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author | Niels M?ller <nisse@lysator.liu.se> | 2019-07-30 07:23:50 +0200 |
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committer | Niels M?ller <nisse@lysator.liu.se> | 2019-07-30 07:23:50 +0200 |
commit | bd83498627dd46bdf94be877324f3e0a4504d41f (patch) | |
tree | a293f40e22dc860f24000671ed1fd4c2ecab5d97 /doc/gmp.texi | |
parent | 67ca9c768abaad67d33a8178d9494b42d24433c7 (diff) | |
download | gmp-bd83498627dd46bdf94be877324f3e0a4504d41f.tar.gz |
Jacobi algorithm documentation, from Seth Troisi
* doc/gmp.texi (Jacobi Symbol): Update algorithm documentation.
* tests/mpz/t-jac.c: Comment update.
Diffstat (limited to 'doc/gmp.texi')
-rw-r--r-- | doc/gmp.texi | 72 |
1 files changed, 58 insertions, 14 deletions
diff --git a/doc/gmp.texi b/doc/gmp.texi index 1ca76bdd8..40d642b76 100644 --- a/doc/gmp.texi +++ b/doc/gmp.texi @@ -8934,23 +8934,64 @@ current size of the cofactors. @subsection Jacobi Symbol @cindex Jacobi symbol algorithm -[This section is obsolete. The current Jacobi code actually uses a very -efficient algorithm.] +@c Editor Note: I don't see other people defining the inputs, it would be nice +@c here because the code uses (a/b) where other references use (n/k) -@code{mpz_jacobi} and @code{mpz_kronecker} are currently implemented with a -simple binary algorithm similar to that described for the GCDs (@pxref{Binary -GCD}). They're not very fast when both inputs are large. Lehmer's multi-step -improvement or a binary based multi-step algorithm is likely to be better. +Jacobi symbol @m{\left(a \over b\right), (@var{a}/@var{b})} -When one operand fits a single limb, and that includes @code{mpz_kronecker_ui} -and friends, an initial reduction is done with either @code{mpn_mod_1} or -@code{mpn_modexact_1_odd}, followed by the binary algorithm on a single limb. -The binary algorithm is well suited to a single limb, and the whole -calculation in this case is quite efficient. +Initially if either operand fits in a single limb, a reduction is done with +either @code{mpn_mod_1} or @code{mpn_modexact_1_odd}, followed by the binary +algorithm on a single limb. The binary algorithm is well suited to a single limb, +and the whole calculation in this case is quite efficient. -In all the routines sign changes for the result are accumulated using some bit -twiddling, avoiding table lookups or conditional jumps. +For inputs larger than @code{GCD_DC_THRESHOLD}, @code{mpz_jacobi}, +@code{mpz_legendre} and @code{mpz_kronecker} are computed via the HGCD (Half +GCD) function, as a generalization to Lehmer's algorithm. +Most GCD algorithms reduce @math{a} and @math{b} by repeatatily computing the +quotient @m{q = \lfloor a/b \rfloor, q = floor(a/b)} and iteratively replacing + +@c Couldn't figure out macros with commas. +@tex +$$ a, b = b, a - q * b$$ +@end tex +@ifnottex +@math{a, b = b, a - q * b} +@end ifnottex + +Different algorithms use different methods for calculating q, but the core +algorithm is the same if we use @ref{Lehmer's Algorithm} or +@ref{Subquadratic GCD, HGCD}. + +At each step it is possible to compute if the reduction inverts the Jacobi +symbol based on the two least significant bits of @var{a} and @var{b}. For +more details see ``Efficient computation of the Jacobi symbol'' by +M@"oller (@pxref{References}). + +A small set of bits is thus used to track state +@itemize +@item +current sign of result (1 bit) + +@item +two least significant bits of @var{a} and @var{b} (4 bits) + +@item +a pointer to which input is currently the denominator (1 bit) +@end itemize + +In all the routines sign changes for the result are accumulated using fast bit +twiddling which avoids conditional jumps. + +The final result is calculated after verifying the inputs are coprime (GCD = 1) +by raising @m{(-1)^e,(-1)^e} + +Much of the HGCD code is shared directly with the HGCD implementations, such +as the 2x2 matrix calculation, @xref{Lehmer's Algorithm} basecase and +@code{GCD_DC_THRESHOLD}. + +The asymptotic running time is @m{O(M(N)\log N),O(M(N)*log(N))}, where +@math{M(N)} is the time for multiplying two @math{N}-limb numbers. @need 1000 @node Powering Algorithms, Root Extraction Algorithms, Greatest Common Divisor Algorithms, Algorithms @@ -10910,8 +10951,11 @@ Dan Zuras, ``On Squaring and Multiplying Large Integers'', ARITH-11: IEEE Symposium on Computer Arithmetic, 1993, pp.@: 260 to 271. Reprinted as ``More on Multiplying and Squaring Large Integers'', IEEE Transactions on Computers, volume 43, number 8, August 1994, pp.@: 899-908. -@end itemize +@item +Niels M@"oller, ``Efficient computation of the Jacobi symbol'', @texlinebreak{} +@uref{https://arxiv.org/abs/1907.07795} +@end itemize @node GNU Free Documentation License, Concept Index, References, Top @appendix GNU Free Documentation License |