Polynomial Modular Inverses
Inverting a polynomial modulo another using the extended Euclidean algorithm, and the finite field application.
Engineering articles and subject areas in the KEVOS knowledge library. 1397 pages.
Inverting a polynomial modulo another using the extended Euclidean algorithm, and the finite field application.
Schoolbook, Karatsuba and evaluation-interpolation methods for polynomial multiplication, and where the crossovers lie.
The structure of F[X]/(f), its basis, arithmetic, and the decomposition when f is reducible.
Dense and sparse polynomial representations, coefficient domains, and the normalisation invariants every implementation must maintain.
Evaluating a polynomial at a square matrix: matrix powers, why the constant term becomes a multiple of the identity, and why the factored form gives the same answer.
The distinction between a formal polynomial and the function it induces, and why the two differ over finite rings.
A linear system has no solution, exactly one, or infinitely many — never two. The trichotomy, its geometric reading, its proof, and what each case means in practice.
The pre-image of a vector under a linear transformation: when it is empty, why a non-empty pre-image is a translate of the kernel, and how it partitions the domain.
What a primality certificate is, why verification is cheaper than production, and what a certificate does and does not guarantee.
Why proving compositeness is easy, proving primality is harder, and factoring is harder still — and what this asymmetry means in practice.
How rational primes split, remain inert or ramify in a quadratic field, decided entirely by the Kronecker symbol.
Decomposing a prime that does not divide the index, by factoring the defining polynomial modulo that prime.
How rational primes factor in the maximal order, ramification indices and residue degrees, and the degree relation that constrains them.
Dirichlet's theorem on primes in arithmetic progressions, equidistribution across residue classes, and computational consequences.
The model of randomised computation, Las Vegas and Monte Carlo algorithms, and what a probabilistic guarantee means.
The standard proof patterns of linear algebra: definitions as two-way implications, set equality, equivalences, contrapositives, uniqueness, chains of identities and TFAE cycles.
Transpose invariance, multiplicativity over matrix products, and the equivalence between a zero determinant and singularity, with the consequences for inverses and rank.
Eigenvalue theorems: independence for distinct eigenvalues, zero eigenvalues and singularity, and the spectra of powers, polynomials, inverses and transposes.
Algebraic rules for matrix inverses: uniqueness, the reversal rule for products, inverse of an inverse, inverse of a transpose and of a scalar multiple.
Associativity, distributivity, the identity and zero matrices, scalar rules, and how transposition, conjugation and the inner product interact with matrix products.
The kernel of a linear transformation is isomorphic to the null space of its matrix representation, and the range to the column space; rank and nullity transfer.
Similarity is an equivalence relation preserving the characteristic polynomial, eigenvalues, trace, determinant and rank; equal spectra do not imply similarity.
Theorems derived from the vector space axioms alone: uniqueness of the zero vector and inverses, the zero-scalar rules and the three cancellation laws.
Standard tables of number fields, elliptic curves, class numbers and factorisations, and how to use them responsibly.
Discriminants and integral bases of quadratic fields, given by closed formulas with no computation required.
Quadratic residues modulo a prime, the exact split into residues and non-residues, and the group-theoretic reason for it.
Choosing the factor base for the quadratic sieve, the quadratic residue criterion, and the multiplier.
Constructing the quotient group from a subgroup, well-definedness of the induced operation, and the standard examples.
Computing the p-radical of an order as a kernel, and the ring of multipliers that enlarges the order.
Random variables, their distributions, joint behaviour and independence.
The range of a linear transformation: definition, why it is a subspace of the codomain, its identity with the column space, and the surjectivity criterion.
Rank and nullity of a linear transformation: dimensions of the range and kernel, the rank-nullity theorem, and dimension tests for injectivity and surjectivity.
Rank is the dimension of the column space, nullity the dimension of the null space; both come from reduced row-echelon form and sum to the column count.
A square matrix is nonsingular exactly when its rank equals its size and its nullity is zero, with the consolidated list of nonsingular matrix equivalences.
A matrix and its transpose always have the same rank, so row rank equals column rank, while their nullities generally differ by the difference in shape.
Recovering a rational function from a residue modulo a polynomial, with degree bounds replacing size bounds.
Using rational function reconstruction inside computer algebra for exact computation over function fields.
Recovering a rational number from its residue modulo n, the uniqueness conditions, and the role of the extended Euclidean algorithm.
Applying rational reconstruction inside computer algebra systems for exact linear solving, interpolation and gcd computation.
Recovering the structure and explicit generators of a finite abelian group from a matrix of relations among a generating set.
How linear combination, span, relations of linear dependence and linear independence transfer unchanged from column vectors to any abstract vector space.
Definition, uniqueness and engineering use of reduced row-echelon form (RREF): leading ones, pivot columns, zero rows and the canonical form of a matrix under row operations.
Amplifying the success probability of a randomised algorithm by independent repetition, for one-sided and two-sided error.
Reduction of indefinite binary forms, the cycle of reduced forms in each class, and how the cycle encodes the regulator.
Reducing a positive definite binary quadratic form to the unique reduced form in its class, and the resulting class number algorithm.
Extracting fundamental units and the regulator from the kernel of the relation matrix, and confirming the unit system is fundamental.
Generating relations among ideal classes, assembling the sparse matrix, and knowing when enough relations have been collected.
Positional representation of multiprecision integers, base selection, sign handling and normalisation invariants.