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    Topology

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    • Preliminaries and Introduction
      • 1.1Introduction to Topology - Basics
      • 1.2Notions in Set Theory
      • 1.3Basics of Metric Spaces
    • Convergence in Topology
      • 2.1Sequence Convergence in Metric Spaces
      • 2.2Cauchy Sequences
      • 2.3Point-set Topology
    • Introduction to Normed Spaces
      • 3.1Basic Concepts and Notions
      • 3.2Properties of Normed Spaces
      • 3.3Subspaces in Normed Spaces
    • Vector Spaces & Linear Operators
      • 4.1Review of Vector Spaces
      • 4.2Linear Operators and functionals
      • 4.3Topological Vector Spaces
    • Finite Dimensional Normed Spaces
      • 5.1Geometry of Normed Spaces
      • 5.2Finite Dimensional Normed Spaces and Subspaces
      • 5.3The Hahn-Banach Theorem
    • Infinite Dimensional Normed Spaces
      • 6.1The Banach Fixed Point Theorem
      • 6.2The Principle of Uniform Boundedness
      • 6.3Weak and Weak* topologies
    • Compactness and Completeness in Normed Spaces
      • 7.1Review of Compactness
      • 7.2Compactness in Normed Spaces
      • 7.3Complete Normed Spaces (Banach Spaces)
    • Applications of Normed Spaces
      • 8.1Normed Spaces in Functional Analysis
      • 8.2Normed Spaces in Quantum Mechanics
      • 8.3Normed Spaces in Engineering and Sciences

    Finite Dimensional Normed Spaces

    Geometry of Normed Spaces

    vector space on which a distance is defined

    Vector space on which a distance is defined.

    In the study of topology and normed spaces, understanding the geometry of these spaces is crucial. This article will delve into the concepts of distance, angle, and orthogonality in normed spaces, and explore the properties that make them geometrically unique.

    Distance in Normed Spaces

    In a normed space, the distance between two points is defined by the norm of the difference between the two points. This concept is a generalization of the Euclidean distance in real space. The distance function in a normed space has the following properties:

    1. Non-negativity: The distance between any two points is always non-negative.
    2. Identity of indiscernibles: The distance between two points is zero if and only if the two points are the same.
    3. Symmetry: The distance from point A to point B is the same as the distance from point B to point A.
    4. Triangle inequality: The distance from point A to point C is less than or equal to the sum of the distances from point A to point B and from point B to point C.

    Angle and Orthogonality

    In normed spaces, the concepts of angle and orthogonality are more complex than in Euclidean space. In a normed space, two vectors are orthogonal if their inner product is zero. However, not all normed spaces have an inner product, so the concept of orthogonality is not always applicable.

    The concept of angle in a normed space is also more complex. In Euclidean space, the angle between two vectors can be defined using the dot product. In a normed space, however, there is no general definition of angle that is applicable in all cases.

    Unique Geometric Properties of Normed Spaces

    Normed spaces have several unique geometric properties. For example, every normed space is a metric space, but not every metric space is a normed space. This is because the norm induces a metric, but not all metrics come from a norm.

    Another unique property of normed spaces is that they are always convex. This means that for any two points in the space, the line segment connecting them is entirely contained within the space.

    In conclusion, the geometry of normed spaces is a rich and complex field that generalizes many concepts from Euclidean geometry. Understanding this geometry is crucial for studying more advanced topics in topology and functional analysis.

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