This University of Oxford Part A options paper covers fourteen printed sections and nineteen questions. [ref] The archive contains the complete editable eleven-page transcription. Bounded official-source searches found no advertised answers to this exact paper. All 30 source leaves and their unnumbered tasks are covered below. The source's mechanics potential is retained in the transcription, and its physical interpretation is qualified in the solution. The string-length and statistical-distribution assumptions are also made explicit where needed.
Count the pairs for which fixes . Counting first by group elements gives , while counting first by points gives . On a group orbit of size , orbit-stabilizer theorem makes each stabilizer have size , so that group orbit contributes to the second sum. Dividing by proves Burnside's lemma:
A tetrahedron has four vertices. A rotational symmetry is determined by the image of one vertex, with four possibilities, and the cyclic orientation of the three vertices around it, with three possibilities. All these choices are realizable, so its rotational symmetry group of a tetrahedron has order . More explicitly, its elements are the identity, the two nontrivial rotational symmetries around each of four vertex-to-opposite-face axes, and the half-turn about each of three axes through opposite edge midpoints. Thus there is one element of order 1, eight of order 3, and three of order 2. The induced permutations of vertices are the even permutations, identifying the group with .
Apply the group action to the set of edge colourings. A colouring is fixed by a rotational symmetry precisely when its colour is constant on each cycle of the induced edge permutation. The identity has six edge cycles and fixes colourings. A vertex-axis rotational symmetry has two cycles of length three, fixing . An opposite-edge half-turn fixes the two edges on its axis as sets and exchanges the other four in two pairs, giving four cycles and fixed colourings. Therefore
Reflections are excluded because the equivalence in the source uses rotational symmetries.
Map the integers into a field by . Its kernel is a prime ideal of , since the image has no zero divisors. Thus the kernel is either zero or for a prime . In the zero case, the map extends injectively to the rational numbers by taking quotients of nonzero integers. In the other case, its image is the field . This proves the prime-field assertion.
A finite field cannot contain the infinite rational field, so it has characteristic . It is a finite-dimensional vector space over its prime field , say of dimension , and choosing a basis counts its elements as
For existence, put and take a splitting field of over . Its derivative is , so it has exactly distinct polynomial roots. The polynomial roots are closed under addition and multiplication because the Frobenius identity gives and . They include , are closed under additive inverses, and for a nonzero polynomial root , . They therefore form a field of exactly elements. Indeed this field is the splitting field because it contains all polynomial roots and is generated by them.
In order 4, characteristic is 2. For , the multiplicative group has order 3, so and . Factorization of gives . The quadratic has no polynomial root in and is the minimal polynomial. Write . The complete tables are
For an element in order 8, the tower law makes divide3. It is not1, so its minimal polynomial is an irreducible monic cubic. Its constant term must be1. A cubic has no polynomial root at 1 exactly when , and absence of a polynomial root is equivalent to cubic irreducibility. Consequently the two possibilities are
Both occur: together with and they factor over , whose distinct polynomial roots are exactly the eight elements of the field. Each cubic contributes its three polynomial roots.
Euler's totient function counts the integers coprime to , equivalently the invertible residue classes modulo . Among , exactly the multiples of are not coprime to the prime power. Hence
Factor . Its distinct prime-power factors are pairwise coprime, so the permitted multiplicativity gives
For , the empty product is one and agrees with .
Use prime factorization and multiplicativity to check the identity one prime at a time. Fix and put , , . The local factors to compare are
If either exponent is zero, and the equality follows from . If both are positive, the prime-power formula makes both sides
Multiplying the local identities over all primes and using gives
This accounts for repeated prime factors shared by the two inputs, which ordinary coprime multiplicativity alone would not remove.
Fermat's little theorem states that for a prime and an integer not divisible by ,
Equivalently, for every integer , with divisibility by allowed in that latter formulation.
Since , its factorial is even, so is odd and its prime divisor is odd. Also cannot divide , since it would then divide1. Modulo ,
Raise this equation to the integer power . Fermat's little theorem gives
As is odd, and are distinct residues. Thus the exponent is even, and
If a prime divisor of satisfied , it would divide and therefore divide the difference , impossible. Hence .
Every integer has a prime divisor, and (ii) makes each of its prime divisors congruent to 1 modulo 4. Taking arbitrarily large produces such primes beyond every bound. Therefore
Equivalently, if their list were finite, choosing at least its largest member would produce a new member larger than that supposed maximum.
The monotone convergence theorem says that if almost everywhere and the functions are measurable on a measure space, then
with infinite integrals permitted. The limit is measurable after the usual modification on any exceptional null set.
The dominated convergence theorem says that if measurable functions converge almost everywhere to and satisfy almost everywhere for an integrable nonnegative function , then is integrable and
The theorem applies equally to real or complex functions. In particular domination must be by one fixed Lebesgue integrable function, rather than by a different bound for each .
Put . These are nonnegative measurable functions increasing to , possibly initially with value infinity. Monotone convergence theorem gives
An infinite value on a set of positive measure would force an infinite integral. Thus is finite almost everywhere and, after setting it to zero on its null exceptional set if desired, is integrable.
Where is finite, the real series is absolutely convergent. Define its sum to be there and zero on the exceptional null set. Measurability follows as an almost-everywhere limit of partial sums, and almost everywhere gives integrability. Every partial sum is dominated by , so dominated convergence theorem yields
In fact the convergence is also in the integrable-function norm:
Use for . For the source's functions,
The last integral follows by the substitution and integration by parts. Since converges, (ii) permits summing the integrals and identifies an integrable almost-everywhere sum.
For every , the geometric series gives
The functions vanish on , and the single endpoint does not change the integral. Use the supplied integral of to obtain
The estimates include negative through its absolute value, and the case gives zero on both sides.
Fubini's theorem for the product of two sigma-finite measure spaces states that an integrable measurable function on the product has integrable sections almost everywhere, the section integrals define Lebesgue integrable functions, and both iterated integrals equal the product integral. The integrability hypothesis is absolute integrability. For nonnegative measurable functions, Tonelli's theorem gives equality of the possibly infinite product and iterated integrals without first assuming finiteness.
The displayed function is not Lebesgue integrable. Its value at the origin can be assigned arbitrarily, since a point is a null set. On and ,
Consequently Tonelli's theorem gives the divergent lower bound
The signed iterated integrals illustrate why the hypothesis matters. For , , so integration first in and then in gives . Integrating first in gives , using . Exceptional boundary sections have measure zero. Thus finite iterated values do not establish product integrability.
Choose measurable versions of the two Lebesgue integrable functions and consider . Translation and the corresponding linear change of variables preserve Lebesgue measurability; one can first use Borel versions and then disregard the resulting null-set changes. Tonelli's theorem and translation invariance give
Fubini theorem therefore shows that the section in is integrable for almost every . Define by that section integral where it exists and by zero on the exceptional null set. Fubini theorem also makes this a measurable Lebesgue integrable function, with
Its almost-everywhere defining formula is precisely the desired convolution. This construction explains why an everywhere-existing pointwise integral is not required.
For fixed real , multiplication by does not change the absolute value. The product integrability proved in (ii) therefore justifies Fubini theorem in the following calculation. Set in the inner integral:
Thus
The positive exponential convention in the source is used throughout; no normalization factor is introduced under that convention.
The product topology on has the open rectangles , with open in and open in , as a topological basis. The projection preimages are and , so both projections are continuous.
If is continuous, both coordinate compositions are continuous. Conversely, if both are continuous, then
is open for every basic rectangle, proving continuity of . Given paths between two chosen endpoints in each factor, their coordinatewise pair is therefore a continuous path in the product, proving that a product of path-connected spaces is path-connected.
For the compact-neighborhood assertion, fix . For each , choose an open rectangle containing inside . Compactness of chooses finitely many covering . Put
Then , , and : any point of belongs to one of those rectangles' second factors, while lies in every first factor.
Compactness of now selects finitely many covering . Set
These are open, contain and , and if , choose an with and use . Hence
If or is empty, take the corresponding open factor empty and the other factor the whole space; the assertions then hold directly. No Hausdorff assumption on the factors is needed.
A Hausdorff space separates any two distinct points by disjoint open neighborhoods. For a subspace , intersect such neighborhoods in with to obtain disjoint neighborhoods in the subspace topology. Thus subspaces inherit the Hausdorff property.
If lies off the diagonal of a Hausdorff space's square, choose disjoint open neighborhoods of and of . The open rectangle contains the pair and avoids the diagonal. Therefore its complement is open and the diagonal is closed.
The map given by is continuous by the coordinate criterion from E3. The equality locus is and is closed as an inverse image of a closed set.
Let be the quotient map. If the quotient is Hausdorff, apply the same argument to in both coordinates:
is closed in .
Conversely suppose is closed and is open. Take two distinct quotient points, with representatives . Since , an open rectangle around it avoids . The images and are open quotient neighborhoods. They are disjoint, because a quotient point in their intersection would have equivalent representatives , , giving . Hence the quotient is Hausdorff. Thus closedness of the relation and openness of the quotient map suffice for a Hausdorff quotient.
A sufficient regular-level condition is at every point with . The implicit function theorem then makes the zero level a two-dimensional continuously differentiable submanifold. Its tangent space is
For a minimizing pair and any tangent vector , take a differentiable surface curve with , . The function has a minimum at zero, so its derivative vanishes. Varying the other point similarly proves orthogonality to .
For the particular surfaces, minimize the distance from the origin to the second surface first. Put , , so and . Then
Let . Since , this is at least , with equality when one of is zero. For , this quadratic has its minimum at , with value 5. For , it decreases up to zero and has minimum9 on that half-line. The global minimum is therefore5, attained at
All points of this surface lie outside the unit sphere. For any such , the distance to the sphere is , attained at by the triangle inequality. Consequently
This is a global minimization, not merely a stationary-point calculation.
Figure 1.
Nearest points on the two surfaces in the section
. Details.
Write . For endpoint-zero variations , the first variations are
For a normal constrained extremal, choose a variation with . Given any , use the implicit function theorem to choose a small correction in the direction so that preserves the constraint. Differentiating it and the stationarity condition at zero gives
Integrate the derivative-of-variation term by parts. Since the variations vanish at both endpoints, the boundary term is zero. The fundamental lemma of the calculus of variations then gives
The regularity condition on the constraint is what permits the coefficient of to be normalized to 1. In a degenerate case, the general multiplier statement uses with the two coefficients not both zero; the source's displayed form is the normal case.
For a string described as a function graph , its arc-length element is . Inextensibility therefore gives
This also forces , with equality only for the straight function graph.
For the upper function graph, the vertical cross-section of the enclosed region has length , so its area is . A maximizing nonnegative arch therefore uses and in the normal Euler-Lagrange equation. It becomes
Integrating once gives . The concave upper branch has and integrates to . The equal zero endpoint heights force and . Hence
It is a circular arc. To find its parameter, substitute into the length integral: , giving
This scalar equation determines numerically when needed; no explicit solution is required.
The arch is a global maximum in its smooth function graph regime. For , the integrand is concave and strictly concave in its slope. Its supporting-tangent inequality, integrated against any competing function graph with the same endpoint values, has first-order term zero by the Euler-Lagrange equation. Thus . On the fixed-length class this is ; strict slope concavity also gives uniqueness.
The source leaves the length range implicit. A twice continuously differentiable function graph of this form needs , giving . At the straight function graph is the degenerate solution. The semicircle limit has vertical endpoint tangents and is outside that smooth function graph class. For , no arc in the claimed smooth function graph family exists, so the stated formula cannot describe a twice continuously differentiable maximizing function graph under those unrestricted data. Allowing overhanging curves changes the admissible class.
Figure 1.
The circular arch and its smooth graph length range
. Details.
Write the position of a mass element relative to the centre of mass as . Expand its squared velocity and integrate:
The mixed term vanishes because . Also
using the scalar triple-product identity. Therefore
In principal axes the inertia tensor is diagonal, so the second term is . Substituting the three Euler-angle components given in the source gives its displayed kinetic-energy expression directly.
For , the first two component squares have opposite mixed terms and sum to . Put . Using the orientation-dependent potential printed in the source therefore gives the formal model
The cyclic coordinates have conserved momenta . Consequently are constant. The coordinate is also cyclic, with
For imposed fixed tilt , conservation of and forces constant. Impose the fixed-height condition in this formal constrained model. Its equation is
Set the tilt constant and divide by its nonzero sine. This gives
A real polynomial root requires its quadratic discriminant to be nonnegative:
When this condition holds the two algebraic rates are .
There is a physical inconsistency in the printed data that must be kept distinct from this algebra. If are literally Cartesian coordinates of the centre of mass in uniform gravity, the gravitational potential is , not . The printed Lagrangian consequently does not follow from that Cartesian-height interpretation. Moreover its unconstrained equation is , so constant height at the indicated tilt requires a constraint reaction. The requested rate and discriminant follow from the printed orientation-dependent potential with fixed height imposed; a standard heavy-top interpretation instead uses a height proportional to an axis distance times , with the reference point and corresponding inertia specified consistently. The kinetic-energy derivation is independent of this source inconsistency.
Set , choose for a negative bound-state energy, and write . Multiplying the radial equation by gives
For , its second derivative is . Substitution cancels the two terms and gives
For the physical hydrogen problem, the angular eigenvalue has a nonnegative integer. Regularity at the origin selects the Frobenius exponent , rather than the singular branch. Put
The equation for the series factor is , and coefficient comparison yields
The regular confluent-hypergeometric solution generically grows like in this series factor; after the extracted it is not normalizable. A bound state requires termination at some degree , namely . Thus is an integer greater than , and
Regularity, normalizability and the integer angular index are the physical conditions selecting this spectrum; the differential equation without those conditions would admit many other solutions.
For , necessarily and . With ,
A normalized spatial ground state is . In spherical coordinates the radial probability has weight . Constants and the angular integral cancel in the tail ratio. The supplied integral with gives
Milne-Thomson's circle theorem inserts an impermeable circular boundary into a two-dimensional irrotational incompressible flow. If is analytic in a neighborhood of the closed disc and its flow singularities lie outside, the new complex potential outside is
Reflection and coefficient conjugation make the second term analytic outside the circle, with its image singularities inside. On , , so the two terms sum to : the streamfunction is constant there. Thus no velocity crosses the circle. At infinity the image term tends to the constant , which has no effect on velocity, and the far-field flow is retained. This proves the construction, with an additive potential constant immaterial.
Put , . For the dipole the reflected potential is , giving
Its image pole is , inside the cylinder. The complex velocity is
Near , the second term is with , while is analytic there. The square of the pole term has no residue, nor does . The cross term has residue , so
Take the contour counterclockwise around the cylinder, as in the supplied Blasius force theorem. The residue theorem gives . Therefore
The force points toward the dipole. Its independence of dipole orientation follows from the product in the sole residue contribution.
Irrotational motion in this simply connected fluid region has a velocity potential, . Incompressibility gives , hence .
The moving surface is a material surface: differentiating along a particle gives at . Linearizing about a flat stationary surface drops the product term and evaluates at zero, giving there. The Unsteady Bernoulli equation, after dropping quadratic velocity terms and absorbing the time-only constant into , is . The linear capillary pressure at the surface is relative to atmosphere, in the sign convention of the source. Therefore
For choose the harmonic potential decaying at infinite depth,
Its vertical derivative at zero equals . Substitution into the dynamic condition gives . Thus
The two positive terms are the gravitational and capillary contributions to the restoring force.
Independence means for all Borel sets . For variables with a joint density this is equivalent to factorization of that density into the two marginal densities almost everywhere.
The inverse transformation is , , on , . Its absolute Jacobian determinant is . Multiplying the independent gamma densities by it gives
The density is zero outside that support. Integrating in with the gamma integral gives
It is a beta density. Its normalization also proves the beta integral . The joint density consequently factors as this normalized beta density times
Thus is gamma with shape and rate , and are independent.
Finally . All relevant first moments are finite, and independence gives , while . Hence
This identity follows from the particular beta-gamma independence here; a general ratio of random variables would not permit moving expectation through division.
Starting from a state , let be the first return time, with value infinity if no return occurs. The state is recurrent if and transient if this probability is less than 1. A recurrent state is positive recurrent if , and null recurrent if that expectation is infinite.
If and communicate, choose with and . The Chapman-Kolmogorov equations give, for every ,
If is recurrent, the supplied criterion makes infinite. Summing this inequality shows that is also infinite, so is recurrent. The same argument with the states exchanged gives the converse. Hence recurrence and transience are class properties: states in one communicating class cannot have different answers to that dichotomy.
Assume , as required by the source's selection probabilities, and put . Conditional on the red book's current position, the next independent selection determines its move without needing its earlier history. Selecting the red book moves it left, unless already leftmost. Selecting the plain book immediately to its right moves it right. Every other selection leaves its position unchanged. Thus this position process is a Markov chain on , with
and boundary self-loop probabilities , . These account for every selection and each row sums to one.
Stationarity at the first state gives , hence . When , for the second state substitution of this identity into its stationarity equation gives . More generally, summing stationarity over the initial segment equates its sole outward and inward probability flows:
Write . Then . Normalization gives
The expression is positive also for , since both numerator prefactor and denominator are negative. The uniform case is exactly , when all books are equally likely to be selected. Since both neighboring transition probabilities are positive, the finite chain is irreducible; the displayed stationary distribution is therefore unique.
Minimize the residual sum of squares . Differentiating gives the normal equations . Full column rank makes positive definite and invertible, so the unique minimizer is
Since , it is unbiased. The independent common-variance errors give , hence
Independent Gaussian errors with common variance are a sufficient condition for this estimator also to be the maximum likelihood estimator: their log-likelihood differs from by terms independent of . Profiling an unknown common variance gives the same minimizer. Mean and variance assumptions alone do not specify a likelihood.
For the seven design points, and . In increasing time order the design matrix is
Its columns are mutually orthogonal: the odd sums vanish and . Their squared lengths are , respectively. Therefore
In particular . Testing for a quadratic contribution means testing against .
The cooling measurements are stated to have zero-mean errors and known common variance, but normality is not explicitly assumed for them. Under the independent-error linear regression model as stated, Chebyshev's inequality gives a valid conservative level- test: reject when
Its null rejection probability is at most because the estimator has mean zero and the calculated variance. If Gaussian errors are additionally assumed, the sharper exact test uses under the null and rejects for . With only seven observations, exact normal calibration cannot be deduced from the printed moment assumptions alone.
For a sample of size , define
For the zero-mean Gaussian sample, the standardized vector has independent standard normal coordinates. Apply an orthogonal transformation whose first row is . The resulting coordinates remain independent standard normals: their joint density depends only on squared Euclidean length and the transformation has unit absolute Jacobian. Its first coordinate is , while orthogonal decomposition gives
Thus
The ratio of the first independent standard normal and the square root of the normalized chi-square variable has a Student probability distribution, giving
For the paired height observations, form one cross-minus-self difference per pot. The sampling units for this test are the fifteen differences, not thirty separate plant heights. Under the usual independent normal model for differences, a null mean of zero gives a statistic. The observed statistic is
For the two-sided alternative, reject at significance level if . Its two-sided -value is . This uses the recorded values without performing the numerical calculation forbidden by the question. The normal difference model is what makes the small-sample Student calibration exact.
For the positive-direction alternative, use the same paired statistic , but reject at level only when . Its one-sided -value is
Because the observed mean difference is positive and the null Student probability distribution is symmetric, the two-sided -value is twice this upper-tail probability, consistent with the supplied and .
The two-sided value is the null-model probability of a test statistic at least as far from zero in either direction as the observation. The one-sided value uses only the direction of larger cross-fertilized heights. They are probabilities under the assumed null sampling distribution, not posterior probabilities that the null hypothesis is true.
At the reported precision, the two-sided result is on the conventional 5 percent boundary; rounding can matter for a strict numerical threshold. The one-sided result is significant at5 percent and supports a positive mean difference if that directional alternative was chosen in advance. Choosing the direction after observing the sign would not justify using the smaller one-sided probability as a prespecified test. The paired design controls shared pot conditions, while the inference still relies on the independence and probability distribution assumptions for the differences.
The elementary elimination step replaces row by row minus a multiple of an earlier pivot row . With coordinate vectors , its premultiplication matrix is
and its inverse is , since . Choose as the current entry below the pivot divided by the current pivot. Required pivots are assumed nonzero, consistently with elimination without row interchanges.
For dimension 4, first eliminate positions , then , then . Thus
The rightmost operation acts first, and every multiplier is computed from the matrix at its own stage. For general , the numbers of eliminations in successive columns are , totaling ; a zero multiplier simply gives an identity operation.
The product is unit lower triangular and is upper triangular. Its inverse is unit lower triangular, so
The stored multiplier in position is the corresponding subdiagonal entry of , as follows by reversing the pivot-row subtractions column by column.
If is upper Hessenberg, only the first subdiagonal can be nonzero below the diagonal. At stage only position needs elimination. Subtracting row cannot create lower entries further down because its entries before its pivot are already zero. Hence only operations are needed. The inverse factors occur in increasing column order, and their cross products vanish, giving
which is lower bidiagonal; is upper triangular, possibly dense above its diagonal.
If the Hessenberg matrix is also symmetric, it is tridiagonal. At each elimination step the pivot row has no entries past its immediate superdiagonal, so the updated matrix retains that upper bandwidth. Thus is lower bidiagonal and is upper bidiagonal, with at most two nonzero entries in each row, as required.
A real inner product is a bilinear symmetric form satisfying for every nonzero , and . Its norm is . An orthogonal polynomial family has nonzero members of exact degrees , with for different indices. Exact degree is part of this definition; merely belonging to the indicated polynomial vector spaces would not suffice.
Distinct degrees make linearly independent. There are of them in the -dimensional space , so they form a basis. Any lower-degree polynomial is their linear combination, and bilinearity therefore gives for every .
Use the orthogonal-projection characterization: is the best approximation to in a finite-dimensional subspace exactly when is orthogonal to . Here is already orthogonal to , so its unique best approximation is zero. For , is nonzero and therefore cannot be that best approximation. Directly,
For the specified weight, symmetry makes every odd moment vanish, while
Choose and . A monic quadratic orthogonal to has no linear term by symmetry, and orthogonality to 1 requires . Thus a valid answer is
The weight vanishes only at one point, so a nonzero polynomial has positive squared norm; the form is indeed positive definite on the polynomial vector space. Nonzero rescalings of individual family members give equally valid unnormalized answers.

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