3.1 Statement and proof of the Hahn-Banach Theorem

2 min readjuly 22, 2024

The is a cornerstone of functional analysis. It allows us to extend bounded linear functionals from subspaces to entire normed spaces, keeping their norms intact. This powerful tool opens doors to studying dual spaces and weak topologies.

The theorem's proof uses , a heavy-duty tool in set theory. It constructs a maximal of the original functional, showing that this extension must cover the whole space. This approach gives us the extension's existence without explicitly building it.

Hahn-Banach Theorem

Hahn-Banach theorem for normed spaces

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  • Assumes XX is a normed linear space contains a subspace YY
  • Considers a ff defined on the subspace YY
  • Guarantees the existence of a FF defined on the entire space XX that extends ff
    • Preserves the values of ff on YY, so F(y)=f(y)F(y) = f(y) for all yYy \in Y
    • Maintains the norm of ff, ensuring F=f\|F\| = \|f\|

Proof using Zorn's lemma

  • Defines the set F\mathcal{F} consisting of pairs (Z,g)(Z, g)
    • ZZ represents a subspace of XX containing the original subspace YY
    • gg is a bounded linear functional on ZZ that extends the original functional ff
  • Introduces a on F\mathcal{F} where (Z1,g1)(Z2,g2)(Z_1, g_1) \leq (Z_2, g_2) if Z1Z_1 is a subset of Z2Z_2 and g2g_2 restricted to Z1Z_1 equals g1g_1
  • Demonstrates that every in F\mathcal{F} has an
    • Constructs the upper bound (Z,g)(Z, g) by taking the union of subspaces ZαZ_\alpha and defining g(z)=gα(z)g(z) = g_\alpha(z) for zZαz \in Z_\alpha
    • Verifies that (Z,g)(Z, g) is indeed an upper bound for the chain
  • Applies Zorn's Lemma to conclude that F\mathcal{F} has a (Z0,g0)(Z_0, g_0)
  • Argues that Z0Z_0 must be equal to the entire space XX, completing the proof of the theorem

Significance in functional extension

  • Enables the extension of bounded linear functionals from a subspace to the entire normed linear space
  • Ensures that the extended functional preserves the norm of the original functional
  • Provides a powerful tool for studying dual spaces and weak topologies in functional analysis
  • Guarantees the existence of the extension without explicitly constructing it

Applications to normed spaces

  • Applies to the space C[0,1]C[0,1] of continuous functions on the interval [0,1][0,1] with the supremum norm
    • Considers the subspace YY of polynomials and defines f(p)=p(0)f(p) = p(0) for polynomials pYp \in Y
    • Asserts the existence of a bounded linear functional FF on C[0,1]C[0,1] that extends ff
  • Extends to the space 1\ell^1 of absolutely summable sequences with the 1\ell^1 norm
    • Takes the subspace YY of sequences with only finitely many non-zero terms
    • Defines a functional f((xn))=n=1anxnf((x_n)) = \sum_{n=1}^\infty a_n x_n for sequences (xn)Y(x_n) \in Y, where (an)(a_n) is a sequence in \ell^\infty
    • Confirms the existence of an extension of ff to a bounded linear functional on the entire space 1\ell^1

Key Terms to Review (25)

Banach space: A Banach space is a complete normed vector space, meaning it is a vector space equipped with a norm such that every Cauchy sequence converges to a limit within the space. This property of completeness is crucial for ensuring the convergence of sequences, which allows for more robust analysis and applications in functional analysis.
Bounded Linear Functional: A bounded linear functional is a linear map from a vector space to its underlying field that is continuous and has a finite norm. This means that there exists a constant such that the absolute value of the functional applied to any vector in the space is less than or equal to this constant times the norm of that vector. Bounded linear functionals play a crucial role in understanding dual spaces, the Hahn-Banach Theorem, and the weak* topology, as they help in extending functionals while preserving continuity and facilitate various analyses of convergence and topology in functional spaces.
Bounded linear functional: A bounded linear functional is a specific type of linear functional that is continuous and maps elements from a normed vector space to the underlying field, typically the real or complex numbers. This concept is essential for understanding dual spaces, as it relates directly to the behavior of linear functionals in relation to the norms of the spaces they operate on.
Boundedness: Boundedness refers to the property of a function or operator whereby it does not grow indefinitely, meaning there exists a constant that limits the output relative to the input. This concept is central in analysis, particularly in understanding linear operators and their behavior within normed linear spaces.
Chain: In the context of functional analysis, a chain refers to a totally ordered subset of a vector space, where each element is comparable to every other element in terms of the ordering relation. This concept is crucial when discussing the Hahn-Banach Theorem, as it relates to extending linear functionals and understanding their properties in ordered vector spaces.
Compactness Argument: A compactness argument refers to a method used in functional analysis and mathematical logic, leveraging the property of compactness in topological spaces. This argument shows that if every finite subset of a collection of statements has a model, then the entire collection also has a model. It's crucial for establishing the existence of functionals or extending them under certain conditions, especially in the context of the Hahn-Banach Theorem.
Completeness: Completeness in the context of functional analysis refers to a property of a space whereby every Cauchy sequence converges to a limit within that space. This concept is essential in differentiating between normed spaces and Banach spaces, emphasizing that a Banach space is a normed space that is complete, ensuring that limits of sequences are always contained within the space.
Continuity: Continuity refers to the property of a function where small changes in the input result in small changes in the output. This concept is vital in analysis as it ensures that the behavior of functions is predictable and stable, particularly when dealing with linear operators and spaces. Understanding continuity is crucial in various contexts, such as operator norms, the behavior of adjoints, and applications within spectral theory and functional analysis.
David Hilbert: David Hilbert was a German mathematician whose work laid foundational aspects of modern functional analysis, particularly through his contributions to the theory of infinite-dimensional spaces and linear operators. His ideas and results have become pivotal in understanding various areas of mathematics, influencing topics like the Hahn-Banach theorem and spectral theory.
Dual Pairing: Dual pairing is a mathematical concept that involves a bilinear form between a vector space and its dual space, allowing for the evaluation of linear functionals on vectors. This relationship is foundational in functional analysis, as it connects elements of a vector space with their corresponding linear functionals, facilitating the understanding of dual spaces and supporting the application of the Hahn-Banach theorem.
Dual Space: The dual space of a vector space consists of all linear functionals defined on that space. It captures the idea of measuring or evaluating vectors in terms of how they interact with linear functionals, which are themselves linear maps that take vectors as input and return scalars.
Embedding: In functional analysis, embedding refers to a way of representing one mathematical structure within another, typically more complex, structure. This concept is particularly significant when considering the Hahn-Banach Theorem, which facilitates the extension of linear functionals while preserving certain properties, allowing for an effective comparison and integration of spaces such as normed spaces into larger ones like Banach spaces.
Extension: In functional analysis, an extension refers to a way of expanding a linear functional defined on a subspace of a vector space to the entire space while preserving its properties. This concept is crucial for understanding how certain linear functionals can be broadened without losing their original characteristics, allowing for greater versatility in analysis and applications.
Extension Property: The extension property refers to the ability to extend a linear functional defined on a subspace of a vector space to the entire space while preserving its properties, such as linearity and boundedness. This concept is crucial in understanding the Hahn-Banach Theorem, which guarantees that under certain conditions, such extensions are possible, allowing us to work with larger spaces while maintaining the characteristics of functionals defined on smaller subspaces.
Hahn-Banach Theorem: The Hahn-Banach Theorem is a fundamental result in functional analysis that allows the extension of bounded linear functionals defined on a subspace to the entire space without increasing their norm. This theorem is crucial for understanding dual spaces, as it provides a way to construct continuous linear functionals, which are essential in various applications across different mathematical domains.
Isomorphism: Isomorphism is a mathematical concept that describes a mapping between two structures that preserves their properties and operations. In functional analysis, isomorphisms reveal deep connections between spaces, such as the relationship between a space and its dual space, as well as the implications of the Hahn-Banach Theorem in establishing extensions of linear functionals without losing their properties.
Maximal element: A maximal element in a partially ordered set is an element that is not less than any other element in that set with respect to the given order. In simpler terms, if you have a set of items and you can't find anything that's 'greater' than this one, then it's maximal. This concept connects to functional analysis through its role in various theorems and proofs, particularly in establishing the existence of certain functionals or extensions in spaces, such as those explored in the Hahn-Banach Theorem.
Normed Space: A normed space is a vector space equipped with a function called a norm that assigns a non-negative length or size to each vector in the space. This norm allows for the measurement of distance and the exploration of convergence, continuity, and other properties within the space, facilitating the analysis of linear functionals, dual spaces, and other important concepts in functional analysis.
Partial Order: A partial order is a binary relation that is reflexive, antisymmetric, and transitive, allowing for a comparison of elements in a set that may not all be comparable. This means some elements can be related, while others may not have a defined relationship, creating a structure where certain elements can be considered 'less than' or 'equal to' others, but not necessarily in a total manner. Understanding partial orders is crucial when discussing concepts like vector spaces and their duals in functional analysis, particularly in relation to the Hahn-Banach Theorem.
Separating Hyperplane: A separating hyperplane is a flat affine subspace that divides a space into two distinct half-spaces, where points on one side belong to one set and points on the other side belong to another set. This concept is crucial in various mathematical fields, particularly in optimization and functional analysis, as it provides a geometric interpretation of linear separation between convex sets. Separating hyperplanes play an essential role in understanding the Hahn-Banach theorem, which involves extending linear functionals and thus relates to the ability to separate points from convex sets.
Stefan Banach: Stefan Banach was a prominent Polish mathematician who is best known for his foundational contributions to functional analysis, particularly through the establishment of Banach spaces and the Hahn-Banach theorem. His work laid the groundwork for modern analysis and introduced key concepts that are essential for understanding the structure of normed spaces and bounded linear operators.
Sublinear Function: A sublinear function is a real-valued function defined on a vector space that satisfies two main properties: positive homogeneity and subadditivity. This means that for any scalar $eta \geq 0$ and any vectors $x$ and $y$, the function meets the criteria $f(\beta x) = \beta f(x)$ and $f(x + y) \leq f(x) + f(y)$. Sublinear functions play a crucial role in the Hahn-Banach Theorem as they help extend linear functionals while preserving their boundedness.
Upper Bound: An upper bound is a value that is greater than or equal to every element in a given set, providing a limit beyond which no elements of the set can exceed. This concept is essential in various mathematical contexts, especially in optimization and functional analysis, as it helps define the constraints within which solutions exist. Understanding upper bounds allows for effective analysis of functions and their properties, particularly in proving the existence of continuous linear functionals.
Weak Topology: Weak topology is a type of topology on a normed space that is generated by the continuous linear functionals defined on that space. Unlike the standard topology, which is determined by the norm, the weak topology allows for convergence based on the behavior of these linear functionals, making it particularly useful in functional analysis for studying dual spaces and compactness properties.
Zorn's Lemma: Zorn's Lemma is a fundamental principle in set theory that states if every chain (a totally ordered subset) in a partially ordered set has an upper bound, then the entire set contains at least one maximal element. This lemma is crucial for proving the existence of various mathematical objects and structures, particularly in functional analysis, where it supports the Hahn-Banach Theorem.
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