Statistics of energy spectra of a strongly disordered system of interacting electrons

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表面增强拉曼散射

表面增强拉曼散射

601
1. INTRODUCTION
SERS: surface-enhanced Raman spectroscopy Raman scattering: inelastic scattering of a photon from a molecule in which the frequency change precisely matches the difference in vibrational energy levels LSPR: localized surface plasmon resonance
Surface-Enhanced Raman Spectroscopy
Paul L. Stiles, Jon A. Dieringer, Nilam C. Shah, and Richard P. Van Duyne
Department of Chemistry, Northwestern University, Evanston, Illinois 60208; email: vanduyne@
Annu. Rev. Anal. Chem. 2008. 1:601–26 First published online as a Review in Advance on March 18, 2008 The Annual Review of Analytical Chemistry is online at This article’s doi: 10.1146/annurev.anchem.1.031207.112814 Copyright c 2008 by erved 1936-1327/08/0719-0601$20.00
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科学文献

科学文献

Analysis of Electron and Muon Size Spectra of EAS R.Glasstetter,T.Antoni,W.D.Apel,F.Badea,K.Bekk,K.Bernl¨o hr,E.Bollmann,H.Bozdog,I.M.Brancus,A.Chilingarian,K.Daumiller,P.Doll,J.Engler,F.Feßler,H.J.Gils, R.Haeusler,W.Hafemann,A.Haungs,D.Heck,J.R.H¨o randel,T.Holst,K.-H.Kampert, J.Kempa,H.O.Klages,J.Knapp,H.J.Mathes,H.J.Mayer,ke,D.M¨uhlenberg,J.Oehlschl¨a ger,M.Petcu,H.Rebel,M.Risse,M.Roth,G.Schatz,F.K.Schmidt,H.Schieler, T.Thouw,H.Ulrich,A.Vardanyan,B.Vulpescu,J.H.Weber,J.Wentz,T.Wibig,T.Wiegert,D.Wochele,J.Wochele,J.Zabierowski,Institut f¨u r Experimentelle Kernphysik,University of Karlsruhe,D-76021Karlsruhe,Germany Institut f¨u r Kernphysik,Forschungszentrum Karlsruhe,D-76021Karlsruhe,GermanyNational Institute of Physics and Nuclear Engineering,RO-7690Bucharest,RomaniaCosmic Ray Division,Yerevan Physics Institute,Yerevan36,ArmeniaDepartment of Experimental Physics,University of Lodz,PL-90950Lodz,PolandSoltan Institute for Nuclear Studies,PL-90950Lodz,PolandAbstractThe electron and muon numbers of extensive air showers in the energy region around the knee are measured by the detectors of the KASCADE array.To understand the resulting size spectra one has to take into account thefluctuations of the shower development in the atmosphere as well as the uncertainties of the applied recon-struction methods.A consistent interpretation of both spectra allows to derive a primary energy spectrum and a mass composition.1Introduction:The KASCADE–Experiment(Klages et al.,1997)at the Forschungszentrum Karlsruhe(110m a.s.l.,Ger-many)was designed to determine the different particle numbers and distributions in an extensive air shower (EAS)in quite a number of ways in the energy region around the so-called knee(10-10eV).Therefore,it consists of a200200m scintillator array with252detector stations for the detection of the extensive elec-tron and muon component and a1620m central sampling calorimeter for the measurement of individual hadrons.Additionally,there are multiwire proportional chambers and streamer tubes for muon tracking.The various types of particle detection minimize ambiguities which arise from the largefluctuations in the shower development.They enable us to derive the energy and mass of the primary particle on an event-by-event basis via multiparameter analysis methods.A different approach,which is used in this analysis,is to look at the spectra of electron and muon numbers as they are measured by the KASCADE–array and derive the primary energy spectrum from these.This is possible since the energy spectra of different primary particles transform differently to the size spectra;the muon number of an EAS is increasing with primary mass,whereas the electron number is decreasing.However,in any analysis the shower developmentfluctuations as well as the reconstruction errors have to be known quantitatively to account for systematical errors,especially if dealing with steep power law spectra.The spectra used for this analysis are based on a data set measured from Oct.1996-Nov.1998with over12 Mio.reconstructed events in a zenith angle interval from18to25.The so-called truncated muon number used in the following denotes the integrated number of muons in the region from40m to200m around the core,whereas the electron number is reconstructed over all radial distances.2Mathematics:The influence of any type of fluctuations on a certain distribution of observables or even just the transfor-mation of one observable to another is described by a Fredholm integral equation of 1st kind :(1)The lefthand side represents the evaluated size spectra for various primaries ,and the so-called kernel function is the probability for a primary of the given energy that an air shower is reconstructed with a certain shower size .Actually it is helpful to factorize the kernel function to reflect the stages of shower development,detector sampling and reconstruction:(2)with the probability,that a shower arrives at the observation level with given size ,the trigger efficiency ,which depends mainly on the number of detected particles and the probability ,taking into account the statistical and systematical reconstruction errors.To solve equation (1)for the primary spectruman appropriate parameterization of the primary spectrum is done and the spectral parameters are estimated by fitting the theoretical distribution (1)to the measured size spectra.This method allows us to use the additional information that the primary spectrum obeys a power law.In the following analysis the primary energy spectrum is parameterized as a function of five parameters.The spectral indices below and above the knee,the position of the knee ,the flux at the knee and the width of the knee ,which describes the region around the knee,where the spectral index is changing from to .3Fluctuations:s h o w e r f l u c t u a t i o n s ∆l g (N e )s h o w e r f l u c t u a t i o n s ∆l g (N µ,t r )electron number lg(N e )s t a t . r e c . e r r o r s ∆l g (N e )trunc. muon number lg(N µ,tr )Figure 1:Shower development fluctuations and statisticalreconstruction errors of shower sizes.To determine the above kernel functions one needs detailed information about the de-pendence of fluctuations on primary energy resp.showers size for the various primary par-ticles.The shower simulation code CORSIKA (Heck et al.,1998)was used with the interaction model OGSJET to obtain the necessary data.To minimize the amount of simulations the MC data set was limited to proton and iron primaries with a zenith angle of 22.For the study of the shower development fluctuations and the aver-age dependence of shower size upon primary energy the thinning option of CORSIKA was used which allowed the generation of an appro-priate large number of individual showers from3eV up to 10eV .A different data set of full simulated showers from 10eV to 10eV was used to get the detector responses from a detailed detector monte carlo.These responses where analyzed in the same way as the experi-mental data by the KASCADE reconstruction code to get the statistical and systematical errors of the recon-struction as well as the efficiencies.Figure 1shows the parameterized standard deviations resulting from this analysis.Both kind of fluctuations are well described by a normal distribution on a logarithmic scale.Since the statistical errors do not depend significantly on the type of the primary,only one function is used for the parameterization.It can be seen that for protons the shower fluctuations always are dominating,whereas for iron induced showers those are reduced by a factor of about 3.Therefore the statistical errors become important,especially for the muon component of small showers.electron number lg(N e ) e v e n t s11010101010101010Figure 2:Fit of shower size spectrum in-cluding proton fluctuations.To illustrate the effect of the fluctuations in Fig.2,the fit of the electron size spectrum using the proton kernel function and the resulting energy spectrum parameters are plotted.The data are as well described as in former analyses (Glasstetter et al.,1998)where the size spectra directly were parameterized by two power law functions.Now the fluctuations have been taken intoaccount and the values of the parameters have changed signif-icantly.The dashed line shows the hypothetical spectrum that would have been measured with the quoted primary parametersand fluctuations switched off .In Table 1the results of direct fits are listed together with theactual ones,which are obtained by separate fits to the electron and truncated muon spectra assuming a pure proton or iron com-position.Fit errors are not given because the systematical errorsby assuming the wrong composition are at least a factor of 10larger than the statistical ones.As one can see the primary spec-tral indices have become smaller by 0.1-0.2.The knee positions are also at smaller values,hence,the primary fluxes at the knee have become larger.Nevertheless,the fluxes and spectral indices above the knee,derived separately from the electron and muon spectra with these assumed pure compositions,are still inconsistent even with fluctuations taken into account.PROTONIRONno-2.835.6-3.441.3-3.04 5.2-2.88 3.7-3.224.7-2.849.0fluct.-2.58 3.0-3.027.1Table 1:Comparison of primary energy spectra fit parameters derived independently from electron and muonspectra assuming pure compositions (in PeV and in m s sr GeV ).4Spectra and Composition:The above analyses have shown that it is obviously impossible to describe the observed size spectra by anypure composition in a consistent way.On the other hand,using the presented fitting procedure there is no reason anymore to fit the size spectra separately.Therefore,a combined -minimization has been chosen to fit both size spectra simultaneously:(3)Therepresent the number of events in the bin with width and the theoretical functions are now the sum over the Fredholm integrals (1)for the two extreme primary particles (p and Fe),which should be taken as representatives for a light and heavy group of primary particles..。

能源重要的数据

能源重要的数据

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High-Temperature Industrial Heat
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Moderate water pollution
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Figure 17-16 Page 361 Slide 19
Figure 17-17 Page 361
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The Economics of Energy Production

The Economics of Energy Production

The Economics of Energy ProductionEnergy production plays a critical role in the global economy, as it provides the power necessary to fuel various industries and support the daily activities of individuals around the world. The economics of energy production is a complex and multifaceted topic that encompasses several key aspects, including cost considerations, market dynamics, and environmental impact.One of the primary factors that influence the economics of energy production is the cost of generating energy. Different sources of energy, such as coal, natural gas, nuclear power, and renewable resources like solar and wind power, have varying production costs. The cost-effectiveness of each energy source depends on factors such as the availabilityof resources, the efficiency of the technology used to generate energy, and regulatory policies that can impact production costs.In recent years, there has been a growing emphasis on the importance of transitioning towards sustainable and renewable sources of energy. This shift is largely driven by concerns over the environmental impact of traditional fossil fuels, such as coal and oil, which contribute to air pollution, greenhouse gas emissions, and climate change. Renewable energy sources, on the other hand, offer a cleaner and more sustainable alternative that can help reduce environmental harm and mitigate the effects of global warming.The economics of energy production also involves considerations of market dynamics and supply and demand factors. Energy markets are influenced by geopolitical events, technological advancements, and changes in consumer preferences. Fluctuations in energy prices can have significant impacts on the overall economy, as energy costs directly affect the production costs of industries, transportation costs, and household expenditures.Government policies and regulations also play a vital role in shaping the economics of energy production. Governments may provide subsidies or incentives to promote the development of renewable energy sources or impose regulations to limit carbonemissions and encourage investment in cleaner technologies. These policies can influence the competitiveness of different energy sources and drive innovation in the energy sector.In addition to economic factors, the social and environmental impacts of energy production are important considerations in evaluating the overall costs and benefits of different energy sources. The extraction and combustion of fossil fuels can have detrimental effects on local communities, such as air and water pollution, health risks, and land degradation. Renewable energy sources offer the potential to reduce these negative impacts and create opportunities for sustainable development.Overall, the economics of energy production is a complex and dynamic field that requires careful analysis and consideration of multiple factors. As the global economy continues to evolve, the need to transition towards cleaner and more sustainable sources of energy becomes increasingly urgent. By understanding the economic implications of energy production and investing in renewable technologies, we can create a more resilient and environmentally-friendly energy system for the future.。

基于退步控制方法的绳系卫星回收张力控制

基于退步控制方法的绳系卫星回收张力控制

2010年1月第36卷第1期北京航空航天大学学报Journa l o f Be iji ng U nivers it y of A eronauti cs and A stronauti cs January 2010V o.l 36 N o 1收稿日期:2008 12 16基金项目:国家自然科学基金资助项目(10702003)作者简介:钟 睿(1984-),男,江西赣州人,博士生,zhongru i a @.基于退步控制方法的绳系卫星回收张力控制钟 睿 徐世杰(北京航空航天大学宇航学院,北京100191)摘 要:利用退步控制方法研究了绳系卫星系统TSS(Tethered Sate llite Syste m )的平面内回收控制问题,提出了一种新的张力控制律.该控制律设计由两步组成:首先利用退步控制将摆角稳定到目标值,然后通过设计摆角的目标值实现系绳的回收和回收速度的控制.控制率设计了分段连续的目标角度方案和延时环节,可以使TSS 回收过程各状态量变化平滑.数值仿真结果表明,该控制律在圆轨道、近圆轨道和大偏心率的椭圆轨道都有很好的控制效果.关 键 词:绳系卫星系统;控制规律;退步控制方法;子星回收中图分类号:V 474.292文献标识码:A 文章编号:1001 5965(2010)01 0026 05Tensi on control strategy for TSS retrieval process based onbacksteppi ng controlm ethodZhong Rui Xu Sh iji e(School ofA stronauti cs ,B eiji ng U n i vers it y of Aeronau tics and Astronau tics ,Beiji ng 100191,C hina)Abstr act :A ne w tension control la w based on backstepping contr o lm et h od w as proposed for planar re trieva l contr o l of tethered satellite syste m (TSS).The contro l l a w was designed in t w o steps .Firstly ,the p lanar s w i n g angle w as stab ilized i n to target va l u e v ia using backsteppi n g contr o lm ethod .Then ,t h e re trieva l ve l o c ity w as controlled by design i n g appropriate pro file for the tar get va l u e .A conti n uous piece w ise profile w as a dopted f o r t h e tar get va l u e and a delay ter m was added to ensure a better retrieva lbehav i o r .Nu m erical si m u la ti o n results va lidate t h at the con tro l la w desi g ned here wo r ksw e ll f o r TSS m ission in circu lar ,near circu lar or b its and also elli p ti c al orbit w ith large eccentricity .Key wor ds :tethered satellite syste m;contr o l a l g orit h m;backsteppi n g contro l m ethod ;subsate llite re trieva l空间任务的多样性要求开发新的卫星系统.绳系卫星系统TSS(Te t h ered Satellite Syste m )已经向人们展示了其广泛的用途和应用前景,例如空间实验、空间运输、大型空间结构的构建等等.典型的TSS 可以利用绳系卷扬机构将子星释放、滞留和回收到母星中,以完成各种任务.近30年来,TSS 一直是航天领域的研究热点之一[1].TSS 回收过程的控制问题一直是研究的难点,由于系统包含有负阻尼,其动力学行为呈现不稳定的现象[2],给收绳带来了困难.很多学者都在探讨如何解决TSS 的控制,特别是回收过程的控制问题,取得一些成果.于韶华[3]等基于非线性动态理论分析,提出了速度距离控制方法,该方法实现方便且控制效果比较明显;黄奕永[4]等人对速度距离法提出了改进,扩大了二阶系统的稳定域,提高了释放速度;近年来,最优控制理论被越来越多的应用到TSS 的控制问题当中,文献[5-6]发表了大量的文献证明最优控制是解决TSS 控制的一种很好的工具;而对于最优控制问题,除了采用Pontyag i n 极大值原理推导给出状态及其协变量的一组方程进行求解外,越来越多的学者开始采用基于伪谱离散的直接配点法(pseudospectra l kno tti n g m ethods),文献[7]采用Cheby shev 伪谱离散的方法将TSS 连续时间的最优控制转化为标准的二次型问题,取得了较好的控制效果.本文提出一种新的设计思路:在系绳张力控制条件下,TSS 的控制可以认为是一个欠驱动问题,退步控制[8]应用于这类问题具有控制律设计灵活的特点,且本身具有良好的动态和稳态性能.本文研究面内情况下的TSS 的控制问题,运用退步控制理论设计了回收过程的张力控制律,并通过加入延时环节使张力变化平滑.该控制律在收绳速率上与已有的研究成果相近,但是在回收稳定性方面的性能略优.近年来对TSS 回收过程的研究大多限于圆轨道情况,对椭圆轨道的情况研究较少,而本文得到控制率可以适用的椭圆轨道偏心率范围较广.1 绳系动力学模型所研究的TSS 系统由一颗子星S 和母星M 组成.轨道坐标系建立如图1所示:x 轴沿母星速度方向,y 轴沿地心与母星连线方向.绳系问题非常复杂,为简化分析过程,作如下假设:图1 T SS 示意图1)地球视为中心重力体,TSS 母星和子星均视为质点,姿态运动不予考虑.2)子星质量远小于母星,后者的运动轨道不受前者影响.3)柔绳无质量、无弹性变形.4)作用在TSS 系统上的唯一外力是重力,忽略其他外力.5)柔绳张力沿着绳的方向,没有垂直绳方向的控制力和能量耗散.根据以上假设,TSS 的动力学方程[3]可以写为L-L2-L (v +)2cos 2=LR -3M (3cos 2sin 2-1)-Tm-1(1)L (v+)+2L(v+)-2L (v +)tan =3 LR -3M cos sin(2)L+2L+L (v+)2cos sin =-3 LR -3M sin 2cos sin +FM-1(3)式中,F 为面外推力;T 为系绳张力; 为地球引力常数;m 和M 分别表示子星和母星的质量;L 为绳长;R M 为母星到地心的距离,且R M L; 是系绳与轨道平面的夹角; 是系绳在轨道平面内的投影与x 轴的夹角;v 是近地点幅角;求导符号表示对时间t 的导数.平面情况下式(1)和式(2)可简化为L-L (v+)2= LR -3M (3sin 2 -1)-Tm-1(4)v++2LL-1(v+ )=1.5 R -3M sin 2 (5)2 摆角稳定的退步控制率退步方法的设计过程中,将一部分状态变量或状态变量的组合看成虚拟控制量,并根据Lya punov 方法对它们进行中间控制律的设计.为了方便中间控制率的设计,首先定义如下辅助变量:z 1=e +k 1 e +k 0z 0z0= e(6)式中,角度误差 e = - d ; d 是给定的目标角度;k 1和k 0为正的参数.z 1相当于一般退步控制中的中间状态误差量,易知z 1就是一个PI D 控制律且当z 1 0时, e 渐近地收敛到0.对式(6)求导,结合式(5)并考虑到一般任务中选取 d =d =0得到:z1= e +k 1e +k 0 e =-v-2LL-1(v+)+1.5 R -3M sin 2 +k 1+k 0 e(7)将2LL -1(v+)视为虚拟控制量,再令z 2=2LL -1(v+)-u (8)则z 2是中间控制误差,而u 是一个可以使z 1收敛的中间控制律.选择:u =-v+1.5 R -3M sin 2 +k 1+k 0 e +z 1(9)将式(8)和式(9)代入式(7),则有z1=-z 1-z 2(10) 选择Lyapunov 函数:V 1=12k 2z 21(11)式中k 2为正的参数,对式(11)求导得到:V1=k 2z 1(-z 1-z 2)=-k 2z 21-k 2z 1z 2(12)27第1期 钟 睿等:基于退步控制方法的绳系卫星回收张力控制由上式可见,如果z 2 0,则可以得到V1=-k 2z 21<0,从而根据Lyapunov 稳定性理论,z 1 0.为使系统稳定,接下来的任务是设计真实控制律T,使z 2 0.为求得真实的控制律,需要知道中间控制误差的时间导数,结合式(4)、式(5)、式(8)和式(9)可求得:z2=a +b T(13)其中a = R -3M [(6si n 2-2)(v+)-1.5(1+k 1)si n 2 +3LL-1sin 2 -3cos2 ]+4.5 R -4M R M sin 2 +2(v+)3-6L 2L -2(v+)+v+2(k 1+1)LL-1(v+)+(k 1+1)v-k 0-k 1-k 0 e (14)b =-2(v+)L -1m-1(15)式中的RM 和v项可由轨道动力学得到.再选取Lyapunov 函数:V 2=V 1+12z 22(16)对式(16)求导得到:V2=V1+z 2z 2=-k 2z 21-(k 2z 1-a -b T )z 2(17)由此,只需要真实控制量T 满足:k 2z 1-a -b T =k 3z 2(18)其中k 3为正的参数,则有V2=-k 2z 21-k 3z 22<0(19)系统渐近稳定.因此可得系统的真实控制律为T =b -1(k 2z 1-a -k 3z 2)(20)式中各变量在上文推导过程中均已给出.稳定回收的情况下,TSS 的轨道角速度要比绳的摆动快很多,所以控制律不会因为b =0而奇异.3 回收控制率设计上节得到的张力控制律可以满足TSS 系绳的摆角收敛到期望值 d .要实现系绳的回收,即必须满足L<0,这一点可以通过设计期望值 d 来实现,分析如下:综合式(8)和式(9)可以得到:-v+1.5 R-3M s i n 2 +k 1+k 0 e +z 1=2LL -1(v +)-z 2(21)当稳定后,摆角误差 e 、中间状态误差z 1和中间控制误差z 2都收敛到0,摆角的各阶时间导数也为0,则可以得到:L=( /p 3)0.5(1+e co s v )(e sin v +0.75si n 2 d )L(22)由此可见,绳长速率L主要和目标角度 d 有关,L<0即TSS 处于回收阶段的充要条件:e si n v +0.75sin 2 d <0(23)式(23)表明,当偏心率很小时, d 的取值范围基本为(-!/2,0),而随着偏心率的增大这一范围不断变小.重力梯度平衡时,由图1易见平衡摆角为-!/2,不妨假设子星的轨道高度低于母星,即 d 的取值范围是(-!,0),则回收的速度达到最快的充要条件是sin 2 d =-1,即 d =-!/4.此时式(23)时时满足的条件是e <0.75,这说明上文得到的张力控制律也适用于偏心率较大的椭圆轨道.在圆轨道情况下,绳长速率简化为L=∀#L (24)这与于韶华在速度距离法[3]中得到的结果相同.对控制律的分析表明,对收绳速度的控制可以通过改变目标角度 d 来实现,为了使回收过程变得平滑,设计如下的目标角度方案:d =-!/4 L b <L !L if(L )L s !L !L b -!/20!L <L s(25)式中,L i ,L b 和L s 分别为绳的初始长度和过渡过程绳长的上下域值,f (L )是一个人为设计的平滑过渡函数,满足:f (L b )=-!/4f (L s )=-!/2f(L b )=f(L s )=0(26)式(25)使回收初期,收绳速度达到最快,而当绳长在变得足够小之后,目标角度平滑地由最快速的收绳角度变化到平衡角度,以使绳长稳定.需要说明的是:前文设计控制律时假定目标角度的导数为0,而这在过渡过程中并不满足,但是由于该过程只是整个回收过程的一小部分,故影响不大.另外,如果初始时刻TSS 处于平衡状态,采用式(25)作为目标角度方案,初始的角度误差 e 比较大,造成中间状态误差z 1、控制误差z 2和时变参数a 都会比较大.由式(20)可以看出,退步控制律得到的初始张力会是一个比较大的值,即28北京航空航天大学学报2010年存在一个突变过程,这对于收绳过程是不利的.另外,系绳的张力必须为正,这一点可以通过调节参数来尽量实现,同时,在张力为负值时令其为0.为此可以将张力控制律修正为T tu r e=0.5[T(1-e-kt)+T i e-kt]+0.5|T(1-e-kt)+T i e-kt|(27)式中,T i为初始时刻绳的张力;k是一个正的常数.由式(27)可见:随着时间的推移,修正后的张力逐步逼近退步控制设计的张力,即控制率的有效性可以得到保证,而延时环节的存在推迟了波峰出现的时间,避免了突变的发生.4 数值仿真不防假设TSS任务中绳长为L=20km,(美国航空航天局NASA和意大利空间局ASI合作研制的绳系卫星系统TSS1试验的释放绳长即为20k m)子星质量m=500kg.1)圆轨道回收过程图2是TSS在圆轨道回收操作的仿真结果;其中母星运行的轨道高度为200km,各参数分别取为k0=5∀10-7,k1=1∀10-3,k2=k3=1∀10-6,k=1∀10-3.目标角度方案取为L i=20k m,L b=6km,L s=3km,f(L)=-3! 8+! 8sin!3(L-3)-!2.释放初值取为重力梯度平衡状态,由式(4)易得初始张力(即平衡张力)为T i=3m#2L,#为轨道角速度.为了作图和比较的方便,以下仿真结果按惯例将各变量的单位量归一化:时间为1/#,长度为L,张力为m#2L,角度为弧度.通过图2可以看出,本文给出的控制率在回收时间(大约相当于3.1h)上优于文献[3]的结果,而与文献[7]近似.虽然初始阶段的控制力比后者的结果大,(文献[7]的性能函数考虑了能量消耗最优)但是整个过程中摆角的波动比较小,绳长速率的最大值也更小,即回收过程更为平稳.2)椭圆轨道上TSS的回收过程图3和图4是椭圆轨道上TSS回收过程的仿真结果.TSS母星运行的轨道近地点高度均为200k m,偏心率分别为0.1和0.4.假定回收过程开始于母星运行到近地点处.各控制参数取值及目标角度方案与圆轨道情况相同.根据文献[3],椭圆轨道的TSS在垂直方向无法保持平衡,而是保持一个有界的周期运动,常值的平衡张力是不存在的,故将控制率中的初始张力修正为T i=3m n2L式中,n为平均角速度,这个初始张力可以认为是椭圆轨道TSS的平均张力.相应的,仿真结果各变量的单位量变成:时间为1/n,长度为L,张力为m n2L,角度为弧度.图2 圆轨道上T SS的回收过程图3 椭圆轨道上TSS的回收过程(e=0.1)图4 椭圆轨道上TSS的回收过程(e=0.4)从仿真结果可以看出,上文得到的张力控制律在小偏心率的椭圆轨道工作得很好,张力波动明显小于文献[3]的结果.对于大偏心率的椭圆轨道,回收过程会出现系绳短暂的释放过程,但是这对回收时间的影响有限,且整个回收过程中绳长、摆角和张力的变化都比较平滑,退步控制方法29第1期 钟 睿等:基于退步控制方法的绳系卫星回收张力控制得到的控制率具有良好的稳态和动态性能.已有文献中对大偏心率椭圆轨道情况下的TSS研究很少,故可供比较的研究成果也很少,如何避免系绳的释放过程是今后的主要研究内容之一.5 结 论仅有系绳张力作用下的TSS控制可以归结为一个欠驱动问题,可以利用退步控制来加以解决.本文利用这种设计方法得到了TSS回收过程的一种张力控制律,该控制律可以将摆角稳定到目标值,通过调节目标角度来控制回收速度.退步控制的设计过程比较灵活,能够将非线性的TSS控制问题最终转化为调节PI D参数的问题,从而具有良好的动态和稳态性能.数值仿真结果表明,本文得到的张力控制律在圆轨道和椭圆轨道情况下都能很好地控制TSS的回收过程,对工程应用有一定的参考价值.参考文献(References)[1]Cart m ellM P,M c Ken zie D J.A revie w of space tet h er research[J].Progress i n Aeros pace S ciences,2008,44:1-21[2]Kum arK D.R evi ew of dyna m i cs and con trol ofnonel ectrodyna mic tet h ered s atellite syst e m s[J].Journ al of Spacecraft and Rockets,2006,43(4):705-720[3]于绍华,刘强,杨林娜.绳系卫星系统二维平面运动和常规动力学[J].宇航学报,2000,21(4):15-24Yu Shaohua,Li u Q iang,Y ang L i nna.Regular dyna m i cs of i npla nar m oti on oftethered satelli te syste m[J].Jou r n al of As tronau tics,2000,21(4):15-24(i n Ch i nese)[4]黄奕勇,杨乐平.改进的绳系卫星系统距离速率控制律[J].上海航天,2007(3):30-33H uang Y iyong,Yang Lep i ng.The research on t he m od ified rangerate con trol l a w for tethered sat ellit e[J].Aeros pace Shangh a,i 2007(3):30-33(i n Ch i nese)[5]W illi a m s P.Op ti m al dep loy 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The power of the sun Concentrated solar power

The power of the sun Concentrated solar power

The power of the sun Concentrated solarpowerConcentrated solar power, also known as CSP, is a technology that uses mirrors or lenses to concentrate a large area of sunlight onto a small area. This concentrated light is then converted into heat, which drives a steam turbine to generate electricity. The power of the sun is harnessed in a way that is both sustainable and environmentally friendly. However, like any technology, concentrated solar power also has its challenges and limitations. From an environmental perspective, concentrated solar power offers significant benefits. It is a clean and renewable energy source that produces no greenhouse gas emissions during operation. This means that it can play a crucial role in reducing the carbon footprint of power generation, thereby contributing to efforts to combat climate change. Additionally, the use of concentrated solar power can help conserve natural resources and protect ecosystems by reducing the reliance on fossil fuels. Furthermore, concentrated solar power has the potential to create economic opportunities and drive innovation. The construction and operation of CSP plants require a skilled workforce, which can lead to job creation and economic development in the regions where these plants are located. Moreover, the continued advancement of CSP technology can spur research and development in related fields, leading to technological breakthroughs and the growth of associated industries. Despite these advantages, concentrated solar power also faces challenges that need to be addressed. One of the main limitations of CSP is its reliance on weather conditions. Cloud cover, rain, and other atmospheric factors can affect the amount of sunlight reaching the solar collectors, which in turn impacts the efficiency of power generation. This variability poses a challenge for ensuring a consistent and reliable energy supply from CSP plants. Another challenge is the high initial cost of building CSP plants. The infrastructure required for concentrated solar power, including the mirrors, receivers, and thermal storage systems, involves significant investment. While the operational costs of CSP are relatively low, the upfront capital expenditure can be a barrier to the widespread adoption of this technology, especially in comparison to the declining costs of other renewableenergy sources such as solar photovoltaic panels. Moreover, the land requirements for CSP plants can be substantial. Large areas of land are needed to accommodate the solar collectors and other infrastructure, which can lead to land use conflicts, particularly in densely populated regions or areas with competing land uses. Additionally, the environmental impact of land disturbance and habitat fragmentation needs to be carefully managed to ensure the sustainable deployment of concentrated solar power. In conclusion, the power of the sun harnessed through concentrated solar power represents a promising avenue for sustainable energy generation. Its environmental benefits, potential for economic growth, and capacity for technological innovation make it a compelling option for the future of energy production. However, it is essential to address the challenges of weather variability, high upfront costs, and land use considerations to fully realize the potential of concentrated solar power as a clean and reliable energy source. With continued research, investment, and strategic planning, concentrated solar power can play a vital role in the transition to a more sustainable and low-carbon energy future.。

太阳散发出热量的英文

太阳散发出热量的英文

太阳散发出热量的英文The Sun Emits HeatThe Sun, the central star of our solar system, plays a vital role in sustaining life on Earth. One of its most significant contributions is the emission of heat, which has a profound impact on our planet's climate and weather systems.The Sun's heat is generated through a process called nuclear fusion, which occurs in its core. In this process, hydrogen atoms fuse together to form helium, releasing an enormous amount of energy in the form of heat and light. This energy travels from the Sun's core to its surface and then radiates outward into space.When this solar radiation reaches Earth, it warms the planet's surface, influencing various climatic and weather patterns. The distribution of solar heat across the Earth's surface affects temperatures, wind patterns, and precipitation. For instance, areas thatreceive more direct sunlight, such as the equator, tend to be warmer, while regions that receive less direct sunlight, like the poles, are cooler.The heat from the Sun is essential for life on Earth. It drives the water cycle by evaporating water from oceans, rivers, and lakes, which then condenses into clouds and falls as precipitation. This cycle is crucial for replenishing freshwater sources and supporting ecosystems.Moreover, the Sun's heat influences seasonal changes. During summer, the tilt of the Earth's axis causes the Sun's rays to hit more directly, leading to higher temperatures. Conversely, in winter, the Sun's rays are more indirect, resulting in cooler temperatures.In summary, the Sun’s emission of heat is fundamental to life on Earth. It regulates our climate, drives weather patterns, and supports essential processes such as the water cycle. Understanding the Sun’s role in emitting heat helps us appreciate its significancein sustaining the delicate balance of our planet's environment.。

New Model Atmospheres Testing the Solar Spectrum in the UV

New Model Atmospheres Testing the Solar Spectrum in the UV

a r X i v :0710.1318v 1 [a s t r o -p h ] 5 O c t 20072Rodriguez-Merino et al.During the last decades several groups have developed computational codes capable to calculate model atmospheres and spectra at high resolu-tion,some of whom have allowed the public use of their codes,among others, the codes Atlas9,Atlas12and Synthe built by Kurucz4(1993a,b)and Tlusty and Synspec constructed by Hubeny&Lanz5(1992).In particular, Atlas9and Synthe codes have been used by our group to calculate the UVBLUE grid of theoretical SEDs and to investigate its potential for stel-lar and populations studies in the ultraviolet(UV)wavelength interval(see Rodriguez-Merino et al.2005for more details).The UV wavelength range has historically been challenging in many branches of modern astrophysics since the observed stellar spectra are not well reproduced by predictions of theoretical models.One possible reason is the missing opacity problem(see Holweger1970;Gustafsson et al.1975),but another probable reason is actually that most of the model atmospheres do not provide the atmosphere structure near the stellar surface,where most of the UV radiation emerges.Therefore,it is crucial to calculate new models which describe the outermost layers of the stellar atmospheres.In this work we briefly describe the structure of a new model atmosphere for the Sun which incorporates layers down to logτRoss=−13.That is,opti-cal depths more thanfive orders of magnitude thinner compared to classical models currently in use.This model has been couplet to Synthe codes for testing their compatibility and exploring the effects of such layers on the UV flux.2Model AtmospheresThe model atmospheres employed here have been developed by Cardona,Criv-ellari and Simonneau(CCS),these models use the Implicit Integral Method to solve the radiative transfer(Crivellari&Simonneau1994;Simonneau& Crivellari1993;Crivellari et al.2002);this algorithm allows a stable and pre-cise computation down to very low values ofτRoss.The models are based on approximations typical of classical models,namely,plane-parallel and homo-geneous layers,steady state,hydrostatic,local thermodynamical,and radia-tive equilibria(convection has not been included here).We have considered the continuum opacity of ten elements(H,He,C,N,O,Na,Mg,Al,Si,Ca) and for three of them also the line opacity accounting for20absorption lines (12for H,6for He,and2for Ca),which provide the large part of the ab-sorption needed to compute the atmospheric structure.Figure1displays a comparison between the temperature profile of the new model atmosphere with and without line opacity(solid thick and thin lines,respectively)and a Kurucz’s model(dotted line)with similar physical parameters(T eff=5780K, log g=4.5,[M/H]=+0.0).New Model Atmospheres3Fig.1.The temperature profile of the CCS model atmosphere,with(thick curve) and without(thin curve)line opacity,and of a Kurucz model(dotted curve)for solar physical parameters.In order to explore qualitatively the role of the most external atmospheric layers,in Fig.2(kindly provided by L.Crivellari)we track the value of the Rosseland optical depth at which the atmosphere becomes optically thin at each frequency.We can see how several strong lines and,in particular,the Lyman lines and break,which dominate the UV range,are produced in the most external layers(logτRoss∼−7to logτRoss∼−13).Currently,there are no classical model atmospheres that take into account the effects of these external regions in the SEDs of stellar models.3Synthetic SpectraOnce a model atmosphere has been computed the next step is to calculate the synthetic spectrum by solving the transfer equation at every layer in the atmosphere.Since the model here presented was not calculated within the Kurucz machinery,our main goal was to test if Synthe is able to handle extended models,and if so,run Synthe with the new model and analyze the effects of the layers at depths in the interval logτRoss∼−7–logτRoss∼−13 on the emergent spectrum.After successfully modifying the output of the solar CCS model with line opacity to be compatible with the input data required by Synthe,we computed a synthetic spectrum at high resolution (R=λ/∆λ=522000)covering the near ultraviolet interval,from2000to 4500˚A.The line list by Kurucz(1992)has been adopted to account for indi-vidual line absorption.In Figure3we display the spectra(pure continuum and4Rodriguez-Merino et al.Fig.2.Rosseland optical depth of formation of the main absorption features in a solar model as a function of frequency.The dot-dashed line displays the upper layer of the Kurucz model.Note that the UV features form well above the limiting log τROSS∼-7.continuum+line absorption)obtained with CCS model(solid line)and a Ku-rucz’s solar model(dotted line).For the sake of clarity,line spectra have been degraded with a Gaussian kernel to a resolution of FWHM=6˚A.Although we are well aware that at present it is not possible to carry out any detailed comparison between the calculated SED of the new model with either results from other codes or observed data(mainly due to the lack of line opacity and convective transport),it is interesting to note that the CCS modelfluxes are sistematically lower in the wavelength interval employed.Another interesting exercise we have conducted is the comparison of the effects on the UV-blue spectrum of different parts of the atmosphere.We have segmented the CCS model so as to have three models with different limiting optical depth at the surface:logτRoss=−13,logτRoss=−10,and logτRoss=−7.For each model we have calculated a synthetic spectrum(at R=522000).Figure4shows theflux ratios in two spectral windows,2000–2550˚A(left panels)and4000–4550˚A(right panels),using theflux of theNew Model Atmospheres5Fig.3.Near-UV synthetic solar spectra computed with Synthe using the CCS model with line opacity and Kurucz model atmospheres.Spectra are shown at a resolution of FWHM=6˚A.model with limiting depth logτRoss=−13as a reference.In the lower left panel,where we plot the ratio Fλ(logτRoss=−13)/Fλ(logτRoss=−7),we can visualize the strong effects of the external layers,which produce deeper lines.These effects might turn out to be important also in models which include non-thermal heating.4Concluding RemarksThe main result of this work is that Synthe series of codes is capable of treat-ing the CCS model atmospheres,which reach very low values ofτRoss.The analysis of the effects of extending the atmosphere indicates that at mid-UV wavelengths the effects are significant while negligible in the blue.The follow-ing steps are to extend the analysis to models with atmospheric parameters different of the Sun,to complement the opacity(both continuous and of lines) as well as to introduce more chemical species.We are in the process of includ-ing convection for intermediate and cool star models.A detailed comparison at high resolution with an observed solar atlas(Kurucz et al.1984)is also underway.6Rodriguez-Merino et al.Fig.4.Flux ratio of synthetic spectra computed from models with differentτRoss limits(see Sec.3for explanation).References1.Buzzoni,A.1995,ApJS,98,692.Crivellari,L.,&Simonneau,E.1994,ApJ,429,3313.Crivellari,L.,Cardona,O.,&Simonneau,E.2002,Astrophysics45,4804.Gustafsson,B.,Bell,R.A.,Eriksson,K.,&Nordlund,A.1975,A&A42,4075.Holweger,H.1970,A&A4,116.Hubeny,I.,&Lanz,T.1992,A&Ap,262,5017.Kurucz,R.1993a,SYNTHE Spectrum Synthesis Programs and Line Data.Ku-rucz CD-ROM No.18.Cambridge,Mass.:Smithsonian Astrophysical Observa-tory,188.Kurucz,R.1993b,ATLAS9Stellar Atmosphere Programs and2km/s grid.Ku-rucz CD-ROM No.13.Cambridge,Mass.:Smithsonian Astrophysical Obser-vatory,139.Kurucz,R.L.1992,Revista Mexicana de Astronomia y Astrofisica,23,4510.Kurucz,R.L.,Furenlid,I.,Brault,L.,&Testerman,L.1984,Solarflux atlasfrom296to1300nm,National Solar Observatory Atlas,Sunspot(Nat.Sol.Obs.:New Mexico).11.Rodr´ıguez-Merino,L.H.,Chavez,M.,Bertone,E.,&Buzzoni,A.2005,ApJ626,41112.Simonneau,E.,&Crivellari,L.1993,ApJ,409,830。

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a rX iv:c ond-ma t/987159v1[c ond-m at.m es -hall]1J ul1998Statistics of energy spectra of a strongly disordered system of interacting electrons R.Berkovits 1and B.I.Shklovskii 21The Minerva Center for the Physics of Mesoscopics,Fractals and Neural Networks,Department of Physics,Bar-Ilan University,Ramat-Gan 52900,Israel 2Theoretical Physics Institute,Department of Physics,University of Minnesota,Minneapolis MN 55455(February 1,2008)Abstract Statistics of many particle energy levels of a finite two-dimensional system of interacting electrons is numerically studied.It is shown that the statistics of these levels undergoes a Poisson to Wigner crossover as the strength of the disorder is decreased.This transition occurs at a similar strength of disorder as the one-electron delocalization crossover in a finite 2d system and develops almost simultaneously at all energies.We interpret this crossover in terms of delocalization in the space of occupation numbers of strongly bound and compact electron-hole pairs (excitons).PACS numbers:71.55.Jv,71.27.+a,73.20.DxTypeset using REVT E XI.INTRODUCTIONThe statistics of the quantum energy spectra of a disordered system of noninteracting electrons,for example,the Anderson model,was shown to be a good diagnostic tool to study an insulator-metal transition[1].It was discovered that the crossover from Poisson distribution of the nearest neighbor level spacings to a Wigner distribution sharpens with the system size.Finite size scaling then permits tofind out whether the transition exists and if it does to calculate quite accurately transition point and indexes[1,2].Recently attention has started to shift in the direction of spectral statistics of the total energy of afinite disordered system of interacting electrons[3–8].Good examples of such systems are quantum dots(here we are talking about the energies of the excited states of the dot and not about the charging spectrum).All previous works that we know of deal with metallic systems which are well above insulator-metal transition.For such system a Poisson-Wigner(P-W)crossover was predicted with a growing energy or interaction strength [3–6,8].The relation of this crossover to delocalization in Fock space and the decay of one electron states was discussed[3].The intriguing question of whether such statistics can work as a tool to study insulator-metal transition has not yet been addressed.In this paper we concentrate on the two-dimensional case where the very existence of a transition in an interacting system is under debate for a long time.We started this work by exploring whether we can obtain any evidence for the transition by studying thefinite size effects in the statistics of levels of the total energy of a many particle system.As far as we know this is thefirst study of such statistics at the insulating side of the delocalization crossover and at the crossover itself.We did notfind any conclusive evidence for this crossover.Instead we found that the delocalization crossover as function of the decreasing disorder generates a P-W crossover in the excited state statistics which takes place almost uniformly at all energies larger than the single level spacing(the energy of the many body excited states are calculated from the many body ground state).We interpret the excited states with high energies as consisting of several electron-hole excitations.Eachelectron-hole pair is bound by Coulomb interaction.We call such excitations excitons.At strong enough disorder states are localized in the space of states with different number of excitons or,in other words,states of very close energies but with different number of excitons do not mix coherently.As a result,the nearest level distribution function of many body states is Poissonian.With decreasing disorder the rate of decay of an exciton to smaller energy excitons becomes of the order of spacing between many particle levels.The fact that this P-W crossover is almost independent on energy and interaction differs drastically from what happens in metallic samples[3–6,8].This occurs because the density of states of the excitons and the exciton-exciton interactions are different from the ones for weakly interacting electron-hole pairs in a metal.II.MODELThe numerical study is based on the following interacting many-particle tight-binding Hamiltonian:H=k,j ǫk,j a†k,j a k,j−Vk,j(a†k,j+1a k,j+a†k+1,j a k,j)+h.c+H int,(1)whereǫk,j is the energy of a site(k,j),chosen randomly between−W/2and W/2with uni-form probability,and V is a constant hopping matrix element.The interaction Hamiltonian is given by:H int=Uk,j>l,pa†k,j a k,j a†l,p a l,pWe will use the energy level statistics as an indication of the Anderson transition in Fock space.A convenient way to characterize the change in the statistics of a system proposed in Ref.[1]is to study the parameterγdefined as∞2P(s)ds−e−πγ=for energies E>2∆(where∆is the the single electron level spacing)is rather uniform and does not depend strongly on interaction strength nor on excitation energy.This feature becomes more pronounced as the disorder increases and is in strong contrast to the situation in the metallic regime,in which interesting features were seen as function of the interaction strength and excitation energy.This behavior clearly shows that at a large W the different high energy many particle states can be close in energy but nevertheless can have small repulsion,i.e.,interactions do not couple different many particle states no matter what energy is available.We interpret this behavior as the result of the high energy many particle states being composed of several electron-hole excitations(excitons).Neighboring many particle states usually are composed of a different number of excitons and are related by a very weak interaction matrix element between them no matter how strong the interactions are.Thus,no repulsion between the states appears and the statistics is essentially Poissonic for any interaction strength or energy. The P-W crossover as the disorder W decreases is rather uniform and shows no strong dependence on energy or interaction strength(as long as one is still above the transition and the interaction U>2V).We interpret this crossover as result of the delocalization of the system in the space of states with different number of excitons which happens once the matrix element for the decay of a typical exciton into two smaller ones becomes of the order of the spacing between many particle levels.The energy independent P-W crossover revealed here differs drastically from the pre-dictions and calculations made for Fock space delocalization in metallic systems[3–8].We relate this fact to the difference between the excitons of the insulating phase and the weakly interacting electron-hole pairs of the metallic samples.Contrary to the latter ones,excitons consist of an electron and a hole strongly bounded to each other by the Coulomb interaction. In the limit of large W and U in the classical Coulomb glass this exciton is just the classical compact electron-hole pair excitation of Ref.[10].Due to the existence of the Coulomb gap, electron-hole excitations corresponding to the transfer of an electron by a small distance (compact pair)are known to have a constant density of states at small energies.On theother hand,in a metallic dot the joint density of states of weakly interacting electron-hole pairs is linear in energy.We expect that such a difference is preserved in the quantum system.Tofind the P-W crossover we have to use the density of states of excitons and the matrix elements for an exciton decay.We have already mentioned that there is a drastic difference between the exciton density of states of metallic and insulating samples.The matrix elements of the exciton decay should be different from the matrix element of the emission of an electron-hole pair by a free electron used in Refs.[3–7]as well.Thus a drastic difference between the P-W crossovers for metallic and insulating cases seems to be natural.Unfortunately we could not prove the uniform energy P-W crossover in the insulating case.In Fig.3we present a more quantitative description of the P-W crossover.We show the results forγaveraged over3%and10%of the low lying many particle energy levels for intermediate values of the interaction(U=8V,12V,16V)and for different lattice sizes and electron numbers.It is obvious that in all casesγincreases as the disorder W is enhanced. This is a possible indication of the signature of the single electron delocalization crossover on the many particle spectrum.There is no significant difference between the values ofγfor3%and10%of the spectrum,nor a strong dependence on interaction strength,so that crossover indeed happens rather uniformly in energy and interaction strength.As larger values of disorder are approached the difference becomes even smaller and the many particle spectrum becomes even more uniform.Because not much depends on energy there is an a priori chance that this crossover somehow reflects an insulator-metal transition in a many particle interacting system.As can be seen in Fig.3there is no clearfinite size behavior.This probably means that we are dealing with a crossover,not a phase transition.Before we conclude we want to comment on the importance of excitons introduced above. Now we concern ourselves with the localization of excitons in real space.The following scenario seems likely(although we have not found a way to prove it using our numerical data). Excitons are localized as long as the disorder dominates and the many body level statisticsis Poissonian.There might exist a crossover regime where the charge is still localized but the excitons become delocalized.In the case when a metal-insulator transition exists(in three and possibly for the interacting case in two dimensions)the exciton delocalization happens on the insulating side of the critical region of the metal-insulator transition.This scenario can result in a situation where electronic conductivity is exponentially small while the electronic thermal conductivity changes as a power of temperature[11].Another consequence of the possible exciton delocalization is that they can play a crucial role in low temperature variable range hopping.At low temperatures they can assist electron hopping much more effectively than phonons.As a result the prefactor of the variable range hopping can acquire an universal value e2/h,which was observed experimentally.This in turn leads to a very simple microscopic interpretation of the dynamic scaling at a number of quantum phase transition points,such as the quantum Hall or the superconductor-insulator transitions[12,13].Arguments for the delocalization of two interacting electrons above the Fermi sea in a situation where both of them are localized(as well as the other electrons of the Fermi sea) were given in Refs.[14,15].In the case of electrons interacting via the Coulomb interac-tion these arguments should not work because the joint density of states of two electrons drastically decreases at small energy due to the Coulomb gap in the one-electron density of states.However,for a compact electron-hole pair,an exciton,as we mentioned above, Coulomb effects increase its density of states making these arguments more plausible.Ac-tually these arguments were applied to the exciton before[15],however,the effect of the Coulomb enhancement was not considered.In conclusion,we found a P-W crossover in the statistics of the nearest neighbor spacings of many particle levels,which occurs almost simultaneously at all energies.To interpret this crossover we introduced excitons and speculated that the crossover is related to the increase of their interaction which in turn leads to the transition from a description where each state corresponds to a number of weakly interacting excitons to new states which are delocalized in the space of the old ones.This transition is similar to delocalization in Fock space inmetallic samples recently studied in Refs.[3–8].ACKNOWLEDGMENTSWe are grateful for discussions to A.Yu.Dobin,A.A.Koulakov,M.M.Fogler and D.L. Shepelyansky.R.B.research was supported by The Israel Science Foundations Centers of Excellence Program.B.I.S.acknowledges support from NSF under Grant DMR-9616880.REFERENCES[1]B.I.Shklovskii,B.Shapiro,B.R.Sears,mbrianides,and H.B.Shore,Phys.Rev.B47,11487(1993).[2]R.Berkovits and Y.Avishai,Phys.Rev.B53,R16125(1996).[3]B.L.Altshuler,Y.Gefen,A.Kamanev and L.S.Levitov,Phys.Rev.Lett.78,2803(1997).[4]Ph.Jacquod and D.L.Shepelyansky,Phys.Rev.Lett.79,1837(1997).[5]P.G.Silvestrov,Phys.Rev.Lett.79,3994(1997).[6]B.Georgeot and D.L.Shepelyansky,Phys.Rev.Lett.79,4365(1997).[7]D.Weinmann,J.L.Pichard and Y.Imry,J.Phys.I(France)7,1559(1997).[8]R.Berkovits and Y.Avishai,Phys.Rev.Lett.80,568(1998).[9]A.MacKinnon and B.Kramer,Z.Phys.B,53,1(1983).[10]B.I.Shklovskii,A.L.Efros,Electronic properties of doped semiconductors,(Springer,Heidelberg(1984)).[11]A.L.Burin,L.A.Maksimov,and I.Ya.Polishchuk,JETP Lett.49,785(1989).[12]D.G.Polyakov,B.I.Shklovskii,Phys.Rev.B48,11167(1993).[13]I.L.Aleiner,D.G.Polyakov,B.I.Shklovskii,”Physics of Semiconductors”,WorldScientific,p.787,(1995)[14]D.L.Shepelyansky,Phys.Rev.Lett.73,2067(1994).[15]J.Imry,Europhysics Lett.30,405(1995).FIGURES 0.0 1.0 2.0 3.0s0.00.20.40.60.81.0P (s )W=10W=15W=20W=25W=30PoissonWigner1015202530W0.00.20.40.60.8γFIG.1.The values of γfor the spacing between the many particle ground-state and the first excited state as function of the disorder W for a 4×3lattice with 4electrons.Inset:the distribution P (s )for different values of disorder and a given interaction (U =10V )0510********e x c i t a t i o n e n e r g yU (a)0510********e x c i t a t i o n e n e r g yU (b)0510********e x c i t a t i o n e n e r g yU (c)FIG.2.A gray scale map of the values ofγas function of the interaction strength U and excitation energy in units of the single electron level spacing∆for a4×3lattice with4electrons(a) W=10V,(b)W=20V,(c)W=30V.The corresponding single level spacings are(a)∆=0.899V, (b)∆=1.595V,and(c)∆=2.344V.51015202530W0.00.20.40.60.81.0γ3x33x34x34x34x44x44x3,U=124x3,U=16FIG.3.The values of γas function of disorder W for a 3×3lattice with 3electrons,4×3lattice with 4electrons,4×4lattice with 4electrons,at interaction strength U =8V ,and for a 4×3lattice with 4electrons also for U =12V and U =16V .The full line corresponds to the value of γaveraged over the lowest 3%of the spacings in the many particle spectrum,and the dotted line corresponds to γaveraged over the lowest 10%of the spacings.。

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