Separate the variables in this first-order ordinary differential equation:
Integration gives , so . On the interval containing the prescribed point , we have . The initial condition therefore gives , hence . Choosing the positive square root to match that initial condition yields
The maximal interval containing on which this solves the explicit ordinary differential equation is . At the left endpoint , the original denominator vanishes and the derivative becomes unbounded. Directly, and , verifying the equation throughout this interval.
On an interval avoiding zero put . A real solution requires , and the principal square root is . The homogeneous first-order differential equation reduces to
Where , separation of variables gives . Thus the nonconstant pieces are
restricted to intervals where the cosine of the phase is nonnegative. This sign condition is essential when substituting back into the original square root.
There are also the solutions and . They can join the nonconstant pieces with a continuous first derivative, because the transformed rate vanishes but is not Lipschitz continuous at . For example, on the positive axis every gives
The sticking solutions of a bounded square-root differential equation describe the same joining mechanism on either half-axis after using the increasing variable .
Isolate the square root: . A real solution must have , because a real principal square root is nonnegative. Squaring gives , hence . The candidate zero violates ; substitution verifies the other candidate. Thus
The sign restriction prevents the extraneous solution introduced by squaring.
Isolate the square root: . Its right side must be nonnegative, so retain the condition before squaring. Squaring then gives
Both candidates pass the original equation: and . Thus
The substitution check excludes the possibility of extraneous roots introduced by squaring.
Use the integration by substitution , with . On this interval , so it cancels the positive denominator square root. The transformed integral is
Its integrand is even. Therefore the answer in the PDF's modulus-amplitude convention for the elliptic integral of the second kind is
The modulus is , not the squared parameter .
Write a square root as , with real. Equating the real part and imaginary part of its square gives and . Taking complex modulus also gives . Therefore
Since , the signs agree. The two roots are
The changes both signs together, rather than independently.
Independence makes the variances of the attendance indicators additive. The binomial distribution therefore gives . Its positive square root is the standard deviation:
A constant sequence must satisfy the fixed point equation . The square root forces . Squaring gives , so the negative algebraic root is inadmissible. Hence
Starting at produces the constant sequence .
Solving for gives with . For large , the square root is , so the two asymptotes are
The curve lies between these lines on the right side and has its nearest point, with vertical tangent, at . As increases it travels from the lower unbounded end through that vertex to the upper unbounded end. The left hyperbola branch is not part of the given curve.
Figure 1.
The parametrized right branch of a hyperbola, its foci, nearest point, and asymptotes
. Details.
For the composite square root, throughout the restricted interval. Differentiate with respect to :
The second expression comes from differentiating both and . The endpoints where are excluded here.
In , every row sums to one, so is an eigenvector with eigenvalue . The antisymmetric direction gives eigenvalue . A direction orthogonal to both is , and direct multiplication shows that it lies in the kernel of a linear map. Normalizing all three gives the complete system
They form an orthonormal basis of . The extra zero eigenvalue reflects the one-dimensional kernel of a linear map for this rank-two rectangular matrix. The question's symbols denote the eigenvalues of ; the nonzero singular values of are their square roots, namely and .
The Newton root-finding iteration follows the current tangent line to its horizontal-axis intersection. Since , it gives
A positive initial guess is appropriate for the positive square root; negative starting values instead target the negative root.
Put . The double-angle trigonometric identities imply . Since is in the first quadrant, the positive square root is required. The half-angle identities then give the requested expression in terms of :
Branches and cuts. For the square root of z squared minus one, a branch point is a point around which analytic continuation along an arbitrarily small closed loop can change the value of a chosen branch of a multivalued function. Near , the square root behaves as ; near it is a nonzero analytic factor times . One circuit around either point reverses its sign. Thus the finite branch points are . Infinity is not a branch point: in the expression is , which has two single-valued meromorphic choices near zero.
A single branch cut can join to ; its shortest choice is the real segment . Any surviving loop then surrounds either both branch points or neither, so it produces no sign change. Alternatively, use two branch cuts, and , each joining a branch point to infinity. On the resulting slit region one can choose a consistent branch of a multivalued function.
For the finite cut, fix at infinity, equivalently for . To give its actual values on both sides, put
For , the selected square root is
Here ; when , . Squaring verifies the formula because . Its real part has the sign of , its imaginary part has the sign of , and it matches the chosen value at infinity. In particular, the two boundary values on the branch cut are
Outside the cut, . Reversing the global branch of a multivalued function reverses every displayed value.
Differential equation. Write with this finite cut, and orient counterclockwise with one circuit around it. Since is fixed and avoids the branch points, differentiation under the integral sign gives
On the contour . Therefore
The last contour integral vanishes because the expression in brackets returns to its original value after circling both branch points. This proves , including at ; division by is unnecessary.
Figure 1.
Shrinking a counterclockwise contour around the finite square-root cut
. The upper lip runs from 1 to -1, and the lower lip returns from -1 to 1. The endpoint arcs have vanishing integrals. The values shown use the branch that behaves as z at infinity. Details.
Value at zero. Near either endpoint , the integrand at zero is . A small arc of radius has length and hence contributes . The upper lip runs from to , and the lower lip from to . Thus
Using evaluates the final integral as , and so
The same deformation gives . The sign of reverses if either the global square-root choice or the contour orientation is reversed; the differential equation is unaffected.
Choose the square root of one minus z squared with : explicitly with principal square roots. It is single valued and holomorphic away from the two specified exterior real branch cuts. If for , its boundary values are
For example, above the right cut approaches the negative real axis from below, selecting ; above the left cut approaches it from above, selecting . Continuing once around either branch point changes the sign, which explains the need for cuts.
Apply the residue theorem to on a large disk slit along both cuts, with small arcs excluding . The only enclosed pole is at zero, and its residue is . On the positively oriented boundary of the slit domain, the upper right lip runs from one to , and the lower right lip returns from to one. The jump in gives their combined integral as , where . The left lips similarly give after the substitution .
Figure 1.
A contour around the two exterior square-root cuts
. Original schematic. The two slit boundaries are traversed with the retained domain on the left; each contributes twice the same real integral multiplied by i. The sole enclosed pole is at zero. Details.
The small arcs contribute because the branch singularities have order . The large arc contributes because . Taking limits therefore yields , and hence
The real substitution independently reduces the integral to , confirming its value and sign.
Use the same principal square root , which is holomorphic on because its argument avoids the nonpositive real axis. Then
is a holomorphic function satisfying
Thus it is a holomorphic branch of the requested square root. This construction does not require a global holomorphic logarithm of or separately. Its sign is fixed by at infinity, so . The negative of this function is the other holomorphic branch; any two branches have a continuous quotient taking values in , which is constant because is connected.
There is no such map for the domain printed in the paper. The planar domain is not simply connected. For example, a sufficiently large positively oriented circle surrounds and lies in , while
The integrand is holomorphic on . If were simply connected, the Cauchy integral theorem would force this integral to be zero. A conformal bijection is a homeomorphism and preserves simple connectivity, whereas is simply connected. Thus a conformal bijection is impossible.
The explicit construction also pinpoints the missing point. Define
This Möbius transformation sends the removed line segment to the nonpositive real axis, together with infinity. More precisely, its image on the stated planar domain is
since has no finite solution when . Conversely, its inverse is defined for every in this set and cannot lie on , proving this image description exactly.
Take the principal square root of , characterized by positive real part, and then multiply by . The result is the conformal map
Each stage is injective and onto the indicated image; the square root maps the slit plane to the right half-plane, with the point omitted here. Hence this is a conformal bijection onto the punctured upper half-plane. Its inverse is
If the source is instead on the Riemann sphere, the same map extends with and becomes a conformal bijection onto all of . Indeed, in the local coordinate it has expansion , whose derivative at is nonzero. This gives the sphere version of the requested construction without silently changing the printed planar domain.
A real square matrix is an orthogonal matrix when , equivalently its columns form an orthonormal basis. Here is the transpose and the identity matrix. For every vector ,
Taking nonnegative square roots proves
Thus an orthogonal matrix preserves the Euclidean norm.
Since every , the diagonal matrix is invertible. Set
The division is by the diagonal entry of row . Thus is an upper triangular matrix with diagonal entries one and .
To use symmetry without assuming the conclusion, multiply by the matrix inverse of and its transpose:
The matrix is symmetric because is a symmetric matrix. It is also an upper triangular matrix, since every factor on the right is an upper triangular matrix. A symmetric upper triangular matrix is diagonal. Its diagonal is exactly , because and have diagonal entries one. Hence , giving
This is the LDL decomposition.
Take the positive square roots of the diagonal entries:
The matrix is a lower triangular matrix with positive diagonal, and
This is a Cholesky decomposition. For a nonzero vector , the vector is nonzero because is invertible. Therefore
Here is the Euclidean norm. Thus is a positive-definite matrix.