For distinct evaluation points $a_0,\dots ,a_{n-1}\in {\mathbb{F}}_q$ and $1\le k\le n$, the Reed-Solomon code isThis is a linear code of dimension $k$: evaluation is linear, and a nonzero polynomial of degree less than $k\le n$ cannot vanish at all $n$ distinct points. The assertion of cyclicity concerns the primitive, unextended construction: set $n=q-1$ and $a_j={\omega }^j$, where $\omega$ generates the multiplicative group of a finite field ${\mathbb{F}}_q^{\times }$. Arbitrary evaluation sets or arbitrary coordinate orders need not make a Reed-Solomon code a cyclic code.

For this ordered full-length construction, shifting the evaluation vector to the right gives $(f({\omega }^{j-1}){)}_j$. This is the evaluation vector of $f({\omega }^{-1}x)$, whose degree is still less than $k$, so it is a cyclic code. Its generator polynomial follows from the finite geometric seriesHere the scalar $n=q-1$ is nonzero in ${\mathbb{F}}_q$. Write $f(x)={\sum }_{a=0}^{k-1}{m}_a{x}^a$ and $c(x)={\sum }_{j=0}^{n-1}f({\omega }^j)x^j$. For $1\le \ell \le n-k$,since $1\le a+\ell \le n-1$. Thus every word is divisible by $g(x)={\prod }_{\ell =1}^{n-k}(x-{\omega }^{\ell })$. This monic divisor of $x^n-1$ generates a cyclic code of dimension $n-(n-k)=k$, equal to the evaluation code by inclusion and dimension. Hence

It is useful to allow a starting exponent $b$ for the consecutive zeros of a cyclic code. Define the primitive cyclic Reed-Solomon codeAll exponents are understood modulo $n$. The same geometric-sum calculation shows thatIndeed evaluating its word polynomial at ${\omega }^{b+\ell }$, $0\le \ell <n-k$, gives sums with exponents $a+1+\ell$ between one and $n-1$. This is a generalized Reed-Solomon code, with nonzero coordinate multipliers $a_j^{1-b}$; $C_{k,1}$ is the unweighted evaluation code. Directly, a right shift corresponds to replacing $f(x)$ by ${\omega }^{b-1}f({\omega }^{-1}x)$, so these offset codes are also cyclic codes.

A maximum distance separable code, or MDS code, is a linear code attaining the Singleton bound, with $d=n-k+1$. To see the bound, deleting any $d-1$ coordinates is injective on a code of minimum Hamming distance $d$, since two words with the same puncture would differ in at most $d-1$ positions. Therefore $q^k\le q^{n-d+1}$ and $d\le n-k+1$. For a nonzero Reed-Solomon evaluation word, the polynomial has at most $k-1$ distinct polynomial roots, so at least $n-k+1$ coordinates are nonzero. Nonzero coordinate multipliers do not change these zero positions. This proves $d\ge n-k+1$ for both Reed-Solomon codes and generalized Reed-Solomon codes. Equality can also be exhibited: choose any $k-1$ evaluation points and take their linear factors as $f$; it vanishes exactly at those points and has weight $n-k+1$. Thus

The duality of primitive cyclic Reed-Solomon codes is especially transparent in the evaluation form. Assume first $1\le k<n$. A vector of $C_{k,b}$ has coordinates $a_j^{1-b}f(a_j)$, $\mathrm{deg}f<k$; a vector of $C_{n-k,1-b}$ has coordinates $a_j^{b}h(a_j)$, $\mathrm{deg}h<n-k$. Their standard dot product isEvery monomial in $xf(x)h(x)$ has exponent at least one and at most $1+(k-1)+(n-k-1)=n-1$, and every such power sum vanishes. Thus $C_{n-k,1-b}\subseteq C_{k,b}^{\perp }$. Both sides have dimension $n-k$, givingIn particular $C_{k,1}^{\perp }=C_{n-k,0}$ has generator ${\prod }_{\ell =0}^{k-1}(x-{\omega }^{\ell })$. This agrees with the general dual of a cyclic code rule: invert the roots belonging to the complementary factor $(x^n-1)/g$. The dual is a Reed-Solomon code in the consecutive-zero convention. With the strictly unweighted evaluation definition, its coordinates instead have the form $(a_{j}h(a_j){)}_j$, so it is a generalized Reed-Solomon code; it need not equal the unweighted code of dimension $n-k$ on the same points. This convention distinction is essential. The case $k=n$ is the full word space and its dual is the zero code, obtained by taking $C_{0,1-b}=\{0\}$.

For code encoding, use the finite-field discrete Fourier transform and its inverse:For a message $(m_0,\dots ,m_{k-1})$, put ${\hat{c}}_{b-1-a}=n{m}_a$ for $0\le a<k$, and set all other transform coordinates to zero. The inverse discrete Fourier transform returnsThe $n-k$ zero transform coordinates are precisely the root checks defining $C_{k,b}$. This gives non-systematic encoding by evaluation. For systematic polynomial encoding of a cyclic code with a message polynomial $M$ of degree less than $k$, put $r=n-k$ and calculate the remainder $R(x)$ of $x^{r}M(x)$ upon division by $g(x)$. Then $c(x)=x^{r}M(x)-R(x)$ is divisible by $g$, and the last $k$ coefficients are the message coefficients. Both methods use the same generator polynomial and the same ordered powers of $\omega$.

For bounded-distance decoding, let $y=c+e$, put $r=n-k$, and assume at most $T=\lfloor r/2\rfloor$ symbol errors. The following description uses the Reed-Solomon key equation and fixes the transform and locator conventions explicitly.

The denominator in the Forney algorithm is nonzero for distinct locations. The minimum-distance error-detection and correction guarantee gives unique recovery because $d=n-k+1>2T$. If the required locator or a valid correction cannot be found, declare decoding failure. Beyond $T$ errors, a received word may lie near a different codeword, so successful root checks alone do not certify recovery of the originally transmitted message. The guaranteed correction radius is $\lfloor (n-k)/2\rfloor$ symbol errors.

Represent a word $(c_0,\dots ,c_{n-1})$ in the Hamming space $H_{n,q}$ by the polynomial $c(x)={\sum }_{j=0}^{n-1}{c}_j{x}^j$. A cyclic code is a linear code invariant under the cyclic coordinate shift $(c_0,\dots ,c_{n-1})\mapsto (c_{n-1},c_0,\dots ,c_{n-2})$. Under this identification the shift is multiplication by $x$ modulo $x^n-1$. A shift-invariant vector subspace is closed under multiplication by every polynomial, since such multiplication is a linear combination of shifts. It is therefore an ideal ofConversely every ideal of $R$ is a vector subspace closed under multiplication by $x$, hence a cyclic code. Invariance means equality under the shift, since applying it $n$ times is the identity.

Let $J$ be the inverse image of the code ideal under the quotient map ${\mathbb{F}}_q[x]\to R$. It contains $(x^n-1)$ and is nonzero. Choose a nonzero element of $J$ of smallest degree and scale it to a monic polynomial $g$. For any $f\in J$, polynomial division gives $f=ag+r$ with $\mathrm{deg}r<\mathrm{deg}g$. Since $r=f-ag\in J$, minimality forces $r=0$. Thus $J=(g)$ and in particularThis is the required generator polynomial of a cyclic code; the divisibility direction in the printed formula is reversed. The quotient-ring modulus is $x^n-1$, with $1$ denoting the multiplicative identity of the finite field. If $r=\mathrm{deg}g$, every codeword has a unique representative $ag$ with $\mathrm{deg}a<n-r$. Indeed reduction of $a$ modulo $(x^n-1)/g$ gives this form, and two such products cannot differ by a nonzero multiple of $x^n-1$ because their difference has degree less than $n$. ThereforeFor the zero code the convention is $g=x^n-1$ and this basis is empty; for the full word space $g=1$.

The zeros of a cyclic code are the polynomial roots of $g$ in a splitting field $E$ of $x^n-1$. Suppose first that the characteristic $p$ of ${\mathbb{F}}_q$ does not divide $n$. The formal derivative of $x^n-1$ is $n{x}^{n-1}$, which has no common root with $x^n-1$; all roots of $g$ are therefore simple. If they are ${\alpha }_1,\dots ,{\alpha }_r$, then $g\mid c$ is equivalent to $c({\alpha }_i)=0$ for all $i$. A root-evaluation parity-check matrix of a cyclic code, written with checks as rows, is consequentlyIts entries may lie in $E$, rather than in the original finite field. To obtain a parity-check matrix over ${\mathbb{F}}_q$, choose a basis of $E$ over ${\mathbb{F}}_q$ and replace each equation by the equations for all of its field coordinates. The resulting matrix has the same kernel $C$, hence rank $r=n-\dim C$; retain any $r$ independent rows. More economically, choose one root from each Frobenius conjugate orbit. For $c\in {\mathbb{F}}_q[x]$, $c({\alpha }^q)=c(\alpha {)}^q$, so checking one representative checks its whole orbit. Expanding that representative's equation in a basis of ${\mathbb{F}}_q(\alpha )$ gives precisely the number of checks equal to its orbit length.

No coprimality hypothesis is stated in the question, so the repeated-root cyclic code case must also be distinguished. Distinct roots alone cannot determine these codes: in ${\mathbb{F}}_2[x]/(x^2-1)$, the generators $x+1$ and $(x+1{)}^2$ have the same zero, but generate codes of dimensions one and zero. In general write $g={\prod }_i(x-{\alpha }_i{)}^{m_i}$ in $E[x]$. The correct checks areusing Hasse derivatives. Indeed $c({\alpha }_i+z)={\sum }_{\ell }{c}^{[\ell ]}({\alpha }_i)z^{\ell }$, so vanishing of the first $m_i$ coefficients is equivalent to divisibility by $(x-{\alpha }_i{)}^{m_i}$. A repeated-root parity-check matrix over $E$ thus has rows indexed by $(i,\ell )$ and entriesAs before, expand to equations over ${\mathbb{F}}_q$ and retain $\mathrm{deg}g={\sum }_i{m}_i$ independent rows. The ordinary root-evaluation matrix is exactly the special case $m_i=1$.

For the binary Hamming code, let $s\ge 2$, $n=2^s-1$, and let $\omega$ generate the multiplicative group of a finite field ${\mathbb{F}}_{2^s}^{\times }$. This is possible because that group is a cyclic group. Choose a basis of ${\mathbb{F}}_{2^s}$ over ${\mathbb{F}}_2$. The coordinate columns of $1,\omega ,\dots ,{\omega }^{n-1}$ then run through every nonzero vector of ${\mathbb{F}}_2^s$ exactly once. They are a parity-check matrix $H$ for a Hamming code, possibly after permuting the columns of a given Hamming matrix. Thusis equivalent to the Hamming code. Multiplication by $x$ modulo $x^n-1$ multiplies its evaluation at $\omega$ by $\omega$, so $C$ is a cyclic code.

The parity-check matrix has rank $s$ because its columns contain a basis. It has no zero column or repeated column, so no nonzero word of weight one or two is in its kernel. Two distinct nonzero columns have a nonzero sum, which is a third distinct column; these three columns give a word of weight three. Hence $C$ has parameters $[2^s-1,2^s-s-1,3]$.

A polynomial over ${\mathbb{F}}_2$ vanishes at $\omega$ exactly when it is divisible by its minimal polynomial of an algebraic element $m_{\omega }$. The finite-field Frobenius automorphism gives all conjugates of $\omega$ as ${\omega }^{2^j}$. Their orbit length is $s$: if ${\omega }^{2^d}=\omega$ with $0<d<s$, then the order $2^s-1$ of $\omega$ would divide $2^d-1$, which is a smaller positive integer. Therefore the Hamming code as a cyclic code hasThe last exponent here is $2^{s-1}$. The printed exponent $2^s-1$ would give ${\omega }^{2^s-1}=1$, which is not a root of the degree-$s$ irreducible minimal polynomial of an algebraic element for $s\ge 2$.

Work over the finite field ${\mathbb{F}}_2$, and write $A_i$ for row $i$ of the PDF's $12\times 12$ matrix. The first row has Hamming weight eleven; all other rows have Hamming weight seven. To check their intersections economically, index the last eleven columns modulo eleven. The last eleven rows, after deleting the first column, are the successive cyclic shifts of the set $D=\{0,1,3,4,5,9\}$. Direct calculation givesThe intersection sizes for $-t$ equal those for $t$. Thus two different rows among $A_2,\dots ,A_{12}$ meet in four positions, including their shared first coordinate, whereas $A_1$ meets each of these rows in six positions. All these intersection sizes are even numbers, while each row weight is an odd number. Consequently $A{A}^T=I$. The first row and column agree, and the entry of the last eleven-by-eleven block depends only on the sum of its row and column indices modulo eleven, because successive rows are left shifts. Thus $A$ is a symmetric matrix, so $A^2=I$.

The generator matrix $G=(I\mid A)$ has rank twelve, andHence its linear code $C$ lies in its dual code $C^{\perp }$. Both have dimension twelve, so $C=C^{\perp }$: it is a self-dual code. Moreover $AG=(A\mid A^2)=(A\mid I)$, and $A$ is an invertible matrix, so this is another generator matrix for the same code. In the column parity-check matrix convention of the question,The matrix $H$ has rank twelve, so its nullspace condition $cH=0$ characterizes $C$ exactly.

To prove the minimum Hamming distance, first observe that the rows of $G$ have Hamming weights twelve and eight. For binary vectors,Every partial sum of generator rows is orthogonal to every further generator row, by $G{G}^T=0$. Its intersection with that row therefore contains an even number of positions. Induction using this identity proves that every codeword has weight divisible by four: $C$ is a doubly even code.

The systematic-matrix proof of extended Golay distance now excludes weight four. Write a codeword as $(u,uA)$ and put $k=\mathrm{wt}(u)$. If its total weight were four, $1\le k\le 4$. For $k=1$, the right half is a row of $A$ and has weight seven or eleven. For $k=2$, the right half is the sum of two distinct rows; the intersection counts above give weight $11+7-2\cdot 6=6$ or $7+7-2\cdot 4=6$. For $k=3$, the right half would be a unit vector, but then $u=(uA)A$ would be a row of $A$, of weight seven or eleven. For $k=4$, the right half would vanish, contradicting invertibility of $A$. Thus no nonzero word has weight four. Every nonzero weight is consequently at least eight, and any generator row other than the first attains eight. Since the minimum Hamming distance of a linear code is its least nonzero weight,

Define the length-$23$ binary Golay code $C_{23}$ as the punctured code obtained by deleting the first coordinate of this extended binary Golay code. This puncturing is injective on $C$, because a nonzero word in its kernel would have weight one. Thus $\dim C_{23}=12$, and deleting one coordinate gives $d(C_{23})\ge 7$. The sum of the first two generator rows has weight eight and first coordinate one, so its puncture has weight seven. Therefore $d(C_{23})=7$. In fact any coordinate can be punctured: every left coordinate except the first occurs in a weight-eight generator row, the first occurs in the sum just used, and every right coordinate occurs in at least one of the weight-eight generator rows.

The radius-three Hamming balls around the $2^{12}$ words of $C_{23}$ are disjoint, since two centers in intersecting balls would have Hamming distance at most six. Each ball containswords. Their combined size is $2^{12}{2}^{11}=2^{23}$, the size of the entire binary Hamming space. Hence

For decoding in $C$, write the received word as $y=c+(p,q)$, where $(p,q)$ is the unknown error in its two halves. Its syndrome isLet $e_i$ denote the length-twelve unit vector. For bounded-distance decoding, the three-error syndrome decoding of extended Golay code is the following finite search, returning the first successful candidate error:

Every returned candidate has total Hamming weight at most three and the required syndrome. Conversely, an error of total weight at most three has a half of weight zero or one. The tests exhaust respectively $q=0$, $q=e_i$, $p=0$, and $p=e_i$, so they find every such error. Two distinct successful candidates would differ by a nonzero codeword of weight at most six, contradicting $d(C)=8$. Thus the result is unique, and the decoded word is $y+(p,q)$. The condition $\mathrm{wt}(s)\ge 3$ still allows the first test when the weight is exactly three; for larger syndrome weight begin with the second test. A large syndrome weight alone does not imply more than three errors.

The decoder corrects every error of weight at most three; failure means that the received word is outside all radius-three decoding balls. Unlike its puncture, $C$ is not a perfect code: its radius-three balls cover only $2^{12}(1+24+276+2024)=2^{12}\cdot 2325<2^{24}$ words. Without the three-error assumption, a successful test identifies a nearby codeword but need not identify the transmitted word.

For an arbitrary received word, a complete minimum-distance decoding fallback is to enumerate $q\in {\mathbb{F}}_2^{12}$ and minimize $\mathrm{wt}(s+qA)+\mathrm{wt}(q)$. Every error with the observed syndrome has exactly the form $(s+qA,q)$, so a minimizer gives a nearest codeword $y+(s+qA,q)$. Report all minimizers if there is a tie. This also decodes outside the guaranteed radius in the nearest-word sense, while making no unsupported claim that the transmitted word is determined. Thus a syndrome of weight at least three alone is insufficient for guaranteed recovery; either the three-error hypothesis or a choice among nearest words is needed.

There are two necessary qualifications to the printed formula. Critical points satisfy $g^{\prime }=0$, not $g^{\prime }=1$. At a point with $g^{\prime }=1$, the local degree is one and the printed summand is zero. In addition, $\log \Vert g^{\prime }(0)\Vert$ is finite only when $g^{\prime }(0)\ne 0$; constant maps and origin-critical maps need separate treatment.

These are genuine issues even for otherwise ordinary disc maps. The map $g(z)=(z-1/2{)}^2/4$ maps the unit disc into itself and has $g^{\prime }(0)\ne 0$. Its derivative never equals one in the disc, so the printed count is zero, but it has a ramification point at $1/2$ of multiplicity one. For $R>1/2$ the correct identity has the additional term $\log (2R)$, proving that the displayed identity with the literal printed count is false. Also $g(z)=z^2$ shows the undefined basepoint logarithm in an origin-critical example.

Prove the intended identity first for a nonconstant map with $g^{\prime }(0)\ne 0$. Let $H(z)=2|g^{\prime }(z)|/(1-|g(z){|}^2)$ be its hyperbolic derivative density and $u=\log H$. Away from derivative zeros, $\log |g^{\prime }|$ is harmonic, and direct differentiation givesAt a zero $a$ of $g^{\prime }$ of multiplicity $m_a$, factor $g^{\prime }=(z-a{)}^{m_a}h$ with $h(a)\ne 0$. Its logarithm contains $m_a\log |z-a|$, whose distributional Laplacian is $2\pi m_a{\delta }_a$. ThusThe local map degree is $m_a+1$, so this is the required excess-degree weighting.

For a smooth function, differentiating its circular mean and applying the divergence theorem gives ${\overline{u}}^{\prime }(r)=(2\pi r{)}^{-1}{\int }_{|z|<r}\Delta udA$. Integrating in $r$ gives the logarithmic Green-Jensen formula. Factoring the isolated logarithmic singularities extends it to the present $u$:Substitution yields the critical-point Jensen identity for the hyperbolic derivativewhere $N_{\mathrm{crit}}={\sum }_{|a|<R:g^{\prime }(a)=0}{m}_a\log (R/|a|)$. This is the requested formula with the critical-point typo corrected. Initially choose a circle containing no ramification point on its boundary; continuity and integrability of logarithmic boundary singularities extend the result to the remaining radii.

By Schwarz-Pick theorem, $H(z)\le 2/(1-|z{|}^2)$. ThereforeThe normalized hyperbolic distance is $\rho (R)=\log ((1+R)/(1-R))$, andConsequentlyOne can take $C_1=1$ and $C_2=\log (2/H(0))\ge 0$. Since the corrected count is nonnegative in the noncritical-basepoint case, this also proves the growth bound for $T_{\mathbb{D}}$ with the literal printed, identically zero count, though not its false identity.

For completeness, if $g^{\prime }$ vanishes to order $m\ge 1$ at zero, put $c={\lim }_{z\to 0}H(z)/|z{|}^m>0$ andApply the same formula to $\log H-m\log |z|$, which is regular at zero. It givesThe origin contribution is a regularized Jensen term, not the undefined $\log (R/0)$. If one instead omits the origin term, the upper bound gains $-m\log R$; this is bounded for $R\ge 1/2$, while the characteristic and off-origin count are bounded on any smaller compact disc. Thus a bound $C_1\rho +C_2$ still holds for that nonnegative-count convention after enlarging $C_2$. For a constant map $H=0$ and $T_{\mathbb{D}}=0$, so its characteristic growth bound is trivial; the logarithmic identity and a finite critical-divisor count are not defined. These qualifications resolve all maps allowed by the original opening sentence without asserting an undefined equality.

If $\varphi$ is identically zero there are no exceptions. Otherwise choose $x_0$ with $\varphi (x_0)>0$ and put $I_{+}=\{x\ge x_0:{\varphi }^{\prime }(x)>\varphi (x{)}^2\}$. Monotonicity implies $\varphi (x)>0$ thereafter. On this set, $1<{\varphi }^{\prime }/{\varphi }^2$, whenceAdding the finite initial interval $[0,x_0]$ provesThis derivative growth outside a finite-measure set controls exceptional radii in Nevanlinna estimates. For example let $T_s$ be the smooth spherical characteristic and $A(r)=r{T}_s^{\prime }(r)$ its increasing area-counting function. Apply the lemma to $T_s+1$ and $A+1$: outside the union of two finite-measure sets,Their logarithms are consequently $O(\log r+\log (T_s+1))$. Such derivative/area bounds in estimates from the Poisson-Jensen formula give the Nevanlinna logarithmic derivative lemma, $m(r,f^{\prime }/f)=O({\log }^{+}{T}_f+\log r)$ outside a finite-length set. The second main theorem uses that estimate as its error term. The elementary growth lemma controls that error and its exceptional set; it is not itself a substitute for the analytic estimates.

We use the truncated second main theorem stated in the preceding solution, together with the fact that a transcendental meromorphic function has $T_f(r)/\log r\to \infty$. Here is a justification of the latter fact. If there are infinitely many poles, fixing any arbitrarily large finite pole count gives $N(r;\infty )\ge A\log r-O_A(1)$. If there are only finitely many poles, multiply by a polynomial $p$ removing them to obtain a transcendental entire function $h=pf$. Its Taylor series has nonzero coefficients of arbitrarily high degrees $n$. Cauchy's coefficient estimate gives $\log M_h(r/2)\ge n\log r-O_n(1)$; the subharmonic function Poisson estimate gives $\log M_h(r/2)\le 3m(r,h)$. Since $T_h\le T_f+O(\log r)$, letting $n$ be arbitrarily large proves the claimed ratio limit. Thus the second-theorem error is $o(T_f)$ along large nonexceptional radii.

Let $N_{\mathrm{simple}}(r;a)$ count just the simple $a$-points. A multiple $a$-point of degree $m\ge 2$ contributes one to the truncated count and at least two to the full count; a simple point contributes one to each. Hence, with the same positive logarithmic weights for large radii,If each of the five values had only finitely many simple preimages, each simple counting function would be $O(\log r)$. Summing and using the first main theorem would give ${\sum }_{j=1}^5\overline{N}(r;a_j)\le (5/2)T_f+O(\log r)$. But the second theorem requires $3T_f\le \sum \overline{N}+o(T_f)$, a contradiction. This proves the stronger result five values force infinitely many simple preimages:In particular more than one simple zero is necessary, but more than one target with simple zeros is not necessary.

For the last distinction, take a nonsingular Weierstrass elliptic function scaled so that ${\wp }^{\prime 2}=4\wp (\wp -1)(\wp +1)$; it has branch values $-1,0,1,\infty$. These are the four totally ramified Weierstrass values: finite branch preimages have local degree two, and all poles are double. SetThe first four targets are the images of those branch values under the Möbius transformation. Their preimages remain double; at a lattice pole, for example, $f(z)\sim (z-z_{\ast }{)}^2$. The last target corresponds to $\wp =3$, where ${\wp }^{\prime 2}=96\ne 0$, so every such preimage is simple. The degree-two torus map attains that regular value, and periodicity produces infinitely many preimages in the plane. This nonconstant elliptic function is transcendental because it has infinitely many poles. Exactly one of the five selected finite targets therefore has simple preimages.

The growth order of a meromorphic function isThe order of the integrated count is defined analogously using ${\log }^{+}N(R;a)$, with an identically zero count assigned order zero. Constants have function order zero. These are growth orders, not local zero or pole orders. For nonconstant $f$, the first main theorem gives $\rho (N(\cdot ;a))\le \rho (f)$ for every target.

Use the truncated Nevanlinna second main theorem in the following standard form: for distinct fixed targets $a_1,\dots ,a_q$,outside an exceptional set of radii of finite linear measure. For finite order the error is $O(\log R)$; replacing each truncated count by its full count preserves the inequality.

Suppose $0<\rho (f)<\infty$ and three targets have counting orders below $\rho (f)$. Choose $\mu$ strictly between the maximum of their three orders and $\rho (f)$. Each full count is at most $R^{\mu }$ eventually. The theorem with $q=3$ then gives $T_f(R)\le C{R}^{\mu }$ for sufficiently large radii outside the exceptional set. Its tail measure is eventually less than one, so every interval $[R,R+1]$ contains a nonexceptional radius $R^{\prime }$. Monotonicity of the characteristic yields $T_f(R)\le T_f(R^{\prime })\le C(R+1{)}^{\mu }$ for all large $R$. This contradicts its order. If $\rho (f)=0$, all the counting orders are already zero. Hence the counting-order exceptions for a finite-order meromorphic function satisfyThe exponential has order one but omits both zero and infinity, so those two counts are zero; this realizes two exceptions.

For a Möbius map $U(w)=(aw+b)/(cw+d)$ with $ad-bc\ne 0$, translation and multiplication by a nonzero constant change $T$ by $O(1)$, as follows directly from the proximity inequalities and unchanged pole multiplicities. The first main theorem also gives $T(1/h)=T(h)+O(1)$. If $c=0$, $U$ is affine. If $c\ne 0$, write $U(w)=a/c+K/(cw+d)$ with $K\ne 0$ and use these three elementary operations. Thus $T_{U\circ f}=T_f+O(1)$, proving

For the sum, a pole of $f_1+f_2$ has order no larger than the sum of the two pole orders, andTherefore $T_{f_1+f_2}\le T_{f_1}+T_{f_2}+O(1)$ andIf $\rho (f_1)>\rho (f_2)$, apply the same inequality to $f_1=(f_1+f_2)-f_2$. It forces $\rho (f_1)\le \max (\rho (f_1+f_2),\rho (f_2))$, hence the sum's order equals $\rho (f_1)$. The reversed case is identical. This reasoning also handles an infinite larger order. For equal orders cancellation can be strict: $f_1=e^z$, $f_2=-e^z$ both have order one, but their sum is zero of order zero.

For a nonconstant meromorphic map, write $T_f(R)=m(R,f)+N(R;\infty )$ in the usual normalization, where $m=(2\pi {)}^{-1}\int {\log }^{+}|f(R{e}^{i\theta })|d\theta$. Let $N(R;a)$ count $a$-points with their local degrees, and let $\overline{N}(R;a)$ count each distinct point once, using the same integrated logarithmic weights. At infinity the local degree is the pole order. The Nevanlinna deficiency and Nevanlinna ramification index areThe latter is an asymptotic excess-multiplicity index, not the integer local ramification degree. The Nevanlinna first main theorem gives $N(R;a)\le T_f(R)+O(1)$ and identifies deficiency with the lower limiting normalized proximity. The target $a$ ranges over the Riemann sphere, not just the real line.

The exponential is entire and has no poles. ConsequentlyThus $c=1/\pi$ in this normalization.

To obtain the rational-composition growth, represent the nonconstant degree-$d$ sphere map by relatively prime homogeneous polynomials $(P,Q)$ of degree $d$. Their joint norm on the unit sphere in ${\mathbb{C}}^2$ has a positive minimum and finite maximum: simultaneous vanishing would contradict relative primeness on the projective line. Homogeneity therefore gives constants $0<A\le B<\infty$ withApply this to the entire nonvanishing lift $(e^z,1)$. The logarithmic joint norm differs from $d\log \Vert (e^z,1)\Vert$ by a bounded function. Its circular mean minus the value at zero is the spherical characteristic. It differs from the ordinary characteristic by $O(1)$: Jensen's formula applied to the entire denominator counts its zeros, whilecontrols the proximity replacement. If the denominator vanishes at zero, factor its zero and use its leading coefficient in Jensen's formula; the discrepancy is still a basepoint-dependent constant. This proves the rational composition law for the Nevanlinna characteristic here and givesIf $U$ is constant, $d=0$ and its characteristic is bounded instead.

For a simultaneous nonzero deficiency and ramification example choosea degree-three polynomial composed with the exponential. Its characteristic is $3R/\pi +O(1)$. Its only zeros are $2\pi in$, $n\in \mathbb{Z}$, all of multiplicity two. The number of distinct such points in a large disc is $R/\pi +O(1)$, so integration of their count givesThe origin contribution is handled by its usual logarithmic counting term. ThereforeThis is simultaneous deficiency and ramification for an exponential polynomial: the missing exponential value contributes a deficit, while the attained value is attained with double multiplicity.

Use the curvature-minus-one normalization of the hyperbolic metric:The associated distance is $d(z,w)=2\mathrm{artanh}|(z-w)/(1-\overline{w}z)|$. A connected Riemann surface has its complete canonical Poincare metric on a Riemann surface precisely when its universal cover is conformally the unit disc. By the uniformization theorem, the other simply connected covering types are the complex plane and Riemann sphere. Disc automorphisms preserve $\lambda (z)|dz|$, as direct differentiation of $(z-a)/(1-\overline{a}z)$ shows; therefore the metric descends through the deck group. This is the uniformization notion of hyperbolicity, not the different potential-theoretic Green-function classification.

First prove the needed Schwarz lemma. If $F:\mathbb{D}\to \mathbb{D}$ is holomorphic and $F(0)=0$, then $F(z)/z$ extends holomorphically at zero. On $|z|=r<1$ its modulus is at most $1/r$. The maximum modulus principle and $r\uparrow 1$ give $|F(z)|\le |z|$ and $|F^{\prime }(0)|\le 1$.

Write ${\psi }_a(z)=(z-a)/(1-\overline{a}z)$. Conjugating $f$ by the source and target disc automorphisms, ${\psi }_{f(a)}\circ f\circ {\psi }_a^{-1}$ fixes zero. Applying the derivative bound givesIntegrate along any piecewise smooth path and then take the infimum of lengths: $d(f(z),f(w))\le d(z,w)$. This proves the Schwarz-Pick theorem. Contraction means nonexpansion, not a uniform Lipschitz constant strictly smaller than one; automorphisms preserve all distances.