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pqc/external/flint-2.4.3/ulong_extras/doc/ulong_extras.txt
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/*=============================================================================
This file is part of FLINT.
FLINT is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
FLINT is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with FLINT; if not, write to the Free Software
Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
=============================================================================*/
/******************************************************************************
Copyright (C) 2009 William Hart
Copyright (C) 2010 Sebastian Pancratz
Copyright (C) 2010 Fredrik Johansson
******************************************************************************/
*******************************************************************************
Random functions
*******************************************************************************
void n_randinit(flint_rand_t state)
Initialise a random state for use in random functions.
void n_randclear(flint_rand_t state)
Release any memory used by a random state.
mp_limb_t n_randlimb(flint_rand_t state)
Returns a uniformly pseudo random limb.
The algorithm generates two random half limbs $s_j$, $j = 0, 1$,
by iterating respectively $v_{i+1} = (v_i a + b) \bmod{p_j}$ for
some initial seed $v_0$, randomly chosen values $a$ and $b$ and
\code{p_0 = 4294967311 = nextprime(2^32)} on a 64-bit machine
and \code{p_0 = nextprime(2^16)} on a 32-bit machine and
\code{p_1 = nextprime(p_0)}.
mp_limb_t n_randbits(flint_rand_t state, unsigned int bits)
Returns a uniformly pseudo random number with the given number of
bits. The most significant bit is always set, unless zero is passed,
in which case zero is returned.
mp_limb_t n_randtest_bits(flint_rand_t state, int bits)
Returns a uniformly pseudo random number with the given number of
bits. The most significant bit is always set, unless zero is passed,
in which case zero is returned. The probability of a value with a
sparse binary representation being returned is increased. This
function is intended for use in test code.
mp_limb_t n_randint(flint_rand_t state, mp_limb_t limit)
Returns a uniformly pseudo random number up to but not including
the given limit. If zero is passed as a parameter, an entire random
limb is returned.
mp_limb_t n_randtest(flint_rand_t state)
Returns a pseudo random number with a random number of bits,
from $0$ to \code{FLINT_BITS}. The probability of the special
values $0$, $1$, \code{COEFF_MAX} and \code{WORD_MAX} is increased
as is the probability of a value with sparse binary representation.
This random function is mainly used for testing purposes.
This function is intended for use in test code.
mp_limb_t n_randtest_not_zero(flint_rand_t state)
As for \code{n_randtest()}, but does not return $0$.
This function is intended for use in test code.
mp_limb_t n_randprime(flint_rand_t state, unsigned slong bits, int proved)
Returns a random prime number (proved = 1) or probable prime (proved = 0)
with \code{bits} bits, where \code{bits} must be at least 2 and
at most \code{FLINT_BITS}.
mp_limb_t n_randtest_prime(flint_rand_t state, int proved)
Returns a random prime number (proved = 1) or probable prime (proved = 0)
with size randomly chosen between 2 and \code{FLINT_BITS} bits.
This function is intended for use in test code.
*******************************************************************************
Basic arithmetic
*******************************************************************************
mp_limb_t n_pow(mp_limb_t n, ulong exp)
Returns \code{n^exp}. No checking is done for overflow. The exponent
may be zero. We define $0^0 = 1$.
The algorithm simply uses a for loop. Repeated squaring is
unlikely to speed up this algorithm.
mp_limb_t n_flog(mp_limb_t n, mp_limb_t b)
Returns $\floor{\log_b x}$.
Assumes that $x \geq 1$ and $b \geq 2$.
mp_limb_t n_clog(mp_limb_t n, mp_limb_t b)
Returns $\ceil{\log_b x}$.
Assumes that $x \geq 1$ and $b \geq 2$.
*******************************************************************************
Miscellaneous
*******************************************************************************
ulong n_revbin(ulong in, ulong bits)
Returns the binary reverse of \code{in}, assuming it is the given
number of bits in length, e.g.\ \code{n_revbin(10110, 6)} will return
\code{110100}.
int n_sizeinbase(mp_limb_t n, int base)
Returns the exact number of digits needed to represent $n$ as a
string in base \code{base} assumed to be between 2 and 36.
Returns 1 when $n = 0$.
*******************************************************************************
Basic arithmetic with precomputed inverses
*******************************************************************************
mp_limb_t n_mod_precomp(mp_limb_t a, mp_limb_t n, double ninv)
Returns $a \bmod{n}$ given a precomputed inverse of $n$ computed
by\\ \code{n_precompute_inverse()}. We require \code{n < 2^FLINT_D_BITS}
and \code{a < 2^(FLINT_BITS-1)} and $0 \leq a < n^2$.
We assume the processor is in the standard round to nearest
mode. Thus \code{ninv} is correct to $53$ binary bits, the least
significant bit of which we shall call a place, and can be at most
half a place out. When $a$ is multiplied by $ninv$, the binary
representation of $a$ is exact and the mantissa is less than $2$, thus we
see that \code{a * ninv} can be at most one out in the mantissa. We now
truncate \code{a * ninv} to the nearest integer, which is always a round
down. Either we already have an integer, or we need to make a change down
of at least $1$ in the last place. In the latter case we either get
precisely the exact quotient or below it as when we rounded the
product to the nearest place we changed by at most half a place.
In the case that truncating to an integer takes us below the
exact quotient, we have rounded down by less than $1$ plus half a
place. But as the product is less than $n$ and $n$ is less than $2^{53}$,
half a place is less than $1$, thus we are out by less than $2$ from
the exact quotient, i.e.\ the quotient we have computed is the
quotient we are after or one too small. That leaves only the case
where we had to round up to the nearest place which happened to
be an integer, so that truncating to an integer didn't change
anything. But this implies that the exact quotient $a/n$ is less
than $2^{-54}$ from an integer. We deal with this rare case by
subtracting 1 from the quotient. Then the quotient we have computed is
either exactly what we are after, or one too small.
mp_limb_t n_mod2_precomp(mp_limb_t a, mp_limb_t n, double ninv)
Returns $a \bmod{n}$ given a precomputed inverse of $n$ computed by\\
\code{n_precompute_inverse()}. There are no restrictions on $a$ or
on $n$.
As for \code{n_mod_precomp()} for $n < 2^{53}$ and $a < n^2$ the
computed quotient is either what we are after or one too large or small.
We deal with these cases. Otherwise we can be sure that the
top $52$ bits of the quotient are computed correctly. We take
the remainder and adjust the quotient by multiplying the
remainder by \code{ninv} to compute another approximate quotient as
per \code{mod_precomp}. Now the remainder may be either
negative or positive, so the quotient we compute may be one
out in either direction.
mp_limb_t n_mod2_preinv(mp_limb_t a, mp_limb_t n, mp_limb_t ninv)
Returns $a \bmod{n}$ given a precomputed inverse of $n$ computed by
\code{n_preinvert_limb()}. There are no restrictions on $a$ or on $n$.
The old version of this function was implemented simply by
making use of\\ \code{udiv_qrnnd_preinv()}.
The new version uses the new algorithm of Granlund and
M\"oller~\citep{GraMol2010}. First $n$ is normalised and a
shifted into two limbs to compensate. Then their algorithm is
applied verbatim and the result shifted back.
% Torbjorn Granlund and Niels Moller
% Improved Division by Invariant Integers
% http://www.lysator.liu.se/~nisse/archive/draft-division-paper.pdf
mp_limb_t n_divrem2_precomp(mp_limb_t * q, mp_limb_t a, mp_limb_t n,
double npre)
Returns $a \bmod{n}$ given a precomputed inverse of $n$ computed by\\
\code{n_precompute_inverse()} and sets $q$ to the quotient. There
are no restrictions on $a$ or on $n$.
This is as for \code{n_mod2_precomp()} with some additional care taken
to retain the quotient information. There are also special
cases to deal with the case where $a$ is already reduced modulo
$n$ and where $n$ is $64$ bits and $a$ is not reduced modulo $n$.
mp_limb_t n_ll_mod_preinv(mp_limb_t a_hi, mp_limb_t a_lo,
mp_limb_t n, mp_limb_t ninv)
Returns $a \bmod{n}$ given a precomputed inverse of $n$ computed by
\code{n_preinvert_limb()}. There are no restrictions on $a$, which
will be two limbs \code{(a_hi, a_lo)}, or on $n$.
The old version of this function merely reduced the top limb
\code{a_hi} modulo $n$ so that \code{udiv_qrnnd_preinv()} could
be used.
The new version reduces the top limb modulo $n$ as per
\code{n_mod2_preinv()} and then the algorithm of Granlund and
M\"oller~\citep{GraMol2010} is used again to reduce modulo $n$.
% Torbjorn Granlund and Niels Moller
% Improved Division by Invariant Integers
% http://www.lysator.liu.se/~nisse/archive/draft-division-paper.pdf
mp_limb_t n_lll_mod_preinv(mp_limb_t a_hi, mp_limb_t a_mi,
mp_limb_t a_lo, mp_limb_t n, mp_limb_t ninv)
Returns $a \bmod{n}$, where $a$ has three limbs \code{(a_hi, a_mi, a_lo)},
given a precomputed inverse of $n$ computed by \code{n_preinvert_limb()}.
It is assumed that \code{a_hi} is reduced modulo $n$. There are no
restrictions on $n$.
This function uses the algorithm of Granlund and
M\"oller~\citep{GraMol2010} to first reduce the top two limbs
modulo $n$, then does the same on the bottom two limbs.
% Torbjorn Granlund and Niels Moller
% Improved Division by Invariant Integers
% http://www.lysator.liu.se/~nisse/archive/draft-division-paper.pdf
mp_limb_t n_mulmod_precomp(mp_limb_t a, mp_limb_t b, mp_limb_t n, double ninv)
Returns $a b \bmod{n}$ given a precomputed inverse of $n$
computed by\\ \code{n_precompute_inverse()}. We require
\code{n < 2^FLINT_D_BITS} and $0 \leq a, b < n$.
We assume the processor is in the standard round to nearest
mode. Thus \code{ninv} is correct to $53$ binary bits, the least
significant bit of which we shall call a place, and can be at most half
a place out. The product of $a$ and $b$ is computed with error at most
half a place. When \code{a * b} is multiplied by $ninv$ we find that the
exact quotient and computed quotient differ by less than two places. As
the quotient is less than $n$ this means that the exact quotient is at
most $1$ away from the computed quotient. We truncate this quotient to
an integer which reduces the value by less than $1$. We end up with a
value which can be no more than two above the quotient we are after and
no less than two below. However an argument similar to that for
\code{n_mod_precomp()} shows that the truncated computed quotient cannot
be two smaller than the truncated exact quotient. In other words the
computed integer quotient is at most two above and one below the quotient
we are after.
mp_limb_t n_mulmod2_preinv(mp_limb_t a, mp_limb_t b,
mp_limb_t n, mp_limb_t ninv)
Returns $a b \bmod{n}$ given a precomputed inverse of $n$ computed by\\
\code{n_preinvert_limb()}. There are no restrictions on $a$, $b$ or
on $n$. This is implemented by multiplying using \code{umul_ppmm()} and
then reducing using \code{n_ll_mod_preinv()}.
mp_limb_t n_mulmod_preinv(mp_limb_t a, mp_limb_t b, mp_limb_t n,
mp_limb_t ninv, ulong norm)
Returns $a b \pmod{n}$ given a precomputed inverse of $n$ computed by\\
\code{n_preinvert_limb()}, assuming $a$ and $b$ are reduced modulo $n$
and $n$ is normalised, i.e. with most significant bit set. There are
no other restrictions on $a$, $b$ or $n$.
The value \code{norm} is provided for convenience. As $n$ is required
to be normalised, it may be that $a$ and $b$ have been shifted to the
left by \code{norm} bits before calling the function. Their product
then has an extra factor of $2^\text{norm}$. Specifying a nonzero
\code{norm} will shift the product right by this many bits before
reducing it.
The algorithm use is that of Granlund and M\"oller~\citep{GraMol2010}.
% Torbjorn Granlund and Niels Moller
% Improved Division by Invariant Integers
% http://www.lysator.liu.se/~nisse/archive/draft-division-paper.pdf
*******************************************************************************
Greatest common divisor
*******************************************************************************
mp_limb_t n_gcd(mp_limb_t x, mp_limb_t y)
Returns the greatest common divisor $g$ of $x$ and $y$.
We require $x \geq y$.
The algorithm is a slight embelishment of the Euclidean algorithm
which uses some branches to avoid most divisions.
One wishes to compute the quotient and remainder of $u_3 / v_3$ without
division where possible. This is accomplished when $u_3 < 4 v_3$, i.e.\
the quotient is either $1$, $2$ or $3$.
We first compute $s = u_3 - v_3$. If $s < v_3$, i.e.\ $u_3 < 2 v_3$, we
know the quotient is $1$, else if $s < 2 v_3$, i.e.\ $u_3 < 3 v_3$ we
know the quotient is $2$. In the remaining cases, the quotient must
be $3$. When the quotient is $4$ or above, we use division. However this
happens rarely for generic inputs.
mp_limb_t n_gcd_full(mp_limb_t x, mp_limb_t y)
Returns the greatest common divisor $g$ of $x$ and $y$.
No assumptions are made about $x$ and $y$.
mp_limb_t n_gcdinv(mp_limb_t * a, mp_limb_t x, mp_limb_t y)
Returns the greatest common divisor $g$ of $x$ and $y$ and computes
$a$ such that $0 \leq a < y$ and $a x = \gcd(x, y) \bmod{y}$, when
this is defined. We require $0 \leq x < y$.
This is merely an adaption of the extended Euclidean algorithm with
appropriate normalisation.
mp_limb_t n_xgcd(mp_limb_t * a, mp_limb_t * b, mp_limb_t x, mp_limb_t y)
Returns the greatest common divisor $g$ of $x$ and $y$ and unsigned
values $a$ and $b$ such that $a x - b y = g$. We require $x \geq y$.
We claim that computing the extended greatest common divisor via the
Euclidean algorithm always results in cofactor $\abs{a} < x/2$,
$\abs{b} < x/2$, with perhaps some small degenerate exceptions.
We proceed by induction.
Suppose we are at some step of the algorithm, with $x_n = q y_n + r$
with $r \geq 1$, and suppose $1 = s y_n - t r$ with
$s < y_n / 2$, $t < y_n / 2$ by hypothesis.
Write $1 = s y_n - t (x_n - q y_n) = (s + t q) y_n - t x_n$.
It suffices to show that $(s + t q) < x_n / 2$ as $t < y_n / 2 < x_n / 2$,
which will complete the induction step.
But at the previous step in the backsubstitution we would have had
$1 = s r - c d$ with $s < r/2$ and $c < r/2$.
Then $s + t q < r/2 + y_n / 2 q = (r + q y_n)/2 = x_n / 2$.
See the documentation of \code{n_gcd()} for a description of the
branching in the algorithm, which is faster than using division.
*******************************************************************************
Jacobi and Kronecker symbols
*******************************************************************************
int n_jacobi(mp_limb_signed_t x, mp_limb_t y)
Computes the Jacobi symbol of $x \bmod{y}$. Assumes that $y$ is positive
and odd, and for performance reasons that $\gcd(x, y) = 1$.
This is just a straightforward application of the law of quadratic
reciprocity. For performance, divisions are replaced with some
comparisons and subtractions where possible.
int n_jacobi_unsigned(mp_limb_t x, mp_limb_t y)
Computes the Jacobi symbol, allowing $x$ to go up to a full limb.
*******************************************************************************
Modular Arithmetic
*******************************************************************************
mp_limb_t n_addmod(mp_limb_t a, mp_limb_t b, mp_limb_t n)
Returns $(a + b) \bmod{n}$.
mp_limb_t n_submod(mp_limb_t a, mp_limb_t b, mp_limb_t n)
Returns $(a - b) \bmod{n}$.
mp_limb_t n_invmod(mp_limb_t x, mp_limb_t y)
Returns a value $a$ such that $0 \leq a < y$ and
$a x = \gcd(x, y) \bmod{y}$, when this is defined.
We require $0 \leq x < y$.
Specifically, when $x$ is coprime to $y$, $a$ is the inverse
of $x$ in $\Z / y \Z$.
This is merely an adaption of the extended Euclidean algorithm
with appropriate normalisation.
mp_limb_t n_powmod_precomp(mp_limb_t a, mp_limb_signed_t exp,
mp_limb_t n, double npre)
Returns \code{a^exp} modulo $n$ given a precomputed inverse of $n$
computed by\\ \code{n_precompute_inverse()}. We require $n < 2^{53}$
and $0 \leq a < n$. There are no restrictions on \code{exp}, i.e.\
it can be negative.
This is implemented as a standard binary powering algorithm using
repeated squaring and reducing modulo $n$ at each step.
mp_limb_t n_powmod_ui_precomp(mp_limb_t a, mp_limb_t exp,
mp_limb_t n, double npre)
Returns \code{a^exp} modulo $n$ given a precomputed inverse of $n$
computed by\\ \code{n_precompute_inverse()}. We require $n < 2^{53}$
and $0 \leq a < n$. The exponent \code{exp} is unsigned and so
can be larger than allowed by \code{n_powmod_precomp}.
This is implemented as a standard binary powering algorithm using
repeated squaring and reducing modulo $n$ at each step.
mp_limb_t n_powmod(mp_limb_t a, mp_limb_signed_t exp, mp_limb_t n)
Returns \code{a^exp} modulo $n$. We require \code{n < 2^FLINT_D_BITS}
and $0 \leq a < n$. There are no restrictions on \code{exp}, i.e.\
it can be negative.
This is implemented by precomputing an inverse and calling the
\code{precomp} version of this function.
mp_limb_t n_powmod2_preinv(mp_limb_t a, mp_limb_signed_t exp, mp_limb_t n,
mp_limb_t ninv)
Returns \code{(a^exp) % n} given a precomputed inverse of $n$ computed
by \code{n_preinvert_limb()}. We require $0 \leq a < n$, but there are no
restrictions on $n$ or on \code{exp}, i.e.\ it can be negative.
This is implemented as a standard binary powering algorithm using
repeated squaring and reducing modulo $n$ at each step.
mp_limb_t n_powmod2(mp_limb_t a, mp_limb_signed_t exp, mp_limb_t n)
Returns \code{(a^exp) % n}. We require $0 \leq a < n$, but there are
no restrictions on $n$ or on \code{exp}, i.e.\ it can be negative.
This is implemented by precomputing an inverse limb and calling the
\code{preinv} version of this function.
mp_limb_t n_powmod2_ui_preinv(mp_limb_t a, mp_limb_t exp, mp_limb_t n,
mp_limb_t ninv)
Returns \code{(a^exp) % n} given a precomputed inverse of $n$ computed
by \code{n_preinvert_limb()}. We require $0 \leq a < n$, but there are no
restrictions on $n$. The exponent \code{exp} is unsigned and so can be
larger than allowed by \code{n_powmod2_preinv}.
This is implemented as a standard binary powering algorithm using
repeated squaring and reducing modulo $n$ at each step.
mp_limb_t n_sqrtmod(mp_limb_t a, mp_limb_t p)
Computes a square root of $a$ modulo $p$.
Assumes that $p$ is a prime and that $a$ is reduced modulo $p$.
Returns 0 if $a$ is a quadratic non-residue modulo $p$.
slong n_sqrtmod_2pow(mp_limb_t ** sqrt, mp_limb_t a, slong exp)
Computes all the square roots of \code{a} modulo \code{2^exp}. The roots
are stored in an array which is created and whose address is stored in
the location pointed to by \code{sqrt}. The array of roots is allocated
by the function but must be cleaned up by the user by calling
\code{flint_free}. The number of roots is returned by the function. If
\code{a} is not a quadratic residue modulo \code{2^exp} then 0 is
returned by the function and the location \code{sqrt} points to is set to
NULL.
slong
n_sqrtmod_primepow(mp_limb_t ** sqrt, mp_limb_t a, mp_limb_t p, slong exp)
Computes all the square roots of \code{a} modulo \code{p^exp}. The roots
are stored in an array which is created and whose address is stored in
the location pointed to by \code{sqrt}. The array of roots is allocated
by the function but must be cleaned up by the user by calling
\code{flint_free}. The number of roots is returned by the function. If
\code{a} is not a quadratic residue modulo \code{p^exp} then 0 is
returned by the function and the location \code{sqrt} points to is set to
NULL.
slong n_sqrtmodn(mp_limb_t ** sqrt, mp_limb_t a, n_factor_t * fac)
Computes all the square roots of \code{a} modulo \code{m} given the
factorisation of \code{m} in \code{fac}. The roots are stored in an array
which is created and whose address is stored in the location pointed to by
\code{sqrt}. The array of roots is allocated by the function but must be
cleaned up by the user by calling \code{flint_free}. The number of roots
is returned by the function. If \code{a} is not a quadratic residue modulo
\code{m} then 0 is returned by the function and the location \code{sqrt}
points to is set to NULL.
*******************************************************************************
Prime number generation and counting
*******************************************************************************
void n_primes_init(n_primes_t iter)
Initialises the prime number iterator \code{iter} for use.
void n_primes_clear(n_primes_t iter)
Clears memory allocated by the prime number iterator \code{iter}.
mp_limb_t n_primes_next(n_primes_t iter)
Returns the next prime number and advances the state of \code{iter}.
The first call returns 2.
Small primes are looked up from \code{flint_small_primes}.
When this table is exhausted, primes are generated in blocks
by calling \code{n_primes_sieve_range}.
void n_primes_jump_after(n_primes_t iter, mp_limb_t n)
Changes the state of \code{iter} to start generating primes
after $n$ (excluding $n$ itself).
void n_primes_extend_small(n_primes_t iter, mp_limb_t bound)
Extends the table of small primes in \code{iter} to contain
at least two primes larger than or equal to \code{bound}.
void n_primes_sieve_range(n_primes_t iter, mp_limb_t a, mp_limb_t b)
Sets the block endpoints of \code{iter} to the smallest and
largest odd numbers between $a$ and $b$ inclusive, and
sieves to mark all odd primes in this range.
The iterator state is changed to point to the first
number in the sieved range.
void n_compute_primes(ulong num_primes)
Precomputes at least \code{num_primes} primes and their \code{double}
precomputed inverses and stores them in an internal cache.
Assuming that FLINT has been built with support for thread-local storage,
each thread has its own cache.
const mp_limb_t * n_primes_arr_readonly(ulong num_primes)
Returns a pointer to a read-only array of the first \code{num_primes}
prime numbers. The computed primes are cached for repeated calls.
The pointer is valid until the user calls \code{n_cleanup_primes}
in the same thread.
const double * n_prime_inverses_arr_readonly(ulong n)
Returns a pointer to a read-only array of inverses of the first
\code{num_primes} prime numbers. The computed primes are cached for
repeated calls. The pointer is valid until the user calls
\code{n_cleanup_primes} in the same thread.
void n_cleanup_primes()
Frees the internal cache of prime numbers used by the current thread.
This will invalidate any pointers returned by
\code{n_primes_arr_readonly} or \code{n_prime_inverses_arr_readonly}.
mp_limb_t n_nextprime(mp_limb_t n, int proved)
Returns the next prime after $n$. Assumes the result will fit in an
\code{mp_limb_t}. If proved is $0$, i.e.\ false, the prime is not
proven prime, otherwise it is.
ulong n_prime_pi(mp_limb_t n)
Returns the value of the prime counting function $\pi(n)$, i.e.\ the
number of primes less than or equal to $n$. The invariant
\code{n_prime_pi(n_nth_prime(n)) == n}.
Currently, this function simply extends the table of cached primes up to
an upper limit and then performs a binary search.
void n_prime_pi_bounds(ulong *lo, ulong *hi, mp_limb_t n)
Calculates lower and upper bounds for the value of the prime counting
function \code{lo <= pi(n) <= hi}. If \code{lo} and \code{hi} point to
the same location, the high value will be stored.
The upper approximation is $1.25506 n / \ln n$, and the
lower is $n / \ln n$. These bounds are due to Rosser and
Schoenfeld~\citep{RosSch1962} and valid for $n \geq 17$.
We use the number of bits in $n$ (or one less) to form an
approximation to $\ln n$, taking care to use a value too
small or too large to maintain the inequality.
mp_limb_t n_nth_prime(ulong n)
Returns the $n$th prime number $p_n$, using the mathematical indexing
convention $p_1 = 2, p_2 = 3, \dotsc$.
This function simply ensures that the table of cached primes is large
enough and then looks up the entry.
void n_nth_prime_bounds(mp_limb_t *lo, mp_limb_t *hi, ulong n)
Calculates lower and upper bounds for the $n$th prime number $p_n$,
\code{lo <= p_n <= hi}. If \code{lo} and \code{hi} point to the same
location, the high value will be stored. Note that this function will
overflow for sufficiently large $n$.
We use the following estimates, valid for $n > 5$:
\begin{align*}
p_n & > n (\ln n + \ln \ln n - 1) \\
p_n & < n (\ln n + \ln \ln n) \\
p_n & < n (\ln n + \ln \ln n - 0.9427) \quad (n \geq 15985)
\end{align*}
The first inequality was proved by Dusart~\citep{Dus1999}, and the last
is due to Massias and Robin~\citep{MasRob1996}. For a further overview,
see \url{http://primes.utm.edu/howmany.shtml}.
We bound $\ln n$ using the number of bits in $n$ as in
\code{n_prime_pi_bounds()}, and estimate $\ln \ln n$ to the nearest
integer; this function is nearly constant.
% P. Dusart, "The kth prime is greater than k(ln k+ln ln k-1) for k> 2,"
% Math. Comp., 68:225 (January 1999) 411--415.
% J. Massias and G. Robin, "Bornes effectives pour certaines fonctions
% concernant les nombres premiers," J. Theorie Nombres Bordeaux, 8
% (1996) 215-242.
*******************************************************************************
Primality testing
*******************************************************************************
int n_is_oddprime_small(mp_limb_t n)
Returns $1$ if $n$ is an odd prime smaller than
\code{FLINT_ODDPRIME_SMALL_CUTOFF}. Expects $n$
to be odd and smaller than the cutoff.
This function merely uses a lookup table with one bit allocated for each
odd number up to the cutoff.
int n_is_oddprime_binary(mp_limb_t n)
This function performs a simple binary search through
the table of cached primes for $n$. If it exists in the array it returns
$1$, otherwise $0$. For the algorithm to operate correctly
$n$ should be odd and at least $17$.
Lower and upper bounds are computed with \code{n_prime_pi_bounds()}.
Once we have bounds on where to look in the table, we
refine our search with a simple binary algorithm, taking
the top or bottom of the current interval as necessary.
int n_is_prime_pocklington(mp_limb_t n, ulong iterations)
Tests if $n$ is a prime using the Pocklington--Lehmer primality
test. If $1$ is returned $n$ has been proved prime. If $0$ is returned
$n$ is composite. However $-1$ may be returned if nothing was proved
either way due to the number of iterations being too small.
The most time consuming part of the algorithm is factoring
$n - 1$. For this reason \code{n_factor_partial()} is used,
which uses a combination of trial factoring and Hart's one
line factor algorithm~\citep{Har2009} to try to quickly factor $n - 1$.
Additionally if the cofactor is less than the square root of
$n - 1$ the algorithm can still proceed.
One can also specify a number of iterations if less time
should be taken. Simply set this to \code{~WORD(0)} if this is irrelevant.
In most cases a greater number of iterations will not
significantly affect timings as most of the time is spent
factoring.
See
\url{http://mathworld.wolfram.com/PocklingtonsTheorem.html}
for a description of the algorithm.
int n_is_prime_pseudosquare(mp_limb_t n)
Tests if $n$ is a prime according to~\citep[Theorem~2.7]{LukPatWil1996}.
% "Some results on pseudosquares" by Lukes, Patterson and Williams,
% Math. Comp. vol 65, No. 213. pp 361-372. See
% http://www.ams.org/mcom/1996-65-213/S0025-5718-96-00678-3/
% S0025-5718-96-00678-3.pdf
We first factor $N$ using trial division up to some limit $B$.
In fact, the number of primes used in the trial factoring is at
most \code{FLINT_PSEUDOSQUARES_CUTOFF}.
Next we compute $N/B$ and find the next pseudosquare $L_p$ above
this value, using a static table as per
\url{http://research.att.com/~njas/sequences/b002189.txt}.
As noted in the text, if $p$ is prime then Step~3 will pass. This
test rejects many composites, and so by this time we suspect
that $p$ is prime. If $N$ is $3$ or $7$ modulo $8$, we are done,
and $N$ is prime.
We now run a probable prime test, for which no known
counterexamples are known, to reject any composites. We then
proceed to prove $N$ prime by executing Step~4. In the case that
$N$ is $1$ modulo $8$, if Step~4 fails, we extend the number of primes
$p_i$ at Step~3 and hope to find one which passes Step~4. We take
the test one past the largest $p$ for which we have pseudosquares
$L_p$ tabulated, as this already corresponds to the next $L_p$ which
is bigger than $2^{64}$ and hence larger than any prime we might be
testing.
As explained in the text, Condition~4 cannot fail if $N$ is prime.
The possibility exists that the probable prime test declares a
composite prime. However in that case an error is printed, as
that would be of independent interest.
int n_is_prime(mp_limb_t n)
Tests if $n$ is a prime. Up to $10^{16}$ this simply calls
\code{n_is_probabprime()} which is a primality test up to that limit.
Beyond that point it calls \code{n_is_probabprime()} and returns $0$
if $n$ is composite, then it calls \code{n_is_prime_pocklington()}
which proves the primality of $n$ in most cases. As a fallback,
\code{n_is_prime_pseudosquare()} is called, which will unconditionally
prove the primality of $n$.
int n_is_strong_probabprime_precomp(mp_limb_t n, double npre,
mp_limb_t a, mp_limb_t d)
Tests if $n$ is a strong probable prime to the base $a$. We
require that $d$ is set to the largest odd factor of $n - 1$ and
\code{npre} is a precomputed inverse of $n$ computed with
\code{n_precompute_inverse()}. We also require that $n < 2^{53}$,
$a$ to be reduced modulo $n$ and not $0$ and $n$ to be odd.
If we write $n - 1 = 2^s d$ where $d$ is odd then $n$ is a strong
probable prime to the base $a$, i.e.\ an $a$-SPRP, if either
$a^d = 1 \pmod n$ or $(a^d)^{2^r} = -1 \pmod n$ for some~$r$ less
than~$s$.
A description of strong probable primes is given here:
\url{http://mathworld.wolfram.com/StrongPseudoprime.html}
int n_is_strong_probabprime2_preinv(mp_limb_t n, mp_limb_t ninv,
mp_limb_t a, mp_limb_t d)
Tests if $n$ is a strong probable prime to the base $a$. We require
that $d$ is set to the largest odd factor of $n - 1$ and \code{npre}
is a precomputed inverse of $n$ computed with \code{n_preinvert_limb()}.
We require a to be reduced modulo $n$ and not $0$ and $n$ to be odd.
If we write $n - 1 = 2^s d$ where $d$ is odd then $n$ is a strong
probable prime to the base $a$ (an $a$-SPRP) if either $a^d = 1 \pmod n$
or $(a^d)^{2^r} = -1 \pmod n$ for some $r$ less than $s$.
A description of strong probable primes is given here:
\url{http://mathworld.wolfram.com/StrongPseudoprime.html}
int n_is_probabprime_fermat(mp_limb_t n, mp_limb_t i)
Returns $1$ if $n$ is a base $i$ Fermat probable prime. Requires
$1 < i < n$ and that $i$ does not divide $n$.
By Fermat's Little Theorem if $i^{n-1}$ is not congruent to $1$
then $n$ is not prime.
int n_is_probabprime_fibonacci(mp_limb_t n)
Let $F_j$ be the $j$th element of the Fibonacci sequence
$0, 1, 1, 2, 3, 5, \dotsc$, starting at $j = 0$. Then if $n$ is prime
we have $F_{n - (n/5)} = 0 \pmod n$, where $(n/5)$ is the Jacobi
symbol.
For further details, see~\citep[pp.~142]{CraPom2005}.
We require that $n$ is not divisible by $2$ or $5$.
int n_is_probabprime_BPSW(mp_limb_t n)
Implements the Baillie--Pomerance--Selfridge--Wagstaff probable primality
test. There are no known counterexamples to this being a primality test.
For further details, see~\citep{CraPom2005}.
int n_is_probabprime_lucas(mp_limb_t n)
For details on Lucas pseudoprimes, see~\citep[pp.~143]{CraPom2005}.
We implement a variant of the Lucas pseudoprime test as
described by Baillie and Wagstaff~\citep{BaiWag1980}.
int n_is_probabprime(mp_limb_t n)
Tests if $n$ is a probable prime. Up to \code{FLINT_ODDPRIME_SMALL_CUTOFF}
this algorithm uses \code{n_is_oddprime_small()} which uses a lookup table.
Next it calls \code{n_compute_primes()} with the maximum table size and
uses this table to perform a binary search for $n$ up to the table limit.
Then up to $10^{16}$ it uses a number of strong probable prime tests,
\code{n_is_strong_probabprime_precomp()}, etc., for various bases. The
output of the algorithm is guaranteed to be correct up to this bound due
to exhaustive tables, described at
\url{http://uucode.com/obf/dalbec/alg.html}.
Beyond that point the BPSW probabilistic primality test is used, by
calling the function \code{n_is_probabprime_BPSW()}. There are no known
counterexamples, but it may well declare some composites to be prime.
*******************************************************************************
Square root and perfect power testing
*******************************************************************************
mp_limb_t n_sqrt(mp_limb_t a)
Computes the integer truncation of the square root of $a$. The integer
itself can be represented exactly as a double and its square root is
computed to the nearest place. If $a$ is one below a square, the
rounding may be up, whereas if it is one above a square, the rounding
will be down. Thus the square root may be one too large in some
instances. We also have to be careful when the square of this too large
value causes an overflow. The same assumptions hold for a single
precision float provided the square root itself can be represented
in a single float, i.e.\ for $a < 281474976710656 = 2^{46}$.
mp_limb_t n_sqrtrem(mp_limb_t * r, mp_limb_t a)
Computes the integer truncation of the square root of $a$. The integer
itself can be represented exactly as a double and its square root is
computed to the nearest place. If $a$ is one below a square, the
rounding may be up, whereas if it is one above a square, the rounding
will be down. Thus the square root may be one too large in some
instances. We also have to be careful when the square of this too
large value causes an overflow. The same assumptions hold for a
single precision float provided the square root itself can be
represented in a single float, i.e. for \
$a < 281474976710656 = 2^{46}$. The remainder is computed by
subtracting the square of the computed square root from $a$.
int n_is_square(mp_limb_t x)
Returns $1$ if $x$ is a square, otherwise $0$.
This code first checks if $x$ is a square modulo $64$,
$63 = 3 \times 3 \times 7$ and $65 = 5 \times 13$, using lookup tables,
and if so it then takes a square root and checks that the square of this
equals the original value.
int n_is_perfect_power235(mp_limb_t n)
Returns $1$ if $n$ is a perfect square, cube or fifth power.
This function uses a series of modular tests to reject most
non $235$-powers. Each modular test returns a value from $0$ to $7$
whose bits respectively indicate whether the value is a square,
cube or fifth power modulo the given modulus. When these are
logically \code{AND}ed together, this gives a powerful test which will
reject most non-$235$ powers.
If a bit remains set indicating it may be a square, a standard
square root test is performed. Similarly a cube root or fifth
root can be taken, if indicated, to determine whether the power
of that root is exactly equal to $n$.
*******************************************************************************
Factorisation
*******************************************************************************
int n_remove(mp_limb_t * n, mp_limb_t p)
Removes the highest possible power of $p$ from $n$, replacing
$n$ with the quotient. The return value is that highest
power of $p$ that divided $n$. Assumes $n$ is not $0$.
For $p = 2$ trailing zeroes are counted. For other primes
$p$ is repeatedly squared and stored in a table of powers
with the current highest power of $p$ removed at each step
until no higher power can be removed. The algorithm then
proceeds down the power tree again removing powers of $p$
until none remain.
int n_remove2_precomp(mp_limb_t * n, mp_limb_t p, double ppre)
Removes the highest possible power of $p$ from $n$, replacing
$n$ with the quotient. The return value is that highest
power of $p$ that divided $n$. Assumes $n$ is not $0$. We require
\code{ppre} to be set to a precomputed inverse of $p$ computed
with \code{n_precompute_inverse()}.
For $p = 2$ trailing zeroes are counted. For other primes
$p$ we make repeated use of \code{n_divrem2_precomp()} until division
by $p$ is no longer possible.
void n_factor_insert(n_factor_t * factors, mp_limb_t p, ulong exp)
Inserts the given prime power factor \code{p^exp} into
the \code{n_factor_t} \code{factors}. See the documentation for
\code{n_factor_trial()} for a description of the \code{n_factor_t} type.
The algorithm performs a simple search to see if $p$ already
exists as a prime factor in the structure. If so the exponent
there is increased by the supplied exponent. Otherwise a new
factor \code{p^exp} is added to the end of the structure.
There is no test code for this function other than its use by
the various factoring functions, which have test code.
mp_limb_t n_factor_trial_range(n_factor_t * factors,
mp_limb_t n, ulong start, ulong num_primes)
Trial factor $n$ with the first \code{num_primes} primes, but
starting at the prime with index start (counting from zero).
One requires an initialised \code{n_factor_t} structure, but factors
will be added by default to an already used \code{n_factor_t}. Use
the function \code{n_factor_init()} defined in \code{ulong_extras} if
initialisation has not already been completed on factors.
Once completed, \code{num} will contain the number of distinct
prime factors found. The field $p$ is an array of \code{mp_limb_t}'s
containing the distinct prime factors, \code{exp} an array
containing the corresponding exponents.
The return value is the unfactored cofactor after trial
factoring is done.
The function calls \code{n_compute_primes()} automatically. See
the documentation for that function regarding limits.
The algorithm stops when the current prime has a square
exceeding $n$, as no prime factor of $n$ can exceed this
unless $n$ is prime.
The precomputed inverses of all the primes computed by
\code{n_compute_primes()} are utilised with the \code{n_remove2_precomp()}
function.
mp_limb_t n_factor_trial(n_factor_t * factors, mp_limb_t n, ulong num_primes)
This function calls \code{n_factor_trial_range()}, with the value of
$0$ for \code{start}. By default this adds factors to an already existing
\code{n_factor_t} or to a newly initialised one.
mp_limb_t n_factor_power235(ulong *exp, mp_limb_t n)
Returns $0$ if $n$ is not a perfect square, cube or fifth power.
Otherwise it returns the root and sets \code{exp} to either $2$,
$3$ or $5$ appropriately.
This function uses a series of modular tests to reject most
non $235$-powers. Each modular test returns a value from $0$ to $7$
whose bits respectively indicate whether the value is a square,
cube or fifth power modulo the given modulus. When these are
logically \code{AND}ed together, this gives a powerful test which will
reject most non-$235$ powers.
If a bit remains set indicating it may be a square, a standard
square root test is performed. Similarly a cube root or fifth
root can be taken, if indicated, to determine whether the power
of that root is exactly equal to $n$.
mp_limb_t n_factor_one_line(mp_limb_t n, ulong iters)
This implements Bill Hart's one line factoring algorithm~\citep{Har2009}.
It is a variant of Fermat's algorithm which cycles through a large number
of multipliers instead of incrementing the square root. It is faster than
SQUFOF for $n$ less than about $2^{40}$.
mp_limb_t n_factor_lehman(mp_limb_t n)
Lehman's factoring algorithm. Currently works up to $10^{16}$, but is
not particularly efficient and so is not used in the general factor
function. Always returns a factor of $n$.
mp_limb_t n_factor_SQUFOF(mp_limb_t n, ulong iters)
Attempts to split $n$ using the given number of iterations
of SQUFOF. Simply set \code{iters} to \code{~WORD(0)} for maximum
persistence.
The version of SQUFOF imlemented here is as described by Gower
and Wagstaff~\citep{GowWag2008}.
% Jason Gower and Sam Wagstaff
% "Square form factoring"
% Math. Comp. 77, 2008, pp 551-588, see:
% http://www.ams.org/mcom/2008-77-261/S0025-5718-07-02010-8/home.html
We start by trying SQUFOF directly on $n$. If that fails we
multiply it by each of the primes in \code{flint_primes_small} in
turn. As this multiplication may result in a two limb value
we allow this in our implementation of SQUFOF. As SQUFOF
works with values about half the size of $n$ it only needs
single limb arithmetic internally.
If SQUFOF fails to factor $n$ we return $0$, however with
\code{iters} large enough this should never happen.
void n_factor(n_factor_t * factors, mp_limb_t n, int proved)
Factors $n$ with no restrictions on $n$. If the prime factors are
required to be certified prime, one may set \code{proved} to $1$,
otherwise set it to $0$, and they will only be probable primes
(with no known counterexamples to the conjecture that they are
in fact all prime).
For details on the \code{n_factor_t} structure, see
\code{n_factor_trial()}.
This function first tries trial factoring with a number of primes
specified by the constant \code{FLINT_FACTOR_TRIAL_PRIMES}. If the
cofactor is $1$ or prime the function returns with all the factors.
Otherwise, the cofactor is placed in the array \code{factor_arr}. Whilst
there are factors remaining in there which have not been split, the
algorithm continues. At each step each factor is first checked to
determine if it is a perfect power. If so it is replaced by the power
that has been found. Next if the factor is small enough and composite,
in particular, less than \code{FLINT_FACTOR_ONE_LINE_MAX} then
\code{n_factor_one_line()} is called with
\code{FLINT_FACTOR_ONE_LINE_ITERS} to try and split the factor. If
that fails or the factor is too large for \code{n_factor_one_line()}
then \code{n_factor_SQUFOF()} is called, with
\code{FLINT_FACTOR_SQUFOF_ITERS}. If that fails an error results and
the program aborts. However this should not happen in practice.
mp_limb_t n_factor_trial_partial(n_factor_t * factors, mp_limb_t n,
mp_limb_t * prod, ulong num_primes, mp_limb_t limit)
Attempts trial factoring of $n$ with the first \code{num_primes primes},
but stops when the product of prime factors so far exceeds \code{limit}.
One requires an initialised \code{n_factor_t} structure, but factors
will be added by default to an already used \code{n_factor_t}. Use
the function \code{n_factor_init()} defined in \code{ulong_extras} if
initialisation has not already been completed on \code{factors}.
Once completed, \code{num} will contain the number of distinct
prime factors found. The field $p$ is an array of \code{mp_limb_t}'s
containing the distinct prime factors, \code{exp} an array
containing the corresponding exponents.
The return value is the unfactored cofactor after trial
factoring is done. The value \code{prod} will be set to the product
of the factors found.
The function calls \code{n_compute_primes()} automatically. See
the documentation for that function regarding limits.
The algorithm stops when the current prime has a square
exceeding $n$, as no prime factor of $n$ can exceed this
unless $n$ is prime.
The precomputed inverses of all the primes computed by
\code{n_compute_primes()} are utilised with the \code{n_remove2_precomp()}
function.
mp_limb_t n_factor_partial(n_factor_t * factors,
mp_limb_t n, mp_limb_t limit, int proved)
Factors $n$, but stops when the product of prime factors so far
exceeds \code{limit}.
One requires an initialised \code{n_factor_t} structure, but factors
will be added by default to an already used \code{n_factor_t}. Use
the function \code{n_factor_init()} defined in \code{ulong_extras} if
initialisation has not already been completed on \code{factors}.
On exit, \code{num} will contain the number of distinct prime factors
found. The field $p$ is an array of \code{mp_limb_t}'s containing the
distinct prime factors, \code{exp} an array containing the corresponding
exponents.
The return value is the unfactored cofactor after factoring is done.
The factors are proved prime if \code{proved} is $1$, otherwise
they are merely probably prime.
mp_limb_t n_factor_pp1(mp_limb_t n, ulong B1, ulong c)
Factors $n$ using Williams' $p + 1$ factoring algorithm, with prime
limit set to $B1$. We require $c$ to be set to a random value. Each
trial of the algorithm with a different value of $c$ gives another
chance to factor $n$, with roughly exponentially decreasing chance
of finding a missing factor. If $p + 1$ (or $p - 1$) is not smooth
for any factor $p$ of $n$, the algorithm will never succeed. The
value $c$ should be less than $n$ and greater than $2$.
If the algorithm succeeds, it returns the factor, otherwise it
returns $0$ or $1$ (the trivial factors modulo $n$).
*******************************************************************************
Arithmetic functions
*******************************************************************************
int n_moebius_mu(mp_limb_t n)
Computes the Moebius function $\mu(n)$, which is defined as $\mu(n) = 0$
if $n$ has a prime factor of multiplicity greater than $1$, $\mu(n) = -1$
if $n$ has an odd number of distinct prime factors, and $\mu(n) = 1$ if
$n$ has an even number of distinct prime factors. By convention,
$\mu(0) = 0$.
For even numbers, we use the identities $\mu(4n) = 0$ and
$\mu(2n) = - \mu(n)$. Odd numbers up to a cutoff are then looked up from
a precomputed table storing $\mu(n) + 1$ in groups of two bits.
For larger $n$, we first check if $n$ is divisible by a small odd square
and otherwise call \code{n_factor()} and count the factors.
void n_moebius_mu_vec(int * mu, ulong len)
Computes $\mu(n)$ for \code{n = 0, 1, ..., len - 1}. This
is done by sieving over each prime in the range, flipping the sign
of $\mu(n)$ for every multiple of a prime $p$ and setting $\mu(n) = 0$
for every multiple of $p^2$.
int n_is_squarefree(mp_limb_t n)
Returns $0$ if $n$ is divisible by some perfect square, and $1$ otherwise.
This simply amounts to testing whether $\mu(n) \neq 0$. As special
cases, $1$ is considered squarefree and $0$ is not considered squarefree.
mp_limb_t n_euler_phi(mp_limb_t n)
Computes the Euler totient function $\phi(n)$, counting the number of
positive integers less than or equal to $n$ that are coprime to $n$.
*******************************************************************************
Factorials
*******************************************************************************
mp_limb_t n_factorial_fast_mod2_preinv(ulong n, mp_limb_t p, mp_limb_t pinv)
Returns $n! \bmod p$ given a precomputed inverse of $p$ as computed
by \code{n_preinvert_limb()}. $p$ is not required to be a prime, but
no special optimisations are made for composite $p$.
Uses fast multipoint evaluation, running in about $O(n^{1/2})$ time.
mp_limb_t n_factorial_mod2_preinv(ulong n, mp_limb_t p, mp_limb_t pinv)
Returns $n! \bmod p$ given a precomputed inverse of $p$ as computed
by \code{n_preinvert_limb()}. $p$ is not required to be a prime, but
no special optimisations are made for composite $p$.
Uses a lookup table for small $n$, otherwise computes the product
if $n$ is not too large, and calls the fast algorithm for extremely
large $n$.
*******************************************************************************
Primitive Roots and Discrete Logarithms
*******************************************************************************
mp_limb_t n_primitive_root_prime_prefactor(mp_limb_t p, n_factor_t * factors)
Returns a primitive root for the multiplicative subgroup of $Z/pZ$
where $p$ is prime given the factorisation ($factors$) of $p - 1$.
mp_limb_t n_primitive_root_prime(mp_limb_t p)
Returns a primitive root for the multiplicative subgroup of $Z/pZ$
where $p$ is prime.
mp_limb_t n_discrete_log_bsgs(mp_limb_t b, mp_limb_t a, mp_limb_t n)
Returns the discrete logarithm of $b$ with respect to $a$ in the
multiplicative subgroup of $Z/nZ$ when $Z/nZ$ is cyclic That is,
it returns an number $x$ such that $a^x = b \bmod n$. The
multiplicative subgroup is only cyclic when $n$ is $2$, $4$,
$p^k$, or $2p^k$ where $p$ is an odd prime and $k$ is a positive
integer.
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