Alphabeta Math
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17 results · all verified · 15 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 2 not AI-judged were verified by owner audit (typically over a confirmed judge false positive), not failures.

Triangularisation and Jordan Form: Examples and Counterexamples

1 · Prerequisites

2 · Summary

3 · Logical flowchart

4 · Definitions, theorems and proofs

None yet.

5 · Examples, counterexamples and false statements

ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passaudited 2026-08-16Open item page →

The quotient of F3 by a coordinate line and its canonical projection

Example

Let W=F(1,0,0)F3. Every coset in F3/W has a unique representative (0,y,z), the cosets (0,1,0)+W,(0,0,1)+W form a basis of the quotient, and the canonical projection is π(x,y,z)=(x,y,z)+W=(0,y,z)+W. Thus dim(F3/W)=2 and kerπ=W.

Facts & Assumptions

Given: The coordinate line W=F(1,0,0) in F3.

[L1]

v+W=v+W exactly when vvW; the quotient operations are independent of representatives and make V/W a vector space; and the canonical projection π:VV/W is a surjective linear map with kerπ=W (Coset equality, well-defined quotient operations, and the canonical projection with kernel W).

[L2]

Representatives of a quotient basis, placed after a basis of W, form a basis of the original space (A quotient basis lifts to a basis adapted to W).

Verification

technique · computation
1.1

Subtracting (x,0,0)W shows (x,y,z)+W=(0,y,z)+W; if two such representatives agree, their difference (0,yy,zz) lies in W, forcing y=y and z=z.

L1algebra
1.2

The standard list ((1,0,0),(0,1,0),(0,0,1)) is a basis of F3, so [L2] makes the last two cosets a quotient basis.

L2algebra
2.1

The displayed formula for π, its dimension, and kerπ=W now follow from steps 1.1-1.2 and [L1].

step 1.1step 1.2L1
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The first isomorphism theorem for (x,y,z)(x+y,y+z)

Example

For T:F3F2,T(x,y,z)=(x+y,y+z), one has kerT=F(1,1,1) and imT=F2. The induced map T~:F3/F(1,1,1)F2,(x,y,z)+kerT(x+y,y+z) is an isomorphism, with inverse (a,b)(a,0,b)+kerT.

Facts & Assumptions

Given: The displayed coordinate map T.

[L1]

The first isomorphism theorem gives a unique isomorphism V/kerTimT sending v+kerT to T(v) (First isomorphism theorem for vector spaces: V/kerT is isomorphic to imT).

Verification

technique · computation
1.1

Solving x+y=0 and y+z=0 gives (x,y,z)=y(1,1,1), so the kernel is the stated line.

algebra
1.2

For every (a,b)F2, T(a,0,b)=(a,b), so T is surjective.

algebra
2.1

Fact [L1] gives the induced isomorphism with the displayed formula, and step 1.2 shows that sending (a,b) to (a,0,b)+kerT is its two-sided inverse.

step 1.1step 1.2L1
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A split 3×3 operator that is triangularisable but not diagonalisable

Example

Over any field, let A=J2(0)J1(0)=(010000000). Then χA=x3 and μA=x2. Hence A is triangularisable over its base field but is not diagonalisable.

Facts & Assumptions

Given: The displayed matrix A.

[L1]

An endomorphism is triangularisable exactly when its characteristic polynomial splits over the base field (T is triangularisable iff its minimal polynomial splits iff its characteristic polynomial splits).

[L2]

An endomorphism is diagonalisable exactly when its minimal polynomial is a product of distinct linear factors (An endomorphism is diagonalisable if and only if its minimal polynomial is a product of distinct linear factors).

Verification

technique · computation
1.1

The matrix is strictly upper triangular, so direct determinant computation gives χA=x3; also A0 but A2=0, so μA=x2.

algebra
2.1

The polynomial x3 splits, so [L1] confirms triangularisability, while the repeated factor in x2 makes [L2] rule out diagonalisability.

step 1.1L1L2
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Building an upper-triangular matrix from a complete invariant flag

Example

On Q3, define Te1=2e1,Te2=e1+3e2,Te3=2e1e2+4e3. The complete flag 0e1e1,e2Q3 is T-invariant, and in the flag-adapted basis (e1,e2,e3), [T]=(212031004).

Facts & Assumptions

Given: The displayed action of T on the standard basis of Q3.

[L1]

A basis gives an upper-triangular matrix exactly when its successive spans form a complete invariant flag (Complete invariant flags are equivalent to upper-triangular matrices).

Verification

technique · computation
1.1

The formulas show Te1e1 and Te1,e2e1,e2, while the final space is automatically invariant.

algebra
2.1

The coordinate columns of Te1,Te2,Te3 give the displayed matrix, and [L1] identifies this upper-triangular form with the verified complete flag.

step 1.1L1algebra
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Building a Jordan-string basis for a nilpotent operator on F6

Example

Let (e1,,e6) be the standard basis of F6 and define Ne1=0,Ne2=e1,Ne3=e2,Ne4=0,Ne5=e4,Ne6=0. Then (e1,e2,e3), (e4,e5), and (e6) are Jordan strings whose concatenation is a basis. Thus [N]=J3(0)J2(0)J1(0) and N3=0N2.

Facts & Assumptions

Given: The displayed endomorphism on the standard basis of F6.

[L1]

A nilpotent Jordan string satisfies Nv1=0 and Nvj=vj1 for j2 (Jordan blocks, Jordan strings, and their endpoints).

[L2]

Every finite-dimensional nilpotent endomorphism admits a basis of Jordan strings (Every finite-dimensional nilpotent endomorphism has a basis of Jordan strings).

Verification

technique · computation
1.1

The six displayed images verify [L1] separately for the three listed strings, and their concatenation is the standard basis.

L1algebra
2.1

In that order the matrix has blocks J3(0), J2(0), and J1(0); direct iteration gives N3=0 and N2e3=e10, consistently with [L2].

step 1.1L2algebra
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Recovering J3(0),J2(0),J1(0) from ranks of powers

Example

Suppose a nilpotent endomorphism on a six-dimensional space has power ranks ρ0=6,ρ1=3,ρ2=1,ρ3=ρ4=0. Then its nilpotent Jordan blocks have sizes 3,2,1, each occurring once.

Facts & Assumptions

Given: The displayed rank sequence.

[L1]

The number of blocks of size at least k is ρk1ρk, and the number of size exactly k is ρk12ρk+ρk+1 (Power ranks determine every nilpotent Jordan-block multiplicity).

Verification

technique · computation
1.1

The successive differences ρk1ρk are 3,2,1,0 for k=1,2,3,4, so there are respectively three, two, one, and zero blocks of size at least those values.

L1algebra
2.1

Taking successive differences again gives one block of each exact size 1,2,3 and none larger; their sizes sum to 6, as required.

step 1.1L1algebra
ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-16Open item page →

Recovering a 5×5 Jordan form from shifted power ranks at two eigenvalues

Example

Let T=J3(0)J2(1). Its shifted-power ranks are ρk(0): 5,4,3,2,2,,ρk(1): 5,4,3,3,3,. Their second differences recover one size-three block at 0 and one size-two block at 1. Accordingly χT=μT=x3(x1)2.

Facts & Assumptions

Given: The displayed block diagonal matrix T.

[L1]

The exact-size k block count at λ is ρk1(λ)2ρk(λ)+ρk+1(λ) (Ranks of shifted powers determine Jordan form up to block order).

[L2]

Jordan block sizes give the characteristic and minimal polynomials by total and maximum exponents, respectively (For split operators, Jordan blocks read off eigenspace multiplicities and both canonical polynomials).

Verification

technique · computation
1.1

At λ=0, the J2(1) summand stays invertible while the ranks of powers of J3(0) are 3,2,1,0,0,, giving 5,4,3,2,2,. At λ=1, the J3(0)I summand stays invertible while the nilpotent part of J2(1) has ranks 2,1,0,0,, giving 5,4,3,3,.

algebra
2.1

Applying [L1] gives one exact size-three block at 0, one exact size-two block at 1, and zero other blocks; [L2] then gives both displayed polynomials.

step 1.1L1L2algebra
ExampleConstruction: Literature-sourcedVerification: AI-adaptedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-16Open item page →

The real quarter-turn acquires diagonal Jordan form over C

Example

The real quarter-turn R=(0110) has no Jordan form over R, but after scalar extension to C the basis ((1,i),(1,i)) gives [R]=diag(i,i)=J1(i)J1(i).

Facts & Assumptions

Given: The displayed real matrix, read over R and then over C.

[L1]

Jordan form over the base field exists exactly when the characteristic polynomial splits over that field (Jordan form over the base field exists exactly when the characteristic polynomial splits).

Verification

technique · computation
1.1

Direct computation gives χR=x2+1, which has no real root and hence does not split over R; [L1] rules out real Jordan form.

L1algebra
2.1

Over C, R(1,i)=i(1,i) and R(1,i)=i(1,i); these eigenvectors are independent, so their basis gives the displayed diagonal Jordan form, as [L1] permits.

L1algebra
False statementConstruction: AI-adaptedVerification: AI-adaptedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-16Open item page →

FALSE: Every finite-dimensional endomorphism is triangularisable over its base field

Statement

False claim. Every endomorphism of a finite-dimensional vector space is triangularisable over its base field.

Facts & Assumptions

Given: The real quarter-turn R=(0110).

[L1]

An endomorphism is triangularisable over F exactly when its characteristic polynomial splits over F (T is triangularisable iff its minimal polynomial splits iff its characteristic polynomial splits).

Refutation

technique · counterexample
1.1

Direct determinant computation gives χR=x2+1. It has no root in R, so it does not split over the base field.

algebra
2.1

Fact [L1] therefore says that R is not triangularisable over R, refuting the universal claim.

step 1.1L1
False statementConstruction: AI-adaptedVerification: AI-adaptedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-16Open item page →

FALSE: Every finite-dimensional endomorphism has Jordan form over its base field

Statement

False claim. Every endomorphism of a finite-dimensional vector space has Jordan canonical form over its base field.

Facts & Assumptions

Given: The real quarter-turn R=(0110).

[L1]

Jordan form over F exists exactly when the characteristic polynomial splits over F (Jordan form over the base field exists exactly when the characteristic polynomial splits).

Refutation

technique · counterexample
1.1

The characteristic polynomial of R is x2+1, which has no real root and does not split over R.

algebra
2.1

By [L1], R has no Jordan form over its real base field, so the claim is false; scalar extension to C is essential in this example.

step 1.1L1
False statementConstruction: Literature-sourcedVerification: AI-adaptedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-16Open item page →

FALSE: Equal characteristic and minimal polynomials imply similarity

Statement

False claim. Two matrices with the same characteristic polynomial and the same minimal polynomial must be similar.

Facts & Assumptions

Given: For any λF, A=J2(λ)J2(λ),B=J2(λ)J1(λ)J1(λ).

[L1]

Jordan block sizes give the characteristic polynomial by total size and the minimal polynomial by largest size (For split operators, Jordan blocks read off eigenspace multiplicities and both canonical polynomials).

[L2]

Split matrices are similar exactly when their Jordan block multisets agree (Split matrices are similar exactly when their Jordan block multisets agree).

Refutation

technique · counterexample
1.1

Both matrices have total size four and largest block size two, so [L1] gives χA=χB=(xλ)4 and μA=μB=(xλ)2.

L1algebra
1.2

Nevertheless rank(AλI)=2 while rank(BλI)=1, and their block multisets are respectively {2,2} and {2,1,1}.

algebra
2.1

Fact [L2] therefore says that A and B are not similar, refuting the claim.

step 1.2L2
False statementConstruction: AI-adaptedVerification: AI-adaptedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-16Open item page →

FALSE: Jordan canonical form is a unique literal matrix without fixing block order

Statement

False claim. The Jordan canonical form of an endomorphism is a unique literal matrix even when no ordering convention for its blocks has been fixed.

Facts & Assumptions

Given: The two block diagonal matrices A=J2(0)J1(1) and B=J1(1)J2(0).

[L1]

Shifted-power ranks determine Jordan form uniquely only up to permutation of its blocks (Ranks of shifted powers determine Jordan form up to block order).

Refutation

technique · counterexample
1.1

Both A and B are Jordan matrices with the same block multiset, and a permutation matrix that moves the one-dimensional block past the two-dimensional block conjugates one to the other.

algebra
1.2

Their diagonal sequences are (0,0,1) and (1,0,0), so AB as literal matrices.

algebra
2.1

This is precisely the block-order freedom retained in [L1], and it refutes literal uniqueness without an additional ordering convention.

step 1.1step 1.2L1
False statementConstruction: AI-adaptedVerification: AI-generatedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-16Open item page →

FALSE: Geometric multiplicity alone determines Jordan block sizes

Statement

False claim. The geometric multiplicity of an eigenvalue determines all Jordan block sizes at that eigenvalue.

Facts & Assumptions

Given: For any λF, A=J3(λ)J1(λ),B=J2(λ)J2(λ).

[L1]

The geometric multiplicity is the number of Jordan blocks for the eigenvalue (For split operators, Jordan blocks read off eigenspace multiplicities and both canonical polynomials).

[L2]

Ranks of shifted powers determine every Jordan block size (Ranks of shifted powers determine Jordan form up to block order).

Refutation

technique · counterexample
1.1

Each matrix has exactly two λ-blocks, so [L1] gives geometric multiplicity two for both.

L1algebra
1.2

Yet (AλI)2 has rank one, contributed by J3(0)2, while (BλI)2=0; [L2] therefore distinguishes the block multisets {3,1} and {2,2}.

L2algebra
2.1

Equal geometric multiplicity has not determined the sizes, so the claim is false.

step 1.1step 1.2
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Computing commuting diagonal and nilpotent parts of a split Jordan matrix

Example

Over any field, put T=J2(0)J2(1). Then D=0I2I2=3T22T3,N=TD=J2(0)J2(0). Thus T=D+N, the operator D is diagonal, N2=0, and DN=ND.

Facts & Assumptions

Given: The displayed block diagonal operator T.

[L1]

For a split minimal polynomial, the primary projections are polynomials in the endomorphism (Each projection in the primary decomposition is a polynomial in the endomorphism).

[L2]

On each generalised eigenspace, the operator is the eigenvalue scalar plus a nilpotent operator (Split characteristic polynomials decompose into generalised eigenspaces of the algebraic multiplicities).

Verification

technique · computation
1.1

For h(x)=3x22x3, one has h(0)=h(0)=0 and h(1)=1, h(1)=0; evaluating on the two size-two blocks therefore gives h(J2(0))=0 and h(J2(1))=I2. These identities remain valid in characteristics 2 and 3 by direct reduction.

L1algebra
2.1

Hence D=h(T) is the scalar part on the two generalised eigenspaces, while N=TD is the direct sum of their nilpotent parts as in [L2].

step 1.1L2
3.1

The displayed blocks give N2=0 and DN=ND; commutation also follows because both D and N=Th(T) are polynomials in T.

step 2.1algebra
False statementConstruction: AI-adaptedVerification: AI-adaptedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-16Open item page →

FALSE: Every endomorphism has a commuting diagonal-plus-nilpotent decomposition over its base field

Statement

False claim. Every endomorphism T over its base field can be written T=D+N with D diagonalisable, N nilpotent, and DN=ND.

Facts & Assumptions

Given: The real quarter-turn R=(0110).

[L1]

A commuting family whose characteristic polynomials split is simultaneously triangularisable (A commuting split family is simultaneously triangularisable).

[L3]

A nilpotent endomorphism has characteristic polynomial xn (Characterisations of a nilpotent endomorphism).

[L4]

An endomorphism is triangularisable exactly when its characteristic polynomial splits (T is triangularisable iff its minimal polynomial splits iff its characteristic polynomial splits).

Refutation

technique · counterexample
1.1

Suppose R=D+N as claimed. By [L2], χD splits, while [L3] makes χN=x2 split; commutation and [L1] give one real basis in which both D and N are upper triangular.

assume-contraL1L2L3
2.1

Their sum R is upper triangular in that basis, so [L4] would make χR split over R.

step 1.1L4algebra
3.1

But direct computation gives χR=x2+1, which has no real root. This contradiction refutes the claimed decomposition over the base field.

step 2.1discharge-contradictionalgebra
ExampleConstruction: AI-generatedVerification: AI-generatedprecheck passaudited 2026-08-16Open item page →

A companion operator with a visible cyclic vector and equal canonical polynomials

Example

For f=x3+x+1, let C=(001101010). Then e1,Ce1,C2e1 are e1,e2,e3, so e1 is cyclic. The matrix is the companion matrix of f, and μC=χC=f.

Remarks

Over F2, the polynomial x3+x+1 is irreducible and the same column orientation represents multiplication by its residue class in F8=F2[x]/(x3+x+1). This fixes the convention for a downstream computation of the Frobenius map of F8/F2; the present matrix is multiplication by the residue class, not the Frobenius operator, and no forward dependency is used here.

Facts & Assumptions

Given: The displayed companion matrix C and v=e1.

[L1]

If mT,v=xd+ad1xd1++a0, then (v,Tv,,Td1v) is an ordered basis of Z(v;T), and in this basis TZ(v;T) has the companion matrix with ones on the subdiagonal and last column (a0,,ad1) (A vector annihilator gives a power basis and its companion matrix).

[L2]

An endomorphism of a finite-dimensional vector space has a cyclic vector if and only if μT=χT (A cyclic vector exists exactly when the minimal and characteristic polynomials agree).

Verification

technique · computation
1.1

Matrix multiplication gives Ce1=e2 and C2e1=e3, so the three power vectors are the standard basis and e1 is cyclic.

algebra
2.1

The columns show Ce3=e1e2, so C3e1=Ce3=e1e2=e1Ce1 and hence f(C)e1=(C3+C+I)e1=0. Since f(C) commutes with C, f(C)Cje1=Cjf(C)e1=0 for j=0,1,2, and step 1.1 makes e1,Ce1,C2e1 a basis, so f(C)=0.

step 1.1algebra
3.1

By step 1.1 the vector e1 is cyclic, so [L2] gives μC=χC, and [L3] makes χC monic of degree 3; thus μC is monic of degree 3. By step 2.1, μC divides the monic degree-three polynomial f, so μC=f and therefore μC=χC=f. Since mC,e1 divides f and (e1,Ce1,C2e1) is a basis of Z(e1;C)=F3, mC,e1=f, and [L1] in that basis is exactly the displayed matrix, with last column (a0,a1,a2)=(1,1,0).

step 1.1step 2.1L1L2L3algebra
CounterexampleConstruction: Literature-sourcedVerification: AI-adaptedprecheck passjudge pass (deepseek-v4-pro + gpt-5.6-terra)audited 2026-08-16Open item page →

The identity on F2 has no cyclic vector

Statement refuted

Every endomorphism of a finite-dimensional vector space has a cyclic vector.

Facts & Assumptions

Given: The identity endomorphism I of F2.

[L1]

An endomorphism has a cyclic vector exactly when its minimal and characteristic polynomials are equal (A cyclic vector exists exactly when the minimal and characteristic polynomials agree).

Counterexample

technique · counterexample
1.1

For any vF2, every power Ikv equals v, so Z(v;I)=Fv has dimension at most one and cannot equal F2.

algebra
2.1

Equivalently, μI=x1 while χI=(x1)2, so [L1] also rules out a cyclic vector. Thus the identity on F2 refutes the universal claim.

L1algebra

Sources