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8 results · all verified · 3 also independently AI-judged
Every result on this page is machine-checked by a proof checker and read in full and owner-audited; the judge is an additional, independent cross-model AI review of the proofs. The 5 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Bounded Linear Operators and Quotient Spaces — Examples

1 · Prerequisites

2 · Summary

The companion page keeps the bounded-operator and quotient package concrete: product projections, shifts, and evaluation functionals; a standard unbounded differentiation map; the quotient-by-kernel model of a range; the oscillation norm on functions modulo constants; and two guardrails against over-reading the theory, one analytic and one algebraic.

3 · Logical flowchart

4 · Definitions, theorems and proofs

None yet.

5 · Examples, counterexamples and false statements

ExampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passaudited 2026-09-01Open item page →

Coordinate projections and inclusions on a finite product Banach space

Example

Let X and Y be Banach spaces over the same scalar field and equip X×Y with the maximum product norm

(x,y)max:=max{x,y}.

Then the coordinate projections

πX(x,y)=x,πY(x,y)=y,

and the coordinate inclusions

ιX(x)=(x,0),ιY(y)=(0,y)

are bounded linear operators. Moreover,

πX=ιX={1,X{0},0,X={0},πY=ιY={1,Y{0},0,Y={0}.

Facts & Assumptions

Given: Banach spaces X and Y over the same scalar field, their product X×Y with the maximum norm, and vectors xX, yY.

[L1]

The maximum product norm is one of the standard product norms (The standard product norms on a finite product of normed spaces).

[L2]

A finite product of Banach spaces is Banach, and bounded linear operators are the members of B(,) (Finite products of Banach spaces are Banach, A bounded linear operator between normed spaces, The spaces (\mathcal B(X,Y)) and (\mathcal B(X)) of bounded linear operators).

[L3]

The operator norm is the unit-ball supremum and therefore records the least global bound of a bounded linear operator (The operator norm as the least bound and as the unit-sphere or unit-ball supremum).

Verification

technique · direct
1.1

By [L1], (x,y)maxx and (x,y)maxy, so πX(x,y)(x,y)max and πY(x,y)(x,y)max. Thus both projections are bounded with operator norm at most 1 by [L2] and [L3].

L1L2L3
2.1

For xX and yY, [L1] gives ιX(x)max=(x,0)max=x and ιY(y)max=(0,y)max=y. So ιX1 and ιY1, with equality whenever the relevant domain is nonzero. If X{0}, choose uX with u=1. Then ιX(u)max=1, and also πX(u,0)=1=(u,0)max, so ιX=πX=1. If X={0}, then both ιX and πX are the zero operator, so both norms are 0. The same argument with Y gives the corresponding statements for ιY and πY.

step 1.1L1L3choose
3.1

Therefore πXB(X×Y,X), πYB(X×Y,Y), ιXB(X,X×Y), and ιYB(Y,X×Y), with the norms stated above.

step 1.1step 2.1L2
ExampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-01Open item page →

Forward and backward shifts on classical sequence spaces and their exact operator norms

Example

On either of the normed spaces

c0:={x=(xn)n0:xn0}or:={x=(xn)n0:supnxn<},

equipped with the supremum norm x:=supnxn, define the forward and backward shifts by

F(x0,x1,x2,):=(0,x0,x1,), B(x0,x1,x2,):=(x1,x2,x3,).

Then F and B are bounded linear operators and

F=B=1.

Facts & Assumptions

Given: One of the normed spaces c0 or with the supremum norm, and a sequence x=(xn)n0 in that space.

[L2]

A bounded linear operator is a linear map with a uniform norm bound (A bounded linear operator between normed spaces).

[L3]

The operator norm is the least global bound, equivalently the unit-ball supremum (The operator norm as the least bound and as the unit-sphere or unit-ball supremum).

Verification

technique · direct
1.1

On either space, F and B are linear by coordinatewise inspection. Also Fxx and Bxx, so both operators are bounded with operator norm at most 1 by [L2] and [L3].

L2L3
2.1

The vectors e0=(1,0,0,) and e1=(0,1,0,) lie in both spaces. They satisfy Fe0=e0=1 and Be1=e0=1, so F1 and B1.

step 1.1
3.1

Combining steps 1.1 and 2.1 gives F=B=1 on both c0 and .

step 1.1step 2.1
ExampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passaudited 2026-09-01Open item page →

The evaluation functional on (C(K)) has norm one

Example

Let K be a nonempty compact metric space, let K{R,C} be the scalar field, let C(K,K) carry the supremum norm, and let x0K. Define

δx0:C(K,K)K,δx0(f):=f(x0).

Then δx0 is a bounded linear functional of norm 1.

Facts & Assumptions

Given: A nonempty compact metric space K, a scalar field K{R,C}, a point x0K, and the space C(K,K) of continuous K-valued functions on K with the supremum norm.

[L2]

A bounded linear operator is a linear map with a uniform norm bound (A bounded linear operator between normed spaces).

[L3]

The operator norm is the least global bound, equivalently the unit-ball supremum (The operator norm as the least bound and as the unit-sphere or unit-ball supremum).

Verification

technique · direct
1.1

The map δx0 is linear, and for every fC(K,K), δx0(f)=f(x0)f. Hence δx0 is bounded with operator norm at most 1 by [L2] and [L3].

L2L3
2.1

Let 1 be the constant function 1 on K. Then 1=1 and δx0(1)=1, so δx01. Therefore δx0=1.

step 1.1
ExampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passaudited 2026-09-01Open item page →

Differentiation on polynomials is unbounded for the supremum norm

Example

Let P[0,1] be the real polynomial functions on [0,1] with the supremum norm, and let

D:P[0,1]P[0,1],Dp:=p.

Then D is linear but not bounded for the supremum norm.

Facts & Assumptions

Given: The differentiation operator D on P[0,1] and the polynomials pn(x):=xn.

[L1]

A bounded linear operator requires one constant C such that DpCp for every polynomial p (A bounded linear operator between normed spaces).

Verification

technique · direct
1.1

Differentiation is linear on polynomials. For each n1, pn=1 on [0,1], while Dpn(x)=nxn1 and therefore Dpn=n.

givenalgebra
2.1

If D were bounded, [L1] would give a constant C with n=DpnCpn=C for every n1, impossible. Hence D is unbounded.

step 1.1L1assume-contradischarge-contradiction
ExampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passaudited 2026-09-01Open item page →

The quotient by the kernel is isometric to the range with its induced quotient norm

Example

Let T:XY be a bounded linear operator between normed spaces, and write M:=kerT. The factor map

T:X/MimT,T(x+M):=Tx,

is a linear isomorphism. If imT is equipped with the induced quotient norm

Txquot:=x+MX/M,

then T is an isometry.

Facts & Assumptions

Given: A bounded linear operator T:XY and its kernel M:=kerT.

[L1]

A bounded linear operator is in particular linear (A bounded linear operator between normed spaces).

[L2]

The kernel and image are the sets kerT={x:Tx=0} and imT={Tx:xX} (Kernel and image of a linear map).

[L3]

The kernel is a linear subspace, and a linear map is injective exactly when its kernel is trivial (The kernel and image are linear subspaces, and a linear map is injective if and only if its kernel is trivial).

[L4]

The quotient seminorm is the infimum over representatives (The quotient seminorm (|x+M|{X/M}=\inf{m\in M}|x+m|=\operatorname{dist}(x,M))).

[L5]

A linear map that vanishes on a subspace factors uniquely through the algebraic quotient (Universal property of the quotient vector space).

Verification

technique · direct
1.1

Since T is linear by [L1], the set M=kerT is a linear subspace by [L3], and certainly MkerT. Therefore [L5] gives a unique linear map T:X/MY with T(x+M)=Tx. Its range is exactly imT, so we may read it as a map into imT.

L1L2L3L5
2.1

If T(x+M)=0, then Tx=0, so xkerT=M by [L2]. Hence x+M=M, the zero coset. Therefore T is injective by [L3].

step 1.1L2L3
2.2

If Tx=Ty, then xykerT=M by [L2], so x+M=y+M. Thus the formula Txquot:=x+MX/M is well defined on imT, using the quotient seminorm of [L4]. By construction, T(x+M)quot=x+MX/M for every coset, so T is an isometry onto imT.

step 1.1L2L4
3.1

Steps 1.1, 2.1, and 2.2 show that X/kerT is linearly isomorphic to the range of T, and isometric once the range is given the induced quotient norm.

step 1.1step 2.1step 2.2
ExampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-01Open item page →

For real continuous functions modulo constants, the quotient norm is half the oscillation

Example

Let K be a nonempty compact metric space, let C(K,R) carry the supremum norm, and let M be the subspace of constant functions. For fC(K,R) write

osc(f):=maxKfminKf.

Then in the quotient C(K,R)/M,

f+M=12osc(f).

Facts & Assumptions

Given: A nonempty compact metric space K, a real-valued continuous function f on K, and the constant-function subspace M.

[L1]

The quotient seminorm is f+M=infcRfc (The quotient seminorm (|x+M|{X/M}=\inf{m\in M}|x+m|=\operatorname{dist}(x,M))).

[L2]

A continuous real-valued function on a nonempty compact metric space attains its maximum and minimum (A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value).

[L3]

The quotient seminorm is a norm when the subspace is closed (The quotient seminorm is a norm exactly when the subspace is closed).

Verification

technique · direct
1.1

By [L2], let m:=minKf and M0:=maxKf, and put c0:=(M0+m)/2. Then for every xK, mf(x)M0, so f(x)c0(M0m)/2. Hence fc0(M0m)/2.

L2algebra
2.1

For any real constant c, both M0c and mc are bounded above by fc. Since the distance between M0 and m is M0m, at least one of those two numbers is at least (M0m)/2. Therefore fc(M0m)/2 for every c.

step 1.1L2algebra
3.1

Steps 1.1 and 2.1 give infcRfc=(M0m)/2, so [L1] yields f+M=osc(f)/2. The constant subspace is closed because a uniform limit of constant functions is constant, so [L3] confirms that this is an honest norm on the quotient.

step 1.1step 2.1L1L3
CounterexampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passaudited 2026-09-01Open item page →

A closed subspace of a Banach space need not contain a nearest point to every ambient vector

Statement refuted

Refuted claim: every closed linear subspace of a Banach space contains a nearest point to every ambient vector.

In the real Banach space

c0:={x=(xn)n0:xnR, xn0}

with the supremum norm, define

φ(x):=n=02n1xn,

let

H:=kerφ,

and set x:=2e0=(2,0,0,). Then H is a closed linear subspace of c0, the distance from x to H is 1, and no point of H realizes that distance.

Facts & Assumptions

Given: The real normed space c0, the functional φ, its kernel H, and the vector x:=2e0.

Counterexample

technique · direct
1.1

Let (x(m)) be a Cauchy sequence in c0 for the supremum norm, with coordinates x(m)=(xn(m))n0. For each n, the scalar sequence (xn(m))m is Cauchy because xn(m)xn()x(m)x(). Since the scalars are real, let zn:=limmxn(m). Choosing M0 with x(m)x()<1 for m,M0 and letting gives znx(M0)+1 for every n, so z:=(zn) is bounded. Given ε>0, choose M such that x(m)x()<ε/2 whenever m,M. Letting coordinatewise gives xn(m)znε/2 for every n and every mM, hence x(m)zε/2. Fix such an m and choose N with xn(m)<ε/2 for all nN, since x(m)c0. Then zn<ε for nN, so zc0. The displayed uniform estimate also gives x(m)z0. Therefore c0 is Banach.

constructalgebra
2.1

The series defining φ converges absolutely and φ(z)n=02n1znz for every zc0, so φ is a bounded linear functional with φ1. If z(m)H and z(m)z in c0, then φ(z)=φ(zz(m))zz(m)0, so zH. Thus H is a closed linear subspace. Also φ(x)=1.

step 1.1algebra
3.1

For every yH one has φ(xy)=1, hence 1=φ(xy)xy by step 2.1. Therefore dist(x,H)1.

step 2.1algebra
3.2

For N1, define z(N)c0 by zn(N):=(12N)1 for 0n<N and zn(N):=0 for nN. Then φ(z(N))=(12N)1n=0N12n1=1, so y(N):=xz(N) lies in H, and xy(N)=z(N)=(12N)11. Hence dist(x,H)1.

step 2.1construct
4.1

Steps 3.1 and 3.2 give dist(x,H)=1. Suppose some yH satisfied xy=1, and put z:=xy. Then z=1 and φ(z)=1 by step 2.1. Also 1=φ(z)=n=02n1znn=02n1znn=02n1z=1.

step 2.1step 3.1step 3.2assume-contraalgebra
5.1

So equality holds throughout in step 4.1, forcing zn=1 and zn0 for every n. That contradicts zc0, since a sequence converging to 0 cannot have all coordinates equal to 1 in modulus.

step 4.1discharge-contradiction
6.1

Thus H is a closed subspace of the Banach space c0, the distance from x to H is 1, and no yH attains it. This refutes the claim.

step 1.1step 2.1step 3.1step 3.2step 5.1
CounterexampleConstruction: Literature-sourcedVerification: AI-generatedprecheck passjudge pass (gpt-5.6-terra)audited 2026-09-01Open item page →

An algebraic complement need not be a topological complement

Statement refuted

Refuted claim: every algebraic direct-sum decomposition of a normed space is automatically a topological direct sum.

Assume the Axiom of Choice and fix a Hamel basis H of c0 containing all standard unit vectors en. Let M:=span{e0}, let W be the kernel of the linear map P:c0M defined on basis vectors by

P(e0)=e0,P(en)=ne0 for n1,P(h)=0 for hH{en:n0},

and extend linearly. Then c0=MW algebraically, but W is not a topological complement of M.

Facts & Assumptions

Given: The normed space c0, the Hamel basis H, the one-dimensional subspace M=span{e0}, and the algebraic projection P above.

[L2]

A topological complement is a direct-sum partner with bounded coordinate projections (A complemented closed subspace of a normed space).

Counterexample

technique · direct
1.1

By construction, P is linear, P2=P, and ran(P)=M. So W:=kerP satisfies c0=MW algebraically: every vector decomposes as Px+(xPx), and the intersection is trivial because P acts as the identity on M and vanishes on W.

givenalgebra
2.1

The projection P is not bounded for the supremum norm. Indeed, un:=en/n satisfies un=1/n0, while P(un)=e0 for every n1, so P(un)=1. No bounded linear map can behave this way at 0.

step 1.1
3.1

Suppose, toward a contradiction, that W were a topological complement of M. Then [L2] gives a bounded projection onto M along W, and that projection is unique because the decomposition x=m+w with mM, wW determines the projection value m pointwise. But P already has exactly that range and kernel by step 1.1, so the bounded projection would have to equal P, contradicting step 2.1.

step 1.1step 2.1L2assume-contradischarge-contradiction
4.1

Therefore c0=MW is an algebraic decomposition that is not a topological direct sum. This refutes the claim.

step 1.1step 3.1

Remarks

  • The example is intentionally non-load-bearing: it uses a Hamel basis and therefore the Axiom of Choice.
  • The point is not that complements are rare, but that boundedness of the coordinate projections is extra structure and must be stated.

Sources