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from Wikipedia
For the function that maps a Person to their Favorite Food, the image of Gabriela is Apple. The preimage of Apple is the set {Gabriela, Maryam}. The preimage of Fish is the empty set. The image of the subset {Richard, Maryam} is {Rice, Apple}. The preimage of {Rice, Apple} is {Gabriela, Richard, Maryam}.

In mathematics, for a function , the image of an input value is the single output value produced by when passed . The preimage of an output value is the set of input values that produce .

More generally, evaluating at each element of a given subset of its domain produces a set, called the "image of under (or through) ". Similarly, the inverse image (or preimage) of a given subset of the codomain is the set of all elements of that map to a member of

The image of the function is the set of all output values it may produce, that is, the image of . The preimage of is the preimage of the codomain . Because it always equals (the domain of ), it is rarely used.

Image and inverse image may also be defined for general binary relations, not just functions.

Definition

[edit]
is a function from domain to codomain . The image of element is element . The preimage of element is the set {}. The preimage of element is .
is a function from domain to codomain . The image of all elements in subset is subset . The preimage of is subset
is a function from domain to codomain The yellow oval inside is the image of . The preimage of is the entire domain

The word "image" is used in three related ways. In these definitions, is a function from the set to the set

Image of an element

[edit]

If is a member of then the image of under denoted is the value of when applied to is alternatively known as the output of for argument

Given the function is said to take the value or take as a value if there exists some in the function's domain such that Similarly, given a set is said to take a value in if there exists some in the function's domain such that However, takes [all] values in and is valued in means that for every point in the domain of .

Image of a subset

[edit]

Throughout, let be a function. The image under of a subset of is the set of all for It is denoted by or by when there is no risk of confusion. Using set-builder notation, this definition can be written as[1][2]

This induces a function where denotes the power set of a set that is the set of all subsets of See § Notation below for more.

Image of a function

[edit]

The image of a function is the image of its entire domain, also known as the range of the function.[3] This last usage should be avoided because the word "range" is also commonly used to mean the codomain of

Generalization to binary relations

[edit]

If is an arbitrary binary relation on then the set is called the image, or the range, of Dually, the set is called the domain of

Inverse image

[edit]

Let be a function from to The preimage or inverse image of a set under denoted by is the subset of defined by

Other notations include and [4] The inverse image of a singleton set, denoted by or by is also called the fiber or fiber over or the level set of The set of all the fibers over the elements of is a family of sets indexed by

For example, for the function the inverse image of would be Again, if there is no risk of confusion, can be denoted by and can also be thought of as a function from the power set of to the power set of The notation should not be confused with that for inverse function, although it coincides with the usual one for bijections in that the inverse image of under is the image of under

Notation for image and inverse image

[edit]

The traditional notations used in the previous section do not distinguish the original function from the image-of-sets function ; likewise they do not distinguish the inverse function (assuming one exists) from the inverse image function (which again relates the powersets). Given the right context, this keeps the notation light and usually does not cause confusion. But if needed, an alternative[5] is to give explicit names for the image and preimage as functions between power sets:

Arrow notation

[edit]
  • with
  • with

Star notation

[edit]
  • instead of
  • instead of

Other terminology

[edit]
  • An alternative notation for used in mathematical logic and set theory is [6][7]
  • Some texts refer to the image of as the range of [8] but this usage should be avoided because the word "range" is also commonly used to mean the codomain of

Examples

[edit]
  1. defined by
    The image of the set under is The image of the function is The preimage of is The preimage of is also The preimage of under is the empty set
  2. defined by
    The image of under is and the image of is (the set of all positive real numbers and zero). The preimage of under is The preimage of set under is the empty set, because the negative numbers do not have square roots in the set of reals.
  3. defined by
    The fibers are concentric circles about the origin, the origin itself, and the empty set (respectively), depending on whether (respectively). (If then the fiber is the set of all satisfying the equation that is, the origin-centered circle with radius )
  4. If is a manifold and is the canonical projection from the tangent bundle to then the fibers of are the tangent spaces This is also an example of a fiber bundle.
  5. A quotient group is a homomorphic image.

Properties

[edit]
Counter-examples based on the real numbers
defined by
showing that equality generally need
not hold for some laws:
Image showing non-equal sets: The sets and are shown in blue immediately below the -axis while their intersection is shown in green.

General

[edit]

For every function and all subsets and the following properties hold:

Image Preimage

(equal if for instance, if is surjective)[9][10]

(equal if is injective)[9][10]
[9]
[11] [11]
[11] [11]

Also:

Multiple functions

[edit]

For functions and with subsets and the following properties hold:

Multiple subsets of domain or codomain

[edit]

For function and subsets and the following properties hold:

Image Preimage
[11][12]
[11][12]
(equal if is injective[13])
[11]
(equal if is injective[13])
[11]

(equal if is injective)

The results relating images and preimages to the (Boolean) algebra of intersection and union work for any collection of subsets, not just for pairs of subsets:

(Here, can be infinite, even uncountably infinite.)

With respect to the algebra of subsets described above, the inverse image function is a lattice homomorphism, while the image function is only a semilattice homomorphism (that is, it does not always preserve intersections).

See also

[edit]

Notes

[edit]

References

[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
In mathematics, the image of a set SS under a function f:XYf: X \to Y is defined as the subset f(S)={f(x)xS}f(S) = \{ f(x) \mid x \in S \} of the codomain YY, comprising all elements of YY that are produced as outputs by applying ff to elements of SS. This concept captures the "reach" of the function restricted to SS, distinguishing it from the full codomain, which may include elements not attained by ff. When SS coincides with the entire domain XX, the image f(X)f(X) is commonly referred to as the range of ff or simply the image of the function, representing the actual set of all possible outputs without regard to the 's size. A function is surjective (or onto) its image equals the , meaning every element in YY is attained. Key properties of images include monotonicity—for subsets S1S2S_1 \subseteq S_2, f(S1)f(S2)f(S_1) \subseteq f(S_2)—and preservation of unions, as f(S1S2)=f(S1)f(S2)f(S_1 \cup S_2) = f(S_1) \cup f(S_2), though intersections are preserved only up to inclusion in general. The notion of image extends across mathematical disciplines; in linear algebra, for a linear map T:VWT: V \to W between vector spaces, the image is the subspace im(T)={T(v)vV}\operatorname{im}(T) = \{ T(v) \mid v \in V \}, which equals the span of the columns of the matrix representing TT and determines the map's rank via the rank-nullity theorem. In topology and analysis, images under continuous functions preserve connectedness and compactness, aiding in the study of spaces and limits. These properties underpin applications in optimization, where images define feasible sets, and in computer science, for modeling data transformations.

Core Definitions

Image of an Element

In , the of an element under a function is defined as follows: for a function f:XYf: X \to Y and an element xXx \in X, the f(x)f(x) is the unique element yYy \in Y such that y=f(x)y = f(x). This notation f(x)f(x) directly represents the output assigned to the input xx, encapsulating the core operation of the function as a rule that pairs each domain element with exactly one element. This concept underscores the mapping aspect of functions, where ff systematically associates elements of the domain XX to elements of the YY. Functions are required to be total, meaning every xXx \in X has a defined f(x)f(x), and single-valued, ensuring that no input maps to more than one output, which distinguishes them from general relations. Without these properties, the image would not be uniquely determined for each element. The understanding of the image of an element presupposes a basic grasp of functions as mappings between sets, where the domain and are specified sets, and the function provides a consistent assignment for all inputs. The collection of such images for elements in a forms the image of that .

Image of a Subset

In the context of a function f:XYf: X \to Y, the image of a subset AXA \subseteq X is formally defined as the set f(A)={f(x)xA}Y.f(A) = \{ f(x) \mid x \in A \} \subseteq Y. This construction collects all elements of the codomain YY that are outputs of elements from AA under ff. The fact that f(A)f(A) is a subset of YY follows directly from the definition of a function, as each f(x)f(x) for xAx \in A lies in YY by construction; the set comprehension ensures no elements outside YY are included. To see this, suppose yf(A)y \in f(A); then there exists xAx \in A such that y=f(x)y = f(x), and since ff maps to YY, yYy \in Y. This generalizes the image of a single element f(x)f(x), which is merely an individual point in YY, by aggregating such points into a set that may vary in and is typically a proper of the unless ff is surjective onto YY from AA. For the empty , the image is f()=f(\emptyset) = \emptyset, since the set comprehension yields no elements when there are none in \emptyset to map.

Image of a Function

The image of a function f:XYf: X \to Y is defined as the set im(f)=f(X)={f(x)xX}Y\operatorname{im}(f) = f(X) = \{f(x) \mid x \in X\} \subseteq Y, consisting of all elements in the YY that are outputs of ff for some input in the domain XX. This set represents the actual outputs produced by the function, distinguishing it from the potentially larger . The image is also referred to as the range of the function, emphasizing the subset of YY that ff effectively reaches. In general, im(f)Y\operatorname{im}(f) \subseteq Y, and equality holds if and only if ff is surjective onto YY. The notation im(f)\operatorname{im}(f) is a standard way to denote this set in mathematical literature. A key property is that if the domain XX is non-empty, then the image im(f)\operatorname{im}(f) is also non-empty, as the function assigns at least one element in YY to each element in XX. This follows directly from the definition of a function in set theory, where every element of the domain is mapped. The image of the full function is thus a specific instance of the image of a subset under ff, taken over the entire domain XX.

Generalizations

Binary Relations

In the context of binary relations, the image concept generalizes the notion from functions to more flexible associations between sets. A binary relation RX×YR \subseteq X \times Y defines, for each element xXx \in X, the image R(x)={yY(x,y)R}R(x) = \{ y \in Y \mid (x, y) \in R \}, which is a subset of YY that may be empty, a singleton, or contain multiple elements depending on the pairs involving xx. This contrasts with the image under a function, where each f(x)f(x) is at most a singleton since functions are single-valued binary relations satisfying f(x)1|f(x)| \leq 1 for all xx. For a subset AXA \subseteq X, the image under RR is defined as R(A)=xAR(x)R(A) = \bigcup_{x \in A} R(x), collecting all elements of YY related to at least one element of AA. This direct image operation preserves the multi-valued nature of relations, allowing R(A)R(A) to encompass diverse outputs without the injectivity or surjectivity constraints typical of functions. The full image of the relation, R(X)R(X), represents the projection of RR onto YY, specifically R(X)={yYxX such that (x,y)R}R(X) = \{ y \in Y \mid \exists x \in X \text{ such that } (x, y) \in R \}, which is the range of RR and may be a proper subset of YY if RR is not surjective. This construction highlights how binary relations extend the image to capture broader relational structures in set theory.

Other Mathematical Contexts

In linear algebra, the image of a T:VWT: V \to W between vector spaces over the same field is defined as the subspace im(T)=span{T(v)vV}\operatorname{im}(T) = \operatorname{span}\{ T(v) \mid v \in V \} of WW. This subspace captures the directions in WW that can be reached from VV under TT, and it forms a key component in theorems like the rank-nullity theorem, where the dimension of the image equals the rank of TT. In , the image of a f:XYf: X \to Y between topological spaces is simply f(X)Yf(X) \subseteq Y, equipped with the . preserve certain topological properties in their images; for instance, the continuous image of a is connected, and the continuous image of a is compact. These inheritance properties highlight how the image reflects structural features of the domain under continuity. In , the image of a morphism f:ABf: A \to B in a category with images is defined via the canonical factorization f=mef = m \circ e, where e:AIe: A \to I is an and m:IBm: I \to B is a , with mm being universal among such monomorphisms factoring ff. This generalizes the set-theoretic and exists in categories like abelian categories or regular categories, where it can be computed as the kernel of the of ff. In homomorphisms between algebraic structures, such as group homomorphisms, the preserves the operation, forming a substructure isomorphic to the quotient by the kernel.

Inverse Images

Definition

In , the inverse image, also known as the preimage, of a under a function provides a way to pull back sets from the to the domain, serving as a dual operation to the forward image of a . For a function f:XYf: X \to Y and a BYB \subseteq Y, the inverse image f1(B)f^{-1}(B) is defined as the set {xXf(x)B}X\{x \in X \mid f(x) \in B\} \subseteq X. When considering single elements, for yYy \in Y, the inverse image f1(y)f^{-1}(y) is the set {xXf(x)=y}\{x \in X \mid f(x) = y\}, which is referred to as the of ff over yy or the at yy. A key aspect of the inverse image is that it is always defined for any subset BYB \subseteq Y, regardless of whether BB intersects the image of ff; in particular, f(f1(B))Bf(f^{-1}(B)) \subseteq B. Special cases include the inverse image of the empty set, where f1()=f^{-1}(\emptyset) = \emptyset, and the inverse image of the entire codomain, where f1(Y)=Xf^{-1}(Y) = X.

Basic Properties

The inverse image operation preserves unions, intersections, and complements of subsets of the . Specifically, for a function f:XYf: X \to Y and subsets BiYB_i \subseteq Y for iIi \in I, it holds that f1(iIBi)=iIf1(Bi)f^{-1}\left(\bigcup_{i \in I} B_i\right) = \bigcup_{i \in I} f^{-1}(B_i) and f1(iIBi)=iIf1(Bi)f^{-1}\left(\bigcap_{i \in I} B_i\right) = \bigcap_{i \in I} f^{-1}(B_i). Additionally, for any BYB \subseteq Y, f1(YB)=Xf1(B)f^{-1}(Y \setminus B) = X \setminus f^{-1}(B). These preservation properties can be verified through element-chasing arguments establishing set equality via double inclusion. For unions, suppose xf1(iIBi)x \in f^{-1}\left(\bigcup_{i \in I} B_i\right); then f(x)iIBif(x) \in \bigcup_{i \in I} B_i, so f(x)Bkf(x) \in B_k for some kIk \in I, implying xf1(Bk)iIf1(Bi)x \in f^{-1}(B_k) \subseteq \bigcup_{i \in I} f^{-1}(B_i). Conversely, if xiIf1(Bi)x \in \bigcup_{i \in I} f^{-1}(B_i), then xf1(Bk)x \in f^{-1}(B_k) for some kk, so f(x)BkiIBif(x) \in B_k \subseteq \bigcup_{i \in I} B_i, hence xf1(iIBi)x \in f^{-1}\left(\bigcup_{i \in I} B_i\right). The proofs for intersections and complements follow analogously: for complements, if xf1(YB)x \in f^{-1}(Y \setminus B), then f(x)YBf(x) \in Y \setminus B, so f(x)Bf(x) \notin B and thus xf1(B)x \notin f^{-1}(B), yielding xXf1(B)x \in X \setminus f^{-1}(B); the reverse inclusion uses the contrapositive. The inverse image is monotonic with respect to subset inclusion: if BCYB \subseteq C \subseteq Y, then f1(B)f1(C)f^{-1}(B) \subseteq f^{-1}(C). To see this, take xf1(B)x \in f^{-1}(B); then f(x)BCf(x) \in B \subseteq C, so xf1(C)x \in f^{-1}(C). Inverse images also relate to images in precise ways that highlight their duality. For any AXA \subseteq X and BYB \subseteq Y, f(f1(B))=Bf(X)f(f^{-1}(B)) = B \cap f(X), where f(X)f(X) denotes the of ff; equality to BB holds if ff is surjective. Similarly, f1(f(A))Af^{-1}(f(A)) \supseteq A, with equality if ff is injective. These relations follow from the definitions: for f(f1(B))Bf(X)f(f^{-1}(B)) \subseteq B \cap f(X), any yf(f1(B))y \in f(f^{-1}(B)) satisfies y=f(x)y = f(x) for some xx with f(x)Bf(x) \in B, so yBy \in B and yf(X)y \in f(X); the reverse inclusion holds since for yBf(X)y \in B \cap f(X), there exists xXx \in X with f(x)=yBf(x) = y \in B, so xf1(B)x \in f^{-1}(B) and y=f(x)f(f1(B))y = f(x) \in f(f^{-1}(B)).

Notations

Arrow and Star Notations

In mathematics, the image of a subset AXA \subseteq X under a function f:XYf: X \to Y is most commonly denoted by f(A)f(A), representing the set {f(x)xAX}\{f(x) \mid x \in A \subseteq X\}. For the full image of the function itself—that is, the image of the entire domain XX—the notations im(f)\operatorname{im}(f) or f(X)f(X) are standard, with im(f)\operatorname{im}(f) often preferred to emphasize the range as a key property of ff. In some texts, to avoid ambiguity with the image of individual elements, the direct image is denoted by f[A]f[A] or the arrow notation f(A)f^\to(A). The arrow notation f(A)f^\to(A), which extends ff to a map on power sets P(X)P(Y)\mathcal{P}(X) \to \mathcal{P}(Y). For instance, T.S. Blyth employs \mapfA\map{f^\to} A in this context to clearly denote the induced mapping on subsets. For the inverse image of a subset BYB \subseteq Y under ff, the standard notation is f1(B)f^{-1}(B), defined as {xXf(x)B}\{x \in X \mid f(x) \in B\} regardless of whether ff is invertible. In more advanced settings, such as category theory, the star notation f(B)f^*(B) is sometimes used for the inverse image, particularly in discussions of adjoint functors like geometric morphisms. The choice of notation depends on context: f(A)f(A) suits general subset images in introductory treatments, while im(f)\operatorname{im}(f) highlights the function's range in analyses of surjectivity or properties.

Alternative Terminology

In mathematical , the image of a AA under a function ff, denoted f(A)f(A), is sometimes referred to as the direct image, particularly in contexts involving sheaf theory and where it corresponds to the pushforward operation ff_*. This terminology distinguishes it from the inverse image and emphasizes the forward mapping action. Additionally, when considering the image of the entire domain, im(f)\operatorname{im}(f), the term "range" is often used as a , though "" is preferred in more formal and advanced writing to avoid ambiguity with the . For the inverse image f1(B)f^{-1}(B), common alternative terms include "preimage," "inverse image," and "counterimage," with the latter appearing in some topology texts to highlight its role without implying the existence of a function inverse. In category-theoretic settings, it is frequently called the "pullback," reflecting its adjoint relationship to the direct image in structures like geometric morphisms. Context-specific usages further diversify the terminology. In topology, "image" typically presupposes continuous maps, where the direct image of an need not be open, a nuance emphasized in foundational texts. In algebra, the kernel of a is a special case of the preimage under the , underscoring the inverse image's role in preserving structures like ideals or subgroups./10:_Group_and_Subgroup_Structures/10.01:_Defining_a_Group_Homomorphism) Regional variations are notable in French mathematical traditions, where Bourbaki and associated works by Dieudonné employ "image directe" for the direct image and "image réciproque" for the inverse image, influencing much of modern . These terms align with the arrow notations ff_* and ff^*, but prioritize descriptive phrasing in expository writing. Caution is advised to distinguish these concepts from the image of an , which applies only to bijective cases and does not generalize to arbitrary subsets.

Properties

General Properties

The image of a subset under a function preserves inclusions: if ABXA \subseteq B \subseteq X for a function f:XYf: X \to Y, then f(A)f(B)f(A) \subseteq f(B). This follows directly from the definition of the image, as every element in AA is also in BB, so its image under ff lies in both f(A)f(A) and f(B)f(B). Additionally, the image of the entire domain satisfies im(f)Y\operatorname{im}(f) \subseteq Y always, where YY is the codomain, though equality holds ff is surjective. For finite sets, the cardinality of the image provides bounds related to injectivity: in general, f(A)A|f(A)| \leq |A| for AXA \subseteq X, with equality if and only if ff restricted to AA is injective. A key structural property is that the image operation commutes with unions: for a family of subsets {Ai}iIX\{A_i\}_{i \in I} \subseteq X, f(iIAi)=iIf(Ai)f\left(\bigcup_{i \in I} A_i\right) = \bigcup_{i \in I} f(A_i). This holds because any element in the image of the union arises from some AiA_i, and conversely, elements in the union of images come from the respective subsets.

Properties Involving Compositions and Multiple Sets

In the context of function composition, consider functions f:XYf: X \to Y and g:YZg: Y \to Z. The image of the composite function gfg \circ f satisfies im(gf)g(imf)\operatorname{im}(g \circ f) \subseteq g(\operatorname{im} f), since every element in im(gf)\operatorname{im}(g \circ f) is of the form g(f(x))g(f(x)) for some xXx \in X, and f(x)imff(x) \in \operatorname{im} f, so it lies in the image of imf\operatorname{im} f under gg. Equality holds if gg is injective when restricted to imf\operatorname{im} f, ensuring that distinct elements in imf\operatorname{im} f map to distinct elements without collapsing. For multiple subsets, the image operator preserves unions: if A,BXA, B \subseteq X, then f(AB)=f(A)f(B)f(A \cup B) = f(A) \cup f(B), as every element in the union is the image of some element in AA or BB, and conversely. For intersections, f(AB)f(A)f(B)f(A \cap B) \subseteq f(A) \cap f(B), since any image from the intersection must appear in both individual images, but the reverse inclusion may fail unless ff is injective, in which case distinct preimages preserve the overlap exactly. Under iterated compositions, images form a nonincreasing : for a function f:XXf: X \to X, im(fn+1)im(fn)\operatorname{im}(f^{n+1}) \subseteq \operatorname{im}(f^n) for each n1n \geq 1, as the property for two functions extends inductively, leading to eventual stabilization in finite settings or contraction in broader analyses.

Examples

Elementary Examples

Consider the squaring function f:RRf: \mathbb{R} \to \mathbb{R} defined by f(x)=x2f(x) = x^2. The of this function, denoted im(f)\operatorname{im}(f), consists of all non-negative real numbers, so im(f)=[0,)\operatorname{im}(f) = [0, \infty). A constant function provides another basic case. Let f:RRf: \mathbb{R} \to \mathbb{R} be defined by f(x)=cf(x) = c for some fixed real number cc. The image of ff is the singleton set im(f)={c}\operatorname{im}(f) = \{c\}. For any non-empty subset ARA \subseteq \mathbb{R}, the image f(A)={c}f(A) = \{c\}, matching im(f)\operatorname{im}(f). This shows how the image remains unchanged regardless of the input set's size, as long as it is non-empty. Relations generalize functions, and their images follow a similar definition. Consider the equality relation RR on the natural numbers N\mathbb{N}, where R={(n,m)N×N:n=m}R = \{(n, m) \in \mathbb{N} \times \mathbb{N} : n = m\}. For a fixed nNn \in \mathbb{N}, the section R(n)={mN:(n,m)R}={n}R(n) = \{m \in \mathbb{N} : (n, m) \in R\} = \{n\}, a singleton set. The overall image im(R)=N\operatorname{im}(R) = \mathbb{N}, as every natural number appears as a second coordinate. In all cases, the image of a subset satisfies f(A)im(f)f(A) \subseteq \operatorname{im}(f) for a function ff, or analogously for relations, since elements of f(A)f(A) are outputs produced by inputs in AA, hence in the full . This inclusion holds by the definition of the as the set of all possible outputs.

Advanced Examples

In linear algebra, the of a linear transformation T:VWT: V \to W between finite-dimensional vector spaces is the subspace spanned by the columns of the matrix representing TT, known as the column space. By the rank-nullity theorem, the dimension of the equals the rank of the matrix, providing a measure of the transformation's "reach" within the . In abstract algebra, the image of a group homomorphism ϕ:GH\phi: G \to H is a subgroup of HH, specifically the smallest subgroup containing all elements ϕ(g)\phi(g) for gGg \in G. A classic example is the evaluation homomorphism ϕ:ZZ\phi: \mathbb{Z} \to \mathbb{Z} sending a polynomial p(x)p(x) to p(2)p(2); its image is 2Z2\mathbb{Z}, the even integers, which is a proper subgroup of Z\mathbb{Z}. This illustrates the first isomorphism theorem, where G/ker(ϕ)im(ϕ)G / \ker(\phi) \cong \operatorname{im}(\phi), linking the image to quotient structures. In topology, the image of a continuous map preserves key properties like connectedness: if XX is connected and f:XYf: X \to Y is continuous, then f(X)f(X) is connected in YY. Similarly, the image of a compact set under a continuous map is compact. In category theory, the image of a morphism f:ABf: A \to B is defined as the universal monomorphism m:IBm: I \to B such that there exists g:AIg: A \to I with mg=fm \circ g = f, generalizing set-theoretic images to arbitrary categories. In the category of sets, this coincides with the usual image; in the category of abelian groups, it is the subgroup generated by the elements in the image of ff. For instance, in the category Ab\mathbf{Ab} of abelian groups, the image of the inclusion 2ZZ2\mathbb{Z} \hookrightarrow \mathbb{Z} is 2Z2\mathbb{Z} itself, as it is already a monomorphism. This construction ensures the image is the "least" subobject through which ff factors.

References

  1. https://proofwiki.org/wiki/Definition:Image_of_Subset_under_Mapping/Notation
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