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Linear Recurrences and Rational Generating Functions
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
- Countability and Uncountability
- Determinants of Matrices over a Commutative Ring
- Divisibility, Euclidean Domains, Principal Ideal Domains and Unique Factorisation
- Eigenvalues, Eigenvectors and the Characteristic Polynomial
- Finite Counting, Factorials and Binomial Coefficients
- Formal Power Series
- 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
- 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 Field of Fractions and Localisation
- The ZFC Axioms and the Basic Set Constructions
- Vector Spaces, Linear Subspaces, Span and Direct Sums
2 · Summary
Formal power series over a commutative ring, coefficient extraction with its linearity and extensionality, the unit criterion for a formal power series, and the formal derivative with its algebra are published. So are matrices over a commutative ring and their arithmetic, the determinant, Laplace cofactor expansion, minors, cofactors and the adjugate with the adjugate identity, the characteristic polynomial of a matrix and of an operator, the Cayley–Hamilton theorem, the spectral mapping theorem for polynomials, the trace as the sum of the eigenvalues, polynomial division over a field with Bézout's identity and unique factorisation, splitting fields, and the rational function field as a field of fractions.
A constant-coefficient linear recurrence and a rational generating function describe the same object: for a fixed denominator the initial-value, recurrence-sequence, numerator and rational-series spaces are linearly isomorphic, and no root is chosen. Reduced denominators give the minimal order, finite modification preserves eventual recurrence and rationality, rational series are closed under sums, products and Hadamard products, and over a splitting field partial fractions with the repeated-pole binomial series give the polynomial-times-exponential closed form. Companion matrices and Cayley–Hamilton connect the recurrence and matrix pictures. A finite weighted digraph makes walks entries of transfer-matrix powers; the formal matrix geometric series presents the walk series as a cofactor over , trace and logarithmic-derivative formulas follow, and prefix automata make the generating function of words avoiding finitely many factors rational.
3 · Logical flowchart
4 · Definitions, theorems and proofs
Constant-coefficient linear recurrences, their starting index and their characteristic polynomial
Definition
Let be a field, let be a sequence in , and let . A constant-coefficient linear recurrence of order starting at is an identity
where and . Its characteristic polynomial and reciprocal denominator are
The recurrence holds from the start when , and it is eventual when such an exists. An order-zero recurrence starting at means for every ; its characteristic polynomial and reciprocal denominator are both . This convention makes finitely supported sequences precisely the sequences of eventual order zero.
For a bi-infinite sequence , the same displayed identity is a recurrence of order when it holds for every . The condition then lets the identity be solved both forward and backward.
Rational formal power series, proper presentations and reduced denominators
Definition
Let be a commutative ring. A formal power series (Formal power series over a commutative ring and the coefficient-extraction functional ) is rational if there are polynomials such that is a unit and
in . Equivalently, , where is the unique formal inverse supplied by A formal power series is a unit exactly when its constant coefficient is a unit.
Now let be a field. Multiplying numerator and denominator by gives a normalised presentation with . Such a presentation is proper when or (Degree, leading coefficient and monic polynomial, with the zero polynomial having no degree). It is reduced when and have no common nonunit factor. A polynomial series has the reduced presentation , and the zero series has reduced presentation .
A polynomial occurring in a normalised reduced presentation is called a reduced denominator of . The minimal-order theorem will show that all reduced denominators of one series have the same degree.
The initial-value, recurrence-sequence, numerator and fixed-denominator rational-series spaces all have dimension
Statement
Let be a field, let , let with , and put . The following four -vector spaces are naturally linearly isomorphic:
- the initial-value space ;
- the space of sequences satisfying for every ;
- the space of polynomials with or ;
- the space of formal series with or .
Each space has dimension .
Facts & Assumptions
Given: A field , a positive order , coefficients with , and .
An order- recurrence from the start is for every (Constant-coefficient linear recurrences, their starting index and their characteristic polynomial).
A proper fixed-denominator series has the form with and either or (Rational formal power series, proper presentations and reduced denominators).
Formal series are equal exactly when all their coefficients agree, and (Coefficient extraction is -linear, separates formal series, shifts under multiplication by , and converts products to finite convolution).
The standard unit vectors form a basis of , so , including the zero-dimensional boundary (The standard list with and for is an ordered basis of ; hence , and is the zero space with basis and dimension ).
Proof
Given , set for and recursively define ; this produces exactly one recurrence sequence with those initial values.
For a recurrence sequence with , [L3] gives for , so every such coefficient is zero by [L1] and has degree below or is zero.
Because , division by is defined formally, and is a linear bijection from the numerator space to the proper fixed-denominator series space.
Initial-value extraction is linear, and step 1.1 is its linear inverse; hence the initial-value and recurrence-sequence spaces are linearly isomorphic.
Conversely, if has no nonzero coefficient in degrees , the same coefficient identity read backwards gives the recurrence for every ; thus is a linear bijection from the recurrence-sequence space to the degree- numerator space.
Coefficient extraction identifies the numerator space with , and [L4] gives its dimension ; the linear isomorphisms in steps 2.1, 2.2 and 1.3 therefore give dimension for all four spaces.
A coefficient sequence is eventually linearly recurrent if and only if its formal generating function is rational
Statement
Let be a field, let be a sequence in , and let . Then satisfies an eventual constant-coefficient linear recurrence if and only if is a rational formal power series.
More precisely, let with and . The sequence satisfies the corresponding recurrence from index exactly when has no nonzero coefficient of degree at least . In particular, the recurrence starts at zero exactly when is zero or has degree below .
Facts & Assumptions
Given: A field , a sequence , and its formal generating function .
For fixed with and , multiplication by identifies sequences recurrent from zero with numerators of degree below (The initial-value, recurrence-sequence, numerator and fixed-denominator rational-series spaces all have dimension ).
If and , there are unique with and either or (Division algorithm for polynomials over a field).
Proof
Suppose first that satisfies an order- recurrence from index . For , coefficient extraction gives , so is a polynomial and is rational.
An eventual order-zero recurrence means that is eventually zero, so is a polynomial and is rational with denominator .
Conversely, suppose with . Rescale so that , and use [L2] to write with or ; then .
If , [L1] says that the coefficients of satisfy the order- recurrence from zero, while the polynomial changes only finitely many coefficients; hence the coefficients of satisfy that recurrence eventually. If , then is eventually zero and has eventual order zero.
The coefficient calculation in step 1.1 is reversible: for fixed positive-degree , the recurrence holds at exactly when . This gives the stated starting-index clause and completes both directions.
initial values determine a sequence satisfying a fixed order- recurrence
Statement
Fix a field , an integer , and coefficients with . For every initial list , there is exactly one sequence satisfying
and for .
Facts & Assumptions
Given: A field , a positive order , fixed recurrence coefficients with nonzero trailing coefficient, and an initial list in .
Initial-value extraction is a linear isomorphism from the fixed-recurrence sequence space to (The initial-value, recurrence-sequence, numerator and fixed-denominator rational-series spaces all have dimension ).
Proof
Surjectivity in [L1] gives a recurrence sequence with the prescribed initial values.
Injectivity in [L1] says that two recurrence sequences with the same initial list are equal, proving uniqueness. This includes , where one initial value determines every later term.
The least eventual recurrence order is the degree of the reduced denominator
Statement
Let be rational over a field, and let be a normalised reduced presentation. The least order of an eventual constant-coefficient recurrence satisfied by is , with the convention that . Thus polynomial series have minimal eventual order zero.
Facts & Assumptions
Given: A rational series over a field , where and are coprime.
A sequence is eventually linearly recurrent exactly when its generating function is rational, and a denominator of degree supplies an eventual recurrence of order (A coefficient sequence is eventually linearly recurrent if and only if its formal generating function is rational).
The polynomial ring over a field is a unique factorisation domain (For every field , is a unique factorisation domain).
Proof
If satisfies an eventual recurrence of order , [L1] gives a polynomial and a normalised denominator of degree with , so .
Since and are coprime in the UFD , the identity forces ; therefore .
If , the presentation itself gives by [L1] an eventual recurrence of order , so step 2.1 proves minimality. If , then is a polynomial and its coefficients are eventually zero, giving minimal order zero.
Changing finitely many coefficients preserves rationality and eventual linear recurrence
Statement
Let and be sequences over a field which differ at only finitely many indices. Then the generating series is rational if and only if is rational. Equivalently, is eventually linearly recurrent if and only if is eventually linearly recurrent.
A finite modification need not preserve a recurrence with starting index zero.
Facts & Assumptions
Given: Two sequences and over a field which differ at only finitely many indices.
A coefficient sequence is eventually linearly recurrent if and only if its formal generating function is rational (A coefficient sequence is eventually linearly recurrent if and only if its formal generating function is rational).
Proof
The difference has finite support, so it is a polynomial.
If is rational, then is rational; the same argument with proves the converse.
Applying [L1] to both series converts step 2.1 into the equivalence of eventual recurrence.
For the final warning, the zero sequence satisfies from zero, while changing only to destroys that identity at , even though the modified sequence is eventually zero.
For a bi-infinite linear recurrence over , the two half-series satisfy in
Statement
Let be a field, let , and let satisfy
where . Put
Both series are rational, and in the rational function field ,
More precisely, write with , , and . If
then and , while and . Finally,
holds exactly when for every . If , the recurrence and force , so the main identity holds and the minima are intentionally left undefined.
Facts & Assumptions
Given: A field and a bi-infinite order- recurrence with nonzero trailing coefficient.
An eventual recurrence has a rational generating function, and a recurrence from zero with reciprocal denominator gives a numerator of degree below (A coefficient sequence is eventually linearly recurrent if and only if its formal generating function is rational).
The fraction field of is the rational function field (For a field , is its rational function field; in particular ).
Proof
Applying [L1] to the positive half gives with , and applying it to the reversed negative half gives rationality of .
In the vector space of all formal sums , multiplication by the polynomial is coefficientwise finite. The recurrence says , so linearity gives .
The lowest nonzero coefficient of equals the lowest nonzero coefficient of , because ; hence the positive minimum is and .
Substitute for in step 2.1 and interpret both quotients in [L2]; this gives in , not as an equality of formal power series.
Rewriting as shows that its first nonzero term has degree and coefficient , proving the negative-side clauses.
Apply the main identity to replace by ; coefficient comparison then shows that is equivalent to for every integer .
If , then , so for ; solving the recurrence backwards using gives for all , and the main identity remains valid.
Rational formal power series are closed under sums and Cauchy products
Statement
Let be a commutative ring. If are rational, then both and the Cauchy product are rational. This includes zero series and polynomial presentations.
Facts & Assumptions
Given: Rational presentations and over a commutative ring .
A rational formal series has a presentation whose denominator has unit constant coefficient (Rational formal power series, proper presentations and reduced denominators).
A formal series is a unit exactly when its constant coefficient is a unit (A formal power series is a unit exactly when its constant coefficient is a unit).
Proof
The product has unit constant coefficient , so it is a unit of by [L2].
The identities and have polynomial numerators and the denominator from step 1.1, so [L1] makes both series rational. The formulas remain valid when a numerator is zero or a denominator is .
The Hadamard product of two rational formal power series over a field is rational
Statement
Let be a field. If and are rational formal power series over , then their Hadamard product
is rational.
Facts & Assumptions
Given: Rational series and over a field .
A coefficient sequence has a rational generating function exactly when it is eventually linearly recurrent (A coefficient sequence is eventually linearly recurrent if and only if its formal generating function is rational).
A linearly independent subset of a vector space spanned by vectors has at most elements (If has a spanning set with elements, then every linearly independent subset of is finite with at most elements; in particular has no linearly independent subset equinumerous with ).
Proof
By [L1], after deleting finite prefixes the sequences and satisfy recurrences of orders and . Hence all shifts of the first tail lie in the span of its first shifts, and all shifts of the second tail lie in the span of its first shifts.
If or , one tail and hence the product tail is zero, so [L1] already proves rationality. It remains to take .
Let be the span, inside the vector space of -valued sequences, of the coefficientwise products with and . Every simultaneous shift belongs to by bilinear expansion.
By [L2], among any simultaneous shifts of the product tail there is a nontrivial linear dependence. Remove initial and terminal zero coefficients from such a relation and normalise its last coefficient to ; the remaining first coefficient is nonzero and the relation is an eventual constant-coefficient recurrence for .
Applying [L1] to the product sequence in step 4.1 proves that is rational in the positive-order case. Together with step 2.1, this covers all rational inputs, and finite prefixes discarded in step 1.1 do not affect eventual recurrence.
Reciprocal-root convention: corresponds to
Statement
The recurrence convention of Constant-coefficient linear recurrences, their starting index and their characteristic polynomial pairs
with . Therefore, in any field over which splits,
The roots of are the reciprocals , while the numbers appearing in recurrence closed forms are the characteristic roots . The nonzero trailing coefficient in the recurrence makes every nonzero. This convention is algebraic and does not assert convergence of at any value of (Rational formal power series, proper presentations and reduced denominators).
A proper rational function with split denominator has a unique repeated-pole partial-fraction expansion
Statement
Let be a field, let be pairwise distinct and nonzero, let , and put
For every with or , there are unique scalars such that
For , every is zero.
Facts & Assumptions
Given: A field , distinct nonzero , positive multiplicities , and a proper numerator for .
A split recurrence denominator has factors corresponding to the characteristic factors (Reciprocal-root convention: corresponds to ).
Coprime polynomials over a field admit with (Bézout identity and the Euclidean algorithm for polynomials over a field).
Splitting permits a factorisation into linear factors with repetitions recording multiplicity (Polynomials that split and splitting fields of a polynomial or a family of polynomials).
Proof
The powers are pairwise coprime: distinct linear factors have no common root, and [L2] then gives a Bezout identity for every pair.
Iterating the two-factor Bezout decomposition gives polynomials with such that ; at each stage the remainder modulo supplies .
Each has a unique expansion , because the polynomials form a basis of the polynomials of degree below .
If the displayed partial-fraction sum is zero, clear denominators and reduce modulo ; all terms except the th vanish, so . The second factor is invertible modulo by [L2], hence for every , and step 3.1 gives every .
Steps 2.1 and 3.1 give existence, while step 4.1 gives uniqueness. The zero numerator yields the all-zero coefficients.
Repeated poles expand formally as
Statement
Let be a commutative ring, let , and let . In ,
The binomial coefficient acts by repeated addition in . The formula includes , , and and is purely formal.
Facts & Assumptions
Given: A commutative ring , an element , and an integer .
A formal series is invertible exactly when its constant coefficient is a unit, and its inverse is unique (A formal power series is a unit exactly when its constant coefficient is a unit).
The coefficient of a Cauchy product is (Coefficient extraction is -linear, separates formal series, shifts under multiplication by , and converts products to finite convolution).
Binomial coefficients count finite subsets and satisfy , , and for (The set of -element subsets and the binomial coefficient ).
The hockey-stick identity is (Pascal's rule , and the hockey-stick identity ).
Proof
For , put . By [L2], the constant coefficient of is and every positive coefficient is , so by [L1]; this is the formula because .
Assume the formula holds for one . Multiplying its right-hand side by the series from step 1.1, [L2] makes the coefficient of equal to .
Terms below vanish by [L3], so [L4] changes the sum in step 2.1 to ; therefore the product is the claimed series for exponent .
The base case and induction step prove the formula for every . At the coefficient is , and at all positive coefficients vanish, so the stated boundaries are included.
Over a named splitting field in characteristic zero, repeated characteristic roots give polynomial-times-exponential closed forms
Statement
Let be a field of characteristic zero, let satisfy an order- recurrence from zero, and let be a splitting field of its characteristic polynomial. If
in , with distinct roots , then there are unique polynomials with such that
Conversely, every sequence of this form satisfies the recurrence whose characteristic polynomial is the displayed product. Equality is in , and no identification with or is assumed.
Facts & Assumptions
Given: A characteristic-zero field , a sequence satisfying a recurrence from zero, a named splitting field , and the displayed factorisation of its characteristic polynomial.
A recurrence from zero has a proper rational generating function with its reciprocal denominator (A coefficient sequence is eventually linearly recurrent if and only if its formal generating function is rational).
The factorisation corresponds to (Reciprocal-root convention: corresponds to ).
A proper fraction with that split denominator has a unique expansion (A proper rational function with split denominator has a unique repeated-pole partial-fraction expansion).
Formally, (Repeated poles expand formally as ).
A splitting field is generated by the roots over the base field, and repeated factors record their multiplicities (Polynomials that split and splitting fields of a polynomial or a family of polynomials).
Characteristic zero means that no positive natural multiple of the field identity is zero (The characteristic of a ring: the least with when one exists, and otherwise).
The binomial coefficient satisfies when ( for ; hence , the quotient is a natural number, and ).
Proof
By [L1] the generating function is with or , and [L2] identifies with the split product in .
By [L6], every positive factorial is nonzero and hence invertible in . For put , the product being empty for , so . Each has degree and leading coefficient , and for every natural the identity from [L7] gives . The degrees are distinct, so triangular elimination makes a basis of the polynomials in of degree below .
Conversely, expand each in the binomial-polynomial basis from step 1.2. Then [L4] shows that the generating function of has denominator dividing ; summing gives a rational function with denominator dividing , so [L1] gives the recurrence with characteristic polynomial dividing the displayed product. Multiplying by any missing factors gives the displayed order- recurrence itself.
Apply [L3] and then [L4] to obtain .
Step 1.2 rewrites each coefficient as , so grouping the terms of step 2.2 with the same gives with , a polynomial in of degree below . Uniqueness follows from the uniqueness in [L3], the basis property in step 1.2, and coefficient extensionality.
Steps 3.1 and 2.1 prove both directions, including repeated roots and the case of one root. The condition in the recurrence excludes zero among the .
The row-shift companion matrix of a linear recurrence
Definition
Let be a commutative ring, let , and let
The row-shift companion matrix of this recurrence polynomial is the matrix (Finite rectangular matrices over a commutative ring, their entries, rows and columns) whose entries are
with all other entries zero. Thus
For a recurrence sequence , its state at time is the column vector . This convention matches the signs and order in Constant-coefficient linear recurrences, their starting index and their characteristic polynomial.
The companion matrix advances the recurrence state vector by one step
Statement
Let satisfy an order- recurrence from zero over a field, let be its row-shift companion matrix, and put . Then
for every .
Facts & Assumptions
Given: An order- recurrence sequence , its state vectors , and its companion matrix .
The companion matrix has shift rows and final row (The row-shift companion matrix of a linear recurrence).
Matrix multiplication is , and is the identity matrix (Entrywise ring-matrix operations, rectangular matrix products, identity matrices and transpose).
Matrix multiplication is associative and satisfies (Matrix arithmetic over a commutative ring is associative, unital and distributive, and transpose reverses products).
Proof
Multiplying by , the first rows return and the final row returns , so .
At , one has .
If , then step 1.1 and associativity give .
Induction proves for every , together with the one-step identity from step 1.1.
A recurrence companion matrix has the recurrence characteristic polynomial
Statement
Let be a field, let , and let be the row-shift companion matrix associated with
Then the matrix characteristic polynomial is exactly
Facts & Assumptions
Given: A positive integer , coefficients , and their row-shift companion matrix .
The row-shift companion matrix has superdiagonal entries and final row (The row-shift companion matrix of a linear recurrence).
For a field matrix , its characteristic polynomial is (For , the characteristic polynomial is when , with for the unique matrix).
A determinant may be expanded along any row or column as the sum of entries times their cofactors (Laplace expansion computes the determinant along every row and every column over a commutative ring).
Proof
For , one has and .
Assume the formula for size . In , the first column has only two nonzero entries: in row and in row .
Expanding that column by [L3], the cofactor of is the size- companion determinant by the induction hypothesis.
The minor of the entry is triangular with diagonal entries ; its determinant is , and the cofactor sign is also , so this contribution is .
Therefore , which is the claimed polynomial.
The base case and induction step prove the formula for every .
For an invertible matrix over a field, Cayley-Hamilton makes every matrix-power entry and trace sequence linearly recurrent
Statement
Let be a field, let , and let be invertible. Write
Then , and for every pair the sequence , as well as the sequence , satisfies from the order- recurrence
Facts & Assumptions
Given: A field , a positive size , and an invertible matrix with the displayed characteristic polynomial.
Every finite-dimensional endomorphism satisfies its characteristic polynomial: (Cayley-Hamilton: every finite-dimensional endomorphism satisfies its characteristic polynomial, ).
A matrix defines the coordinate endomorphism (For , the coordinate endomorphism , with and ).
The operator characteristic polynomial is the characteristic polynomial of any representing matrix (The basis-independent characteristic polynomial of an endomorphism of a finite-dimensional space, including in dimension zero).
The matrix characteristic polynomial is (For , the characteristic polynomial is when , with for the unique matrix).
The trace of a field matrix is the finite sum of its diagonal entries (The trace as the sum of the diagonal entries).
An invertible positive-sized matrix over a commutative ring has unit determinant (An invertible square matrix over a commutative ring has unit determinant).
Proof
Apply [L1] to the coordinate endomorphism [L2]. By [L3], its characteristic polynomial is , so the representing matrices satisfy .
By [L4], the constant coefficient is . The determinant is a unit by [L6], so in the field and the relation has order under the page's recurrence convention.
Multiplying the identity in step 1.1 by gives for every .
Extracting the entry from step 2.1 proves the displayed recurrence for every matrix-power entry; summing its diagonal entries and using [L5] proves the same recurrence for the trace sequence.
Steps 3.1 and 1.2 establish both families of order- recurrences from .
The Fibonacci sequence and Lucas sequence
Definition
The Fibonacci sequence and Lucas sequence are defined by
and, for every ,
Both are order- recurrences in the convention of Constant-coefficient linear recurrences, their starting index and their characteristic polynomial, with characteristic polynomial and reciprocal denominator . The distinct initial pairs distinguish the two sequences.
The trace of a square matrix over a commutative ring
Definition
Let be a commutative ring, let , and let (Finite rectangular matrices over a commutative ring, their entries, rows and columns). The trace of over is
For , this is the empty sum and equals . The subscript may be omitted when the coefficient ring is clear.
For matrices over a field, the commutative-ring trace agrees with the published matrix trace
Statement
Let be a field, let , and let . Then the commutative-ring trace equals the published field-matrix trace . This includes .
Facts & Assumptions
Given: A field , a size , and a matrix .
The commutative-ring trace is , with empty sum zero when (The trace of a square matrix over a commutative ring).
The published field trace is , with empty sum zero when (The trace as the sum of the diagonal entries).
Proof
By [L1], the commutative-ring trace of is the finite diagonal sum .
By [L2], the published field trace of is the same finite diagonal sum.
Comparing steps 1.1 and 1.2 proves equality; for both are the same empty sum .
Finite weighted directed multigraphs, weighted walks and their transfer matrices
Definition
Let be a commutative ring (Commutative ring). A finite weighted directed multigraph over consists of a finite vertex set , a finite edge set , source and target maps , and a weight map . Parallel edges and loops are allowed.
A walk of length from to is a sequence of edges with , , and whenever . Its weight is . At length zero there is one empty walk from to , of weight , and no empty walk between distinct vertices.
The transfer matrix or weighted adjacency matrix is (Finite rectangular matrices over a commutative ring, their entries, rows and columns) defined by
An empty edge sum is . Rows record sources and columns record targets.
The entry of is the total weight of length- walks from to
Statement
Let be the transfer matrix of a finite weighted directed multigraph over a commutative ring . For every and vertices ,
The sum is over all length- walks from to . Powers of a square matrix are the ones given by the recursion and , where is the number of vertices; the cited matrix laws supply the product and the identity but no power notation, so the recursion is fixed here. At , both sides are when and otherwise.
Facts & Assumptions
Given: A finite weighted directed multigraph over , its transfer matrix , vertices , and a length .
The transfer entry is the sum of the weights of all edges from to , and the unique empty walk at a vertex has weight (Finite weighted directed multigraphs, weighted walks and their transfer matrices).
Matrix multiplication is and the identity matrix has diagonal entries and off-diagonal entries (Entrywise ring-matrix operations, rectangular matrix products, identity matrices and transpose).
For matrices over a commutative ring of compatible shapes, and , and the entrywise additive and distributive laws hold, including all zero-sized shapes (Matrix arithmetic over a commutative ring is associative, unital and distributive, and transpose reverses products).
Proof
For , the recursion in the Statement gives , so , which is when and otherwise by [L2]; this agrees with the empty-walk convention in [L1], the empty walk being the unique walk of length from to and existing only when .
Assume the formula at length . The recursion gives , so by the product formula of [L2].
Substitute the induction formula and the edge-sum definition [L1] into step 1.2. The distributive laws of [L3] expand the result into one product for each length- walk from to followed by one edge from to .
Every length- walk has a unique penultimate vertex and last edge, so the expansion in step 2.1 is exactly the total weight of all length- walks from to .
The base case and induction step prove the formula for all .
Formally, over every commutative coefficient ring
Statement
Let be a commutative ring, let , and let . In the matrix ring ,
The matrix series is defined entrywise. The identity is formal, including , and uses no norm, convergence, or spectral-radius hypothesis.
Facts & Assumptions
Given: A commutative ring , a size , and a matrix .
Formal series are coefficient functions with Cauchy product (Formal power series over a commutative ring and the coefficient-extraction functional ).
Cauchy multiplication makes a commutative ring containing (Cauchy multiplication makes a commutative ring containing as the finitely supported subring).
Matrix products use finite row-column sums and is the identity matrix (Entrywise ring-matrix operations, rectangular matrix products, identity matrices and transpose).
Matrix multiplication is associative and distributive, including zero-sized shapes (Matrix arithmetic over a commutative ring is associative, unital and distributive, and transpose reverses products).
Proof
Define entrywise. The constant coefficient of is , and for every its coefficient is .
The same coefficient calculation on the other side gives the constant coefficient and positive coefficient for .
Coefficient extensionality makes both products equal to , so is the two-sided inverse of . For all matrices are the unique empty matrix and the same identity holds.
Transfer-matrix theorem: weighted-walk generating functions are cofactors of divided by
Statement
Let be a commutative ring, let a finite weighted directed multigraph have vertices and transfer matrix , and put . For vertices ,
The quotient is a rational formal power series over because has constant coefficient .
Facts & Assumptions
Given: A nonempty finite weighted directed multigraph over , its transfer matrix , vertices , and .
The entry of is the total weight of length- walks from to (The entry of is the total weight of length- walks from to ).
Formally, over every commutative coefficient ring (Formally, over every commutative coefficient ring).
The adjugate satisfies (Deleted-row-and-column minors, cofactors, the cofactor matrix and the adjugate over a commutative ring).
For a positive-sized square matrix, (For every positive-sized square matrix over a commutative ring, ).
If is a unit, then (If is a unit, then ).
The determinant is the finite Leibniz sum over permutations (For , the determinant over a commutative ring by the Leibniz formula, and for a real matrix).
A formal series is a unit exactly when its constant coefficient is a unit (A formal power series is a unit exactly when its constant coefficient is a unit).
Cauchy multiplication makes a commutative ring (Cauchy multiplication makes a commutative ring containing as the finitely supported subring).
Proof
By [L2], the entry of is , and [L1] identifies each coefficient with the total weight of the corresponding walks.
Setting gives . In the Leibniz sum [L6], only the identity permutation contributes to , so has constant coefficient and is a unit by [L7].
Apply [L4] and [L5] over the commutative ring from [L8] to obtain .
Taking the entry in step 2.1 and using [L3] gives .
Combining steps 1.1 and 3.1 proves the formula, with no analytic hypothesis. The assumption is exactly the positive-size domain of [L3] through [L6].
Statement
Let be a commutative ring, let , let , and put . Then, with the formal derivative,
The subscript names the coefficient ring the trace is taken over. Since has entries in , not in , the trace here is the one belonging to the commutative ring ; the defining formula is the same.
Facts & Assumptions
Given: A commutative ring , a positive size , a matrix , and .
The ring trace is the finite sum of the diagonal entries (The trace of a square matrix over a commutative ring).
The adjugate is the transpose of the cofactor matrix, so (Deleted-row-and-column minors, cofactors, the cofactor matrix and the adjugate over a commutative ring).
The determinant is the Leibniz sum (For , the determinant over a commutative ring by the Leibniz formula, and for a real matrix).
The formal derivative is coefficientwise and sends to and constants to (The formal derivative ).
Formal differentiation is linear and satisfies the product rule (Formal differentiation is linear and satisfies product, power, quotient, chain, and coefficient-recovery laws).
Proof
Differentiate the finite Leibniz sum [L3]. By [L5], each product contributes one term for each selected matrix entry, and grouping all terms that differentiate leaves its cofactor .
By [L1] and matrix multiplication, . Using [L2] and renaming the finite indices gives .
Thus . Since by [L4], this is .
Comparing steps 2.1 and 1.2 gives the displayed derivative identity. Positive size supplies every cofactor used in [L2].
Closed walks have trace and logarithmic-derivative generating functions
Statement
Let be a commutative ring, let , let be a transfer matrix, and put . Then
and
The coefficient is the total weight of all closed walks of length . Each trace subscript names the commutative ring its argument's entries lie in: , while has entries in , so that numerator is . The defining formula is the same in each case. The second expression is a formal logarithmic derivative; no logarithm or convergence is required.
Facts & Assumptions
Given: A positive-sized transfer matrix over a commutative ring , , and .
The transfer-matrix formula identifies each entry of with the corresponding weighted-walk series and with an adjugate entry divided by (Transfer-matrix theorem: weighted-walk generating functions are cofactors of divided by ).
The ring trace is the finite sum of diagonal entries, including the empty-sum convention (The trace of a square matrix over a commutative ring).
Proof
Sum the diagonal instances of [L1]. By [L3], the left side is and the numerator on the right is , proving the first identity and the closed-walk interpretation.
From [L1], . Multiplying by , taking the trace over where has its entries, and then multiplying by gives , the right-hand coefficients being the traces over of the matrices .
Dividing [L2] by the unit gives . Combine this with step 1.2 to obtain the second identity.
Both calculations take place in , so they require no topology or spectral-radius assumption.
Let be a field, , and . If in , then the transfer-matrix trace series is
Statement
Let be a field, let , and let . Suppose that its characteristic polynomial is displayed as a product of linear factors in the base field,
where roots are repeated according to algebraic multiplicity. Then
and, formally,
When is a transfer matrix, this is the eigenvalue form of its closed-walk trace series.
Facts & Assumptions
Given: A field , a positive size , a matrix , and the displayed split factorisation of in .
For a transfer matrix, the closed-walk series is (Closed walks have trace and logarithmic-derivative generating functions).
The matrix defines the coordinate endomorphism (For , the coordinate endomorphism , with and ).
The characteristic polynomial of an endomorphism equals that of any representing matrix (The basis-independent characteristic polynomial of an endomorphism of a finite-dimensional space, including in dimension zero).
The trace of an endomorphism equals the trace of any representing matrix (The basis-independent trace of an endomorphism of a finite-dimensional vector space).
If , then for every polynomial (If in , then for every : the eigenvalues of are , counted with algebraic multiplicity).
When the characteristic polynomial splits, the trace is the sum of its roots with algebraic multiplicity (If in , then : trace is the sum of the eigenvalues counted with algebraic multiplicity).
The case of the repeated-pole formula is (Repeated poles expand formally as ).
Over a field, the commutative-ring matrix trace equals the published matrix trace (For matrices over a field, the commutative-ring trace agrees with the published matrix trace).
Proof
Let be the coordinate endomorphism from [L2]. By [L3], the given factorisation is also .
Apply [L5] to . The roots of are with the displayed multiplicities, so [L6] gives .
By [L4] and [L8], the left side in step 2.1 is in either trace convention. This proves the coefficient formula, including .
Multiply the coefficient formula by , sum formally over , and apply [L7] to each of the finitely many roots; this yields the displayed rational-series identity.
If is a transfer matrix, [L1] identifies the left side of step 4.1 with its closed-walk trace series. The split factorisation was assumed at the outset and is not inferred from algebraic closure or diagonalisation.
Finite words, contiguous factors, avoidance and proper-prefix states
Definition
Let be a finite set, called an alphabet. A word of length over is a function from the natural number (The natural numbers (von Neumann)) to , written . The unique word of length zero is the empty word . Concatenation of words and is denoted by .
A word is a contiguous factor of if for some . It is a prefix if , a suffix if , and a proper prefix if it is a prefix other than the whole word.
For a set of words, a word avoids if none of its contiguous factors belongs to . Its set of proper-prefix states is
If is nonempty and every word in is nonempty, then . If is finite, then is finite.
The longest-suffix prefix automaton for a finite set of forbidden factors
Definition
Let be a finite alphabet and let be a finite nonempty set of nonempty words over . With as in Finite words, contiguous factors, avoidance and proper-prefix states, the prefix automaton for has state set , initial state , and the following transitions.
For and , reject the letter if the concatenation contains a factor in . Otherwise define to be the longest suffix of that belongs to , and put an edge labelled from to . This state exists because , and it is unique because suffixes of distinct lengths are distinct.
For enumeration, give every edge weight over . Different letters that induce the same transition remain parallel edges, so the associated transfer-matrix entry is the number of such letters.
Words over a finite alphabet avoiding finitely many nonempty factors have a rational length generating function
Statement
Let be a finite alphabet and let be a finite set of nonempty words over . If is the number of length- words over that avoid every factor in , then
is a rational formal power series over .
Facts & Assumptions
Given: A finite alphabet and a finite set of nonempty words.
A rational formal series has a polynomial numerator and a polynomial denominator with unit constant coefficient (Rational formal power series, proper presentations and reduced denominators).
For nonempty , the prefix automaton retains the longest suffix that is a proper prefix of a forbidden word and rejects a transition that creates a forbidden factor (The longest-suffix prefix automaton for a finite set of forbidden factors).
For a finite weighted digraph with transfer matrix , the total weight of length- walks from to is (The entry of is the total weight of length- walks from to ).
Every fixed-entry walk generating series of a nonempty finite weighted digraph is a cofactor of divided by , hence rational (Transfer-matrix theorem: weighted-walk generating functions are cofactors of divided by ).
Finite sums of rational formal power series are rational (Rational formal power series are closed under sums and Cauchy products).
Proof
If and , then and coefficientwise, so [L1] makes rational.
Suppose now that is nonempty. After a word avoiding has been read, the automaton state is the longest suffix of belonging to : this holds initially at , and repeated application of [L2] preserves it as each accepted letter is appended.
Let avoid , let be its state from step 1.2, and let . If contains a forbidden factor , that factor ends at the appended letter, so with a suffix of ; and avoids and is a proper prefix of , so . Since is the longest suffix of in , the word is a suffix of , so is a factor of and [L2] rejects . Conversely, is a suffix of , so any factor of in is a factor of . Thus [L2] rejects exactly the extensions that cease to avoid .
Steps 1.2 and 2.1 give a weight-preserving bijection between length- words avoiding and length- walks in the prefix automaton from to any state in .
By [L3], . Each series is rational by [L4], and their finite sum is rational by [L5]. Together with the empty- case in step 1.1, this proves the result.
Binary words avoiding any fixed nonempty factor have a rational length generating function
Statement
Fix a nonempty binary word . If is the number of words in that do not contain as a contiguous factor, then is a rational formal power series over .
Facts & Assumptions
Given: A nonempty word over the finite alphabet .
Words over a finite alphabet that avoid a finite set of nonempty factors have a rational length generating function (Words over a finite alphabet avoiding finitely many nonempty factors have a rational length generating function).
Proof
The alphabet is finite, and is a finite set of nonempty words.
Apply [L1] using step 1.1. Its conclusion is the asserted rationality.
5 · Examples, counterexamples and false statements
None yet.
Sources
Standard references
Recommended treatments; not extraction sources.
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Sections 4.1-4.2
- B. E. Sagan, Combinatorics: The Art of Counting, Section 3.7
- M. Waldschmidt, Linear Recurrence Sequences VI, slides 5-18
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Section 4.1
- B. E. Sagan, Combinatorics: The Art of Counting, Sections 3.6-3.7
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Theorem 4.1.1
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Theorem 4.1.1 and Proposition 4.2.2
- B. E. Sagan, Combinatorics: The Art of Counting, Theorem 3.7.1
- M. Waldschmidt, Linear Recurrence Sequences VI, slides 5-6
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Corollary 4.2.1
- M. Waldschmidt, Linear Recurrence Sequences VI, Order of a linear recurrence sequence
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Proposition 4.2.2
- M. Waldschmidt, Linear Recurrence Sequences VI, ultimately recurrent sequences
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Proposition 4.2.3 and Corollary 4.2.4
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Section 4.2
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Proposition 4.2.5
- M. Waldschmidt, Linear Recurrence Sequences VI, reciprocal characteristic polynomial
- M. Waldschmidt, Linear Recurrence Sequences VI, slides 19-28
- M. Waldschmidt, Linear Recurrence Sequences VI, slides 16-18
- M. Waldschmidt, Linear Recurrence Sequences VI, slide 17
- H. Pinkham, Linear Algebra, Chapter 10
- M. Waldschmidt, Linear Recurrence Sequences VI, slide 18
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Examples 4.1.2 and 4.7.16
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Section 4.7
- S. Axler, Linear Algebra Done Right, 4th ed., Definition 8.47
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Section 4.7.1
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Theorem 4.7.1
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Theorem 4.7.2
- J. Gallier and J. Quaintance, Linear Algebra for Computer Vision, Robotics, and Machine Learning, Section 6.4
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Corollary 4.7.3
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Corollaries 4.7.3-4.7.4
- H. Pinkham, Linear Algebra, Section 12.3
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Example 4.7.7 and Proposition 4.7.8
- R. P. Stanley, Enumerative Combinatorics, vol. 1, 2nd ed., Proposition 4.7.8