GNU Free Documentation License, Version 1.2

The functions in the `NumTheory`

file are predominantly basic
operations from number theory. Most of the functions may be
applied to machine integers or big integers (*i.e.* values of
type `BigInt`

). Please recall that computational number theory is
not the primary remit of CoCoALib, so do not expect to find a
complete collection of operations here -- you would do better to
look at Victor Shoup's NTL (Number Theory Library), or PARI/GP,
or some other specialized library/system.

See also `IntOperations`

for very basic arithmetic operations on integers,
and `BigRat`

for very basic arithmetic operations on rational numbers.

Several of these functions give errors if they are handed unsuitable values:
unless otherwise indicated below the error is of type `ERR::BadArg`

.
All functions expecting a modulus will throw an error if the modulus is
less than 2 (or an `unsigned long`

value too large to fit into a `long`

).

The main functions available are:

`gcd(m,n)`

computes the non-negative gcd of`m`

and`n`

. If both args are machine integers, the result is of type`long`

(or error if it does not fit); otherwise result is of type`BigInt`

.`ExtGcd(a,b,m,n)`

computes the non-negative gcd of`m`

and`n`

; also sets`a`

and`b`

so that`gcd = a*m+b*n`

. If`m`

and`n`

are machine integers then`a`

and`b`

must be of type (signed)`long`

. If`m`

and`n`

are of type`BigInt`

then`a`

and`b`

must also be of type`BigInt`

. The cofactors`a`

and`b`

satisfy`abs(a) <= abs(n)/2g`

and`abs(b) <= abs(m)/2g`

where`g`

is the gcd (inequalities are strict if possible). Error if`m=n=0`

.`InvMod(r,m)`

computes the least positive inverse of`r`

modulo`m`

; throws error (`ERR::DivByZero`

) if the inverse does not exist. Throws error (`ERR::BadModulus`

) if`m < 2`

(or too big for`long`

). Result is of type`long`

if`m`

is a machine integer; otherwise result is of type`BigInt`

.`InvModNoCheck(r,m)`

computes the least positive inverse of`r`

modulo`m`

;**ASSUMES**`0 <= r < m`

and`2 <= m <= MaxLong`

; result is a`long`

. Throws error`ERR::DivByZero`

if`gcd(r,m)`

is not 1.`lcm(m,n)`

computes the non-negative lcm of`m`

and`n`

. If both args are machine integers, the result is of type`long`

; otherwise result is of type`BigInt`

. Gives error`ERR::ArgTooBig`

if the lcm of two machine integers is too large to fit into an`long`

.`eratosthenes(n)`

build`vector<bool>`

sieve of Eratosthenes up to`n`

; entry`k`

corresponds to integer`2*k+1`

; max valid index is`n/2`

`IsPrime(n)`

tests the positive number`n`

for primality (may be**very slow**for larger numbers). Gives error if`n <= 0`

.`IsProbPrime(n)`

tests the positive number`n`

for primality (fairly fast for large numbers, but in very rare cases may falsely declare a number to be prime). Gives error if`n <= 0`

.`IsProbPrime(n,iters)`

tests the positive number`n`

for primality; performs`iters`

iterations of the Miller-Rabin test (default value is 25). Gives error if`n <= 0`

.`NextPrime(n)`

and`PrevPrime(n)`

compute next or previous positive prime (fitting into a machine`long`

); returns 0 if none exists. Gives error if`n <= 0`

.`NextProbPrime(N)`

and`PrevProbPrime(N)`

compute next or previous positive probable prime (uses`IsProbPrime`

). Gives error if`N <= 0`

.`SmoothFactor(n,limit)`

finds small prime factors of`n`

(up to & including the specified`limit`

); result is a`factorization`

object. Gives error if`limit`

is not positive or too large to fit into a`long`

.`factor(n)`

finds the complete factorization of`n`

(**WARNING**may be**very slow**for large numbers); NB**implementation incomplete**`SmallestNonDivisor(n)`

finds smallest (positive prime) non-divisor of`n`

; if`n=0`

throws`ERR::NotNonZero`

.`IsSqFree(n)`

returns`true`

if`n`

is square-free, otherwise`false`

; for`BigInt`

result is a`bool3`

`FactorMultiplicity(b,n)`

find largest`k`

such that`power(b,k)`

divides`n`

(error if`b < 2`

or`n`

is zero)`EulerPhi(n)`

computes Euler's*totient*function of the positive number`n`

(*i.e.*the number of integers up to`n`

which are coprime to`n`

, or the degree of the`n`

-th cyclotomic polynomial). Gives error if`n <= 0`

.`PrimitiveRoot(p)`

computes the least positive primitive root for the positive prime`p`

. Gives error if`p`

is not a positive prime.**WARNING**May be**very slow**for large`p`

(because it must factorize`p-1`

).`MultiplicativeOrderMod(res,mod)`

computes multiplicative order of`res`

modulo`mod`

. Throws error`ERR::BadArg`

if`mod < 2`

or`gcd(res,mod)`

is not 1.`PowerMod(base,exp,modulus)`

computes`base`

to the power`exp`

modulo`modulus`

; result is least non-negative residue. If`modulus`

is a machine integer then the result is of type`long`

(or error if it does not fit), otherwise the result is of type`BigInt`

. Gives error if`modulus <= 1`

. Gives`ERR::DivByZero`

if`exp`

is negative and`base`

cannot be inverted. If`base`

and`exp`

are both zero, it produces 1.`SimplestBigRatBetween(A,B)`

computes the simplest rational between`A`

and`B`

`SimplestBinaryRatBetween(A,B)`

computes the simplest binary rational between`A`

and`B`

; result is a rational of form N*2^k where the integer N is minimal.`BinomialRepr(N,r)`

produces the repr of`N`

as a sum of binomial coeffs with "denoms"`r, r-1, r-2, ...`

`NumPartitions(n)`

computes number of partitions of`n`

,*i.e.*how many distinct ways to write`n`

as a sum of positive integers (error if`n`

is negative)

Several of these functions give errors if they are handed unsuitable values:
unless otherwise indicated below the error is of type `ERR::BadArg`

.

Recall that any real number has an expansion as a **continued fraction**
(*e.g.* see Hardy & Wright for definition and many properties). This expansion
is finite for any rational number. We adopt the following conventions which
guarantee that the expansion is unique:

- the last partial quotient is greater than 1 (except for the expansion of integers <= 1)
- only the very first partial quotient may be non-positive.

For example, with these conventions the expansion of -7/3 is (-3, 1, 2).

The main functions available are:

`ContFracIter(q)`

constructs a new continued fraction iterator object`IsEnded(CFIter)`

true iff the iterator has moved past the last*partial quotient*`IsFinal(CFIter)`

true iff the iterator is at the last*partial quotient*`quot(CFIter)`

gives the current*partial quotient*as a`BigInt`

(or throws`ERR::IterEnded`

)`*CFIter`

gives the current*partial quotient*as a`BigInt`

(or throws`ERR::IterEnded`

)`++CFIter`

moves to next*partial quotient*(or throws`ERR::IterEnded`

)`ContFracApproximant()`

for constructing a rational from its continued fraction quotients`CFA.myAppendQuot(q)`

appends the quotient`q`

to the continued fraction`CFA.myRational()`

returns the rational associated to the continued fraction`CFApproximantsIter(q)`

constructs a new continued fraction approximant iterator`IsEnded(CFAIter)`

true iff the iterator has moved past the last "partial quotient"`*CFAIter`

gives the current continued fraction approximant as a`BigRat`

(or throws`ERR::IterEnded`

)`++CFAIter`

moves to next approximant (or throws`ERR::IterEnded`

)`CFApprox(q,eps)`

gives the simplest cont. frac. approximant to`q`

with relative error at most`eps`

CoCoALib offers the class `CRTMill`

for reconstructing an integer from
several residue-modulus pairs via Chinese Remaindering. At the moment the
moduli from distinct pairs must be coprime.

The operations available are:

`CRTMill()`

ctor; initially the residue is 0 and the modulus is 1`CRT.myAddInfo(res,mod)`

give a new residue-modulus pair to the`CRTMill`

(error if`mod`

is not coprime to all previous moduli)`CRT.myAddInfo(res,mod,CRTMill::CoprimeModulus)`

give a new residue-modulus pair to the`CRTMill`

asserting that`mod`

is coprime to all previous moduli --`CRTMill::CoprimeModulus`

is a constant`CombinedResidue(CRT)`

the combined residue with absolute value less than or equal to`CombinedModulus(CRT)/2`

`CombinedModulus(CRT)`

the product of the moduli of all pairs given to the mill

CoCoALib offers two heuristic methods for reconstructing rationals from residue-modulus pairs; they have the same user interface but internally one algorithm is based on continued fractions while the other uses lattice reduction. The methods are heuristic, so may (rarely) produce an incorrect result.

**NOTE** the heuristic requires the (combined) modulus to be a certain
amount larger than strictly necessary to reconstruct the correct
answer (assuming perfect bounds are known). In practice, this means
that **the methods always fail if the combined modulus is too small**.

The constructors available are:

`RatReconstructByContFrac(threshold)`

ctor for continued fraction method mill with given threshold (0 --> use default)`RatReconstructByLattice(SafetyFactor)`

ctor for lattice method mill with given`SafetyFactor`

(0 --> use default)

The operations available are:

`reconstructor.myAddInfo(res,mod)`

give a new residue-modulus pair to the reconstructor`IsConvincing(reconstructor)`

gives`true`

iff the mill can produce a*convincing*result`ReconstructedRat(reconstructor)`

gives the reconstructed rational (or an error if`IsConvincing`

is not true).`BadMFactor(reconstructor)`

gives the "bad factor" of the combined modulus.

There is also a function for deterministic rational reconstruction which requires certain bounds to be given in input. It uses the continued fraction method.

`RatReconstructWithBounds(e,P,Q,res,mod)`

where`e`

is upper bound for number of "bad" moduli,`P`

and`Q`

are upper bounds for numerator and denominator of the rational to be reconstructed, and`(res[i],mod[i])`

is a residue-modulus pair with distinct moduli being coprime.

Correctness of `ExtendedEuclideanAlg`

is not immediately clear,
because the cofactor variables could conceivably overflow -- in fact
this cannot happen (at least on a binary computer): for a proof see
Shoup's book *A Computational Introduction to Number Theory and Algebra*,
in particular Theorem 4.3 and the comment immediately following it. There is
just one line where a harmless "overflow" could occur -- it is commented in
the code.

I have decided to make `ExtGcd`

give an error if the inputs are both zero
because this is an exceptional case, and so should be handled specially. I
note that `mpz_exgcd`

accepts this case, and returns two zero cofactors; so if we
decide to accept this case, we should do the same -- this all fits in well with
the (reasonable/good) principle that "zero inputs have zero cofactors".

Several functions are more complicated than you might expect because I wanted them
to be correct for all possible machine integer inputs (*e.g.* including the
most negative `long`

value).

In some cases the function which does all the work is implemented as a file
local function operating on `unsigned long`

values: the function should
normally be used only via the "dispatch" functions whose args are of type
`MachineInt`

or `BigInt`

.

The impl of `eratosthenes`

is fairly straightforward given that I chose
to represent only odd numbers in the table: the `k`

-th entry corresponds
to the integer `2*k+1`

. Overflow cannot occur: recall that the table
size is at most half the biggest `long`

. I'm hoping that C++11 will
avoid the cost of copying the result upon returning. Anyway, I think the
code is a decent compromise between readability, speed and space efficiency.

The continued fraction functions are all pretty simple. The only tricky
part is that the "end" of the `ContFracIter`

is represented by both
`myFrac`

and `myQuot`

being zero. This means that a newly created
iterator for zero is already ended.

`CFApproximantsIter`

delegates most of the work to `ContFracIter`

.

Several functions return `long`

values when perhaps `unsigned long`

would possibly be better choice (since it offers a greater range, and
in the case of `gcd`

it would permit the fn to return a result always,
rather than report "overflow"). The choice of return type was dictated
by the coding conventions, which were in turn dictated by the risks of nasty
surprises to unwary users unfamiliar with the foibles of unsigned values in C++.

Should there also be procedural forms of functions which return `BigInt`

values?
(*e.g.* gcd, lcm, InvMod, PowerMod, and so on). (2016-06-27 this will probably become irrelevant when using "move" semantics in C++11).

Certain implementations of `PowerMod`

should be improved (*e.g.* to use
`PowerModSmallModulus`

whenever possible). Is behaviour for 0^0 correct?

`LucasTest`

should produce a certificate, and be made publicly accessible.

How should the cont frac iterators be printed out???

`ContFracIter`

could be rather more efficient for rationals having
very large numerator and denominator. One way would be to compute with
num and den divided by the same large factor (probably a power of 2),
and taking care to monitor how accurate these "scaled" num and den are.
I'll wait until there is a real need before implementing (as I expect
it will turn out a bit messy).

`CFApproximantsIter::operator++()`

should be made more efficient.