-objective reservoir operation problems are then used to pre-condition the full search of the original optimization problem. In two case studies, the Dahuofang reservoir and the inter-basin multi-reservoir system in Liaoning province, China, sensitivity analysis results show that reservoir performance is strongly controlled by a small proportion of decision variables. Sensitivity-informed dimension reduction and pre-conditioning are evaluated in their ability to improve the efficiency and effectiveness of multi-objective evolutionary optimization. Overall, this study illustrates the efficiency and effectiveness of the sensitivity-informed method and the use of global sensitivity analysis to inform dimension reduction of optimization problems when solving complex multi-objective reservoir operation problems.China Postdoctoral Science FoundationNatural Science Foundation of Chin

Use of many-objective visual analytics to analyze water supply objective tradeoffs with water transfer

This is the author accepted manuscript. The final version is available from ASCE via the DOI in this record.The construction of water transfer projects can have a considerable impact on the operation of the receiving reservoir. This study investigates the change of the objective tradeoffs in multi-objective reservoir operation problems due to the introduction of water transfer using a case study of the East-to-West Water Transfer project in northeastern China. Two optimization cases are constructed to analyze the tradeoff changes: a base case with no water transfer which considers four objectives, i.e., minimizing industry water shortage, minimizing agriculture water shortage, minimizing water spillage, and maximizing ecological satisfaction; a future post-construction case which considers an additional objective to minimize the amount of water transferred. Results obtained from the case study show increasing water transfer substantially reduces the intensity of the competition between industrial and agricultural water shortages, and the objective tradeoffs among water spillage, ecological satisfaction and agricultural shortage index are substantially changed because of water transfer. In addition, the amount of water transferred with high efficiency regarding each objective is identified, and three solutions of different orders of magnitude in diverted water have been recommended for informed decision making considering efficiency and benefit. This study implies that many-objective visual analytics can be used to determine the optimal amount of water transferred in terms of water efficiency revealed in different objective tradeoff spaces.This study was supported by the National Natural Science Foundation of China (Grant Nos. 51320105010, 51279021, and 51409043), and by the Ministry of Water Resources of China (Grant No. 201401014-2). The fourth author was partially supported by the Engineering and Physical Sciences Research Council (EPSRC) under the Building Resilience into Risk Management project (EP/N010329/1)