Part IB, 2007, Paper 1
Part IB, 2007, Paper 1
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1.II.11H
commentDefine what it means for a function to be differentiable at a point with derivative a linear map
State the Chain Rule for differentiable maps and . Prove the Chain Rule.
Let denote the standard Euclidean norm of . Find the partial derivatives of the function where they exist.
1.I.3F
commentFor the function
determine the Taylor series of around the point , and give the largest for which this series converges in the disc .
1.II.13F
commentBy integrating round the contour , which is the boundary of the domain
evaluate each of the integrals
[You may use the relations and for
1.II.16E
commentA steady magnetic field is generated by a current distribution that vanishes outside a bounded region . Use the divergence theorem to show that
Define the magnetic vector potential . Use Maxwell's equations to obtain a differential equation for in terms of .
It may be shown that for an unbounded domain the equation for has solution
Deduce that in general the leading order approximation for as is
Find the corresponding far-field expression for .
1.I.5D
commentA steady two-dimensional velocity field is given by
(i) Calculate the vorticity of the flow.
(ii) Verify that is a possible flow field for an incompressible fluid, and calculate the stream function.
(iii) Show that the streamlines are bounded if and only if .
(iv) What are the streamlines in the case
1.II.17D
commentWrite down the Euler equation for the steady motion of an inviscid, incompressible fluid in a constant gravitational field. From this equation, derive (a) Bernoulli's equation and (b) the integral form of the momentum equation for a fixed control volume with surface .
(i) A circular jet of water is projected vertically upwards with speed from a nozzle of cross-sectional area at height . Calculate how the speed and crosssectional area of the jet vary with , for .
(ii) A circular jet of speed and cross-sectional area impinges axisymmetrically on the vertex of a cone of semi-angle , spreading out to form an almost parallel-sided sheet on the surface. Choose a suitable control volume and, neglecting gravity, show that the force exerted by the jet on the cone is
(iii) A cone of mass is supported, axisymmetrically and vertex down, by the jet of part (i), with its vertex at height , where . Assuming that the result of part (ii) still holds, show that is given by
1.I.2A
commentState the Gauss-Bonnet theorem for spherical triangles, and deduce from it that for each convex polyhedron with faces, edges, and vertices, .
1.II.10G
comment(i) State a structure theorem for finitely generated abelian groups.
(ii) If is a field and a polynomial of degree in one variable over , what is the maximal number of zeroes of ? Justify your answer in terms of unique factorization in some polynomial ring, or otherwise.
(iii) Show that any finite subgroup of the multiplicative group of non-zero elements of a field is cyclic. Is this true if the subgroup is allowed to be infinite?
1.I.1G
commentSuppose that is a basis of the complex vector space and that is the linear operator defined by , and .
By considering the action of on column vectors of the form , where , or otherwise, find the diagonalization of and its characteristic polynomial.
1.II.9G
commentState and prove Sylvester's law of inertia for a real quadratic form.
[You may assume that for each real symmetric matrix A there is an orthogonal matrix , such that is diagonal.]
Suppose that is a real vector space of even dimension , that is a non-singular quadratic form on and that is an -dimensional subspace of on which vanishes. What is the signature of
1.II.19C
commentConsider a Markov chain on states with transition matrix , where , so that 0 and are absorbing states. Let
be the event that the chain is absorbed in 0 . Assume that for .
Show carefully that, conditional on the event is a Markov chain and determine its transition matrix.
Now consider the case where , for . Suppose that , and that the event occurs; calculate the expected number of transitions until the chain is first in the state 0 .
1.II.14D
commentDefine the Fourier transform of a function that tends to zero as , and state the inversion theorem. State and prove the convolution theorem.
Calculate the Fourier transforms of
Hence show that
and evaluate this integral for all other (real) values of .
1.II.12A
commentLet and be topological spaces. Define the product topology on and show that if and are Hausdorff then so is .
Show that the following statements are equivalent.
(i) is a Hausdorff space.
(ii) The diagonal is a closed subset of , in the product topology.
(iii) For any topological space and any continuous maps , the set is closed in .
1.I.6F
commentSolve the least squares problem
using method with Householder transformation. (A solution using normal equations is not acceptable.)
1.I.8C
commentState and prove the max-flow min-cut theorem for network flows.
1.II.15B
commentThe relative motion of a neutron and proton is described by the Schrödinger equation for a single particle of mass under the influence of the central potential
where and are positive constants. Solve this equation for a spherically symmetric state of the deuteron, which is a bound state of a proton and neutron, giving the condition on for this state to exist.
[If is spherically symmetric then
1.I.4B
commentWrite down the position four-vector. Suppose this represents the position of a particle with rest mass and velocity v. Show that the four momentum of the particle is
where .
For a particle of zero rest mass show that
where is the three momentum.
1.I.7C
commentLet be independent, identically distributed random variables from the distribution where and are unknown. Use the generalized likelihood-ratio test to derive the form of a test of the hypothesis against .
Explain carefully how the test should be implemented.
1.II.18C
commentLet be independent, identically distributed random variables with
where is an unknown parameter, , and . It is desired to estimate the quantity .
(i) Find the maximum-likelihood estimate, , of .
(ii) Show that is an unbiased estimate of and hence, or otherwise, obtain an unbiased estimate of which has smaller variance than and which is a function of .
(iii) Now suppose that a Bayesian approach is adopted and that the prior distribution for , is taken to be the uniform distribution on . Compute the Bayes point estimate of when the loss function is .
[You may use that fact that when are non-negative integers,