public BigInteger[] Solve()
{
/* Solving a linear equation over a residue class is not so trivial if the modulus is not a prime.
* This is because residue classes with a composite modulus is not a field, which means that not all elements
* of this ring do have an inverse.
* We cope with this problem by factorizing the modulus in its prime factors and solving gauss over them
* separately (in the case of p^q (q>1) by using "hensel lifting").
* We can use the chinese remainder theorem to get the solution we need then.
* But what happens if we aren't able to factorize the modulus completely, because this is to inefficient?
* There is a simple trick to cope with that:
* Try the gauss algorithm with the composite modulus. Either you have luck and it works out without a problem
* (in this case we can just go on), or the gauss algorithm will have a problem inverting some number.
* In the last case, we can search for the gcd of this number and the composite modulus. This gcd is a factor of the modulus,
* so that solving the equation helped us finding the factorization.
*/
FiniteFieldGauss gauss = new FiniteFieldGauss();
HenselLifting hensel = new HenselLifting();
List <Msieve.Factor> modfactors = Msieve.TrivialFactorization(mod);
List <KeyValuePair <BigInteger[], Msieve.Factor> > results; //Stores the partial solutions together with their factors
bool tryAgain;
try
{
do
{
results = new List <KeyValuePair <BigInteger[], Msieve.Factor> >();
tryAgain = false;
for (int i = 0; i < modfactors.Count; i++)
{
if (modfactors[i].prime) //mod prime
{
if (modfactors[i].count == 1)
{
results.Add(new KeyValuePair <BigInteger[], Msieve.Factor>(gauss.Solve(MatrixCopy(), modfactors[i].factor), modfactors[i]));
}
else
{
results.Add(new KeyValuePair <BigInteger[], Msieve.Factor>(hensel.Solve(MatrixCopy(), modfactors[i].factor, modfactors[i].count), modfactors[i]));
}
}
else //mod composite
{
//Try using gauss:
try
{
BigInteger[] res = gauss.Solve(MatrixCopy(), modfactors[i].factor);
results.Add(new KeyValuePair <BigInteger[], Msieve.Factor>(res, modfactors[i])); //Yeah, we had luck :)
}
catch (NotInvertibleException ex)
{
//We found a factor of modfactors[i]:
BigInteger notInvertible = ex.NotInvertibleNumber;
List <Msieve.Factor> morefactors = Msieve.TrivialFactorization(modfactors[i].factor / notInvertible);
List <Msieve.Factor> morefactors2 = Msieve.TrivialFactorization(notInvertible);
modfactors.RemoveAt(i);
ConcatFactorLists(modfactors, morefactors);
ConcatFactorLists(modfactors, morefactors2);
tryAgain = true;
break;
}
}
}
} while (tryAgain);
}
catch (LinearDependentException ex)
{
//We have to throw away dependent rows and try again later:
Array.Sort(ex.RowsToDelete, (a, b) => (b - a));
foreach (int row in ex.RowsToDelete)
{
matrix.RemoveAt(row);
}
return(null);
}
BigInteger[] result = new BigInteger[size];
//"glue" the results together:
for (int i = 0; i < size; i++)
{
List <KeyValuePair <BigInteger, BigInteger> > partSolItem = new List <KeyValuePair <BigInteger, BigInteger> >();
for (int c = 0; c < results.Count; c++)
{
partSolItem.Add(new KeyValuePair <BigInteger, BigInteger>(results[c].Key[i], BigInteger.Pow(results[c].Value.factor, results[c].Value.count)));
}
result[i] = CRT(partSolItem);
}
return(result);
}