For , expand the exponential function in powers of :
The constant and linear terms cancel in , giving
For , is exponentially small:
The small- correction is smaller than every positive power of beyond the displayed linear term. In dimensional terms, the large- leading mass is , while the small- limit is .
The original PDF puts both in the exponent in the second equation. Since the exponential function is injective, gives . Put , so . The first equation then gives
Thus , so and . The unique real solution of the simultaneous equations is
The function graphs intersect when , so or . For , the exponential function satisfies , making the upper graph. The enclosed area is therefore
The antiderivative of follows by integration by parts.
For real , , so multiplication by the hyperbolic cosine is reversible. The identities and give
Thus . The exponential function is injective, so the unique real solution is
The chain rule and the quotient rule give
The exponential function and denominator are positive, so the stationary points occur exactly at . Their values are
The derivative is negative for and positive for , so is a local minimum and a local maximum. They are also global extrema, since .
The chain rule gives
Since , the exponent is at most , with equality precisely at . The exponential function is increasing, so
The sign of the derivative, positive for and negative for , gives the same conclusion.
All are positive, and . The logarithm turns consecutive ratios into differences, producing the finite telescoping sum
Thus, already for every finite ,
If the partial sums converge to , the continuity of the exponential function gives
The shift from to preserves the limit of a sequence. Convergence of the partial sums is established in part (f), so no convergence assumption is left unsupported.
Set . The exponential function identity reduces the problem to the quadratic equation
Positivity excludes , so . Since the exponential function is strictly increasing, the unique answer is .
Induction on gives , including . The absolutely convergent matrix exponential series may therefore be applied term by term to each eigenvector:
Thus
For a repeated eigenvalue, every nonzero vector in its eigenspace remains an eigenvector. Because the real exponential function is injective, distinct real eigenvalues of do not merge under this transformation.
Classification and existence. For , an ordinary point is one where are analytic. There are two independent analytic power series solutions, with arbitrary initial values . A regular singular point is a singular point where and are analytic. The Frobenius method then constructs solutions beginning with , where solves the indicial equation. At least one Frobenius solution exists; two such solutions exist without logarithms when the two exponents differ by a noninteger. Repeated exponents or an integer difference can require a logarithmic second solution.
For this equation,
Both are analytic at zero, while themselves have poles there. Thus zero is a regular singular point.
Indicial equation and recurrence. Multiply by and insert , :
The lowest power has coefficient , giving
The coefficient of is
For either exponent the common factor is nonzero for , so the recurrence relation reduces to
Normalizing each leading coefficient to one, the two Frobenius solutions are
More explicitly, . The distinct leading powers establish linear independence, so on the positive real side of the singular point. The displayed exponential function is the requested closed-form solution; substitution gives , which makes the differential expression zero.
Convergence. For either exponent the ratio of successive terms in the coefficient power series is
Thus both coefficient series have by the ratio test. This does not remove the branch point of : its analytic coefficient factor is entire, while the full Frobenius solution requires a square-root branch away from zero in the complex plane. The differential equation has no other finite singular points to limit continuation of these coefficient series.
In the upper half-plane, the argument lies strictly between zero and , while can be any real number. Conversely, if with , then is in the upper half-plane and .
Thus the principal complex logarithm is a conformal bijection from the upper half-plane onto that horizontal strip, with inverse the exponential function restricted to the strip.
For , the number avoids the nonpositive real axis. Define the branch of the complex logarithm by
Here the principal argument is selected as a continuous map on that slit domain, so this is a holomorphic function, with derivative and . For example, locally writing gives , verifying the complex derivative. The normalization also makes this branch of the complex logarithm unique: any two continuous choices differ by a constant integer multiple of on the connected slit domain, and their values at agree.
To evaluate the corresponding analytic branch of a square root on the unit circle, factor
For , we have and . Thus this factorization already uses the selected principal argument, with no hidden change by . It follows that
Halving this expression and applying the exponential function gives
Since , the desired branch value is
For instance, gives , a quick check that the sign agrees with the normalization.
The two terms in the preceding formula are the real part and imaginary part. Their squared sum is the squared complex modulus:
Here follows directly from the exponential function definitions. The hyperbolic sine modulus identity therefore yields
Equality holds exactly when , that is, when is an integer multiple of . The lower bound is uniform in , which will control whole vertical sides of the contour rather than just their endpoints.
Start with the exponential function definition of the hyperbolic sine and use Euler's formula:
Identifying the hyperbolic sine and hyperbolic cosine in the final line gives
On the first quadrant choose the holomorphic logarithm with . It maps to , so its image is precisely the strip . Its inverse there is the exponential function; both derivatives are nonzero. Composing with part (i) gives
This is a bijective conformal map from the lens onto the strip, with inverse
The logarithm's branch is fixed by its argument range on the quadrant. Using a different branch would shift the strip vertically by an integer multiple of . This is the lens-to-strip logarithmic conformal map.
For the ideal guaranteed-delay model, the total untreated yearly input at operating days is
Since the discharge is a decreasing function of the residence time, the minimum is obtained at equality:
This is half-lives and corresponds to L of carbon-dioxide-equivalent delay volume. The three-hour choice provides margin; operating every day instead would require at least minutes under the same assumptions.
This minimum is conditional on a guaranteed residence time. More generally the surviving fraction is
where is the residence time distribution. Because the exponential function is convex function, a spread of transit times gives more surviving radioactive activity than plug flow at the same mean time. A perfectly mixed continuously flowing vessel has a steady-state survival fraction , not . Thus no unique minimum tank filling time follows without specifying the filling, retention and emptying schedule. The boxed minimum applies to the explicitly specified delay system, and must not be represented as approval of an unspecified tank.
Let be the fraction still crystalline. Under the direct-impact amorphization model, damage events occur randomly and independently; an event striking already amorphous material does not create that much additional amorphous volume. Only the crystalline fraction can be newly converted, so
The product of the given event rate density and damage volume has units of inverse time:
For radiation-induced amorphization, , giving
Using days per year, the corresponding calendar date is approximately 3555 CE, measured from disposal preparation in 2050.
A linear estimate misses repeated hits to already damaged regions and therefore predicts too rapid an approach to . The exponential function model never reaches exactly in finite time. Its assumptions include constant dose rate, fixed effective damage volume, no annealing and no spatial correlation of damage. Actual alpha decay generates recoil damage as well as the alpha particle's track; the stated damage volume must be understood as the effective volume per radioactive decay for the chosen model.
Amorphous is not synonymous with dissolved or failed containment. Radiation damage can change swelling, connected porosity and leach behaviour, so testing must compare structural evolution with element release. Accelerated self-irradiation and parallel dissolution measurements are useful precisely because crystallinity alone is not the performance endpoint.[ref]
For a closed unit-branching radioactive decay chain, the rate equations are
The first gives . Multiply the second by its integrating factor :
Integrate from zero to . For ,
so
The coefficients can individually be negative; the physical population is nonnegative because the production integral is nonnegative. For equal nuclear decay constants , the finite limit is
A sum of two constant-coefficient copies of the same exponential function cannot represent this limit; the factor is essential.