# -*- coding: utf-8 -*-
from __future__ import print_function, division
from sympy.core.compatibility import as_int, range
from sympy.core.function import Function
from sympy.core.numbers import igcd, igcdex, mod_inverse
from sympy.core.power import isqrt
from sympy.core.singleton import S
from .primetest import isprime
from .factor_ import factorint, trailing, totient, multiplicity
from random import randint, Random
[docs]def n_order(a, n):
"""Returns the order of ``a`` modulo ``n``.
The order of ``a`` modulo ``n`` is the smallest integer
``k`` such that ``a**k`` leaves a remainder of 1 with ``n``.
Examples
========
>>> from sympy.ntheory import n_order
>>> n_order(3, 7)
6
>>> n_order(4, 7)
3
"""
from collections import defaultdict
a, n = as_int(a), as_int(n)
if igcd(a, n) != 1:
raise ValueError("The two numbers should be relatively prime")
factors = defaultdict(int)
f = factorint(n)
for px, kx in f.items():
if kx > 1:
factors[px] += kx - 1
fpx = factorint(px - 1)
for py, ky in fpx.items():
factors[py] += ky
group_order = 1
for px, kx in factors.items():
group_order *= px**kx
order = 1
if a > n:
a = a % n
for p, e in factors.items():
exponent = group_order
for f in range(e + 1):
if pow(a, exponent, n) != 1:
order *= p ** (e - f + 1)
break
exponent = exponent // p
return order
def _primitive_root_prime_iter(p):
"""
Generates the primitive roots for a prime ``p``
Examples
========
>>> from sympy.ntheory.residue_ntheory import _primitive_root_prime_iter
>>> list(_primitive_root_prime_iter(19))
[2, 3, 10, 13, 14, 15]
References
==========
.. [1] W. Stein "Elementary Number Theory" (2011), page 44
"""
# it is assumed that p is an int
v = [(p - 1) // i for i in factorint(p - 1).keys()]
a = 2
while a < p:
for pw in v:
# a TypeError below may indicate that p was not an int
if pow(a, pw, p) == 1:
break
else:
yield a
a += 1
[docs]def primitive_root(p):
"""
Returns the smallest primitive root or None
Parameters
==========
p : positive integer
Examples
========
>>> from sympy.ntheory.residue_ntheory import primitive_root
>>> primitive_root(19)
2
References
==========
.. [1] W. Stein "Elementary Number Theory" (2011), page 44
.. [2] P. Hackman "Elementary Number Theory" (2009), Chapter C
"""
p = as_int(p)
if p < 1:
raise ValueError('p is required to be positive')
if p <= 2:
return 1
f = factorint(p)
if len(f) > 2:
return None
if len(f) == 2:
if 2 not in f or f[2] > 1:
return None
# case p = 2*p1**k, p1 prime
for p1, e1 in f.items():
if p1 != 2:
break
i = 1
while i < p:
i += 2
if i % p1 == 0:
continue
if is_primitive_root(i, p):
return i
else:
if 2 in f:
if p == 4:
return 3
return None
p1, n = list(f.items())[0]
if n > 1:
# see Ref [2], page 81
g = primitive_root(p1)
if is_primitive_root(g, p1**2):
return g
else:
for i in range(2, g + p1 + 1):
if igcd(i, p) == 1 and is_primitive_root(i, p):
return i
return next(_primitive_root_prime_iter(p))
[docs]def is_primitive_root(a, p):
"""
Returns True if ``a`` is a primitive root of ``p``
``a`` is said to be the primitive root of ``p`` if gcd(a, p) == 1 and
totient(p) is the smallest positive number s.t.
a**totient(p) cong 1 mod(p)
Examples
========
>>> from sympy.ntheory import is_primitive_root, n_order, totient
>>> is_primitive_root(3, 10)
True
>>> is_primitive_root(9, 10)
False
>>> n_order(3, 10) == totient(10)
True
>>> n_order(9, 10) == totient(10)
False
"""
a, p = as_int(a), as_int(p)
if igcd(a, p) != 1:
raise ValueError("The two numbers should be relatively prime")
if a > p:
a = a % p
return n_order(a, p) == totient(p)
def _sqrt_mod_tonelli_shanks(a, p):
"""
Returns the square root in the case of ``p`` prime with ``p == 1 (mod 8)``
References
==========
.. [1] R. Crandall and C. Pomerance "Prime Numbers", 2nt Ed., page 101
"""
s = trailing(p - 1)
t = p >> s
# find a non-quadratic residue
while 1:
d = randint(2, p - 1)
r = legendre_symbol(d, p)
if r == -1:
break
#assert legendre_symbol(d, p) == -1
A = pow(a, t, p)
D = pow(d, t, p)
m = 0
for i in range(s):
adm = A*pow(D, m, p) % p
adm = pow(adm, 2**(s - 1 - i), p)
if adm % p == p - 1:
m += 2**i
#assert A*pow(D, m, p) % p == 1
x = pow(a, (t + 1)//2, p)*pow(D, m//2, p) % p
return x
[docs]def sqrt_mod(a, p, all_roots=False):
"""
Find a root of ``x**2 = a mod p``
Parameters
==========
a : integer
p : positive integer
all_roots : if True the list of roots is returned or None
Notes
=====
If there is no root it is returned None; else the returned root
is less or equal to ``p // 2``; in general is not the smallest one.
It is returned ``p // 2`` only if it is the only root.
Use ``all_roots`` only when it is expected that all the roots fit
in memory; otherwise use ``sqrt_mod_iter``.
Examples
========
>>> from sympy.ntheory import sqrt_mod
>>> sqrt_mod(11, 43)
21
>>> sqrt_mod(17, 32, True)
[7, 9, 23, 25]
"""
if all_roots:
return sorted(list(sqrt_mod_iter(a, p)))
try:
p = abs(as_int(p))
it = sqrt_mod_iter(a, p)
r = next(it)
if r > p // 2:
return p - r
elif r < p // 2:
return r
else:
try:
r = next(it)
if r > p // 2:
return p - r
except StopIteration:
pass
return r
except StopIteration:
return None
def _product(*iters):
"""
Cartesian product generator
Notes
=====
Unlike itertools.product, it works also with iterables which do not fit
in memory. See http://bugs.python.org/issue10109
Author: Fernando Sumudu
with small changes
"""
import itertools
inf_iters = tuple(itertools.cycle(enumerate(it)) for it in iters)
num_iters = len(inf_iters)
cur_val = [None]*num_iters
first_v = True
while True:
i, p = 0, num_iters
while p and not i:
p -= 1
i, cur_val[p] = next(inf_iters[p])
if not p and not i:
if first_v:
first_v = False
else:
break
yield cur_val
def sqrt_mod_iter(a, p, domain=int):
"""
Iterate over solutions to ``x**2 = a mod p``
Parameters
==========
a : integer
p : positive integer
domain : integer domain, ``int``, ``ZZ`` or ``Integer``
Examples
========
>>> from sympy.ntheory.residue_ntheory import sqrt_mod_iter
>>> list(sqrt_mod_iter(11, 43))
[21, 22]
"""
from sympy.polys.galoistools import gf_crt1, gf_crt2
from sympy.polys.domains import ZZ
a, p = as_int(a), abs(as_int(p))
if isprime(p):
a = a % p
if a == 0:
res = _sqrt_mod1(a, p, 1)
else:
res = _sqrt_mod_prime_power(a, p, 1)
if res:
if domain is ZZ:
for x in res:
yield x
else:
for x in res:
yield domain(x)
else:
f = factorint(p)
v = []
pv = []
for px, ex in f.items():
if a % px == 0:
rx = _sqrt_mod1(a, px, ex)
if not rx:
return
else:
rx = _sqrt_mod_prime_power(a, px, ex)
if not rx:
return
v.append(rx)
pv.append(px**ex)
mm, e, s = gf_crt1(pv, ZZ)
if domain is ZZ:
for vx in _product(*v):
r = gf_crt2(vx, pv, mm, e, s, ZZ)
yield r
else:
for vx in _product(*v):
r = gf_crt2(vx, pv, mm, e, s, ZZ)
yield domain(r)
def _sqrt_mod_prime_power(a, p, k):
"""
Find the solutions to ``x**2 = a mod p**k`` when ``a % p != 0``
Parameters
==========
a : integer
p : prime number
k : positive integer
Examples
========
>>> from sympy.ntheory.residue_ntheory import _sqrt_mod_prime_power
>>> _sqrt_mod_prime_power(11, 43, 1)
[21, 22]
References
==========
.. [1] P. Hackman "Elementary Number Theory" (2009), page 160
.. [2] http://www.numbertheory.org/php/squareroot.html
.. [3] [Gathen99]_
"""
from sympy.core.numbers import igcdex
from sympy.polys.domains import ZZ
pk = p**k
a = a % pk
if k == 1:
if p == 2:
return [ZZ(a)]
if not is_quad_residue(a, p):
return None
if p % 4 == 3:
res = pow(a, (p + 1) // 4, p)
elif p % 8 == 5:
sign = pow(a, (p - 1) // 4, p)
if sign == 1:
res = pow(a, (p + 3) // 8, p)
else:
b = pow(4*a, (p - 5) // 8, p)
x = (2*a*b) % p
if pow(x, 2, p) == a:
res = x
else:
res = _sqrt_mod_tonelli_shanks(a, p)
# ``_sqrt_mod_tonelli_shanks(a, p)`` is not deterministic;
# sort to get always the same result
return sorted([ZZ(res), ZZ(p - res)])
if k > 1:
# see Ref.[2]
if p == 2:
if a % 8 != 1:
return None
if k <= 3:
s = set()
for i in range(0, pk, 4):
s.add(1 + i)
s.add(-1 + i)
return list(s)
# according to Ref.[2] for k > 2 there are two solutions
# (mod 2**k-1), that is four solutions (mod 2**k), which can be
# obtained from the roots of x**2 = 0 (mod 8)
rv = [ZZ(1), ZZ(3), ZZ(5), ZZ(7)]
# hensel lift them to solutions of x**2 = 0 (mod 2**k)
# if r**2 - a = 0 mod 2**nx but not mod 2**(nx+1)
# then r + 2**(nx - 1) is a root mod 2**(nx+1)
n = 3
res = []
for r in rv:
nx = n
while nx < k:
r1 = (r**2 - a) >> nx
if r1 % 2:
r = r + (1 << (nx - 1))
#assert (r**2 - a)% (1 << (nx + 1)) == 0
nx += 1
if r not in res:
res.append(r)
x = r + (1 << (k - 1))
#assert (x**2 - a) % pk == 0
if x < (1 << nx) and x not in res:
if (x**2 - a) % pk == 0:
res.append(x)
return res
rv = _sqrt_mod_prime_power(a, p, 1)
if not rv:
return None
r = rv[0]
fr = r**2 - a
# hensel lifting with Newton iteration, see Ref.[3] chapter 9
# with f(x) = x**2 - a; one has f'(a) != 0 (mod p) for p != 2
n = 1
px = p
while 1:
n1 = n
n1 *= 2
if n1 > k:
break
n = n1
px = px**2
frinv = igcdex(2*r, px)[0]
r = (r - fr*frinv) % px
fr = r**2 - a
if n < k:
px = p**k
frinv = igcdex(2*r, px)[0]
r = (r - fr*frinv) % px
return [r, px - r]
def _sqrt_mod1(a, p, n):
"""
Find solution to ``x**2 == a mod p**n`` when ``a % p == 0``
see http://www.numbertheory.org/php/squareroot.html
"""
pn = p**n
a = a % pn
if a == 0:
# case gcd(a, p**k) = p**n
m = n // 2
if n % 2 == 1:
pm1 = p**(m + 1)
def _iter0a():
i = 0
while i < pn:
yield i
i += pm1
return _iter0a()
else:
pm = p**m
def _iter0b():
i = 0
while i < pn:
yield i
i += pm
return _iter0b()
# case gcd(a, p**k) = p**r, r < n
f = factorint(a)
r = f[p]
if r % 2 == 1:
return None
m = r // 2
a1 = a >> r
if p == 2:
if n - r == 1:
pnm1 = 1 << (n - m + 1)
pm1 = 1 << (m + 1)
def _iter1():
k = 1 << (m + 2)
i = 1 << m
while i < pnm1:
j = i
while j < pn:
yield j
j += k
i += pm1
return _iter1()
if n - r == 2:
res = _sqrt_mod_prime_power(a1, p, n - r)
if res is None:
return None
pnm = 1 << (n - m)
def _iter2():
s = set()
for r in res:
i = 0
while i < pn:
x = (r << m) + i
if x not in s:
s.add(x)
yield x
i += pnm
return _iter2()
if n - r > 2:
res = _sqrt_mod_prime_power(a1, p, n - r)
if res is None:
return None
pnm1 = 1 << (n - m - 1)
def _iter3():
s = set()
for r in res:
i = 0
while i < pn:
x = ((r << m) + i) % pn
if x not in s:
s.add(x)
yield x
i += pnm1
return _iter3()
else:
m = r // 2
a1 = a // p**r
res1 = _sqrt_mod_prime_power(a1, p, n - r)
if res1 is None:
return None
pm = p**m
pnr = p**(n-r)
pnm = p**(n-m)
def _iter4():
s = set()
pm = p**m
for rx in res1:
i = 0
while i < pnm:
x = ((rx + i) % pn)
if x not in s:
s.add(x)
yield x*pm
i += pnr
return _iter4()
[docs]def is_quad_residue(a, p):
"""
Returns True if ``a`` (mod ``p``) is in the set of squares mod ``p``,
i.e a % p in set([i**2 % p for i in range(p)]). If ``p`` is an odd
prime, an iterative method is used to make the determination:
>>> from sympy.ntheory import is_quad_residue
>>> sorted(set([i**2 % 7 for i in range(7)]))
[0, 1, 2, 4]
>>> [j for j in range(7) if is_quad_residue(j, 7)]
[0, 1, 2, 4]
See Also
========
legendre_symbol, jacobi_symbol
"""
a, p = as_int(a), as_int(p)
if p < 1:
raise ValueError('p must be > 0')
if a >= p or a < 0:
a = a % p
if a < 2 or p < 3:
return True
if not isprime(p):
if p % 2 and jacobi_symbol(a, p) == -1:
return False
r = sqrt_mod(a, p)
if r is None:
return False
else:
return True
return pow(a, (p - 1) // 2, p) == 1
[docs]def is_nthpow_residue(a, n, m):
"""
Returns True if ``x**n == a (mod m)`` has solutions.
References
==========
.. [1] P. Hackman "Elementary Number Theory" (2009), page 76
"""
a, n, m = as_int(a), as_int(n), as_int(m)
if m <= 0:
raise ValueError('m must be > 0')
if n < 0:
raise ValueError('n must be >= 0')
if a < 0:
raise ValueError('a must be >= 0')
if n == 0:
if m == 1:
return False
return a == 1
if n == 1:
return True
if n == 2:
return is_quad_residue(a, m)
return _is_nthpow_residue_bign(a, n, m)
def _is_nthpow_residue_bign(a, n, m):
"""Returns True if ``x**n == a (mod m)`` has solutions for n > 2."""
# assert n > 2
# assert a > 0 and m > 0
if primitive_root(m) is None:
# assert m >= 8
for prime, power in factorint(m).items():
if not _is_nthpow_residue_bign_prime_power(a, n, prime, power):
return False
return True
f = totient(m)
k = f // igcd(f, n)
return pow(a, k, m) == 1
def _is_nthpow_residue_bign_prime_power(a, n, p, k):
"""Returns True/False if a solution for ``x**n == a (mod(p**k))``
does/doesn't exist."""
# assert a > 0
# assert n > 2
# assert p is prime
# assert k > 0
if a % p:
if p != 2:
return _is_nthpow_residue_bign(a, n, pow(p, k))
if n & 1:
return True
c = trailing(n)
return a % pow(2, min(c + 2, k)) == 1
else:
a %= pow(p, k)
if not a:
return True
mu = multiplicity(p, a)
if mu % n:
return False
pm = pow(p, mu)
return _is_nthpow_residue_bign_prime_power(a//pm, n, p, k - mu)
def _nthroot_mod2(s, q, p):
f = factorint(q)
v = []
for b, e in f.items():
v.extend([b]*e)
for qx in v:
s = _nthroot_mod1(s, qx, p, False)
return s
def _nthroot_mod1(s, q, p, all_roots):
"""
Root of ``x**q = s mod p``, ``p`` prime and ``q`` divides ``p - 1``
References
==========
.. [1] A. M. Johnston "A Generalized qth Root Algorithm"
"""
g = primitive_root(p)
if not isprime(q):
r = _nthroot_mod2(s, q, p)
else:
f = p - 1
assert (p - 1) % q == 0
# determine k
k = 0
while f % q == 0:
k += 1
f = f // q
# find z, x, r1
f1 = igcdex(-f, q)[0] % q
z = f*f1
x = (1 + z) // q
r1 = pow(s, x, p)
s1 = pow(s, f, p)
h = pow(g, f*q, p)
t = discrete_log(p, s1, h)
g2 = pow(g, z*t, p)
g3 = igcdex(g2, p)[0]
r = r1*g3 % p
#assert pow(r, q, p) == s
res = [r]
h = pow(g, (p - 1) // q, p)
#assert pow(h, q, p) == 1
hx = r
for i in range(q - 1):
hx = (hx*h) % p
res.append(hx)
if all_roots:
res.sort()
return res
return min(res)
[docs]def nthroot_mod(a, n, p, all_roots=False):
"""
Find the solutions to ``x**n = a mod p``
Parameters
==========
a : integer
n : positive integer
p : positive integer
all_roots : if False returns the smallest root, else the list of roots
Examples
========
>>> from sympy.ntheory.residue_ntheory import nthroot_mod
>>> nthroot_mod(11, 4, 19)
8
>>> nthroot_mod(11, 4, 19, True)
[8, 11]
>>> nthroot_mod(68, 3, 109)
23
"""
from sympy.core.numbers import igcdex
a, n, p = as_int(a), as_int(n), as_int(p)
if n == 2:
return sqrt_mod(a, p, all_roots)
# see Hackman "Elementary Number Theory" (2009), page 76
if not is_nthpow_residue(a, n, p):
return None
if primitive_root(p) is None:
raise NotImplementedError("Not Implemented for m without primitive root")
if (p - 1) % n == 0:
return _nthroot_mod1(a, n, p, all_roots)
# The roots of ``x**n - a = 0 (mod p)`` are roots of
# ``gcd(x**n - a, x**(p - 1) - 1) = 0 (mod p)``
pa = n
pb = p - 1
b = 1
if pa < pb:
a, pa, b, pb = b, pb, a, pa
while pb:
# x**pa - a = 0; x**pb - b = 0
# x**pa - a = x**(q*pb + r) - a = (x**pb)**q * x**r - a =
# b**q * x**r - a; x**r - c = 0; c = b**-q * a mod p
q, r = divmod(pa, pb)
c = pow(b, q, p)
c = igcdex(c, p)[0]
c = (c * a) % p
pa, pb = pb, r
a, b = b, c
if pa == 1:
if all_roots:
res = [a]
else:
res = a
elif pa == 2:
return sqrt_mod(a, p , all_roots)
else:
res = _nthroot_mod1(a, pa, p, all_roots)
return res
[docs]def quadratic_residues(p):
"""
Returns the list of quadratic residues.
Examples
========
>>> from sympy.ntheory.residue_ntheory import quadratic_residues
>>> quadratic_residues(7)
[0, 1, 2, 4]
"""
p = as_int(p)
r = set()
for i in range(p // 2 + 1):
r.add(pow(i, 2, p))
return sorted(list(r))
[docs]def legendre_symbol(a, p):
r"""
Returns the Legendre symbol `(a / p)`.
For an integer ``a`` and an odd prime ``p``, the Legendre symbol is
defined as
.. math ::
\genfrac(){}{}{a}{p} = \begin{cases}
0 & \text{if } p \text{ divides } a\\
1 & \text{if } a \text{ is a quadratic residue modulo } p\\
-1 & \text{if } a \text{ is a quadratic nonresidue modulo } p
\end{cases}
Parameters
==========
a : integer
p : odd prime
Examples
========
>>> from sympy.ntheory import legendre_symbol
>>> [legendre_symbol(i, 7) for i in range(7)]
[0, 1, 1, -1, 1, -1, -1]
>>> sorted(set([i**2 % 7 for i in range(7)]))
[0, 1, 2, 4]
See Also
========
is_quad_residue, jacobi_symbol
"""
a, p = as_int(a), as_int(p)
if not isprime(p) or p == 2:
raise ValueError("p should be an odd prime")
a = a % p
if not a:
return 0
if is_quad_residue(a, p):
return 1
return -1
[docs]def jacobi_symbol(m, n):
r"""
Returns the Jacobi symbol `(m / n)`.
For any integer ``m`` and any positive odd integer ``n`` the Jacobi symbol
is defined as the product of the Legendre symbols corresponding to the
prime factors of ``n``:
.. math ::
\genfrac(){}{}{m}{n} =
\genfrac(){}{}{m}{p^{1}}^{\alpha_1}
\genfrac(){}{}{m}{p^{2}}^{\alpha_2}
...
\genfrac(){}{}{m}{p^{k}}^{\alpha_k}
\text{ where } n =
p_1^{\alpha_1}
p_2^{\alpha_2}
...
p_k^{\alpha_k}
Like the Legendre symbol, if the Jacobi symbol `\genfrac(){}{}{m}{n} = -1`
then ``m`` is a quadratic nonresidue modulo ``n``.
But, unlike the Legendre symbol, if the Jacobi symbol
`\genfrac(){}{}{m}{n} = 1` then ``m`` may or may not be a quadratic residue
modulo ``n``.
Parameters
==========
m : integer
n : odd positive integer
Examples
========
>>> from sympy.ntheory import jacobi_symbol, legendre_symbol
>>> from sympy import Mul, S
>>> jacobi_symbol(45, 77)
-1
>>> jacobi_symbol(60, 121)
1
The relationship between the ``jacobi_symbol`` and ``legendre_symbol`` can
be demonstrated as follows:
>>> L = legendre_symbol
>>> S(45).factors()
{3: 2, 5: 1}
>>> jacobi_symbol(7, 45) == L(7, 3)**2 * L(7, 5)**1
True
See Also
========
is_quad_residue, legendre_symbol
"""
m, n = as_int(m), as_int(n)
if n < 0 or not n % 2:
raise ValueError("n should be an odd positive integer")
if m < 0 or m > n:
m = m % n
if not m:
return int(n == 1)
if n == 1 or m == 1:
return 1
if igcd(m, n) != 1:
return 0
j = 1
if m < 0:
m = -m
if n % 4 == 3:
j = -j
while m != 0:
while m % 2 == 0 and m > 0:
m >>= 1
if n % 8 in [3, 5]:
j = -j
m, n = n, m
if m % 4 == 3 and n % 4 == 3:
j = -j
m %= n
if n != 1:
j = 0
return j
[docs]class mobius(Function):
"""
Möbius function maps natural number to {-1, 0, 1}
It is defined as follows:
1) `1` if `n = 1`.
2) `0` if `n` has a squared prime factor.
3) `(-1)^k` if `n` is a square-free positive integer with `k`
number of prime factors.
It is an important multiplicative function in number theory
and combinatorics. It has applications in mathematical series,
algebraic number theory and also physics (Fermion operator has very
concrete realization with Möbius Function model).
Parameters
==========
n : positive integer
Examples
========
>>> from sympy.ntheory import mobius
>>> mobius(13*7)
1
>>> mobius(1)
1
>>> mobius(13*7*5)
-1
>>> mobius(13**2)
0
References
==========
.. [1] https://en.wikipedia.org/wiki/M%C3%B6bius_function
.. [2] Thomas Koshy "Elementary Number Theory with Applications"
"""
@classmethod
def eval(cls, n):
if n.is_integer:
if n.is_positive is not True:
raise ValueError("n should be a positive integer")
else:
raise TypeError("n should be an integer")
if n.is_prime:
return S.NegativeOne
elif n is S.One:
return S.One
elif n.is_Integer:
a = factorint(n)
if any(i > 1 for i in a.values()):
return S.Zero
return S.NegativeOne**len(a)
def _discrete_log_trial_mul(n, a, b, order=None):
"""
Trial multiplication algorithm for computing the discrete logarithm of
``a`` to the base ``b`` modulo ``n``.
The algorithm finds the discrete logarithm using exhaustive search. This
naive method is used as fallback algorithm of ``discrete_log`` when the
group order is very small.
Examples
========
>>> from sympy.ntheory.residue_ntheory import _discrete_log_trial_mul
>>> _discrete_log_trial_mul(41, 15, 7)
3
See Also
========
discrete_log
References
==========
.. [1] "Handbook of applied cryptography", Menezes, A. J., Van, O. P. C., &
Vanstone, S. A. (1997).
"""
a %= n
b %= n
if order is None:
order = n
x = 1
for i in range(order):
if x == a:
return i
x = x * b % n
raise ValueError("Log does not exist")
def _discrete_log_shanks_steps(n, a, b, order=None):
"""
Baby-step giant-step algorithm for computing the discrete logarithm of
``a`` to the base ``b`` modulo ``n``.
The algorithm is a time-memory trade-off of the method of exhaustive
search. It uses `O(sqrt(m))` memory, where `m` is the group order.
Examples
========
>>> from sympy.ntheory.residue_ntheory import _discrete_log_shanks_steps
>>> _discrete_log_shanks_steps(41, 15, 7)
3
See Also
========
discrete_log
References
==========
.. [1] "Handbook of applied cryptography", Menezes, A. J., Van, O. P. C., &
Vanstone, S. A. (1997).
"""
a %= n
b %= n
if order is None:
order = n_order(b, n)
m = isqrt(order) + 1
T = dict()
x = 1
for i in range(m):
T[x] = i
x = x * b % n
z = mod_inverse(b, n)
z = pow(z, m, n)
x = a
for i in range(m):
if x in T:
return i * m + T[x]
x = x * z % n
raise ValueError("Log does not exist")
def _discrete_log_pollard_rho(n, a, b, order=None, retries=10, rseed=None):
"""
Pollard's Rho algorithm for computing the discrete logarithm of ``a`` to
the base ``b`` modulo ``n``.
It is a randomized algorithm with the same expected running time as
``_discrete_log_shanks_steps``, but requires a negligible amount of memory.
Examples
========
>>> from sympy.ntheory.residue_ntheory import _discrete_log_pollard_rho
>>> _discrete_log_pollard_rho(227, 3**7, 3)
7
See Also
========
discrete_log
References
==========
.. [1] "Handbook of applied cryptography", Menezes, A. J., Van, O. P. C., &
Vanstone, S. A. (1997).
"""
a %= n
b %= n
if order is None:
order = n_order(b, n)
prng = Random()
if rseed is not None:
prng.seed(rseed)
for i in range(retries):
aa = prng.randint(1, order - 1)
ba = prng.randint(1, order - 1)
xa = pow(b, aa, n) * pow(a, ba, n) % n
c = xa % 3
if c == 0:
xb = a * xa % n
ab = aa
bb = (ba + 1) % order
elif c == 1:
xb = xa * xa % n
ab = (aa + aa) % order
bb = (ba + ba) % order
else:
xb = b * xa % n
ab = (aa + 1) % order
bb = ba
for j in range(order):
c = xa % 3
if c == 0:
xa = a * xa % n
ba = (ba + 1) % order
elif c == 1:
xa = xa * xa % n
aa = (aa + aa) % order
ba = (ba + ba) % order
else:
xa = b * xa % n
aa = (aa + 1) % order
c = xb % 3
if c == 0:
xb = a * xb % n
bb = (bb + 1) % order
elif c == 1:
xb = xb * xb % n
ab = (ab + ab) % order
bb = (bb + bb) % order
else:
xb = b * xb % n
ab = (ab + 1) % order
c = xb % 3
if c == 0:
xb = a * xb % n
bb = (bb + 1) % order
elif c == 1:
xb = xb * xb % n
ab = (ab + ab) % order
bb = (bb + bb) % order
else:
xb = b * xb % n
ab = (ab + 1) % order
if xa == xb:
r = (ba - bb) % order
try:
e = mod_inverse(r, order) * (ab - aa) % order
if (pow(b, e, n) - a) % n == 0:
return e
except ValueError:
pass
break
raise ValueError("Pollard's Rho failed to find logarithm")
def _discrete_log_pohlig_hellman(n, a, b, order=None):
"""
Pohlig-Hellman algorithm for computing the discrete logarithm of ``a`` to
the base ``b`` modulo ``n``.
In order to compute the discrete logarithm, the algorithm takes advantage
of the factorization of the group order. It is more efficient when the
group order factors into many small primes.
Examples
========
>>> from sympy.ntheory.residue_ntheory import _discrete_log_pohlig_hellman
>>> _discrete_log_pohlig_hellman(251, 210, 71)
197
See Also
========
discrete_log
References
==========
.. [1] "Handbook of applied cryptography", Menezes, A. J., Van, O. P. C., &
Vanstone, S. A. (1997).
"""
from .modular import crt
a %= n
b %= n
if order is None:
order = n_order(b, n)
f = factorint(order)
l = [0] * len(f)
for i, (pi, ri) in enumerate(f.items()):
for j in range(ri):
gj = pow(b, l[i], n)
aj = pow(a * mod_inverse(gj, n), order // pi**(j + 1), n)
bj = pow(b, order // pi, n)
cj = discrete_log(n, aj, bj, pi, True)
l[i] += cj * pi**j
d, _ = crt([pi**ri for pi, ri in f.items()], l)
return d
[docs]def discrete_log(n, a, b, order=None, prime_order=None):
"""
Compute the discrete logarithm of ``a`` to the base ``b`` modulo ``n``.
This is a recursive function to reduce the discrete logarithm problem in
cyclic groups of composite order to the problem in cyclic groups of prime
order.
It employs different algorithms depending on the problem (subgroup order
size, prime order or not):
* Trial multiplication
* Baby-step giant-step
* Pollard's Rho
* Pohlig-Hellman
Examples
========
>>> from sympy.ntheory import discrete_log
>>> discrete_log(41, 15, 7)
3
References
==========
.. [1] http://mathworld.wolfram.com/DiscreteLogarithm.html
.. [2] "Handbook of applied cryptography", Menezes, A. J., Van, O. P. C., &
Vanstone, S. A. (1997).
"""
n, a, b = as_int(n), as_int(a), as_int(b)
if order is None:
order = n_order(b, n)
if prime_order is None:
prime_order = isprime(order)
if order < 1000:
return _discrete_log_trial_mul(n, a, b, order)
elif prime_order:
if order < 1000000000000:
return _discrete_log_shanks_steps(n, a, b, order)
return _discrete_log_pollard_rho(n, a, b, order)
return _discrete_log_pohlig_hellman(n, a, b, order)
