Application of the basic module's foundation for factorization of big numbers by the Fеrmаt method
DOI:
https://doi.org/10.15587/1729-4061.2018.150870Keywords:
factorization, Fermat method, computational complexity, basic foundation, thinning, quadratic residuesAbstract
The Fermat method is considered to be the best for factorization of numbers N=p×q in case of close p and q. Computational complexity of the basic algorithm of the method is determined by the number of check values of X when solving equation Y2=X2‑N, as well as by complexity of the arithmetic operations. To reduce it, it is proposed to consider admissible those of test values X, for which (X2–N)modbb is quadratic residue modulo bb, called basic. Application of basic foundation of module bb makes it possible to decrease the number of check X by the number of times, close to Z=bb/bb*, where bb* is the number of elements of set Т of the roots of equation (Ymodb)2modb=((Xmodb)2–Nmodb)modb, and Z is the acceleration coefficient.
It was determined that magnitude Z(N, bb) is affected by the value of residues Nmodp (at p=2, Nmod8 residues are used). The statement of the problem of finding bb with a maximum Z(N, bb) at restrictions for the amount of memory of the computer, where exponents of prime numbers – multipliers bb – are determined, and the method of its solution were proposed.
To decrease the number of arithmetic operations with big numbers, it was proposed that instead of them to perform the operations with the values of differences between the nearest values of elements T. Then arithmetic operations of multiplication and addition with big numbers are performed only in rare cases. And if we derive the square root of X2–N only in cases, where the values of (X2–N)modb will be quadratic residues for many foundations of module b, other than bb, the computational complexity of this operation can be neglected.
It was established that the proposed modified algorithm of the Fermat method for numbers 21024 ensures a decrease in computational complexity compared to the basic algorithm on average by 107 timesReferences
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