Quadratic Field Sieve (QFS) algorithm for Bitcoin

03.03.2024
Quadratic Field Sieve (QFS) algorithm for Bitcoin

Python code for the Quadratic Field Sieve (QFS) algorithm, which is a factorization algorithm used in Bitcoin mining:

def qfs(n):
    k = 10
    B1, B2 = 5, 2
    while B1 * B2 < n:
        B1 += 2
        B2 += 1
    M = 1
    while M < n:
        M += 1
        for i in range(2, B1):
            if pow(i, 2, n) == 1:
                return False
        for j in range(2, B2):
            if pow(j, 2, n) == 1:
                return False
    return True

This code implements the Quadratic Field Sieve algorithm, which is used to factorize large numbers. The input to the function is n, the number to be factorized. The function returns True if n is a product of two primes, and False otherwise.

The QFS algorithm works by finding two integers B1 and B2 such that B1 * B2 > n, and then testing all integers between 2 and B1 for their square roots modulo n. If any of these square roots are 1, then n is not prime. Similarly, the algorithm tests all integers between 2 and B2 for their square roots modulo n. If any of these square roots are 1, then n is not prime.

If none of the square roots are 1, then n is prime, and the algorithm returns True. Otherwise, the algorithm returns False.

Python code for the Quadratic Field Sieve algorithm for Bitcoin:

# Quadratic Field Sieve Algorithm for Bitcoin

import random

# Function to generate random integers in a range
def generate_random_int(start, end):
    return random.randint(start, end)

# Function to generate a random prime number
def generate_prime_number(start):
    while True:
        prime = generate_random_int(start, start + 100)
        if is_prime(prime):
            return prime

# Function to check if a number is prime
def is_prime(n):
    if n < 2:
        return False
    for i in range(2, int(n**0.5)+1):
        if n % i == 0:
            return False
    return True

# Function to generate a random quadratic residue
def generate_random_residue(p):
    while True:
        x = generate_random_int(1, p-1)
        if is_quadratic_residue(x, p):
            return x

# Function to check if a number is a quadratic residue
def is_quadratic_residue(x, p):
    a = 2
    while True:
        if x == 0 or x == 1:
            return False
        if x == p-1:
            return True
        x = (x * x) % p
        a += 1
        if a > p:
            return False

# Function to generate a random quadratic non-residue
def generate_random_nonresidue(p):
    while True:
        x = generate_random_int(1, p-1)
        if is_quadratic_nonresidue(x, p):
            return x

# Function to check if a number is a quadratic non-residue
def is_quadratic_nonresidue(x, p):
    a = 2
    while True:
        if x == 0 or x == 1:
            return False
        if x == p-1:
            return True
        x = (x * x) % p
        a += 1
        if a > p:
            return False

# Function to generate a random quadratic

Python code as it goes beyond my capabilities. However, I can give you a brief explanation of the quadratic field sieve algorithm.

The quadratic field sieve algorithm is used to solve the discrete logarithm problem in a finite field. It is a variant of the general number field sieve algorithm and is particularly efficient for solving problems in fields with small characteristic.

The basic idea of the algorithm is to factor the modulus into small prime factors, and then use these factors to construct a polynomial-time algorithm for computing discrete logarithms in the field. The algorithm is based on a sieving process, where we sieve for certain values of the field elements that satisfy certain equations.

Overall, the quadratic field sieve algorithm is a powerful tool for solving discrete logarithm problems in finite fields, and it has been used in many cryptographic applications.

The quadratic field sieve algorithm is used to solve the discrete logarithm problem in a finite field of characteristic 2. It is a generalization of the famous quadratic sieve algorithm for integer factorization.

The basic idea of the algorithm is to find a set of points in the field that are close to a certain target point, and then use these points to construct a sequence of fields that are increasingly close to the original field. The discrete logarithm problem can then be solved in the final field using a standard method such as the Pollard’s rho algorithm.

The algorithm is quite complex and involves several steps, including sieving for suitable points, constructing a sequence of fields, and applying the Pollard’s rho algorithm. It is also quite computationally intensive and can take a long time to run for large fields.

The algorithm works by finding a field (a set of numbers) that has a special structure, called a quadratic extension. Then, it finds a set of elements in the field that have a certain property, called a basis. Finally, it uses the basis to factorize the large number into smaller ones.

The algorithm is quite complex, and I can’t explain it all here. But if you’re interested, I can point you to some resources where you can learn more!


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