Characteristics and genesis of clay minerals in the northern margin of the Qaidam Basin

In order to develop appropriate reservoir protection measures in the northern margin of the Qaidam Basin and improve its oil and gas recovery efficiency,characteristics of clay minerals from eleven clay rock samples from the northern margin of the Qaidam Basin were investigated using X-ray diffraction analysis,the Scanning Electron Microscope（SEM）and energy spectrum analysis.Clay mineral composition and distribution characteristics of the main hydrocarbon reservoirs,i.e.,from the Jurassic and Paleogene-Neogene,were explored.We analyzed the main factors which affected these attributes.The results show that the major clay minerals in the northern margin are chlorite,kaolinite,illite,smectite and illite/smectite inter-stratified minerals.Illite is the most widely spread clay mineral in this area. Chlorite is mainly found in the entire Neogene and in shallow horizons of the Paleogene.Smectite is enriched in the shallow Paleogene-Neogene.There are large amounts of kaolinite and illite/smectite inter-stratified minerals in the Jurassic.The major factors affecting the different development of clay minerals in the region are properties of parent rocks,paleoclimate and paleowater media conditions, diagenesis transformation,tectonic and terrain conditions.

Continuous Multipartite Entangled Representation and Its Wigner Operator and Marginal Distribution

By extending the EPR bipartite entanglement to multipartite case, we briefly introduce a continuous multipartite entangled representation and its canonical conjugate state in the multi-mode Fock space, analyze their Schmidt decompositions and give their entangling operators. Furthermore, based on the above analysis we also find the n-mode Wigner operator. In doing so we may identify the physical meaning of the marginal distribution of the Wigner function.

Multi-population and diffusion UMDA for dynamic multimodal problems

In dynamic environments,it is important to track changing optimal solutions over time.Univariate marginal distribution algorithm（UMDA） which is a class algorithm of estimation of distribution algorithms attracts more and more attention in recent years.In this paper a new multi-population and diffusion UMDA（MDUMDA） is proposed for dynamic multimodal problems.The multi-population approach is used to locate multiple local optima which are useful to find the global optimal solution quickly to dynamic multimodal problems.The diffusion model is used to increase the diversity in a guided fashion,which makes the neighbor individuals of previous optimal solutions move gradually from the previous optimal solutions and enlarge the search space.This approach uses both the information of current population and the part history information of the optimal solutions.Finally experimental studies on the moving peaks benchmark are carried out to evaluate the proposed algorithm and compare the performance of MDUMDA and multi-population quantum swarm optimization（MQSO） from the literature.The experimental results show that the MDUMDA is effective for the function with moving optimum and can adapt to the dynamic environments rapidly.

Two-Variable Hermite Polynomial Excitation of Two-Mode Squeezed Vacuum State as Squeezed Two-Mode Number State

We find that the squeezed two-mode number state is just a two-variable Hermite polynomial excitation of thetwo-mode squeezed vacuum state (THPES).We find that the Wigner function of THPES and its marginal distributionsare just related to two-variable Hermite polynomials (or Laguerre polynomials) and that the tomogram of THPES canbe expressed by one-mode Hermite polynomial.

Social Energy:Mining Energy From the Society

The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social systems.From this perspective,we define "social energy" as a complex sociotechnical system of energy systems,social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system interactions.The recent advancement in intelligent technology,including artificial intelligence and machine learning technologies,sensing and communication in Internet of Things technologies,and massive high performance computing and extreme-scale data analytics technologies,enables the possibility of substantial advancement in socio-technical system optimization,scheduling,control and management.In this paper,we provide a discussion on the nature of energy,and then propose the concept and intention of social energy systems for electrical power.A general methodology of establishing and investigating social energy is proposed,which is based on the ACP approach,i.e., "artificial systems"(A), "computational experiments"(C) and "parallel execution"(P),and parallel system methodology.A case study on the University of Denver(DU) campus grid is provided and studied to demonstrate the social energy concept.In the concluding remarks,we discuss the technical pathway,in both social and nature sciences,to social energy,and our vision on its future.

Some Properties of Two-mode Displaced Excited Squeezed Vacuum States

In this paper,two-mode displaced excited squeezed vacuum states (TDESVS) are constructed and theirnormalization and completeness are investigated.Using the entangled state representation and Weyl ordering formof the Wigner operator,the Wigner functions of TDESVS are obtained and the variations of Wigner functions withthe parameters m,n and r are investigated.Besides,two marginal distributions of Wigner functions of TDESVS areobtained,which exhibit some entangled properties of the two-particle's system in TDESVS.

Design Tide Hydrograph with A Given Risk Threshold by A Copula-Based Multivariate Method

This paper describes the development of a T-year design tide hydrograph （DTH）. A core innovation is that the proposed technique uses the design risk threshold and copula-based conditional risk probability to analyze the optimal combination of high waters and low waters of the DTH. A brief description of the method is presented. The in situ semi-diurnal tide data at the coast of Jiangsu Province in China are analyzed. Marginal distributions for high waters and low waters of tides are examined. Furthermore, the joint distributions, condition risk probabilities and risk thresholds of high waters and low waters are presented. Results of the DTH from the proposed method are compared with those from the traditional same-multiple enlarging design approach. It is demonstrated that the proposed method is preferable.

A new approach to obtaining positive-definite Wigner operator for two entangled particles with different masses

Based on our previously proposed Wigner operator in entangled form, we introduce the generalized Wigner operator for two entangled particles with different masses, which is expected to be positive-definite. This approach is able to convert the generalized Wigner operator into a pure state so that the positivity can be ensured. The technique of integration within an ordered product of operators is used in the discussion.

Husimi Functions of Excited Squeezed Vacuum States

Based on the Husimi operator in pure state form introduced by Fan et al,which is a squeezed coherentstate projector,and the technique of integration within an ordered product (IWOP) of operators,as well as the entangledstate representations,we obtain the Husimi functions of the excited squeezed vacuum states (ESVS) and two marginaldistributions of the Husimi functions of the ESVS.

Wigner functions and tomograms of the even and odd binomial states

Using the coherent state representation of Wigner operator and the technique of integration within an ordered product （IWOP） of operators, the Wigner functions of the even and odd binomial states （EOBSs） are obtained. The physical meaning of the Wigner functions for the EOBSs is given by means of their marginal distributions. Moreover, the tomograms of the EOBSs are calculated by virtue of intermediate coordinate-momentum representation in quantum optics.

Distribution Locational Marginal Pricing Based Equilibrium Optimization Strategy for Data Center Park with Spatial-temporal Demand-side Resources

This paper proposes a distribution locational marginal pricing(DLMP) based bi-level Stackelberg game framework between the internet service company(ISC) and distribution system operator(DSO) in the data center park. To minimize electricity costs, the ISC at the upper level dispatches the interactive workloads(IWs) across different data center buildings spatially and schedules the battery energy storage system temporally in response to DLMP. Photovoltaic generation and static var generation provide extra active and reactive power. At the lower level, DSO calculates the DLMP by minimizing the total electricity cost under the two-part tariff policy and ensures that the distribution network is uncongested and bus voltage is within the limit. The equilibrium solution is obtained by converting the bi-level optimization into a single-level mixed-integer second-order cone programming optimization using the strong duality theorem and the binary expansion method. Case studies verify that the proposed method benefits both the DSO and ISC while preserving the privacy of the ISC. By taking into account the uncertainties in IWs and photovoltaic generation, the flexibility of distribution networks is enhanced, which further facilitates the accommodation of more demand-side resources.

Calculation Model and Allocation Strategy of Network Usage Charge for Peer-to-peer and Community-based Energy Transaction Market

The emergence of prosumers in distribution systems has enabled competitive electricity markets to transition from traditional hierarchical structures to more decentralized models such as peer-to-peer(P2P)and community-based(CB)energy transaction markets.However,the network usage charge(NUC)that prosumers pay to the electric power utility for network services is not adjusted to suit these energy transactions,which causes a reduction in revenue streams of the utility.In this study,we propose an NUC calculation method for P2P and CB transactions to address holistically economic and technical issues in transactive energy markets and distribution system operations,respectively.Based on the Nash bargaining(NB)theory,we formulate an NB problem for P2P and CB transactions to solve the conflicts of interest among prosumers,where the problem is further decomposed into two convex subproblems of social welfare maximization and payment bargaining.We then build the NUC calculation model by coupling the NB model and AC optimal power flow model.We also employ the Shapley value to allocate the NUC to consumers fairly for the NUC model of CB transactions.Finally,numerical studies on IEEE 15-bus and 123-bus distribution systems demonstrate the effectiveness of the proposed NUC calculation method for P2P and CB transactions.

Speedup in classical simulation of Gaussian boson sampling

Gaussian boson sampling is an alternative model for demonstrating quantum computational supremacy,where squeezed states are injected into every input mode, instead of applying single photons as in the case of standard boson sampling. Here by analyzing numerically the computational costs, we establish a lower bound for achieving quantum computational supremacy for a class of Gaussian bosonsampling problems. Specifically, we propose a more efficient method for calculating the transition probabilities, leading to a significant reduction of the simulation costs. Particularly, our numerical results indicate that one can simulate up to 18 photons for Gaussian boson sampling at the output subspace on a normal laptop, 20 photons on a commercial workstation with 256 cores, and about 30 photons for supercomputers. These numbers are significantly smaller than those in standard boson sampling, suggesting that Gaussian boson sampling could be experimentally-friendly for demonstrating quantum computational supremacy.

Transactive Energy Systems in Active Distribution Networks:A Comprehensive Review

Increasing penetration of distributed energy resources(DERs)introduced by different stakeholders,poses an immense challenge to power network operators.The traditional direct control of local DERs has the risk of violating preferences and privacies of stakeholders.A promising solution for supplydemand coordination is to utilize a transactive energy(TE)based energy management method to indirectly coordinate the local DERs,which enables the distribution-level energy providers,consumers,and prosumers to trade energy with each other through a transactive energy system(TES)trading platform.This paper provides a comprehensive review of a TES and presents a detailed classification from different perspectives,including TES participants,structure,commodity,clearing method,and solution algorithm.The presented detailed component-scale classification can be used as a reference for future TES designs.Finally,two additional market tools,i.e.,penalty mechanism and loss allocation mechanism,are discussed as future focus areas,which can be seen as necessary complements to a TES for ensuring feasibility and fairness of energy trading.

Bivariate joint distribution analysis of the flood characteristics under semiparametric copula distribution framework for the Kelantan River basin in Malaysia

Flood is becoming the severe hydrologic issue at the Kelantan River basin in Malaysia.The joint distribution analysis amongst multiple interacting flood characteristics,i.e.,flood peak discharge flow,volume,and duration series usually provide a comprehensive understanding of the hydrologic risk assessments through visualizing the multivariate exceedance probability or return periods.The traditional copulas-based methodology is frequently employed under parametric settings where parametric family functions are often employed to model univari-ate marginal distribution before capturing their dependence structure.Actually,no universal rules and literature are imposed to model any flood vectors through any fixed or predefined density function,which would follow the different distribution and needs to model by fitting most parsimonious function.Also,the copula function already relaxes the restriction of selecting marginal distributions from the same distribution families.Therefore,incorporation of non-parametric kernel density estimations or KDE would be much stable and less biased smoothing alternatives than the parametric approach.In this literature,the semi-parametric copula-based methodology is incorporated,where the flood marginals are modelled under the kernel functions and applied as a case study for 50 years annual maximum(AM)flood samples of the Kelantan River basin at the Gulliemard Bridge gauge station in Malaysia.The Archimedean families copulas(i.e.,Frank,Gumbel and Clayton)and Elliptical copula(i.e.,Gaussian copula)are tested,and thus best-fitted copulas are employed to model the bivariate joint distribution amongst flood characteristics,and which further employed to derive joint and conditional return periods.

Effect of atmospheric parameters on fine particulate concentration in suburban Shanghai

A study was conducted on the effect of atmospheric parameters, including temperature, wind speed, and relative humidity, on fine particulate mass concentrations measured in Jiading District of Shanghai, China, during the period from January 2009 to January 2010. A sensitivity analysis was applied to investigate the interaction between atmospheric parameters and particulate mass concentration. The experiment revealed that the concentration of particulates increased with particle size from 0.1 to 1.0 μm, and decreased with the increase of particle size from 1.0 to 2.5 μm. The effects of atmospheric parameters on fine mass concentrations were significantly particle size-dependent. The PM1.0-2.5 may come from the size increase of smaller particulates after moisture absorption, And the variation of concentrations of PM0.1-l.0 was mainly attributed to the accumulation of PM0.1. The ventilation index and dilution index were calcu- lated on the basis of data collected in December 2009. A correlation analysis indicated that there was a significant relation between these two indexes and the particulate concentration by examining the three particle size ranges, 0.0-0.1, 0.1-1.0, and 1,0-2.5 μm. The Spearman correlation coefficients that related the ventilation index to the concentration for the three particle size ranges were -0.45, -0.56 and -0.47, respectively, while the coefficients that related the dilution index to the concentration were -0.36, -0.42 and -0.45, respectively.