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A Tour of NTL: Examples: Modular Arithmetic </title>
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A Tour of NTL: Examples: Modular Arithmetic
</p>
</h1>
<p> <hr> <p>
NTL also supports modular integer arithmetic.
The class <tt>ZZ_p</tt>
represents the integers mod <tt>p</tt>.
Despite the notation, <tt>p</tt> need not in general be prime,
except in situations where this is mathematically required.
The classes <tt>vec_ZZ_p</tt>, <tt>mat_ZZ_p</tt>,
and <tt>ZZ_pX</tt> represent vectors, matrices, and polynomials
mod <tt>p</tt>, and work much the same way as the corresponding
classes for <tt>ZZ</tt>.
<p>
Here is a program that reads a prime number <tt>p</tt>,
and a polynomial <tt>f</tt> modulo <tt>p</tt>, and factors it.
<p>
<pre>
#include <NTL/ZZ_pXFactoring.h>
int main()
{
ZZ p;
cin >> p;
ZZ_p::init(p);
ZZ_pX f;
cin >> f;
vec_pair_ZZ_pX_long factors;
CanZass(factors, f);
cout << factors << "\n";
// calls "Cantor/Zassenhaus" algorithm
}
</pre>
<p>
As a program is running, NTL keeps track of a "current modulus"
for the class <tt>ZZ_p</tt>, which can be initialized or changed
using <tt>ZZ_p::init</tt>.
This must be done before any variables are declared or
computations are done that depend on this modulus.
<p>
Please note that for efficiency reasons,
NTL does not make any attempt to ensure that
variables declared under one modulus are not used
under a different one.
If that happens, the behavior of a program in this
case is completely unpredictable.
<p> <hr> <p>
Here are two more examples that illustrate the <tt>ZZ_p</tt>-related
classes.
The first is a vector addition routine (already supplied by NTL):
<p>
<pre>
#include <NTL/vec_ZZ_p.h>
void add(vec_ZZ_p& x, const vec_ZZ_p& a, const vec_ZZ_p& b)
{
long n = a.length();
if (b.length() != n) Error("vector add: dimension mismatch");
x.SetLength(n);
long i;
for (i = 0; i < n; i++)
add(x[i], a[i], b[i]);
}
</pre>
<p>
The second example is an inner product routine (also supplied by NTL):
<p>
<pre>
#include <NTL/vec_ZZ_p.h>
void InnerProduct(ZZ_p& x, const vec_ZZ_p& a, const vec_ZZ_p& b)
{
long n = min(a.length(), b.length());
long i;
ZZ accum, t;
accum = 0;
for (i = 0; i < n; i++) {
mul(t, rep(a[i]), rep(b[i]));
add(accum, accum, t);
}
conv(x, accum);
}
</pre>
<p>
This second example illustrates two things.
First, it illustrates the use of function <tt>rep</tt> which
returns a read-only reference to the representation of a <tt>ZZ_p</tt>
as a <tt>ZZ</tt> between <tt>0</tt> and <tt>p-1</tt>.
Second, it illustrates a useful algorithmic technique,
whereby one computes over <tt>ZZ</tt>, reducing mod <tt>p</tt>
only when necessary.
This reduces the number of divisions that need to be performed significantly,
leading to much faster execution.
<p>
The class <tt>ZZ_p</tt> supports all the basic arithmetic
operations in both operator and procedural form.
All of the basic operations support a "promotion logic",
promoting <tt>long</tt> to <tt>ZZ_p</tt>.
<p>
Note that the class <tt>ZZ_p</tt> is mainly useful only
when you want to work with vectors, matrices, or polynomials
mod <tt>p</tt>.
If you just want to do some simple modular arithemtic,
it is probably easier to just work with <tt>ZZ</tt>s directly.
This is especially true if you want to work with many different
moduli: modulus switching is supported, but it is a bit awkward.
<p>
The class <tt>ZZ_pX</tt> supports all the basic arithmetic
operations in both operator and procedural form.
All of the basic operations support a "promotion logic",
promoting both <tt>long</tt> and <tt>ZZ_p</tt> to <tt>ZZ_pX</tt>.
<p>
See <a href="ZZ_p.txt"><tt>ZZ_p.txt</tt></a> for details on <tt>ZZ_p</tt>;
see <a href="ZZ_pX.txt"><tt>ZZ_pX.txt</tt></a> for details on <tt>ZZ_pX</tt>;
see <a href="ZZ_pXFactoring.txt"><tt>ZZ_pXFactoring.txt</tt></a> for details on
the routines for factoring polynomials over <tt>ZZ_p</tt>;
see <a href="vec_ZZ_p.txt"><tt>vec_ZZ_p.txt</tt></a> for details on <tt>vec_ZZ_p</tt>;
see <a href="mat_ZZ_p.txt"><tt>mat_ZZ_p.txt</tt></a> for details on <tt>mat_ZZ_p</tt>.
<p> <hr> <p>
There is a mechanism for saving and restoring a modulus,
which the following example illustrates.
This routine takes as input an integer polynomial
and a prime, and tests if the polynomial is irreducible modulo
the prime.
<p>
<pre>
#include <NTL/ZZX.h>
#include <NTL/ZZ_pXFactoring.h>
long IrredTestMod(const ZZX& f, const ZZ& p)
{
ZZ_pBak bak; // save current modulus in bak
bak.save();
ZZ_p::init(p); // set the current modulus to p
return DetIrredTest(to_ZZ_pX(f));
// old modulus is restored automatically when bak is destroyed
// upon return
}
</pre>
<p>
The modulus switching mechanism is actually quite a bit
more general and flexible than this example illustrates.
<p>
The function <tt>to_ZZ_pX</tt> is yet another of NTL's many
conversion functions.
We could also have used the equivalent procedural form:
<pre>
ZZ_pX f1;
conv(f1, f);
return DetIrredTest(f1);
</pre>
<p> <hr> <p>
Suppose in the above example that <tt>p</tt> is known in advance
to be a small, single-precision prime.
In this case, NTL provides a class <tt>zz_p</tt>, that
acts just like <tt>ZZ_p</tt>,
along with corresponding classes <tt>vec_zz_p</tt>,
<tt>mat_zz_p</tt>, and <tt>zz_pX</tt>.
The interfaces to all of the routines are generally identical
to those for <tt>ZZ_p</tt>.
However, the routines are much more efficient, in both time and space.
<p>
For small primes, the routine in the previous example could be coded
as follows.
<p>
<pre>
#include <NTL/ZZX.h>
#include <NTL/lzz_pXFactoring.h>
long IrredTestMod(const ZZX& f, long p)
{
zz_pBak bak;
bak.save();
zz_p::init(p);
return DetIrredTest(to_zz_pX(f));
}
</pre>
<p> <hr> <p>
The following is a routine (essentially the same as implemented in NTL)
for computing the GCD of polynomials with integer coefficients.
It uses a "modular" approach: the GCDs are computed modulo small
primes, and the results are combined using the Chinese Remainder Theorem (CRT).
The small primes are specially chosen "FFT primes", which are of
a special form that allows for particular fast polynomial arithmetic.
<p>
<pre>
#include <NTL/ZZX.h>
void GCD(ZZX& d, const ZZX& a, const ZZX& b)
{
if (a == 0) {
d = b;
if (LeadCoeff(d) < 0) negate(d, d);
return;
}
if (b == 0) {
d = a;
if (LeadCoeff(d) < 0) negate(d, d);
return;
}
ZZ c1, c2, c;
ZZX f1, f2;
content(c1, a);
divide(f1, a, c1);
content(c2, b);
divide(f2, b, c2);
GCD(c, c1, c2);
ZZ ld;
GCD(ld, LeadCoeff(f1), LeadCoeff(f2));
ZZX g, res;
ZZ prod;
zz_pBak bak;
bak.save();
long FirstTime = 1;
long i;
for (i = 0; ;i++) {
zz_p::FFTInit(i);
long p = zz_p::modulus();
if (divide(LeadCoeff(f1), p) || divide(LeadCoeff(f2), p)) continue;
zz_pX G, F1, F2;
zz_p LD;
conv(F1, f1);
conv(F2, f2);
conv(LD, ld);
GCD(G, F1, F2);
mul(G, G, LD);
if (deg(G) == 0) {
res = 1;
break;
}
if (FirstTime || deg(G) < deg(g)) {
prod = 1;
g = 0;
FirstTime = 0;
}
else if (deg(G) > deg(g)) {
continue;
}
if (!CRT(g, prod, G)) {
PrimitivePart(res, g);
if (divide(f1, res) && divide(f2, res))
break;
}
}
mul(d, res, c);
if (LeadCoeff(d) < 0) negate(d, d);
}
</pre>
<p>
See <a href="lzz_p.txt"><tt>lzz_p.txt</tt></a> for details on <tt>zz_p</tt>;
see <a href="lzz_pX.txt"><tt>lzz_pX.txt</tt></a> for details on <tt>zz_pX</tt>;
see <a href="lzz_pXFactoring.txt"><tt>lzz_pXFactoring.txt</tt></a> for details on
the routines for factoring polynomials over <tt>zz_p</tt>;
see <a href="vec_lzz_p.txt"><tt>vec_lzz_p.txt</tt></a> for details on <tt>vec_zz_p</tt>;
see <a href="mat_lzz_p.txt"><tt>mat_lzz_p.txt</tt></a> for details on <tt>mat_zz_p</tt>.
<p> <hr> <p>
Arithmetic mod 2 is such an important special case that NTL
provides a class <tt>GF2</tt>, that
acts just like <tt>ZZ_p</tt> when <tt>p == 2</tt>,
along with corresponding classes <tt>vec_GF2</tt>,
<tt>mat_GF2</tt>, and <tt>GF2X</tt>.
The interfaces to all of the routines are generally identical
to those for <tt>ZZ_p</tt>.
However, the routines are much more efficient, in both time and space.
<p>
This example illustrates the <tt>GF2X</tt> and <tt>mat_GF2</tt>
classes with a simple routine to test if a polynomial over GF(2)
is irreducible using linear algebra.
NTL's built-in irreducibility test is to be preferred, however.
<pre>
#include <NTL/GF2X.h>
#include <NTL/mat_GF2.h>
long MatIrredTest(const GF2X& f)
{
long n = deg(f);
if (n <= 0) return 0;
if (n == 1) return 1;
if (GCD(f, diff(f)) != 1) return 0;
mat_GF2 M;
M.SetDims(n, n);
GF2X x_squared = GF2X(2, 1);
GF2X g;
g = 1;
for (long i = 0; i < n; i++) {
VectorCopy(M[i], g, n);
M[i][i] += 1;
g = (g * x_squared) % f;
}
long rank = gauss(M);
if (rank == n-1)
return 1;
else
return 0;
}
</pre>
<p>
Note that the statement
<pre>
g = (g * x_squared) % f;
</pre>
could be replace d by the more efficient code sequence
<pre>
MulByXMod(g, g, f);
MulByXMod(g, g, f);
</pre>
but this would not significantly impact the overall
running time, since it is the Gaussian elimination that
dominates the running time.
<p>
See <a href="GF2.txt"><tt>GF2.txt</tt></a> for details on <tt>GF2</tt>;
see <a href="GF2X.txt"><tt>GF2X.txt</tt></a> for details on <tt>GF2X</tt>;
see <a href="GF2XFactoring.txt"><tt>GF2XFactoring.txt</tt></a> for details on
the routines for factoring polynomials over <tt>GF2</tt>;
see <a href="vec_GF2.txt"><tt>vec_GF2.txt</tt></a> for details on <tt>vec_GF2</tt>;
see <a href="mat_GF2.txt"><tt>mat_GF2.txt</tt></a> for details on <tt>mat_GF2</tt>.
<p>
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