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The first chip identifies the source of the statement or construction; the second identifies the source of its local proof or verification.
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- AI-generated: a genuinely novel statement formulated by AI, with no source for the claim itself.
These labels describe origin, not correctness: citations and verification chips remain separate evidence.
Triangularisation and Jordan Form: Examples and Counterexamples
1 · Prerequisites
- Binary Operations, Monoids, Groups and Subgroups
- Construction of the Natural Numbers
- Construction of the Real Numbers via Cauchy Sequences
- Construction of the Real Numbers via Dedekind Cuts
- Cosets, Index and Lagrange's Theorem
- Countability and Uncountability
- Determinants of Matrices over a Commutative Ring
- Diagonalisation and the Minimal Polynomial
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Eigenvalues, Eigenvectors and the Characteristic Polynomial
- Finite Counting, Factorials and Binomial Coefficients
- Foundations of the Real Numbers for Analysis
- Group Actions, Orbits, Stabilisers and Cayley's Theorem
- Ideals, Quotient Rings and the Isomorphism Theorems for Rings
- Linear Independence, Bases and Dimension
- Linear Transformations, Rank-Nullity and Quotient Spaces
- Matrices, the Matrix of a Linear Map, and Change of Basis
- Normal Subgroups and Quotient Groups
- Order, Zorn's Lemma, and the Axiom of Choice
- Polynomial Rings, the Division Algorithm and Roots
- Relations, Functions, and Quotients
- Rings, Subrings, Integral Domains and Fields
- Roots, Rational Powers, and Classical Inequalities
- Simple Field Extensions and the Construction of the Complex Numbers
- Splitting Fields
- Symmetric Groups, Cycle Decomposition and the Sign Homomorphism
- The Determinant of a Linear Operator, Cofactors and Cramer's Rule
- The ZFC Axioms and the Basic Set Constructions
- Triangularisation, Generalised Eigenspaces and Jordan Canonical Form
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
3 · Logical flowchart
4 · Definitions, theorems and proofs
None yet.
5 · Examples, counterexamples and false statements
The quotient of by a coordinate line and its canonical projection
Example
Let . Every coset in has a unique representative , the cosets form a basis of the quotient, and the canonical projection is Thus and .
Facts & Assumptions
Given: The coordinate line in .
exactly when ; the quotient operations are independent of representatives and make a vector space; and the canonical projection is a surjective linear map with (Coset equality, well-defined quotient operations, and the canonical projection with kernel ).
Representatives of a quotient basis, placed after a basis of , form a basis of the original space (A quotient basis lifts to a basis adapted to ).
Verification
Subtracting shows ; if two such representatives agree, their difference lies in , forcing and .
The standard list is a basis of , so [L2] makes the last two cosets a quotient basis.
The displayed formula for , its dimension, and now follow from steps 1.1-1.2 and [L1].
The first isomorphism theorem for
Example
For one has and . The induced map is an isomorphism, with inverse .
Facts & Assumptions
Given: The displayed coordinate map .
The first isomorphism theorem gives a unique isomorphism sending to (First isomorphism theorem for vector spaces: is isomorphic to ).
Verification
Solving and gives , so the kernel is the stated line.
For every , , so is surjective.
Fact [L1] gives the induced isomorphism with the displayed formula, and step 1.2 shows that sending to is its two-sided inverse.
A split operator that is triangularisable but not diagonalisable
Example
Over any field, let Then and . Hence is triangularisable over its base field but is not diagonalisable.
Facts & Assumptions
Given: The displayed matrix .
An endomorphism is triangularisable exactly when its characteristic polynomial splits over the base field ( is triangularisable iff its minimal polynomial splits iff its characteristic polynomial splits).
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
The matrix is strictly upper triangular, so direct determinant computation gives ; also but , so .
The polynomial splits, so [L1] confirms triangularisability, while the repeated factor in makes [L2] rule out diagonalisability.
Building an upper-triangular matrix from a complete invariant flag
Example
On , define The complete flag is -invariant, and in the flag-adapted basis ,
Facts & Assumptions
Given: The displayed action of on the standard basis of .
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
The formulas show and , while the final space is automatically invariant.
The coordinate columns of give the displayed matrix, and [L1] identifies this upper-triangular form with the verified complete flag.
Building a Jordan-string basis for a nilpotent operator on
Example
Let be the standard basis of and define Then , , and are Jordan strings whose concatenation is a basis. Thus and .
Facts & Assumptions
Given: The displayed endomorphism on the standard basis of .
A nilpotent Jordan string satisfies and for (Jordan blocks, Jordan strings, and their endpoints).
Every finite-dimensional nilpotent endomorphism admits a basis of Jordan strings (Every finite-dimensional nilpotent endomorphism has a basis of Jordan strings).
Verification
The six displayed images verify [L1] separately for the three listed strings, and their concatenation is the standard basis.
In that order the matrix has blocks , , and ; direct iteration gives and , consistently with [L2].
Recovering from ranks of powers
Example
Suppose a nilpotent endomorphism on a six-dimensional space has power ranks Then its nilpotent Jordan blocks have sizes , each occurring once.
Facts & Assumptions
Given: The displayed rank sequence.
The number of blocks of size at least is , and the number of size exactly is (Power ranks determine every nilpotent Jordan-block multiplicity).
Verification
The successive differences are for , so there are respectively three, two, one, and zero blocks of size at least those values.
Taking successive differences again gives one block of each exact size and none larger; their sizes sum to , as required.
Recovering a Jordan form from shifted power ranks at two eigenvalues
Example
Let . Its shifted-power ranks are Their second differences recover one size-three block at and one size-two block at . Accordingly
Facts & Assumptions
Given: The displayed block diagonal matrix .
The exact-size block count at is (Ranks of shifted powers determine Jordan form up to block order).
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
At , the summand stays invertible while the ranks of powers of are , giving . At , the summand stays invertible while the nilpotent part of has ranks , giving .
Applying [L1] gives one exact size-three block at , one exact size-two block at , and zero other blocks; [L2] then gives both displayed polynomials.
The real quarter-turn acquires diagonal Jordan form over
Example
The real quarter-turn has no Jordan form over , but after scalar extension to the basis gives
Facts & Assumptions
Given: The displayed real matrix, read over and then over .
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
Direct computation gives , which has no real root and hence does not split over ; [L1] rules out real Jordan form.
Over , and ; these eigenvectors are independent, so their basis gives the displayed diagonal Jordan form, as [L1] permits.
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 .
An endomorphism is triangularisable over exactly when its characteristic polynomial splits over ( is triangularisable iff its minimal polynomial splits iff its characteristic polynomial splits).
Refutation
Direct determinant computation gives . It has no root in , so it does not split over the base field.
Fact [L1] therefore says that is not triangularisable over , refuting the universal claim.
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 .
Jordan form over exists exactly when the characteristic polynomial splits over (Jordan form over the base field exists exactly when the characteristic polynomial splits).
Refutation
The characteristic polynomial of is , which has no real root and does not split over .
By [L1], has no Jordan form over its real base field, so the claim is false; scalar extension to is essential in this example.
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 ,
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).
Split matrices are similar exactly when their Jordan block multisets agree (Split matrices are similar exactly when their Jordan block multisets agree).
Refutation
Both matrices have total size four and largest block size two, so [L1] gives and .
Nevertheless while , and their block multisets are respectively and .
Fact [L2] therefore says that and are not similar, refuting the claim.
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 and .
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
Both and 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.
Their diagonal sequences are and , so as literal matrices.
This is precisely the block-order freedom retained in [L1], and it refutes literal uniqueness without an additional ordering convention.
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 ,
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).
Ranks of shifted powers determine every Jordan block size (Ranks of shifted powers determine Jordan form up to block order).
Refutation
Each matrix has exactly two -blocks, so [L1] gives geometric multiplicity two for both.
Yet has rank one, contributed by , while ; [L2] therefore distinguishes the block multisets and .
Equal geometric multiplicity has not determined the sizes, so the claim is false.
Computing commuting diagonal and nilpotent parts of a split Jordan matrix
Example
Over any field, put . Then Thus , the operator is diagonal, , and .
Facts & Assumptions
Given: The displayed block diagonal operator .
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).
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
For , one has and , ; evaluating on the two size-two blocks therefore gives and . These identities remain valid in characteristics and by direct reduction.
Hence is the scalar part on the two generalised eigenspaces, while is the direct sum of their nilpotent parts as in [L2].
The displayed blocks give and ; commutation also follows because both and are polynomials in .
FALSE: Every endomorphism has a commuting diagonal-plus-nilpotent decomposition over its base field
Statement
False claim. Every endomorphism over its base field can be written with diagonalisable, nilpotent, and .
Facts & Assumptions
Given: The real quarter-turn .
A commuting family whose characteristic polynomials split is simultaneously triangularisable (A commuting split family is simultaneously triangularisable).
A diagonalisable endomorphism has a basis of eigenvectors (A diagonalisable endomorphism is one admitting a basis of eigenvectors, equivalently a diagonal matrix representation).
A nilpotent endomorphism has characteristic polynomial (Characterisations of a nilpotent endomorphism).
An endomorphism is triangularisable exactly when its characteristic polynomial splits ( is triangularisable iff its minimal polynomial splits iff its characteristic polynomial splits).
Refutation
Suppose as claimed. By [L2], splits, while [L3] makes split; commutation and [L1] give one real basis in which both and are upper triangular.
Their sum is upper triangular in that basis, so [L4] would make split over .
But direct computation gives , which has no real root. This contradiction refutes the claimed decomposition over the base field.
A companion operator with a visible cyclic vector and equal canonical polynomials
Example
For , let Then are , so is cyclic. The matrix is the companion matrix of , and
Remarks
Over , the polynomial is irreducible and the same column orientation represents multiplication by its residue class in . This fixes the convention for a downstream computation of the Frobenius map of ; 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 and .
If , then is an ordered basis of , and in this basis has the companion matrix with ones on the subdiagonal and last column (A vector annihilator gives a power basis and its companion matrix).
An endomorphism of a finite-dimensional vector space has a cyclic vector if and only if (A cyclic vector exists exactly when the minimal and characteristic polynomials agree).
For , the polynomial is monic of degree ( is monic of degree ; for its coefficient is and its constant coefficient is , while ).
Verification
Matrix multiplication gives and , so the three power vectors are the standard basis and is cyclic.
The columns show , so and hence . Since commutes with , for , and step 1.1 makes a basis, so .
By step 1.1 the vector is cyclic, so [L2] gives , and [L3] makes monic of degree ; thus is monic of degree . By step 2.1, divides the monic degree-three polynomial , so and therefore . Since divides and is a basis of , , and [L1] in that basis is exactly the displayed matrix, with last column .
The identity on has no cyclic vector
Statement refuted
Every endomorphism of a finite-dimensional vector space has a cyclic vector.
Facts & Assumptions
Given: The identity endomorphism of .
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
For any , every power equals , so has dimension at most one and cannot equal .
Equivalently, while , so [L1] also rules out a cyclic vector. Thus the identity on refutes the universal claim.
Sources
Standard references
Recommended treatments; not extraction sources.