Dec 31, 2023—Mar 15, 2024

Courses

  1. Introduction: Sets, subsets, permutations, functions, partitions. Indistinguishable elements, multisets, binary algebra of subsets. Rules of sum and product, convolutions, counting pairs. Binomial and multinomial coefficients. Stirling numbers of second kind, definition and a recurrenat formula.
  2. Graphs: General notions and examples. Isomorphism. Connectivity. Euler graphs. Trees. Cayley’s theorem. Bipartite graphs. Konig’s theorem, P. Hall’s theorem.
  3. The inclusion-exclusion method: The complete inclusion-exclusion theorem. An explicit formula for the Stirling numbers. Counting permutations under constraints, rook polynomials.
  4. Generating functions: General notion, combinatorial meaning of operations on generating functions. Theory of recurrence equations with constant coefficients: the general solution of the homogeneous equation, general and special cases of nonhomogeneity. Catalan numbers. Partitions of numbers, Ferrers diagrams. Exponential generating functions, counting words, set partitions, etc.

The goal of the workshop is to accompany first year mathematics majors, and to improve their skills in writing formal proofs. In the course of the workshop, the students will work in small groups on writing proofs, with an emphasis on topics related to the foundational first year courses.

Axioms of the reals. Sequences: limits, monotone sequences, the Bolzano-Weierstrass theorem, Cauchy’s criterion, the number e. Limits of functions. Continuous functions: equivalent definitions of continuity, properties of the elementary functions, the exponential function, the Intermediate Value Theorem, existence of extrema in closed and bounded sets, uniform continuity and Cantor’s theorem. Introduction to derivatives: the definition of the derivative and differentiation rules, the derivative of an inverse function, derivatives of elementary functions, Fermat’s theorem, Rolle’s theorem and Lagrange’s Mean Value Theorem.

  • Complex numbers. Fields: definition and properties. Examples.
  • Systems of Linear equations. Gauss elimination process.
  • Matrices and operations on them. Invertible matrices.
  • Determinant: definition and properties. Adjoint matrix. Cramer rule.
  • Vector spaces and subspaces. Linear spanning and linear dependence. Basis and dimension. Coordinates with respect to a given basis.
  • Linear transformations. Kernel and Image. Isomorphism of vector spaces. Matrix of a linear transformation with respect to given bases.
  • The space of linear transformations between two vector spaces. Dual space
  • Groups as symmetries. Examples: cyclic, dihedral, symmetric and matrix groups.
  • Homomorphism. Subgroups and normal subgroups. Quotient groups. Lagrange’s theorem. The isomorphism theorems. Direct products of groups.
  • Actions of groups on sets. Cayley’s theorem.
  • Group automorphisms.
  • Sylow’s theorems. Application: classification of groups of small order.
  • Composition series and Jordan–Hoelder theorem. Solvable groups.
  • Classification of finite abelian groups, finitely-generated abelian groups.
  • Symmetric group and alternating group. The alternating group is simple.
  • Rings, maximal and prime ideals, integral domain, quotient ring. Homomorphism theorems.
  • Multilinear algebra: Quotient spaces. Tensor products of vector spaces. Action of $S_n$ on tensor powers. Exterior and symmetric algebras. Multilinear forms and determinant.
  • Optional topics: group of symmetries of platonic solids, free groups, semidirect products, representation theory of finite groups.

Algebras and sigma-algebras of subsets, the extension theorem and construction of Lebesgue’s measure on the line, general measure spaces, measurable functions and their distribution functions, integration theory, convergence theorems (Egorov’s, relations between convergence in measure and a.e. convergence), the spaces $L_1$ and $L_2$ and their completeness, signed measures, the Radon-Nikodym theorem, measures in product spaces and Fubini’s theorem.

  1. Introduction and historical background: the Hilbert-Witehead program, paradoxes in set theory, independence theorems.
  2. First order logic: formulas, structures truth value of a formula in a model, calculus with and without equality.
  3. Goedel’s Completeness theorem: deduction systems for propositional logic, the completeness theorem for propositional logic and for first order logic. The model existence theorem and the compactness theorem.Applications and corollaries (Upward Lowenheim-Skolem).
  4. Goedel’s incompleteness theorem: codes, Goedel’s fixed point theorem, Tarski’s theorem on the non-definability of truth.
  5. Corollaries of incompleteness, as time allows.

Graphs and sub-graphs, trees, connectivity, Euler tours, Hamilton cycles, matching, vertex and edge colorings, planar graphs, introduction to Ramsey theory, directed graphs, probabilistic methods and linear algebra tools in Graph Theory.

An introduction to the basic notions of probability theory:

sample spaces limits of events conditional probability independent events sigma algebras, continuous spaces, Lebesgue measure random variables and distributions independence expectation variance and covariance convergence of random variables: almost-sure, in Lp, in probability law of large numbers convergence in law central limit theorem

  1. Rings and ideals (revisited and expanded).
  2. Modules, exact sequences, tensor products.
  3. Noetherian rings and modules over them.
  4. Hilbert’s basis theorem.
  5. Finitely generated modules over PID.
  6. Hilbert’s Nullstellensatz.
  7. Affine varieties.
  8. Prime ideals and localization. Primary decomposition.
  9. Discrete valuation rings.
  1. The Fourier transform: convolutions, the inversion formula, Plancherel’s theorem, Hermite functions, tempered distributions. The Poisson summation formula. The Fourier transform in R^n.
  2. The Laplace transform. Connections with convolutions and the Fourier transform. Laguerre polynomials. Applications to ODE’s. Uniqueness, Lerch’s theorem.
  3. Classification of the second order PDE: elliptic, hyperbolic and parabolic equations, examples of Laplace, Wave and Heat equations.
  4. Elliptic equations: Laplace and Poisson equations, Dirichlet and Neumann boundary value problems, Poisson kernel, Green’s functions, properties of harmonic functions, Maximum principle
  5. Analytical methods for resolving partial differential equations: Sturm-Liouville problem and the method of separation of variables for bounded domains, applications for Laplace, Wave and Heat equations including non-homogenous problems. Applications of Fourier and Laplace transforms for resolving problems in unbounded domains.

Bibliography

  1. Stein E. and Shakarchi R., Fourier analysis, Princeton University Press, 2003.
  2. Korner T.W., Fourier analysis, Cambridge University Press, 1988.
  3. Katznelson Y., An Introduction to Harmonic Analysis, Dover publications. 4. John, Partial differential equations, Reprint of the fourth edition. Applied Mathematical Sciences, 1. Springer-Verlag, New York, 1991.
  4. Evans Lawrence C. Partial Differential Equations, Second Edition.
  5. Gilbarg D.; Trudinger N. S. Elliptic partial differential equations of second order, Reprint of the 1998 edition. Classics in Mathematics. Springer-Ver lag, Berlin, 2001.
  6. Zauderer E. Partial differential equations of applied mathematics, Second edition. Pure and Applied Mathematics (New York). A Wiley-Interscience Publication. John Wiley & Sons, Inc., New York, 1989. xvi+891 pp. ISBN: 0-471-61298-7.

Metric and normed spaces. Equivalence of norms in finite dimensional spaces, the Heine-Borel theorem. Convergence of sequences and series of functions: pointwise, uniform, in other norms. Term-by-term differentiation and integration of series of functions, application to power series. Completeness: completeness of the space of continuous functions on a closed interval and a compact metric space. The Weierstrass $M$-test. The Baire category theorem and applications, bounded linear functionals and the Banach-Steinhaus theorem. Compactness in function spaces and the Arzela-Ascoli theorem. Introduction to Fourier series: Cesaro means, convolutions and Fejer’s theorem. The Weierstrass approximation theorem. $L^2$ convergence. Pointwise convergence, the Dirichlet kernel and Dini’s criterion.

Open, closed and compact sets in Euclidean space. Matrix norms and equivalence of norms. Limits and continuity in several variables. Curves and path connectedness. Partial and directional derivatives, the gradient and differentiability. The implicit, open and inverse function theorems. Largange multipliers. Optimization: the Hessian matrix and critical points. Multivariable Riemann integration: Fubini’s theorem and the change of variables formula.

  • Topological manifolds. The fundamental group and covering spaces. Applications.
  • Singular homology and applications.
  • Smooth manifolds. Differential forms and Stokes’ theorem, definition of de-Rham cohomology.
  • Additional topics as time permits.
  1. Expander graphs and their applications — Equivalent definitions, Mixing Lemma, Alon–Boppana Theorem, Applications, Constructions
  2. Kazhdan Property (T) - group representations (short intro.), Cayley and Schrier graphs, Property (T) — definition and properties, examples, construction of expander graphs via property (T)
  3. Additional topics (as time allows)

Teaching method: ZOOM lectures.

Active web page: https://sites.google.com/view/amyekut-math/home/teaching/comm-alg-2023-24-a

Prerequisite: Introduction to Commutative Algebra

Ignore file “syllabus ver 1” and the entry in the BGU course catalog. See file “Syllabus ver 2”

Topics: 1. Recalling basic commutative algebra. 2. More basic commutative algebra. 3. Limits in algebra. 4. Adic completion. 5. Completion of noetherian rings. 6. Complete local rings. 7. Differential commutative algebra. 8. Étale ring homomorphisms. 9. Smooth ring homomorphisms.

Banach spaces and Hilbert spaces. Basic properties of Hilbert spaces. Topological vector spaces. Banach-Steinhaus theorem; open mapping theorem and closed graph theorem. Hahn-Banach theorem. Duality. Measures on locally compact spaces; the dual of $C(X)$. Weak and weak-$*$ topologies; Banach-Alaoglu theorem. Convexity and the Krein-Milman theorem. The Stone-Weierstrass theorem. Compact operators on Hilbert space. Introduction to Banach algebras and Gelfand theory. Additional topics as time permits.

Notes

  • Courses marked with (*) are required for admission to the M.Sc. program in Mathematics.
  • The M.Sc. degree requires the successful completion of at least 2 courses marked (#). See the graduate program for details
  • The graduate courses are open to strong undergraduate students who have a grade average of 85 or above and who have obtained permission from the instructors and the head of the teaching committee.
  • Please see the detailed undergraduate and graduate programs for the for details on the requirments and possibilities for complete the degree.