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Mathematics公理在传统逻辑中，公理（古希腊语: ἀξίωμα, 德语、英语: Axiom）是没有经过证明，但被当作不证自明的一个命题。因此，其真实性被视为是理所当然的，且被当做演绎及推论其他（理论相关）事实的起点。当不断要求证明时，因果关系毕竟不能无限地追溯，而需停止于无需证明的公理。通常公理都很简单，且符合直觉，如“ a + b = b + a {\displaystyle a+b=b+a} ”。 不同的系统，会预计不同的公理。例如非欧几何的公理，和欧氏几何的公理就有一点不同；另外，集合论的选择公理在许多系统的建构中，也富有争议。有些系统坚持不预设选择公理。也有一些数学家在建构系统时，刻意排除掉皮亚诺公理中的数学归纳法，以确保所有的证明，都可以直接演算。 在数学中，公理这一词被用于两种相关但相异的意思之下——逻辑公理和非逻辑公理。在这两种意义之下，公理都是用来推导其他命题的起点。和定理不同，一个公理（除非有冗余的）不能被其他公理推导出来，否则它就不是起点本身，而是能够从起点得出的某种结果—可以干脆被归为定理了。 逻辑公理通常是被视为普遍为真的陈述（如 ( A ∧ B ) → A {\displaystyle (A\land B)\rightarrow A} ），而非逻辑公理（如 a + b = b + a {\displaystyle a+b=b+a} ）则实际上是在一特定数学理论（如算术）中的定义性的性质。在后者的意思之下，公理又可被称为“公设”。一般而言，非逻辑公理并不是一个不证自明的事实，而应该说是在建构一个数学理论的过程中被用来推导的一个形式逻辑表示式。要公理化一个知识系统，就是要去证明该系统的主张都可以由数目不多而又可明确理解的陈述（公理）推导出来。一般来说都有多种方法来公理化一个给定的数学领域。
An axiom, postulate, or assumption, is a statement that is taken to be true, to serve as a premise or starting point for further reasoning and arguments. The word comes from the Ancient Greek word ἀξίωμα (axíōma), meaning 'that which is thought worthy or fit' or 'that which commends itself as evident'. The precise definition varies across fields of study. In classical philosophy, an axiom is a statement that is so evident or well-established, that it is accepted without controversy or question. In modern logic, an axiom is a premise or starting point for reasoning. In mathematics, an axiom may be a "logical axiom" or a "non-logical axiom". Logical axioms are taken to be true within the system of logic they define and are often shown in symbolic form (e.g., (A and B) implies A), while non-logical axioms are substantive assertions about the elements of the domain of a specific mathematical theory, for example a + 0 = a in integer arithmetic. Non-logical axioms may also be called "postulates", "assumptions" or "proper axioms".
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 行列式（英语：Determinant），记作 det ( A ) {\displaystyle \det(A)} 或 | A | {\displaystyle |A|} ，是一个在方块矩阵上计算得到的标量。行列式可以看作是有向面积或体积的概念在一般的欧几里得空间中的推广。或者说，在欧几里得空间中，行列式描述的是一个线性变换对“体积”所造成的影响。无论是在线性代数、多项式理论，还是在微积分学中（比如说换元积分法中），行列式作为基本的数学工具，都有着重要的应用。 行列式概念最早出现在解线性方程组的过程中。十七世纪晚期，关孝和与莱布尼茨的著作中已经使用行列式来确定线性方程组解的个数以及形式。十八世纪开始，行列式开始作为独立的数学概念被研究。十九世纪以后，行列式理论进一步得到发展和完善。矩阵概念的引入使得更多有关行列式的性质被发现，行列式在许多领域都逐渐显现出重要的意义和作用，其定义也被推广到诸如线性自同态和向量组等结构上。 行列式的特性可以被概括为一个交替多线性形式，这个本质使得行列式在欧几里德空间中可以成为描述“体积”的函数。
In mathematics, the determinant is a scalar-valued function of the entries of a square matrix that has many properties which make it fundamental for the study of square matrices and linear transformations represented by them. The determinant of a matrix A is commonly denoted det(A), det A, or |A|.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 内积空间（英语：inner product space）是增添了某种运算的向量空间，这种运算叫做内积，它推广了原来欧几里德空间的点积，而从比较一般的角度看待向量的“夹角”、“长度”还有“正交性”。
In mathematics, an inner product space is a real or complex vector space endowed with an operation called an inner product. The inner product of two vectors in the space is a scalar, often denoted with angle brackets such as in ⟨ a , b ⟩ {\displaystyle \langle a,b\rangle } . Inner products allow formal definitions of intuitive geometric notions, such as lengths, angles, and orthogonality (zero inner product) of vectors. Inner product spaces generalize Euclidean vector spaces, in which the inner product is the dot product or scalar product of Cartesian coordinates. Inner product spaces of infinite dimensions are widely used in functional analysis. Inner product spaces over the field of complex numbers are sometimes referred to as unitary spaces. The first usage of the concept of a vector space with an inner product is due to Giuseppe Peano, in 1898.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 线性映射（英语：linear map）是向量空间之间，保持向量加法和标量乘法的函数。线性映射也是向量空间作为模的同态。 线性算子（英语：linear operator）与线性变换（英语：linear transformation，又称线性变换）是与线性映射相关的惯用名词，但其实际意义存在许多分歧，详见相关名词一节。
In mathematics, and more specifically in linear algebra, a linear map, linear mapping, or linear operator is a particular kind of function between vector spaces, which respects the basic operations of vector addition and scalar multiplication. A standard example of a linear map is an m × n {\displaystyle m\times n} matrix, which takes vectors in n {\displaystyle n} -dimensions into vectors in m {\displaystyle m} -dimensions in a way that is compatible with addition of vectors, and multiplication of vectors by scalars. When the two vector spaces are the same, a linear map is also called a linear transformation or linear endomorphism. A linear map is a homomorphism of vector spaces.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 数学是研究数量、结构以及空间等概念及其变化的一门学科，属于形式科学的一种。数学利用抽象化和逻辑推理，从计数、计算、量度、对物体形状及运动的观察发展而成。数学家们拓展这些概念，以公式化新的猜想，以及从选定的公理及定义出发，严谨地推导出一些定理。 纯粹数学的知识与运用是生活中不可或缺的一环。对数学基本概念的完善，早在古埃及、美索不达米亚及古印度历史上的古代数学文本便可观见，而在古希腊那里有更为严谨的处理。从那时开始，数学的发展便持续不断地小幅进展，至16世纪的文艺复兴时期，因为新的科学发现和数学革新两者的交互，致使数学的加速发展，直至今日。数学并成为许多国家及地区的教育中的一部分。 数学在许多领域都有应用，包括科学、工程、医学、经济学和金融学等。数学对这些领域的应用通常被称为应用数学，有时亦会激起新的数学发现，并导致全新学科的发展，例如物理学的实质性发展中建立的某些理论激发数学家对于某些问题的不同角度的思考。数学家也研究纯粹数学，就是数学本身的实质性内容，而不以任何实际应用为目标。许多研究虽然以纯粹数学开始，但其过程中也发现许多可用之处。
Mathematics is a field of knowledge concerned with abstract concepts such as numbers, geometric shapes, sets, functions, and probabilities. It uses logical reasoning and proof to study and establish their properties, often expressed as theorems, formulas, and equations. Mathematics is widely used to model and solve problems in science, engineering, technology, economics, and everyday life. There are many areas of mathematics, including number theory (the study of integers and their properties), algebra (the study of operations and the structures they form), geometry (the study of shapes and spaces that contain them), analysis (the quantitative study of approximation and convergence), and set theory (presently used as a foundation for all mathematics). Mathematics involves the description and manipulation of abstract objects that are either abstractions from nature or purely abstract entities that are stipulated to have certain properties, called axioms.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 向量空间是一群可缩放和相加的数学实域（如实数甚至是函数）所构成的特殊集合，其特殊之处在于缩放和相加后仍属于这个集合。这些数学实域被称为向量，而向量空间正是线性代数的主要研究对象。
In mathematics, a vector space (also called a linear space) is a set whose elements, often called vectors, can be added together and multiplied ("scaled") by numbers called scalars. The operations of vector addition and scalar multiplication must satisfy certain requirements, called vector axioms. Real vector spaces and complex vector spaces are kinds of vector spaces based on different kinds of scalars: real numbers and complex numbers. Scalars can also be, more generally, elements of any field. Vector spaces generalize Euclidean vectors, which allow modeling of physical quantities (such as forces and velocity) that have not only a magnitude, but also a direction. The concept of vector spaces is fundamental for linear algebra, together with the concept of matrices, which allows computing in vector spaces. This provides a concise and synthetic way for manipulating and studying systems of linear equations. Vector spaces are characterized by their dimension, which, roughly speaking, specifies the number of independent directions in the space.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 数学中，特别是泛函分析中，作用于希尔伯特空间X、Y之间的紧算子 T : X → Y {\displaystyle T:X\rightarrow Y} 的奇异值是自伴算子 T ∗ T {\displaystyle T^{*}T} （ T ∗ {\displaystyle T^{*}} 表示T的伴随）的非负特征值的平方根。 奇异值是非负实数，一般按递减顺序排列（ σ 1 ( T ) , σ 2 ( T ) , … {\displaystyle \sigma _{1}(T),\ \sigma _{2}(T),\dots } ）。最大的奇异值 σ 1 ( T ) {\displaystyle \sigma _{1}(T)} 等于T的算子范数（见极小-极大定理）。
In mathematics, in particular in functional analysis, the singular values of a compact operator T : X → Y {\displaystyle \,T\!:X\rightarrow Y} acting between Hilbert spaces X {\displaystyle X} and Y {\displaystyle Y} , are the square roots of the (necessarily non-negative) eigenvalues of the self-adjoint operator T ∗ T {\displaystyle T^{*}T} (where T ∗ {\displaystyle T^{*}} denotes the adjoint of T {\displaystyle T} ).
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 在数学上，特别是线性代数中，对于一个给定的方阵 A {\displaystyle A} ，它的特征向量（eigenvector，也译固有向量、本征向量） v {\displaystyle v} 经过这个线性变换之后，得到的新向量仍然与原来的 v {\displaystyle v} 保持在同一条直线上，但其长度或方向也许会改变。即 A v = λ v {\displaystyle Av=\lambda v} ， λ {\displaystyle \lambda } 为标量，即特征向量的长度在该线性变换下缩放的比例，称 λ {\displaystyle \lambda } 为其特征值（eigenvalue，也译固有值、本征值）。如果特征值为正，则表示 v {\displaystyle v} 在经过线性变换的作用后方向也不变；如果特征值为负，说明方向会反转；如果特征值为0，则是表示缩回零点。但无论怎样，仍在同一条直线上。图1给出了一个以油画《蒙娜丽莎》为题材的例子。在一定条件下（如其矩阵形式为实对称矩阵的线性变换），一个变换可以由其特征值和特征向量完全表述，也就是说：所有的特征向量组成了这向量空间的一组基底。一个特征空间（eigenspace）是具有相同特征值的特征向量与一个同维数的零向量的集合，可以证明该集合是一个线性子空间，比如 E λ = { u ∈ V ∣ A u…
In linear algebra, an eigenvector ( EYE-gən-) or characteristic vector is a (nonzero) vector that has its direction unchanged (or reversed) by a given linear transformation. More precisely, an eigenvector v {\displaystyle \mathbf {v} } of a linear transformation T {\displaystyle T} is scaled by a constant factor λ {\displaystyle \lambda } when the linear transformation is applied to it: T v = λ v {\displaystyle T\mathbf {v} =\lambda \mathbf {v} } . The corresponding eigenvalue, characteristic value, or characteristic root is the multiplying factor λ {\displaystyle \lambda } (possibly a negative or complex number). Geometrically, vectors are multi-dimensional quantities with magnitude and direction, often pictured as arrows.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 代数是一个较为基础的数学分支。它的研究对象有许多。诸如数、数量、代数式、关系、方程理论、代数结构等等都是代数学的研究对象。 初等代数一般在中学时讲授，介绍代数的基本思想：研究当我们对数字作加法或乘法时会发生什么，以及了解变量的概念和如何建立多项式并找出它们的根。 代数的研究对象不仅是数字，还有各种抽象化的结构。例如整数集作为一个带有加法、乘法和序关系的集合就是一个代数结构。在其中我们只关心各种关系及其性质，而对于“数本身是什么”这样的问题并不关心。常见的代数结构类型有群、环、域、模、线性空间等。
Algebra is a branch of mathematics that deals with abstract systems, known as algebraic structures, and the manipulation of expressions within those systems. It is a generalization of arithmetic that introduces variables and algebraic operations other than the standard arithmetic operations, such as addition and multiplication. Elementary algebra is the main form of algebra taught in schools. It examines mathematical statements using variables for unspecified values and seeks to determine for which values the statements are true. To do so, it uses different methods of transforming equations to isolate variables. Linear algebra is a closely related field that investigates linear equations and combinations of them called systems of linear equations. It provides methods to find the values that solve all equations in the system at the same time, and to study the set of these solutions. Abstract algebra studies algebraic structures, which consist of a set of mathematical objects together with one or several operations defined on that set.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 在数学中，特别是点集拓扑学中，紧空间（英语：compact space）是对欧几里得空间 R n {\displaystyle \mathbb {R} ^{n}} 中的有界闭集合的推广。 欧几里得空间 R n {\displaystyle \mathbb {R} ^{n}} 的所有有界闭集合是紧致的。例如，在 R {\displaystyle \mathbb {R} } 中，单位区间 [ 0 , 1 ] {\displaystyle [0,1]} 是紧致的，但整数集合 Z {\displaystyle \mathbb {Z} } 不是（它不是有界的），半开区间 [ 0 , 1 ) {\displaystyle [0,1)} 也不是（它不是闭合的）。 广义的定义是如果对于一个拓扑空间的所有开覆盖，都可以找到有限的子覆盖，则称此拓扑空间是紧致的。根据海涅-博雷尔定理，欧几里得空间的子集紧致当且仅当它“闭集且有界”。 注意：某些作者如布尔巴基使用术语“预紧致”，并把“紧致”保留给是豪斯多夫空间并且“预紧致”的拓扑空间。一个单一的紧致集合有时称为紧统（compactum）。在法语的数学著作中，quasi-compact是指紧致，compact是指紧致且豪斯多夫，不同于英语。
In mathematics, especially general topology and mathematical analysis, compactness is a property of a space that makes it behave in many ways like a finite set. For instance, on a finite set every infinite sequence must take some value infinitely often, by the pigeonhole principle. For subsets of Euclidean space, the analogous statement is sequential compactness: a set is compact if and only if every infinite sequence in the set has a subsequence that converges to a point of the set. Likewise, whereas every real-valued function on a finite set is bounded and attains its maximum and minimum, every continuous real-valued function on a compact space has these properties. For compact subsets of Euclidean space, this is the extreme value theorem. Another basic property of finite sets is that every cover of a finite set by subsets has a finite subcover: one may choose, for each point of the finite set, a member of the cover containing it. The corresponding topological property is used to define compactness: a topological space is compact if every open cover has a finite subcover.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 导数（英语：derivative）是微积分学中的一个概念。函数在某一点的导数是指这个函数在这一点附近的变化率（即函数在这一点的切线斜率）。导数的本质是通过极限的概念对函数进行局部的线性逼近。当函数 f {\displaystyle f} 的自变量在一点 x 0 {\displaystyle x_{0}} 上产生一个增量 h {\displaystyle h} 时，函数输出值的增量与自变量增量 h {\displaystyle h} 的比值在 h {\displaystyle h} 趋于0时的极限如果存在，即为 f {\displaystyle f} 在 x 0 {\displaystyle x_{0}} 处的导数，记作 f ′ ( x 0 ) {\displaystyle f'(x_{0})} 、 d f d…
In mathematics, the derivative is a fundamental tool that quantifies the sensitivity to change of a function's output with respect to its input. The derivative of a function of a single variable at a chosen input value, when it exists, is the slope of the tangent line to the graph of the function at that point. The tangent line is the best linear approximation of the function near that input value. The derivative is often described as the instantaneous rate of change, the ratio of the instantaneous change in the dependent variable to that of the independent variable. The process of finding a derivative is called differentiation. There are multiple different notations for differentiation. Leibniz notation, named after Gottfried Wilhelm Leibniz, is represented as the ratio of two differentials, whereas prime notation is written by adding a prime mark. Higher order notations represent repeated differentiation, and they are usually denoted in Leibniz notation by adding superscripts to the differentials, and in prime notation by adding additional prime marks.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 微分几何研究微分流形的几何性质，是现代数学中的一主流研究方向，也是广义相对论的基础，与拓扑学、代数几何及理论物理关系密切。 古典微分几何起源于微积分，主要内容为曲线论和曲面论。欧拉、蒙日和高斯被公认为古典微分几何的奠基人。近代微分几何的创始人是黎曼，他在1854年创立了黎曼几何（实际上黎曼提出的是芬斯勒几何），这成为了近代微分几何的主要内容，并在相对论有极为重要的作用。埃利·嘉当和陈省身等人曾在微分几何领域做出极为杰出的贡献。
Differential geometry is a mathematical discipline that studies the geometry of smooth shapes and smooth spaces, otherwise known as smooth manifolds. It uses the techniques of vector calculus, linear algebra and multilinear algebra. The field has its origins in the study of spherical geometry as far back as antiquity. It also relates to astronomy, the geodesy of the Earth, and later the study of hyperbolic geometry by Lobachevsky. The simplest examples of smooth spaces are the plane and space curves and surfaces in the three-dimensional Euclidean space, and the study of these shapes formed the basis for development of modern differential geometry during the 18th and 19th centuries. Since the late 19th century, differential geometry has grown into a field concerned more generally with geometric structures on differentiable manifolds. A geometric structure is one which defines some notion of size, distance, shape, volume, or other rigidifying structure.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 在拓扑学中，同胚（英语：Homeomorphism）是两个拓扑空间之间的双连续函数。同胚是拓扑空间范畴中的同构；也就是说，它们是保持给定空间的所有拓扑性质的映射。如果两个空间之间存在同胚，那么这两个空间就称为同胚的，从拓扑学的观点来看，两个空间是相同的。 拓扑空间是一个几何物体，同胚就是把物体连续延展和弯曲，使其成为一个新的物体。因此，正方形和圆是同胚的，但球面和环面就不是。有一个笑话是说，拓扑学家不能区分咖啡杯和甜甜圈，这是因为一个足够柔软的甜甜圈可以捏成咖啡杯的形状（见图）。
In mathematics and more specifically in topology, a homeomorphism (from Greek roots meaning "similar shape", named by Henri Poincaré), also called topological isomorphism, or bicontinuous function, is a bijective and continuous function between topological spaces that has a continuous inverse function. Homeomorphisms are the isomorphisms in the category of topological spaces—that is, they are the mappings that preserve all the topological properties of a given space. Two spaces with a homeomorphism between them are called homeomorphic, and from a topological viewpoint they are the same. Very roughly speaking, a topological space is a geometric object, and a homeomorphism results from a continuous deformation of the object into a new shape. Thus, a square and a circle are homeomorphic to each other, but a sphere and a torus are not. However, this description can be misleading. Some continuous deformations do not produce homeomorphisms, such as the deformation of a line into a point.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 在数学中，度量空间（英语：Metric space）是具有距离这一个概念的集合，装配了一个称为度量的函数，用以表示此集合中任两个成员间的距离。历史上是由法国数学家莫里斯·弗雷歇在1906年于其法语著作《Sur quelques points du calcul fonctionnel》首次使用。 度量空间中最符合人们对于现实直观理解的为三维欧几里得空间。事实上，“度量”的概念即是欧几里得距离四个周知的性质之推广。欧几里得度量定义了两点间之距离为连接这两点的直线段之长度。此外，亦存在其他的度量空间，如椭圆几何与双曲几何，而在球体上以角度量测之距离亦为一度量。狭义相对论使用双曲几何的双曲面模型，作为速度之度量空间。 度量空间还能导出开集与闭集之类的拓扑性质，这导致了对更抽象的拓扑空间之研究。
In mathematics, a metric space is a set together with a notion of distance between its points. The distance is measured by a function called a metric or distance function. Metric spaces are a general setting for studying many of the concepts of mathematical analysis and geometry. The most familiar example of a metric space is 3-dimensional Euclidean space with its usual notion of distance. Other well-known examples are a sphere equipped with the angular distance and the hyperbolic plane. A metric may correspond to a metaphorical, rather than physical, notion of distance. For example, the set of 100-character Unicode strings can be equipped with the Hamming distance, which measures the number of characters that need to be changed to get from one string to another. Metric spaces appear in many different branches of mathematics. For example, Riemannian manifolds, normed vector spaces, and graphs may be viewed as metric spaces. In abstract algebra, the field of p-adic numbers is the completion of the field of rational numbers with respect to a certain metric.
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View content license ↗ 在数学中，某个集合 X 上的 σ-代数（英语：σ-algebra）又叫 σ-域（英语：σ-field），是 X 的某群子集合所构成的特殊子集族。这个子集族对于补集运算和可数个并集运算具有封闭性（因此对于可数个交集运算也是封闭的）。σ-代数在测度论里可以用来定义所谓的“可测集合”，是测度论的基础概念之一。 σ-代数的概念大约起始于1900~1930年，它随着测度论的发展而逐渐清晰。最著名的 σ-代数是关于实数轴测度的波莱尔σ-代数（得名于法国数学家埃米·波莱尔），以及1901年亨利·勒贝格建立的勒贝格σ-代数。而现代的测度理论的公理化体系就建立在勒贝格的相关理论之上。在这个领域中，σ-代数不仅仅是用于建立公理体系，也是一个强有力的工具，在定义许多重要的概念如条件期望和鞅的时候，都需要用到。
In mathematical analysis and in probability theory, a σ-algebra ("sigma algebra") is part of the formalism for defining sets that can be measured. In calculus and analysis, for example, σ-algebras are used to define the concept of sets with area or volume. In probability theory, they are used to define events for which a probability can be defined. In this way, σ-algebras help to formalize the notion of size. In formal terms, a σ-algebra (also σ-field, where the σ comes from the German Summe, meaning "sum") on a set X {\displaystyle X} is a nonempty collection Σ {\displaystyle \Sigma } of subsets of X {\displaystyle X} closed under complement, countable unions, and countable intersections. The ordered pair ( X , Σ ) {\displaystyle (X,\Sigma )} is called a measurable space.
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View content license ↗ 张量（英语：Tensor）在数学中是一个代数对象，描述了与矢量空间相关的代数对象集之间的多重线性映射。张量可以作为不同的对象之间的映射，例如矢量、标量以及其他张量。张量有很多种类型，包括标量和矢量、对偶矢量、矢量空间之间的多重线性映射，甚至还有一些运算，例如点积。张量的定义独立于任何基，尽管它们通常由与特定坐标系相关的基中的分量来表示；这些分量形成一个数组，可以将其视为高维矩阵。 n {\displaystyle n} 维空间上的 r {\displaystyle r} 阶张量有 n r {\displaystyle n^{r}} 个分量， r {\displaystyle r} 也称为该张量的秩（与矩阵的秩和阶均无关系）。
In mathematics, a tensor is an algebraic object that describes a multilinear relationship between sets of algebraic objects associated with a vector space. Tensors may map between different objects such as vectors, scalars, and even other tensors. There are many types of tensors, including scalars and vectors (which are the simplest tensors), dual vectors, multilinear maps between vector spaces, and even some operations such as the dot product. Tensors are defined independent of any basis, although they are often referred to by their components in a basis related to a particular coordinate system; those components form an array, which can be thought of as a high-dimensional matrix.
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View content license ↗ 拓扑空间（英语：Topological space）是一种赋予“一点附近”这个概念的抽象数学结构；拓扑空间也是一个集合，其元素称为点，由此可以定义出如收敛、连通、连续等概念。拓扑空间在现代数学的各个分支都有应用，是一个居于中心地位的、统一性的概念。拓扑空间有独立研究的价值，研究拓扑空间的数学分支称为拓扑学。
In mathematics, a topological space is, roughly speaking, a space in which closeness is defined but cannot necessarily be measured by a numeric distance. More specifically, a topological space is a set whose elements are called points, along with an additional structure called a topology, which can be defined as a set of neighbourhoods for each point that satisfy some axioms formalizing the concept of closeness. There are several equivalent definitions of a topology, the most commonly used of which is the definition through open sets. A topological space is the most general type of a mathematical space in which limits, continuity, and connectedness can be defined. Common types of topological spaces include Euclidean spaces, metric spaces and manifolds. Although very general, topological spaces are fundamental and are used in virtually every branch of modern mathematics. The study of topological spaces in their own right is called general topology (or point-set topology).
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View content license ↗ 切空间（Tangent space）是在某一点所有的切向量组成的线性空间。向量（切向量）存在多种定义。直观的讲，如果所研究的流形（Manifold）是一个三维空间中的曲面，则在每一点的切向量，就是和该曲面相切的向量，切空间就是和该曲面相切的平面。
In mathematics, the tangent space of a manifold is a generalization of tangent lines to curves in two-dimensional space and tangent planes to surfaces in three-dimensional space in higher dimensions. In the context of physics, the tangent space to a manifold at a point can be viewed as the space of possible velocities for a particle moving on the manifold.
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View content license ↗ 在数学上，特别是拓朴学中，开集是对实数开区间进行推广之后得到的抽象集合。 通常微积分的课程中，会借助欧式空间的距离去描述数列极限；直观上，当 n {\displaystyle n} 越来越大时，数列 x n {\displaystyle x_{n}} 跟 a {\displaystyle a} 极其靠近，则称 a {\displaystyle a} 是数列 x n {\displaystyle x_{n}} 的极限，但这需要距离去严谨的描述“靠近程度”，开集就是来自于“ a {\displaystyle a} 点附近”这样的直观概念。类似的，函数极限也需要距离的概念去严谨定义。
In general topology and mathematical analysis, an open set is a generalization of an open interval in the real line. In a metric space (a set with a distance defined between every two points), an open set is a set that, with every point P in it, contains all points of the metric space that are sufficiently near to P (that is, all points whose distance to P is less than some value depending on P). More generally, an open set is a member of a given collection of subsets of a given set, a collection that has the property of containing every union of its members, every finite intersection of its members, the empty set, and the whole set itself. A set in which such a collection is given is called a topological space, and the collection is called a topology. These conditions are very loose, and allow enormous flexibility in the choice of open sets. For example, every subset can be open (the discrete topology), or no subset can be open except the space itself and the empty set (the indiscrete topology).
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View content license ↗ 在拓扑空间中，闭集是指其补集为开集的集合。在一个拓扑空间内，闭集可以定义为一个包含所有其极限点的集合。在完备度量空间中，一个闭集的极限运算是闭合的。不要混淆于闭流形。
In topology, a branch of mathematics, a closed set is a set that contains all of its boundary points. An example is the closed interval [ a , b ] {\displaystyle [a,b]} , which is closed in the real line because it includes both points a {\displaystyle a} and b {\displaystyle b} of its boundary. A point is on the boundary if every neighbourhood of it meets both the set and its complement. A set is thus closed if it is equal to its closure, the set obtained by adjoining all boundary points to it. Closed sets are defined as subsets of topological spaces. The topology of a space is usually described in terms of its open sets, which determine what counts as a "neighborhood" of its points. A set is closed if it is the complement of an open set.
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View content license ↗ 在数学中，曲（qū）率（英语：curvature）即“弯曲度”，是描述几何体弯曲程度的量；直观地说，曲率是曲线偏离直线的量（程度），或是曲面偏离平面的量（程度）。 在不同的几何学领域中，曲率的具体定义不完全相同。曲率可分为外在曲率和内蕴曲率，二者有重要的区别。前者的定义需要把几何体嵌入到欧氏空间中，后者则是直接定义在黎曼流形上。 曲线的曲率通常是标量，但也可以定义曲率向量。对于更复杂的对象，曲率要用更复杂的线性代数来描述，例如一般的黎曼曲率张量。
In mathematics, curvature is any of several strongly related concepts in geometry that intuitively measure the amount by which a curve deviates from being a straight line or by which a surface deviates from being a plane. If a curve or surface is contained in a larger space, curvature can be defined extrinsically relative to the ambient space. Curvature of Riemannian manifolds of dimension at least two can be defined intrinsically without reference to a larger space. For curves, curvature describes how sharply the curve bends. The canonical examples are circles: smaller circles bend more sharply and hence have higher curvature. For a point on a general curve, the direction of the curve is described by its tangent line. How sharply the curve is bending at that point can be measured by how much that tangent line changes direction per unit distance along the curve. Curvature measures the angular rate of change of the direction of the tangent line, or the unit tangent vector, of the curve per unit distance along the curve. Curvature is expressed in units of radians per unit distance.
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View content license ↗ 测地线（英语：geodesic）又称大地线或短程线，数学上可视作直线在弯曲空间中的推广；在有度规定义存在之时，测地线可以定义为空间中两点的局域最短路径。测地线（英语：geodesic）的名字来自对于地球尺寸与形状的大地测量学（英语：geodesy）。
In geometry, a geodesic () is a curve representing in some sense the locally shortest path (arc) between two points in a surface, or more generally in a Riemannian manifold. The term also has meaning in any differentiable manifold with a connection. It is a generalization of the notion of a "straight line". The noun geodesic and the adjective geodetic come from geodesy, the science of measuring the size and shape of Earth, though many of the underlying principles can be applied to any ellipsoidal geometry. In the original sense, a geodesic was the shortest route between two points on the Earth's surface. For a spherical Earth, it is a segment of a great circle (see also great-circle distance). The term has since been generalized to more abstract mathematical spaces; for example, in graph theory, one might consider a geodesic between two vertices/nodes of a graph. In a Riemannian manifold or submanifold, geodesics are characterised by the property of having vanishing geodesic curvature.
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View content license ↗ 微分形式（英语：Differential form）是多变量微积分，微分拓扑和张量分析领域的一个数学概念。现代意义上的微分形式，及其以楔积和外微分结构形成外代数的想法，都是由法国数学家埃里·嘉当引入的。 例如，一元微积分中的表达式 f ( x ) d x {\displaystyle f(x)\ dx} 是1-形式的一个例子，并且可以在 f {\displaystyle f} 定义域内的一个区间 [ a , b ] {\displaystyle [a,b]} 上进行积分： ∫ a b f ( x ) d x .
In mathematics, differential forms provide a unified approach to define integrands over curves, surfaces, volumes, and higher-dimensional manifolds. The modern notion of differential forms was pioneered by Élie Cartan. It has many applications, especially in geometry, topology and physics. For instance, the expression f ( x ) d x {\displaystyle f(x)\,dx} is an example of a 1-form, and can be integrated over an interval [ a , b ] {\displaystyle [a,b]} contained in the domain of f {\displaystyle f} : ∫ a b f ( x ) d x .
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View content license ↗ 在数学中，流形（英语：manifold）是一类可以局部欧几里得空间化的拓扑空间，即在此拓扑空间中，每个点附近都类似于欧氏空间。更精确地说，n维流形或简称n流形（n-manifold）是指一种拓扑空间，其性质是每个点都有一个邻域同胚于n维欧氏空间的某个开集。 直观地说，流形可以在局部引入坐标，因此即使整体形状弯曲或较复杂，在足够小的范围内仍可像平直空间一样描述。流形是欧几里得空间中的曲线、曲面等概念的推广；欧几里得空间本身就是最简单的流形的实例，而类似于地球表面的球面则是一个稍微复杂的例子。一般地，流形可以看作由许多局部类似于欧几里得空间的平直的“坐标片”折弯并拼合而成，不同坐标片之间通过坐标变换相互衔接。 一维流形的例子包括直线和圆，但不包括自交的“8”字形曲线，因为其交点附近不像直线的一段。二维流形又称为曲面，其例子包括平面、球面和环面。其中，环面也可出现在物理系统的位形空间中，例如双摆的位形空间。 流形是几何学、拓扑学和现代数学物理中的基本概念，常用于描述几何形体及其局部性质。通过在流形上加入额外结构，可以得到可微流形、黎曼流形、辛流形、洛伦兹流形等不同类型。可微流形作为一个研究形体的可微性的平台，允许在其上讨论微积分；黎曼流形可以定义距离和角度；辛流形常用于经典力学的哈密顿形式，其相空间通常带有辛结构；广义相对论中的时空模型则通常使用四维洛伦兹流形或更一般的伪黎曼流形。物理学上，经典力学的相空间和构造广义相对论的时空模型的四维伪黎曼流形都是流形的实例。位形空间中也可以定义流形，环面就是双摆的位形空间。 在直观上，一般可以把几何形体的拓扑结构看作是完全“柔软”的，因为所有变形（同胚）会保持拓扑结构不变；而把解析几何结构看作是“刚性”的，因为整体的结构都是固定的。例如，当一个多项式在 ( 0 , 1 ) {\displaystyle (0,1)} 区间的取值确定了，则其在整个实数范围的值都随之被固定，可见局部的变动会导致全局的变化。光滑流形可以看作是介于纯粹拓扑对象与带有更强解析结构的对象之间的模型。
In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point. More precisely, an n {\displaystyle n} -dimensional manifold, or n {\displaystyle n} -manifold for short, is a topological space with the property that each point has a neighborhood that is homeomorphic to an open subset of n {\displaystyle n} -dimensional Euclidean space. One-dimensional manifolds include lines and circles, but not self-crossing curves such as a figure-eight. Two-dimensional manifolds are also called surfaces. Examples include the plane, the sphere, and the torus, and also the Klein bottle and real projective plane. The concept of a manifold is central to many parts of geometry and modern mathematical physics because it allows complicated structures to be described in terms of well-understood topological properties of simpler spaces. Manifolds naturally arise as solution sets of systems of equations and as graphs of functions.
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View content license ↗ 勒贝格积分（英语：Lebesgue integral）是现代数学中的一个积分概念，它将积分运算扩展到任何测度空间中。在最简单的情况下，对一个非负值的函数的积分可以看作是函数图像与 x {\displaystyle x} 轴之间的面积。勒贝格积分则将积分运算扩展到更广的函数（可测函数），并且也扩展了可以进行积分运算的集合（可测空间）。 最早的积分运算对于非负值的函数来说，其积分相当于使用求极限的手段来计算一个多边形的面积，但这过程需要函数足够规则。但是随着对更加不规则的函数的积分运算的需要不断产生，很快就产生了对更加广义的求极限手段的要求来定义相应的积分运算。 在实分析和在其它许多数学领域中勒贝格积分拥有一席重要的地位。勒贝格积分是以昂利·勒贝格命名的，他于1904年引入了这个积分定义。 今天勒贝格积分有狭义和广义两种意义。广义地说是对于一个在一般测度空间（的子集合）上的函数积分，在这情况下其测度不必然是勒贝格测度。狭义则是指对于勒贝格测度在实数线或者更高维数的欧几里得空间的一个子集合上函数的积分。
In mathematics, the integral of a non-negative function of a single variable can be regarded, in the simplest case, as the area between the graph of that function and the x-axis. The Lebesgue integral, named after French mathematician Henri Lebesgue, is one way to make this concept rigorous and to extend it to more general functions. The Lebesgue integral is more general than the Riemann integral, which it largely replaced in mathematical analysis since the first half of the 20th century. It can accommodate functions with discontinuities arising in many applications that are pathological from the perspective of the Riemann integral. The Lebesgue integral also has generally better analytical properties. For instance, under mild conditions, it is possible to exchange limits with Lebesgue integration, while the conditions for doing this with a Riemann integral are comparatively restrictive. Furthermore, the Lebesgue integral can be generalized in a straightforward way to more general spaces, measure spaces, such as those that arise in probability theory.
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View content license ↗ 在泛函分析中，卷积（convolution），或译为叠积、褶积或旋积，是透过两个函数 f {\displaystyle f} 和 g {\displaystyle g} 生成第三个函数的一种数学算子，表征函数 f {\displaystyle f} 与经过翻转和平移的 g {\displaystyle g} 的乘积函数所围成的曲边梯形的面积。如果将参加卷积的一个函数看作区间的指示函数，卷积还可以被看作是“移动平均”的推广。
In mathematics (in particular, functional analysis), convolution is a mathematical operation on two functions f {\displaystyle f} and g {\displaystyle g} that produces a third function f ∗ g {\displaystyle f*g} , as the integral of the product of the two functions after one is reflected about the y-axis and shifted. The term convolution refers to both the resulting function and to the process of computing it. The integral is evaluated for all values of shift, producing the convolution function. The choice of which function is reflected and shifted before the integral does not change the integral result (see commutativity). Graphically, it expresses how the 'shape' of one function is modified by the other.
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View content license ↗ 散（sàn）度（divergence）是向量分析中的一个向量算子，将向量空间上的一个向量场（矢量场）对应到一个标量场上。散度描述的是向量场里一个点是汇聚点还是发源点，形象地说，就是这包含这一点的一个微小体元中的向量是“向外”居多还是“向内”居多。 举例来说，考虑空间中的静电场，其空间里的电场强度是一个矢量场。正电荷附近，电场线“向外”发射，所以正电荷处的散度为正值，电荷越大，散度越大。负电荷附近，电场线“向内”，所以负电荷处的散度为负值，电荷越大，散度越小。向量值函数的散度为一个标量，而二阶张量的散度是向量值函数。
In vector calculus, divergence is a vector operator that operates on a vector field, producing a scalar field giving the rate that the vector field alters the volume in an infinitesimal neighborhood of each point. (In 2D this "volume" refers to area.) More precisely, the divergence at a point is the rate that the flow of the vector field modifies a volume about the point in the limit, as a small volume shrinks down to the point. As an example, consider air as it is heated or cooled. The velocity of the air at each point defines a vector field. While air is heated in a region, it expands in all directions, and thus the velocity field points outward from that region. The divergence of the velocity field in that region would thus have a positive value. While the air is cooled and thus contracting, the divergence of the velocity has a negative value.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 在向量微积分中，梯度（英语：gradient）是一种关于多元导数的概括。平常的一元（单变量）函数的导数是标量值函数，而多元函数的梯度是向量值函数。多元可微函数 f {\displaystyle f} 在点 P {\displaystyle P} 上的梯度，是以 f {\displaystyle f} 在 P {\displaystyle P} 上的偏导数为分量的向量。 就像一元函数的导数表示这个函数图形的切线的斜率，如果多元函数在点 P {\displaystyle P} 上的梯度不是零向量，则它的方向是这个函数在 P {\displaystyle P} 上最大增长的方向、而它的量是在这个方向上的增长率。 梯度向量中的幅值和方向是与坐标的选择无关的独立量。 在欧几里德空间或更一般的流形之间的多元可微映射的向量值函数的梯度推广是雅可比矩阵。在巴拿赫空间之间的函数的进一步推广是弗雷歇导数。
In vector calculus, the gradient of a scalar-valued differentiable function f {\displaystyle f} of several variables is the vector field (or vector-valued function) ∇ f {\displaystyle \nabla f} whose value at a point p {\displaystyle p} gives the direction and the rate of fastest increase. The gradient transforms like a vector under change of basis of the space of variables of f {\displaystyle f} . If the gradient of a function is non-zero at a point p {\displaystyle p} , the direction of the gradient is the direction in which the function increases most quickly from p {\displaystyle p} , and the magnitude of the gradient is the rate of increase in that direction, the greatest absolute directional derivative. Further, a point where the gradient is the zero vector is known as a stationary point.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 拉普拉斯变换（英语：Laplace transform）是应用数学中常用的一种积分变换，又名拉氏变换，其符号为 L { f ( t ) } {\displaystyle \displaystyle {\mathcal {L}}\left\{f(t)\right\}} 。拉氏变换是一个线性变换，可将一个有实数变量 t ( t ≥ 0 ) {\displaystyle t(t\geq 0)} 的函数变换为一个变量为复数 s {\displaystyle s} 的函数： F ( s ) = ∫ 0 ∞ f ( t ) e − s t d t .
In mathematics, the Laplace transform, named after Pierre-Simon Laplace (), is an integral transform that converts a function of a real variable (usually t {\displaystyle t} , in the time domain) to a function of a complex variable s {\displaystyle s} (in the complex-valued frequency domain, also known as s-domain or s-plane). The functions are often denoted using a lowercase symbol for the time-domain function and the corresponding uppercase symbol for the frequency-domain function, e.g. x ( t ) {\displaystyle x(t)} and X ( s ) {\displaystyle X(s)} . The transform is useful for converting differentiation and integration in the time domain into the algebraic operations multiplication and division in the Laplace domain (analogous to how logarithms are useful for simplifying multiplication and division into addition and subtraction).
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
View content license ↗ 在数学中，泰勒级数（英语：Taylor series，Taylor expansion）用无限项连加式——级数来表示一个函数，这些相加的项由函数在某一点的导数求得。泰勒级数是以于1715年发表了泰勒公式和泰勒展开的英国数学家布鲁克·泰勒（Sir Brook Taylor）来命名的。通过函数在自变量零点的导数求得的泰勒级数又叫做麦克劳林级数（英语：Maclaurin series），以苏格兰数学家科林·麦克劳林（Colin Maclaurin）的名字命名。 拉格朗日在1797年之前，最先提出带有余项的现在形式的泰勒定理。实际应用中，泰勒级数需要截断，只取有限项，可以用泰勒定理估算这种近似的误差。一个函数的有限项的泰勒级数叫做泰勒多项式。一个函数的泰勒级数是其泰勒多项式的极限（如果存在极限）。即使泰勒级数在每点都收敛，函数与其泰勒级数也可能不相等。在开区间（或复平面上的开区间）上，与自身泰勒级数相等的函数称为解析函数。
In mathematical analysis, the Taylor series or Taylor expansion of a function is an infinite sum of terms that are expressed in terms of the function's derivatives at a single point. For most common functions, the function and the sum of its Taylor series are equal near this point. Taylor series are named after Brook Taylor, who introduced them in 1715. A Taylor series is also called a Maclaurin series when 0 is the point where the derivatives are considered, after Colin Maclaurin, who made extensive use of this special case of Taylor series in the 18th century. The partial sum formed by the first n + 1 terms of a Taylor series is a polynomial of degree n that is called the nth Taylor polynomial of the function. Taylor polynomials are approximations of a function, which become generally more accurate as n increases. Taylor's theorem gives quantitative estimates on the error introduced by the use of such approximations. If the Taylor series of a function is convergent, its sum is the limit of the infinite sequence of the Taylor polynomials.
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Wikipedia contributors · Retrieved2026-10-04 · CC BY-SA 4.0. Introductions were extracted as plain text and shortened. Language versions may emphasize different aspects.For concept reference; consult the original standards for authoritative requirements.
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