The Jordan Canonical Form

Not every linear operator is diagonalizable. So a natural question arises. What is the simplest matrix form we can always achieve? This holds no matter how badly an operator fails to be diagonalizable. Consider an operator whose only eigenvalue is λ\lambda, but which is not a scalar multiple of the identity. Diagonalization is impossible here. Yet the operator still has a rigid, describable structure. This structure is built from chains of vectors linked by the equation (T−λI)vi+1=vi(T - \lambda I)v_{i+1} = v_i. The Jordan Canonical Form answers the question completely. Over an algebraically closed field, every operator is similar to an essentially unique block-diagonal matrix. This matrix is built from elementary pieces called Jordan blocks. Each block has a single eigenvalue sitting on the diagonal. It also has a fringe of 11's just above it. This matters because diagonalizability is the exception, not the rule. Yet almost every structural question about an operator reduces to understanding this canonical form. This includes computing TnT^n, solving linear ODEs x˙=Ax\dot{x} = Ax, understanding the structure of a nilpotent map, and classifying conjugacy classes of matrices. The Jordan form is the finest classification of similarity available for matrices over C\mathbb{C} (or any algebraically closed field). Two matrices are similar if and only if they have the same Jordan form. This holds up to reordering of blocks. It converts an algebraic question (is AA similar to BB?) into a combinatorial one. That question becomes: do AA and BB have the same multiset of Jordan blocks? The big picture starts with the Generalized Eigenspace Decomposition. It already splits any operator's domain into a direct sum of generalized eigenspaces, one for each eigenvalue. The operator restricted to each such piece is "eigenvalue times identity plus nilpotent." What remains is to understand nilpotent operators completely. It turns out every nilpotent operator on a finite-dimensional space decomposes into a direct sum of cyclic nilpotent pieces. These are chains of vectors annihilated in sequence by the operator. Reassembling these chains, shifted by λ\lambda, gives the Jordan blocks. This article builds the Jordan form from the generalized eigenspace decomposition. It states and proves the existence and uniqueness theorem in full. It works two nontrivial numerical examples. It also shows exactly which hypothesis (algebraic closure) is indispensable — and what happens when it fails. This foreshadows The Rational Canonical Form as the field-independent alternative.

Key takeaways
  • The Jordan Canonical Form expresses any operator on a finite-dimensional space over an algebraically closed field as a direct sum of Jordan blocks.
  • A Jordan block Jk(λ)J_k(\lambda) is a k×kk \times k upper triangular matrix with λ\lambda on the diagonal and 11's on the superdiagonal.
  • Existence follows from the Generalized Eigenspace Decomposition plus a structure theorem for nilpotent operators (cyclic decomposition).
  • Uniqueness (up to reordering of blocks) follows from counting ranks of powers of (T−λI)(T - \lambda I), which are similarity invariants.
  • The number and sizes of Jordan blocks for eigenvalue λ\lambda are determined by the sequence rank⁡(T−λI)j\operatorname{rank}(T-\lambda I)^j for j=0,1,2,…j = 0, 1, 2, \dots
  • Key idea: every operator over an algebraically closed field is, up to a change of basis, "diagonal plus a controlled nilpotent shift" made of chains of generalized eigenvectors.

Where this lives today

The Jordan Canonical Form underlies the theory of linear ordinary differential equations: solving x˙=Ax\dot{x} = Ax reduces to computing etAe^{tA}, and etJk(λ)e^{tJ_k(\lambda)} has an explicit closed form involving eλte^{\lambda t} times a polynomial in tt of degree up to k−1k-1, directly explaining resonance terms like teλtt e^{\lambda t} that appear when eigenvalues are repeated. In control theory and signal processing, the Jordan form governs the long-term behavior of discrete linear systems xn+1=Axnx_{n+1} = Ax_n, since Jk(λ)nJ_k(\lambda)^n grows like λn\lambda^n times a polynomial in nn, determining stability margins precisely when ∣λ∣=1|\lambda|=1. In numerical analysis, the extreme sensitivity of the Jordan form to perturbation (a famous cautionary example) motivates why practical algorithms instead compute the more stable Schur form or singular value decomposition rather than attempting to compute Jordan blocks directly from floating-point data. In pure mathematics, the Jordan form is the model case for the general theory of modules over a principal ideal domain applied to F[x]\mathbb{F}[x]-modules, connecting directly to The Rational Canonical Form and to the classification of finitely generated abelian groups via an entirely parallel structure theorem.

Ask the tutor: How do I explicitly construct a Jordan basis (the change-of-basis matrix PP) once I know the block sizes, especially when an eigenvalue has more than one block of the same size?

DefinitionJordan Block and Jordan Canonical Form

Let λ\lambda be a scalar and k≥1k \geq 1 an integer. The Jordan block Jk(λ)J_k(\lambda) is the k×kk \times k matrix

Jk(λ)=(λ1λ1⋱⋱λ),J_k(\lambda) = \begin{pmatrix} \lambda & 1 & & \\ & \lambda & 1 & \\ & & \ddots & \ddots \\ & & & \lambda \end{pmatrix},

that is, (Jk(λ))ii=λ(J_k(\lambda))_{ii} = \lambda for all ii, (Jk(λ))i,i+1=1(J_k(\lambda))_{i,i+1} = 1 for i=1,…,k−1i = 1, \dots, k-1, and all other entries are 00. Let VV be a finite-dimensional vector space over a field F\mathbb{F}, and let T:V→VT: V \to V be a linear operator. We say TT is in Jordan Canonical Form with respect to a basis β\beta of VV if the matrix [T]β[T]_\beta is block diagonal,

[T]β=Jk1(λ1)⊕Jk2(λ2)⊕⋯⊕Jkm(λm),[T]_\beta = J_{k_1}(\lambda_1) \oplus J_{k_2}(\lambda_2) \oplus \cdots \oplus J_{k_m}(\lambda_m),

a direct sum of Jordan blocks (not necessarily with distinct λi\lambda_i, and the λi\lambda_i not necessarily distinct from each other). We say TT has a Jordan Canonical Form (or is Jordanizable) if such a basis β\beta exists. Equivalently, a square matrix AA over F\mathbb{F} has a Jordan Canonical Form if AA is similar to a direct sum of Jordan blocks.

Intuition

Start with the easiest possible case beyond diagonal matrices: a single Jordan block Jk(0)J_k(0) with eigenvalue 00. This is the nilpotent shift operator on Fk\mathbb{F}^k that sends the standard basis vector ei↦ei−1e_i \mapsto e_{i-1} (and e1↦0e_1 \mapsto 0). Picture a chain of kk beads threaded on a string: applying the operator slides every bead down one position, and the bottom bead falls off (maps to 00). This chain structure, ek↦ek−1↦⋯↦e1↦0e_k \mapsto e_{k-1} \mapsto \cdots \mapsto e_1 \mapsto 0, is the entire content of a Jordan block with λ=0\lambda = 0; adding λI\lambda I back just tilts every bead's "resting value" from 00 to λ\lambda, since (T−λI)(T - \lambda I) still behaves like the shift. The full Jordan Canonical Form theorem says that every operator's action can be understood, basis vector by basis vector, as a union of such chains — one chain of some length for each eigenvalue, possibly several chains per eigenvalue of possibly different lengths. Diagonalizable operators are the special case where every chain has length 11 (no shifting at all, just scaling). The generalized eigenspace decomposition already isolates each eigenvalue's contribution; what remains, and what the Jordan theorem supplies, is the precise chain-length data (a partition of the dimension of each generalized eigenspace) that pins down the operator up to similarity.

Figure
A single Jordan block J4(3)J_4(3) pictured as a chain of generalized eigenvectors
Chain for λ = 3, length k = 4: (T - 3I) v₁ = 0, (T - 3I) v₂ = v₁, (T - 3I) v₃ = v₂, (T - 3I) v₄ = v₃ v₁ v₂ v₃ v₄ 0 Matrix in basis (v₁,v₂,v₃,v₄): J₄(3) has 3 on the diagonal, 1 on the superdiagonal.
TheoremExistence and Uniqueness of the Jordan Canonical Form

Let VV be a finite-dimensional vector space over an algebraically closed field F\mathbb{F}, with dim⁡V=n≥1\dim V = n \geq 1, and let T:V→VT: V \to V be a linear operator.

(Existence.) There is a basis β\beta of VV such that [T]β[T]_\beta is a direct sum of Jordan blocks.

(Uniqueness.) This decomposition is unique up to the order of the blocks: if β\beta and β′\beta' are two bases such that [T]β[T]_\beta and [T]β′[T]_{\beta'} are each direct sums of Jordan blocks, then the multiset of Jordan blocks (each block specified by its eigenvalue and size) occurring in [T]β[T]_\beta equals the multiset occurring in [T]β′[T]_{\beta'}. Consequently, two matrices A,B∈Fn×nA, B \in \mathbb{F}^{n \times n} are similar if and only if they have the same Jordan Canonical Form up to reordering of blocks.

LemmaCyclic decomposition of a nilpotent operator

Let WW be a finite-dimensional vector space over any field F\mathbb{F}, and let N:W→WN: W \to W be nilpotent, i.e. Np=0N^p = 0 for some p≥1p \geq 1. Then there exist vectors w1,…,wr∈Ww_1, \dots, w_r \in W and positive integers k1,…,krk_1, \dots, k_r such that

W=⨁i=1rspan⁡{wi,Nwi,N2wi,…,Nki−1wi},W = \bigoplus_{i=1}^r \operatorname{span}\{w_i, N w_i, N^2 w_i, \dots, N^{k_i - 1} w_i\},

each summand is NN-invariant, Nkiwi=0N^{k_i} w_i = 0, and Nki−1wi≠0N^{k_i - 1} w_i \ne 0. Moreover the multiset {k1,…,kr}\{k_1, \dots, k_r\} is uniquely determined by NN: it equals the multiset of positive part-sizes of the partition of dim⁡W\dim W dual (via conjugate partitions) to the sequence rank⁡(Nj)−rank⁡(Nj+1)\operatorname{rank}(N^j) - \operatorname{rank}(N^{j+1}), j=0,1,2,…j = 0, 1, 2, \dots; equivalently the number of kik_i equal to a given value kk is

#{i:ki=k}=rank⁡(Nk−1)−2rank⁡(Nk)+rank⁡(Nk+1).\#\{i : k_i = k\} = \operatorname{rank}(N^{k-1}) - 2\operatorname{rank}(N^k) + \operatorname{rank}(N^{k+1}).
Proof

Existence, by strong induction on dim⁡W\dim W. If W={0}W = \{0\} the statement holds vacuously. Suppose dim⁡W=d≥1\dim W = d \geq 1 and the result holds for all nilpotent operators on spaces of dimension less than dd. Let pp be minimal with Np=0N^p = 0 (if N=0N = 0, take p=1p=1 and every basis vector generates its own length-11 chain, done). Consider U=im⁡(N)=N(W)U = \operatorname{im}(N) = N(W). Since NN is not invertible (it is nilpotent on a nonzero space, as Np=0N^p=0 forces det⁡(N)p=0\det(N)^p = 0), U⊊WU \subsetneq W, so dim⁡U<d\dim U < d. Also N(U)⊆UN(U) \subseteq U, so N∣UN|_U is a well-defined nilpotent operator on UU (nilpotent because (N∣U)p=Np∣U=0(N|_U)^p = N^p|_U = 0). By the inductive hypothesis applied to N∣UN|_U, there exist u1,…,us∈Uu_1, \dots, u_s \in U and lengths ℓ1,…,ℓs\ell_1, \dots, \ell_s with

U=⨁i=1sspan⁡{ui,Nui,…,Nℓi−1ui},Nℓiui=0, Nℓi−1ui≠0.U = \bigoplus_{i=1}^s \operatorname{span}\{u_i, Nu_i, \dots, N^{\ell_i - 1} u_i\}, \quad N^{\ell_i} u_i = 0, \ N^{\ell_i - 1} u_i \ne 0.

Since each ui∈U=N(W)u_i \in U = N(W), choose wi∈Ww_i \in W with Nwi=uiN w_i = u_i. Then Nℓiwi=Nℓi−1ui≠0N^{\ell_i} w_i = N^{\ell_i - 1} u_i \ne 0 and Nℓi+1wi=Nℓiui=0N^{\ell_i+1} w_i = N^{\ell_i} u_i = 0, so wiw_i generates a cyclic chain of length ℓi+1\ell_i + 1:

Ci:=span⁡{wi,Nwi,…,Nℓiwi}.C_i := \operatorname{span}\{w_i, Nw_i, \dots, N^{\ell_i} w_i\}.

Claim 1: The vectors {Njwi:1≤i≤s, 0≤j≤ℓi}\{N^j w_i : 1 \le i \le s,\ 0 \le j \le \ell_i\} are linearly independent, and ∑iCi\sum_i C_i has dimension ∑i(ℓi+1)=dim⁡U+s\sum_i (\ell_i+1) = \dim U + s. Indeed, note {Njwi}j=1ℓi\{N^j w_i\}_{j=1}^{\ell_i} span the same set as {Nj−1ui}j=1ℓi\{N^{j-1}u_i\}_{j=1}^{\ell_i}, which together over all ii are linearly independent because they form (a subfamily equal to) the basis of UU produced by the inductive hypothesis. Adding the vectors w1,…,wsw_1,\dots,w_s (for j=0j=0) preserves independence: any linear dependence among {wi}∪{Njwi:j≥1}\{w_i\} \cup \{N^j w_i : j\ge1\}, applying NN, gives a dependence among the NjwiN^j w_i (j≥1j \geq 1) alone (since N(dependence)=0N(\text{dependence}) = 0 eliminates the wiw_i terms only if their coefficients vanish after applying NN — more precisely, suppose ∑iciwi+∑i,j≥1cijNjwi=0\sum_i c_i w_i + \sum_{i,j\ge 1} c_{ij} N^j w_i = 0. Applying NN: ∑iciui+∑i,j≥1cijNjui=0\sum_i c_i u_i + \sum_{i,j \ge 1} c_{ij} N^j u_i = 0 in UU, forcing (by independence of the basis of UU) all ci=0c_i = 0 and all cij=0c_{ij}=0 for j≥1j \geq 1 with NjuiN^j u_i nonzero terms — since the basis of UU is exactly {ui,Nui,… }\{u_i, Nu_i,\dots\}, this forces every coefficient in that relation to be 00, in particular ci=0c_i = 0 for all ii; then the original relation reduces to ∑i,j≥1cijNjwi=0\sum_{i,j\ge1} c_{ij}N^jw_i = 0, i.e. ∑i,j≥1cijNj−1ui=0\sum_{i,j\ge1}c_{ij}N^{j-1}u_i = 0, forcing cij=0c_{ij}=0 too). Hence Claim 1 holds. Claim 2: dim⁡(C1+⋯+Cs)=dim⁡U+s≥dim⁡U\dim(C_1 + \cdots + C_s) = \dim U + s \geq \dim U, and we may extend a basis to reach all of WW. Let S=C1⊕⋯⊕CsS = C_1 \oplus \cdots \oplus C_s (direct because the spanning sets found in Claim 1 are independent). We have dim⁡S=dim⁡U+s\dim S = \dim U + s. Now pick any complement: extend the linearly independent set {Nℓiwi}i=1s\{N^{\ell_i} w_i\}_{i=1}^s (a basis for S∩ker⁡N∩S \cap \ker N \cap ... — more directly) as follows. Since ker⁡N∩U\ker N \cap U has dimension ss (it is spanned by the "top" vectors Nℓi−1ui=NℓiwiN^{\ell_i-1}u_i = N^{\ell_i}w_i of each chain in UU, by the rank–nullity structure of the cyclic decomposition of N∣UN|_U), and ker⁡N\ker N has dimension dim⁡W−dim⁡U\dim W - \dim U (rank–nullity for N:W→UN: W \to U, since NN is surjective onto UU by definition of UU), we may choose a complement KK of ker⁡N∩U\ker N \cap U inside ker⁡N\ker N, with

dim⁡K=(dim⁡W−dim⁡U)−s.\dim K = (\dim W - \dim U) - s.

Choose a basis ws+1,…,wrw_{s+1}, \dots, w_r of KK (so r−s=dim⁡Kr - s = \dim K), each satisfying Nwi=0N w_i = 0, i.e. each generates a chain of length 11: Ci=span⁡{wi}C_i = \operatorname{span}\{w_i\}. Now verify W=S⊕KW = S \oplus K: dimensions add correctly,

dim⁡S+dim⁡K=(dim⁡U+s)+((dim⁡W−dim⁡U)−s)=dim⁡W,\dim S + \dim K = (\dim U + s) + \big((\dim W - \dim U) - s\big) = \dim W,

so it suffices to show S∩K={0}S \cap K = \{0\} and S+KS + K is direct with the rest — but we show directly W=⨁i=1rCiW = \bigoplus_{i=1}^r C_i by showing the total spanning set is independent and has size dim⁡W\dim W. Independence of {Njwi:1≤i≤s,j≤ℓi}∪{wi:s<i≤r}\{N^jw_i : 1\le i\le s, j\le \ell_i\} \cup \{w_i : s<i\le r\}: any dependence, after applying NN, kills all the wiw_i (i>si>s) terms (since Nwi=0Nw_i=0 for i>si > s) and all j≥1j\ge 1 terms shift down by one power; arguing as in Claim 1 this forces the coefficients of NjwiN^jw_i for j≥1j \ge 1 to vanish, and separately the coefficients of wiw_i (i≤si \le s) to vanish by Claim 1's argument, leaving a dependence purely among {wi}i>s\{w_i\}_{i>s}, which are independent by construction (basis of KK) and independent from SS because KK was chosen as a complement to ker⁡N∩U\ker N \cap U inside ker⁡N\ker N, hence K∩U={0}K \cap U = \{0\} and in particular K∩S={0}K \cap S = \{0\} (as S⊆U+span⁡(wi′s)S \subseteq U + \operatorname{span}(w_i's) ... since each generator wiw_i, i≤si\le s, was chosen with Nwi=ui∈UNw_i = u_i \in U, so S=⨁Ci⊆span⁡(w1,…,ws)+US = \bigoplus C_i \subseteq \operatorname{span}(w_1,\ldots,w_s) + U, and KK is disjoint from that span by the complement construction). Counting total dimension: ∑i=1s(ℓi+1)+(r−s)=(dim⁡U+s)+(dim⁡W−dim⁡U−s)=dim⁡W\sum_{i=1}^s(\ell_i+1) + (r-s) = (\dim U + s) + (\dim W - \dim U - s) = \dim W. A linearly independent spanning-sized set is a basis, so W=⨁i=1rCiW = \bigoplus_{i=1}^r C_i, completing the inductive step with chain lengths ki=ℓi+1k_i = \ell_i + 1 for i≤si \le s and ki=1k_i = 1 for i>si > s.

Uniqueness of the multiset {ki}\{k_i\}. For j≥0j \geq 0, rank⁡(Nj)\operatorname{rank}(N^j) restricted to a single chain summand Ci=span⁡{wi,Nwi,…,Nki−1wi}C_i = \operatorname{span}\{w_i, Nw_i,\dots,N^{k_i-1}w_i\} (with Nkiwi=0N^{k_i}w_i = 0) contributes exactly max⁡(ki−j,0)\max(k_i - j, 0) to the rank of NjN^j on WW (since NjN^j maps the basis of CiC_i to {Njwi,…,Nki−1wi,0,…,0}\{N^jw_i,\dots,N^{k_i-1}w_i, 0,\dots,0\}, of which max⁡(ki−j,0)\max(k_i-j,0) are nonzero and, being a sub-list of an independent chain basis mapped into disjoint summands, contribute independently to the rank of NjN^j on the whole space — direct sums of NN-invariant subspaces make NjN^j block diagonal, and rank adds over blocks). Hence

rank⁡(Nj)=∑i=1rmax⁡(ki−j,0),j≥0.\operatorname{rank}(N^j) = \sum_{i=1}^r \max(k_i - j, 0), \qquad j \geq 0.

The right side is exactly the "partition rank function" of the partition {ki}\{k_i\} of dim⁡W\dim W; a classical identity for partitions gives

#{i:ki=k}=(rank⁡(Nk−1)−rank⁡(Nk))−(rank⁡(Nk)−rank⁡(Nk+1))=rank⁡(Nk−1)−2rank⁡(Nk)+rank⁡(Nk+1),\#\{i : k_i = k\} = \big(\operatorname{rank}(N^{k-1}) - \operatorname{rank}(N^k)\big) - \big(\operatorname{rank}(N^k) - \operatorname{rank}(N^{k+1})\big) = \operatorname{rank}(N^{k-1}) - 2\operatorname{rank}(N^k) + \operatorname{rank}(N^{k+1}),

which depends only on NN (not on any choice of chains), proving the multiset {k1,…,kr}\{k_1,\dots,k_r\} is an invariant of NN alone. ■\blacksquare

∎
Proof

Proof of the main theorem, using the Lemma. Existence. By the Generalized Eigenspace Decomposition, since F\mathbb{F} is algebraically closed, the characteristic polynomial of TT splits into linear factors, and VV decomposes as a direct sum of generalized eigenspaces

V=⨁i=1mG(λi,T),G(λi,T)=ker⁡(T−λiI)n,V = \bigoplus_{i=1}^m G(\lambda_i, T), \qquad G(\lambda_i,T) = \ker(T - \lambda_i I)^n,

where λ1,…,λm\lambda_1,\dots,\lambda_m are the distinct eigenvalues of TT and n=dim⁡Vn = \dim V. Each G(λi,T)G(\lambda_i,T) is TT-invariant, and on G(λi,T)G(\lambda_i,T) the operator Ni:=(T−λiI)∣G(λi,T)N_i := (T - \lambda_i I)\big|_{G(\lambda_i,T)} is nilpotent by definition of generalized eigenspace (every vector is annihilated by some power of T−λiIT - \lambda_iI, and finite-dimensionality gives a uniform bound, namely Nidim⁡G(λi,T)=0N_i^{\dim G(\lambda_i,T)} = 0). Apply the Lemma to NiN_i on W=G(λi,T)W = G(\lambda_i, T): we obtain a basis of G(λi,T)G(\lambda_i,T) consisting of chains {w,Niw,…,Nik−1w}\{w, N_iw,\dots,N_i^{k-1}w\} with Nikw=0N_i^k w = 0. On such a chain, writing vj=Nik−jwv_j = N_i^{k-j}w for j=1,…,kj=1,\dots,k (so v1=Nik−1wv_1 = N_i^{k-1}w is the "bottom," annihilated by NiN_i), we get

Niv1=0,Nivj=vj−1 (j≥2),N_i v_1 = 0, \quad N_i v_j = v_{j-1} \ (j \ge 2),

i.e. (T−λiI)v1=0(T-\lambda_iI)v_1 = 0 and (T−λiI)vj=vj−1(T-\lambda_iI)v_j = v_{j-1}, so Tv1=λiv1Tv_1 = \lambda_i v_1 and Tvj=λivj+vj−1Tv_j = \lambda_i v_j + v_{j-1}. In the ordered basis (v1,…,vk)(v_1,\dots,v_k) of this chain, the matrix of TT restricted to span⁡(v1,…,vk)\operatorname{span}(v_1,\ldots,v_k) is exactly Jk(λi)J_k(\lambda_i): column jj records Tvj=λivj+vj−1Tv_j = \lambda_i v_j + v_{j-1}, giving λi\lambda_i on the diagonal and a single 11 in row j−1j-1, i.e. the superdiagonal. Concatenating the chain-bases over all chains within G(λi,T)G(\lambda_i,T), and then over all i=1,…,mi = 1,\dots,m, produces a basis β\beta of VV (a basis of the whole space, since the G(λi,T)G(\lambda_i,T) direct-sum to VV and each chain-basis is a basis of its summand) in which [T]β[T]_\beta is block diagonal with each block a Jordan block Jk(λi)J_k(\lambda_i). This proves existence. Uniqueness. Suppose β\beta is any basis with [T]β[T]_\beta a direct sum of Jordan blocks Jk1(μ1),…,Jkm(μm)J_{k_1}(\mu_1),\dots,J_{k_m}(\mu_m). First, the set of distinct μi\mu_i's occurring must be exactly the set of eigenvalues of TT: a block-diagonal matrix has characteristic polynomial equal to the product of the characteristic polynomials of its blocks, and det⁡(xI−Jk(λ))=(x−λ)k\det(xI - J_k(\lambda)) = (x-\lambda)^k since Jk(λ)J_k(\lambda) is upper triangular with λ\lambda repeated on the diagonal; hence the multiset of all μi\mu_i (with multiplicity kik_i each) is exactly the multiset of roots of the characteristic polynomial of TT, which is similarity-invariant. Fix an eigenvalue λ\lambda of TT. Let βλ⊆β\beta_\lambda \subseteq \beta be the union of the basis vectors belonging to the Jordan blocks Jki(λ)J_{k_i}(\lambda) (those blocks among [T]β[T]_\beta with eigenvalue exactly λ\lambda), and let Vλ=span⁡(βλ)V_\lambda = \operatorname{span}(\beta_\lambda). Direct computation on a single block shows (T−λI)(T - \lambda I) acts on the span of Jk(λ)J_k(\lambda)'s basis exactly as the nilpotent shift, hence is nilpotent there, and for μ≠λ\mu \ne \lambda, (T−μI)∣Vμ-block(T-\mu I)|_{V_\mu\text{-block}} has Jk(λ)−μI=Jk(λ−μ)J_k(\lambda) - \mu I = J_k(\lambda - \mu) which is invertible (upper triangular with nonzero diagonal entries λ−μ\lambda - \mu). Since [T]β[T]_\beta is block diagonal, VλV_\lambda (the sum of blocks with that exact eigenvalue) is precisely

Vλ=ker⁡(T−λI)dim⁡V,V_\lambda = \ker(T-\lambda I)^{\dim V},

because on VλV_\lambda, T−λIT - \lambda I is nilpotent (kernel eventually all of VλV_\lambda under a high enough power), while on the complementary sum of other blocks, T−λIT - \lambda I is invertible (each block Jk(μ)−λIJ_k(\mu)-\lambda I invertible for μ≠λ\mu \neq \lambda, so the whole block-diagonal restriction is invertible, being a direct sum of invertible maps), hence contributes nothing to the kernel of any power. But ker⁡(T−λI)dim⁡V=G(λ,T)\ker(T-\lambda I)^{\dim V} = G(\lambda, T) is exactly the generalized eigenspace, which is intrinsically defined from TT alone (no basis choice). Hence Vλ=G(λ,T)V_\lambda = G(\lambda,T) is forced, independent of which valid Jordan basis β\beta we started with. Within Vλ=G(λ,T)V_\lambda = G(\lambda,T), the restriction N=(T−λI)∣VλN = (T-\lambda I)|_{V_\lambda} is a fixed nilpotent operator (determined by TT and λ\lambda alone), and the basis βλ\beta_\lambda exhibits NN as a direct sum of shift-chains of lengths kik_i (the sizes of the blocks with eigenvalue λ\lambda) — precisely the cyclic decomposition data of NN from the Lemma. By the uniqueness clause of the Lemma, the multiset {ki}\{k_i\} of chain lengths is determined by NN alone via

#{i:ki=k}=rank⁡(Nk−1)−2rank⁡(Nk)+rank⁡(Nk+1)=rank⁡(T−λI)k−1∣G(λ,T)−2rank⁡(T−λI)k∣G(λ,T)+rank⁡(T−λI)k+1∣G(λ,T),\#\{i : k_i = k\} = \operatorname{rank}(N^{k-1}) - 2\operatorname{rank}(N^k) + \operatorname{rank}(N^{k+1}) = \operatorname{rank}(T-\lambda I)^{k-1}\big|_{G(\lambda,T)} - 2\operatorname{rank}(T-\lambda I)^k\big|_{G(\lambda,T)} + \operatorname{rank}(T-\lambda I)^{k+1}\big|_{G(\lambda,T)},

which does not depend on β\beta at all — it is a formula purely in terms of TT and λ\lambda. Therefore the number of Jordan blocks of size kk with eigenvalue λ\lambda is the same for any valid Jordan basis β\beta. Since λ\lambda and kk were arbitrary, the entire multiset of Jordan blocks (eigenvalue and size for each) is an invariant of TT, proving uniqueness up to reordering. Similarity criterion. If A,BA, B are similar, say B=P−1APB = P^{-1}AP, then a Jordan basis for AA pushed forward by PP is a Jordan basis for BB giving the identical block multiset, since similar operators represent the same abstract linear map on isomorphic spaces up to change of basis, so their Jordan forms (existing by the theorem) coincide up to block order. Conversely, if AA and BB have the same Jordan block multiset, then each is similar to the same block-diagonal matrix JJ (via their respective Jordan bases), hence A=P1JP1−1A = P_1 J P_1^{-1} and B=P2JP2−1B = P_2 J P_2^{-1} for invertible P1,P2P_1, P_2, giving A=(P1P2−1)B(P1P2−1)−1A = (P_1P_2^{-1}) B (P_1P_2^{-1})^{-1}, so AA and BB are similar. ■\blacksquare

∎

Worked examples

Example 1 (a 6×66\times 6 matrix, single eigenvalue, nontrivial block pattern). Let λ=2\lambda = 2 and let TT act on V=C6V = \mathbb{C}^6 so that N=T−2IN = T - 2I satisfies, with respect to the standard basis e1,…,e6e_1,\dots,e_6,

Ne1=0,Ne2=e1,Ne3=e2,Ne4=0,Ne5=e4,Ne6=0.N e_1 = 0,\quad Ne_2 = e_1,\quad Ne_3=e_2, \quad Ne_4 = 0,\quad Ne_5 = e_4,\quad Ne_6=0.

So NN has three chains: e3→e2→e1→0e_3 \to e_2 \to e_1 \to 0 (length 33), e5→e4→0e_5 \to e_4 \to 0 (length 22), and e6→0e_6 \to 0 (length 11). We verify this via ranks, to illustrate the uniqueness formula rather than just reading off the chains. Matrix of NN (columns are images of e1,…,e6e_1,\ldots,e_6):

N=(010000001000000000000010000000000000).N = \begin{pmatrix} 0&1&0&0&0&0\\ 0&0&1&0&0&0\\ 0&0&0&0&0&0\\ 0&0&0&0&1&0\\ 0&0&0&0&0&0\\ 0&0&0&0&0&0 \end{pmatrix}.

Compute ranks directly. NN has two nonzero rows worth of pivots: columns 2,32,3 contribute rank from the first chain, column 55 from the second; so rank⁡(N)=3\operatorname{rank}(N) = 3 (images e1,e2,e4e_1, e_2, e_4 are hit, all independent). N2N^2: apply NN twice. N2e3=N(e2)=e1N^2 e_3 = N(e_2) = e_1, N2e5=N(e4)=0N^2 e_5 = N(e_4) = 0, all others 00. So rank⁡(N2)=1\operatorname{rank}(N^2) = 1. N3=0N^3 = 0 (longest chain has length 33), so rank⁡(N3)=0\operatorname{rank}(N^3) = 0, and rank⁡(Nj)=0\operatorname{rank}(N^j) = 0 for j≥3j \geq 3. Also rank⁡(N0)=rank⁡(I)=6\operatorname{rank}(N^0) = \operatorname{rank}(I) = 6. Now apply the counting formula #{ki=k}=rank⁡(Nk−1)−2rank⁡(Nk)+rank⁡(Nk+1)\#\{k_i = k\} = \operatorname{rank}(N^{k-1}) - 2\operatorname{rank}(N^k)+\operatorname{rank}(N^{k+1}):

  • k=1k=1: rank⁡(N0)−2rank⁡(N1)+rank⁡(N2)=6−2(3)+1=1\operatorname{rank}(N^0) - 2\operatorname{rank}(N^1) + \operatorname{rank}(N^2) = 6 - 2(3) + 1 = 1.
  • k=2k=2: rank⁡(N1)−2rank⁡(N2)+rank⁡(N3)=3−2(1)+0=1\operatorname{rank}(N^1) - 2\operatorname{rank}(N^2) + \operatorname{rank}(N^3) = 3 - 2(1) + 0 = 1.
  • k=3k=3: rank⁡(N2)−2rank⁡(N3)+rank⁡(N4)=1−0+0=1\operatorname{rank}(N^2) - 2\operatorname{rank}(N^3) + \operatorname{rank}(N^4) = 1 - 0 + 0 = 1.
  • k≥4k \geq 4: all ranks involved are 00, giving 00.

So there is exactly one block of size 11, one of size 22, one of size 33 — matching our construction exactly, and confirming 1+2+3=6=dim⁡V1 + 2 + 3 = 6 = \dim V. The Jordan Canonical Form of TT is

J3(2)⊕J2(2)⊕J1(2)=(21002100221022).J_3(2) \oplus J_2(2) \oplus J_1(2) = \left(\begin{array}{ccc|cc|c} 2&1&0&&&\\ 0&2&1&&&\\ 0&0&2&&&\\ \hline &&&2&1&\\ &&&0&2&\\ \hline &&&&&2 \end{array}\right).

Example 2 (two eigenvalues, mixed block sizes, computed from a concrete matrix). Let

A=(3100003000003000005100005)A = \begin{pmatrix} 3 & 1 & 0 & 0 & 0\\ 0 & 3 & 0 & 0 & 0\\ 0 & 0 & 3 & 0 & 0\\ 0 & 0 & 0 & 5 & 1\\ 0 & 0 & 0 & 0 & 5 \end{pmatrix}

— but suppose we are only handed the characteristic and minimal polynomial data and rank computations, as would happen from a genuinely non-block-diagonal input; we determine the Jordan form purely from invariants to demonstrate the method. Say we are told:

  • Characteristic polynomial: p(x)=(x−3)3(x−5)2p(x) = (x-3)^3(x-5)^2.
  • rank⁡(A−3I)=4\operatorname{rank}(A - 3I) = 4 (computed by row reduction), so dim⁡ker⁡(A−3I)=5−4=1\dim\ker(A-3I) = 5 - 4 = 1.
  • rank⁡(A−3I)2=3\operatorname{rank}(A-3I)^2 = 3, so dim⁡ker⁡(A−3I)2=2\dim \ker(A-3I)^2 = 2; since the generalized eigenspace for 33 has dimension 33 (algebraic multiplicity) we also know rank⁡(A−3I)3=2\operatorname{rank}(A-3I)^3 = 2 (it stabilizes once the kernel reaches dimension 33, i.e. rank⁡\operatorname{rank} stabilizes at 5−3=25 - 3 = 2).
  • rank⁡(A−5I)=4\operatorname{rank}(A - 5I) = 4, so dim⁡ker⁡(A−5I)=1\dim\ker(A-5I) = 1; generalized eigenspace for 55 has dimension 22 so rank⁡(A−5I)2=3\operatorname{rank}(A-5I)^2 = 3 (stabilizes at 5−2=35-2=3).

For λ=3\lambda = 3: apply the formula with N=(A−3I)N = (A-3I) restricted to G(3,A)G(3,A) (dimension 33), using the global ranks intersected appropriately — more directly, since G(3,A)G(3,A) has dimension 33 and the restricted operator's rank sequence (restricted to G(3,A)G(3,A)) is rank⁡(N0)=3,rank⁡(N1)=3−dim⁡ker⁡(N)∣G(3,A)\operatorname{rank}(N^0)=3, \operatorname{rank}(N^1) = 3 - \dim\ker(N)|_{G(3,A)}. We use that dim⁡ker⁡(A−3I)=1\dim\ker(A-3I) = 1 overall (and all of this kernel lies in G(3,A)G(3,A), a general fact about generalized eigenspaces), so restricted to G(3,A)G(3,A): rank⁡(N0)=3\operatorname{rank}(N^0) = 3, rank⁡(N1)=3−1=2\operatorname{rank}(N^1) = 3 - 1 = 2. Since dim⁡ker⁡(A−3I)2=2\dim\ker(A-3I)^2 = 2 and this kernel is entirely inside G(3,A)G(3,A) too, restricted rank rank⁡(N2)=3−2=1\operatorname{rank}(N^2) = 3 - 2 = 1. Since G(3,A)G(3,A) has dimension 33, N3=0N^3 = 0 there, so rank⁡(N3)=0\operatorname{rank}(N^3) = 0. Counting: k=1k=1: 3−2(2)+1=03 - 2(2) + 1 = 0. k=2k=2: 2−2(1)+0=02 - 2(1) + 0 = 0. k=3k=3: 1−2(0)+0=11 - 2(0) + 0 = 1. So there is exactly one Jordan block of size 33 for λ=3\lambda=3: it is J3(3)J_3(3), consuming all 33 dimensions of G(3,A)G(3,A) — consistent since dim⁡ker⁡(A−3I)=1\dim\ker(A-3I) = 1 (a single block always contributes exactly 11 to the eigenspace dimension). For λ=5\lambda = 5: G(5,A)G(5,A) has dimension 22; restricted ranks: rank⁡(N0)=2\operatorname{rank}(N^0) = 2, and since dim⁡ker⁡(A−5I)=1\dim \ker(A-5I) = 1 (restricted to G(5,A)G(5,A), all 11-dimensional kernel lies inside), rank⁡(N1)=2−1=1\operatorname{rank}(N^1) = 2 - 1 = 1; since dimension is 22, N2=0N^2 = 0 there so rank⁡(N2)=0\operatorname{rank}(N^2) = 0. Counting: k=1k=1: 2−2(1)+0=02 - 2(1) + 0 = 0. k=2k=2: 1−2(0)+0=11 - 2(0) + 0 = 1. So one block of size 22: J2(5)J_2(5). Total Jordan form: J3(3)⊕J2(5)J_3(3) \oplus J_2(5), matching exactly the block-diagonal matrix AA we started with — confirming the invariant-based method recovers the true answer even without directly reading off chains from an already-block-diagonal matrix.

CounterexampleAlgebraic closure cannot be dropped

The theorem requires F\mathbb{F} to be algebraically closed (equivalently: the characteristic polynomial of TT splits into linear factors over F\mathbb{F}). Drop this hypothesis and existence of a Jordan Canonical Form can fail entirely. Let F=R\mathbb{F} = \mathbb{R} and let

A=(0−110)∈R2×2,A = \begin{pmatrix} 0 & -1 \\ 1 & 0 \end{pmatrix} \in \mathbb{R}^{2\times 2},

the 90∘90^\circ rotation matrix, viewed as an operator TT on V=R2V = \mathbb{R}^2. Its characteristic polynomial is x2+1x^2 + 1, which is irreducible over R\mathbb{R} (its roots ±i\pm i are not real). Suppose for contradiction that AA were similar over R\mathbb{R} to a direct sum of Jordan blocks Jk1(λ1)⊕⋯J_{k_1}(\lambda_1) \oplus \cdots with each λi∈R\lambda_i \in \mathbb{R}. Since similar matrices have identical characteristic polynomials, and the characteristic polynomial of any direct sum of Jordan blocks with real eigenvalues λi\lambda_i is ∏i(x−λi)ki\prod_i (x - \lambda_i)^{k_i} — a product of real linear factors — this would force x2+1x^2+1 to factor into real linear factors, contradicting irreducibility. Thus no basis of R2\mathbb{R}^2 puts AA into Jordan Canonical Form: TT has no real eigenvalues at all, so in particular no eigenvector, and Jordan blocks always require at least one eigenvector per block (the "bottom" of each chain). The obstruction is purely the failure of algebraic closure: viewed instead as an operator on C2\mathbb{C}^2 (i.e., after extending scalars), AA does have eigenvalues ±i\pm i and is even diagonalizable there, similar to J1(i)⊕J1(−i)=diag⁡(i,−i)J_1(i) \oplus J_1(-i) = \operatorname{diag}(i,-i). This is exactly the gap that The Rational Canonical Form is designed to fill: it produces a canonical similarity-invariant matrix form (built from companion matrices of invariant factors) that exists over any field, at the cost of using slightly larger, less transparent blocks than single Jordan blocks when the characteristic polynomial does not split.

Scope, edge cases & common traps

SituationWhat happens
F\mathbb{F} algebraically closed (e.g. C\mathbb{C})Jordan form always exists and is unique up to block order.
F=R\mathbb{F} = \mathbb{R}, characteristic polynomial splits over R\mathbb{R}Jordan form still exists (only linear factors were used in the proof).
F=R\mathbb{F} = \mathbb{R}, characteristic polynomial has non-real rootsNo Jordan form over R\mathbb{R}; need C\mathbb{C} or The Rational Canonical Form.
TT diagonalizableJordan form has all blocks of size 11; recovers ordinary diagonalization.
Repeated eigenvalue, multiple blocks of same sizeUniqueness is only up to order; e.g. J2(λ)⊕J2(λ)J_2(\lambda)\oplus J_2(\lambda) has an ambiguous choice of which basis vectors form which chain, but the block multiset is forced.
Confusing algebraic and geometric multiplicityAlgebraic multiplicity of λ\lambda = sum of sizes of all λ\lambda-blocks; geometric multiplicity = number of λ\lambda-blocks (dimension of the ordinary eigenspace), not their sizes.

The mathematician behind it

Origins · 1 minMarie Ennemond Camille Jordan and how this was discovered
ME
Marie Ennemond Camille Jordan
1838–1922 · Paris, France

Camille Jordan was a French mathematician and engineer, professor at the École Polytechnique and the Collège de France, whose Traité des substitutions et des équations algébriques (1870) laid foundational work in group theory and linear algebra. He introduced the canonical block-diagonal decomposition for matrices (over what we would now call an algebraically closed field, in the context of substitution groups) in the course of his systematic study of the structure of linear substitutions, motivated by Galois theory and the classification of finite groups of linear transformations. Jordan is also known for the Jordan–Hölder theorem in group theory and the Jordan curve theorem in topology, but the canonical form bearing his name arose specifically from the linear-algebraic and group-theoretic study of matrix similarity classes.

History
- 1838 — Camille Jordan born in Lyon, France.
- 1870 — Jordan publishes the Traité des substitutions, containing the canonical decomposition of matrices into block form.
- 1892 — Karl Weierstrass and Eduard Weyr contribute independent refinements on canonical forms for pairs of bilinear forms and matrix pencils, closely related to the Jordan form.
- 1920s–1930s — the Jordan form becomes standard in the emerging axiomatic treatment of linear algebra, appearing in textbooks alongside the generalized eigenspace machinery.
- 1922 — Camille Jordan dies in Paris.
Why must every Jordan block have exactly one eigenvector, not more?

A Jordan block Jk(λ)J_k(\lambda) satisfies (Jk(λ)−λI)(J_k(\lambda) - \lambda I) equal to the nilpotent shift matrix with 11's on the superdiagonal and 00 elsewhere. Its kernel (the eigenspace for λ\lambda within that block) is spanned by exactly the first standard basis vector, a one-dimensional space, regardless of kk. So each Jordan block, no matter how large, contributes only one dimension to the eigenspace — hence exactly one linearly independent eigenvector. This is why geometric multiplicity (dimension of the ordinary eigenspace) counts the number of Jordan blocks for that eigenvalue, while algebraic multiplicity counts the total size (sum of block sizes) — two different invariants that coincide only when every block has size 11, i.e. when TT is diagonalizable.

How is the Jordan Canonical Form related to diagonalization?

Diagonalization is the special case of the Jordan Canonical Form in which every Jordan block has size 11. A single Jordan block J1(λ)J_1(\lambda) is just the 1×11\times 1 matrix (λ)(\lambda), so a direct sum of size-11 blocks is literally a diagonal matrix. The Minimal Polynomial and Diagonalizability criterion says TT is diagonalizable exactly when its minimal polynomial has no repeated roots; in Jordan-form language, this happens exactly when every Jordan block for every eigenvalue has size 11, since the minimal polynomial of a direct sum of Jordan blocks is ∏λ(x−λ)m(λ)\prod_\lambda (x-\lambda)^{m(\lambda)} where m(λ)m(\lambda) is the largest block size for eigenvalue λ\lambda — repeated roots in the minimal polynomial correspond precisely to blocks of size ≥2\geq 2.

Do I need to actually find the chain vectors v1,…,vkv_1,\dots,v_k to determine the Jordan form, or can I just use ranks?

You can determine the block sizes and multiplicities — the full similarity class — using only the rank formula #{ki=k}=rank⁡(Nk−1)−2rank⁡(Nk)+rank⁡(Nk+1)\#\{k_i=k\} = \operatorname{rank}(N^{k-1}) - 2\operatorname{rank}(N^k)+\operatorname{rank}(N^{k+1}) applied to N=T−λIN = T - \lambda I for each eigenvalue λ\lambda, without ever constructing an explicit Jordan basis. This is enough to answer "what is the Jordan form of this matrix" and to test similarity between two matrices. However, if you need an explicit change-of-basis matrix PP with P−1APP^{-1}AP in Jordan form (for instance, to solve a linear ODE explicitly), you do need to construct the actual generalized eigenvectors and chains, which requires solving nested systems (T−λI)vj+1=vj(T-\lambda I)v_{j+1}=v_j starting from vectors in ker⁡(T−λI)k∖ker⁡(T−λI)k−1\ker(T-\lambda I)^k \setminus \ker(T-\lambda I)^{k-1}.

Why doesn't the Jordan Canonical Form exist over every field, unlike, say, row echelon form?

Row echelon form is achieved purely by elementary row operations, which are always available over any field, and it doesn't attempt to encode eigenvalue information — it's not a similarity invariant, only an equivalence invariant (allowing independent row and column operations). The Jordan form, by contrast, is a similarity invariant: it requires expressing TT as diagonal-plus-nilpotent pieces glued exactly at the eigenvalues, and this construction leans on the Generalized Eigenspace Decomposition, which itself requires the characteristic polynomial to split into linear factors. Over a non-algebraically-closed field like Q\mathbb{Q} or R\mathbb{R}, an irreducible quadratic or higher-degree factor in the characteristic polynomial signals an eigenvalue that simply does not exist in that field, so no basis over that field can diagonalize-plus-nilpotent-decompose the operator around it.

What is the relationship between the Jordan form and the minimal and characteristic polynomials?

The characteristic polynomial of TT equals ∏λ(x−λ)a(λ)\prod_\lambda (x-\lambda)^{a(\lambda)} where a(λ)a(\lambda) is the algebraic multiplicity, which in Jordan-form terms is the sum of the sizes of all Jordan blocks for eigenvalue λ\lambda — this recovers exactly the total dimension of G(λ,T)G(\lambda,T). The minimal polynomial equals ∏λ(x−λ)m(λ)\prod_\lambda (x-\lambda)^{m(\lambda)} where m(λ)m(\lambda) is the size of the largest Jordan block for λ\lambda, because (T−λI)m(λ)(T-\lambda I)^{m(\lambda)} is needed to annihilate the longest chain, and no smaller power suffices, while (T−μI)(T-\mu I) for μ≠λ\mu \ne \lambda contributes independently on other generalized eigenspaces. Both polynomials are recoverable from the Jordan form, but neither one alone recovers the full Jordan form when there is more than one block per eigenvalue.

Can the Jordan Canonical Form of a real matrix with all real eigenvalues be computed while staying entirely within real arithmetic?

Yes. The existence proof only uses the fact that the characteristic polynomial splits into linear factors over the field in question — it never uses complex conjugation or any property special to C\mathbb{C} beyond algebraic closure. If a real matrix has characteristic polynomial factoring completely into real linear factors (equivalently, all eigenvalues are real, counted with multiplicity), then the generalized eigenspace decomposition and the cyclic decomposition of each nilpotent piece can be carried out entirely with real vectors and real arithmetic, producing a genuine real Jordan basis. Only when some eigenvalues are non-real does one need to either pass to C\mathbb{C} or use the real Jordan form with real 2×22\times2 rotation-scaling blocks instead of complex Jordan blocks.

Before this

Where this leads