Information extraction and quantum state distortions in continuous variable quantum telepor

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原子与分子物理学报JOURNAL OF ATOMIC AND MOLECULAR PHYSICS Vol.38No.3 Jun.2021第3"卷第3期2021年6月多粒子GHZ纠缠实验中Fisher信息的保真度方法获取李岩(太原师范学院物理系，晋中030619)摘要：保真度与Fisher信息在量子精密测量和量子纠缠判定中充当着非常重要的角色.本文从概率统计和量子力学学角度出发，阐明了两者之间的区别与联系，给出了保真度方法获取Fisher信信的数学表达式;基于量子子量中常见的宇称测量模型，我们对多粒子Greenberger-Horne-Zeilinger(GHZ)纠缠产生实验中Fisher信信的获取开展了保真度方方研究，通过对实验数据的蒙特卡洛模拟，二阶或高阶曲线拟合获取了系统的Fisher信在，并将其与理论计算结果进行对比，结果表明保真度方方可以有效地获取量子系统的Fishee信在，当体系粒子数目较少时，宜采用二阶拟合方方获取系统的Fishee信在，而当粒子数目较多时,需考虑高阶拟合项的影响.此卜，我们还将多光子GHZ纠缠实验中Fisher信息的保真度获取结果与海林格距离方方方获取结果进行对比，发现二者是一致的，这也进一步验证了保真度方方获取Fisher信息的有效性.本文文研究也为开展与Fisher信息相关的量子拓扑学和量子相变的研究提供了新的途径.关键词：多粒子GHZ纠缠态；Fisher信在；保真度；宇宇测量中图分类号：O56文献标识码：A DOI：10.19855/j.l000-0364.2021.035001Fisher information extraction from multipartite GHZentanglement experimenth via EPelity mettodLI Yan(Department of Physics,Taiyuan Normal University,Jinzhong030619,China)Abstract:Both fidelity and Fishes t n formation(FI)play an importdnt role in quantum precision measurement and quantum entanglement detection.From the point of view of probability statistics and quantum mechanics,we investiyatc their relationship and present the formula to obtain FI vis fiOelity method.Based on the common mod­e in quantum mesuement,we study the FI extraction from tye multipagite Greenberges-Home-Zeilinges (GHZ)-entanglement expeaments vis method.By the Monte Cario simulation of expedmentai dati,and second一ordee oe high一ordee curne fitting,we obtain the FI and meenwhile compare O with the theoreticoi re­sults.The results show that tae fidelity method con aficienUy extract FI from quantum systems,and the second 一ordes cuee fitting is needed foe FI in few一paticie cosc,whiie tae highes-order cuee fitting is demanded foe FI S many一paticie cose,in addition,we compare the results of multi-photon cosc obtained by fidelity metaod with those from Hellinges distanco,and find that taey are the same,which furtaer vegnes the validity of tae fi­delity method in obtaining F i.The resesrch alse provides a new way ty study quantum topology and quantum phase transition related i Fi.Key words:Multipaeite GHZ entanglement state;Fishee information；Fidelity;Paety messurement收稿日期：2020-09-23基金项目：山西省高等学校科技创新基金(2020L0512)作者简介：李岩(1988—),男，山西省阳泉市人，博士，讲师，主要从事与曲畑信息相关的多粒子纠缠判定和量子计量研究.E-maii：*****************第38卷原子与分子物理学报第3期1引言随着多粒子体系量子纠缠的快速发展［1'5］和激光冷却操控技术的日益进步“,以量子态纠缠或压缩为基础，实现高精度的物理参数估计成为了量子计量学的核心研究内容［8,9］,与此同时也促进了相关领域的快速发展，如原子干涉仪心，量子磁力计［+2］,量子传感［+3］,量子模拟［4,5，14］等.在量子计量学中，Fisher信息充当着非常重要的角色，不仅对待测参数的误差精度进行了限定［8,9］，如标准量子极限、海森堡极限,也对实现该精度的量子态纠缠进行了判定［15，16］-基于参数估计理论中的无偏差估计和克拉美罗下界定a［I7］，待估参数(如相位)的精度极限可表示为$"I/槡—,F(-为体系的Fisher信息，表示对待测相位信息的认知程度，Fisher信息值越大表明对其掌握越准确、测量精度也越高.2009年，意大利科学家A.Smerzi研究员和L.Pezz e博士在探究Fisher信息的纠缠判定功能时发现，当分离量子态的Fisher信息大于体系所包含的粒子数目N时，可以判定体系含有量子纠缠，以该量子态作为试探态开展量子精密测量，其测量精度会超越标准量子极限，甚至逼近于海森堡极限'+5(.因此，开展Fisher信息在理论和实验上的有效获取成为了量子精密测量中不可或缺的研究内容.Fisher信息是关于条件概率分布的函数，对概率分布的依赖性较强-一般地，条件概率分布的获取较难，特别是在统计模型未知的情况下，条件概率的解析表达式很难得到，导致Fisher信息的获取变得困难［+8］,但从实验的角度出发，条件概率的获取并非难事，Fisher信息也可可从中得到-20I4年，德国科学家在利用扭曲和转动(Twist and turn)哈密顿量实现Rb87原子非高斯态的纠缠实验中，首次采用了海林格距离(Hellinger distance)方法进行了Fisher信息的获取，通过二阶曲线拟合成功地抽取了系统的Fisher信息［I9］.与海林格距离方法类似，保真度也是用来反映概率分布之间差异的［20］,在量子力学中，量子态的保真度用来刻画量子态之间的相似程度［2+］,如衡量量子态在传输过程中的成功率［22］,刻画量子态的相变［23］等，甚至可可用来进行量子态的纠缠判体24(,它可以用来获取系统的Fisher信息吗？最近有学者提出可可利用动态保真度方法(洛施密特回波，Loschmidt echo)来获取系统的Fisher信息［25］,但结合具体实验数据的分析研究并未给出.基于常见的宇称测量模型，本文对多粒子Grenbege z-Ho o n e-Zeilinge z(GHZ)纠缠实验中Fshez信息的保真度方法获取进行了系统的研究,通过对已有宇称测量实验数据［3-5］的蒙特卡洛模拟、保真度计算、曲线拟合等过程，获取系统的Fshez信息，并将其与海林格距离方法的结果作简单比较［26(,研究表明，保真度方法可可有效地获取量子系统的Fisher信息，当体系所含粒子数目较少时，采用高阶拟合方法获取Fisher信息,反之，则采用二阶拟合方法-文章第二部分介绍了宇称测量模型及其在干涉仪和量子纠缠相干性获取中的应用-第三部分从概率统计和量子力学的角度出发，阐述了保真度与Fisher信息之间的区别与联系，给出了保真度获取Fisher信息的表达式-第四部分为本文的核心部分，我们对多粒子(光子、超导量子比特、中性原子)GHZ纠缠实验中的Fisher信息进行了保真度方法获取，并将其与理论计算的最优Fisher信息进行对比-最后一部分对文章进行总结-2宇称测量模型在量子力学中，宇称算符是一个可观测量,其期望值可表示为准概率相空间中的Wigner函数［27］-宇称测量是量子计量学中一种常见的测量方式，早在I996年美国科学家--Bollinger教授就利用宇称测量模型结合最大纠缠探测态实现了海森堡极限的频率估计［28］-在利用光学马赫曾德干涉仪进行高精度的相位估计中，宇称测量算符可表示为［29］6.=(-I)""(I)其中，".表示干涉仪测量端或输出端.处的光子统计数较从式(I)很容易得出，宇称测量算符的本征值只有两个，+I,即待测光子数为偶数,为偶宇称；-I,即待测光子数为奇数，为奇宇称.利用宇称算符平均值〈6.2与干涉仪相位0之间的关系，结合误差传递公式，就可得到相位的估计精度，进一步通过相位与待测物理参数的关系，便可得到待测物理量的相关信息［28］-除此之外，宇称算符测量还用于纠缠判定实验［24］中量子态相干性的获取，其平均值可以表为〈62=((-I)£⑵j="其中,F代表被测量子态包含丿个自旋向上粒子第38卷李岩：多粒子GHZ纠缠实验中Fisher信息的保真度方法获取第3期1/2的概率，或表示含有/个激发量子态的概率[30]-当实验产生的多粒子GHZ纠缠态受外界因素影响时，宇称算符的平均值表示为如下关系[3-5,24,30]〈6〉$F?!"Ycos(0-(3)其中，Y代表量子态的相干性，也称为可见度(vsibility),-表示可可调控的相位.同样地，待测量子态只有偶数激发和奇数激发两种状态，故F,,+PoM=1(4)这样，宇称测量的结果用概率表示为=(1+Yos(N O))((5)P?=(1-Yos(N O))/2(6)上述式(5)和式！6)在下面多粒子GHZ纠缠实验的Fisher信息保真度抽取中会用到，也是本文研究所要用到的条件概率分布，第四部分有详细说明-3保真度与Fisher信息从经典概率统计的角度出发，保真度可可表示为[20](槡槡槡⑺其中会=*Pa,P a，…,P,J和_=*_1,_2，…，q j分别代表两组相近的概率分布,/(P,,_)也称为概率保真度-在量子力学中，量子态可可用希尔伯特空间中的一组完备基展开，表示为其中的一个矢量，其物理意义对应于概率论中的概率幅,即概率的1/2次方'31]-因此，量子态的保真度可以表示为两个态矢量作内积的绝对值，即/(%, %+3)=11%++32丨，其中，I%2可可代表式⑺中的槡,丨％++o2代表表槡.由于本文仅考虑纯态保真度的相关计算，所以混合态保真度部分不作过多介绍，有兴趣的读者可见文献[32,33(•在量子测量实验中，对物理参数的高精密测量最终会映射到与该参数有关的相位估计中[8，A],具体表现形式为条件概率分布的获取，即p(7 O)=E[.(O)4(7)],.O)表示含有相位0信息的量子态密度矩阵，这里4(7)表示正算符测度(Positive-Operator Valued Meesure,POVM),是待测物理量的算符表示，满足完备归一性, (4(7)=1-通常Fisher信息可以表示为x(o)=(+(71o)(%710))2(8)其中，P71-)表示在给定相位0条件下对可观测量测量所得值为7的条件概率.将式(")拓展到量子力学中，对测量算符4(7)进行优化选取，就得到了Fisher信息的最大值，记为量子Fisher信息F q(O)⑼.与保真度的物理意义一样，Fisher 信息也是用来表征近邻量子态之间差别的，不同之处是，Fisher信息是用来衡量量子态之间的可区分程度，对差异进行细画，表征量子态之间的统计速度[15，16,32],即统计距离在概率空间的变化率，而保真度则用来计算量子态之间的宏观区别，表征量子态之间的“跃迁概率”[34]-近邻量子态测量后的条件概率保真度可见表为为60)=(7+(710)7+(710+3)(9)对其进行泰勒展开(保留高阶项)，可得保真度与Fisher信息之间的关系式量33],6-)=1$*F(0)⑻)2$1F'(0)⑻)3+0⑻)4(10)从上式可以看出，二阶项系数包含系统的Fisher信息，高阶项会对二阶项起到修正作用[26].当3较小时，忽略高阶项(三阶项调上)，我们便得到了Fisher信息与保真度之间的关系，F(0)=$436(0(80)2,也可记作Fisher\言息等于4倍的保真率[33]-显然，若保真度/(0)为1,则保真率为0,F(0)也为零，表示近邻量子态不可区分；若保真度不为0,则保真率越大，Fisher信息越大，近邻量子态越容易区分.将该推理应用于干涉仪的相位估计中，则表明Fisher 信息可见将量子态之间的差异(保真度)进行细化，依据克拉美罗下界定理，$0"1/7X(0),系统的Fisher信息越大，意味着待估参数的误差精度$0越小，量子态之间的差别刻画地越精细-4利用保真度方法从实验数据中获取Fisher信息4.1多光子GHZ纠缠实验中Fisher信息的获取在二能级粒子组成的量子系统中，N粒子的GHZ纠缠态表示零28]I%”[〉=-p(I0200+I1200)(11)槡2其中，丨02和丨12分别代表粒子所处的量子状态，如基态和激发态-在多光子GHZ纠缠态的产生实验中[3],为了获得量子态的相干性，对测量算符第3"卷原子与分子物理学报第3期4®N"(0C OS0+0ySi?0)00进行了理论计算和实验数据分析，其中为泡利算符.与式！1)对比,算符符0的本征值也为+1或-1,故可看作是宇称测量算符的操作表示.考虑测量过程中噪声的影响，其平均值表示为140N〉"F(+1I-)-F(-1I-)二Ycos(N-)(12)其中，F(+110)和F(-110)分别为在给定相位-条件下,宇称测量算符符a测量值为+1或-1的条件概率，具体表示为式(5)和式!6),将其代入Fisher信息的表达式("),便得到系统的Fisher信息为X-)Y2N2cos2(N0)1-Y2cos2(N0)二Ycos(N0)(13)对上式进行最大化，得到最优Fisher信息为X opt(-)二Y2N2(14)优化相位为-opt二)/(2N)+))/N,表示实验上在相位-pt附近进行Fisher信息抽取时，可得到Fisher信息的最优值•此处，为了与理想情况下的量子Fisher信息X'"N(Y二1)进行区分,将式！13)最大化所得的Fisher信息记为最优Fish­er信息F O pt'26(.基于以上论述，依据保真度的定义(9)及其与Fisher信息的关系！10),我们便可通过条件概率++110)或+-110)的获取开展Fisher信息的拟合抽取研究•首先，我们对多光子GHZ纠缠实验中的宇称测量数据进行获取，即对文献'3(图2(d)中的最优相位0°pt附近的数据点依次进行获取，包括平均值140N〉及其误差'26(；其次，对获取数据点进行正态分布的蒙特卡洛数值模拟，得到更多数据,即条件概率，…，F(+1I0°pt-3),F(+1I0O p t)，F(+1I-O pt+3),…，随后将其代入公式!9)行保真度计算；最后，利用保真度与Fisher信息之间的关系式(10)进行二阶拟合或高阶拟合获取FsShe信为.图1给出了N=2和N="光子GHZ纠缠实验中保真度随相位间隔3的变化情况，其中绿色圆点代表@二1000次蒙特卡洛数值模拟后计算得到保真度的平均值，误差棒表示其误差变化范围.通过二阶曲线拟合我们得到2光子的Fisher信息为X q= 3.442±0.317，该值与优化Fisher信息公式！14)所得值X O pt二 3.463±0.002—致！Y= 0.930见文献'4().当相位间隔3较大时，需考虑高阶项影响'26(,通过曲线拟合得到"光子的Fisher信息为X q二19.562±5.172,接近于优化Fisher信息值X p二18.5344± 1.997.将上述Fisher信息获取结果与海林格距离方法所得结果进行对比'26(,两者一致，进一步验证了保真度方法能够有效地获取系统的Fisher信息.此外，从 公式上看，H d=1-(7槡(7I0”(7I0+3),真度方法获取.绿色圆点表示保真度，误差棒代表其标准差，红色实线为曲线拟合结果，黑色虚线代表其误差变化范围.(a)N=2光子实验数据中保真度随相位间隔3二0.045)的变化.(b)N=8光子实验数据中保真度随相位间隔3二0.031)的变化•Fig.1FI extraction from multi一photon GHZ expeQ­mental data by fidelity method.The green dotsare the fidelity and the xrorbar denotes thestandard eiroe,red line denotes the fitting resultand black dashed lines mean the eiroiregion.(a)The fidelity of N二2photons&dalt with re-speot t。

信息检索中的特征工程与语义关系提取技术信息检索（Information Retrieval）是指从大规模的文本库中检索出与用户需求相关的信息。

而特征工程（Feature Engineering）和语义关系提取技术（Semantic Relationship Extraction）则是信息检索领域中常用的两种技术手段。

本文将着重介绍这两种技术在信息检索中的应用和实现方式。

特征工程是指对原始数据进行处理，提取出对目标任务有用的特征，以便于机器学习算法的应用和模型的训练。

在信息检索中，特征工程的目标是将文本转化成向量形式，以便于计算机进行处理和分析。

常用的特征工程方法包括词袋模型（Bag of Words）和词嵌入（Word Embedding）。

词袋模型将文本表示成词的集合，不考虑词的顺序和语法结构。

可以将每个词看作是特征向量中的一个维度，每个文本则对应一个向量，向量的每个维度表示该词在文本中的出现次数或者tf-idf值。

由于词袋模型简单、易于实现和解释，因此被广泛应用于文本分类、检索和聚类等任务中。

而词嵌入则将每个词表示成一个稠密的向量，捕捉到词之间的语义关系。

常见的词嵌入算法有word2vec和GloVe。

这些算法通过学习词之间的上下文关系，将词映射到一个低维的空间中，使得语义相似的词在向量空间中距离较近。

词嵌入在信息检索中的应用包括查询扩展、相关性评分和聚类等任务。

除了特征工程，语义关系提取技术也在信息检索中发挥着重要作用。

语义关系提取旨在从文本中抽取出实体之间的语义关系，如“公司A收购了公司B”中的“收购”关系。

常用的语义关系提取方法包括基于规则的方法和基于机器学习的方法。

基于规则的方法依赖于人工设计的规则，通过文本中的语法结构和关键词进行关系抽取。

这种方法优点是可解释性强，但缺点是需要大量的人力和时间来构建规则，并且对于复杂的关系难以适应。

而基于机器学习的方法则通过训练一个分类器或序列标注器来自动识别和提取语义关系。

专利名称：EXTRACTION OF SPECTRAL INFORMATION发明人：Rajesh Menon申请号：US14444718申请日：20140728公开号：US20150032402A1公开日：20150129专利内容由知识产权出版社提供专利附图：摘要：A spectral distribution of incident light can be determined to increase collected spectral information. The spectral distribution of the incident light can be represented as a sum of spectral components after the incident light passes through a spectrumselective element. A signal at each color pixel of the spectrum selective element can bedetermined using, in part, the sum of the spectral components, where the spectral components are represented by a set of preliminary values. An error associated with the signal at each color pixel of the spectrum selective element is calculated. One or more perturbations are performed on each of the preliminary values and the error associated with the signal at each color pixel of the spectrum selective element is recalculated. The perturbations on each of the preliminary values is repeated until the error stabilizes within a predetermined range in order to assign the stabilized preliminary values as the spectral components in the incident light.申请人：University of Utah Research Foundation地址：Salt Lake City UT US国籍：US更多信息请下载全文后查看。

量子信息的英文缩写英文回答：Quantum information is an emerging field that deals with the storage, processing, and communication of information using quantum systems. It has the potential to revolutionize many different fields, including computing, communication, and cryptography.One of the most important concepts in quantum information is the qubit. A qubit is a quantum-mechanical two-level system, which can be in a superposition of both states simultaneously. This is in contrast to a classical bit, which can only be in one state at a time.Another important concept in quantum information is entanglement. Entanglement is a quantum-mechanical phenomenon that occurs when two or more qubits are linked together in such a way that they cannot be described independently. This can lead to a number of strange andcounterintuitive effects, such as the ability to teleport qubits and the violation of Bell's inequality.Quantum information is still a relatively new field, but it has already made a number of important advances. These advances have the potential to lead to new and revolutionary technologies in the future.中文回答：量子信息是一个新兴领域，它利用量子系统来存储、处理和传递信息。

University of Wisconsin-Madison(UMW)周玉龙1101213442 计算机应用UMW简介美国威斯康辛大学坐落于美国密歇根湖西岸的威斯康辛州首府麦迪逊市，有着风景如画的校园，成立于1848年, 是一所有着超过150年历史的悠久大学。

威斯康辛大学是全美最顶尖的三所公立大学之一，是全美最顶尖的十所研究型大学之一。

在美国，它经常被视为公立的常青藤。

与加利福尼亚大学、德克萨斯大学等美国著名公立大学一样，威斯康辛大学是一个由多所州立大学构成的大学系统，也即“威斯康辛大学系统”（University of Wisconsin System）。

在本科教育方面，它列于伯克利加州大学和密歇根大学之后，排在公立大学的第三位。

除此之外，它还在本科教育质量列于美国大学的第八位。

按美国全国研究会的研究结果，威斯康辛大学有70个科目排在全美前十名。

在上海交通大学的排行中，它名列世界大学的第16名。

威斯康辛大学是美国大学联合会的60个成员之一。

特色专业介绍威斯康辛大学麦迪逊分校设有100多个本科专业，一半以上可以授予硕士、博士学位，其中新闻学、生物化学、植物学、化学工程、化学、土木工程、计算机科学、地球科学、英语、地理学、物理学、经济学、德语、历史学、语言学、数学、工商管理（MBA）、微生物学、分子生物学、机械工程、哲学、西班牙语、心理学、政治学、统计学、社会学、动物学等诸多学科具有相当雄厚的科研和教学实力，大部分在美国大学相应领域排名中居于前10名。

学术特色就学术方面的荣耀而言，威斯康辛大学麦迪逊校区的教职员和校友至今共获颁十七座诺贝尔奖和二十四座普立兹奖；有五十三位教职员是国家科学研究院的成员、有十七位是国家工程研究院的成员、有五位是隶属于国家教育研究院，另外还有九位教职员赢得了国家科学奖章、六位是国家级研究员（Searle Scholars）、还有四位获颁麦克阿瑟研究员基金。

威斯康辛大学麦迪逊校区虽然是以农业及生命科学为特色，但是令人注目，同时也是吸引许多传播科系学子前来留学的最大诱因，则是当前任教于该校新闻及传播研究所、在传播学界有「近代美国传播大师」之称的杰克·麦克劳（Jack McLauld）。

第24卷第7期2 0 18年7月计算机集成制造系统Computer Integrated Manufacturing Systems Vol. 24 No. 7 July 2 0 18D O I：10. 13196/j.cims.2018. 07. 009面向自然过程文本的案例信息抽取倪维健，韦振胜，曾庆田+，刘彤(山东科技大学计算机科学与工程学院，山东青岛266510)摘要:针对描述具体流程案例信息的自然文本,提出一种案例自动抽取方法，实现了无结枸过程文本向结枸 化事件日志转换,从而为后续的过程挖掘研究提供数据支持。

首先对过程文本案例抽取任务进行了形式化描述，抽象出活动/属性实体识别、活动/属性关系识别、活动顺序关系识别3个核心任务，然后应用半监督统计学习技术分别设计了解决方法。

选取中文菜谱文档为实例开展了大规模实验研究，对所提出的案例信息抽取方法的有效性进行了全面评估。

实验结果表明，所提方法能够在少量人工标注数据的基础上有效利用同领域内大量未标注过程文本提升案例抽取效果，且无需人工设计复杂的规则，具有良好的领域适用性。

关键词:案例#言息抽取;过程文本;半监督学习中图分类号:TP391 文献标识码:ACase information extraction from natural procedure textNlW eijian，WEIZhensheng，ZENGQingtian+，LIUTong(College of Computer Science and Engineering ,Shandong University of Science and Technology，Qingdao 266510, China)Abstract：Aiming at the natural text for describing specific process case，a new approach to automatically extr case information was introduced，which realized the transformation from unstructured procedure text to structuredevent logs, and provided valuable data resource in downstream process mining tasks. Based on a formal defi key concepts in procedure text，case information extraction was divided into three sub t asks:activity/property entityrecognition，activity/property relation recognition and activity sequence recognition，each of which was approachedin a semi-supervised way. Experiments with Chinese recipe documents demonstrated that the proposed approach wascapable of constructing c ase information extraction model by using a small amount of labeled text，with the help ofthe huge number of unlabeled t ext in the same domain, Furthermore，the proposed approach could be easi to real-world domains as it was independent on complicated manually-designed rules.Keywords:case;information extraction；procedure text；semi-supervised learning〇引言过程挖掘作为业务过程建模与分析的重要手 段，已在计算机科学、管理科学、数据科学等多个领 域得到了广泛的关注。

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Absorption Spectroscopy原子吸收光谱Attenuated Total Reflectance Spectroscopy衰减全反射光谱Electron Paramagnetic Spectroscopy电子顺磁谱Electron Spectroscopy电子光谱Infrared Spectroscopy红外光谱Fourier Transform Spectrosopy傅里叶变换光谱Gamma-ray Spectroscopy伽玛射线光谱Multiplex or Frequency-Modulated Spectroscopy复用或频率调制光谱X-ray SpectroscopyX射线光谱色谱：Gas Chromatography气相色谱High Performance Liquid Chromatography 高效液相色谱Thin-Layer Chromatography 薄层色谱magnesium silicate gel硅酸镁凝胶retention time保留时间mobile phase流动相stationary phase固定相反应类型：agitated tank搅拌槽 catalytic reactor 催化反应器batch stirred tank reactor间歇搅拌反应釜continuous stirred tank 连续搅拌釜exothermic reactions放热反应 pilot plant试验工厂fluidized bed Reactor流动床反应釜multiphase chemical reactions 多相化学反应packed bed reactor填充床反应器redox reaction氧化还原反应reductant-oxidant氧化还原剂 acid base reaction酸碱反应 additionreaction加成反应chemical equation化学方程式 valence electron价电子combination reaction化合反应hybrid orbital 杂化轨道decomposition reaction分解反应substitution reaction取代(置换)反应Lesson5 Classification of Unit Operations单元操作Fluid 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