i have read section about The Extended Euclidean Algorithm & Modular Inverses,which states that it not only computes GCD(n,m) but also a and b such that a*n+b*b=1;
algorithm is described by by this way:
Write down n, m, and the two-vectors (1,0) and (0,1)
Divide the larger of the two numbers by the smaller - call this
quotient q
Subtract q times the smaller from the larger (ie reduce the larger
modulo the smaller)
(i have question here if we denote by q n/m,then n-q*m is not equal to 0?because q=n/m;(assume that n>m),so why it is necessary such kind of operation?
then 4 step
4.Subtract q times the vector corresponding to the smaller from the
vector corresponding to the larger
5.Repeat steps 2 through 4 until the result is zero
6.Publish the preceding result as gcd(n,m)
so my question for this problem also is how can i implement this steps in code?please help me,i dont know how start and from which point could i start to solve such problem,for clarify result ,it should look like this
An example of this algorithm is the following computation of 30^(-1)(mod 53);
53 30 (1,0) (0,1)
53-1*30=23 30 (1,0)-1*(0,1)=(1,-1) (0,1)
23 30-1*23=7 (1,-1) (0,1)-1*(1,-1)=(-1,2)
23-3*7=2 7 (1,-1)-3*(-1,2)=(4,-7) (-1,2)
2 7-3*2=1 (4,-7) (-1,2)-3*(4,7)=(-13,23)
2-2*1=0 1 (4,-7)-2*(-13,23)=(30,-53) (-13,23)
From this we see that gcd(30,53)=1 and, rearranging terms, we see that 1=-13*53+23*30,
so we conclude that 30^(-1)=23(mod 53).
The division is supposed to be integer division with truncation. The standard EA for gcd(a, b) with a <= b goes like this:
b = a * q0 + r0
a = r0 * q1 + r1
r0 = r1 * q2 + r2
...
r[N+1] = 0
Now rN is the desired GCD. Then you back-substitute:
r[N-1] = r[N] * q[N+1]
r[N-2] = r[N-1] * q[N] + r[N]
= (r[N] * q[N+1]) * q[N] + r[N]
= r[N] * (q[N+1] * q[N] + 1)
r[N-3] = r[N-2] * q[N-1] + r[N-1]
= ... <substitute> ...
Until you finally reach rN = m * a + n * b. The algorithm you describe keeps track of the backtracking data right away, so it's a bit more efficient.
If rN == gcd(a, b) == 1, then you have indeed found the multiplicative inverse of a modulo b, namely m: (a * m) % b == 1.
Related
I've been trying to solve this problem:
Find Euler's totient function of binomial coefficient C(n, m) = n! / (m! (n - m)!) modulo 10^9 + 7, m <= n < 2 * 10^5.
One of my ideas was that first, we can precalculate the values of phi(i) for all i from 1 to n in linear time, also we can calculate all inverses to numbers from 1 to n modulo 10^9 + 7 using, for example, Fermat's little theorem. After that, we know, that, in general, phi(m * n) = phi(m) * phi(n) * (d / fi(d)), d = gcd(m, n). Because we know that gcd((x - 1)!, x) = 1, if x is prime, 2 if x = 4, and x in all other cases, we can calculate phi(x!) modulo 10^9 + 7 in linear time. However, in the last step, we need to calculate phi(n! / ((m! (n - m)!), (if we already know the function for factorials), so, if we are using this method, we have to know gcd(C(n, m), m! (n - m)!), and I don't know how to find it.
I've also been thinking about factorizing the binomial coefficient, but there seems no efficient way to do this.
Any help would be appreciated.
First, factorize all numbers 1..(2*10^5) as products of prime powers.
Now, factorize n!/k! = n(n-1)(n-2)...(n-k+1) as a product of prime powers by multiplying together the factors of the individual parts. Factorize (n-k)! as a product of prime powers. Subtract the latter powers from the former (to account for the divide).
Now you've got C(n, k) as a product of prime powers. Use the formula phi(N) = N * prod(1 - 1/p for p|N) to calculate phi(C(n, k)), which is straightforward given that you've computed the a list of all the prime powers that divide C(n, k) in the second step.
For example:
phi(C(9, 4)) = 9*8*7*6*5 / 5*4*3*2*1
9*8*7*6*5 = 3*3 * 2*2*2 * 7 * 3*2 * 5 = 7*5*3^3*2^4
5*4*3*2*1 = 5 * 2*2 * 3 * 2 * 1 = 5*3*2^3
9*8*7*6*5/(5*4*3*2*1) = 7*3^2*2
phi(C(9, 4)) = 7*3^2*2 * (1 - 1/7) * (1 - 1/3) * (1 - 1/2) = 36
I've done it in integers rather than integers mod M, but it seems like you already know how division works in the modulo ring.
I use a fairly standard method to retrieve the monic polynomial coefficients from a cubic Bézier curve's control points:
std::array<double, 3> getBezierCubicCoefficients( const std::array<double, 4>& bezier )
{
const auto d = 1.0 / ( bezier[3] - 3*bezier[2] + 3*bezier[1] - bezier[0] );
return { ( 3*bezier[2] - 6*bezier[1] + 3*bezier[0] ) * d,
( 3*bezier[1] - 3*bezier[0] ) * d,
bezier[0] * d };
}
This works fine 99% of the time, but as you have probably guessed, fails under certain coordinates which cause d's divisor to evaluate to zero - causing d to evaluate to Inf.
My question is: what to do under this circumstance?
Have I actually got a quadratic curve in disguise, and should I perform degree reduction instead? Should I just fudge the numbers so d is very large, but won't cause Infs? (I really hope that isn't the answer).
As you probably already know, the monomic coefficients c can be calculated from the Bezier coefficients by multiplying with the following matrix:
/ 1 -3 3 -1 \
| 3 -6 3 |
(c0 c1 c2 c3) = (b0 b1 b2 b3) | 3 -3 |
\ 0 1 /
If the resulting c3 = -b0 + 3b1 - 3b2 + b3 is zero, then you'll get a quadratic polynomial (at most). In degenerate cases, other coefficients can yield 0, too. In the edge case, you end up with a constant.
http://ayazdzulfikar.blogspot.in/2014/12/penggunaan-fenwick-tree-bit.html?showComment=1434865697025#c5391178275473818224
For example being told that the value of the function or f (i) of the index-i is an i ^ k, for k> = 0 and always stay on this matter. Given query like the following:
Add value array [i], for all a <= i <= b as v Determine the total
array [i] f (i), for each a <= i <= b (remember the previous function
values clarification)
To work on this matter, can be formed into Query (x) = m * g (x) - c,
where g (x) is f (1) + f (2) + ... + f (x).
To accomplish this, we
need to know the values of m and c. For that, we need 2 separate
BIT. Observations below for each update in the form of ab v. To
calculate the value of m, virtually identical to the Range Update -
Point Query. We can get the following observations for each value of
i, which may be:
i <a, m = 0
a <= i <= b, m = v
b <i, m = 0
By using the following observation, it is clear that the Range Update - Point Query can be used on any of the BIT. To calculate the value of c, we need to observe the possibility for each value of i, which may be:
i <a, then c = 0
a <= i <= b, then c = v * g (a - 1)
b <i, c = v * (g (b) - g (a - 1))
Again, we need Range Update - Point Query, but in a different BIT.
Oiya, for a little help, I wrote the value of g (x) for k <= 3 yes: p:
k = 0 -> x
k = 1 -> x * (x + 1) / 2
k = 2 -> x * (x + 1) * (2x + 1) / 6
k = 3 -> (x * (x + 1) / 2) ^ 2
Now, example problem SPOJ - Horrible Queries . This problem is
similar issues that have described, with k = 0. Note also that
sometimes there is a matter that is quite extreme, where the function
is not for one type of k, but it could be some that polynomial shape!
Eg LA - Alien Abduction Again . To work on this problem, the solution
is, for each rank we make its BIT counter m respectively. BIT combined
to clear the counters c it was fine.
How can we used this concept if:
Given an array of integers A1,A2,…AN.
Given x,y: Add 1×2 to Ax, add 2×3 to Ax+1, add 3×4 to Ax+2, add 4×5 to
Ax+3, and so on until Ay.
Then return Sum of the range [Ax,Ay].
Using Chebyshev polynomials, we can compute sin(2*Pi/n) exactly using the CGAL and CORE library, like the following piece of codes:
#include <CGAL/CORE_Expr.h>
#include <CGAL/Polynomial.h>
#include <CGAL/number_utils.h>
//return sin(theta) and cos(theta) for theta = 2pi/n
static std::pair<AA, AA> sin_cos(unsigned short n) {
// We actually use -x instead of x since root_of will give the k-th
// smallest root but we want the second largest one without counting.
Polynomial x(CGAL::shift(Polynomial(-1), 1));
Polynomial twox(2*x);
Polynomial a(1), b(x);
for (unsigned short i = 2; i <= n; ++i) {
Polynomial c = twox*b - a;
a = b;
b = c;
}
a = b - 1;
AA cos = -CGAL::root_of(2, a.begin(), a.end());
AA sin = CGAL::sqrt(AA(1) - cos*cos);
return std::make_pair(sin, cos);
}
But if I want to compute sin(2*m*Pi/n) exactly, where m and n are integers, what is the formula of the polynomial that I should use? Thanks.
(Partial solution.)
This is essentially computing the real and imaginary part of the roots of unity as algebraic numbers. Let's denote w(m) = exp(2*pi*I*m/n). Then, w(m) itself is a complex root of En(x) = x^n-1.
You need to find a defining polynomial of Re(w(m)). Resultants are a tool to find such a polynomial: 2*Re(w(m)) is a root of Res (En(x-y), En(y); y).
For an explanation why this is the case: Note that 2*Re(w(m)) = w(m) + conj(w(m)), and that the complex roots of En come in conjugate pairs; hence, also conj(w(m)) is a root of En. Now loosely speaking, the En(y) part "constrains" y to be any (complex) root of En, and combining this with the first argument allows x to take any complex value such that x-y is a root of En as well. Hence, a possible assignment is y = conj(w(m)) and x-y = w(m), hence x = w(m)+conj(w(m)) = 2*Re(w(m)).
CGAL can compute resultants of multivariate polynomials, so you can compute this resultant, and you simply have to pick the correct real root. (The largest one will obviously be w(0) = 1, the smallest one is 2*Re(w(floor(n/2))).)
Unfortunately, the resultant has a high complexity (degree n^2), and resultant computation will not be the fastest operation you've ever seen. Also, you'll pay for dense polynomials although your instances are very sparse and structured. YMMV; I have no clue about your use case, and if you need higher degrees.
However, I did a few tests in a computer algebra system, and I found that the resultant splits into factors of more reasonable size, and that all its real roots actually belong to a much simpler polynomial of degree floor(n/2)+1 only. (No proof, just an observation.)
I don't know of a direct formula to write down this factor, and I don't want to speculate about it. But maybe some people at mathoverflow or math.stackexchange can help?
EDIT: Here is a guess for at least a recursive formula.
I write s(n,x) for the significant factor of the resultant polynomial containing all real roots but 0. This means that s(n,x) has all values 2*Re(w(m)) for m != n/4, 3*n/4 as roots.
s(0,x) = 0
s(1,x) = x - 2
s(2,x) = x^2 - 4
s(3,x) = x^2 - x - 2
s(4,x) = x^2 - 4
s(5,x) = x^3 - x^2 - 3*x + 2
s(6,x) = x^4 - 5*x^2 + 4
s(7,x) = x^4 - x^3 - 4*x^2 + 3*x + 2
s(8,x) = x^4 - 6*x^2 + 8
s(n,x) = (x^2-2)*s(n-4,x) - s(n-8,x)
Waiting for a proof...
I need to find n!%1000000009.
n is of type 2^k for k in range 1 to 20.
The function I'm using is:
#define llu unsigned long long
#define MOD 1000000009
llu mulmod(llu a,llu b) // This function calculates (a*b)%MOD caring about overflows
{
llu x=0,y=a%MOD;
while(b > 0)
{
if(b%2 == 1)
{
x = (x+y)%MOD;
}
y = (y*2)%MOD;
b /= 2;
}
return (x%MOD);
}
llu fun(int n) // This function returns answer to my query ie. n!%MOD
{
llu ans=1;
for(int j=1; j<=n; j++)
{
ans=mulmod(ans,j);
}
return ans;
}
My demand is such that I need to call the function 'fun', n/2 times. My code runs too slow for values of k around 15. Is there a way to go faster?
EDIT:
In actual I'm calculating 2*[(i-1)C(2^(k-1)-1)]*[((2^(k-1))!)^2] for all i in range 2^(k-1) to 2^k. My program demands (nCr)%MOD caring about overflows.
EDIT: I need an efficient way to find nCr%MOD for large n.
The mulmod routine can be speeded up by a large factor K.
1) '%' is overkill, since (a + b) are both less than N.
- It's enough to evaluate c = a+b; if (c>=N) c-=N;
2) Multiple bits can be processed at once; see optimization to "Russian peasant's algorithm"
3) a * b is actually small enough to fit 64-bit unsigned long long without overflow
Since the actual problem is about nCr mod M, the high level optimization requires using the recurrence
(n+1)Cr mod M = (n+1)nCr / (n+1-r) mod M.
Because the left side of the formula ((nCr) mod M)*(n+1) is not divisible by (n+1-r), the division needs to be implemented as multiplication with the modular inverse: (n+r-1)^(-1). The modular inverse b^(-1) is b^(M-1), for M being prime. (Otherwise it's b^(phi(M)), where phi is Euler's Totient function.)
The modular exponentiation is most commonly implemented with repeated squaring, which requires in this case ~45 modular multiplications per divisor.
If you can use the recurrence
nC(r+1) mod M = nCr * (n-r) / (r+1) mod M
It's only necessary to calculate (r+1)^(M-1) mod M once.
Since you are looking for nCr for multiple sequential values of n you can make use of the following:
(n+1)Cr = (n+1)! / ((r!)*(n+1-r)!)
(n+1)Cr = n!*(n+1) / ((r!)*(n-r)!*(n+1-r))
(n+1)Cr = n! / ((r!)*(n-r)!) * (n+1)/(n+1-r)
(n+1)Cr = nCr * (n+1)/(n+1-r)
This saves you from explicitly calling the factorial function for each i.
Furthermore, to save that first call to nCr you can use:
nC(n-1) = n //where n in your case is 2^(k-1).
EDIT:
As Aki Suihkonen pointed out, (a/b) % m != a%m / b%m. So the method above so the method above won't work right out of the box. There are two different solutions to this:
1000000009 is prime, this means that a/b % m == a*c % m where c is the inverse of b modulo m. You can find an explanation of how to calculate it here and follow the link to the Extended Euclidean Algorithm for more on how to calculate it.
The other option which might be easier is to recognize that since nCr * (n+1)/(n+1-r) must give an integer, it must be possible to write n+1-r == a*b where a | nCr and b | n+1 (the | here means divides, you can rewrite that as nCr % a == 0 if you like). Without loss of generality, let a = gcd(n+1-r,nCr) and then let b = (n+1-r) / a. This gives (n+1)Cr == (nCr / a) * ((n+1) / b) % MOD. Now your divisions are guaranteed to be exact, so you just calculate them and then proceed with the multiplication as before. EDIT As per the comments, I don't believe this method will work.
Another thing I might try is in your llu mulmod(llu a,llu b)
llu mulmod(llu a,llu b)
{
llu q = a * b;
if(q < a || q < b) // Overflow!
{
llu x=0,y=a%MOD;
while(b > 0)
{
if(b%2 == 1)
{
x = (x+y)%MOD;
}
y = (y*2)%MOD;
b /= 2;
}
return (x%MOD);
}
else
{
return q % MOD;
}
}
That could also save some precious time.