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Zheng Li

Publications and source records attributed to Zheng Li.

At least 469 records · Page 26Linked to original sources

Multiconfiguration time-dependent Hartree impurity solver for nonequilibrium dynamical mean-field theory

Nonequilibrium dynamical mean-field theory (DMFT) solves correlated lattice models by obtaining their local correlation functions from an effective model consisting of a single impurity in a self-consistently determined bath. The recently developed mapping of this impurity problem from the Keldysh time contour onto a time-dependent single-impurity Anderson model (SIAM) [C. Gramsch et al., Phys. Rev. B 88, 235106 (2013)] allows one to use wave function-based methods in the context of nonequilibrium DMFT. Within this mapping, long times in the DMFT simulation become accessible by an increasing number of bath orbitals, which requires efficient representations of the time-dependent SIAM wave function. These can be achieved by the multiconfiguration time-dependent Hartree (MCTDH) method and its multi-layer extensions. We find that MCTDH outperforms exact diagonalization for large baths in which the latter approach is still within reach and allows for the calculation of SIAMs beyond the system size accessible by exact diagonalization. Moreover, we illustrate the computation of the self-consistent two-time impurity Green's function within the MCTDH second quantization representation.

cond-mat.str-el↗

Dynamics of fluctuations in a quantum system

"\textit{The noise is the signal}"[R. Landauer, Nature \textbf{392}, 658 (1998)] emphasizes the rich information content encoded in fluctuations. This paper assesses the dynamical role of fluctuations of a quantum system driven far from equilibrium, with laser-aligned molecules as a physical realization. Time evolutions of the expectation value and the uncertainty of a standard observable are computed quantum mechanically and classically. We demonstrate the intricate dynamics of the uncertainty that are strikingly independent of those of the expectation value, and their exceptional sensitivity to quantum properties of the system. In general, detecting the time evolution of the fluctuations of a given observable provides information on the dynamics of correlations in a quantum system.

quant-ph↗

Noise Equivalent Counts Based Emission Image Reconstruction Algorithm of Tomographic Gamma Scanning

Tomographic Gamma Scanning (TGS) is a technique used to assay the nuclide distribution and radioactivity in nuclear waste drums. Both transmission and emission scans are performed in TGS and the transmission image is used for the attenuation correction in emission reconstructions. The error of the transmission image, which is not considered by the existing reconstruction algorithms, negatively affects the final results. An emission reconstruction method based on Noise Equivalent Counts (NEC) is presented. Noises from the attenuation image are concentrated to the projection data to apply the NEC Maximum-Likelihood Expectation-Maximization algorithm. Experiments are performed to verify the effectiveness of the proposed method.

nucl-ex↗

The application of spectrum standardization method for carbon analysis in coal using laser-induced breakdown spectroscopy

Measurements of carbon content in coal using laser-induced breakdown spectroscopy (LIBS) is limited by its low measurement precision and accuracy. A spectrum standardization method was proposed to achieve both reproducible and accurate results for the quantitative analysis of carbon content in coal with LIBS. The proposed method utilized the molecular carbon emissions to compensate the diminution of atomic carbon emission caused by matrix effect. The compensated carbon line intensities were further converted into an assumed standard state with fixed plasma temperature, electron density, and total number density of elemental carbon, which is proportional to its concentration in the coal samples. In addition, in order to obtained better compensation for total carbon number density fluctuations, an iterative algorithm was applied, which is different from our previous standardization calculations. The modified spectrum standardization model was applied to the measurement of carbon content in 24 bituminous coal samples. The results demonstrated that the proposed method had superior performance over the generally applied normalization methods. The average relative standard deviation, the coefficient of determination, the root-mean-square error of prediction, and the average maximum relative error for the modified model were 3.44%, 0.83, 2.71%, and 12.61%, respectively, while the corresponding values for the normalization with segmental spectrum area were 6.00%, 0.75, 3.77%, and 15.40%, respectively, showing an overwhelming improvement.

physics.optics↗

A model combining spectrum standardization and dominant factor based partial least square method for carbon analysis in coal by laser-induced breakdown spectroscopy

Successful quantitative measurement of carbon content in coal using laser-induced breakdown spectroscopy (LIBS) is suffered from relatively low precision and accuracy. In the present work, the spectrum standardization method was combined with the dominant factor based partial least square (PLS) method to improve the measurement accuracy of carbon content in coal by LIBS. The combination model employed the spectrum standardization method to convert the carbon line intensity into standard state for more accurately calculating the dominant carbon concentration, and then applied PLS with full spectrum information to correct the residual errors. The combination model was applied to the measurement of carbon content for 24 bituminous coal samples. The results demonstrated that the combination model could further improve the measurement accuracy compared with both our previously established spectrum standardization model and dominant factor based PLS model using spectral area normalized intensity for the dominant factor model. For example, the coefficient of determination (R2), the root-mean-square error of prediction (RMSEP), and the average relative error (ARE) for the combination model were 0.99, 1.75%, and 2.39%, respectively; while those values for the spectrum standardization method were 0.83, 2.71%, and 3.40%, respectively; and those values for the dominant factor based PLS model were 0.99, 2.66%, and 3.64%, respectively.

physics.optics↗

HERMES: A Hierarchical Broadcast-Based Silicon Photonic Interconnect for Scalable Many-Core Systems

Optical interconnection networks, as enabled by recent advances in silicon photonic device and fabrication technology, have the potential to address on-chip and off-chip communication bottlenecks in many-core systems. Although several designs have shown superior power efficiency and performance compared to electrical alternatives, these networks will not scale to the thousands of cores required in the future. In this paper, we introduce Hermes, a hybrid network composed of an optimized broadcast for power-efficient low-latency global-scale coordination and circuit-switch sub-networks for high-throughput data delivery. This network will scale for use in thousand core chip systems. At the physical level, SoI-based adiabatic coupler has been designed to provide low-loss and compact optical power splitting. Based on the adiabatic coupler, a topology based on 2-ary folded butterfly is designed to provide linear power division in a thousand core layout with minimal cross-overs. To address the network agility and provide for efficient use of optical bandwidth, a flow control and routing mechanism is introduced to dynamically allocate bandwidth and provide fairness usage of network resources. At the system level, bloom filter-based filtering for localization of communication are designed for reducing global traffic. In addition, a novel greedy-based data and workload migration are leveraged to increase the locality of communication in a NUCA (non-uniform cache access) architecture. First order analytic evaluation results have indicated that Hermes is scalable to at least 1024 cores and offers significant performance improvement and power savings over prior silicon photonic designs.

cs.AR↗

Early Observations on Performance of Google Compute Engine for Scientific Computing

Although Cloud computing emerged for business applications in industry, public Cloud services have been widely accepted and encouraged for scientific computing in academia. The recently available Google Compute Engine (GCE) is claimed to support high-performance and computationally intensive tasks, while little evaluation studies can be found to reveal GCE's scientific capabilities. Considering that fundamental performance benchmarking is the strategy of early-stage evaluation of new Cloud services, we followed the Cloud Evaluation Experiment Methodology (CEEM) to benchmark GCE and also compare it with Amazon EC2, to help understand the elementary capability of GCE for dealing with scientific problems. The experimental results and analyses show both potential advantages of, and possible threats to applying GCE to scientific computing. For example, compared to Amazon's EC2 service, GCE may better suit applications that require frequent disk operations, while it may not be ready yet for single VM-based parallel computing. Following the same evaluation methodology, different evaluators can replicate and/or supplement this fundamental evaluation of GCE. Based on the fundamental evaluation results, suitable GCE environments can be further established for case studies of solving real science problems.

cs.DC↗

The Cloud's Cloudy Moment: A Systematic Survey of Public Cloud Service Outage

Inadequate service availability is the top concern when employing Cloud computing. It has been recognized that zero downtime is impossible for large-scale Internet services. By learning from the previous and others' mistakes, nevertheless, it is possible for Cloud vendors to minimize the risk of future downtime or at least keep the downtime short. To facilitate summarizing lessons for Cloud providers, we performed a systematic survey of public Cloud service outage events. This paper reports the result of this survey. In addition to a set of findings, our work generated a lessons framework by classifying the outage root causes. The framework can in turn be used to arrange outage lessons for reference by Cloud providers. By including potentially new root causes, this lessons framework will be smoothly expanded in our future work.

cs.DC↗

Circumstantial-Evidence-Based Judgment for Software Effort Estimation

Expert judgment for software effort estimation is oriented toward direct evidences that refer to actual effort of similar projects or activities through experts' experiences. However, the availability of direct evidences implies the requirement of suitable experts together with past data. The circumstantial-evidence-based judgment proposed in this paper focuses on the development experiences deposited in human knowledge, and can then be used to qualitatively estimate implementation effort of different proposals of a new project by rational inference. To demonstrate the process of circumstantial-evidence-based judgment, this paper adopts propositional learning theory based diagnostic reasoning to infer and compare different effort estimates when implementing a Web service composition project with some different techniques and contexts. The exemplar shows our proposed work can help determine effort tradeoff before project implementation. Overall, circumstantial-evidence-based judgment is not an alternative but complementary to expert judgment so as to facilitate and improve software effort estimation.

cs.SE↗

Towards Technology Independent Strategies for SOA Implementations

Benefiting from the technology based strategies, Service-Oriented Architecture (SOA) has been able to achieve the general goals such as agility, flexibility, reusability and efficiency. Nevertheless, technical conditions alone cannot guarantee successful SOA implementations. As a valuable and necessary supplement, the space of technology independent strategies should also be explored. Through treating SOA system as an instance of organization and identifying the common ground on the similar process of SOA implementation and organization design, this paper uses existing work in organization theory area to inspire the research into technology independent strategies of SOA implementation. As a result, four preliminary strategies that can be applied to organizational area we identify to support SOA implementations. Furthermore, the novel methodology of investigating technology independent strategies for implementing SOA is revealed, which encourages interdisciplinary research across service-oriented computing and organization theory.

cs.SE↗

Building an Expert System for Evaluation of Commercial Cloud Services

Commercial Cloud services have been increasingly supplied to customers in industry. To facilitate customers' decision makings like cost-benefit analysis or Cloud provider selection, evaluation of those Cloud services are becoming more and more crucial. However, compared with evaluation of traditional computing systems, more challenges will inevitably appear when evaluating rapidly-changing and user-uncontrollable commercial Cloud services. This paper proposes an expert system for Cloud evaluation that addresses emerging evaluation challenges in the context of Cloud Computing. Based on the knowledge and data accumulated by exploring the existing evaluation work, this expert system has been conceptually validated to be able to give suggestions and guidelines for implementing new evaluation experiments. As such, users can conveniently obtain evaluation experiences by using this expert system, which is essentially able to make existing efforts in Cloud services evaluation reusable and sustainable.

cs.DC↗

A Factor Framework for Experimental Design for Performance Evaluation of Commercial Cloud Services

Given the diversity of commercial Cloud services, performance evaluations of candidate services would be crucial and beneficial for both service customers (e.g. cost-benefit analysis) and providers (e.g. direction of service improvement). Before an evaluation implementation, the selection of suitable factors (also called parameters or variables) plays a prerequisite role in designing evaluation experiments. However, there seems a lack of systematic approaches to factor selection for Cloud services performance evaluation. In other words, evaluators randomly and intuitively concerned experimental factors in most of the existing evaluation studies. Based on our previous taxonomy and modeling work, this paper proposes a factor framework for experimental design for performance evaluation of commercial Cloud services. This framework capsules the state-of-the-practice of performance evaluation factors that people currently take into account in the Cloud Computing domain, and in turn can help facilitate designing new experiments for evaluating Cloud services.

cs.DC↗

Effort-Oriented Classification Matrix of Web Service Composition

Within the service-oriented computing domain, Web service composition is an effective realization to satisfy the rapidly changing requirements of business. Therefore, the research into Web service composition has unfolded broadly. Since examining all of the related work in this area becomes a mission next to impossible, the classification of composition approaches can be used to facilitate multiple research tasks. However, the current attempts to classify Web service composition do not have clear objectives. Furthermore, the contexts and technologies of composition approaches are confused in the existing classifications. This paper proposes an effort-oriented classification matrix for Web service composition, which distinguishes between the context and technology dimension. The context dimension is aimed at analyzing the environment influence on the effort of Web service composition, while the technology dimension focuses on the technique influence on the effort. Consequently, besides the traditional classification benefits, this matrix can be used to build the basis of cost estimation for Web service composition in future research.

cs.SE↗

Software Cost Estimation Framework for Service-Oriented Architecture Systems using Divide-and-Conquer Approach

Due to the complexity of Service-Oriented Architecture (SOA), cost and effort estimation for SOA-based software development is more difficult than that for traditional software development. Unfortunately, there is a lack of published work about cost and effort estimation for SOA-based software. Existing cost estimation approaches are inadequate to address the complex service-oriented systems. This paper proposes a novel framework based on Divide-and-Conquer (D&C) for cost estimation for building SOA-based software. By dealing with separately development parts, the D&C framework can help organizations simplify and regulate SOA implementation cost estimation. Furthermore, both cost estimation modeling and software sizing work can be satisfied respectively by switching the corresponding metrics within this framework. Given the requirement of developing these metrics, this framework also defines the future research in four different directions according to the separate cost estimation sub-problems.

cs.SE↗

Towards a Taxonomy of Performance Evaluation of Commercial Cloud Services

Cloud Computing, as one of the most promising computing paradigms, has become increasingly accepted in industry. Numerous commercial providers have started to supply public Cloud services, and corresponding performance evaluation is then inevitably required for Cloud provider selection or cost-benefit analysis. Unfortunately, inaccurate and confusing evaluation implementations can be often seen in the context of commercial Cloud Computing, which could severely interfere and spoil evaluation-related comprehension and communication. This paper introduces a taxonomy to help profile and standardize the details of performance evaluation of commercial Cloud services. Through a systematic literature review, we constructed the taxonomy along two dimensions by arranging the atomic elements of Cloud-related performance evaluation. As such, this proposed taxonomy can be employed both to analyze existing evaluation practices through decomposition into elements and to design new experiments through composing elements for evaluating performance of commercial Cloud services. Moreover, through smooth expansion, we can continually adapt this taxonomy to the more general area of evaluation of Cloud Computing.

cs.DC↗

On a Catalogue of Metrics for Evaluating Commercial Cloud Services

Given the continually increasing amount of commercial Cloud services in the market, evaluation of different services plays a significant role in cost-benefit analysis or decision making for choosing Cloud Computing. In particular, employing suitable metrics is essential in evaluation implementations. However, to the best of our knowledge, there is not any systematic discussion about metrics for evaluating Cloud services. By using the method of Systematic Literature Review (SLR), we have collected the de facto metrics adopted in the existing Cloud services evaluation work. The collected metrics were arranged following different Cloud service features to be evaluated, which essentially constructed an evaluation metrics catalogue, as shown in this paper. This metrics catalogue can be used to facilitate the future practice and research in the area of Cloud services evaluation. Moreover, considering metrics selection is a prerequisite of benchmark selection in evaluation implementations, this work also supplements the existing research in benchmarking the commercial Cloud services.

cs.DC↗

Correlated dynamics of the motion of proton-hole wave-packets in a photoionized water cluster

We explore the correlated dynamics of an electron-hole and a proton after ionization of a protonated water cluster by extreme ultra-violet (XUV) light. An ultrafast decay mechanism is found in which the proton--hole dynamics after the ionization are driven by electrostatic repulsion and involve a strong coupling between the nuclear and electronic degrees of freedom. We describe the system by a quantum-dynamical approach and show that non-adiabatic effects are a key element of the mechanism by which electron and proton repel each other and become localized at opposite sides of the cluster. Based on the generality of the decay mechanism, similar effects may be expected for other ionized systems featuring hydrogen bonds.

physics.chem-ph↗

A Non-linearized PLS Model Based on Multivariate Dominant Factor for Laser-induced Breakdown Spectroscopy Measurements

A multivariate dominant factor based non-linearized PLS model is proposed. The intensities of different lines were taken to construct a multivariate dominant factor model, which describes the dominant concentration information of the measured species. In constructing such a multivariate model, non-linear transformation of multi characteristic line intensities according to the physical mechanisms of lased induced plasma spectrum were made, combined with linear-correlation-based PLS method, to model the nonlinear self-absorption and inter-element interference effects. This enables the linear PLS method to describe non-linear relationship more accurately and provides the statistics-based PLS method with physical backgrounds. Moreover, a secondary PLS is applied utilizing the whole spectra information to further correct the model results. Experiments were conducted using standard brass samples. Taylor expansion was applied to make the nonlinear transformation to describe the self-absorption effect of Cu. Then, line intensities of another two elements, Pb and Zn, were taken into account for inter-element interference. The proposed method shows a significant improvement when compared with conventional PLS model. Results also show that, even compared with the already-improved baseline dominant-factor-based PLS model, the present PLS model based on the multivariate dominant factor yields the same calibration quality (R2=0.999) while decreasing the RMSEP from 2.33% to 1.97%. The overall RMSE was also improved to 1.05% from 1.27%.

physics.optics↗