Computational Number Theory and Algebra

Algebra plays an important role in both finding algorithms, and understanding the limitations of computation. This course will focus on some of the fundamental algebraic concepts that arise in computation, and the algebraic algorithms that have applications in real life. The course will cover the problems of fast integer (or polynomial) multiplication (or factoring), fast matrix multiplication, primality testing, computing discrete logarithm, error-correcting codes, lattice- based cryptography, etc. The course intends to introduce both basic concepts and practical applications.

INTENDED AUDIENCE :Computer Science & Engineering, Mathematics, Electronics, Physics, & similar disciplines.
PREREQUISITES :Preferable (but not necessary)-- Theory of Computation, Algorithms, Algebra
INDUSTRIES SUPPORT :Cryptography, Coding theory, Computer Algebra, Symbolic Computing Software, Cyber Security, Learning Software

COURSE LAYOUT

Week 1:Outline. Notation. Background.Week 2:GCD. Chinese remaindering. Fast polynomial multiplication.Week 3:Fast integer multiplication. Fast integer division. Fast gcd.Week 4:Fast matrix multiplication. Tensor rank.
Week 5:Factorization over finite fields.Week 6:Berlekamp, Cantor-Zassenhaus factoring algorithms.Week 7:Reed-Solomon code. List decoding. Bivariate polynomial factoring.Week 8:Kaltofen's blackbox multivariate factoring.
Week 9:Integral polynomial factoring. LLL algo. Shortest vector in lattice.Week 10:Lattice-based cryptography.Week 11:Primality testing. RSA cryptosystem. Diffie-Hellman. Discrete Log.Week 12:Integer factoring. Pollard, Fermat, Morrison-Brillhart, Quadratic sieve methods.