Math 642 Final Exam Review Spring 2015
The final exam for Math 642 will be held on Monday, May 11, from 8 to
10, in our usual classroom (ARCC 205). The test covers the material
from sections 7.1, 7.2, 10.1-10.3, as well as the material on tempered
distributions that we discussed in class. I'll have office hours on
Friday: 1-3, 4-5.
Operators on Hilbert space
- Unbounded operators
- Terms: densely defined, closed & closable, extensions,
adjoint, self adjoint, resolvent operator, resolvent set, spectrum
(discrete, continuous, and residual)
- Resolvent operator (L − λI)−1
- Analytic, bounded on the resolvent set.
- Spectrum of a self-adjoint operator real; no residual spectrum.
- Spectral theorem
- Be able to define the term spectral family,
Eλ. Be able to state the spectral theorem.
- Kodaira/Weyl/Stone formula, Green's functions, and spectral
transform. Be able to find the spectral transform in simple cases
Fourier transform, Fourier sine and cosine transforms.
Fourier transforms
- Definition of transform and inverse transform. (Use whichever
sign convention you want, just be consistent.)
- Be able to establish simple properties (Theorem 7.2).
- Be able to compute transforms and inverses of transforms.
Know the convolution theorem and be able to establish simple
L1 properties of convolutions f,g ∈
L1 implies that f∗g ∈
L1.
- Be able to prove or sketch a proof for each of these:
- ``Useful'' form of Parseval's Theorem.
$\int_{\mathbb R} f(u)\hat g(u)du = \int_{\mathbb R}
\hat f(u)g(u)du$.
- Sampling theorem
- Uncertainty principle
Schwartz space and tempered distributions
- Schwartz space S
(See Feldman's
online notes).
- Definition and notation
- Semi-norm and (equivalent) metric space topologies
- Theorem. The Fourier transform of S is S. Be able
to sketch a proof of this.
- Tempered distributions, S′
(See Feldman's
online notes.)
- Definition and notation, derivatives of distributions,
multiplcation of a distribution by C∞ functions
increasing polynomially
- Know the coninuity test for a linear functional to be a tempered
distribution (Feldman, Theorem 6, pg. 7)
- The Fourier transform of a tempered distribution is defined via
Parseval's identity,
$\int_{\mathbb R} T(u)\hat \phi(u)du = \int_{\mathbb R}
\hat T(u)\phi(u)du$
- Examples of Fourier transforms of tempered distributions
Asymptotic analysis
- Asymptotic estimates and series; big "O" and little "o" notation
- Watson's lemma. Be able to state, prove, and use it.
- Laplace's method. Be able to derive asymptotic estimates,
e.g. Stirling's formula.
- Practice problems. See
assignment 9.
Structure of the exam
There will be 5 to 7 questions. You will be asked to state a few
definitions, and to do problems similar
to
assigned homework problems (starting with assignment 6) and
examples done in class. In addition, you will be asked to give or
sketch a proof for a major theorem or lemma from the material above.
Updated 5/8/2015 (fjn).