The map is an involution, so
If is an eigenvalue of , then . Hence every eigenvalue belongs to
Because has distinct roots, the transform is diagonalizable; which fourth roots occur and their multiplicities depend on .
Applying the transform twice gives
By the finite geometric series, the inner sum over is when and zero otherwise. Therefore
which is the stated with the label interpreted modulo .
For , the binary label is the integer , so
where and . It is a product state and hence has no quantum entanglement.
For , the quantum Fourier transform is
Its matrix is unitary because character orthogonality for the cyclic group gives orthogonal rows.
Set
This is an elliptic function. Write and in the expansion from part (i). At a lattice point, the coefficient of in is , and its constant coefficient is ; there are no other singular terms. Every apparent pole is therefore a removable singularity, and extends to an entire elliptic function with value zero at the lattice points.
An entire elliptic function is bounded on a fundamental parallelogram and hence everywhere. By Liouville theorem it is constant, and its value at zero is zero. Thus , proving the Weierstrass elliptic differential equation
For each nonzero period lattice point , the binomial series gives
Pairing with cancels every odd power. Hence the Laurent series of the Weierstrass elliptic function is
which is the stated coefficient formula.
Eliminate to obtain the two-dimensional autonomous differential equation
Its Jacobian matrix at the endemic equilibrium is
Since ,
The trace-determinant stability criterion shows that both eigenvalues have negative real part. The Endemic equilibrium of the SIR model with waning immunity is therefore locally asymptotically stable.
At an endemic equilibrium, , so forces
The equation gives . The conservation law therefore yields
A positive endemic state exists exactly when , equivalently when the basic reproduction number exceeds one.
The hat matrix is an orthogonal projection of rank , so is an orthogonal projection of rank . Because is a standard multivariate normal distribution vector, Cochran's theorem gives
Thus . Substituting this into the preceding formula gives the Distribution of the Akaike information criterion in a normal linear model:
For the normal linear model, the Gaussian likelihood gives
Maximization over gives the ordinary least squares estimator , and maximization over the variance gives
At this value the quadratic term in is . There are regression coefficients and one variance parameter, so substitution into the Akaike information criterion yields
Conditional independence makes the log-likelihood
A maximum-likelihood estimator is any . If the model has fitted real parameters, its Akaike information criterion is
The language is not context-free. Suppose it had pumping length in the pumping lemma for context-free languages, and apply the lemma to . Write with , , and for every .
Let and be the respective numbers of s and s in . If , pumping with or destroys equality of the two block lengths. Hence a valid decomposition would require . Pumping with would then produce , where . But
so is not a square number. This contradiction proves the square-count language is not context-free.
A context-free grammar is a quadruple consisting of a finite set of nonterminal symbols, a disjoint finite alphabet of terminal symbols, a start symbol , and a finite set of productions with and . A sentence is a terminal word over an alphabet with , and the generated formal language is .
The first language is context-free. For example, the productions
generate exactly : each recursive production adds two s to the left and two s to the right.
Insert the Fourier mode
into the leapfrog advection scheme. This gives
and hence the amplification polynomial
Its roots are
If , the square root is real for every , and
If , choosing makes the roots non-real multiples of with reciprocal moduli, one of which exceeds one, so the method is unstable.
The endpoint requires care. At the polynomial is
so a generic mode has the form and grows linearly. It satisfies the weaker test often quoted in elementary Fourier analysis, but it violates the root condition for a multistep method because the unit-modulus root is repeated. Therefore the rigorous uniform stability range for arbitrary two-level initial data is
If “stable” is being used only for the non-amplification condition on root moduli, the conventionally quoted range is , with a defective marginal endpoint rather than a uniformly stable case.
Let be the Toeplitz antisymmetric tridiagonal matrix with , , and zero diagonal. Fixed homogeneous endpoint values give the homogeneous update
The hint gives the eigenvalues
Because each is purely imaginary, for every real , so the left matrix is invertible. The two matrices are polynomials in and therefore have the same orthonormal eigenvectors. The amplification matrix
has eigenvalues
The numerator and denominator are complex conjugates, so . Moreover, the common orthonormal eigenbasis makes a normal matrix. By the matrix 2-norm of a normal matrix,
for every . Thus the Crank-Nicolson centered-advection scheme on a finite interval is unconditionally stable:
A complex square matrix is a normal matrix if it commutes with its conjugate transpose:
By unitary diagonalization of a normal matrix, there are a unitary matrix and a diagonal matrix such that
The matrix 2-norm is invariant under multiplication by unitary matrices, so
For a diagonal matrix,
with equality on a coordinate vector belonging to an eigenvalue of greatest modulus. Hence
the matrix 2-norm of a normal matrix.
The stationary contribution travels with group velocity
so . The condition
is therefore equivalent, up to a constant factor, to : the dominant wavelength is much longer than the impacted interval. Its Fourier transform can then be replaced by
which is the total initial vertical velocity integrated over space. The far field cannot resolve and separately and depends only on their product .
Put with fixed . The relevant stationary point will have , so the assumption allows the long-wave approximation
Using , the phase has no stationary point for . The other phase is
with
and
The stationary part of the integral is therefore
By the one-dimensional stationary-phase formula, this is asymptotic to
Since
we obtain
Using , this has the requested form
where
Use the Fourier transform convention
The deep-water capillary-wave dispersion relation makes each Fourier mode satisfy
The transformed initial data are
Therefore
The integrand is even, so Fourier inversion gives the surface response to a localized impulsive velocity

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