Put . The common Dirichlet boundary condition gives on . Expanding the energy functional,
Integration by parts and the field equation make the cross term zero:
Consequently
For , equality holds exactly when . For , equality holds exactly when , so is constant on the connected region; its zero boundary value then again forces . The minimizing property therefore proves uniqueness for the Dirichlet problem in both cases:
Let be two solutions with the same Neumann boundary condition, and set . Then
Multiplying by and applying Green's first identity gives
The integrand is nonnegative. If , both terms can vanish only when , so the solution of the modified Helmholtz equation is unique.
If , the identity only forces . On a connected region, may be any constant. Thus solutions of the Laplace equation with prescribed normal derivative are unique only up to an additive constant, so
No. A standard counterexample comes from the log-normal distribution. Let
and, for a fixed , let
This is a nonnegative density distinct from . For every nonnegative integer , substituting makes the difference of the th moments proportional to
It is the imaginary part of
which vanishes because its phase is . The case also proves that is normalized. Thus the two distributions have every finite moment equal but are different. Unbounded random variables need not be determined by their moments.
The normalizing constant satisfies
For an integer ,
Translation by the integer merely permutes the summation indices, so the final sum is . Consequently
The last equality uses the moment-generating function of the standard normal variable from part (b).
Normalization of the Gaussian distribution gives
Completing the square,
Therefore
and hence
Because and are bounded, their exponential series may be integrated term by term for every real . Thus their moment-generating functions satisfy
and similarly for . Equality of every moment gives equality term by term, so
The only positive equilibrium solves and , hence is
Away from a nullcline,
This is separable:
Integration gives the first integral
Thus one convenient conserved quantity is
Its gradient is
so is its only stationary point in the positive quadrant. Its Hessian matrix is
which is positive definite everywhere. Hence is a strict, indeed global, minimum.
The nearby level curves of are closed curves surrounding this minimum. Since is constant along every trajectory, a solution starting on a sufficiently small nearby level set cannot leave the region bounded by a slightly larger level set. This proves Lyapunov stability of the equilibrium: solutions initially close to remain close for all time.
Write the vector field as
The equilibrium points of a dynamical system in the closed first quadrant are
The Jacobian matrix is
At its eigenvalues are , so this is a saddle equilibrium. Its unstable direction is the positive -axis and its stable direction is the positive -axis; to first order, nearby trajectories satisfy , .
At the eigenvalues are , so it is also a saddle. The -axis is the stable direction, while trajectories entering the quadrant in the direction move away.
At ,
whose eigenvalues are
It is therefore a stable spiral. A point immediately to its right moves upward, so nearby trajectories spiral counterclockwise into the equilibrium. These eigendirections and the inward spiral give the requested local phase-portrait sketches.
For either eigenpair above, and hence for every positive integer . Therefore
so both terms in the solution from part (a), and every linear combination of them, solve the higher-order system.
A system of two scalar differential equations of order has a -dimensional solution space. The displayed family supplies two independent solutions, so there must be
further linearly independent solutions.
Resolve the forcing in the eigenbasis:
In the zero-eigenvalue direction, a constant forcing produces the particular integral . In the unit-eigenvalue direction, a constant particular integral is . Thus a particular integral depends on time exactly when
Adding the complementary solution from part (a), the general solution is
This is the eigenvector form of the usual variation of parameters calculation.
The characteristic polynomial is
For and , corresponding eigenvectors are
They are linearly independent, so the general homogeneous solution is
The stationary equations are
Thus and , giving
The Hessian matrix is
At either nonzero stationary point,
so both are strict local minima.
Along a line through the origin,
where
When and ,
Consequently the origin is a local minimum along the line when
including the equality cases because the positive quartic term then leads. It is also a minimum on the vertical line. It is a local maximum along the line when
In the first case the graph is locally bowl-shaped. In the second it initially bends downward from the origin, but the positive quartic term eventually turns it upward, producing the usual double-well profile.
The multivariable chain rule gives, at ,
Sufficient conditions for a strict local minimum at are and .
At a stationary point, in every direction. Its second derivative is the quadratic form of the Hessian matrix. If
then completing the square gives
for every nonzero direction . The Hessian is therefore positive definite, and the stationary point is a strict local minimum.
After division by , the coefficient of is . The Abel identity for the Wronskian gives
so
For , direct substitution confirms that . Reduction of order gives a second solution proportional to
To extract the requested coefficients, put
For the differential operator
one finds
The analytic correction must therefore satisfy . Its constant and linear coefficients give
Hence
For a normalized equation
is an ordinary point when are analytic there. It is a regular singular point when and are analytic there. These are the ordinary point criterion for a second-order equation and regular singular point criterion for a second-order equation.
Here
so is regular singular. Seek a power-series solution of a differential equation
Equating the coefficient of gives
and hence
Therefore
The series terminates exactly when is a nonnegative integer: the factor with then makes . Thus the polynomial solutions occur for
Divide the keystrokes into disjoint blocks of five, and let be the event that block is exactly HELLO. The events are independent events, and
Consequently
Part (c) shows that infinitely many of these block events occur almost surely. Each occurrence is an occurrence of HELLO in the full typed sequence, so
If , part (b) gives
Thus almost surely. By the convention in the question, this occurs exactly when . Therefore
This is the second Borel-Cantelli lemma for independent events.
Write . Independence gives, first for finite partial counts and then by monotone convergence,
Using factor by factor,
By Tonelli theorem for the nonnegative indicators,
If this is finite, then is finite almost surely: alternatively, Markov inequality gives
Since for every ,
This is the first Borel-Cantelli lemma.
Let be the expected additional number of tosses when the current terminal run contains consecutive heads. Then , and for ,
For , iterating this recurrence from down to gives
Solving,
When , the waiting time is deterministically , which is also the continuous limit of this formula as .

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