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Injective function
Injective function
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In mathematics, an injective function (also known as injection, or one-to-one function[1]) is a function f that maps distinct elements of its domain to distinct elements of its codomain; that is, x1x2 implies f(x1) ≠ f(x2) (equivalently by contraposition, f(x1) = f(x2) implies x1 = x2). In other words, every element of the function's codomain is the image of at most one element of its domain.[2] The term one-to-one function must not be confused with one-to-one correspondence that refers to bijective functions, which are functions such that each element in the codomain is an image of exactly one element in the domain.

A homomorphism between algebraic structures is a function that is compatible with the operations of the structures. For all common algebraic structures, and, in particular for vector spaces, an injective homomorphism is also called a monomorphism. However, in the more general context of category theory, the definition of a monomorphism differs from that of an injective homomorphism.[3] This is thus a theorem that they are equivalent for algebraic structures; see Homomorphism § Monomorphism for more details.

A function that is not injective is sometimes called many-to-one.[2]

Definition

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An injective function, which is not also surjective

Let be a function whose domain is a set The function is said to be injective provided that for all and in if then ; that is, implies Equivalently, if then in the contrapositive statement.

Symbolically, which is logically equivalent to the contrapositive,[4]An injective function (or, more generally, a monomorphism) is often denoted by using the specialized arrows ↣ or ↪ (for example, or ), although some authors specifically reserve ↪ for an inclusion map.[5]

Examples

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For visual examples, readers are directed to the gallery section.

  • For any set and any subset the inclusion map (which sends any element to itself) is injective. In particular, the identity function is always injective (and in fact bijective).
  • If the domain of a function is the empty set, then the function is the empty function, which is injective.
  • If the domain of a function has one element (that is, it is a singleton set), then the function is always injective.
  • The function defined by is injective.
  • The function defined by is not injective, because (for example) However, if is redefined so that its domain is the non-negative real numbers [0,+∞), then is injective.
  • The exponential function defined by is injective (but not surjective, as no real value maps to a negative number).
  • The natural logarithm function defined by is injective.
  • The function defined by is not injective, since, for example,

More generally, when and are both the real line then an injective function is one whose graph is never intersected by any horizontal line more than once. This principle is referred to as the horizontal line test.[2]

Injections can be undone

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Functions with left inverses are always injections. That is, given if there is a function such that for every , , then is injective. The proof is that

In this case, is called a retraction of Conversely, is called a section of For example: is retracted by .

Conversely, every injection with a non-empty domain has a left inverse . It can be defined by choosing an element in the domain of and setting to the unique element of the pre-image (if it is non-empty) or to (otherwise).[6]

The left inverse is not necessarily an inverse of because the composition in the other order, may differ from the identity on In other words, an injective function can be "reversed" by a left inverse, but is not necessarily invertible, which requires that the function is bijective.

Injections may be made invertible

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In fact, to turn an injective function into a bijective (hence invertible) function, it suffices to replace its codomain by its actual image That is, let such that for all ; then is bijective. Indeed, can be factored as where is the inclusion function from into

More generally, injective partial functions are called partial bijections.

Other properties

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The composition of two injective functions is injective.
  • If and are both injective then is injective.
  • If is injective, then is injective (but need not be).
  • is injective if and only if, given any functions whenever then In other words, injective functions are precisely the monomorphisms in the category Set of sets.
  • If is injective and is a subset of then Thus, can be recovered from its image
  • If is injective and and are both subsets of then
  • Every function can be decomposed as for a suitable injection and surjection This decomposition is unique up to isomorphism, and may be thought of as the inclusion function of the range of as a subset of the codomain of
  • If is an injective function, then has at least as many elements as in the sense of cardinal numbers. In particular, if, in addition, there is an injection from to then and have the same cardinal number. (This is known as the Cantor–Bernstein–Schroeder theorem.)
  • If both and are finite with the same number of elements, then is injective if and only if is surjective (in which case is bijective).
  • An injective function which is a homomorphism between two algebraic structures is an embedding.
  • Unlike surjectivity, which is a relation between the graph of a function and its codomain, injectivity is a property of the graph of the function alone; that is, whether a function is injective can be decided by only considering the graph (and not the codomain) of

Proving that functions are injective

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A proof that a function is injective depends on how the function is presented and what properties the function holds. For functions that are given by some formula there is a basic idea. We use the definition of injectivity, namely that if then [7]

Here is an example:

Proof: Let Suppose So implies which implies Therefore, it follows from the definition that is injective.

There are multiple other methods of proving that a function is injective. For example, in calculus if is a differentiable function defined on some interval, then it is sufficient to show that the derivative is always positive or always negative on that interval. In linear algebra, if is a linear transformation it is sufficient to show that the kernel of contains only the zero vector. If is a function with finite domain it is sufficient to look through the list of images of each domain element and check that no image occurs twice on the list.

A graphical approach for a real-valued function of a real variable is the horizontal line test. If every horizontal line intersects the curve of in at most one point, then is injective or one-to-one.

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See also

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Notes

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References

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
In , an injective function, also known as a one-to-one function or an injection, is a function f:ABf: A \to B between two sets that maps distinct elements of its domain AA to distinct elements of its BB; that is, if f(x)=f(y)f(x) = f(y), then x=yx = y for all x,yAx, y \in A. The terms "injective," "surjective," and "bijective" were introduced by the French mathematical collective in their foundational work on during the mid-20th century. Equivalently, an injective function ensures that each element in the has at most one preimage in the domain, meaning no two domain elements share the same output. This property distinguishes injective functions from non-injective ones, where collisions occur (multiple inputs mapping to the same output). For example, the function f:RRf: \mathbb{R} \to \mathbb{R} defined by f(x)=x3f(x) = x^3 is injective because distinct real numbers cube to distinct real numbers, whereas f(x)=x2f(x) = x^2 is not, as f(2)=f(2)=4f(2) = f(-2) = 4. The inverse relation of an injective function is itself a function, though it may not be defined on the entire unless the function is also surjective. Key properties of injective functions include closure under composition: if f:ABf: A \to B and g:BCg: B \to C are both injective, then gf:ACg \circ f: A \to C is injective. For finite sets, an injective function from set AA to set BB implies that the cardinality of AA is less than or equal to that of BB (AB|A| \leq |B|). In linear , a linear transformation between vector spaces is injective if and only if its kernel is the zero , which is essential for understanding isomorphisms and bases. Injective functions form one half of the definition of a (the other being surjectivity), enabling one-to-one correspondences between sets and playing a central role in comparisons, , and proofs of uncountability.

Definition and Characterization

Formal Definition

In set theory, a function f:ABf: A \to B is a relation that assigns to each element of the domain set AA exactly one element of the codomain set BB, without requiring that every element of BB is assigned. Such a function ff is injective if it maps distinct elements of AA to distinct elements of BB; formally, x,yA\forall x, y \in A, if f(x)=f(y)f(x) = f(y), then x=yx = y. This condition is equivalently stated as x,yA\forall x, y \in A, if xyx \neq y, then f(x)f(y)f(x) \neq f(y). The injectivity ensures a one-to-one correspondence between elements of AA and their images under ff in the subset f(A)Bf(A) \subseteq B. The term "injective" was coined by the collective of mathematicians known as and first appeared in their 1954 publication Théorie des ensembles to provide precise terminology in set-theoretic contexts.

Equivalent Formulations

An injective function f:ABf: A \to B can be equivalently characterized by the condition that distinct elements in the domain AA map to distinct elements in the BB, that is, for all x,yAx, y \in A, if xyx \neq y, then f(x)f(y)f(x) \neq f(y). This property is also equivalent to the statement that the preimage (or kernel) of every singleton {b}\{b\} for bBb \in B contains at most one element from AA, meaning each element in BB has at most one preimage under ff. Injectivity differs from surjectivity, which requires every element in BB to have at least one preimage; a function that is both injective and surjective is bijective. A function f:ABf: A \to B is bijective it has both a left inverse g:BAg: B \to A such that gf=idAg \circ f = \mathrm{id}_A and a right inverse h:BAh: B \to A such that fh=idBf \circ h = \mathrm{id}_B, where idA\mathrm{id}_A and idB\mathrm{id}_B are the identity functions on AA and BB, respectively (and in fact g=hg = h). In arrow diagrams, which visually represent functions by drawing arrows from elements of AA to their images in BB, injectivity corresponds to the absence of converging arrows, ensuring no two elements from AA point to the same element in BB.

Examples and Illustrations

Injective Examples

One common example of an injective function is the inclusion map f:NZf: \mathbb{N} \to \mathbb{Z} defined by f(n)=nf(n) = n, where N\mathbb{N} is the set of natural numbers (positive integers) and Z\mathbb{Z} is the set of all integers; this mapping embeds the natural numbers into the integers without repetition, making it injective but not surjective since negative integers lack preimages. Another straightforward example is the linear function f:RRf: \mathbb{R} \to \mathbb{R} given by f(x)=2xf(x) = 2x, which scales real numbers by a factor of 2 and preserves distinctness, ensuring injectivity as distinct inputs yield distinct outputs. For finite sets, consider f:{1,2,3}{a,b,c,d,e}f: \{1,2,3\} \to \{a,b,c,d,e\} defined by f(1)=af(1) = a, f(2)=bf(2) = b, f(3)=cf(3) = c; this assigns each element in the domain to a unique element in the codomain, demonstrating injectivity without covering the entire codomain. In non-mathematical contexts, an injective function can be analogized to assigning unique identification numbers to individuals in a , where each person receives a distinct ID to avoid overlaps, mirroring the one-to-one correspondence of injectivity.

Non-Injective Counterexamples

A provides a simple to injectivity. Consider the function f:RRf: \mathbb{R} \to \mathbb{R} defined by f(x)=5f(x) = 5 for all xRx \in \mathbb{R}. This function maps every to the same output value 5, so for any distinct x1x2x_1 \neq x_2, it holds that f(x1)=f(x2)f(x_1) = f(x_2), violating the injectivity condition. Another common non-injective function is the squaring function on the real numbers. Define f:RRf: \mathbb{R} \to \mathbb{R} by f(x)=x2f(x) = x^2. Here, f(1)=1=f(1)f(-1) = 1 = f(1), but 11-1 \neq 1, demonstrating that distinct inputs can produce the same output. Functions between finite sets can also fail injectivity when the domain is larger than the codomain, as illustrated by the pigeonhole principle. For example, consider f:{1,2,3}{a,b}f: \{1,2,3\} \to \{a,b\} where f(1)=af(1) = a, f(2)=af(2) = a, and f(3)=bf(3) = b. Since f(1)=f(2)f(1) = f(2) but 121 \neq 2, the function is not injective. In each of these cases, the violation of injectivity arises because there exist distinct elements in the domain that map to the same element in the codomain.

Core Properties

Closure under Composition

Injective functions are closed under composition. Specifically, if f:ABf: A \to B and g:BCg: B \to C are both injective, then their composition gf:ACg \circ f: A \to C is also injective. To see this, suppose (gf)(x)=(gf)(y)(g \circ f)(x) = (g \circ f)(y); then g(f(x))=g(f(y))g(f(x)) = g(f(y)), so f(x)=f(y)f(x) = f(y) by injectivity of gg, and thus x=yx = y by injectivity of ff. This property ensures that chains of injective mappings remain injective, which is useful in constructing embeddings and analyzing function structures.

Reversibility and Inverses

A function f:ABf: A \to B is injective if and only if there exists a left inverse g:BAg: B \to A such that the composition gf=idAg \circ f = \mathrm{id}_A, the on AA. To construct such a gg, for each bBb \in B, if bb is in the image f(A)f(A) then set g(b)g(b) to be the unique aAa \in A with f(a)=bf(a) = b, which exists and is unique by injectivity; if bf(A)b \notin f(A), set g(b)g(b) to some fixed element of AA (assuming AA \neq \emptyset). This ensures g(f(x))=xg(f(x)) = x for all xAx \in A. This left inverse undoes the mapping of ff precisely on its : for any xAx \in A, g(f(x))=xg(f(x)) = x, recovering the original input from its output in f(A)f(A). However, gg need not be defined uniquely or meaningfully outside f(A)f(A), as elements of Bf(A)B \setminus f(A) are not in the range of ff. When restricted to its image, an injective function f:Af(A)f: A \to f(A) becomes bijective, admitting a two-sided inverse f1:f(A)Af^{-1}: f(A) \to A satisfying both f1f=idAf^{-1} \circ f = \mathrm{id}_A and ff1=idf(A)f \circ f^{-1} = \mathrm{id}_{f(A)}. This inverse coincides with the left inverse gg on f(A)f(A). Thus, injective functions are not generally invertible from AA to BB without adjusting the codomain to the image, underscoring that injectivity alone does not guarantee full reversibility over the entire .

Cardinality and Size Preservation

An injective function f:ABf: A \to B implies that the cardinality of the domain set AA is less than or equal to the of the set BB, denoted AB|A| \leq |B|. This inequality holds in general for any sets AA and BB, where for infinite sets, AB|A| \leq |B| is defined precisely by the existence of such an injection. For finite sets, an injective function f:ABf: A \to B implies AB|A| \leq |B| in the standard numerical sense, and equality A=B|A| = |B| holds ff is bijective. In this case, injectivity alone ensures that no elements of AA map to the same element in BB, so the size of the matches A|A|, which cannot exceed B|B| without repetition. Moreover, if A=B|A| = |B|, the injection must cover all of BB, making it surjective as well. In the infinite case, the situation is more subtle, as injectivity does not necessarily imply surjectivity even when cardinalities are equal. For example, the function f:NZf: \mathbb{N} \to \mathbb{Z} defined by f(n)=n/2f(n) = n/2 if nn is even and f(n)=(n+1)/2f(n) = -(n+1)/2 if nn is odd is injective but not surjective, yet N=Z|\mathbb{N}| = |\mathbb{Z}| because injections exist both ways, establishing equal cardinality via the Schröder–Bernstein theorem. The Schröder–Bernstein theorem states that if there exist injective functions f:ABf: A \to B and g:BAg: B \to A, then there is a bijection between AA and BB, so A=B|A| = |B|. If A=B|A| = |B|, an existing injection from AA to BB can be extended to a , though this extension generally requires the for infinite sets to select appropriate mappings on the complement of the image.

Preservation of Distinctness

An injective function preserves the distinctness of elements by ensuring that distinct inputs in the domain are mapped to distinct outputs in the . Formally, a function f:ABf: A \to B is injective if for all x,yAx, y \in A, xyx \neq y implies f(x)f(y)f(x) \neq f(y), or equivalently, f(x)=f(y)f(x) = f(y) implies x=yx = y. This property prevents the collapsing of distinct points under the mapping, maintaining separation at the level of individual elements. This preservation extends to subsets of the domain. Specifically, if XX and YY are disjoint subsets of AA (i.e., XY=X \cap Y = \emptyset), then their images under ff are also disjoint: f(X)f(Y)=f(X) \cap f(Y) = \emptyset. To see this, suppose there exists zf(X)f(Y)z \in f(X) \cap f(Y); then z=f(x)z = f(x) for some xXx \in X and z=f(y)z = f(y) for some yYy \in Y, so f(x)=f(y)f(x) = f(y) implies x=yx = y by injectivity, contradicting XY=X \cap Y = \emptyset. Injective functions also induce injections on collections of subsets. In particular, ff induces an injective map from the power set P(A)\mathcal{P}(A) to P(B)\mathcal{P}(B), defined by sending each subset SAS \subseteq A to its image f(S)={f(s)sS}f(S) = \{f(s) \mid s \in S\}. This induced map is injective because if f(S)=f(T)f(S) = f(T), then for every sSs \in S, f(s)f(T)f(s) \in f(T), so sTs \in T by injectivity of ff, and similarly TST \subseteq S, hence S=TS = T. When an order is defined on the domain and codomain, monotonic injective functions further preserve that order. A strictly increasing (or strictly decreasing) function between ordered sets is injective and maintains the relative ordering of elements, as x<yx < y implies f(x)<f(y)f(x) < f(y) (or f(x)>f(y)f(x) > f(y) for decreasing), ensuring both distinctness and structural separation.

Proof Techniques

Direct Proof Methods

One of the primary direct methods to establish that a function f:ABf: A \to B is injective involves assuming f(x)=f(y)f(x) = f(y) for arbitrary x,yAx, y \in A and demonstrating that this equality implies x=yx = y. This approach leverages algebraic properties of the function to manipulate the equation f(x)f(y)=0f(x) - f(y) = 0 and factor out (xy)(x - y), showing that the remaining factor is nonzero unless x=yx = y. For polynomial functions, this technique is particularly effective. Consider f(x)=x3+xf(x) = x^3 + x. Assume f(x)=f(y)f(x) = f(y), so x3+x=y3+yx^3 + x = y^3 + y. Rearranging gives x3y3+xy=0x^3 - y^3 + x - y = 0, which factors as (xy)(x2+xy+y2+1)=0(x - y)(x^2 + xy + y^2 + 1) = 0. The factor x2+xy+y2+1x^2 + xy + y^2 + 1 can be rewritten as (x+y2)2+34y2+11>0\left(x + \frac{y}{2}\right)^2 + \frac{3}{4}y^2 + 1 \geq 1 > 0 for all real x,yx, y, since the is positive semidefinite and the added constant ensures strict positivity. Thus, xy=0x - y = 0, so x=yx = y, proving injectivity. Similarly, for exponential functions, direct algebraic manipulation applies. Let f(x)=exf(x) = e^x. Assume f(x)=f(y)f(x) = f(y), so ex=eye^x = e^y. This implies exy=1e^{x - y} = 1. By the properties of the exponential function, ez=1e^z = 1 if and only if z=0z = 0, so xy=0x - y = 0 and x=yx = y. This confirms injectivity on the reals. For differentiable functions on the real numbers, another direct method uses the derivative to show strict monotonicity, which implies injectivity. If f(x)>0f'(x) > 0 for all xx in an interval, then ff is strictly increasing. To prove this leads to injectivity, suppose f(a)=f(b)f(a) = f(b) with a<ba < b. By Rolle's theorem, there exists c(a,b)c \in (a, b) such that f(c)=0f'(c) = 0, contradicting f(x)>0f'(x) > 0. Thus, no such aba \neq b exists, so ff is injective. For instance, f(x)=x3+xf(x) = x^3 + x has f(x)=3x2+1>0f'(x) = 3x^2 + 1 > 0, confirming the earlier algebraic result via this calculus approach. In cases of finite domains, direct proof can involve explicit computational verification. For a function f:STf: S \to T where SS and TT are finite sets, compute f(x)f(x) for each xSx \in S and confirm that all images are distinct, ensuring no collisions occur. This exhaustive check establishes injectivity when the domain size does not exceed the codomain size, as seen in simple mappings like permutations of finite sets.

Contrapositive and Other Approaches

One effective indirect method for establishing the injectivity of a function f:ABf: A \to B is to prove the contrapositive of the definition: for all x,yAx, y \in A, if xyx \neq y, then f(x)f(y)f(x) \neq f(y). This logically equivalent form often simplifies reasoning by assuming distinct inputs and showing distinct outputs. A classic example is the f(x)=ex:R(0,)f(x) = e^x: \mathbb{R} \to (0, \infty). Assume xyx \neq y. , suppose x>yx > y. Then, since the exponential function is strictly increasing, ex>eye^x > e^y, so f(x)f(y)f(x) \neq f(y). Thus, ff is injective. In , consider the f(x)=ax+b(modn)f(x) = ax + b \pmod{n} on Z/nZ\mathbb{Z}/n\mathbb{Z}. This is injective precisely when gcd(a,n)=1\gcd(a, n) = 1. To verify, assume xy(modn)x \neq y \pmod{n}, so xy≢0(modn)x - y \not\equiv 0 \pmod{n}. Then a(xy)≢0(modn)a(x - y) \not\equiv 0 \pmod{n} because gcd(a,n)=1\gcd(a, n) = 1 implies aa has a modular inverse. Thus, ax+b≢ay+b(modn)ax + b \not\equiv ay + b \pmod{n}, confirming injectivity under the gcd condition and extending to permutations of Z/nZ\mathbb{Z}/n\mathbb{Z}, where such functions generate the . For finite sets, the provides an indirect test for non-injectivity: if A>B|A| > |B|, then ff cannot be injective, as some element in BB would have multiple preimages. Conversely, to affirm injectivity positively in finite cases, one may verify the contrapositive across all pairs with xyx \neq y or use the fact that injectivity holds if no collisions occur under the mapping.

Extensions and Generalizations

In Linear Algebra

In linear algebra, a T:[V](/page/V.)WT: [V](/page/V.) \to W between vector spaces is injective its kernel is trivial, that is, ker(T)={0}\ker(T) = \{ \mathbf{0} \}. This condition means that the only vector in VV mapped to the zero vector in WW is the zero vector itself, ensuring that distinct vectors in VV are mapped to distinct vectors in WW. The rank-nullity theorem provides a dimensional perspective: for finite-dimensional vector spaces, dim(V)=dim(ker(T))+dim(\im(T))\dim(V) = \dim(\ker(T)) + \dim(\im(T)). If TT is injective, then dim(ker(T))=0\dim(\ker(T)) = 0, so dim(V)=dim(\im(T))dim(W)\dim(V) = \dim(\im(T)) \leq \dim(W). This implies that injective linear maps exist only when the dimension of the domain does not exceed that of the , preserving or reducing dimensionality without collapse. In matrix terms, a T:RnRmT: \mathbb{R}^n \to \mathbb{R}^m is represented by an m×nm \times n matrix AA, and TT is if and only if AA has full column rank, meaning \rank(A)=n\rank(A) = n. By the equality of row and column ranks, this requires the columns of AA to be linearly independent. If m<nm < n, full column rank is impossible, so no such injective map exists. For instance, the n×nn \times n identity matrix InI_n has full column rank nn, representing an injective map from Rn\mathbb{R}^n to Rn\mathbb{R}^n, as its kernel is trivial and the rank-nullity theorem confirms dim(Rn)=0+n\dim(\mathbb{R}^n) = 0 + n. In contrast, a singular matrix like (1000)\begin{pmatrix} 1 & 0 \\ 0 & 0 \end{pmatrix} has rank 1 < 2, a non-trivial kernel spanned by (0,1)T(0,1)^T, and thus is not injective.

In Category Theory

In category theory, the notion of an injective function is generalized to that of a monomorphism, which captures the essential property of left-cancellability in an abstract setting. Specifically, a morphism f:ABf: A \to B in a category C\mathcal{C} is a monomorphism, denoted \mono\mono, if for every object CC in C\mathcal{C} and every pair of morphisms g,h:CAg, h: C \to A, the equality fg=fhf \circ g = f \circ h implies g=hg = h. This definition abstracts the idea that ff does not identify distinct elements "upstream" in the category. In the category of sets, \Set, monomorphisms coincide precisely with injective functions, as the left-cancellability condition reduces to the standard set-theoretic notion of distinct elements mapping to distinct images. Similarly, in the category of groups, \Grp\Grp, a group homomorphism is a monomorphism if and only if it is injective as a map of underlying sets; for instance, the inclusion of a subgroup into a group is always a monomorphism. However, this equivalence does not hold in all categories: in the category of divisible abelian groups, \DivAb\DivAb, the quotient homomorphism π:QQ/Z\pi: \mathbb{Q} \to \mathbb{Q}/\mathbb{Z} sending qq+Zq \mapsto q + \mathbb{Z} is a monomorphism, despite not being injective on underlying sets, since integers map to the zero class. An important characterization of monomorphisms uses pullbacks: a morphism f:ABf: A \to B is a monomorphism if and only if the canonical diagonal morphism Δ:AA×BA\Delta: A \to A \times_B A, defined by Δ(a)=(a,a)\Delta(a) = (a, a) where the pullback A×BAA \times_B A is taken along ff and the identity on BB, is an isomorphism. This equates the "fiber product" over ff with the domain itself, reflecting that ff identifies no distinct points. In the category of topological spaces, \Top\Top, monomorphisms are the injective continuous maps, but in subcategories such as pointed connected locally path-connected spaces with pointed continuous maps, nontrivial covering maps (e.g., the nn-fold cover S1S1S^1 \to S^1, zznz \mapsto z^n for n>1n > 1) are monomorphisms despite failing to be injective on points, due to unique lifting properties.

References

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