def solve_mod(eqns, modulus, solution_dict=False):
r"""
Return all solutions to an equation or list of equations modulo the
given integer modulus. Each equation must involve only polynomials
in 1 or many variables.
By default the solutions are returned as `n`-tuples, where `n`
is the number of variables appearing anywhere in the given
equations. The variables are in alphabetical order.
INPUT:
- ``eqns`` - equation or list of equations
- ``modulus`` - an integer
- ``solution_dict`` - bool (default: False); if True or non-zero,
return a list of dictionaries containing the solutions. If there
are no solutions, return an empty list (rather than a list containing
an empty dictionary). Likewise, if there's only a single solution,
return a list containing one dictionary with that solution.
EXAMPLES::
sage: var('x,y')
(x, y)
sage: solve_mod([x^2 + 2 == x, x^2 + y == y^2], 14)
[(4, 2), (4, 6), (4, 9), (4, 13)]
sage: solve_mod([x^2 == 1, 4*x == 11], 15)
[(14,)]
Fermat's equation modulo 3 with exponent 5::
sage: var('x,y,z')
(x, y, z)
sage: solve_mod([x^5 + y^5 == z^5], 3)
[(0, 0, 0), (0, 1, 1), (0, 2, 2), (1, 0, 1), (1, 1, 2), (1, 2, 0), (2, 0, 2), (2, 1, 0), (2, 2, 1)]
We can solve with respect to a bigger modulus if it consists only of small prime factors::
sage: [d] = solve_mod([5*x + y == 3, 2*x - 3*y == 9], 3*5*7*11*19*23*29, solution_dict = True)
sage: d[x]
12915279
sage: d[y]
8610183
For cases where there are relatively few solutions and the prime
factors are small, this can be efficient even if the modulus itself
is large::
sage: sorted(solve_mod([x^2 == 41], 10^20))
[(4538602480526452429,), (11445932736758703821,), (38554067263241296179,),
(45461397519473547571,), (54538602480526452429,), (61445932736758703821,),
(88554067263241296179,), (95461397519473547571,)]
We solve a simple equation modulo 2::
sage: x,y = var('x,y')
sage: solve_mod([x == y], 2)
[(0, 0), (1, 1)]
.. warning::
The current implementation splits the modulus into prime
powers, then naively enumerates all possible solutions
(starting modulo primes and then working up through prime
powers), and finally combines the solution using the Chinese
Remainder Theorem. The interface is good, but the algorithm is
very inefficient if the modulus has some larger prime factors! Sage
*does* have the ability to do something much faster in certain
cases at least by using Groebner basis, linear algebra
techniques, etc. But for a lot of toy problems this function as
is might be useful. At least it establishes an interface.
TESTS:
Make sure that we short-circuit in at least some cases::
sage: solve_mod([2*x==1], 2*next_prime(10^50))
[]
Try multi-equation cases::
sage: x, y, z = var("x y z")
sage: solve_mod([2*x^2 + x*y, -x*y+2*y^2+x-2*y, -2*x^2+2*x*y-y^2-x-y], 12)
[(0, 0), (4, 4), (0, 3), (4, 7)]
sage: eqs = [-y^2+z^2, -x^2+y^2-3*z^2-z-1, -y*z-z^2-x-y+2, -x^2-12*z^2-y+z]
sage: solve_mod(eqs, 11)
[(8, 5, 6)]
Confirm that modulus 1 now behaves as it should::
sage: x, y = var("x y")
sage: solve_mod([x==1], 1)
[(0,)]
sage: solve_mod([2*x^2+x*y, -x*y+2*y^2+x-2*y, -2*x^2+2*x*y-y^2-x-y], 1)
[(0, 0)]
"""
from sage.rings.all import Integer, Integers, crt_basis
from sage.symbolic.expression import is_Expression
from sage.misc.all import cartesian_product_iterator
from sage.modules.all import vector
from sage.matrix.all import matrix
if not isinstance(eqns, (list, tuple)):
eqns = [eqns]
eqns = [eq if is_Expression(eq) else (eq.lhs() - eq.rhs()) for eq in eqns]
modulus = Integer(modulus)
if modulus < 1:
raise ValueError("the modulus must be a positive integer")
vars = list(set(sum([list(e.variables()) for e in eqns], [])))
vars.sort(key=repr)
if modulus == 1: # degenerate case
ans = [tuple(Integers(1)(0) for v in vars)]
return ans
factors = modulus.factor()
crt_basis = vector(Integers(modulus),
crt_basis([p**i for p, i in factors]))
solutions = []
has_solution = True
for p, i in factors:
solution = _solve_mod_prime_power(eqns, p, i, vars)
if len(solution) > 0:
solutions.append(solution)
else:
has_solution = False
break
ans = []
if has_solution:
for solution in cartesian_product_iterator(solutions):
solution_mat = matrix(Integers(modulus), solution)
ans.append(
tuple(
c.dot_product(crt_basis) for c in solution_mat.columns()))
# if solution_dict == True:
# Relaxed form suggested by Mike Hansen (#8553):
if solution_dict:
sol_dict = [dict(zip(vars, solution)) for solution in ans]
return sol_dict
else:
return ans
def solve_mod(eqns, modulus, solution_dict = False):
r"""
Return all solutions to an equation or list of equations modulo the
given integer modulus. Each equation must involve only polynomials
in 1 or many variables.
By default the solutions are returned as `n`-tuples, where `n`
is the number of variables appearing anywhere in the given
equations. The variables are in alphabetical order.
INPUT:
- ``eqns`` - equation or list of equations
- ``modulus`` - an integer
- ``solution_dict`` - bool (default: False); if True or non-zero,
return a list of dictionaries containing the solutions. If there
are no solutions, return an empty list (rather than a list containing
an empty dictionary). Likewise, if there's only a single solution,
return a list containing one dictionary with that solution.
EXAMPLES::
sage: var('x,y')
(x, y)
sage: solve_mod([x^2 + 2 == x, x^2 + y == y^2], 14)
[(4, 2), (4, 6), (4, 9), (4, 13)]
sage: solve_mod([x^2 == 1, 4*x == 11], 15)
[(14,)]
Fermat's equation modulo 3 with exponent 5::
sage: var('x,y,z')
(x, y, z)
sage: solve_mod([x^5 + y^5 == z^5], 3)
[(0, 0, 0), (0, 1, 1), (0, 2, 2), (1, 0, 1), (1, 1, 2), (1, 2, 0), (2, 0, 2), (2, 1, 0), (2, 2, 1)]
We can solve with respect to a bigger modulus if it consists only of small prime factors::
sage: [d] = solve_mod([5*x + y == 3, 2*x - 3*y == 9], 3*5*7*11*19*23*29, solution_dict = True)
sage: d[x]
12915279
sage: d[y]
8610183
For cases where there are relatively few solutions and the prime
factors are small, this can be efficient even if the modulus itself
is large::
sage: sorted(solve_mod([x^2 == 41], 10^20))
[(4538602480526452429,), (11445932736758703821,), (38554067263241296179,),
(45461397519473547571,), (54538602480526452429,), (61445932736758703821,),
(88554067263241296179,), (95461397519473547571,)]
We solve a simple equation modulo 2::
sage: x,y = var('x,y')
sage: solve_mod([x == y], 2)
[(0, 0), (1, 1)]
.. warning::
The current implementation splits the modulus into prime
powers, then naively enumerates all possible solutions
(starting modulo primes and then working up through prime
powers), and finally combines the solution using the Chinese
Remainder Theorem. The interface is good, but the algorithm is
very inefficient if the modulus has some larger prime factors! Sage
*does* have the ability to do something much faster in certain
cases at least by using Groebner basis, linear algebra
techniques, etc. But for a lot of toy problems this function as
is might be useful. At least it establishes an interface.
TESTS:
Make sure that we short-circuit in at least some cases::
sage: solve_mod([2*x==1], 2*next_prime(10^50))
[]
Try multi-equation cases::
sage: x, y, z = var("x y z")
sage: solve_mod([2*x^2 + x*y, -x*y+2*y^2+x-2*y, -2*x^2+2*x*y-y^2-x-y], 12)
[(0, 0), (4, 4), (0, 3), (4, 7)]
sage: eqs = [-y^2+z^2, -x^2+y^2-3*z^2-z-1, -y*z-z^2-x-y+2, -x^2-12*z^2-y+z]
sage: solve_mod(eqs, 11)
[(8, 5, 6)]
Confirm that modulus 1 now behaves as it should::
sage: x, y = var("x y")
sage: solve_mod([x==1], 1)
[(0,)]
sage: solve_mod([2*x^2+x*y, -x*y+2*y^2+x-2*y, -2*x^2+2*x*y-y^2-x-y], 1)
[(0, 0)]
"""
from sage.rings.all import Integer, Integers, crt_basis
from sage.symbolic.expression import is_Expression
from sage.misc.all import cartesian_product_iterator
from sage.modules.all import vector
from sage.matrix.all import matrix
if not isinstance(eqns, (list, tuple)):
eqns = [eqns]
eqns = [eq if is_Expression(eq) else (eq.lhs()-eq.rhs()) for eq in eqns]
modulus = Integer(modulus)
if modulus < 1:
raise ValueError("the modulus must be a positive integer")
vars = list(set(sum([list(e.variables()) for e in eqns], [])))
vars.sort(key=repr)
if modulus == 1: # degenerate case
ans = [tuple(Integers(1)(0) for v in vars)]
return ans
factors = modulus.factor()
crt_basis = vector(Integers(modulus), crt_basis([p**i for p,i in factors]))
solutions = []
has_solution = True
for p,i in factors:
solution =_solve_mod_prime_power(eqns, p, i, vars)
if len(solution) > 0:
solutions.append(solution)
else:
has_solution = False
break
ans = []
if has_solution:
for solution in cartesian_product_iterator(solutions):
solution_mat = matrix(Integers(modulus), solution)
ans.append(tuple(c.dot_product(crt_basis) for c in solution_mat.columns()))
# if solution_dict == True:
# Relaxed form suggested by Mike Hansen (#8553):
if solution_dict:
sol_dict = [dict(zip(vars, solution)) for solution in ans]
return sol_dict
else:
return ans