Qualifying Exam Dates & system

qualifying exam dates: Winter 2022 (Subject to Change)

Last day to sign up for qualifying exams is: March 1, 2022

Undergraduate students can register for the Basic exam by emailing Brenda Buenrostro at brenda@math.ucla.edu.

Date ExamTime
Monday, March 21, 2022 Basic9 AM – 1 PM (Online)
Tuesday, March 22, 2022 Numerical Analysis9 AM – 1 PM (Online)
  Algebra2 PM – 6 PM (Online)
Wednesday, March 23, 2022 Geometry/Topology9 AM – 1 PM (Online)
  Applied Differential Equations2 PM – 6 PM (Online)
Thursday, March 24, 2022 Analysis9 AM – 1 PM (Online)
  Optimization/Numerical Linear Algebra2 PM – 6 PM (Online)

Qualifying exams are four hour written exams, and are given twice a year, in September right before the start of the Fall quarter, and in March right before the start of the Spring quarter. The Logic qualifying exam is generally offered only in the Fall. Students may petition to have a Spring exam in special circumstances, for example when this is necessary for meeting Satisfactory Progress deadlines. Petitions should be made to the GVC by the end of January.


The following is the syllabus for the Basic Examination (for M.A. and Ph.D.)

Fundamentals of analysis:

  1. One-variable calculus foundations: completeness of the real numbers, sequences, series, limits, continuity, including epsilon-delta arguments, maxima and minima, uniform continuity, definition of the derivative, the mean value theorem, Taylor expansion with remainder, Riemann integral, mean value theorem for integrals, fundamental theorem of calculus, sequences and series of functions, uniform convergence and integration, differentiation under the integral sign, contraction maps, fixed point theory, with applications to Newton’s method and solutions of non-linear equations, numerical integration with error estimation.
  2. Metric space topology and analysis, primarily in R^n: open and closed sets, completeness, convergence of sequences of numbers and functions, closure, compactness, connectedness, uniform continuity, equicontinuity, countability and uncountability (e.g. of the reals), spaces of functions. Basic arguments and theorems of undergraduate analysis using these concepts, including the Bolzano-Weierstrass, the Stone-Weierstrass, and the Arzela-Ascoli theorems.
  3. Multivariable calculus: definition of differentiability in several variables (approximating linear transformation), partial derivatives, chain rule, Taylor expansion in several variables, inverse and implicit function theorems, equality of mixed partials, multivariable integration, change of variables formula.
Linear algebra:

Vector spaces, subspaces, basis and dimension, linear transformations and matrices, rank and nullity, change of basis and similarity of matrices, inner product spaces, orthogonality and, orthonormality, Gram-Schmidt process, adjoints of linear transformations and dual spaces, quadratic forms and symmetric matrices, orthogonal and unitary matrices, diagonalization of hermitian and symmetric matrices, eigenvectors and eigenvalues, and their computation, exponentiation of matrices and application to differential equations, least squares problems, trace, determinant, canonical forms. Systems of linear equations: solvability criteria, Gaussian elimination, row-reduced form, LU decomposition.

Suggested References:

For Analysis and Multivariate Calculus:

1.  T. Tao, Analysis I and II
2. T. Gamelin and R. Greene, Introduction to Topology, Chapter 1
3. C. H. Edwards, Advanced Calculus of Several Variables, Chapters I-III

Each of the following texts also covers much of the analytic material on the syllabus of the Basic Exam:

4. T. Apostol, Mathematical Analysis
5.  M.  Rosenlicht, Introduction to Analysis
6.  W.  Rudin, Principles of Mathematical Analysis

For Linear Algebra:

1.      Linear Algebra and Lecture Notes, by Peter Petersen (available at http://www.math.ucla.edu/~petersen/)
2.      Serge Lang, Linear Algebra
3.      K. Hoffman, Linear Algebra
4.      M. Marcus and H. Minc, Introduction to Linear Algebra
5.       Schaum’s Outline of 3000 Solved Problems of Linear Algebra (a good source of exercises).

The following texts may be useful for Basic Exam preparation for students with an interest or background in Applied Mathematics:

1.      D. Serre, Matrices: Theory and Applications
2.      A. Ralston and P. Rabinowitz, “A First Course in Numerical Analysis”, 2nd edition, Chapters 9 & 10
3.      K. Atkinson, “An Introduction to Numerical Analysis”, 2nd edition,Chapters 7, 8 & 9.
4.      M. Marcus and H. Minc, Introduction to Linear Algebra
5.      Schaum’s Outline of 3000 Solved Problems of Linear Algebra (a good source of exercises).

The Algebra Qualifying Exam will be based on the following syllabus (updated in Fall 2019). The sequence Math 210ABC will prepare students according to this syllabus.

Group Theory: basic notions and results (e.g., homomorphisms, subgroups, quotient groups, cosets, conjugation, generators, Lagrange’s theorem), isomorphism theorems,automorphism groups, symmetric groups, linear groups, group actions and permutation representations, the Sylow theorems and applications to simple groups, free groups and presentations, composition series and the Jordan-Holder theorem, nilpotent and solvable groups, semidirect products and group extensions.

Ring and Module Theory: basic notions and results (e.g., homomorphisms, ideals and generators, subrings, quotient rings), maximal and prime ideals, units, division rings, fields of fractions, PIDs, UFDs, polynomial rings and factorization (e.g., Gauss’s lemma, Eisenstein criterion), structure of finitely generated modules over a PID, canonical forms, duality and bilinear pairings, tensor products, localization, Nakayama’s lemma, torsion and rank, chain conditions and noetherian and artinian rings and modules, exterior powers and determinants.

Field and Galois Theory: basic notions and results, algebraic and transcendental extensions, separable, inseparable and normal extensions, field embeddings, algebraic closure, Galois theory, cyclotomic extensions, finite fields, solvability by radicals, norm and trace, discriminants of polynomials, Hilbert’s Theorem 90, Kummer theory.

Category Theory: basic definitions and examples, full and faithful functors, monomorphisms and epimorphisms, natural transformations, Yoneda’s lemma, representable functors, adjoint functors, equivalences of categories, limits and colimits (e.g., for limits: products, equalizers, pullbacks, initial objects).

Homological Algebra: exact sequences, splittings, snake and five lemmas, projective, injective, and flat modules, complexes, (co)homology.

Commutative Ring Theory: localizations, Hilbert’s basis theorem, integral extensions, radicals of ideals, Zariski topology and Hilbert’s Nullstellensatz, Dedekind rings, DVRs.

Noncommutative Ring Theory: Associative and graded algebras, endomorphism rings, group rings, semisimple rings, irreducible and indecomposable modules, central simple algebras, Artin-Wedderburn theorem, Jacobson radicals.

Representation Theory: basic definitions and examples (e.g,. representations, regular and trivial representations), Schur’s lemma, Maschke’s theorem, characters of finite groups, class functions, orthogonality relations, character tables, induced characters.


• Dummit and Foote, Abstract Algebra.

• Grillet, Abstract Algebra.

• Hungerford, Algebra.

• Jacobson, Basic Algebra I and II.

• Lang, Algebra.

Course material: Mathematics 245AB, the first half of Mathematics 245C, and Mathematics 246AB.

Real Analysis Topics: Lebesgue integration; convergence theorems (uniform convergence, Ego- roff’s theorem, Lusin’s theorem, Lebesgue dominated convergence theorem, monotone conver- gence theorem, Fatou’s lemma); Fubini’s theorem; covering lemmas and differentiation of measures (Lebesgue decomposition theorem, Radon-Nikodym theorem, Jordan decomposition theorem, rela- tions to functions of bounded variation, signed measures and Hahn decompositions); approximate identities; basic functional analysis (linear functionals, Hahn-Banach theorem, open mapping the- orem, closed graph theorem, uniform boundedness principle, strong, weak, and weak* topologies); elementary point set topology including Urysohn’s lemma, the Tychonoff theorem, the Baire Cat- egory theorem and the Stone-Weierstrass theorem. The spaces C(X), the Riesz representation theorem, and the compact subsets of C(X), (Arzela-Ascoli theorem); Hilbert space, self-adjoint linear operators and their spectra; Lp spaces (duality, distribution functions, weak Lp spaces, Hölder’s inequality, Jensen’s inequality, linear operators); basic Fourier analysis (orthonormal sys- tems, trigonometric series, convolutions on Rn, Plancherel’s theorem, Riemann-Lebesgue lemma Poisson summation formula); abstract measure theory; Hausdorff measures.

Complex Analysis Topics: Analytic functions: Examples, sums of power series, exponential and logarithm functions, M¨obius transformations, and spherical representation. Cauchy’s theorem: Goursat’s proof, consequences of Cauchy integral formula, such as Liouville’s theorem, isolated singularities, Casorati-Weierstrass theorem, open mapping theorem, maximum principle, Morera’s theorem, and Schwarz reflection principle. Cauchy’s theorem on multiply connected domains, residue theorem, the argument principle, Rouch´e’s theorem, and the evaluation of definite inte- grals. Harmonic functions: conjugate functions, maximum principle, mean value property, Poisson integrals, Dirichlet problem for a disk, Harnack’s principle, Schwarz lemma and the hyperbolic metric. Compact families of analytic and harmonic functions: series and product developments, Hurwitz theorem, Mittag-Leffler theorem, infinite products, Weierstrass product theorem, Poisson- Jensen formula. Conformal mappings: Elementary mappings, Riemann mapping theorem, mapping of polygons, reflections across analytic boundaries, and mappings of finitely connected domains. Subharmonic functions and the Dirichlet problem. The monodromy theorem and Picard’s theorem. Elementary facts about elliptic functions.

Note: Also all material for the Basic Examination. To prepare, students are advised to work problems from as many old examinations as possible.


  • Folland, G.B. (1984). Real Analysis, New York, Wiley.
  • Roydan, H.L. (1969). Real Analysis, New York, MacMillan
  • Rudin, W. (1986). Real and Complex Analysis, New York, McGraw Hill (3rd edition).
  • Stein, E.M. and Sharkarchi, R. (2005). Real Analysis, Measure Theory, Integration and Hilbert Spaces, Princeton University Press.
  • Wheeden, R. and Zygmund, A. (1977). Measure and Integral, An Introduction to Real Analysis, New York, M. Dekker.
  • Ahlfors, L. (1979). Complex Analysis, New York, McGraw Hill (3rd edition).
  • Gamelin, T.W. (2001). Complex Analysis, New York, Springer.
  • Stein, E.M. and Sharkarchi, R. (2003). Complex Analysis, Princeton University Press
  • Rudin, W. (1976). Principles of Mathematical Analysis, New York. McGraw Hill. (3rd edition).
  • Stein, E.M. and Sharkarchi, R. (2003). Fourier Analysis, Princeton University Press.

Basic Topics

Course material- Mathematics 266AB; additional sources are Mathematics 135AB, 136, and 146. Topics- Spectrum theory of regular boundary value problems and examples of singular Sturm-Liouville problems, related integral equations, special functions; Fourier series, Fourier and Laplace transforms; phase plane analysis of nonlinear equations; asymptotic methods for obtaining approximate solutions of ordinary differential equations; solution of simple initial and boundary value problems for potential, heat and wave equations, Green’s functions, separation of variables.

More Advanced Topics

Course material- Mathematics 266ABC.
Topics- All M.A. level topics as well as: first order partial differential equations; classification and theory of linear and nonlinear higher order partial differential equations; well-posed problems; classical potential theory, Dirichlet and Neumann problems; fundamental solutions; wave equations, Cauchy problem, initial-boundary value problems, energy estimates, method of characteristics, principle of linearization; variational problems; maximum principles; equations of fluid mechanics.


  • Bender C. M. & Orszag, S. A. (1978). Advanced Mathematical Methods for Scientists and Engineers, New York: McGraw-Hill.
  • Boyce, W. E. & Diprima, R. C. (1986). Elementary Differential Equations and Boundary Value Problem (4th edition), New York: Wiley.
  • Courant and Hilbert, Methods of Mathematical Physics, Vols. I, II.
  • Garabedian, Partial Differential Equations.
  • Haberman, Elementary Applied Partial Differential Equations.
  • John, Partial Differential Equations.
  • Stakgold, Boundary Value Problems of Mathematical Physics, Vols. I, II.
  • Zauderer, Partial Differential Equations of Applied Mathematics.
  • Haberman, Elementary Applied Partial Differential Equations

Course material: Mathematics 225ABC. The basic concepts of metric space point-set topology will be presumed known but will not be covered explicitly in the examination. For students unfamiliar with point-set topology, Mathematics 121 is suggested, although the topics covered in the analysis part of the Basic Examination are nearly sufficient. Geometry/Topology Area Exams given prior to September 2009 will cover the older syllabus which can be found here.


The topics covered fall naturally into three categories , corresponding to the three terms of Math. 225. However, the examination itself will be unified, and questions can involve combinations of topics from different areas.

  • 1) Differential topology: manifolds, tangent vectors, smooth maps, tangent bundle and vector bundles in general, vector fields and integral curves, Sard’s Theorem on the measure of critical values, embedding theorem, transversality, degree theory, the Lefshetz Fixed Point Theorem, Euler characteristic, Ehresmann’s theorem that proper submersions are locally trivial fibrations
    2) Differential geometry: Lie derivatives, integrable distributions and the Frobenius Theorem, differential forms, integration and  Stokes’ Theorem, deRham cohomology, including the Mayer-Vietoris sequence, Poincare duality, Thom classes, degree theory and Euler characteristic revisited from the viewpoint of deRham cohomology, Riemannian metrics, gradients, volume forms,  and the interpretation of the classical integral theorems as aspects of Stokes’ Theorem for differential forms
    3) Algebraic topology: Basic concepts of homotopy theory, fundamental group and covering spaces, singular homology and cohomology theory, axioms of homology theory, Mayer-Vietoris sequence, calculation of homology and cohomology of standard spaces, cell complexes and cellular homology, deRham’s theorem on the isomorphism of deRham differential –form cohomology and singular cohomology with real coefficient

Main References:

Additional References:

  • Abraham, R., Marsden, J., and Ratiu T. (1988). Manifolds, Tensor Analysis and Applications, New York: Springer Verlag.
  • Boothby, Introduction to Differentiable Manifolds and Riemannian Geometry
  • Greenberg, M. & Harper, J. (1981). Algebraic Topology, A Course, Reading, Mass.: Benjamin/Cummings Pub. Co.
  • Milnor, J. (1965). Topology from the Differential Viewpoint, Charlottesville, University Press of Virginia.
  • Warner, F., (1983). Foundations of differentiable manifolds and Lie groups, Springer.

Course material- Mathematics 220ABC.

Topics- Model theory: Chapters 1, 2, and 3 of Model Theory by Chang and Keisler; recursion theory: chapters 1 through 5, sections 7.1-7.5, 9.1-9.4, 11.1-11.4, 14.1-14.5, 14.7. 14.8 through page 326 of Theory of Recursive Functions and Effective Computability by Hartley Rogers Jr.; incompleteness and undecidability: Godel’s incompleteness and undecidability results for sufficiently strong theories; the undecidability of predicate logic. Set Theory: Chapters 1,3,4,5 and 6.1-6.4 of Set Theory: An Introduction to Independence Proofs, by Kenneth Kunen; transfinite induction; ordinals and cardinals; cardinal arithematic; constructible sets.

Basic Topics

Course material-Mathematics 151AB and 269A.


Interpolation and approximation: divided differences, Chebycheff systems, Lagrangian interpolation, splines; numerical differentiation and integration: elementary quadrature, Simpson’s, Gauss’s and Romberg’s rules; solutions of nonlinear equations: Newton’s method and its variations, estimate of rate of convergence; error analysis: methods of approximation of round-off errors and fixed and floating point arithmetic; numerical methods in Linear Algebra: Gaussian elimination, diagonalization of symmetric matrices, conditioning; numerical methods for ordinary differential equations; initial value problems, 2 point boundary value problems and eigenvalue problems; introduction to numerical methods for partial differential equations.

More Adavanced Topics

Course material- Mathematics 151 AB and 269ABC.
Difference methods for time dependent problems: stability, consistency, convergence, initial boundary value theory, and nonlinear problems; finite element methods; initial and boundary value problem, approximation theory, linear algebra considerations.

References – Basic Level

  • Conte and de Boor (1980). Elementary Numerical Analysis (3rd edition,) McGraw Hill.
  • Dahlquist and Bjorck (1974). Numerical Methods, Prentice Hall.
  • Henrici (1964). Elements of Numerical Analysis, Addison Wesley.
  • Ralston, J. (1965). A First Course in Numerical Analysis, McGraw Hill.

References – More Advanced Topics

  • Johnson (1987), Numerical Solution of Partial Differential Equations by the Finite Element Method, Cambridge U. Press.
  • Kreiss and Oliger (1973), Methods for the Approximate Solution of Time Dependent Problems, Garp.
  • Richtmyer and Morton (1967), Difference Methods for Initial- Value Problems, Wiley.
  • Sod (1985), Numerical Methods in Fluid Dynamics, Cambridge U. Press.

Course material: Mathematics 273A and Mathematics 270BC.

Optimization Topics: properties of convex functions and convex sets; subgradients and gradients; proximal operators; convex duality; Lagrangian and augmented Lagrangian; gradient descent method, proximal-gradient method, ADMM; forward-backward and Douglas-Rachford splitting methods; stochastic gradient method; coordinate gradient method. The typical applications of these abstract methods. Understanding the tradeoffs between different methods induced by problem structure.

Numerical Linear Algebra Topics: Direct, fast, and iterative algorithms, singular value decomposition, regularization, eigenvalue problems, QR Factorizations, Givens and Householder rotations, least squares solvers, conditioning and stability, Gaussian elimination, Cholesky factorization, Hessenberg reduction, QR algorithm, Arnoldi method, Lanczos method, GMRES, conjugate gradient methods, power method, orthogonalization methods, subspace iteration, discrete transform methods. 

Note: Also all material for the Basic Examination. To prepare, students are advised to work problems from as many old examinations and coursework as possible.


  • Golub and Van Loan, Matrix Computations 4th edition, Johns Hopkins Press
  • Trefethen and Bau, Numerical Linear Algebra
  • Demmel, Applied Numerical Linear Algebra, SIAM
  • Boyd and Vandenberghe, Convex Optimization, Chapters 2-5
  • Bertsekas, Convex Optimization Theory
  • Boyd, Parikh, Chu, Peleato, Eckstein, Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers.
  • Leon Bottou, Large-Scale Machine Learning with Stochastic Gradient Descent.

about the exams

There are two types of qualifying exams: the Basic exam and the Area exams. The Basic exam is designed to be passed by well-trained students before they commence study at UCLA. It examines fundamental topics of the undergraduate mathematics curriculum. The Area exams are graduate level exams. For each Area exam there is a preparatory course sequence. There are Area exams in Algebra, Analysis, Applied Differential Equations, Numerical Analysis, Geometry /Topology, and Logic. Students may attempt any number of examinations in each examination period.

MA students must pass the Basic Exam only. PhD students must pass the Basic exam and two Area exams. MA students must pass the Basic by the beginning of the sixth quarter of study. PhD students must pass the Basic by the fourth quarter of graduate study. A PhD student must pass the one Area examination by the sixth quarter. A PhD student must pass the second Area examination by the seventh quarter of graduate study.

The exams are offered in the Fall and in the Spring, usually just before the beginning of those quarters. Precise dates and times are posted well in advance of the exams. Students must sign up for the exams in the Graduate Office. Each exam lasts 4 hours. Copies of past exams may be downloaded from our website by clicking here: https://ww3.math.ucla.edu/past-qualifying-exams. It is very useful to prepare for exams by doing questions from previous exams. Recent exams are likely to be more relevant since the syllabi have changed over time. However, it is essential to combine problem-solving with studying the exam syllabus theme by theme. In order to learn the material well, you will need to do exercises well beyond those on previous exams.

Each exam is written and graded by a committee created for that purpose. The Graduate Studies Committee approves exam results (passing or failing), taking into account recommendations of the examination committee. Shortly after the Graduate Studies Committee’s decision, students are notified of their exam results. Students are reminded that the grading of exams is a complex matter, and that final result (Pass or Fail) is not usually determined by the total score of all work on all problems. Students should read and follow carefully the instructions of an exam.

Graded exams are kept in the Graduate Office for six months and then destroyed. They may be examined in the Graduate Office during this time. After the results of the exams are announced, there is a one week appeal period during which students may petition, in writing, to a Qual Committee for regrading of problems. Appeals must be submitted via the Graduate Office. The Qual Committee will respond, usually in writing, to any appeal within one week.

Currently, most UCLA PhD students pass all their exams on schedule. However, the few students who fail to pass exams by the required deadlines are deemed not to be making Satisfactory Progress. Each such student is discussed individually by the Graduate Studies Committee at a meeting shortly after the above period of appeals is over. Students who have missed a deadline, or otherwise failed to make Satisfactory Progress, will receive a letter from the Graduate Vice Chair indicating any action that was taken, and detailing any schedule for performance that must be satisfied in order to continue in the program. Only in unusual circumstances will a PhD student who is more than six months behind the schedule of Satisfactory Progress be permitted to remain in the PhD program. Students who are facing negative actions are encouraged to write to GSC, and to speak to the Graduate Vice Chair, before GSC meets, to explain any extenuating circumstances that could positively influence it.