ACM Home Page
Please provide us with feedback. Feedback
Greatest common divisors of polynomials given by straight-line programs
Full text PdfPdf (2.60 MB)
Source Journal of the ACM (JACM) archive
Volume 35 ,  Issue 1  (January 1988) table of contents
Pages: 231 - 264  
Year of Publication: 1988
ISSN:0004-5411
Author
Erich Kaltofen  Rensselaer Polytechnic Institute, Troy, NY
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 38,   Citation Count: 21
Additional Information:

abstract   references   cited by   index terms   review   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/42267.45069
What is a DOI?

ABSTRACT

Algorithms on multivariate polynomials represented by straight-line programs are developed. First, it is shown that most algebraic algorithms can be probabilistically applied to data that are given by a straight-line computation. Testing such rational numeric data for zero, for instance, is facilitated by random evaluations modulo random prime numbers. Then, auxiliary algorithms that determine the coefficients of a multivariate polynomial in a single variable are constructed. The first main result is an algorithm that produces the greatest common divisor of the input polynomials, all in straight-line representation. The second result shows how to find a straight-line program for the reduced numerator and denominator from one for the corresponding rational function. Both the algorithm for that construction and the greatest common divisor algorithm are in random polynomial time for the usual coefficient fields and output a straight-line program, which with controllably high probability correctly determines the requested answer. The running times are polynomial functions in the binary input size, the input degrees as unary numbers, and the logarithm of the inverse of the failure probability. The algorithm for straight-line programs for the numerators and denominators of rational functions implies that every degree-bounded rational function can be computed fast in parallel, that is, in polynomial size and polylogarithmic depth.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
Ano, A. V., STEIGLrrz, K., AND ULLMAN, J.D. Evaluating polynomials at fixed sets of points. SIAM J. Comput. 4 (1975), 533-539.
 
3
BAUR, W., AND STRASSEN, V. The complexity of partial derivatives. Theoret. Comput. Sci. 22 (1983), 317-330.
 
4
BRENT, R. P., GUSTAVSON, F. G., AND YUN, D. Y. Y. Fast solution of Toeplitz systems of quations and computation of Pad6 approximants. J. Algorithms 1 (1980), 259-295.
5
 
6
BtmCH, J. R., AND HoPcRoFr, J. E. Triangular factorization and inversion by fast matrix multiplication. Math. Comput. 28 (1974), 231-236.
 
7
8
 
9
10
 
11
 
12
 
13
 
14
HARDY, G. H., AND WRIGHT, E.M. An Introduction to the Theory of Numbers. Oxford University Press, Oxford, England, 1979.
 
15
 
16
HWINTZ, J., AND SCHNORR, C.P. Testing polynomials which are easy to compute, in Monographie de L'Enseignement Math~matique, vol. 30. Imprimerie Kundig, Gen~ve, Switzerland, 1982, pp. 237-254.
 
17
HYAFIL, L. On the parallel evaluation of multivariate polynomials. SIAM J. Comput. 8 (1979), 120-123.
18
 
19
IBARRA, O. H., MORAN, S., AND ROSIER, L.E. Probabilistic algorithms and straight-line programs for some rank decision problems. Inf. Process. Lett. 12 (1981), 227-232.
 
20
21
 
22
KAL~OFEN, E. Computing with polynomials given by straight-line programs. II. Sparse factorization. In Proceedings of the 26th IEEE Symposium on Foundations of Computer Science. IEEE, New York, 1985, pp. 451-458.
 
23
IC~LTOFEN, E. Factorization of polynomials given by straight-line programs. In Randomness in Computation: Advances in Computing Research, S. Micali, Ed. JAI Press, Greenwich, Conn., Jan. 1987.
24
25
 
26
 
27
KNUTH, D.E. The analysis of algorithms. Actes du congrbs international des Math~maticiens 3 (1970), 269-274.
 
28
 
29
KRISHNAMURTHY, E. V., RAO, T. M., AND SUBRAMANIAN, K. Finite segment p-adic number systems with applications to exact computation. Proc. Indian Acad. Sci. 81, sec. A, 2 (1975), 58-79.
 
30
KUNG, H.T. On computing reciprocals of power series. Numer. Math. 22 (1974), 341-348.
 
31
 
32
MILLER, G. F., AND REIF, J.H. Parallel tree contraction and its application, in Proceedings of the 26th IEEE Symposium on Foundations of Computer Science. IEEE, New York, 1985, pp. 478-489.
33
34
 
35
PLAISTED, D.A. Sparse complex polynomials and polynomial reducibility. J. Comput. Syst. Sci. 14 (1977), pp. 210-221.
 
36
RossEa, J. B., AND SCHOENFELD, L. Approximate formulas of some functions of prime numbers. 111. J. Math. 6 (1962), 64-94.
37
 
38
SCrIONHAGE, A. Schnelle Kettenbruchentwicklungen. Acta inf. 1 (1971), 139-144 (in German).
 
39
SCHOm-L~,GE, A. Schnelle Multiplikation von Polynomen fiber Ktrpern der Charakteristik 2. Acta Inf. 7 (1977), 395-398 (in German).
 
40
SOLOVAY, R. M., AND STRASSErq, V. A fast Monte-Carlo test for primality. SIAM J. Comput. 6{ (1977), 84-85. Correction: 7 (1978), 118.
 
41
STOUTEMEYER, D. R. Which polynomial representation is best? In Proceedings of the 3rd MACSYMA Users'Conference, General Electric, Schenectady, N.Y., 1984, pp. 221-243.
 
42
STRASSEN, V. Berechnung und Programm I. Acta Inf. 1 (1972), 320-335 (in German).{
 
43
STrtASSEN, V. Vermeidung von Divisionen. J. Reine u. Angew. Math. 264 (1973), 182-202 (in German).
 
44
VALIANT, L. The complexity of computing the permanent. Theoret. Comput. Sci. 8 (1979), 189-201.
 
45
VALIANT, L. Reducibility by algebraic projections. L'Enseignement Math. 28 (1982), 253-268.
 
46
VALIANT, L., SKYUM, S., BERKOWITZ, S., AND RACKOFF, C. Fast parallel computation of polynomials using few processors. SIAM J. Comput. 12 ( 1983), 641-644.
 
47

CITED BY  21


REVIEW

"Don Goelman : Reviewer"

This research paper presents two principal results, both of which are algorithms for manipulating polynomials represented by straight-line programs. The first computes the greatest common divisor of a family of multivariate polynomials, and the   more...