Span of a Set of Vectors
The span of a finite set of column vectors is the set of all their linear combinations; membership testing reduces to deciding consistency of a linear system.
Engineering Mathematics articles in the KEVOS Engineering library. 1073 pages.
The span of a finite set of column vectors is the set of all their linear combinations; membership testing reduces to deciding consistency of a linear system.
How to construct and verify a spanning set for a subspace of polynomials or matrices: the set equality argument, the consistency test and a worked construction.
Construct n-r vectors directly from the reduced row-echelon form whose span is exactly the null space of a matrix, using the pattern of ones, zeros and negated entries.
The modular method for exact computation: bounding the result, computing modulo several primes, and reconstructing.
Applying evaluation homomorphisms and modular reduction to control coefficient and degree growth in polynomial computation.
Decomposing a finite-dimensional commutative algebra over a finite field into its simple components, generalising polynomial factorisation.
Extracting square roots modulo a prime: the easy congruence classes, the general Shanks-Tonelli algorithm, and lifting to prime powers.
Removing repeated factors using gcds with the derivative, and the characteristic p complication.
Separating repeated factors using the derivative, and the modification required in positive characteristic.
Statistical distance between distributions, its properties, and its use in proving that a sampler is close to uniform.
Strict versus expected polynomial time, and how a Las Vegas algorithm is converted into a bounded-time one.
Isomorphic vector spaces, isomorphisms as structure-preserving invertible linear maps, why isomorphic spaces share dimension, and how to transfer computations.
The overall design of the Jacobi sum primality test, its two phases, and where its complexity comes from.
The structure of the multiplicative group of integers modulo n, its decomposition by CRT, and computing element orders.
Sub-exponential class group and regulator computation for quadratic fields by relation collection over a factor base.
Index calculus for discrete logarithms in Z_p*, its two phases, and the precomputation asymmetry it creates.
Factoring by congruences of squares, the relation collection and linear algebra phases, and the resulting subexponential cost.
The subfield lattice of a finite field, its correspondence with divisors, and the uniqueness of each subfield.
Subgroups, the subgroup test, generated subgroups, and the subgroup lattice of a finite group.
Submodules, quotient modules, and the correspondence between submodules of a quotient and those of the original.
Subrings, the subring test, and the distinction between subrings and ideals.
Null space, column space, row space, left null space and span are all subspaces. The theorems, their one-line proofs, and how to recognise a subspace on sight.
What a subspace of a vector space is, why a subset inherits six axioms free of charge, and how closure, the zero vector and additive inverses are verified.
Surjective (onto) linear transformations: the defining condition, proof by carrying a symbolic right-hand side, and disproof with one unattainable vector.
How images of a spanning set span the range, why the images of a basis decide surjectivity, and why domain dimension cannot fall below codomain dimension.
Every coefficient matrix induces a linear transformation: kernels are null spaces, ranges are column spaces, and solution sets are pre-images of a vector.
The formal definition of a system of linear equations, double-subscript coefficient notation, what counts as a solution, and why the solution set is the real object of study.
Why Galois group implementations need a curated test set, what a good set covers, and how to build one.
Testing irreducibility over a finite field and constructing irreducible polynomials of prescribed degree.
Deciding quadratic residuosity modulo a prime, and why the problem is easy in this case.
Quadratic residuosity modulo prime powers and composites, the reduction by Chinese remaindering, and where the hardness enters.
The three-condition subspace test: non-empty, closed under addition, closed under scalar multiplication. Proof, worked verifications and the standard counterexamples.
The AKS algorithm in full, its correctness argument, complexity, and why it is not used in practice.
The endomorphism algebra of a vector space, minimal and characteristic polynomials, and the module view of a linear operator.
Shanks' baby step giant step algorithm, its square-root running time, and the time-memory trade-off it embodies.
The Baillie-PSW test combining a strong base-two test with a strong Lucas test, and its status as the practical standard.
Berlekamp's linear algebra approach to factoring over a finite field, the Berlekamp subalgebra, and when it outperforms the GCD pipeline.
The birthday problem, the square-root threshold for collisions, and its algorithmic consequences.
Decomposing any prime, including those dividing the index, by splitting the algebra of the order modulo that prime.
The change-of-basis matrix converts coordinates from one basis to another, is the representation of the identity transformation, and is always non-singular.
Computing the characteristic polynomial via Hessenberg reduction, and its role in producing minimal polynomials of algebraic numbers.
The Chinese remainder theorem as a ring isomorphism, its constructive proof, and its role in decomposing modular computation.
Representing a field element by its images under all embeddings, the analytic information this exposes, and the precision it demands.
CFRAC: generating small quadratic residues from the continued fraction expansion, and the congruence-of-squares framework it established.
The coordinatization principle: questions about linear combinations, independence and spanning in an abstract vector space can be answered in complex n-space.
A cheap modular test deciding whether an order is maximal at a given prime, without computing the maximal order.
The recursive definition of the determinant via submatrices, the 2x2 formula ad - bc, notation and cost, and why a single scalar decides whether a square matrix is singular.
Diffie-Hellman key agreement, the assumptions it rests on, and the authentication gap that makes it vulnerable alone.