Problem statement: I am working on a code that calculates big numbers. Hence, I am easily get beyond the maximum length of "long double". Here is an example below, where part of the code is given that generates big numbers:
int n;
long double summ;
a[1]=1;
b[1]=1;
c[1] = 1; //a, b, c are 1D variables of long double types
summ=1+c[1];
for(n=2; n <=1760; n++){
a[n]=n*n;
b[n]=n;
c[n] = c[n-1]*a[n-1]/b[n]; //Let us assume we have this kind of operation
summ= summ+c[n]; //So basically, summ = 1+c[1]+c[2]+c[3]+...+c[1760]
}
The intermediates values of summ and c[n] are then used to evaluate the ratio c[n]/summ for every integer n. Then, just after the above loop, I do:
for(n=1;n<=1760;n++){
c2[n]=c[n]/summ; //summ is thus here equals to 1+c[1]+c[2]+c[3]+...+c[1760]
}
Output: If we print n, c[n] and summ, we obtain inf after n=1755 because we exceed the length of long double:
n c[n] summ
1752 2.097121e+4917 2.098320e+4917
1753 3.672061e+4920 3.674159e+4920
1754 6.433452e+4923 6.437126e+4923
1755 1.127785e+4927 1.128428e+4927
1756 inf inf
1757 inf inf
1758 inf inf
1759 inf inf
1760 inf inf
Of course, if there is an overflow for c[n] and summ, I cannot evaluate the quantity of interest, which is c2[n].
Questions: Does someone see any solution for this ? How do I need to change the code so that to have finite numerical values (for arbitrary n) ?
I will indeed most likely need to go to very big numbers (n can be much larger than 1760).
Proposition: I know that GNU Multiple Precision Arithmetic (GMP) might be useful but honestly found too many difficulties trying to use this (outside the field), so if there an easier way to solve this, I would be glad to read it. Otherwise, I will be forever grateful if someone could apply GMP or any other method to solve the above-mentioned problem.
NOTE: This does not exactly what OP wants. I'll leave this answer here in case someone has a similar problem.
As long as your final result and all initial values are not out of range, you can very often re-arrange your terms to avoid any overflow. In your case if you actually just want to know c2[n] = c[n]/sum[n] you can re-write this as follows:
c2[n] = c[n]/sum[n]
= c[n]/(sum[n-1] + c[n]) // def. of sum[n]
= 1.0/(sum[n-1]/c[n] + 1.0)
= 1.0/(sum[n-1]/(c[n-1] * a[n-1] / b[n]) + 1.0) // def. of c[n]
= 1.0/(sum[n-1]/c[n-1] * b[n] / a[n-1] + 1.0)
= a[n-1]/(1/c2[n-1] * b[n] + a[n-1]) // def. of c2[n-1]
= (a[n-1]*c2[n-1]) / (b[n] + a[n-1]*c2[n-1])
Now in the final expression neither argument grows out of range, and in fact c2 slowly converges towards 1. If the values in your question are the actual values of a[n] and b[n] you may even find a closed form expression for c2[n] (I did not check it).
To check that the re-arrangement works, you can compare it with your original formula (godbolt-link, only printing the last values): https://godbolt.org/z/oW8KsdKK6
Btw: Unless you later need all values of c2 again, there is actually no need to store any intermediate value inside an array.
I ain't no mathematician. This is what I wrote with the results below. Looks to me that the exponent, at least, is keeping up with your long double results using my feeble only double only...
#include <stdio.h>
#include <math.h>
int main() {
int n;
double la[1800], lb[1800], lc[1800];
for( n = 2; n <= 1760; n++ ) {
lb[n] = log10(n);
la[n] = lb[n] + lb[n];
lc[n] = lc[n-1] + la[n-1] - lb[n];
printf( "%4d: %.16lf\n", n, lc[n] );
}
return 0;
}
/* omitted for brevity */
1750: 4910.8357954121602000
1751: 4914.0785853634488000
1752: 4917.3216235537839000
1753: 4920.5649098413542000
1754: 4923.8084440845114000
1755: 4927.0522261417700000 <<=== Take note, please.
1756: 4930.2962558718036000
1757: 4933.5405331334487000
1758: 4936.7850577857016000
1759: 4940.0298296877190000
1760: 4943.2748486988194000
EDIT (Butterfly edition)
Below is a pretty simple iterative function involving one single and one double precision float values. The purpose is to demonstrate that iterative calculations are exceedingly sensitive to initial conditions. While it seems obvious that the extra bits of the double will "hold-on", remaining closer to the results one would get with infinite precision, the compounding discrepancy between these two versions demonstrate that "demons lurking in small places" will likely remain hidden in the fantastically tiny gaps between finite representations of what is infinite.
Just a bit of fun for a rainy day.
int main() {
float fpi = 3.1415926535897932384626433832;
double dpi = 3.1415926535897932384626433832;
double thresh = 10e-8;
for( int i = 0; i < 1000; i++ ) {
fpi = fpi * 1.03f;
dpi = dpi * 1.03f;
double diff = fabs( dpi - fpi );
if( diff > thresh) {
printf( "%3d: %25.16lf\n", i, diff );
thresh *= 10.0;
}
}
return 0;
}
8: 0.0000001229991486
35: 0.0000010704333473
90: 0.0000100210180918
192: 0.0001092634900033
229: 0.0010121794607585
312: 0.0100316228017618
367: 0.1002719746902585
453: 1.0056506423279643
520: 10.2658853083848950
609: 103.8011477291584000
667: 1073.9984381198883000
736: 10288.9632129669190000
807: 101081.5514678955100000
886: 1001512.2135009766000000
966: 10473883.3271484370000000
This is my homework:
I haven't tried to write the part of Natural Logarithm because I can't solve the part of Exponential.
This is the the approximations of Exponential in C using Taylor Series expansion I wrote.
However, it returns inf. What did I do wrong?
#include <stdio.h>
// Returns approximate value of e^x
// using sum of first n terms of Taylor Series
float exponential(int n, float x)
{
float sum = 1.0f; // initialize sum of series
for (int a = n; a >= 0; ++a ) {
while (x * sum / a < 0.00001) {
break;
}
sum = 1 + x * sum / a;
return sum;
}
}
int main()
{
int n = 0;
float x = 1.0f;
printf("e^x = %.5f", exponential(n, x));
return 0;
}
With How do I ask and answer homework questions? in mind, I will give you a few things to have a careful look at.
From comment by Spektre:
from a quick look you are dividing by zero in while (x * sum / a < 0.00001) during first iteration of for loop as a=n and you called the function with n=0 ... also your code does not match the expansion for e^x at all
Have a look at the for loop:
for (int a = n; a >= 0; ++a )
What is the first value of a? The second? The third?
Keep in mind that the values are determined by ++a.
When will that loop end? It is determined by a >= 0. When is that false?
What is this loop doing?
while (x * sum / a < 0.00001) {
break;
}
I suspect that you programmed "English to C", as "do the outer loop while ...", which is practically from the assignment.
But the loop does something else. Apart from risking the division by 0 mentioned above, if the condition is true it will stay true and cause an endless loop, which then however is immediatly canceled in the first iteration.
The head of your function float exponential(int n, float x) expects n as a parameter. In main you init it with 0. I suspect you are unclear about where that value n is supposed to come from. In fact it is unknown. It is more a result of the calculation than an input.
You are supposed to add up until something happens.
You do not actually ever need the value of n. This means that your for loop is meaningless. The inner loop (though currently pointless) is much closer to your goal.
I will leave it at this for now. Try to use this input.
Feel free to edit the code in your question with improvements.
(Normally that is not appreciated, but in case of homework dialog questions I am fine with it.)
Your current implementation attempt is quite a bit off. Therefore I will describe how you should approach calculating such a series as given in your quesiton.
Let's look at your first formula:
You need to sum up terms e(n) = x^n / n!
To check with your series: 1 == x^0 / 0! - x == x^1 / 1! - ...
To calculate these terms, you need a simple rule how to get from e(n) to e(n+1). Looking at the formula above we see that you can use this rule:
e(n+1) = e(n) * x / (n+1)
Then you need to create a loop around that and sum up all the bits & pieces.
You are clearly not supposed to calculate x^n/n! from scratch in each iteration.
Your condition to stop the loop is when you reach the limit of 1e-5. The limit is for the new e(n+1), not for the sum.
For the other formulas you can use the same approach to find a rule how to calculate the single terms.
You might need to multiply the value by -1 in each step or do something like *x*n/(n+1) instead of *x/(n+1) etc.
Maybe you need to add some check if the formula is supposed to converge. Then maybe print some error message. This part is not clear in your question.
As this is homework, I only point into the direction and leave the implementation work to you.
If you have problems with implementation, I suggest to create a new question.
#include <stdio.h>
int main() {
float power;
printf("Enter the power of e\n");
scanf("%f", &power);
float ans = 1;
float temp = 1;
int i = 1;
while ((temp * power) / i >= 0.00001) {
temp = (temp * power) / i;
ans = ans + temp;
i++;
}
printf("%.5f", ans);
return 0;
}
I think I solved the problem
But the part about Natural Log is not solved, I will try.
I am working on the project where we are approximating e^x using a taylor series, with x being a user entered value. The test values that we have been given are x=.5, x=1.0, and x=1.5. The goal is to get the output is supposed to be a table with a row for each iteration of the loop that creates the series, with the first column containing the number of iterations, the second column the theoretical value (based on exp(x)), the third the total of the summation, and the forth difference between the theoretical value and the iterated value.
My code as it is currently is below. As it stands, my logic has some hole in it, as the code builds and runs, but the output is not correct. If I were to take a stab at my problem, i think that my summation is not starting in the right spot (1), and that the first two terms are wrong (1+x+(x^2/2!)+(x^3/3!)... etc).
What logic should I be using vs what I have? Thanks.
//cs 1325
// Dean Davis
// Dr. Paulk
// series convergence homework.
#include <stdio.h>
#include <float.h> // need it for FLT_EPSILON
#include <math.h>
unsigned long factorial(int); // function will calculate the factorial
int main()
{
int n = 0;
unsigned long fact; // this variable will hold the factorial value
float x; // this will be the value read in from the user
double theoval; // this will hold the theoretical value of e^x
double holder; // will hold the value of the nth term
double total = 0; // will accumulate the total summation
double diff; // will hold the sifferential between theoretical value and the summation
puts("Please enter a numerical value greater than zero: "); // request input
scanf_s("%f", &x); // read it in
theoval=exp(x); // calc the theoretical value
printf("# Iter e^x Sum Diff\n");
printf("------- ------- ------- -------\n"); // set up the output
while ((theoval - total) >= FLT_EPSILON) //the loop to continue to sum the summation
{
fact = factorial(n); // calls the factorial function
holder = (pow(x, n)) / fact; // calculates the term n
total = total + holder; // adds to the sum
diff = theoval - total; // calc the diff
printf(" %-9d%-12.6f%-14.6f%-10.8f\n", n, theoval, total, diff); // output it
if ((theoval - total) >= FLT_EPSILON) // if it is smaller, then we don't wan't to increment n
continue;
else
n++;
}
printf("The number of iterations required for convergence is: %d\n", n); // out put this line
}
unsigned long factorial(int n)
{
unsigned long int fact=n;
if (n == 0) // if n is zero, 0!=1
return 1;
else // so long as it is not, then we can calculate it like this
{
n--; // decrement it
for (n; n > 0; n--)
{
fact = fact*n; // multiply the next number by the product of all the preceding terms
}
return fact;
}
}
Your main problem is here:
if ((theoval - total) >= FLT_EPSILON) // if it is smaller, then we don't wan't to increment n
continue;
else
n++;
The logic is both backwards and unnecessary. It's backwards because you avoid incrementing n in exactly those cases where you want to increment it, and it's unnecessary because in the other cases you're about to exit the loop anyway because the while expression is false. Just increment n unconditionally.
This expression is also a little suspect:
(theoval - total) >= FLT_EPSILON
The macro FLT_EPSILON is related to the spacing between representable float values near 1.0. The spacing is different in different places, so it does not make sense to use it as an absolute error bound. Since the Taylor series has a well defined error bound in the form of the remainder term, I suggest instead computing the maximum possible value of the remainder term for the current n, and exiting if the ratio of that bounding error value value to the current sum is less than some reasonably small value, such as maybe 0.00001.
Besides the issue with if ((theoval - total) >= FLT_EPSILON), there's an issue with the way you're doing factorial. Those values get big quick. 13! = 6227020800 which is outside the range of a 32-bit int, so any more than 13 iterations and you get invalid results.
You don't really want to compute factorial so much as you want to compute the next term. Each term is x / n times the prior term, so you can compute each term without having to explicitly compute x^n or n!.
int n = 1; // Start at 1 with the first term included so we don't divide by 0
double holder = 1; // will hold the value of the nth term
double total = 1; // will accumulate the total summation
while ((theoval - total) >= FLT_EPSILON) //the loop to continue to sum the summation
{
holder = holder * x / n; // compute the next term from the last one
total = total + term; // adds to the sum
printf(" %-9d%-12.6f%-14.6f%-10.8f\n", n, theoval, total, diff); // output it
n++;
}
A simple program I wrote in C takes upwards of half an hour to run. I am surprised that C would take so long to run, because from what I can find on the internet C ( aside from C++ or Java ) is one of the faster languages.
// this is a program to find the first triangular number that is divisible by 500 factors
int main()
{
int a; // for triangular num loop
int b = 1; // limit for triangular num (1+2+3+......+b)
int c; // factor counter
int d; // divisor
int e = 1; // ends loop
long long int t = 0; // triangular number in use
while( e != 0 )
{
c = 0;
// create triangular number t
t = t + b;
b++;
// printf("%lld\n", t); // in case you want to see where it's at
// counts factors
for( d = 1 ; d != t ; d++ )
{
if( t % d == 0 )
{
c++;
}
}
// test to see if condition is met
if( c > 500 )
{
break;
}
}
printf("%lld is the first triangular number with more than 500 factors\n", t);
getchar();
return 0;
}
Granted the program runs through a lot of data, but none of it is ever saved, just tested and passed over.
I am using the Tiny C Compiler on Windows 8.
Is there a reason this runs so slowly? What would be a faster way of achieving the same result?
Thank you!
You're iterating over a ton of numbers you don't need to. By definition, a positive factor is any whole number that can be multiplied by another to obtain the desired product.
Ex: 12 = 1*12, 2*6, and 3*4
The order of multiplication are NOT considered when deciding factors. In other words,
Ex: 12 = 2*6 = 6*2
The order doesn't matter. 2 and 6 are factors once.
The square root is the one singleton that will come out of a factoring of a product that stands alone. All others are in pairs, and I hope that is clear. Given that, you can significantly speed up your code by doing the following:
#include <stdio.h>
#include <stdlib.h>
#include <math.h>
// this is a program to find the first triangular number that is divisible by 500 factors
int main()
{
int c = 0; // factor counter
long long int b = 0; // limit for triangular num (1+2+3+......+b)
long long int d; // divisor
long long int t = 0; // triangular number in use
long long int r = 0; // root of current test number
while (c <= 500)
{
c = 0;
// next triangular number
t += ++b;
// get closest root.
r = floor(sqrt(t));
// counts factors
for( d = 1 ; d < r; ++d )
{
if( t % d == 0 )
c += 2; // add the factor *pair* (there are two)
}
if (t % r == 0) // add the square root if it is applicable.
++c;
}
printf("%lld is the first triangular number with more than 500 factors\n", t);
return 0;
}
Running this on IDEOne.com takes less than two seconds to come up with the following:
Output
76576500 is the first triangular number with more than 500 factors
I hope this helps. (and I think that is the correct answer). There are certainly more efficient ways of doing this (see here for some spoilers if you're interested), but going with your code idea and seeing how far we could take it was the goal of this answer.
Finally, this finds the first number with MORE than 500 factors (i.e. 501 or more) as per your output message. Your comment at the top of the file indicates you're looking for the first number with 500-or-more, which does not match up with your output message.
Without any math analysis:
...
do
{
c = 0;
t += b;
b++;
for (d = 1; d < t; ++d)
{
if (!(t % d))
{
c++;
}
}
} while (c <= 500);
...
You are implementing an O(n^2) algorithm. It would be surprising if the code took less than a half an hour.
Refer to your computer science textbook for a better method compared to this brute force method of: check 1, 1 + 2, 1 + 2 + 3, etc.
You might be able to shorten the inner for loop. Does it really need to check all the way up to t for factors that divide the triangular number. For example, can 10 be evenly divisible by any number greater than 5? or 100 by any number greater than 50?
Thus, given a number N, what is the largest number that can evenly divide N?
Keep reading/researching this problem.
Also, as other people have mentioned, the outer loop could be simply coded as:
while (1)
{
// etc.
}
So, no need need to declare e, or a? Note, this doesn't affect the length of time, but your coding style indicates you are still learning and thus a reviewer would question everything your code does!!
You are doing some unnecessary operations, and I think those instructions are not at all required if we can check that simply.
first :
while(e!=0)
as you declared e=1, if you put only 1 in loop it will work. You are not updating value of e anywhere.
Change that and check whether it works fine or not.
One of the beautiful things about triangle numbers, is that if you have a triangle number, with a simple addition operation, you can have the next one.
I don't know where I am doing wrong in trying to calculate prime factorizations using Pollard's rho algorithm.
#include<stdio.h>
#define f(x) x*x-1
int pollard( int );
int gcd( int, int);
int main( void ) {
int n;
scanf( "%d",&n );
pollard( n );
return 0;
}
int pollard( int n ) {
int i=1,x,y,k=2,d;
x = rand()%n;
y = x;
while(1) {
i++;
x = f( x ) % n;
d = gcd( y-x, n);
if(d!=1 && d!=n)
printf( "%d\n", d);
if(i == k) {
y = x;
k = 2 * k;
}
}
}
int gcd( int a, int b ) {
if( b == 0)
return a;
else
return gcd( b, a % b);
}
One immediate problem is, as Peter de Rivaz suspected the
#define f(x) x*x-1
Thus the line
x = f(x)%n;
becomes
x = x*x-1%n;
and the precedence of % is higher than that of -, hence the expression is implicitly parenthesised as
x = (x*x) - (1%n);
which is equivalent to x = x*x - 1; (I assume n > 1, anyway it's x = x*x - constant;) and if you start with a value x >= 2, you have overflow before you had a realistic chance of finding a factor:
2 -> 2*2-1 = 3 -> 3*3 - 1 = 8 -> 8*8 - 1 = 63 -> 3968 -> 15745023 -> overflow if int is 32 bits
That doesn't immediately make it impossible that gcd(y-x,n) is a factor, though. It just makes it likely that at a stage where theoretically, you would have found a factor, the overflow destroys the common factor that mathematically would exist - more likely than a common factor introduced by overflow.
Overflow of signed integers is undefined behaviour, so there are no guarantees how the programme behaves, but usually it behaves consistently so the iteration of f still produces a well-defined sequence for which the algorithm in principle works.
Another problem is that y-x will frequently be negative, and then the computed gcd can also be negative - often -1. In that case, you print -1.
And then, it is a not too rare occurrence that iterating f from a starting value doesn't detect a common factor because the cycles modulo both prime factors (for the example of n a product of two distinct primes) have equal length and are entered at the same time. You make no attempt at detecting such a case; whenever gcd(|y-x|, n) == n, any further work in that sequence is pointless, so you should break out of the loop when d == n.
Also, you never check whether n is a prime, in which case trying to find a factor is a futile undertaking from the start.
Furthermore, after fixing f(x) so that the % n applies to the complete result of f(x), you have the problem that x*x still overflows for relatively small x (with the standard signed 32-bit ints, for x >= 46341), so factoring larger n may fail due to overflow. At least, you should use unsigned long long for the computations, so that overflow is avoided for n < 2^32. However, factorising such small numbers is typically done more efficiently with trial division. Pollard's Rho method and other advanced factoring algorithms are meant for larger numbers, where trial division is no longer efficient or even feasible.
I'm just a novice at C++, and I am new to Stack Overflow, so some of what I have written is going to look sloppy, but this should get you going in the right direction. The program posted here should generally find and return one non-trivial factor of the number you enter at the prompt, or it will apologize if it cannot find such a factor.
I tested it with a few semiprime numbers, and it worked for me. For 371156167103, it finds 607619 without any detectable delay after I hit the enter key. I didn't check it with larger numbers than this. I used unsigned long long variables, but if possible, you should get and use a library that provides even larger integer types.
Editing to add, the single call to the method f for X and 2 such calls for Y is intentional and is in accordance with the way the algorithm works. I thought to nest the call for Y inside another such call to keep it on one line, but I decided to do it this way so it's easier to follow.
#include "stdafx.h"
#include <stdio.h>
#include <iostream>
typedef unsigned long long ULL;
ULL pollard(ULL numberToFactor);
ULL gcd(ULL differenceBetweenCongruentFunctions, ULL numberToFactor);
ULL f(ULL x, ULL numberToFactor);
int main(void)
{
ULL factor;
ULL n;
std::cout<<"Enter the number for which you want a prime factor: ";
std::cin>>n;
factor = pollard(n);
if (factor == 0) std::cout<<"No factor found. Your number may be prime, but it is not certain.\n\n";
else std::cout<<"One factor is: "<<factor<<"\n\n";
}
ULL pollard(ULL n)
{
ULL x = 2ULL;
ULL y = 2ULL;
ULL d = 1ULL;
while(d==1||d==n)
{
x = f(x,n);
y = f(y,n);
y = f(y,n);
if (y>x)
{
d = gcd(y-x, n);
}
else
{
d = gcd(x-y, n);
}
}
return d;
}
ULL gcd(ULL a, ULL b)
{
if (a==b||a==0)
return 0; // If x==y or if the absolute value of (x-y) == the number to be factored, then we have failed to find
// a factor. I think this is not proof of primality, so the process could be repeated with a new function.
// For example, by replacing x*x+1 with x*x+2, and so on. If many such functions fail, primality is likely.
ULL currentGCD = 1;
while (currentGCD!=0) // This while loop is based on Euclid's algorithm
{
currentGCD = b % a;
b=a;
a=currentGCD;
}
return b;
}
ULL f(ULL x, ULL n)
{
return (x * x + 1) % n;
}
Sorry for the long delay getting back to this. As I mentioned in my first answer, I am a novice at C++, which will be evident in my excessive use of global variables, excessive use of BigIntegers and BigUnsigned where other types might be better, lack of error checking, and other programming habits on display which a more skilled person might not exhibit. That being said, let me explain what I did, then will post the code.
I am doing this in a second answer because the first answer is useful as a very simple demo of how a Pollard's Rho algorithm is to implement once you understand what it does. And what it does is to first take 2 variables, call them x and y, assign them the starting values of 2. Then it runs x through a function, usually (x^2+1)%n, where n is the number you want to factor. And it runs y through the same function twice each cycle. Then the difference between x and y is calculated, and finally the greatest common divisor is found for this difference and n. If that number is 1, then you run x and y through the function again.
Continue this process until the GCD is not 1 or until x and y are equal again. If the GCD is found which is not 1, then that GCD is a non-trivial factor of n. If x and y become equal, then the (x^2+1)%n function has failed. In that case, you should try again with another function, maybe (x^2+2)%n, and so on.
Here is an example. Take 35, for which we know the prime factors are 5 and 7. I'll walk through Pollard Rho and show you how it finds a non-trivial factor.
Cycle #1: X starts at 2. Then using the function (x^2+1)%n, (2^2+1)%35, we get 5 for x. Y starts at 2 also, and after one run through the function, it also has a value of 5. But y always goes through the function twice, so the second run is (5^2+1)%35, or 26. The difference between x and y is 21. The GCD of 21 (the difference) and 35 (n) is 7. We have already found a prime factor of 35! Note that the GCD for any 2 numbers, even extremely large exponents, can be found very quickly by formula using Euclid's algorithm, and that's what the program I will post here does.
On the subject of the GCD function, I am using one library I downloaded for this program, a library that allows me to use BigIntegers and BigUnsigned. That library also has a GCD function built in, and I could have used it. But I decided to stay with the hand-written GCD function for instructional purposes. If you want to improve the program's execution time, it might be a good idea to use the library's GCD function because there are faster methods than Euclid, and the library may be written to use one of those faster methods.
Another side note. The .Net 4.5 library supports the use of BigIntegers and BigUnsigned also. I decided not to use that for this program because I wanted to write the whole thing in C++, not C++/CLI. You could get better performance from the .Net library, or you might not. I don't know, but I wanted to share that that is also an option.
I am jumping around a bit here, so let me start now by explaining in broad strokes what the program does, and lastly I will explain how to set it up on your computer if you use Visual Studio 11 (also called Visual Studio 2012).
The program allocates 3 arrays for storing the factors of any number you give it to process. These arrays are 1000 elements wide, which is excessive, maybe, but it ensures any number with 1000 prime factors or less will fit.
When you enter the number at the prompt, it assumes the number is composite and puts it in the first element of the compositeFactors array. Then it goes through some admittedly inefficient while loops, which use Miller-Rabin to check if the number is composite. Note this test can either say a number is composite with 100% confidence, or it can say the number is prime with extremely high (but not 100%) confidence. The confidence is adjustable by a variable confidenceFactor in the program. The program will make one check for every value between 2 and confidenceFactor, inclusive, so one less total check than the value of confidenceFactor itself.
The setting I have for confidenceFactor is 101, which does 100 checks. If it says a number is prime, the odds that it is really composite are 1 in 4^100, or the same as the odds of correctly calling the flip of a fair coin 200 consecutive times. In short, if it says the number is prime, it probably is, but the confidenceFactor number can be increased to get greater confidence at the cost of speed.
Here might be as good a place as any to mention that, while Pollard's Rho algorithm can be pretty effective factoring smaller numbers of type long long, the Miller-Rabin test to see if a number is composite would be more or less useless without the BigInteger and BigUnsigned types. A BigInteger library is pretty much a requirement to be able to reliably factor large numbers all the way to their prime factors like this.
When Miller Rabin says the factor is composite, it is factored, the factor stored in a temp array, and the original factor in the composites array divided by the same factor. When numbers are identified as likely prime, they are moved into the prime factors array and output to screen. This process continues until there are no composite factors left. The factors tend to be found in ascending order, but this is coincidental. The program makes no effort to list them in ascending order, but only lists them as they are found.
Note that I could not find any function (x^2+c)%n which will factor the number 4, no matter what value I gave c. Pollard Rho seems to have a very hard time with all perfect squares, but 4 is the only composite number I found which is totally impervious to it using functions in the format described. Therefore I added a check for an n of 4 inside the pollard method, returning 2 instantly if so.
So to set this program up, here is what you should do. Go to https://mattmccutchen.net/bigint/ and download bigint-2010.04.30.zip. Unzip this and put all of the .hh files and all of the C++ source files in your ~\Program Files\Microsoft Visual Studio 11.0\VC\include directory, excluding the Sample and C++ Testsuite source files. Then in Visual Studio, create an empty project. In the solution explorer, right click on the resource files folder and select Add...existing item. Add all of the C++ source files in the directory I just mentioned. Then also in solution expolorer, right click the Source Files folder and add a new item, select C++ file, name it, and paste the below source code into it, and it should work for you.
Not to flatter overly much, but there are folks here on Stack Overflow who know a great deal more about C++ than I do, and if they modify my code below to make it better, that's fantastic. But even if not, the code is functional as-is, and it should help illustrate the principles involved in programmatically finding prime factors of medium sized numbers. It will not threaten the general number field sieve, but it can factor numbers with 12 - 14 digit prime factors in a reasonably short time, even on an old Core2 Duo computer like the one I am using.
The code follows. Good luck.
#include <string>
#include <stdio.h>
#include <iostream>
#include "BigIntegerLibrary.hh"
typedef BigInteger BI;
typedef BigUnsigned BU;
using std::string;
using std::cin;
using std::cout;
BU pollard(BU numberToFactor);
BU gcda(BU differenceBetweenCongruentFunctions, BU numberToFactor);
BU f(BU x, BU numberToFactor, int increment);
void initializeArrays();
BU getNumberToFactor ();
void factorComposites();
bool testForComposite (BU num);
BU primeFactors[1000];
BU compositeFactors[1000];
BU tempFactors [1000];
int primeIndex;
int compositeIndex;
int tempIndex;
int numberOfCompositeFactors;
bool allJTestsShowComposite;
int main ()
{
while(1)
{
primeIndex=0;
compositeIndex=0;
tempIndex=0;
initializeArrays();
compositeFactors[0] = getNumberToFactor();
cout<<"\n\n";
if (compositeFactors[0] == 0) return 0;
numberOfCompositeFactors = 1;
factorComposites();
}
}
void initializeArrays()
{
for (int i = 0; i<1000;i++)
{
primeFactors[i] = 0;
compositeFactors[i]=0;
tempFactors[i]=0;
}
}
BU getNumberToFactor ()
{
std::string s;
std::cout<<"Enter the number for which you want a prime factor, or 0 to quit: ";
std::cin>>s;
return stringToBigUnsigned(s);
}
void factorComposites()
{
while (numberOfCompositeFactors!=0)
{
compositeIndex = 0;
tempIndex = 0;
// This while loop finds non-zero values in compositeFactors.
// If they are composite, it factors them and puts one factor in tempFactors,
// then divides the element in compositeFactors by the same amount.
// If the element is prime, it moves it into tempFactors (zeros the element in compositeFactors)
while (compositeIndex < 1000)
{
if(compositeFactors[compositeIndex] == 0)
{
compositeIndex++;
continue;
}
if(testForComposite(compositeFactors[compositeIndex]) == false)
{
tempFactors[tempIndex] = compositeFactors[compositeIndex];
compositeFactors[compositeIndex] = 0;
tempIndex++;
compositeIndex++;
}
else
{
tempFactors[tempIndex] = pollard (compositeFactors[compositeIndex]);
compositeFactors[compositeIndex] /= tempFactors[tempIndex];
tempIndex++;
compositeIndex++;
}
}
compositeIndex = 0;
// This while loop moves all remaining non-zero values from compositeFactors into tempFactors
// When it is done, compositeFactors should be all 0 value elements
while (compositeIndex < 1000)
{
if (compositeFactors[compositeIndex] != 0)
{
tempFactors[tempIndex] = compositeFactors[compositeIndex];
compositeFactors[compositeIndex] = 0;
tempIndex++;
compositeIndex++;
}
else compositeIndex++;
}
compositeIndex = 0;
tempIndex = 0;
// This while loop checks all non-zero elements in tempIndex.
// Those that are prime are shown on screen and moved to primeFactors
// Those that are composite are moved to compositeFactors
// When this is done, all elements in tempFactors should be 0
while (tempIndex<1000)
{
if(tempFactors[tempIndex] == 0)
{
tempIndex++;
continue;
}
if(testForComposite(tempFactors[tempIndex]) == false)
{
primeFactors[primeIndex] = tempFactors[tempIndex];
cout<<primeFactors[primeIndex]<<"\n";
tempFactors[tempIndex]=0;
primeIndex++;
tempIndex++;
}
else
{
compositeFactors[compositeIndex] = tempFactors[tempIndex];
tempFactors[tempIndex]=0;
compositeIndex++;
tempIndex++;
}
}
compositeIndex=0;
numberOfCompositeFactors=0;
// This while loop just checks to be sure there are still one or more composite factors.
// As long as there are, the outer while loop will repeat
while(compositeIndex<1000)
{
if(compositeFactors[compositeIndex]!=0) numberOfCompositeFactors++;
compositeIndex ++;
}
}
return;
}
// The following method uses the Miller-Rabin primality test to prove with 100% confidence a given number is composite,
// or to establish with a high level of confidence -- but not 100% -- that it is prime
bool testForComposite (BU num)
{
BU confidenceFactor = 101;
if (confidenceFactor >= num) confidenceFactor = num-1;
BU a,d,s, nMinusOne;
nMinusOne=num-1;
d=nMinusOne;
s=0;
while(modexp(d,1,2)==0)
{
d /= 2;
s++;
}
allJTestsShowComposite = true; // assume composite here until we can prove otherwise
for (BI i = 2 ; i<=confidenceFactor;i++)
{
if (modexp(i,d,num) == 1)
continue; // if this modulus is 1, then we cannot prove that num is composite with this value of i, so continue
if (modexp(i,d,num) == nMinusOne)
{
allJTestsShowComposite = false;
continue;
}
BU exponent(1);
for (BU j(0); j.toInt()<=s.toInt()-1;j++)
{
exponent *= 2;
if (modexp(i,exponent*d,num) == nMinusOne)
{
// if the modulus is not right for even a single j, then break and increment i.
allJTestsShowComposite = false;
continue;
}
}
if (allJTestsShowComposite == true) return true; // proven composite with 100% certainty, no need to continue testing
}
return false;
/* not proven composite in any test, so assume prime with a possibility of error =
(1/4)^(number of different values of i tested). This will be equal to the value of the
confidenceFactor variable, and the "witnesses" to the primality of the number being tested will be all integers from
2 through the value of confidenceFactor.
Note that this makes this primality test cryptographically less secure than it could be. It is theoretically possible,
if difficult, for a malicious party to pass a known composite number for which all of the lowest n integers fail to
detect that it is composite. A safer way is to generate random integers in the outer "for" loop and use those in place of
the variable i. Better still if those random numbers are checked to ensure no duplicates are generated.
*/
}
BU pollard(BU n)
{
if (n == 4) return 2;
BU x = 2;
BU y = 2;
BU d = 1;
int increment = 1;
while(d==1||d==n||d==0)
{
x = f(x,n, increment);
y = f(y,n, increment);
y = f(y,n, increment);
if (y>x)
{
d = gcda(y-x, n);
}
else
{
d = gcda(x-y, n);
}
if (d==0)
{
x = 2;
y = 2;
d = 1;
increment++; // This changes the pseudorandom function we use to increment x and y
}
}
return d;
}
BU gcda(BU a, BU b)
{
if (a==b||a==0)
return 0; // If x==y or if the absolute value of (x-y) == the number to be factored, then we have failed to find
// a factor. I think this is not proof of primality, so the process could be repeated with a new function.
// For example, by replacing x*x+1 with x*x+2, and so on. If many such functions fail, primality is likely.
BU currentGCD = 1;
while (currentGCD!=0) // This while loop is based on Euclid's algorithm
{
currentGCD = b % a;
b=a;
a=currentGCD;
}
return b;
}
BU f(BU x, BU n, int increment)
{
return (x * x + increment) % n;
}
As far as I can see, Pollard Rho normally uses f(x) as (x*x+1) (e.g. in these lecture notes ).
Your choice of x*x-1 appears not as good as it often seems to get stuck in a loop:
x=0
f(x)=-1
f(f(x))=0