SAT Functions for Boolean Polynomials

These highlevel functions support solving and learning from Boolean polynomial systems. In this context, “learning” means the construction of new polynomials in the ideal spanned by the original polynomials.

AUTHOR:

  • Martin Albrecht (2012): initial version

Functions

sage.sat.boolean_polynomials.learn(F, converter=None, solver=None, max_learnt_length=3, interreduction=False, **kwds)

Learn new polynomials by running SAT-solver solver on SAT-instance produced by converter from F.

INPUT:

  • F - a sequence of Boolean polynomials
  • converter - an ANF to CNF converter class or object. If converter is None then sage.sat.converters.polybori.CNFEncoder is used to construct a new converter. (default: None)
  • solver - a SAT-solver class or object. If solver is None then sage.sat.solvers.cryptominisat.CryptoMiniSat is used to construct a new converter. (default: None)
  • max_learnt_length - only clauses of length <= max_length_learnt are considered and converted to polynomials. (default: 3)
  • interreduction - inter-reduce the resulting polynomials (default: False)

Note

More parameters can be passed to the converter and the solver by prefixing them with c_ and s_ respectively. For example, to increase CryptoMiniSat’s verbosity level, pass s_verbosity=1.

OUTPUT:

A sequence of Boolean polynomials.

EXAMPLES:

sage: from sage.sat.boolean_polynomials import learn as learn_sat # optional - cryptominisat

We construct a simple system and solve it:

sage: set_random_seed(2300)                      # optional - cryptominisat
sage: sr = mq.SR(1,2,2,4,gf2=True,polybori=True) # optional - cryptominisat
sage: F,s = sr.polynomial_system()               # optional - cryptominisat
sage: H = learn_sat(F)                           # optional - cryptominisat
sage: H[-1]                                      # optional - cryptominisat
k033 + 1
sage.sat.boolean_polynomials.solve(F, converter=None, solver=None, n=1, target_variables=None, **kwds)

Solve system of Boolean polynomials F by solving the SAT-problem – produced by converter – using solver.

INPUT:

  • F - a sequence of Boolean polynomials
  • n - number of solutions to return. If n is +infinity then all solutions are returned. If n <infinity then n solutions are returned if F has at least n solutions. Otherwise, all solutions of F are returned. (default: 1)
  • converter - an ANF to CNF converter class or object. If converter is None then sage.sat.converters.polybori.CNFEncoder is used to construct a new converter. (default: None)
  • solver - a SAT-solver class or object. If solver is None then sage.sat.solvers.cryptominisat.CryptoMiniSat is used to construct a new converter. (default: None)
  • target_variables - a list of variables. The elements of the list are used to exclude a particular combination of variable assignments of a solution from any further solution. Furthermore target_variables denotes which variable-value pairs appear in the solutions. If target_variables is None all variables appearing in the polynomials of F are used to construct exclusion clauses. (default: None)
  • **kwds - parameters can be passed to the converter and the
    solver by prefixing them with c_ and s_ respectively. For example, to increase CryptoMiniSat’s verbosity level, pass s_verbosity=1.

OUTPUT:

A list of dictionaries, each of which contains a variable assignment solving F.

EXAMPLES:

We construct a very small-scale AES system of equations:

sage: sr = mq.SR(1,1,1,4,gf2=True,polybori=True)
sage: F,s = sr.polynomial_system()

and pass it to a SAT solver:

sage: from sage.sat.boolean_polynomials import solve as solve_sat # optional - cryptominisat
sage: s = solve_sat(F)                                            # optional - cryptominisat
sage: F.subs(s[0])                                                # optional - cryptominisat
Polynomial Sequence with 36 Polynomials in 0 Variables

This time we pass a few options through to the converter and the solver:

sage: s = solve_sat(F, s_verbosity=1, c_max_vars_sparse=4, c_cutting_number=8) # optional - cryptominisat
c --> ...
...
sage: F.subs(s[0])                                                             # optional - cryptominisat
Polynomial Sequence with 36 Polynomials in 0 Variables

We construct a very simple system with three solutions and ask for a specific number of solutions:

sage: B.<a,b> = BooleanPolynomialRing() # optional - cryptominisat
sage: f = a*b                           # optional - cryptominisat
sage: l = solve_sat([f],n=1)            # optional - cryptominisat
sage: len(l) == 1, f.subs(l[0])         # optional - cryptominisat
(True, 0)

sage: l = sorted(solve_sat([a*b],n=2))        # optional - cryptominisat
sage: len(l) == 2, f.subs(l[0]), f.subs(l[1]) # optional - cryptominisat
(True, 0, 0)

sage: sorted(solve_sat([a*b],n=3))         # optional - cryptominisat
[{b: 0, a: 0}, {b: 0, a: 1}, {b: 1, a: 0}]
sage: sorted(solve_sat([a*b],n=4))         # optional - cryptominisat
[{b: 0, a: 0}, {b: 0, a: 1}, {b: 1, a: 0}]
sage: sorted(solve_sat([a*b],n=infinity))  # optional - cryptominisat
[{b: 0, a: 0}, {b: 0, a: 1}, {b: 1, a: 0}]

In the next example we see how the target_variables parameter works:

sage: from sage.sat.boolean_polynomials import solve as solve_sat # optional - cryptominisat
sage: R.<a,b,c,d> = BooleanPolynomialRing()                       # optional - cryptominisat
sage: F = [a+b,a+c+d]                                             # optional - cryptominisat

First the normal use case:

sage: sorted(solve_sat(F,n=infinity))                             # optional - cryptominisat
[{d: 0, c: 0, b: 0, a: 0},
 {d: 0, c: 1, b: 1, a: 1},
 {d: 1, c: 0, b: 1, a: 1},
 {d: 1, c: 1, b: 0, a: 0}]

Now we are only interested in the solutions of the variables a and b:

sage: solve_sat(F,n=infinity,target_variables=[a,b])              # optional - cryptominisat
[{b: 0, a: 0}, {b: 1, a: 1}]

Note

Although supported, passing converter and solver objects instead of classes is discouraged because these objects are stateful.