An integrating factor for a differential one-form makes the multiplied form exact. If , then and . Equality of the mixed partial derivatives yields
This is a local compatibility condition under the usual smoothness assumptions.
For the trigonometric equation, where its coefficients are defined and division is legitimate, the slope is . In the first quadrant it is positive, small near either axis and large near the upper-right corner. The direction field below uses normalized line segments, so steep directions remain visible.
Multiplication by gives
Thus the multiplying function is an integrating factor, and the implicit general solution is
In the larger square, . The positive- curves have positive and are symmetric about the -axis; the negative- curves are their reflections. For , a graph representation is
with endpoints tending to . The interior curve is . The domain boundaries include singular coefficients or zeros of the integrating factor, so these endpoint limits and smooth continuations through describe the regularized relation; they must not be mistaken for additional solutions of the literal original equation at undefined points.
Figure 1.
Trigonometric direction field, regularized implicit solution family, and the positive higher-order particular solution
. Details.
For independent random variables, their sum has the product of their probability generating functions:
Comparing polynomial coefficients identifies a binomial distribution with parameters :
and the probability is zero at all other values. The common success probability is essential to this binomial form; independent binomial counts with different probabilities do not in general add to a binomial count.
For a nonnegative integer-valued random variable , its probability generating function is
initially defined at least for . A general real-valued random variable need not have a probability generating function in this sense. For a binomial distribution, the binomial theorem gives
Differentiating the generating function produces factorial moments:
Since , the mean and variance are
These formulas include the degenerate endpoint probabilities and .
For , the separated integral is
Inverting gives
The upper branch has , where decreases towards as . The lower branch has , where decreases to as . These are separate maximal intervals: the pole is not part of a solution. For the domain , a lower-branch initial value below necessarily reaches that pole in finite positive . The direction field sketch above displays both exterior branches and a central hyperbolic tangent branch.
Separate variables and integrate on :
Hence the general solution in this region is
Every such solution increases from values near towards , remains strictly between the two equilibria, and is defined for all real .
Independence requires each joint probability to equal the product of the relevant marginals. In particular it implies , equivalent to .
Conversely let and , and assume . The covariance calculation gives . Then
All four joint probabilities therefore factor, proving independence. Hence
This is Bernoulli independence from zero covariance, including degenerate marginals. It is special to two-point variables and is not a general equivalence for arbitrary random variables.
The probabilities satisfy and . Since the variables are indicators,
Their covariance is
Thus the necessary and sufficient condition for uncorrelated random variables is
This uses zero covariance as the definition. If one variable is constant, a normalized correlation coefficient is undefined, but zero covariance and this criterion remain meaningful.
For the stated angle, , so . The minimizing unit vector is therefore , and
Indeed all three pairwise dot products equal , so the vectors lie in one plane, separated by degrees. This is also the global minimum pairwise dot-product sum of three unit vectors: for any three unit vectors,
so , with equality exactly when .
The triangle inequality for the two unit vectors gives . Taking reciprocals and using the negative sign in yields
In fact equality would require , by the equality condition in the Cauchy-Schwarz inequality. Since the two vectors here are linearly independent, the inequality is strict for every admissible pair.
Put and . The linear independence assumption implies . Since is a unit vector, the Cauchy-Schwarz inequality gives
Equality holds exactly when points opposite to . Its required unit length then fixes the scale:
Here because both vectors have unit norm. The minimizing vector is unique, and the minimum pairwise dot-product sum of three unit vectors for these fixed is
Place the cube's vertices at . Every symmetry fixes its centre, and permutes the three perpendicular pairs of face normals, so it is a signed permutation matrix. Conversely every such matrix preserves the cube. The symmetry group of a cube acts transitively on its eight vertices: independent coordinate sign changes take to any vertex.
A symmetry fixing must permute its three incident edges. This gives an injective map from its stabilizer subgroup into , since those three edge directions determine the linear transformation. All six permutations are realized by coordinate permutation matrices, which fix . Thus the vertex stabilizer has order six. The orbit-stabilizer theorem now yields
The use of all symmetries includes reflections as well as the twenty-four elements of the rotational symmetry group of a cube.
For a group action of on a set and , the orbit-stabilizer theorem states
If is finite, this becomes . The underlying bijection sends the left coset to . Equality of two image points is equivalent to , so this map is both well-defined and injective, and it is surjective by the definition of the group orbit.
A positive, counterclockwise rotation takes the standard basis vectors and to and . These images are the columns of its rotation matrix, so
It fixes the origin, preserves the dot product and has determinant one.
The absolute ratio of successive terms is . The ratio test gives convergence for and divergence for , so the radius of convergence is . On the boundary, and
The positive partial sums are bounded, and thus converge. By the comparison test for series, the original power series converges absolutely at every point of .
If , cancellation of successive factors gives for every positive integer . Hence is the identity element exactly when is, proving that conjugate group elements have the same order of a group element. For permutations, the sign group homomorphism similarly gives
Thus conjugate permutations have the same sign of a permutation.
The converse is false: permutation order and sign do not determine conjugacy. In the symmetric group , take and . Both have order three and positive sign. However, fixes three symbols whereas fixes none. If fixes a symbol , then fixes , and applying the inverse conjugation gives a bijection between the fixed-symbol sets. Their different fixed-point counts therefore prove that are not conjugate. Equivalently their cycle types and differ. Equal order and sign are necessary, but not sufficient, for conjugacy.
Compose permutations from right to left. Tracking the four symbols through the two permutation cycles gives and . Thus the cycle decomposition of a permutation is
The disjoint transpositions commute, and squaring their product gives the identity element, while the product itself is nonidentity. Its order of a group element is therefore two. Each transposition has negative sign of a permutation, so the product has sign : it is an even permutation.
Compare with the divergent series from part (i). The ratio of its new summand to is
For completeness, , so . The limit comparison test now gives divergence. Although the exponent exceeds one for each summand, it approaches one and does not produce a convergent p-series with a fixed exponent greater than one.
Because , each of , and is positive and increasing for . Hence is positive, continuous and decreasing. With , , so
The integral test for convergence implies that the series is convergent.

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