The cross product of the direction vectors is . It is nonzero, so a common perpendicular direction exists. Projecting onto its unit vector gives the distance between skew lines:
Thus
The numerator is a scalar triple product; movement along either line does not change this perpendicular projection.
First check the improper integral exists: near zero its numerator is , so the quotient is ; at infinity both exponentials decay. For positive parameters in compact neighborhoods, the differentiated integrands have integrable bounds, justifying differentiation under the integral sign. It gives
Thus , with independent of both parameters. Since , , and
The sign is consistent with the integrand: makes it positive. Neither separate integral converges at zero; it is the difference that is meaningful. The substitution identifies the result as a Frullani integral with an extra factor .
Apply the Leibniz integral rule: differentiate both moving endpoints and the integrand's explicit dependence. The partial derivative is . Hence
The signs distinguish upper and lower endpoint contributions. The formula also holds when the limits occur in reversed order, by the oriented-integral convention. If , the integral defining is identically zero and all displayed terms cancel, so
Let , and take equal subintervals of width . Since sine is continuous, its integral is the limit of the left-endpoint Riemann sums
Using Euler's formula, the corresponding complex sum is a finite geometric series:
Since ,
Taking imaginary parts gives
One can see the same limit entirely within the real sums: the finite trigonometric-sum identity obtained from this geometric sum gives
Thus the evaluation is explicitly by a Riemann sum, as required.
Factor out the dominant cubic term and use a geometric series in :
Thus the requested leading term and absolute error order are
The relative error of retaining only the leading term is ; it differs from the absolute error order .
For any real square matrix , the symmetric and antisymmetric parts of a matrix give , whose summands are respectively a symmetric matrix and an antisymmetric matrix. Here it gives
Transposing the first summand leaves it unchanged; transposing the second changes its sign. Entrywise addition recovers the original matrix. The decomposition is unique because a matrix that is both symmetric and antisymmetric must be zero.
The expression assumes is invertible. By the cyclic property of the trace,
For a real or complex antisymmetric matrix, forces every diagonal entry to satisfy , hence . Therefore
This also demonstrates invariance of the matrix trace under matrix similarity. Antisymmetry of itself is not needed.

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